Puthea Panha

Vannak Vai

Planification Du

DISTRIBUTION BASSE TENSION AVEC INTÉGRATION DE SOURCES PHOTOVOLTAÏQUES Réseau De

PLANNING OF LOW VOLTAGE DISTRIBUTION SYSTEM WITH INTEGRATION OF PV SOURCES AND STORAGE MEANS-CASE OF THE POWER SYSTEM OF CAMBODIA

Keywords: Méthode de Monte Carlo, optimisation, planification, photovoltaïque, réseau de distribution basse tension, stockage, théorie de graphe Monte Carlo method, optimization, planning, photovoltaic, low voltage distribution system, storage, graph theory Monte Carlo method, optimization, planning, photovoltaic, low voltage distribution system, storage, graph theory

Lastly and most importantly, I would like to express my deepest gratitude for my parents (Vai CHUCH

This PhD thesis has been completed in the Laboratoire de Génie Electrique de Grenoble (G2Elab) of the Institut Polytechnique de Grenoble (Grenoble INP) and Institut de Technologie du Cambodge (ITC). I would like to express my sincere appreciation to my directeur de thèse, Bertrand RAISON, my co-encadrants: Marie-Cécile ALVAREZ-HERAULT and Long BUN, for their inspiration, guidance, encouragement, and friendship, without whom this work would not have been possible. BR, you have been being always with me, you were always patient even I had little progress. MC, you constantly guided me even we were so far away (Cambodia-France-California), you have been so kind to provide me with valuable suggestions. BL, you have been always encouraging me with positive thinking. Believe me, 36 months working with them has been a rewarding and enjoyable experience.

I also would like to express my heartfelt gratitude to the rapporteurs, Cristian NICHITA and Marc PETIT, and the member of the committee, Bruno FRANCOIS, for their valuable comments and review of this thesis. Cristian and Marc, you both permitted me to send a manuscript one month after the deadline, that was very kind of you. I would like to say special thanks to Bong Seihakkiry RANN (Electricité du Cambodge-EDC) for discussing and providing me the documents related to current issues of power system in Cambodia. He guided me to select the site study of rural area in Cambodia for my PhD thesis.

Without the financial support of the Bourses du Gouvernement Français (BGF) and G2Elab which offered me a scholarship, this work would not have been possible. I would like to say special thanks to Michael GRAS (BGF) and James ROUDET (Directeur du G2Elab) for granting me the rare opportunity in wonderful city, Grenoble. Special appreciation is extended to Nadine MICHEL and Florence FRANCOIS, administrative staffs of G2Elab, for their help, kindness, and encouragement. We and Bertrand were at Angkor Wat temple together from 19 th to 23 rd November, 2016, I will never forget these days of mine.

I wish also to thank Bong Sophal, president of Cambodia association in Grenoble. Bong Sophal, you are warm welcome to me not only in Grenoble, but also first time in France, Paris-Charles de Gaulle (CDG) Airport. We were together on the way from Paris to Grenoble by car on 30 th August, 2012.

I would like to say many thanks to both Bong Khanna and Khanmony, and their families in Paris. It was my first night I got a good sleep in your home in France, 29 th August, 2012. I am thankful to Om Seth and Om Eam for being so kind to me in Grenoble. Your home always opened and welcome to me, it was my second home in Grenoble. Khmer foods in France were at your home for me. Also, I am very much thankful to Association Française de Solidarité (AFS)-Cambodge for being so supportive to provide me financial support for high school and bachelor of engineering in Battambang and Phnom Penh. AFS has been with me since 2006. I am extremely grateful to Marie et loïc, AFS members in Grenoble for their kindness. It was first time for me on mountain in your home; Noël day. I am grateful to Anne-thérèse and her brother Damien for being my second Maman in AFS. She is always so gentle to me. On 6 th December, we were enjoyable together for la

List of Figures

List of Tables

General Introduction

Day by day, the energy consumptions have continuously increased throughout the world due to a growing number of inhabitants with more comfortable lifestyles. Presently, energy needs have raised concerns regarding fossil fuel depletion, energy efficiency and global warming issues, thus leading our societies to search for alternative energy sources.

Renewable energy sources have been put forward to reduce our dependency on fossil fuel by converting the energy from natural resources into thermal and electric energy. Today, the renewable energy sources are more and more used to provide energy. These sources are usually small size production units lower than 12 MW and located close to the end users.

For that reason they are called distributed generations and are connected to the distribution system. As they can have either a positive or negative impacts on the distribution network, lots of research and development works are studied around the world to make to distribution network evolve toward a more reliable, economic and environmentally friendly grid.

In developing country such as Cambodia, the context is quite different. Even if the the low-voltage distribution systems are being reinforced and expanded in the recent years, about 75% of the population living in rural areas has currently no access to the electricity.

In order to meet the need of the population and society regarding electricity, the Cambodian government has established a policy to promote and encourage the development of electrification [START_REF] Refedc | Program for the development of rural electrification of Electricité Du Cambodge (EDC) through department of Rural Electrification Fund (REF)[END_REF] 1 ; all the villages will have electricity by the year 2020, and at least 70% of the households will have access to grid-quality electricity by the year 2030. These objectives compel the Cambodian government and electricity distributors to perform planning and develop master plans for the development of the distribution network.

In addition, in Cambodia, the electricity is recently supplied by four main different sources, i.e. diesel, hydropower, coal and imports from neighboring countries. In the master plan of the electricity sector development of the country, the government sets hydropower and coal as the two main sources of electricity production. Nevertheless, more and more people having no access to the electricity invest in small photovoltaic production units connected to the LV distribution network and called Solar Home System (SHS). These small production units can have an impact on planning decisions in the low voltage network development because they can change the direction of power flows and even create situation of reverse power flows, i.e. electricity going from the LV grid to the MV grid through the MV/LV substation. It is mandatory to integrate them in planning studies and to find economic solution to best take advantage of their potential benefits.

In that purpose, this thesis investigates novel methodologies and concepts to expand and design the low voltage distribution systems in a long term planning purposes in order to increase the electrification of developing countries such as Cambodia and to maximize the use of SHS. The research tasks performed in this PhD thesis are organized as it follows:

Chapter I will give a state of the art of the power systems in Cambodia focusing on the LV distribution network both in urban and rural areas. The planning principles used for developing the distribution network will also be presented.

In chapter II, optimization tools for the planning of distribution networks using current rules will be developed for both rural and urban areas. The objectives are the minimization of the capital expenditure (CAPEX) and the operation expenditure (OPEX) and the improvement of the load balancing while respecting a set of topological and electrical (current and voltage) constraints. Two novel algorithms will be developed to search for the optimal architecture: a Mixed Integer Quadratically Constrained Programming (MIQCP) and a Shortest Path and First Fit Bin Packing (SP-FFBP) algorithms. The presence of productions will not be considered at this stage. The impacts of uncertainties on the power and location of LV customers will be integrated using Monte Carlo simulations to evaluate the flexibility of the proposed tools.

In chapter III, SHS will be integrated in the planning tools. The maximum amount of PV without causing technical constraints is computed and located in the LV network. Then, the association of storage devices will be studied in order to solve the constrained induced by the PV connections and loads. Different kind of algorithms will enable to locate, size and control theses BES. Finally, a technical and economic analysis will be performed on a simple case study to compare the traditional planning method with the new one.

In chapter IV, the new planning methods developed in chapter III will be applied on two case studies (urban and rural) and compared with the traditional planning method.

Uncertainties on the hourly load profiles will be integrating to evaluate the robustness of the new planning approach. These two case studies will lead to some conclusions and propositions for the development of LV microgrids in developing countries. of over 15 million in 2014 [START_REF] King | Preliminary Results of Cambodia Inter-censal Economic Survey[END_REF]. Currently, the electricity in Cambodia is supplied by four main different sources, i.e. diesel, hydropower, coal and imports from neighboring countries [START_REF] Eac | Report on power sector of the kingdom of Cambodia in Khmer Language[END_REF]. Furthermore, the renewable energy sources such as photovoltaic and biomass already exist, but they are small and still isolated from the national grid. Also, Cambodia is an agricultural country, where over 80 % of the people live in rural areas with agriculture as the main source of subsistence [START_REF] Fao | Cambodia and FAO Achievements and success stories[END_REF]. Among the Southeast Asian region, Cambodia has one of the most expensive electricity tariff {i.e. ~0.18 USD/kWh (Urban-LV) and ~0.3 USD/kWh (Rural-LV)} according to a report from [START_REF] Kongchheng | Energy Market Integration in East Asia: Theories, Electricity Sector and Subsidies[END_REF]and [START_REF] Eac | Report on power sector of the kingdom of Cambodia in Khmer Language[END_REF].

Presently, 74.80 % of the villages, and 65 % of households access to grid quality electricity [START_REF] Mme | Current Status of Renewable Energy in Cambodia[END_REF]. Also, only about 25 % of Cambodian households have access to the electricity in rural area even if this country has a high potential for renewable [PHOK16]. They survive by using diesel engine, battery, kerosene for lighting, TV, multimedia and some other household appliances.

Likewise, to reduce poverty, improve the standard of living and foster economic . However, as renewable energy sources such as solar are abundant only in some particular areas, the government seems to neglect it in his development plan for the electricity sector [START_REF] Mme | Current Status of Renewable Energy in Cambodia[END_REF]. It is thus very interested to highlight the benefits of small scale distributed generations (i.e. photovoltaic and battery energy storage) integration into the low-voltage distribution system in order to encourage the Cambodian government and electricity distributors with these sources. Moreover, in order to apply the concept of planning on low-voltage distribution system, it is necessary to understand the background of the power system such as its current situation and its evolution, and also the architecture of the low-voltage distribution system in Cambodia. The first part of this chapter will describe the current situation of the power system in Cambodia. In the second part, we will provide the structure of the low-voltage distribution system in two different areas (i.e. rural and urban). Finally, we will detail the principles of planning the power distribution system in the last part of this chapter.

I.2 Institutional framework of the Cambodian power sector

The electricity law of the Kingdom of Cambodia defines the responsibility of the

Vannak VAI, Grenoble INP / G2Elab

Page 9

Energy imported from neighboring countries

With the rapid increase in demand following the trend of economic growth, Cambodia does not have sufficient supply for its demand, thus the Royal Government of Cambodia (RGC) needs power from its neighboring countries such as Laos, Thailand, and Vietnam under the power sector cooperation agreement between the Greater Mekong Subregion

Electricity consumption

According to the EAC, consumers' demand for electricity increases every year; hence, the demand for installed electricity-producing capacity must also be increased. In the

I.4 Power distribution system

The distribution system is the final link between the bulk power system and the end users. It provides electricity to the end users from the high voltage (HV) / medium voltage (MV) substations [BENO15]. It consists of the MV and the low voltage (LV) systems. In Cambodia, the MV distribution system consists of three phases (urban areas) and single phases (some rural areas). The line voltage is usually 22 kV in MV system and it is designed as a looped system, but is operated radially. The LV distribution system is perfectly radial and consists of single phase and three phases including a distributed neutral wire. Hz and the variation of the frequency shall be between 49.5 Hz and 50.5 Hz.

National grid

The MV lines connected to the national grid provide electric power supply in areas around the grid substations.

Isolated supply systems

Isolated systems consist of local MV grids having their own generation and supplying a small area, generally belonging to one licensee. The information on number of consumers, energy available and supplied to consumers for these isolated systems has been listed in

Architecture of the low-voltage distribution system

The MV/LV substations are the interface between the MV and LV systems. The MV/LV substations are different whether the area is rural or urban. The main topological constraints depend on geographic and demand of loads. So, both rural and urban topologies are described in the following subsections.

Rural areas

The rural areas are characterized by a low load density (big zone with low consumption). Thus, the conductor length is long, usually with overhead lines with a singlephase and three-phase distribution called main lines along the road. Therefore, the main technical problems in rural areas are the voltage drop at the end of the line.

Urban areas

The urban area is different from rural because its load density is high with short conductor length. Consequently, the main problem to take into account is permissible current in conductor. Currently, almost all the main lines are distributed with three-phase main lines. Since there is no surface irradiation data available to our study, satellite data have been collected to grasp the potential of solar energy over the whole country. The data were downloaded from the National Aeronautics and Space Administration (NASA) home page [NASA17] via HOMER software [START_REF] Homer | HOMER -Hybrid Renewable and Distributed Generation System Design Software[END_REF] and [START_REF]NREL Dynamic Maps, GIS Data, and Analysis Tools -Solar Maps[END_REF]. Figure I-14 represents the monthly average and maximal solar radiation over the country. The monthly average radiation varies between 0.34 kW/m 2 and 0.44 kW/m 2 . with an annual average of 0.40 kW/m 2 . The maximum radiation is higher than 1.3 kW/m 2 .

I.6 Objective of planning

The objectives of planning are to develop the power system in a long term planning perspective (usually 30 years) in order to improve its reliability and quality of service while respecting the technical constraints, being more environmentally-friendly and minimizing the global costs.

Reliability and quality of service

Three indicators usually define the reliability and quality of service in planning studies and are the following ones:

-The SAIDI (System Average Interruption Duration Index) is the average duration of power outage per year per customer.

-The SAIFI (System Average Interruption Frequency Index) is the average power outage frequency per year per customer.

-The ENS (Energy Not Supplied) is the yearly amount of energy non-supplied expressed in kWh per year.

The smaller these indicators are, the higher the reliability and the quality of service of the power system will be. More details about theses indices are provided in [START_REF] Alvarez-Hérault | Architectures des réseaux de Distribution du futur en présence de Production décentralisée[END_REF].

Electrical criteria

This criterion is taken into account through the respect of currents and voltages and the minimization of losses in the power system. These items will be described in the following section.

Permissible current

The permissible current of a device (conductor or transformer) is the maximum current in the steady state condition that can flow through it without exceeding the thermal limitation. This value depends on the gauge of the conductor and the maximum temperature of its insulation [START_REF] Ray | Electrical Power Systems: Concepts, Theory and Practice[END_REF]. Beyond these temperatures, insulation and/or conductor are deteriorated and this can cause fires. The bigger surface of cable section is the smaller the resistance will be. Thus, it is necessary to determine the properly size of the conductors for supplying the load so that the currents flows respect the permissible intensity over the planning horizon. A complete table of conductors used in Cambodia can be found in [START_REF] Lvabc | LV-ABC 0.6-1kV[END_REF]. Table I-5 summarizes the main ones which will be used in this thesis.

Voltage profile

The voltage difference between two points in an electrical circuit is defined as the voltage drop ij V ∆ . According to Ohm's law, the voltage drop is expressed by following equation.

ij ij ij V Z I ∆ = × (I-1)
Where, ij Z : complex impedance of the conductor between point i and j ij I : complex current flowing from point i to j

According to Eq. I-1, the voltage drop is linked to the current flowing through the conductor and its impedance. Moreover, this impedance increases with the length of the conductor and consequently the voltage drop too. Likewise, in case of power system with classical loads, without decentralized production, the voltage at consumers is lower than the voltage at substation. In addition, the voltage profile must also respect the constraint of operation in the power system; presently, the limit of voltage which is implemented for the low-voltage distribution in Cambodia is -10%/+6 % [KING04]. Therefore, it is mandatory to consider conductor length and impedance when applying the distribution planning.

Losses

The power losses are due to heating that occurs when an electrical current flows through a conductor [START_REF] Gladkikh | Optimisation de l 'architecture des réseaux de distribution de l'énergie électrique[END_REF]. For a conductor with a given resistance r in ( / km Ω

), a length L (km), a flowing current I (A) during a period t ∆ (h), the power losses at a given time t and the energy losses during a period of t ∆ are expressed by the following equations. As seen in Eq. I-2 and Eq. I-3, power losses and energy losses are also linked to length and current.

Economic criteria

Other criteria in planning of power distribution system are economic ones; the capital expenditure (CAPEX) and the operational expenditure (OPEX) of the system design must be considered. In order to take into account the fluctuation of currency, the economic calculation uses the actualization principle. The actualization rate is a fixed value i which expresses the fact that N dollars today are worth (1 ) t N i × + in the year t and so encourage to defer investment if possible. If ( ) D t dollars are spent at the year t , the equivalent cost today is

( ) (1 ) t D t i + .
The actualized cost is integrated into the planning studies to choose between different strategies. The total actualized cost is defined by the following formula with total act C -being the current cost at year 0:

0 ( ) ( ) (1 ) N invest total act t t C t Op t C i - = + = + ∑ (I-4)
Where:

-

I.7 Scope of the thesis

This thesis will develop a long-term planning tool of LV distribution system for both electrified and non-electrified areas considering the technical and economic criteria previously defined and the actualized cost method over a planning period of 15 years.

Compared to traditional planning studies, this PhD work will study the impact of uncertainties of load demand (i.e. growth rate, new load, and load profile) on the gridreinforcement decisions. New solutions will be investigated such as the integration of PV generation and battery energy storage (BES) with their control in order to reduce the global cost and increase the electrification of the country. A first concept of LV microgrid architecture including PV and battery energy storage (BES) is then proposed.

In this work, some assumptions are made such as:

o The PV is characterized as a non-predicable renewable energy source in a long term perspective. Consequently, in this thesis, we assume that the power output of PV is proportional to the solar curve available on the NASA home page [START_REF] Nasa | Surface meteorology and Solar Energy[END_REF] in Cambodia.

o The integration of DG as a grid planning option is currently strongly encouraged by the regulation. In that purpose, it is assumed that the regulation accepts the capacity of PV which are found by the developed algorithm.

I.8 Conclusion

In this chapter, we have started from the context and background of the power system in Cambodia. It was highlighted that there is about 75% of own generation and the remaining 25% are imported from neighboring countries even if Cambodia has a high potential for renewables. Presently, the main lines are distributed with single-phase and three-phase conductors along the roads for rural areas, and are almost three-phase for urban areas in Cambodia. In traditional planning, the local generation such as PV and battery energy storage (BES) are not taken into account; thus it is interesting to integrate them into planning studies as alternative solutions to gird reinforcements. The constraints taken into account for the optimal architecture are linked to the topology and the electrical variables Page 22 (i.e. current, voltage and power losses). The main objectives of this thesis are to search for the optimal topology and impact of PV-BES integration in low-voltage distribution systems over the planning horizon. These problems will be considered in the next three chapters.

[

II.1 Introduction

The low-voltage (LV) distribution systems are reinforced and expanded in the recent years due to the load demand increase (i.e. population growth and living standard improvement); these points compel the electricity distributors to perform a planning following these issues. In a planning procedure of power distribution system, it is essential to design an appropriate topology in order to satisfy economic and technical aspects. The LV distribution systems are almost unbalanced radial system due to various single-phase and three-phase loads as shown in Figure II-1. To cope with these problems, a radial distribution system optimization has been developed in the literature to find a lowest investment cost by using either a path search algorithm in [START_REF] Kumar | Optimization of Radial Distribution Networks Using Path Search Algorithm[END_REF] or a direct approach in [START_REF] Samui | A Direct Approach to Optimal Feeder Routing for Radial Distribution System[END_REF]. Also, the authors in [START_REF] Shu | A New Method for Spatial Power Network Planning in Complicated Environments[END_REF] and [START_REF] Monteiro | GIS Spatial Analysis Applied to Electric Line Routing Optimization[END_REF] have been studied the problem of feeders routing respectively by using a mixed integer linear programming model or the dynamic programming; these methods allow to model finely the reality but are applied for transmission networks which are not radial as distribution network. To build a radial topology considering the environment, the researchers in [BOMP02] have been applied a dynamic programming method in order to obtain the topology. Likewise, the work of [START_REF] Lin | Application of geographic information system for substation and feeder planning[END_REF] suggests some heuristics based on simple mathematics to allocate the substations and the feeders of a distribution networks. But both [BOMP02] and [START_REF] Lin | Application of geographic information system for substation and feeder planning[END_REF] focus their studies on the medium voltage networks which phases are balanced. The authors of [GOAR15] studied the optimal planning of urban distribution network considering its topology by using adapted simulated annealing algorithm; this method aims at minimizing the upgrades of the existing network necessary for its expansion. But [GOAR15] considered only balanced three-phase medium-voltage systems.. Also, as the phase balancing gives many advantages in distribution systems, the authors in [START_REF] Echeverri | Optimal phase balancing planning for loss reduction in distribution systems using specialized genetic algoritm[END_REF] have studied the loss reduction obtained thanks to an optimal phase balancing algorithm; this method has reduced the current of line and enhanced the unbalanced voltage factor. Furthermore, other methods such as the mixed-integer programming in [START_REF] Zhu | Phase balancing using mixed-integer programming[END_REF] and the simulated annealing in [ZHU99] propose to switch the phase connection of single-loads to reduce power losses. In these research works, only the existing radial topology is considered. The challenge on LV distribution planning are still missing whilst finding an optimal topology with phase balancing faced to load demand uncertainty in unbalanced system.

Figure II-1 : Example of low voltage distribution system in urban areas

In this chapter, we aim at developing a long-term planning methodology to tackle the challenge of load demand uncertainty (i.e. growth rate and new load connection) in LV distribution system. We develop a novel algorithm to search for an optimal topology by finding which load connection induces the lowest costs (investment and power losses) and phase balancing improvement. In the first part, the low-voltage distribution network model is described. Then, the proposed algorithms are presented as well as the case study on which they will be applied. Finally, simulation results will be provided and analyzed.

Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z       =         (II-1)
If phase a does not exist in the system (i.e. single phase or two phases network), the elements of row and column of this matrix will be equal to zero as shown in Eq. II-2. 0 0 0 0 0 0 0 0

0 0 0 0 0 [ ] and [ ] 0 0 0 0 0 0 bb cb bn bcn cn cb cc cn cc cn nb nc nn nc nn Z Z Z Z Z Z Z Z Z Z Z Z Z Z Z             = =                 (II-2)
Where:

abcn Z : impedance of the system in / km Ω , ii Z : self-impedance of the system, ... i a n = in / km Ω , ij Z : mutual-impedance of system, , ... , ... i j i a n j a n ≠ = = in / km Ω .
The impedance matrix can be computed using the method developed by Carson and

Lewis [START_REF] Kersting | Distribution system modelling and analysis[END_REF]. The values of self and mutual impedance of lines can be calculated from basic data such as the radius of conductor, the GMR (geometric mean radius), the distance between conductors, and the line frequency. The simplified Carson's equations [EBBH11] for calculating self and mutual impedance will be provided in Appendix II-A.

II.2.1.2 Neutral wire model

The current in the neutral wire is the current vector sum in the three phases. The following equations express the current in the neutral wire. The current in the neutral wire is a huge issue in three-phase four-wire low voltage distribution systems. This current not only leads the losses, but also increases the temperature in the neutral wire [BENO15] and can reduce the security for labors .

II.2.1.3 Load model

The loads in distribution system are typically specified by the apparent power consumed. The voltage specified will be always the voltage at the LV terminals of the distribution substation. Iterative techniques are usually employed such as [CIFO03] to deal with the non-linearity of the equations to be solved. The loads on a distribution system can be modeled as [START_REF] Kersting | Distribution system modelling and analysis[END_REF]:

o Constant power: bus bus S I V *   =     o Constant impedance: bus bus bus V I Z = o Constant current: bus I
o Any combination of the above However, the households usually are a mix of constant power, impedance and current loads, but are classically considered as constant power, since power is the common measurement [BENO15]. Therefore, the constant active and reactive power loads model is chosen in this thesis.

The specified apparent powers and voltages of loads are defined as it follows: Further, the line currents for constant active and reactive power loads are given by: / a a a a a an an

S S I V V δ θ *   = = -     (II-8) / b b b b b bn bn S S I V V δ θ *   = = -     / c c c c c cn cn S S I V V δ θ *   = = -    
Where: In this model, the terminal voltages will change during each iteration until the convergence is achieved [START_REF] Kersting | Distribution system modelling and analysis[END_REF].

II.2.2 Power Flow Analysis

II.2.2.1 Classical Power Flow

The classical power flow equations are written using the admittance matrix Y and constant power loads:

* , i i i i i i i j j j bus i Nodes S P jQ V I V Y V * * ∈ ∀ ∈ = + = × = × × ∑ (II-9)
After separation of real and imaginary parts ( S P jQ

= + and Y G jB = +
), and V expressed in its polar form (

j V V e δ ⋅ =
⋅ ), the active and reactive powers are defined as follows.

( ( ) (
)

) i i j ij i j ij i j j bus P V V G cos B sin δ δ δ δ ∈ = ⋅ ⋅ ⋅ - + ⋅ - ∑ (II-10) ( ( ) (
) δ δ δ = -: voltage angle between the bus i and j , ij G : conductance between the bus i and j , ij B : susceptance between the bus i and j .

) i i j ij i j ij i j j bus Q V V G sin B cos δ δ δ δ ∈ = ⋅ ⋅ ⋅ - -⋅ - ∑ (II-

II.2.2.2 Selected Power Flow

Instead of the usual admittance matrix Y , the matrix of lines impedance system Z is used, in which each line has the impedance defined in Eq. II-1 and Eq. II-2. The backward/forward sweep load flow [CIFO03] will be used for unbalanced power flow analysis for this work. The current line and voltage drop are expressed by:

l lr lr J I J = -+ ∑ (II-12) ls lr l l V V V Z J ∆ = -= × (II-13)
Where

II.2.2.3 Voltage Unbalance Factor (VUF)

In a perfectly balanced system, the currents in the three phases are equal and shifted by 2 / 3 π . Therefore, these currents combine in the neutral wire, whose current is equal to zero. However, when the system is unbalanced, they do not cancel themselves, and a neutral current appeared.

The unbalance is defined at every bus by the magnitude of the ratio of the negative sequence voltage neg V by the positive sequence voltage pos V [START_REF] Pillay | Definitions of Voltage Unbalance Call for Short Papers[END_REF]:

Vannak VAI, Grenoble INP / G2Elab Page 36 2 2 , , , , 3 2 , , , , Unbalance( ) , with
j i neg i a i b i c i pos i a i b i c V V a V aV i Nodes a e V V aV a V π + + ∈ = = = + + (II-

II.3 Uncertainty on load demand

The loads growth rate and the apparition of new loads are increasing with unpredictability year by year in the LV distribution network. In this chapter, we thus propose to study the three cases of uncertainty defined as it follows.

II.3.1 Case 1: Evolution of the growth rate of the existing loads

This case considers uncertainty on the growth rate of the existing loads only. In this chapter, its value is assumed to be between 2% and 4%1 per year since there is currently no relevant information available on this growth rate. As depicted in

II.3.2 Case 2: Only new connected loads

The demand of existing loads is assumed to be constant and new loads appear in the network with uncertainties on their locations and powers. The new households will be connected to the LV distribution system by fixing randomly the location (x, y) and peak demand during the planning period study. Figure II-4 shows the demonstration of case 2.

In this example, at the end of the planning period, there are three new households (H10-H11-H12) connected to the LV grid. architecture (number of feeders and optimal paths) is not directly visible and optimization algorithms are required. In this section, two strategies for finding the optimal topology of LV urban networks are explained. Rural areas are characterized by a low load density and the main line path can be usually drawn by hand. In urban area, there are two different cases. If the MV/LV transformer is single phase, then the main line follows the road and the customers are connected to the closest pole. In case of a three phase transformer, an optimization algorithm is required to find which loads will be allocated to which phase so as to balance the network. In this case a First Fit Bin Packing algorithm (FFBP) also used in strategy 1 for urban network is applied. In that purpose, in this chapter, the planning tool only for the urban network will be detailed.

II.4.2 Detailed description of the methodology for planning the urban network

As presented in the context and the literature review of planning issues in LV distribution systems (see II.1), the objective of this part aims at developing a method to cope with designing the optimal topology under uncertainty on load demand. The objective is to minimize the length of the radial topology to deliver electricity to all the end users while ensuring phase balancing and considering technical and economic criteria in the low voltage distribution system. 1) The input data are the location and peak demands of the loads and the MV/LV substation corresponding to a non-electrified area and the planning period. In addition, prevision, of new loads and the minimal, maximal and average load growth of the studied area are assumed.

2) The optimal architecture at the initial year is built as a starting solution. First, all the possible lines locations are created using the Delaunay triangulation algorithm [START_REF] Fang | Delaunay Triangulation Using a Uniform Grid[END_REF] in order to minimize the length of lines and reduce the search space. Then mixed integer quadratically constrained programming-MIQCP [START_REF] Chang | Application of MIQCP based SVC allocation method to a complex real-world grid[END_REF] in ILOG-CPLEX [START_REF]IBM CPLEX Optimizer -United States[END_REF] (Eq. II-15) enables to find the optimal radial topology at the initial year (Strategy 1) and at the end of the planning year with the average load growth (Strategy 2) which minimizes the total length of the network while ensuring the phase balancing.

3) The three case studies of uncertainties previously defined are computed (i.e.

uncertainty on growth rate and new connected loads). 1000 Monte Carlo (NMCS) simulations are done in which the variables are the peak load growth of the existing loads every year, the locations of new loads, their peak power and the year of apparition. Many guides have focused on the simple random sampling, but only one common rule was found from the literature [MATA08] saying that the larger the sample size is, the more information we get. The sample size required may depend on the distribution, number of variables or something else. The only way to see if the number of samples is enough is to make more simulations and see if the result stays similar. In our case, it seems that 1000 random samplings is enough for convergence.

4) The two strategies are compared for the three cases studied. The first one (Strategy 1) consists in making the network evolve year by year without anticipating in the long term.

If new loads appear, they are connected to the architecture using a two stages algorithm (shortest path [CORA14] and first-fit bin packing [RARA07] algorithms). The second strategy (Strategy 2) consists in imagining the target network at the end of the planning period and directly building it as explained in 2). This optimal architecture is kept without any change all over the planning period. Reinforcements can occur if constraints appear.

5) An unbalanced load flow enables to evaluate current and voltage constraints and to reinforce the network.

6) The total actualized cost during the planning study with uncertainty on load growth rate and new connected loads is evaluated for each Monte Carlo simulation.

7) The optimal topology will be selected according to the lowest total actualized cost of each low-voltage system design.

Furthermore, more information on each step will be provided in the following sections.

II.4.3 Mixed Integer Quadratically Constrained Programming-MIQCP[VGBA17]

A graph [START_REF] West | Introduction To Graph Theory Notice Second Edition ( 2001 ) Solution Manual[END_REF] can be used to characterize an electrical grid which is defined as a pair of sets

( , ) G G V E ≡ , where {1.2... } V N =
is a set of N vertices of the graph representing the LV loads and The optimization problem of minimizing the conductor length is modelled as a MIQCP and given by: Minimize:

{ }( , ) } ij E V V e i j V ⊆ × = ∈ , { }
_ _ _ ( , ) ( ) A B C ij ij ph ij ph ij ph ij i j E d x x x x ∈ ⋅ + + + ∑ (II-15)
Where:

_ _ _
, , , {0,1}: state of connection between two buses and , , : phases of system

A B C ij ph ij ph ij ph ij x x x x i j A B C ∈
(0: bus i and bus j are not linked and 1: bus i and bus j are linked) { }, ( , )

ij d i j E + ∈ ℜ ∀ ∈ : distance between two buses
Subject to the following constraints:

• Arborescence ( , ) ( ) _ _ _ 1, \ , is source ( ) : set of incomming edge for vertex 1, ( , ) , ( , ) , ( , )
, ( , )

in ij i j j in th ij ji A ph ij ji B ph ij ji C ph ij ji x j V S S j j x x i j E x x i j E x x i j E x x i j E δ δ ∈ = ∀ ∈ + ≤ ∀ ∈ ≤ ∀ ∈ ≤ ∀ ∈ ≤ ∀ ∈ ∑ (II-16)
• Load balancing

α + = = = ∈ ℜ ∈ =   - ≤     - ∑ ∑ ∑ 2 2 1 2 2 1 1 _ _ _ n C i i n n B C i i i i i i

oad ph eps p load ph p load ph eps

= = =   ≤       - ≤     ∑ ∑ ∑
(II-17)

• Thermal capacity limit of lines

ij ij ij ij A A B B C ij ij ph ij ij ij ph ij ij ij i j E P p ij Q q ij P p x P p x P p ∀ ∈ ≤ ≤ ≤ _ max max max _ _ _ , , C ph ij A A B B C C ij ij ph ij ij ij ph ij ij ij ph ij x Q q x Q q x Q q x ≤ ≤ ≤
(II-18)

• Load phase allocation \ , is source _ {0,1}: phase connection of loads , , or

1,if 1 phase _ _ _ 3,if 3 phase i A B C i i i i V S S load ph i A B C load ph load ph load ph α α ∀ ∈ ∈ =  + + =   (II-19) • Power flow without loss ( , ) ( , )
\ , is source : active power of loads : reactive power of loads _ {0,1}: phase connection of loads , , or _ ,if i connect to 1 phase

_ i i i i i ji ij i i j i E i j E i V S S p i q i load ph i A B C p load ph P P p load ph α α α α α ∈ ∈ ∀ ∈ ∈ = - = ∑ ∑ ( , ) ( , )
,if i connect to 3 phases 3

_ ,if i connect to 1 phase _ ,if i connect to 3 phases 3 i i ji ij i i j i E i j E q load ph Q Q q load ph α α α α α ∈ ∈        - =    ∑ ∑ (II-20)
This modelled is used for finding the optimal network at the initial stage and for strategy 2.

II.4.4 Shortest Path and First Fit Bin Packing (SP-FFBP)

In case 2 and 3, new loads appear in the network from the year 1 to the end of the planning period and have to be connected to the LV grid with the objective of minimizing the conductor usage and optimizing the phase balancing. In that purpose, the shortest path (SP) and first-fit bin-packing (FFBP) algorithms will be applied. In graph theory, the SP problem consists in finding a path between two vertices (or nodes) in a graph such that the sum of the weights (here the length of lines) of its edges is minimized. The FFBP problem consists in packing all items into defined number of bins, while minimizing the difference of total weight of each bin. In this work, the items are the load demands (P, Q) and the bins are the phases (A-B-C) of the power system, respectively.

- = < 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 ) ( )) [y , , ] [1,0,0] ( ( ) ( )& ( ) ( )) [y , , ] [0,1, 0] ( ( ) 7 8 9 1 ( )& ( ) ( )) elseif elseif 0 11 A C n A B C n n n B A B C n n n n A B C n n n C A C B n n

II.4.5 Actualized cost

The actualized cost of the networks over P years for different topologies and planning strategies will be computed. This calculation takes into account the capital expenditure (CAPEX) and the operation expenditure (OPEX) due to power losses. The actualized cost [APCR11] thus can be expressed by:

_ 0 ( ) ( ) (1

II.4.6 Monte-Carlo simulation

To cope with the problem of uncertainty on load demand during the planning study, the Monte-Carlo (MC) simulation will be employed to compute the probability distribution of the overall actualized cost (see II.4.3) by taking into account these uncertainties. The random parameters are the peak load growth rate which is randomly chosen using a uniform law between two extreme values and that location of new loads which is also uniformly randomly chosen. The MC results of the total actualized cost for both strategies with different topologies (see II.6.4.2) will enable to select the best solution.

II.4.7 Load connection phase and reinforcement

Two load categories are taken into account in this work: single phase load (A, B, C) and three phase load (ABC). The loads higher than 10 kW [VGBA17] are classified as threephase loads and single phase loads otherwise. The reinforcements of cables type-LV-ABC (Aerial bundled cable) from 50-70-95-150-240 mm 2 [VGBA17] to avoid the current constraints have been considered in this chapter.

II.5 Strategy of planning

As presented in section II.3, in case of load demand uncertainty, we thus proposed to study two strategies of planning: reinforcing year by year waiting the constraints appear or reinforcing at the initial stage intending to minimize power losses.

II.5.1 Strategy 1: Upgrades year by year

This strategy consists in designing the topology with the initial load demand and all loads will be increased every year over the planning study. The topology will be found by applying a MIQCP algorithm for the initial year. The SP and FFBP algorithms are used from year 1 to the end of the planning study for case 2 and case 3 when new loads have to be connected. Figure II-9 illustrates the principle of this strategy. It can be seen that the loads have been increased from the initial year (light green color) to year 1 (dark green color and other); at that time, it can be noticed that the current constraint has appeared (over the admissible capacity of the cables) for lines (MV/LV-H2 and H2-H5), but not for voltage due to the case of urban area. To avoid these current constraints, the lines have been reinforced (red color of line), e.g. 50 mm2 to 70 mm2. Additionally, this process is applied until the end of the planning study (year P) as shown in the figure. The total active and reactive power is respectively 147 kW and 48.32 kvar (power factor of 0.95) randomly generated for the initial planning year. The details of peak demand for the LV customers and their locations are given in Table II-1. We assumed that fifteen loads will be connected to the LV grid by fixing randomly the location (x, y) and the peak demand (P, Q) as provided in Table II-2. In addition, these new connected loads will randomly appear from year 1 to the end of the planning study.

II.6.4 Simulation result and discussion

All simulation and graphical results have been obtained by using ILOG-CPLEX and MATLAB software.

II.6.4.1 Available paths

The MIQCP algorithm needs all the available paths to be defined as constraints. According to these results, we can conclude that the 2 nd strategy (S2) is selected for the case study 1 (about 36% less expensive) and the 1 st strategy (S1) for the case studies 2 and 3 (between 7 and 14% less expensive).

Figure II-20 shows the CAPEX and OPEX for each year of both strategies 1 and 2 for case 1. In this case, only the existing loads are evolving and no new loads appear during all the planning period. In that case, building directly the optimal structure in the initial year is more economic for two reasons. First, the objective of this strategy is to minimize the total length of conductors while respecting a set of constraints. In the 2 nd strategy, the total length of the final architecture is 2.53 km while the total length of the conductor to reinforce is 3.25 km for the 1 st strategy. As the cost of conductor is proportional to its length, the CAPEX in the 2 nd strategy is lower. In addition, the power losses are reduced over all the planning studies because the size of the conductor is bigger in the 2 nd strategy. Then the OPEX is also lower in the 2 nd strategy. It can be seen that the global cost of strategy 2 is lower than strategy 1 from year 1 to year 9 (resp. year 6) for case study 2 (resp. case study 3) and higher after year 9 (resp. 6). The network found by strategy 2 has more single phase lines because it aims at minimizing the total conductor length. Then, when the number of new loads reaches a certain level, the power losses of strategy 2 becomes higher than strategy 1. It can be concluded that in case of new load appearing over the planning study, the 1 st strategy will be more economic because the uncertainties on new loads have a big impact on the topology. Therefore, the conclusion of this chapter is that the 2 nd strategy will be chosen for areas having a very low probability to have new customers (for example very dense neighborhood), otherwise the 1 st strategy will be applied for areas in development (new districts or new shops). Nevertheless, it is necessary to run theses simulations on other data before generalizing the results.

II.7 Conclusion

This chapter proposed methodologies and tool to plan the LV distribution network considering uncertainties on the load evolution (increasing of the consumption of loads present at the year 1 and new loads appearing during the planning period). Two types of optimization methods were used. The 1 st strategy consists in making the LV network evolve as constraints or new loads appear. In that purpose, the shortest path and fit bin packing algorithms were used. The 2 nd strategy consists in finding the optimal architecture at the end of the planning period and building it at the year1 thanks to a MIQCP algorithm. These 2 strategies have been integrated in a Monte Carlo simulations were the peak load growth per year and per customers, the location, power and year of appearance of new loads are randomly generated. An average actualized cost enable to conclude that the 1 st strategy enable to reach more economic solutions in case of new loads while the 2 nd strategy enable to reach more economic solutions otherwise. These tools enable the planers to design optimal LV grids for non-electrified areas with the objective of minimizing the total length of lines, maximizing the load balancing and respecting a set of technical constraint. In this chapter, only topological options have been considered as planning solutions (reinforcement of cables and optimal design of network). In this tool, the presence of renewable sources has not been considered. Nevertheless, in non-electrified areas, some customers are equipped with PV (SHS) to have access to the electricity but are not connected to the main grids. The next chapter proposes to integrate the presence of PV in the LV planning tool.

Vannak VAI, Grenoble INP / G2Elab

Page 59

Chapter III

Integration of Photovoltaic using Battery

Energy Storage in Low-Voltage

Distribution System

III.1 Introduction

In chapter II, a LV tool has been proposed to find the optimal LV topology in nonelectrified areas. Only the loads and the uncertainties on them have been considered and the effects of PVs have not been studied. Nevertheless, if the production occurs in a moment of low consumption (which is the case for the PV), all the electricity produced is not locally consumed. Over-voltages, over-currents and even reverse power flows at the MV/LV substation (i.e. current going from the LV network to the MV network) can occur and could lead to high investment in the MV network. In Cambodia, the SHS used by customers are small size units and their number is low enough not to cause potential voltage and current constraints. But there is a desynchronization between the time when the peak load occurs (between 19h and 20h regarding the type of areas) and the time when the peak production occurs (between 12h and 13h) in an electrified LV Cambodia system. Then, in an LV network with PVs, reverse power flows are likely to happen. Then the new planning problem becomes: how to connect non-electrified customer while canceling reverse power flows due to PV? In this chapter, a centralized BES has been connected to the MV/LV substation so as to cancel the power flows. For the particular case of rural areas, if undervoltage constraints appear due to the load, decentralized battery energy storage will also be used to prevent from reinforcing the network (no under-voltage constraints in urban areas).

Consequently, this chapter proposes algorithms to locate and size BES in order to integrate PV into the distribution network planning. This novel planning methodology leads to the creation of LV microgrids which could be disconnected to the main grids during some moments of the year enabling to reduce the investment in the MV network. The methodology will be described for the rural case in order to present the two kind of BES strategies used. It will be applied on a simple rural case study (single phase MV/LV transformer) as depicted in Figure III-1. into the grid. The association of PV with BES enables to better control power flows as we know that the energy of PV is only available during the day and depends on the solar radiation received. Thus the BES integration is interested when power is required but cannot be provided by PV. In this chapter, we assume that a single-phase PV unit will be installed at some households. Besides, two possibilities of BES integration (i.e.

decentralized BES and centralized BES) will be investigated in the following section and their performance and costs will be compared. A technical and economic study will compare the interest of the association of PV and BES to reduce the global cost of the network (i.e. the CAPEX and OPEX).

III.2.1 Decentralized BES

The Decentralized Battery Energy Storage (DeBES) is integrated at some households' nodes in the LV distribution system. The objective of PV-DeBES integration is to improve the voltage profile in the whole system without deploying a communication system along the network.

III.2.2 Centralized BES

When the PV production is very high and the consumption low, reverse power flows can go from the LV network to the MV network. Then, the integration of Centralized Battery Energy Storage (CeBES) at the MV/LV substation could be added to store these excesses of power. Another interest of CeBES would be to reduce the power requirement from the MV grid by providing electricity to the customers when the PV production is not enough. The CeBES combined with PV could enable the creation of an LV microgrid with some autonomous operation times which could be potentially disconnecting from the main grid.

III.3 Methodology

The general algorithm proposed to extend the existing LV network to the nonelectrified area is depicted by the flowchart of Figure III-3.

Vannak VAI, Grenoble INP / G2Elab

Page 65 autonomous operation time by using a sizing strategy development (see III.3.2.3). Finally, the two strategies are compared by computed their global actualized cost.

The following section will provide the developed algorithms listed above.

III.3.1 Strategy 1: grid reinforcement

Once the non-electrified customers are connected to the existing LV grid, the grid reinforcement procedure enables to size the lines so as to avoid under voltage and current problems. The cable size will be reinforced considering the peak load of 19h00 (see III.

III.3.2.1 Sizing of Decentralized PVs

There are a lot of uncertainties regarding the PVs locations and powers in the future.

Therefore, the location of PVs is assumed among the households. The objective here is to find out a maximum PV peak power which can be integrated into the LV grid while respecting voltage and current constraints. This problem is solved by using an iterative technique.

III.3.2.2 Location and Sizing of Decentralized BES-DeBES

III.3.2.2.1 Location of DeBES

The under voltage problem is almost always at the furthest connected household with and without the presence of PV. Indeed, the maximal consumption occurs in general when the PV production is low. Then the case of low-voltage constraint is the same with and without PV connected. The DeBES is located in the network in order to remove the lowvoltage constraint. However, the integration of the DeBES at the furthest household is not always the optimal location. Therefore, the optimal location of the DeBES is computed using a genetic algorithm. The advantage of the genetic algorithm here is its ability to avoid being trapped in local optima. Also, this algorithm is able to search a problem with mixedinteger constraint. The objective is to search for the optimal location and power of the DeBES which minimize the power injection at 19h00 (hour when it is maximal). The objective function is formulated as it follows:

Objective: min

t k Pbes (III-1)
Where:

{ }, power injection of DeBES, electrical poles' node at 19 00

t k Pbes k t h + ∈ ℜ ∀ ∈ =
Subject to following constraints:

• Voltage constraint [KING04] limit 0.9 1.06 pu V pu ≤ ≤ (III-2) • Current constraint line max I I ≤ (III-3)
Moreover, the implementation of the GA will be done with generations consisting of 50 individuals of location and sizing. The maximum number of generations is set to be 200.

The fitness of each individual is given by the objective function, and it also considers a penalization if the voltage goes outside the allowed interval, plus another penalization if the current exceeds admissible capacity of cable. The fitness value f for any individual x is 1 be upgraded to 20% bigger in order to satisfy the minimum state of charge of the battery (which have to be higher than 20%) [MJCX14].Then, the sizing of the DeBES is equal to the sum of all the negative (discharge) values of power as follows.

III.3.2.3 Sizing of the centralized BES(CeBES)

The objective of the CeBES is to charge the energy during reverse power flows from the LV grid to the MV grid and to discharge when the grid must supply the LV loads provided that the state of charge of the battery remains between SoCmin and SoCmax.

III.4.4 Simulation results and discussion

In in this part, we focused on the simulation results and discussion. Moreover, the backward/forward load flow algorithm [CIFO03] is used when a power flow analysis is required. The minimal voltage and maximal current are listed in Table III According to these results, we can conclude that the cable size of 95mm2 is selected for the grid reinforcement since there is no voltage and current constraints in our test system.

III.4.4.1 Strategy 1: Grid reinforcement

III.4.4.2 Strategy 2: PV-BES

III.4.4.2.1 PV integration

Currently, there are no information about the percentage of PV use on households (solar home system) and also integrated into the LV distribution system in Cambodia. In this chapter, we will assume that the six households who have the highest load demand will have a single PV unit with an identical maximal power connected to the grid and located at with and without PV-DeBES integration. According to that figure, it is identified that the system does not respect the voltage constraint in case of non-integrated DeBES. However, this constraint has been removed thanks to DeBES. 6kW battery inverter (bi-directional inverter) [SMAS17] which is available in Cambodia, is used for simulation. Also, the same schedule will be repeated in over a year of simulation.

III.4.4.2.3 CeBES integration

The CeBES is installed at the MV/LV substation (1 st bus) and the sizing strategy of the centralized BES is applied to find out its capacity. Besides, the autonomous operation time of the LV system has been increased with the integration of the CeBES and the end users have been supplied with the electricity coming from the PV-DeBES-CeBES in some period without energy from the MV grid. MWh representing about 55 % reduction. Moreover, the LV distribution system could be operated as an isolated microgrid with an autonomous operation time of 78 % per year.

Additionally, the under voltage problem has been completely removed thanks to DeBES integration and its decentralized control.

III.4.4.3 Comparison between grid reinforcement and PV-BES integration

In this work, the actualized cost method is employed to evaluate the two different proposed solutions over N years. This actualized cost takes into account the capital expenditure (CAPEX) and the operation expenditure (OPEX) of the energy losses in the LV distribution system. In addition, the reduction of the energy consumed by the loads thanks to the Ce-BES has been added in the cost computation. Then the energy used is defined as the energy consumed by the loads plus the energy losses.

The actualized cost [APCR11] thus can be expressed by: The CAPEX at the year 1 of the two strategies is detailed in Table III It can be seen that the initial CAPEX for the second solution is about 15 times higher than the first solution. When the OPEX costs are integrated and the total actualized cost is computed, the tendency is reversed. The OPEX cost consists in the cost of the energy the DSO will have to pay. The 2 nd strategy enables to increase the autonomy of the LV grid by decreasing the energy coming from the MV grid. In this case, the energy required without the PV-DeBES-CeBES to supply all the customers is about 47.1 MWh and with this system about 22.8 MWh, i.e. 2 times lower.

_ 0 ( ) ( ) (1
The actualized cost of the 1 st proposed solution is about 94 kUSD and 92 kUSD for 2 nd proposed solution. The cost is almost the same for both strategies however the cost of the 1 st strategy is expected to increase with the planning period. Also, two advantages which cannot be quantified are the cancelation of the reverse power flows and the ability of the LV network to be operated independently from the MV network during a high period (78% of the year) thanks 2 nd solution. Therefore, we can conclude that the 2 nd proposed solution with

Vannak VAI, Grenoble INP / G2Elab Page 86

PV-BES integration is selected our test system in case without taking into account the line construction and maintenance costs.

III.5 Conclusion

In this chapter, a new way of planning non-electrified LV distribution grid has been proposed. It consists of integrating PV and storage as an alternative to grid reinforcement.

In rural LV distribution network, the load density is low leading to long lines with problems of under-voltage. The traditional solution consists in reinforcing the network. The introduction of a decentralized battery (DeBES) enables to solve the problem of lowvoltage constraint. PV is also introduced so as to increase the local production and decrease the power coming from the MV grid). Finally, a centralized storage (CeBES) enables to prevent the electricity produced by the PV to be injected in the MV network and also to bring the LV network as autonomous as possible. This system PV-DeBES-CeBES aims at creating a microgrid as autonomous as possible from the main grid. Several algorithms have been described to size this microgrid and applied on a real case study. The conclusion was the followings:

-The creation of the microgrid requires a high CAPEX investment at the first year, -The OPEX reduce by twice and on the long term this solution is more economic than the reinforcement.

-Other property not quantified have to be pointed out: the microgrid can be autonomic 70% of the year and the peak power has been reduced by two. In other words, potential cost of reinforcement on the MV size would be drastically reduced or avoided.

-The control of the microgrid is simple and based on a two sensors (one for the centralized battery and another for the decentralized battery) so as to prevent from having to develop a complex and expensive ICT system.

Chapter IV

Planning the LV Distribution System with Photovoltaic and Battery Energy

Storage -Case Studies

IV.1 Introduction

In chapter III, a new way of planning the LV distribution grids using PV and storage as well as the required algorithms have been presented. In this chapter, we propose to apply it on two cases studies, an urban and a rural area. In both case, the first step will be to design the network and the second step will be to size the PV (for both areas), to locate, size and control the decentralized storage (only for the rural area) and to size the centralized storage (for both areas).

IV.2 Methodology

The proposed method consists in planning both urban and rural area by integrating the Decentralized PV (DePV), Decentralized BES (DeBES) and Centralized BES (CeBES) in the LV distribution system using a sequential approach. The approaches used for planning an urban area and a rural area are different. Indeed, in urban area, the load density is high with short conductor lengths whereas in rural area conductor lengths are long. Current constraints thus will almost always occur in urban area whereas the voltage constraints will appear in rural area. In this context, planning solutions will be different regarding the type of constraints. The global algorithm proposed will be then different for rural and urban areas and are described in the following section. The main difference is the integration of the DeBES in the case of rural area and not in the case of urban area since the objective of DeBES in this work is to solve under voltage problems.

IV.2.1 LV urban network planning

The proposed method aims at finding the optimal topology as well as sizing the DePV and CeBES while satisfying the bus voltage constraints ( 0.9 1.06 pu V pu ≤ ≤

) and the current flowing through the lines constraints (maximal admissible current of conductors).

In this planning study, the four following objectives will be sequentially achieved:

-Optimal radial topology using the two strategies presented in chapter 1(shortest path The planning period is 15 years with an annual growth rate arbitrary equal to 3%. Then, we size the single-phase PV units which are integrated into the grid at the households' nodes.

Then, the CeBES is also sized in order to solve a potential problem of reverse power flow and also to increase the autonomous operation of the LV network to relieve the MV network. The comparison between the two strategies is discussed thanks to the computation of the actualized cost in the last part of this work.

IV.2.1.1 Actualized cost

The actualized cost of the systems will be computed over N years for different topologies. It computation is given in section III.4.4.3 of chapter III.

IV.2.1.2 Sizing of PVs

There are a lot of uncertainties regarding the PVs locations and power production in the future. Therefore, it is assumed that the consumer having a high demand is interesting to use PV. Then the highest load consumption per phase of each feeder is equipped with a single-phase PV unit. The objective is to find the maximum PV penetration in initial year which can be integrated into grid while respecting voltage and current constraints on each feeder. This PV penetration level is defined as the ratio between the peak power of PV and the peak consumption of grid. It is expressed as:

( ) (%) ( )

Peak Power of PV kW PV penetration Peak Consumption of Grid kW = (IV-1)

In this equation, the denominator stands for a maximum value of the total demand of the grid consumers. The power of the PV units is determined using the flowchart of Figure III-5 explained in chapter III.

IV.2.1.3 Sizing of CeBES

The centralized battery is sized and controlled using the methods explained in section III.3.2.3 of chapter III. We remind that the objective of the battery is to avoid reverse power flow while optimizing the autonomy of the LV network.

IV.2.2 LV rural network planning

For planning a rural area, the proposed method will address an optimal topology with load balancing and minimizing power loss using the Shortest Path (SP) and First-Fit Bin-Packing (FFBP) method and size the PV, DeBES and CeBES to respect the voltage and current constraints. The MIQCP method is not used because the problem is simple in this case. The four following objectives will be achieved in this planning study of a rural area:

-Optimal radial topology with load balancing using SP and FFBP (see chapter II) -Maximization of the DePV penetration, -Optimal sizing of the DeBES as well as the decentralized control algorithm -Optimal sizing of the CeBES we search the optimal topology with load balancing by using first-fit bin-packing [RARA07][VGBA17] on each pole; that means the households are powered from energy meters at pole. After having obtained the optimal topology, we need to define the amount and the location of single-phase PV units and then to find their maximum power penetration according to PV-load curves by using the same iterative technique as the one described in chapter III. After having got the sizing of PVs, we find the optimal location of DeBES by using a genetic algorithm (see in chapter III) [IBA93]. Then, we size its minimum capacity by using an iterative technique at the end of the planning year with a growth rate of 3 % 1 .

IV.2.2.1 Location, sizing and control of the DeBES

The method used to locate, size and control the DeBES is the same as the one developed in chapter III except that it is repeated for the three phases in this case. We remind that the objective of this storage is to relieve the low-voltage constraint due to the load.

IV.2.2.1.1 Integration of the uncertainties on load

To cope with the problem of uncertainty on load profile during the planning study, a Monte-Carlo (MC) simulation is employed to get the statistical distribution of the voltage at the DeBES. For each Monte Carlo simulation, uncertainties on the load profile are integrating by introducing a variation of +/-5% around the profile. The mean value of these simulations will be used to obtain Vset.

IV.2.2.2 Sizing of CeBES

The sizing strategy of the CeBES is the same as the one presented in chapter III.

IV.3 Test systems

IV.3.1 In urban area

IV.3.1.1 Site study

The village located in Sangkat Veal Sbov, Phnom Penh (Cambodia) is selected as a case study in this work. The LV distribution system is supplied from the 22-kV/0.4-kV Transformer at bus 1. The total active and reactive power is respectively 200 kW and 66 kvar for the initial year. Since there is no information available on the load demand for all the households at that site, these data are obtained by using a random draw following a normal distribution with a mean of 5 kW and a standard deviation of 0.5 kW. Figure IV-4 presents the site study and its detailed information (load demands and their coordinates) is provided in Appendix IV-A. Furthermore, a classical cable size of 70 mm 2 (Imax=185A) is used for the main line and 16 mm 2 (Imax=66A) from main line to each energy meter which is presently the standards in Cambodia. Figure IV-8 shows the voltage profile for the peak load (see Appendix III-B) of the two strategies. The voltage drop of strategy 2 is higher than strategy 1 but it remains within the limits at the end of planning period. Indeed, in strategy 2 voltage constraints are not integrated in the set of constraints of the objective function.

IV.3.1.2.2 PV penetration

As mentioned above, a single-phase PV per feeder will be installed at the households having the highest demand consumption. A simulation result of PV penetration is given in Table IV-1 for strategy 1. It can be seen that the sizing of all the single-phase PVs are nearly identical in the whole system and the total PV penetration is about 32% of 200kW total loads. As the phases of the network built are balanced, it is logical that the maximal PV penetration on each phase is equal. In order to compare, strategy 1 and strategy 2, the PV scenarios found for strategy 1 will be applied to strategy 2. In addition, Table IV-2 provides the simulation results of two different proposed algorithms for the initial year in the urban area. As seen in Table IV-2, the energy supplied from the grid has been decreased from 818

MWh to 653 MWh for strategy 1 and from 841 MWh to 674 MWh per year thanks to PV-CeBES integration. In addition, the LV distribution system in our case study can be operated as an isolated microgrid with an autonomous operation time of 26 % due to the support of the CeBES for each topology for the initial year.

Table IV-3 shows the simulation results at the end of the planning year. As the loads demand is increased year by year, all the PV production is locally consumed and no revers power flows appear at the MV/LV substaiton. As seen in Table IV-3, there is no energy stored in CeBES and then the autonomous time of the network is 0%. However, the energy used in network is still decreased by about 13% for strategy 1 and 12% for strategy 2 thanks to PV integration.

IV.3.1.2.4 Comparison between SP-FFBP and MIQCP

In this part, the actualized cost is computed to compare the two different proposed algorithms. The total time study for the analysis is set to 15 years and the discount rate is estimated to 12 % [START_REF] Vai | Low-Voltage Distribution System Planning under Load Demand Uncertainty: Growth Rate with Connection of New Loads[END_REF]. The list of parameters for the economic analysis is the same as Table III-3 of chapter III.

The initial costs of the different algorithms for both cases without/with PV-BES integration are listed in Table IV-4 and Table IV-5. For this primary study, since there is no available information about construction cost of LV distribution, thus the actualized cost here is taken into account only for cable cost, distributed generation cost and cost of the energy used in order to validate both proposed algorithms. It can be seen strategy 1 and 2 are quite equivalent in terms of costs. For the initial years, the cost of the solution PV-BES is the double of the cost without them.

Figure IV-13 shows the global actualized cost of the two strategies. As seen in this figure, in case without PV-BES integration, the actualized cost of the 1 st strategy is about 8530 kUSD and 8856 kUD for 2 nd proposed strategy. Also, these actualized costs have been reduced in the case with PV-BES integration for both algorithms. In all the cases, strategy 1 with PV-BES integration seems to be less expensive that strategy 2.

IV.3.2.2.2 PV penetration

A single-phase PV unit amount per phase will be assumed in order to validate the proposed method since there is no relevant information about PV integration. Therefore, three single-phase PVs per phase allocate to the highest demand are selected in this part to validate the proposed method. The size of PV is found by using the iterative technique of chapter III. Thus, the sizing of each PV unit which is integrated into the grid is listed in the following table. According to these histograms, we can find the average of Vset for each DeBES.

Therefore, the Vset of each DeBES are 0.9087 pu (DeBES phase A), 0.9078 pu (DeBES phase B) and 0.9285 pu (DeBES phase C). These values are used as the reference voltages of the decentralized control of the DeBES without using ICT.

• Sizing of DeBES

According to the optimal location of DeBES (see Figure , the sizing of that battery will be provided by using the iterative technique detailed in chapter III. For this simulation, we assumed that 6/8 kW battery inverter (bi-directional inverter) of According to these results, the cable size of 95mm2 is selected for the grid reinforcement since there is no voltage and current constraints in our test system.

Furthermore, the actualized cost is computed to compare the grid reinforcement and PV-BES integration. The total time study for the analysis is set to 15 years. The list of parameters for the economic analysis is the same as Table III It can be seen that the initial CAPEX for the PV-BES integration is about 30 times higher than the grid-reinforcement. When the OPEX costs are integrated and the total actualized cost is computed, the tendency is reversed. The OPEX cost consists in the cost of the energy the DSO will have to pay. The PV-BES integration enables to increase the autonomy of the LV grid by decreasing the energy coming from the MV grid. The global actualized cost of the grid-reinforcement is about 229 kUSD and 225 kUSD for the PV-BES integration. The cost is almost the same for both strategies however the cost of the grid-reinforcement is expected to increase with the planning period. Also, two advantages which cannot be quantified are the cancelation of the reverse power flows and the ability of the LV network to be operated independently from the MV network. Therefore, we can conclude that the proposed solution with PV-BES integration is selected our test system in case without taking into account the line construction and maintenance costs.

IV.3.2.2.5 Impact of uncertainty on the load profile

This section deals with the impact on the LV system of the uncertainty on the load profile by using a MC simulation. As we got the Vset of each DeBES from the section IV.3.2.2.3, we applied these values to the decentralized control by taking into account the uncertainty on load profile.

IV.4 Conclusion

In this chapter, the new planning principles presented in chapter III have been applied on both urban and rural areas. Even if additional simulations on other networks would be necessary to conclude, a first conclusion is that for developing country the integration of solar and battery into LV grids would not be more expensive that classical planning solutions (and even cheaper). This new way of planning could also bring other advantages such as cancelling reverse power flows and increasing the autonomy of the grids. LV microgrids could be created and isolated from the main grids reducing the investment in the MV network but further studies are required to quantify these advantages.

In addition, the impact of the value of the reference voltage for the DeBES control has been studied thanks to a Monte-Carlo Simulation method applied on the load profile uncertainty over the planning period in rural area. A small error of +/-5% in the case studied does not seem to have a negative impact on network.

Vannak VAI, Grenoble INP / G2Elab

Page 123

General conclusions and future works

The objectives of this thesis were focused on the long term planning of the low voltage distribution systems with the integration of small scale distributed generations (photovoltaic) to challenge the current issues of increasing the electrification and increase the renewable energy in Cambodia. The two main contributions of this thesis are:

-the development of optimization methods to design the LV distribution network with the objectives of minimizing the cost and balancing the network, -to propose a new way of planning the distribution network by coupling the photovoltaic with storage in order to reduce the size of conductors used, to cancel the reverse power flows, to increase the autonomy of the LV grid and to reduce the peak power.

Chapter I has provided the current situation of the power system in Cambodia; it has given the necessary information for further researchers who are interested to current issues of electricity power sector in Cambodia or in developing countries with similar rules.

Chapter II developed two novel algorithms to obtain the optimal architecture for low voltage distribution grids by taking into account the uncertainty on load demand over the planning study (i.e. growth rate and new connected loads). The first one, SP-FFBP (Shortest path and First-Fit Bin-Packing) reduces power losses and improves the load balancing but increases the length of cable used. The second one, MIQCP (Mixt Integer Quadratic Constrained Programming) tries to minimize the total length of the grid and to improve the load balancing. The main conclusion of this chapter is to show that two different strategies can be applied regarding the scenario of uncertainty on the load demand. For urban networks, in case of growth rate evolution of only the existing load demand, the better strategy is to build the network at the initial year considering the predicted load demand at end of the planning study using MIQCP algorithm. If new loads appear during the planning study, the best approach is based on reinforcement principle (upgrading cable size) and building the grid year by year using the SP-FFBP. For rural networks, the main lines follow the road and the connection of customers will be done using the SP (in case of single phase MV/LV transformers) and SP-FFBP (in case of three phase MV/LV transformers).

Chapter III compared the traditional grid-reinforcement method with a new way of planning (PV-BES integration) so as to increase the electricity coverage area while integrating the presence of solar home systems. With this second solution, the electricity distributors do not need to reinforce the lines, but they have to purchase PV-BES and extend cables for new consumers. The maximum installed power of PV was calculated with respect to voltage and current constraints. Moreover, the peak load demand has been decreased thanks to battery energy storage integrated into the grid. Due to the integration of PV in grid, an autonomous operation of low voltage distribution is also possible; that means consumers will be supported by local generations (PV-BES). These two last effects could enable to decrease the required investment in MV planning. This chapter has thus demonstrated that the local generation from small scale solar energy and battery energy storage were useful for the electricity sector in Cambodia. Another contribution of this chapter is the proposed control of the BES without using a large information and communication technology (ICT) system.

Chapter IV applies and validates the new planning method developed in chapter III on two case studies. In urban area, the two algorithms developed in chapter II (SP-FFBP and MIQCP) for the optimal architecture have been used. Then the integration of PV and centralized BES is considered. A technical and economic comparison is made between the two optimal architectures including PV-BES integration by taking into account the global actualized cost. The two following results have been provided:

1-the SP-FFBP gives better results that the MIQCP, 2-the case of PV-BES integration is slightly more economic compared to the case without PV-BES integration for both architectures. The peak load power and the autonomous time of the LV grid are drastically increased.

The same study is conducted for the rural area. In this case, the SP-FFBP has been applied to find out the optimal architecture with load balancing. The maximum installed PV that can be integrated without violating voltage and current constraint was determined.

The location and sizing of both centralized and decentralized BES have been performed in order to solve the under voltage problem due to the peak load and to cancel the reverse power flows at the MV/LV transformer. In this chapter, the effect of uncertainties of the hourly load profile on the settings of the control algorithm over the planning horizon has been integrated. The main conclusion of this chapter is that the integration of PV-BES in LV distribution planning tool is a promising solution which needs to be more investigated and experimented by the Cambodian government and electricity distributors. Additionally, with these developed algorithms, the low-distribution system can be operated as an isolated microgrid independently from main MV network with an autonomous operation time of 70 % and a peak load reduction of 23 % at the end of planning period.

However, to improve this current research, some future works can be recommended. In this research, the investment cost takes into account only equipment price for evaluating the actualized cost of the different case studies of low voltage distribution system. It should be considered to take into account the construction and maintenance costs for each equipment in order to give the general conclusion about the grid design. Moreover, only PV as renewable energy is considered in this thesis, thus other types of small scale renewable sources should be investigated such as biomass (gasification) and picohydropower plant which are abundant in some area in Cambodia. Likewise, the type of battery energy storage is not considered in this research since this thesis was focused on sizing optimization. Therefore, the comparison between different battery energy storage systems should be taken into account in order to select one among them for real application.

Furthermore, this research has studied only the planning of low voltage distribution system.

The novel method and algorithm should be modified and upgraded in order to be applied for current issues in medium voltage (MV) distribution system in further studies such as the optimal location and sizing of multiple distributed generations. The LV customers could then be split into microgrids linked together through the main grids which would require a global optimization. A sensitivity study has also to be made on some parameters such as the location of PV and the range of variation of the load growth and more case studies have to be run to generalize the conclusions. Finally, a Monte Carlo approach has been used to integrate uncertainties in the planning models. Other stochastic techniques have to be investigated such as the modelling of load and productions using probability density functions and a probabilistic load flow.

Increasing the electrification of the developing country is mandatory to bring social and economic progress. This Phd thesis is a first attempt to develop the LV distribution network with a modern and environmentally friendly way.

ij ij Z f j f D f ρ π π - - = ⋅ ⋅ + ⋅ ⋅ ⋅ + +
Where:

( 1)

( ) ( ) ( ) ( ) k ia ia k ia k ib ib ib ic k in ic ic k k k ia ib ic S V I S I V I I S V I I I - - -                             =                             - + +  
Where , ,

                  = +                   ∑ Where , , , and
ia ib ic in

Iline Iline Iline

Iline the current flow in line section and M is the set of line sections connected downstream to bus j.

V V Z Z Z Z Iline V V Z Z Z Z Iline V V Z Z Z Z Iline V V Z Z Z Z Iline                         = - ×                           • Convergence Criterion
The forward and backward sweep process is continued until the difference between the computed and specified voltage at the source is less than a specified tolerance.

Appendix II-C: Impedances matrix of cable

The impedance 4x4 matrix of cable type LV-ABC-4cores of 240mm problèmes principaux de cette thèse sont la recherche de l'architecture optimale et de l'impact de l'intégration de PV-BES au réseau de distribution basse tension sur l'horizon de planification. Ces problèmes seront pris en compte dans les trois chapitres suivants.

Planification du réseau de distribution basse tension sous incertitude des charges

Les réseaux de distribution basse tension (BT) sont renforcés et expansés dans dernières principale avec les temps de fonctionnement autonome de 70 % et 37 % de la réduction maximale de capacité du transformateur MT/BT à la fin de l'horizon de planification.

Perspectives

Malgré notre objectif de fournir la méthode de planification de réseau de distribution Mots clés: Méthode de Monte Carlo, optimisation, planification, photovoltaïque, réseau de distribution basse tension, stockage, théorie de graphe

Abstract:

The energy consumption increases year by year due to the growth of the population and the economic conditions. In this context, the Cambodian government promotes and encourages the development of the electrification through several policies; all the villages must be electrified by 2020 and at least 70 % of the households will be connected to the network by 2030. Besides, lots of non-electrified homes are equipped with solar panels so as to have access to the electricity. Then, the objective of this thesis is to develop planning tools of the low voltage distribution network to contribute to the electrification of the country. The first part of this thesis focusses on the development of architecture's optimization methods to minimize the capital expenditure (CAPEX) and operational expenditure (OPEX) while respecting both topological and electrical constraints (current and voltage) and integrating the uncertainties on the future development of the low voltage customers. The second part of the thesis proposes a new planning solution so as to integrate the current and future solar productions on the low voltage network. This solution consists in adding centralized storage (in urban and rural areas) and decentralized storage (in rural areas). The main advantages would be first to reduce the consumption peak of the medium voltage /low voltage transformer and consequently to reduce the medium voltage investments but also to size low voltage "microgrids" which can be autonomous a big part of the year. A technical and economic comparison with the classic solution of reinforcement allows estimating the interest of this new solution.

Fête

  des lumières 2014 in Lyon city. Special acknowledgement for Dr. Egor Gladkikh and Dr. Alexander MC for giving me the algorithm of MIQCP and Reorder number; it was part of this thesis. You asked me what was my problem and objective, and then you developed it for me in one week. You are very nice to me. I am especially indebted to Bong Nimol KHIM, Victor and Geoffrey for their encouragement and help for administration process of doctoral school; soutenance de thèse. I would also like to thank all PhD Students from the laboratory: Ahmed, Kevin, Hadi, Vannak VAI, Grenoble INP / G2Elab Page viii III.4.4.2.3 CeBES integration .......................................................................... III.4.4.3 Comparison between grid reinforcement and PV-BES integration ...... III.5 Conclusion ......................................................................................................... References ...................................................................................................................... Chapter IV: Planning the LV distribution system with photovoltaic and battery energy storage -case studies ........................................................................................... IV.1 Introduction ........................................................................................................

2 . 2

 22 Sizing of CeBES ................................................................................... IV.3 Test systems ....................................................................................................... IV.3.1 In urban area ................................................................................................ IV.3.1.1 Site study .............................................................................................. IV.3.1.2 Simulation results and discussion ......................................................... IV.3.1.2.1 Topology ........................................................................................ IV.3.1.2.2 PV penetration ................................................................................ IV.3.1.2.3 Sizing of CeBES ............................................................................ IV.3.1.2.4 Comparison between SP-FFBP and MIQCP ............................... IV.3.2 In rural area ................................................................................................ IV.3.2.1 Site study ............................................................................................ IV.3.2.2 Simulation results and discussion ....................................................... IV.3.2.2.1 Optimal topology ......................................................................... IV.3.2.2.2 PV penetration .............................................................................. IV.3.2.2.3 Location and Sizing of DeBES .................................................... IV.3.2.2.4 Sizing of CeBES .......................................................................... IV.3.2.2.5 Impact of uncertainty on the load profile ..................................... IV.4 Conclusion .......................................................................................................

Figure I- 1 :

 1 Figure I-1 : Cambodia map ................................................................................................. Figure I-2 : Governance of the electricity sector in Cambodia [KOSA12] .......................... Figure I-3 : Proportion of energy sent out by licenses at the end of 2015 (%) ................... Figure I-4 : Proportion of energy sent out by types of generation at the end of 2015 (%) .Figure I-5 : Percentage of productions by Cambodia and necessary imports at end of 2015 (%)............................................................................................................................... Figure I-6 : Energy available and sold between 2002 to 2015 ......................................... Figure I-7 : Number of consumers between 2002 to 2015[EAC12][EAC16] .................... Figure I-8 : Map of the MV distribution system at the end of 2015 [EAC16] .................. Figure I-9 : Percentage of energy input of MV grid at the end of 2015 [EAC16] ............. Figure I-10 : Simple architecture of low-voltage distribution with a single phase main line in rural area ................................................................................................................. Figure I-11 : Simple architecture of low-voltage distribution with a three-phase main line in rural area ........................................................................................................................ Figure I-12 : Simple architecture of low-voltage distribution in urban area .................... Figure I-13 : Monthly average daylight in Phnom Penh, Cambodia [CLIM17] ................ Figure I-14 : Monthly average and highest solar radiation ............................................... Figure I-15 : Annual average solar irradiation [JICA06] ...................................................

Figure I- 5 :

 5 Figure I-1 : Cambodia map ................................................................................................. Figure I-2 : Governance of the electricity sector in Cambodia [KOSA12] .......................... Figure I-3 : Proportion of energy sent out by licenses at the end of 2015 (%) ................... Figure I-4 : Proportion of energy sent out by types of generation at the end of 2015 (%) .Figure I-5 : Percentage of productions by Cambodia and necessary imports at end of 2015 (%)............................................................................................................................... Figure I-6 : Energy available and sold between 2002 to 2015 ......................................... Figure I-7 : Number of consumers between 2002 to 2015[EAC12][EAC16] .................... Figure I-8 : Map of the MV distribution system at the end of 2015 [EAC16] .................. Figure I-9 : Percentage of energy input of MV grid at the end of 2015 [EAC16] ............. Figure I-10 : Simple architecture of low-voltage distribution with a single phase main line in rural area ................................................................................................................. Figure I-11 : Simple architecture of low-voltage distribution with a three-phase main line in rural area ........................................................................................................................ Figure I-12 : Simple architecture of low-voltage distribution in urban area .................... Figure I-13 : Monthly average daylight in Phnom Penh, Cambodia [CLIM17] ................ Figure I-14 : Monthly average and highest solar radiation ............................................... Figure I-15 : Annual average solar irradiation [JICA06] ...................................................

Figure II- 1 :

 1 Figure II-1 : Example of low voltage distribution system in urban areas ......................... Figure II-2 : Model of a three phase four-wire line[TENG03] ........................................... Figure II-3 : Uncertainty on load demand of case study 1 ................................................ Figure II-4 : Uncertainty on load demand of case study 2 ................................................ Figure II-5 : Uncertainty on load demand of case study 3 ................................................ Figure II-6 : Flowchart of proposed method ..................................................................... Figure II-7 : Example of a graph representation of a distribution system ........................ Figure II-8 : Pseudocode algorithm of the SP (left) and the FFBP (right) algorithms ..... Figure II-9 : Strategy 1-upgrades year by year ................................................................. Figure II-10 : Strategy 2-upgrades at initial year .............................................................. Figure II-11 : LV Test system representing an urban area ............................................... Figure II-12 : LV-ABC-4Cores Cable .............................................................................. Figure II-13 : Available paths of the distribution system with Delaunay Triangulation .. Figure II-14 : Optimal topology of case 1: 1 st strategy (left) and 2 nd strategy (right) ....... Figure II-15 : Optimal topology (N1-MC) of case 2: 1 st strategy (left) and 2 nd strategy (right) ................................................................................................................................. Figure II-16 : Optimal topology (N1-MC) of case 3: 1 st strategy (left) and 2 nd strategy (right) ................................................................................................................................. Figure II-17 : Histogram of total actualized of case study 1-1 st strategy (left) and 2 nd strategy (right) .................................................................................................................... Figure II-18 :Histogram of total actualized of case study 2-1 st strategy (left) and 2 nd strategy (right) ....................................................................................................................

Figure II- 19 :

 19 Figure II-19 : Histogram of total actualized of case study 3-1 st strategy (left) 2 nd strategy (right) ................................................................................................................................. Figure II-20 : Evolution of the OPEX, CAPEX and their sum for case study 1 ............. Figure II-21 : Evolution of the OPEX, CAPEX and their sum for case study 2 ............. Figure II-22 : Evolution of the OPEX, CAPEX and their sum for case study 3 ..............

Figure III- 1 :

 1 Figure III-1 : Low-voltage distribution system in Bavel-Battambang-Cambodia [13°18'28.8"N,102°52'54.4"E] ........................................................................................... Figure III-2 : Problem of the extension of electricity coverage area in LV distribution system ................................................................................................................................ Figure III-3 : Flowchart of proposed method ................................................................... Figure III-4 : Concept of grid reinforcement .................................................................... Figure III-5 : Flowchart of sizing of PVs integration ....................................................... Figure III-6 : Flowchart of the minimal discharge and maximal charge of DeBES ......... Figure III-7 : Flowchart of decentralized control of DeBES from 10h00 to 20h00 ......... Figure III-8 : Flowchart of the sizing strategy of the centralized BES ............................. Figure III-9 : Control algorithm of CeBES ....................................................................... Figure III-10 : The test system topology of low voltage distribution in Bavel-Battambang-Cambodia [13°18'28.8"N,102°52'54.4"E]..................................................... Figure III-11 : Case study in rural village ......................................................................... Figure III-12 : LV-ABC-2Cores cable .............................................................................. Figure III-13 : Daily PV(highest-lowest) and load curves in rural area ........................... Figure III-14 : Annual PV curve in Cambodia [VGBA17][NASA17] ................................ Figure III-15 :Voltage profile of different cable sizes (50mm2-70mm2-95mm2) ........... Figure III-16 : Voltage profile with PV integration at 11h00 ........................................... Figure III-17 : Evolution of the best DeBES location (21) and Sizing at 19h00 over 200 generations setting ............................................................................................................. Figure III-18 : The test system of low voltage distribution with PV-BES integration ..... Figure III-19 : Max charging (+) and min discharging (-) of DeBES power .................. Figure III-20 : Voltage profile with/without DeBES at time=19h00 (peak load) ............ Figure III-21 : Operation of DeBES over two days of different solar radiation using the decentralized control .......................................................................................................... Figure III-22 : State of charge of DeBES over two days of different solar radiation ....... Figure III-23 : Minimal voltage profile of the system and voltage at the DeBES node over two days of different solar radiation .......................................................................... Figure III-24 : Active powers at the MV/LV substation and power losses over two days of different solar radiations ................................................................................................ Figure III-25 : Histogram of the annual active power at the MV/LV substation without PV-DeBES-CeBES ............................................................................................................ Figure III-26 : Histogram of the annual active power at the MV/LV substation bus with PVs integration................................................................................................................... Figure III-27 : Histogram of the annual active power at the MV/LV substation with PVs-DeBES integration .............................................................................................................

Figure III- 28 :

 28 Figure III-28 : Histogram of the active power per year at the MV/LV substation with PV-DeBES-CeBES .................................................................................................................. Figure III-29 : Histogram of the annual energy of centralized battery energy storage-CeBES ................................................................................................................................

Figure IV- 1 :

 1 Figure IV-1: Example of a low-voltage distribution grid with integrated PV-BES ......... Figure IV-2 : Flowchart of the planning algorithm in urban area ..................................... Figure IV-3 : A flowchart of proposed method in rural area ............................................ Figure IV-4 : Site study in Phnom Penh [11°32'04.9"N 104°58'06.1"E] ......................... Figure IV-5 : Urban area case study ................................................................................. Figure IV-6 : Optimal topology by SP and FFBP algorithm (Strategy 1) ........................ Figure IV-7 : Optimal topology by MIQCP algorithm (Strategy 2) ................................. Figure IV-8 : Voltage profile for the peak load for year 15 using two different strategy (Strategy 1-left, Strategy 2-right) ....................................................................................... Figure IV-9 : Histogram of the annual active power at the MV/LV substation without PV-CeBES (strategy 1-left, strategy 2-right) for the initial year ...................................... Figure IV-10 : Histogram of the annual active power at the MV/LV substation with PVs integration (strategy 1-left, strategy 2-right) for the initial year ........................................ Figure IV-11 : Histogram of the active power per year at the MV/LV substation with PV-CeBES (strategy -left, strategy 2-right) for the initial year ............................................... Figure IV-12 : Histogram of the annual energy of CeBES (strategy 1-left, strategy 2right) for the initial year ..................................................................................................... Figure IV-13 : Total actualized cost of strategy 1 and strategy 2 over 15 years ............ Figure IV-14 : Site study in Sandek, Batheay, Kampong Cham, Cambodia [12°08'34.5'N 104°57'30.3'E] .................................................................................................................. Figure IV-15 : Radial topology with PV-DeBES-CeBES integration of Sandek village, Batheay, Kampong Cham, Cambodia .............................................................................. Figure IV-16 : Histogram of the voltage of the DeBES of phase A at bus 18 for year 15...................................................................................................................................... Figure IV-17 : Histogram of the voltage of the DeBES of phase B at bus 17 for year 15...................................................................................................................................... Figure IV-18 : Histogram of voltage of the DeBES of phase C at bus 21 for year 15 ... Figure IV-19 : Max charging (+) and min discharging (-) of DeBES-A power at bus 18 at the end of planning........................................................................................................... Figure IV-20 : Max charging (+) and min discharging (-) of DeBES-B power at bus 17 at the end of planning........................................................................................................... Figure IV-21 : Max charging (+) and min discharging (-) of DeBES-C power at bus 21 for year 15 ........................................................................................................................ Figure IV-22 : Voltage profile with/without DeBES at time=19h00 (peak load) at year 15...................................................................................................................................... Figure IV-23 : Operation of the DeBES-A and its State of Charge over two days of different solar radiation by decentralized control at the end of the planning period. ...... Figure IV-24 : Operation of the DeBES-B and its State of Charge over two days of different solar radiation by decentralized control at the end of the planning period. ......

Figure IV- 25 :

 25 Figure IV-25 : Operation of the DeBES-C and its State of Charge over two days of different solar radiation by decentralized control at the end of the planning period. ...... 110 Figure IV-26 : Minimum voltage profile of the system and voltage at the DeBES nodes at the highest solar radiation at the end of the planning period. .......................................... 110 Figure IV-27 : Histogram of the annual active power at the MV/LV substation without PV-DeBES-CeBES .......................................................................................................... 111 Figure IV-28 : Histogram of the annual active power at the MV/LV substation with PVs integration ........................................................................................................................ 111 Figure IV-29 : Histogram of the annual active power at the MV/LV substation with PVs-DeBES integration ........................................................................................................... 112 Figure IV-30 : Histogram of the active power per year at the MV/LV substation with PV-DeBES-CeBES ................................................................................................................ 112 Figure IV-31 : Histogram of the annual energy of centralized battery energy storage-CeBES .............................................................................................................................. 113 Figure IV-32 : Daily load profile uncertainty of each household over 1000 samplings. 116 Figure IV-33 : Daily variation of the minimum voltage for phase-A over 1000 samplings at the end of the planning study. ...................................................................................... 116 Figure IV-34 : Daily variation of the minimum voltage for phase-B over 1000 samplings at the end of the planning study. ...................................................................................... 117 Figure IV-35 : Daily variation of the minimum voltage for phase-C over 1000 samplings at the end of the planning study. ...................................................................................... 117 Figure IV-36 : Histogram of minimum voltage without (left) and with (right) DeBES-A integration over 1000 samplings ...................................................................................... 118 Figure IV-37 : Histogram of the minimum voltage without (left) and with (right) DeBES-B integration over 1000 samplings .................................................................................. 118 Figure IV-38 : Histogram of the minimum voltage without (left) and with (right) DeBES-C integration over 1000 samplings .................................................................................. 118

  known as the Kingdom of Cambodia, is a country located in Southeast Asia as depicted by Figure I-1. It has an area of 181 035 km 2 with a population

  development, Cambodian government has established the policy to promote and encourage the development of electrification [REF17]; all the villages in the Kingdom of Cambodia will have access to electricity of any type by the year 2020 and at least 70 % of all households in the Kingdom of Cambodia will have access to quality electricity grid by the year 2030.

Figure I- 1 :

 1 Figure I-1 : Cambodia map

Figure I- 2 :

 2 Figure I-2 : Governance of the electricity sector in Cambodia [KOSA12]

Figure I- 3 :

 3 Figure I-3 : Proportion of energy sent out by licenses at the end of 2015 (%)

Figure I- 4 :

 4 Figure I-4 : Proportion of energy sent out by types of generation at the end of 2015 (%)

(

  GMS) [ASSO10] nations. The percentage of productions in Cambodia as well as the amount of imports of electricity (total: 6015.36 GWh) are shown in Figure I-5 [EAC16].

Figure I- 5 :

 5 Figure I-5 : Percentage of productions by Cambodia and necessary imports at end of 2015 (%)

  meantime, energy sold has increased by around 880 % from 614.03 GWh in 2002 [EAC12] to 6015.35 GWh in 2015 [EAC16] as shown in Figure I-6. Also, the number of consumers has increased by around 20% in 14 years as given in Figure I-7.

Figure I- 6 :Figure I- 7 :

 67 Figure I-6 : Energy available and sold between 2002 to 2015

3 :

 3 Variation of low voltage in Cambodia [KING04]Supplying of the medium voltage (MV) systemsThe MV distribution system is supplied by either the HV national grid through HV/MV substations or through the 22 kV distribution lines coming from Vietnam grid, Thai grid and Laos grid in the border area or MV isolated networks from the bulk power system. The map of the MV distribution system of Cambodia is depicted in Figure I-8.

Figure I- 8 :

 8 Figure I-8 : Map of the MV distribution system at the end of 2015 [EAC16]

  Figure I-11 illustrate the simple architecture in rural areas with single phase and three phases distribution presently implemented in Cambodia.

  Figure I-12 : Simple architecture of low-voltage distribution in urban area

Figure I- 13 :

 13 Figure I-13 : Monthly average daylight in Phnom Penh, Cambodia [CLIM17]

Figure I- 14 :

 14 Figure I-14 : Monthly average and highest solar radiation

1

 1

II. 3 . 1

 31 Case 1: Evolution of the growth rate of the existing loads .......................... II.3.2 Case 2: Only new connected loads .............................................................. II.3.3 Case 3: Evolution of the growth rate of existing loads and connection of new loads ................................................................................................................... II.4 Proposed method ................................................................................................. II.4.1 Type of areas ................................................................................................ II.4.2 Detailed description of the methodology for planning the urban network .. II.4.3 Mixed Integer Quadratically Constrained Programming-MIQCP[VGBA17] II.4.4 Shortest Path and First Fit Bin Packing (SP-FFBP) .................................... II.4.5 Actualized cost ............................................................................................. II.4.6 Monte-Carlo simulation ............................................................................... II.4.7 Load connection phase and reinforcement .................................................. II.5 Strategy of planning ............................................................................................ II.5.1 Strategy 1: Upgrades year by year ............................................................... II.5.2 Strategy 2: Upgrades at initial year .............................................................. II.6 Test system and simulation ................................................................................. II.6.1 Topology and peak demand ......................................................................... II.6.2 Economic parameters ................................................................................... II.6.3 Electrical parameters of cable ...................................................................... II.6.4 Simulation result and discussion .................................................................. II.7 Conclusion ........................................................................................................... References ......................................................................................................................

II. 2 Figure II- 2 :

 22 Figure II-2 : Model of a three phase four-wire line[START_REF] Teng | A direct approach for distribution system load flow solutions[END_REF]

:

  phase and neutral currents of line.

  : phase current injection (a, b, c), an bn cn V --: phase voltage (a, b, c), a b c S --: phase apparent power (a, b, c), a b c δ --: phase voltage angles (a, b, c), a b c θ --: power factor angles (a, b, c).

lJ

  : current flow in branch l lr I : current injection of node lr lr J ∑ : currents in branches downstream node lr V ∆ : voltage drop of branch l ls V : sending end voltage of branch l lr V : receiving end voltage of branch l l Z : series impedance of branch l Furthermore, more details of four-wire unbalanced load flow are further provided in Appendix II-B.

  positive sequences of voltages of the th i bus , i a b c V --: voltage magnitude of phase a b c -of the th i bus

Figure II- 3 :

 3 Figure II-3 : Uncertainty on load demand of case study 1

Figure II- 4 :Figure II- 5 :II. 4

 454 Figure II-4 : Uncertainty on load demand of case study 2 II.3.3 Case 3: Evolution of the growth rate of existing loads and connection of new loads

  Figure II-6 shows a flowchart of the proposed method to automatically optimize the radial topology in low-voltage distribution system. The different steps of this Monte Carlo [HACR10] based algorithm are:

Start

  Figure II-6 : Flowchart of proposed method

  ij e is a set of edges between vertices i and j representing the lines of the network. Figure II-7 illustrates the topological graph which represents the distribution system.

  Figure II-7 : Example of a graph representation of a distribution system

  power flow and maximal active power flow on line , : reactive power flow and maximal reactive power flow on line , ,

  Figure II-8 shows the pseudocode algorithm and concept of the SP-FFBP algorithms applied to this work. Firstly, the SP algorithm is run to find the closest node to connect the new load and then the firstfit bin packing is used to balance the phases of those new connected loads. : planning period study : bus of existing loads : bus of new and existing loads : closest existing loads from the new loads : distance between two buse fo

Figure II- 8 :

 8 Figure II-8 : Pseudocode algorithm of the SP (left) and the FFBP (right) algorithms

FigureFigureFigure

  Figure II-9 : Strategy 1-upgrades year by year

  Figure II-12 : LV-ABC-4Cores Cable

Figure

  Figure II-13 : Available paths of the distribution system with Delaunay Triangulation II.6.4.2 Optimal radial topology

Figure II- 17 :

 17 Figure II-17 : Histogram of total actualized of case study 1-1 st strategy (left) and 2 nd strategy (right)

Figure

  Figure II-20 : Evolution of the OPEX, CAPEX and their sum for case study 1For case studies 2 and 3, new loads will appear during the planning period. Figure II-21 and Figure II-22 show the evolution of the OPEX, CAPEX and their sum over the planning period of strategy 1 and 2 for case study 2 and case study 3 for one given Monte Carlo iteration. It can be seen that the global cost of strategy 2 is lower than strategy 1 from year

FigureFigure

  Figure II-21 : Evolution of the OPEX, CAPEX and their sum for case study 2

Figure III- 1 :

 1 Figure III-1 : Low-voltage distribution system in Bavel-Battambang-Cambodia [13°18'28.8"N,102°52'54.4"E]

  4.3).

Figure III- 4 Figure III- 4 :

 44 Figure III-4 details the process of grid reinforcement.

Figure III- 5 Figure III- 5 :

 55 Figure III-5 : Flowchart of sizing of PVs integration

P

  Figure III-6 : Flowchart of the minimal discharge and maximal charge of DeBES

Figure III- 8 1

 81 Figure shows the flowchart of the sizing strategy. In other words, the CeBES will be the primary source and the MV grid the secondary source when possible. For each hour of the year, the power of charge and discharge of the battery is computed so as to remove the reverse power flows at the MV/LV substation. Then maximal value between the sum of the power charged and the sum of power discharger during a day gives the SoC of the battery.

Figure

  Figure III-10 : The test system topology of low voltage distribution in Bavel-Battambang-Cambodia [13°18'28.8"N,102°52'54.4"E] Figure III-11 shows the existing LV network and the non-electrified loads which required to be connected to the LV network.

  Figure III-11 : Case study in rural village III.4.2 Impedance of the system

FigureIII. 4 . 3

 43 Figure III-12 : LV-ABC-2Cores cable

Figure III- 13 :

 13 Figure III-13 : Daily PV(highest-lowest) and load curves in rural area

Figure

  Figure III-15 shows the voltage at each node of the test system for several cable sizes used in Cambodia at 19h where the peak load occurs.

Figure III- 16 :III. 4 . 4 . 2 . 2

 164422 Figure III-16 : Voltage profile with PV integration at 11h00 III.4.4.2.2 DeBES integration

FigureFigure

  Figure III-17 : Evolution of the best DeBES location (21) and Sizing at 19h00 over 200 generations setting

Figure

  Figure III-20 : Voltage profile with/without DeBES at time=19h00 (peak load) Furthermore, Figure III-21 and Figure III-22 show the result of the power absorbed or injected by the battery and the state of charge of the DeBES by applying the decentralized control of DeBES described in section III.3.2.2.3 over two days of different solar radiation.It can be seen that the results are identical showing that the low-voltage constraint always appear when the PV production is low. The Vset (0.9042 pu) of the DeBES controller is found from Figure III-20 at bus of 21 (optimal location). In this work, we assumed that a

Figure

  Figure III-21 : Operation of DeBES over two days of different solar radiation using the decentralized control

Figure

  Figure III-23 : Minimal voltage profile of the system and voltage at the DeBES node over two days of different solar radiation Moreover, a daily active power flow at the MV/LV substation over two days is also depicted in Figure III-24; there are some negative values due to the PVs integration and the fact that the DeBES cannot store more energy but they will be removed with the use of the CeBES (more details will be provided in section III.4.4.2.3).

  Figure III-24 : Active powers at the MV/LV substation and power losses over two days of different solar radiations

  Figure III-25 shows the histogram of the annual power at the MV/LV substation without PV-BES integration; the maximal active power at the MV/LV substation is about 32 kW. This maximal value is not reduced by the PVs integration since it happens at 19h00 when PVs are not available; but there are some negative values (reverse power flows) at the MV/LV substation as depicted in Figure III-26. However, this maximum active power has been reduced to 21 kW thanks to DeBES integration as given in Figure III-27.

Figure III- 25 :Figure

 25 Figure III-25 : Histogram of the annual active power at the MV/LV substation without PV-DeBES-CeBES

Figure III- 28 :Figure

 28 Figure III-28 : Histogram of the active power per year at the MV/LV substation with PV-DeBES-CeBES

Figure IV- 1 :

 1 Figure IV-1: Example of a low-voltage distribution grid with integrated PV-BES

  fit bin packing and MIQCP), -Maximization of the DePV penetration, -Optimal sizing of the CeBES A flowchart showing the various steps of the proposed algorithm is shown in Figure IV-2.

Start

  Figure IV-2 : Flowchart of the planning algorithm in urban area

Figure IV- 3

 3 Figure IV-3 presents a flowchart of proposed method for planning in rural area.

Figure IV- 4 :Figure IV- 5 :

 45 Figure IV-4 : Site study in Phnom Penh [11°32'04.9"N 104°58'06.1"E]

Figure IV- 7 :

 7 Figure IV-7 : Optimal topology by MIQCP algorithm (Strategy 2)

Figure IV- 9

 9 Figure IV-9 shows the histogram of the annual power at the MV/LV substation without PV-CeBES integration for each topology for the initial year; the maximum active power at the MV/LV substation is about 206 kW (strategy 1) and 216 kW (strategy 2). This maximum power is not reduced by the PVs integration but there are some reverse power flows (-19.4 kW{strategy 1}/-19.1 kW{ strategy 2}) at the MV/LV substation as depicted in Figure IV-10 since the peak loads happened when the PV production is very low.

Figure IV- 9 :Figure

 9 Figure IV-9 : Histogram of the annual active power at the MV/LV substation without PV-CeBES (strategy 1-left, strategy 2-right) for the initial year 20 40 60 80 100 120 140 160 180 200 220 0

Figure IV- 11 :

 11 Figure IV-11 : Histogram of the active power per year at the MV/LV substation with PV-CeBES (strategy -left, strategy 2-right) for the initial year

Figure IV- 13 :

 13 Figure IV-13 : Total actualized cost of strategy 1 and strategy 2 over 15 years

  Figure IV-15 : Radial topology with PV-DeBES-CeBES integration of Sandek village, Batheay, Kampong Cham, Cambodia

••

  Location of DeBESIn our work, we propose to use only one DeBES per phase which is integrated to the LV distribution system. By applying the algorithm of chapter III, the optimal location of DeBES is shown in Figure IV-15 and is located at buses 18 (Ph-A), 17 (Ph-B) and 21(Ph-C) which corresponds to the minimal power discharged at 19h to prevent from low voltage constraint. The fitness evolution of the applied GA to find the location and sizing of DeBES is shown in Appendix IV-E. Reference voltage Vset This part aims at finding Vset by taking into account an uncertainty of +/-5% on the load profile over the planning study. By applying the Monte-Carlo simulation on Vset searching by considering the loads at the end of the planning period over 1000 samplings, we obtained the histogram of Vset for each DeBES as presented in Figure IV-16 to Figure IV-18.

Figure IV- 16 :Figure

 16 Figure IV-16 : Histogram of the voltage of the DeBES of phase A at bus 18 for year

Figure

  Figure IV-19 : Max charging (+) and min discharging (-) of DeBES-A power at bus 18 at the end of planning

Figure

  Figure IV-21 : Max charging (+) and min discharging (-) of DeBES-C power at bus 21 for year 15 Figure IV-22 shows the voltage profile of the complete feeder at 19h00 (peak demand)with and without PV-DeBES integration. According to that figure, it can be seen that the system does not respect the voltage constraint without DeBES but it has been solved by injection power from DeBES.

  Figure IV-22 : Voltage profile with/without DeBES at time=19h00 (peak load) at year 15 Figure IV-23 to Figure IV-24 show a result of scheduling and state of charge of DeBES by applying the decentralized control of DeBES over two days of different solar radiation.

  Figure IV-21. As illustrated in Figure IV-23 to Figure IV-25, the operation of the DeBES by decentralized control at the highest and lowest solar radiation are the same. Also, this schedule will be repeated in over a year of simulation for each DeBES.

Figure IV- 23 :

 23 Figure IV-23 : Operation of the DeBES-A and its State of Charge over two days of different solar radiation by decentralized control at the end of the planning period.

Figure IV- 24 :

 24 Figure IV-24 : Operation of the DeBES-B and its State of Charge over two days of different solar radiation by decentralized control at the end of the planning period.

  Figure IV-25 : Operation of the DeBES-C and its State of Charge over two days of different solar radiation by decentralized control at the end of the planning period. The minimum voltage profile of the system and the voltage profile at the DeBES nodes are shown in Figure IV-26. According to this figure, we can say that the decentralized controller is running well and no under voltage problems has occurred.

FigureIV. 3 . 2 . 2 . 4

 3224 Figure IV-26 : Minimum voltage profile of the system and voltage at the DeBES nodes at the highest solar radiation at the end of the planning period.IV.3.2.2.4 Sizing of CeBES

Figure IV- 27 :Figure

 27 Figure IV-27 : Histogram of the annual active power at the MV/LV substation without PV-DeBES-CeBES

Figure IV- 30 :Figure

 30 Figure IV-30 : Histogram of the active power per year at the MV/LV substation with PV-DeBES-CeBES

  Figure IV-32 shows several samplings (1000) of load profiles considering an uncertainty of +/-5%. With these load uncertainties, we obtain the variation of the daily minimum voltage of each phase with decentralized control of DeBES as illustrated in Figure IV-33 to Figure IV-35. As seen in these figures, the variation of the minimum voltage happens almost always between 18h00 and 21h00 due to high load consumption but these values are acceptable (Voltage > 0.9 pu).

Figure IV- 32 :

 32 Figure IV-32 : Daily load profile uncertainty of each household over 1000 samplings

Figure

  Figure IV-34 : Daily variation of the minimum voltage for phase-B over 1000 samplings at the end of the planning study.

Figure IV- 35 :Figure

 35 Figure IV-35 : Daily variation of the minimum voltage for phase-C over 1000 samplings at the end of the planning study. Furthermore, Figure IV-36 and Figure IV-38 also present histograms of the minimum voltages over the day which occur in the whole LV network with and without DeBES integration.

iiZ

  : self-impedance of conductor i in / km Ω ij Z : mutual-impedance of conductors i and j in / km Ω i GMR : geometric mean radius of conductor i in m ij D : distance between conductors i and j in m ρ : resistivity of earth in .m Ω f : system frequency in Hz Appendix II-B: Four-wires Unbalanced Load Flow The unbalanced load flow simulation of radial system is carried out through forward/backward load flow program to solve load flow in four-wire unbalanced low-

Appendix

  IV-E: Implementation of GA for location and sizing of DeBES In the implementation of GA, we set 50 individuals, 300 generations, 10e-20 of tolerance constraint (TolCon) and 10e-20 of tolerance penalty fitness (TolFun) as inputs in optimization. As seen in Figure C-1 to Figure C-3, the algorithm is terminated at generation lower than 300 due to the average change in the penalty fitness value less than TolFun and constraint violation is less than TolCon.

Figure IV-E- 1 :Figure 1 : 2 :Figure

 112 Figure IV-E-1: Evolution of the best DeBES-A location (18) and Sizing at 19h00 over 300 generations setting

4 . 5 .

 45 années en raison de l'augmentation de charge ; ces points obligent les distributeurs d'électricité à effectuer la planification suite à ces problèmes. Dans une procédure de planification du réseau de distribution, il est essentiel de chercher l'architecture appropriée afin de satisfaire l'aspectes techno-économique. Les réseaux de distribution basse tension sont le réseau radial presque déséquilibré en raison de diverses charges monophasées et triphasées au réseau. Pour faire face à ces problèmes, l'optimisation du réseau distribution radiale a été développée dans la littérature pour trouver le coût d'investissement le plus bas en utilisant l'algorithme de recherche de chemin[START_REF] Kumar | Optimization of Radial Distribution Networks Using Path Search Algorithm[END_REF] ou l'approche directe Dans ce chapitre, l'architecture radiale optimale et la stratégie de planification ont été réalisées en appliquant le PLMNECQ, le plus court chemin, le first-fit bin-packing, et la simulation de Monte-Carlo dans le logiciel ILOG-CPLEX et MATLAB. En outre, les trois cas sur l'incertitude de charge ont été proposés en tenant compte du taux de croissance et des nouvelles charges connectées au cours de l'étude de planification. La meilleure stratégie de conception est sélectionnée pour chaque cas de problème d'incertitude ; la 1ème stratégies est pour le cas 2 et le cas 3 et la 2 ème stratégie est pour le cas 1. De plus, le diagramme triphasé est affiché automatiquement pour les planificateurs de voir la visualisation de l'architecture optimale. Cette méthode proposée est donc efficace et utile pour les distributeurs d'électricité pour dessiner les réseaux de distribution basse tension. Pour accomplir la planification du réseau de distribution basse tension, la planification composée de sources d'énergie renouvelables (RES), de stockage centralisé et décentralisé (CeBES-DeBES) sera étudiés dans les chapitres prochains. Intégration de photovoltaïque en utilisant le stockage sur le réseau de distribution basse tension La consommation d'énergie augmente d'année en année en raison de la croissance de la population et des conditions économiques dans les pays en voie de développement. Actuellement, environ 80 % de la population vivent dans les zones rurales et 75 % des ménages vivent sans l'électricité [PHOK16]. Afin de répondre aux besoins de la population et de la société en termes d'électrification, les distributeurs d'électricité trouvent une solution possible pour leurs consommateurs. Une solution possible a attiré l'intérêt des distributeurs d'électricité afin d'augmenter la couverture de l'électricité sont le renforcement/expansion de réseau et l'intégration de la production locale. En outre, les réseaux de distribution basse tension pour une faible densité de population dans les zones rurales sont caractérisés par une ligne principale monophasée, une faible densité de charge électrique et une utilisation fréquente des lignes aériennes. Dans ce chapitre, nous étudierons un renforcement du réseau et l'intégration de PV-BES au réseau de distribution basse tension. L'objectif principale de ce chapitre est de proposer deux solutions différentes basées sur le renforcement et l'utilisation du PV-BES pour l'extension du réseau existant aux zones non-électrifiées. Ce travail vise à dimensionner la capacité de câble, le PV-BES décentralisé et le BES centralisé intégrés au réseau de distribution basse tension. Ce chapitre a été divisé en trois partie principales afin d'obtenir la solution. Tout d'abord, nous décrivons l'impact général de l'intégration de PV-BES aux réseaux de distribution basse tension. Ensuite, la méthode proposée et les algorithmes développés sont présentés pour accomplir l'objectif de travail (sous tension et flux de puissance inversé). Les résultats de simulation du réseau de distribution basse tension testé sont fournis à la dernière partie. L'impact des photovoltaïques et stockages intégré au réseau de distribution basse tension aérienne avec la ligne principale monophasé a été présenté dans ce chapitre. La comparaison entre le renforcement du réseau et l'intégration de PV-BES a également été fournie. Le dimensionnement du PV décentralisé (DePV) est déterminé en utilisant la technique itérative en considérant les contraintes de tension et de courant. En outre, l'emplacement optimal et le dimensionnement du BES décentralisé (DeBES) ont été soulignés par l'algorithme génétique (GA) et la technique itérative afin de résoudre le problème de sous tension du réseau. Par ailleurs, l'opération de DeBES a été réalisé avec l'algorithme de contrôle décentralisé. De même, la stratégie de dimensionnement du BES centralisé (CeBES) a été développée pour déterminer la capacité de CeBES afin d'éviter le flux de puissance inversé à poste source. De plus, la méthode proposée sera utile pour les distributeurs d'électricité qu'envisagent de faire l'extension de couverture d'électricité par le renforcement du réseau et l'intégration de PV-BES. Planification du réseau de distribution basse tension avec photovoltaïque et stockage -études de cas Dans les deux chapitres précédents, nous avons présenté le réseau de distribution basse tension sous l'incertitude de charge en recherchant l'architecture optimale avec la stratégie de conception et l'intégration de PV-BES en zone rurale avec la ligne principale monophasée. Cependant, ces deux chapitres ne tiennent pas compte de l'intégration de PV-BES (Chapitre II) et de l'incertitude sur le profil de charge avec la ligne principale triphasée (Chapitre III). La méthode proposée porte sur la planification du réseau de distribution basse tension résidentielle dans les zones rurales et urbaines par l'algorithme d'architecture optimale et l'intégration de PV-BES avec la ligne principale triphasée. La méthode proposée est décrite dans la première partie. Ensuite, les résultats de simulation du réseau de distribution résidentielle testée sont fournis. La conclusion est également fournie dans la dernière section du chapitre. Ce chapitre a présenté la planification du réseau de distribution basse tension résidentielle avec l'intégration de DePV, DeBES et CeBES dans les zones rurales et urbaines du Cambodge, en particulier pour les zones non-électrifiées. L'algorithme d'architecture radiale optimale a été développé en utilisant le PLMNECQ, le plus court chemin et le first-fit bin-packing afin de dessiner l'architecture en minimisant l'utilisation des conducteurs et en améliorant l'équilibrage de charge. Par ailleurs, l'algorithme du dimensionnement de DePV a été développé comme la technique itérative sous les contraintes de tension et de courant du réseau électrique. L'emplacement et le dimensionnement de DeBES ont également été réalisés en utilisant l'algorithme génétique et la technique itérative afin de résoudre le problème de sous tension. En outre, la stratégie de dimensionnement de CeBES a été établie pour éviter le flux de puissance inversé du réseau de distribution BT vers le réseau de distribution MT et aussi pour augmenter le temps de fonctionnement autonome. De même, le contrôle décentralisé de DeBES a été développé sans utiliser les technologies de l'information et de la communication (TIC). L'impact de la référence de tension a été étudiée par la méthode de simulation de Monte-Carlo sous l'incertitude du profile de charge au cours de l'horizon de planification sans la zone rurale. De plus, la méthode proposée fournit des conseils et des concepts à ceux qui sont au début du dessin du réseau de distribution basse tension résidentielle. Les objectifs de cette thèse ont été portes sur le développement à long terme de la planification des réseaux de distribution basse tension avec intégration de générations distribuées à petite échelle (photovoltaïques et stockage d'énergie de la batterie) pour défier les problèmes actuels au Cambodge. Les deux contributions principales de ce travail sont de rechercher d'abord l'architecture optimale du réseau de distribution basse tension et dimensionner les générations distribuées intégrées au réseau électrique. Les travaux présentés dans cette thèse peuvent être résumés comme suit : Le chapitre I a fourni la situation actuelle du réseau du Cambodge. Il a fourni les informations nécessaires pour les chercheurs qui s'intéressent aux problèmes actuels du secteur de l'électricité au Cambodge ou les pays en voie de développement ayant des règles similaires. Le chapitre II a développé le nouvel algorithme afin d'obtenir l'architecture optimale pour la conception du réseau de distribution basse tension en zone urbaine en tenant compte de l'incertitude de charges électriques sur l'horizon de planification (i.e. taux de croissance et nouvelles charges connectées). La conclusion principale de ce chapitre est de montrer que les deux stratégies différentes peuvent être appliquées en concernant le scenario d'incertitude de charges électriques. En cas d'évolution du taux de croissance de charges existantes seulement, la meilleure stratégie est de construire le réseau a l'année initiale en tenant compte de charges prévues à la fin d'année de planification en utilisant l'algorithme PLMNECQ. Si les nouvelles charges apparaissent lors de l'étude de planification, la meilleure approche est basée sur le principe de renforcement (câbles) et construction du réseau d'année en année en utilisant les algorithmes de plus court chemin et first-fit bin packing. Le chapitre III a proposé les deux solutions possibles afin d'augmenter le couverture d'électricité pour le village rural pour résoudre le problème de sous tension en bout de ligne de réseau de distribution basse tension. Ces deux solutions possibles sont le renforcement de réseau et l'intégration de sources PV-stockage. Avec cette deuxième solution, les distributeurs d'électricité n'ont pas besoin de renforcer les lignes, mais ils doivent acheter des PV-stockages et des câbles d'extension pour les nouveaux consommateurs. La puissance installée maximale de PV a été calculée en fonction des contraintes de tension et de courant. De plus, la charge maximale (peak load) a été réduite grâce au stockage d'énergie de la batterie connecté au réseau. En raison de l'intégration de PV au réseau, l'opération autonome du réseau de distribution basse tension est également assurée ; cela signifie que les consommateurs seront soutenus par des générations locales (PV-BES). Ce chapitre a ainsi démontré que la générations locale d'énergie renouvelables à petite échelle et le stockage d'énergie de la batterie étaient utiles pour le secteur de l'électricité au Cambodge. Le chapitre IV a concentré sur la planification du réseau de distribution résidentielle basse tension en particulier pour les zones non-électrifiées, en recherchant l'architecture optimale automatiquement et en dimensionnant de sources PV-BES au réseau sur l'horizon de planification. En zone urbaine, les deux algorithmes développés au chapitre II pour l'architecture optimale ont été utilisés. La première partie est basée sur la plus court chemin et le first-fit bin packing, et trouve l'architecture qui minimise la longueur totale et améliore l'équilibrage de charge. Cet algorithme réduit les pertes mais il augment l'utilisation du câble. La deuxième partie est l'algorithme PLMNECQ qui tente de minimiser l'utilisation du câble et d'améliorer l'équilibrage de charge. En conséquence, les pertes de l'architecture proposée pour cet algorithme sont supérieures à celles obtenues avec la première solution proposée. Une fois les architectures obtenues, l'intégration de PV-BES est considérée. La comparaison de techno-économique est faite entre les deux architectures optimales, y compris l'intégration de PV-BES en tenant compte du coût actualisé. Les deux résultats suivant ont été fournis : 1-le premier algorithme est meilleur que le deuxième. 2-le cas de l'intégration de PV-BES est plus économique que le cas sans l'intégration de PV-BES pour les deux architectures. La même étude est menée pour le réseau de distribution résidentielle basse tension en zone rurale. Dans ce cas, le plus court chemin et le first-fit bin-packing ont été appliqués afin d'obtenir l'architecture optimale avec l'équilibrage de charge. La puissance installée maximale de PV qui peut être intégrée au réseau a été déterminé en fonction des contraintes de tension et de courant. L'emplacement et le dimensionnement du BES centralisé et décentralisé ont été effectués afin de résoudre le problème de sous tension et de diminuer le dimensionnement du transformateur MT/BT. L'autre contribution de ce chapitre est le contrôle proposé du BES sans utiliser les technologies de l'information et de la communication (TIC). L'algorithme a été développé en tenant compte de l'hypothèse d'incertitude du profil de charge sur l'horizon de planification. Ce chapitre a conclu que le réseau de distribution basse tension triphasée en tant que la ligne principale avec l'équilibrage de charge et l'intégration de PV-BES est la solution possible que le gouvernement cambodgien et les distributeurs d'électricité devraient considérer. En outre, avec cet algorithme développé, le réseau de distribution basse tension peut être joué le rôle de réseau-micro isolée indépendant du réseau de distribution moyenne tension (MT)

  avec intégration de sources photovoltaïques et stockage-cas du réseau du Cambodge, il est évident que de nombreuses perspectives peuvent êtres recommandés dans ces travaux.Dans cette recherche, le coût d'investissement ne tient compte que le prix de l'équipement pour évaluer le coût actualise de l'architecture différente du réseau de distribution basse tension. Il faut tenir compte des coûts de construction et de maintenance pour chaque équipement afin de fournir la conclusion générale sur la conception du réseau de distribution basse tension. De plus, le type de source PV seulement comme l'énergie renouvelable est considéré pour l'étude primaire dans cette thèse, donc d'autres types de sources renouvelables à petite échelle devraient être étudiés comme la biomasse et le pico-Vannak VAI, Grenoble INP / G2Elab Page 154 hydroélectrique, qui sont abondantes dans certaines régions du Cambodge. De même, le type de stockage d'énergie de la batterie n'est pas considéré dans ce travail puisque cette thèse était portée sur l'optimisation du dimensionnement. Par conséquent, la comparaison entre différents stockages devrait être prise en compte afin de sélectionner l'un d'entre eux pour une application réelle. Par ailleurs, ce travail n'a étudié que la planification du réseau de distribution basse tension. La nouvelle méthode et l'algorithme devraient être modifiés afin d'appliquer pour les problèmes actuels au réseau de distribution moyenne tension dans l'autres études telles que l'emplacement et le dimensionnement optimal de générations distribuées multiples. Le denier point consiste à tester plus d'études de cas avec l'algorithme présenté et à développer un modèle d'incertitude précisé pour tacler à un comportement intermittent de charge et de génération distribuée afin de fournir une conclusion générale, en particulier pour les pays en voie de développement. G2Elab -Laboratoire de Génie Electrique de Grenoble (UMR 5269 CNRS / Grenoble INP / UGA) Bâtiment GreEn-ER, 21 avenue des martyrs CS 90624, 38031 Grenoble Résumé: La consommation d'énergie augmente d'année en année en raison de la croissance de la population et des conditions économiques. Dans ce contexte, le gouvernement Cambodgien a mis en place une politique de promotion et d'encouragement du développement de l'électrification ; tous les villages devront être électrifiés d'ici 2020 et au moins 70% des domiciles auront accès au réseau électrique d'ici 2030. Par ailleurs, de nombreux foyers non électrifiés sont équipés de panneaux solaires afin d'avoir accès à l'électricité. L'objectif de cette thèse est donc de développer des outils de planification du réseau de distribution basse tension afin de contribuer à l'électrification du pays. La première partie de cette thèse se concentre sur le développement d'outils d'optimisation de l'architecture afin de minimiser le coût d'investissement (CAPEX) et d'exploitation (OPEX) qui respecte l'ensemble des contraintes topologies et électriques (courant et tension) tout en intégrant les incertitudes liées au développement des consommateurs basse tension. La deuxième partie de la thèse propose une nouvelle solution de planification afin d'intégrer les productions solaires présentes et à venir sur le réseau basse tension. Cette solution consiste à ajouter du stockage centralisé (en milieu urbain et rural) et du stockage décentralisé (en milieu rural). Les principaux avantages seraient d'une part de réduire le pic de consommation du transformateur moyenne tension/basse tension et donc de réduire les investissements moyenne tension mais également le dimensionnement de « microgrids » basse tension pouvant être autonomes une grande partie de l'année. Une comparaison technico-économique avec la solution classique de renforcement permet d'évaluer l'intérêt de cette nouvelle solution.

  IV.2 Methodology ...................................................................................................... IV.2.1 LV urban network planning ......................................................................... IV.2.1.1 Actualized cost .....................................................................................

IV.2.1.2 Sizing of PVs ........................................................................................ IV.2.1.3 Sizing of CeBES ................................................................................... IV.2.2 LV rural network planning ........................................................................... IV.2.2.1 Location, sizing and control of the DeBES .......................................... IV.2.2.1.1 Integration of the uncertainties on load .......................................... IV.2.

Table I -

 I 1 : Data of the electricity sector at a glance in Cambodia [EAC16] ..................... Table I-2 : Voltage levels in Cambodia [KING04] ............................................................ Table I-3 : Variation of low voltage in Cambodia [KING04] ............................................ Table I-4 : Information of province for MV isolated system at the end of 2015 .............. Table I-5 : The permissible of the conductors used in this thesis ..................................... Table II-1 : Existing load specification at the initial year ................................................. Table II-2 : New connected loads ..................................................................................... Table II-3 : Parameters of the economic analysis [VGBA17] ............................................ Table II-4 : Average actualized cost of each case ............................................................. Table III-1 : Minimal voltage and maximal current with several cable sizes. ..................

	PV		: Photovoltaic
						max
		ij	CAPEX , ij	: Capital Expenditure
	CeBES RES	: Centralized Battery Energy Storage : Renewable Energy Source
	invest C RGC	() t	: Investment cost at the year t : Royal Government of Cambodia
	SAIDI	: System Average Interruption Duration Index
					total act C 	: Total actualized cost over planning study
	SAIFI	: System Average Interruption Frequency Index
					DeBES	: Decentralized Battery Energy Storage
	SoCmin,SoCmax : Minimum and maximum of Stage of Charge of battery
	d SHS	ij	: Distance between two buses and ij : Solar Home System
	SP		EAC	: Electricity Authority of Cambodia : Shortest Path
	EDC TolCon	: Electricité du Cambodge : Constraint Tolerance
	ENS TolFun	: Energy Non-Supplied : Function Tolerance
	FFBP VUF	: First-Fit Bin-Packing : Voltage Unbalance Factor
	V 	n	GA	: Genetic Algorithm : Phase voltage, A, B or C  
	,, i neg pos V	: Negative and positive sequences of voltages of the	i	th	bus
	lr V		HV ICT	: High Voltage : Information Communication Technology : Receiving end voltage of branch
	ls V		IPP	: Independent Power Producer : Sending end voltage of branch
	set V	, bus neutral I 	: Phase and neutral currents injected in the bus, : Voltage reference of DeBES	 	A, B or C
	, line neutral I  _ ph ij x x  , ij	: Phase and neutral currents of line, : State of connection between two buses and A, B or C   ij , A, B or C  
					_ i load ph 	: Phase connection of load i ,	 	A, B or C
					LV	: Low Voltage : Power factor angles,	 	A, B or C
				MCS	: Monte-Carlo Simulation : Phase voltage angles, A, B or C  
		MIME MIQCP () in i	: Ministry of Industry, Mines and Energy : Mixed Integer Quadratically Constrained Programming : Set of incoming edge for th i vertex
	MV i    ij 	j	: Medium Voltage : Voltage angle between the bus i and j
	V 		NASA	: National Aeronautics and Space Administration : Voltage drop of branch
					OPEX	: Operational Expenditure
					t k Pbes	: Power injection of battery for th i bus at time t
					() Ploss t	: Power loss at the year t
						,

Table III-2 : Simulation results of PV-BES integration .................................................... Table III-3 : Parameters for the economic analysis [VGBA17] ......................................... Table III-4 : CAPEX of the two strategies ........................................................................ Table IV-1 : Simulation of PV Penetration in urban area ................................................. Table IV-2 : Summary

of simulation results for the initial year in the urban area ......... Table IV-3 : Summary of simulation results for the end of the planning year in the urban area ................................................................................................................................... Table IV-4 : Initial cost without PV-BES integration of the proposed algorithms ........ Table IV-5 : Initial cost with PV-BES integration of the proposed algorithms .............. Table IV-6 : Simulation of PV penetration in rural area ................................................ Table IV-7 : Summary of simulation results for the initial year in rural area ................ Table IV-8 : Minimal voltage and maximal current for two types of cable reinforcement. .......................................................................................................................................... Table IV-9 : CAPEX of the grid-reinforcement and PV-BES integration .....................

List of Principal Symbols and Abbreviations

ij B : Susceptance between the bus i and j ij G : Conductance between the bus i and j ii pq : Active and reactive power of load i max , ij ij Pp : Active power flow and maximal active power flow on line ij Qq : Reactive power flow and maximal reactive power flow on line ij ij Z : Impedance of the conductor between two buses and ij  

Table I

 I

	Table I-1 : Data of the electricity sector at a glance in Cambodia [EAC16]
	Description	Unit	2014	2015	%Change
	Electricity generated	GWh	3058.36	4489.27	46.79
	Electricity imported from Thailand	GWh	523.56	307.39	-41.29
	Electricity imported from Vietnam	GWh	1256.72	1200.39	-5.16
	Electricity imported from Laos	GWh	13.77	18.31	32.96
	Thailand import 5.11% Total electricity import	GWh	Laos import 0.30% 1803.05	1526.08	-15.36
	Vietnam import Total electricity available	GWh	4861.41	6015.35	23.74
	19.96% Installed Generating Capacity	MW	1511.338	1657.274	9.66
	Number of consumers	#	1424735	1859204	30.49
	Electricity sold to consumers	GWh	4144.12	5205.34	25.61
	Average losses	%	Country production 14.75 13.47	-8.68
			74.63%
					-1. As it
	can be noticed, the energy import from neighboring countries has been decreased by 15%
	due to the increase of the country production.
	Vannak VAI, Grenoble INP / G2Elab				Page 10

Table I -2 : Voltage levels in Cambodia [KING04] Classification of voltage Range of nominal voltage Nominal voltage Highest voltage

 I

				The phase
	and line voltages are usually 230/400 V. Moreover, the length of distribution systems, both
	medium and low voltage, is approximately 7145 km with about 3282 MV/LV substations
	[EAC15]. In addition, the voltage standards in the kingdom of Cambodia are illustrated in
	the following table:
	High Voltage (HV)	U > 35 kV	230 kV 115 kV	245 kV 123 kV
	Medium Voltage (MV) 600 < U ≤ 35 kV	22 kV	24 kV
	Low Voltage (LV)	U ≤ 600 V	230 / 400 V
	Moreover, low voltage at the supply point shall be maintained between -10 and + 6%
	of the nominal value as shown in Table I-3. Also, the rating frequency in Cambodia is 50

MV grid connected from neighboring countries • MV grid connected to the Vietnam system Cambodia imports electricity from Vietnam through 22 kV connections at 18 locations in the provinces of Kampong Cham, Svay Rieng, Kampot, Mondulkiri, Kandal, Takeo, Kratie, Prey Veng and Ratanakiri. The supply is then extended to other licensees. By the

	MV from Vietnam	MV from Thailand	MV from Laos
	6.670%	2.807%	0.309%	Isolated MV
				0.196%
		National grid
			90.018%
	end of 2015, 46 licensees got supply from the Vietnam grid.
	• MV grid connected to the Thailand system
	Cambodia imports electricity from Thailand through 22 kV connections at 8 locations
	in the provinces of Battambang, Pailin, Banteay Meanchey, Koh Kong and Oddor
	Meanchey. The supply is extended to other licensees. By the end of 2015, 8 licensees got
	supply from the Thai grid.
	• MV grid connected to the Laos system
	EDC imports power from Laos to supply to city of Steung Treng and some areas of
	Preah Vihear. By the end of 2015, 9 licensees got supply from the Lao grid.

It is the case in Phnom Penh and the provinces of Kandal, Kampong Speu, Takeo, Kampot, Sihanoukville, Kampong Cham, Kampong Thom, Prey Veng, Banteay Meanchey, Battambang, Siem Reap, Pursat and Kampong Chhanang [EAC16].

Table I

 I

	-4.
	Table I-4 : Information of province for MV isolated system at the end of 2015

Name of Province Number of Licensees Number of consumer s Installed Capacit y (kW) Energy generated (MWh) Energy Sold to consumers (MWh)

	Kampong Cham	3	2447	1272	432.24	384.97
	Kampong Chhnang	2	783	206	155.04	129.54
	Kampong Thom	5	3833	1959	1228.01	1015.28
	Koh Kong	2	762	760	481.34	426.46
	Kratie	4	2298	896	951.05	834.20
	Oddor Meanchay	2	1941	2372	612.52	529.96
	Preah Vihear	6	6111	6218	6025.66	4862.76
	Pursat	1	821	847	636.65	584.86
	Ratanakiri	1	349	220	274.20	253.43
	Siem Reap	3	1832	640	893.09	750.72
	Stueng Treng	1	443	425	103.20	87.60
	Total	30	21620	15815	11793.00	9859.78

Table I -5 : The permissible of the conductors used in this thesis Items Section of conductors (mm 2 ) 4[CHSO15] 50 70 95 150 240[CHSO15]

 I

	Resistance ( / km Ω	)	4.95	0.641 0.443	0.32	0.206	0.125
	Maximum permissible intensity (A)	32	150	185	225	285	432

  REF17] REF, "Transferring the Benefits Resulting from the Development of Electricity to Introduction ......................................................................................................... II.2 Distribution system modeling and power flow ................................................... II.2.1 Low Voltage system modeling ....................................................................

	the Chapter II Population	in	Rural	Area,"	2017.	[Online].	Available:
	Planning of low-voltage distribution system
	with uncertainty on load demand
						Chapter II
	Planning of Low-Voltage Distribution
	System with Uncertainty on Load
						Demand

http://ref.gov.kh/page/products/category/42-Publications. Chapt e r II: Planning of low-voltage distributio n s ystem w it h unc e r t aint y on loa d de ma nd Summary Chapter II: Planning of low-voltage distribution system with uncertainty on load demand ............................................................................................................................................ II.1 II.2.2 Power Flow Analysis ................................................................................... II.3 Uncertainty on load demand ...............................................................................

  )

			total act C	=	P = ∑ t	invest C	t t C Ploss t i + × +	(II-21)
	Where:
	-	_ total act C	: total actualized cost in kUSD
	-	( )

invest C t : investment cost in the year t in kUSD -C : cost of 1 kW peak losses in / kUSD kW -( ) Ploss t : power losses at the year t in kUSD -i : actualization rate in %

Table II -

 II 1 : Existing load specification at the initial year

	No. Bus	Peak active and reactive power P	No. Bus	Peak active and reactive power	No. Bus	Peak active and reactive power

(kW) Q(kvar) P(kW) Q(kvar) P(kW) Q(kvar)

  The actualized cost is computed to make an investment decision. The total time study for the analysis is set to 15 years and the actualization rate is 12 %[VGBA17]. The list of the parameters for the economic analysis is shown in Table

	Table II-2 : New connected loads
	Coordinates	Peak real and reactive power	Coordinates	Peak real and reactive power
	X	Y	P(kW) Q(kvar)	X	Y	P(kW) Q(kvar)
	480	390	4	1.31	510	360	2		0.66
	510	390	3	0.99	540	360	3		0.99
	540	390	4	1.31	570	360	4		1.31
	570	390	10	3.29	600	360	6		1.97
	600	390	4	1.31	630	360	10		3.29
	630	390	4	1.31	660	330	3		0.99
	660	390	10	3.29	600	330	4		1.31
	480	360	3	0.99
	II.6.2 Economic parameters
		Parameters				Value
		Planning period study			15 years
		Discount rate				12 %
	Annual peak power losses cost		1.58 kUSD/kW
		50 mm² cable cost			0.8 kUSD/km
		70 mm² cable cost			1 kUSD/km
		95 mm² cable cost			1.5 kUSD/km
		150 mm² cable cost			2 kUSD/km
		240 mm² cable cost
	1	0	0	12	3	0.99	23	3	0.99
	2	4	1.31	13	3	0.99	24	6	1.97
	3	10	3.29	14	6	1.97	25	4	1.31
	4	6	1.97	15	3	0.99	26	3	0.99
	5	3	0.99	16	3	0.99	27	3	0.99
	6	3	0.99	17	3	0.99	28	3	0.99
	7	6	1.97	18	4	1.31	29	4	1.31
	8	6	1.97	19	4	1.31	30	6	1.97
	9	3	0.99	20	6	1.97	31	10	3.29
	10	10	3.29	21	6	1.97	32	4	1.31
	11	3	0.99	22	3	0.99	33	3	0.99

Table II-3 : Parameters of the economic analysis

[VGBA17]

  Table II-4 lists the summary results of the average actualized costs of each case study.

	Table II-4 : Average actualized cost of each case
			Case study
	Strategy	Case study 1	Case study 2	Case study 3
	1 st strategy (S1)	146 kUSD	150 kUSD	183 kUSD
	2 nd strategy (S2)	93 kUSD	170 kUSD	195 kUSD
	Difference between S2 and S1	+36.30 %	-13.33 %	-6.55 %
	Chosen strategy	S2	S1	S1

Table III -

 III

		6000
		5000
		4000
	Frequency	3000
		2000
		1000
		0	2	4	6	8	10	12	14	16	18	20
							kWh
	Parameters		Without-PV-DeBES-CeBES		With-PV		With-PV-DeBES	With-PV-DeBES-CeBES
	6PV [kWp]			0			1.54		1.54	1.54
	Decentralized BES [kWh]		0			0			17.4	17.4
	Centralized BES [kWh]		0			0			0		19.25
	Maximal power
	at the MV/LV		32.12		32.12		21.20	21.20
	substation [kW]
	Energy supplied
	from grid			51.69		37.70		28.74	22.82
	[MWh/year]
	Autonomous
	time			37.5 (no load)		70.15		69.12	78.26
	[%hours/year]
	Number of
	hours with voltage problem		3			3			0		0
	(V<0.9pu)/day

2 : Simulation results of PV-BES integration

According to the above table, the active power requirement from grid has been decreased drastically by the PV-DeBES-CeBES integration from 32.12 kW to 21.20 kW.

Likewise, the energy supplied from grid has been also decreased from 51.69 MWh to 22.82

  )

			PV inverter cost		0.72 kUSD/kW[NIPO05]
		Bi-directional inverter cost	1.155 kUSD/kW[NIPO05]
				total act C	=	N = ∑ t	invest C	used t C En t t i + × +	(III-7)
	Where:
	-	_ total act C	: total actualized cost in kUSD
	-	invest C	( ) t : investment cost in the year t in kUSD
	-C : electricity price in	/ kUSD kWh
	-		( )
	Table III-3 : Parameters for the economic analysis [VGBA17]
		Parameters			Value
		Planning period			15 years
		Actualization rate			12 %
		Electricity cost			0.3 USD/kWh[EAC15]
	ABC-2x50 mm 2 cable cost	1.6 kUSD/km
	ABC-2x95 mm 2 cable cost	3 kUSD/km
		PV panel cost			1.2 kUSD/kWp[ECOS17]
	Battery energy storage cost	0.13 kUSD/kWh[ECOS17]

used

En t : energy used in the year t in kUSD -i : actualization rate in % The planning period for the analysis is 15 years and the actualization rate is estimated to be 12 %

[VGBA17]

. The list of the parameters for the economic analysis is shown in Table

III

-3.

  -4. For this primary study, since there is no available information about the construction cost of the LV distribution grid in Cambodia, the actualized cost takes into account only the components costs (i.e. cable, PV, BES and converter).

	Table III-4 : CAPEX of the two strategies
			Proposed solution
	Items	1 st : Grid reinforcement	2 nd : PV-BES integration
		Values	Cost(kUSD)	Values	Cost(kUSD)
	2x50 mm 2 cable	0 m	0	211 m (extension)	0.338
	2x95 mm 2 cable	955 m	2.866	0 m	0
	PV	0 kWp	0	1.54x6 kWp	11.088
	DeBES	0 kWh	0	17.4 kWh	2.262
	CeBES			19.25 kWh	2.50
	Grid
	connected	0 kW	0	1.6x6 kW	6.91
	inverter
	BES Bi-			6kW (DeBES)
	directional	0 kW	0	and	20.79
	inverter			16kW(CeBES)
	Total cost		2.866 kUSD		43.888 kUSD

Table IV -

 IV 1 : Simulation of PV Penetration in urban area

	Feeders	Buses of installed PV	Max PV (kWp)	PV Penetration (%)
	F1	9	15.90
	F2 F4	22 31	15.86 15.85	31.76
	F4	36	15.91
	IV.3.1.2.3 Sizing of CeBES

Table IV -

 IV 2 : Summary of simulation results for the initial year in the urban area

	Items	Without-PV-CeBES (strategy 1/ strategy 2)	With-PV (strategy 1/ strategy 2)	With-PV-CeBES (strategy 1/ strategy 2)
	4 single-phase PV [kWp]	0/0	15.85-15.86-15.90-15.91	15.85-15.86-15.90-15.91
	Centralized 3ph-BES [kWh]	0/0	0/0	88.37/ 86.80
	Energy used [MWh/year]	818.98/ 841.38	673.81/ 695.20	653.13/ 674.97
	Active power from grid [kW]	206.14/ 216.48	206.14/ 216.48	206.14/ 216.48
	Autonomous operation time [%/year]	0/0	16.67/ 16.67	26.69/ 26.54

Table IV -

 IV 3 : Summary of simulation results for the end of the planning year in the urban area

	Items	Without-PV-CeBES (strategy 1/ strategy 2)	With-PV (strategy 1/ strategy 2)	With-PV-CeBES (strategy 1/ strategy 2)
	Energy stored in CeBES [kWh]	0/0	0/0	0/ 0
	Energy used [MWh/year]	1286.6/1343.6	1119.3/ 1175.2	1119.3/ 1175.2
	Active power from grid [kW]	326.04/353.12	326.04/353.12 326.04/ 353.12
	Autonomous operation time [%/year]	0/0	0/ 0	0/ 0
	Furthermore, the histogram of simulation results at the end of the planning period are
	provided in Appendix IV-C.

Table IV -

 IV 4 : Initial cost without PV-BES integration of the proposed algorithms

			Proposed method without PV-BES
	Items	Strategy 1 : SP-FFBP	Strategy 2: MIQCP
		Amount	Cost(kUSD)	Amount	Cost(kUSD)
	70mm 2 cable	3440 m	3.440	2005 m	2.005
	Energy used per year	818.98 MWh	147.416	841.38 MWh	151.448
	Total cost		150.856 kUSD		153.453 kUSD
	Vannak VAI, Grenoble INP / G2Elab			Page 102

Table IV -

 IV 5 : Initial cost with PV-BES integration of the proposed algorithms

			Proposed method with PV-BES
	Items	Strategy 1 : SP-FFBP	Strategy 2: MIQCP
		Amount (unit)	Cost(kUSD)	Amount(unit)	Cost(kUSD)
	70mm 2 cable	3440 m	3.440	2005 m	2.005
	Energy used per year	653.13 MWh	117.563	674.97 MWh	121.495
	PV	63.52 kWp	76.224	63.52 kWp	76.224
	BES	88.37 kWh	11.488	86.80 kWh	11.284
	Grid
	connected	4*16 2 kWp	46.08	4*16 kWp	46.08
	inverter
	BES Bi-
	directional	36 3 kW	41.58	36 kW	41.58
	inverter
	Total cost		296.375 kUSD		298.668 kUSD

Table IV -

 IV 6 : Simulation of PV penetration in rural area

	Phase connection		Households with PV		Sizing
	A	62	86	111	2.40 kWp
	B	52	77	89	3.28 kWp
	C	32	48	125	3.06 kWp
	IV.3.2.2.

3 Location and Sizing of DeBES

Table IV -

 IV 7 : Summary of simulation results for the initial year in rural areaAs seen in TableIV-7, the under voltage has been occurred in case without distributed generation, thus the grid-reinforcement is performed in order to remove this problem. TableIV-8 shows the minimal voltage and maximal current for cable reinforcement (i.e. 70mm 2 and 95mm 2 ) used in Cambodia at 19h where the peak load occurs at the end of planning period.

	Energy used [MWh/year]	4500 5000 82.58	54.54		53.38			14.67
	Autonomous time [%/year]	4000 37.5 (no load)	79.44		79.44			90.9
	Number of	3500
	(V<0.9pu)/day hours with Occurrence voltage problem	2000 2500 3000	3	3		0			0
		1500
		1000
		500
		20 0	40	60	80	100	120	140	160
					kWh
		Without-
	Parameters	PV-DeBES-	With-PV	With-PV-DeBES		With-PV-DeBES-CeBES
			CeBES
	Three single-
	phases PV[A-	0	[2.4,3.28,3.06]	[2.4,3.28,3.06]		[2.4,3.28,3.06]
	B-C] -[kWp]
	Decentralized BES [kWh]	0	0		[13.73,13.09,18.37] [13.73,13.09,18.37]
	Active power
	from grid	47.44	47.44		45.44		40.35
	[kW]

Table IV -

 IV 8 : Minimal voltage and maximal current for two types of cable reinforcement.

			Max current (in
	Cable size	Min voltage (pu)	% of the maximal admissible	Decision
			current)
	ABC-4x70mm2	0.89 pu	64.5 %	NO
	ABC-4x95mm2	0.92 pu	51.9 %	YES

  -3 of chapter III. The CAPEX at the initial year for the two strategies are detailed in Table IV-9.

	Grid
	connected		0 kW	0	2.5x3kW+3.3x6kW	19.656
	inverter
	BES Bi-directional inverter	0 kW	0	6-6-8 kW (DeBES) and 48 kW(CeBES)	78.54
	Total cost			5.114kUSD	157.892kUSD
	Table IV-9 : CAPEX of the grid-reinforcement and PV-BES integration
					Solution
	Items		Grid reinforcement	PV-BES integration
			Values	Cost(kUSD)	Values	Cost(kUSD)
	4x50 mm 2 cable		0 m	0	3409.42 m	2.728
	4x95 mm 2 cable	3409.42 m	5.114	0 m	0
	PV		0 kWp	0	[2.4,3.28,3.06]x3kWp	31.464
	DeBES		0 kWh	0	[13.73,13.09,18.37]kWh	5.879
	CeBES				151 kWh	19.630

D: Load specification of LV distribution system for rural area-case study

	31		9000 124	175 0.443		74	-16	89	9000 0.414 117	178	511 0.342
	32		8000 39		221 0.489		75	-4	8000 104 0.423 118	189	512 0.402
	33 34		7000 41 69		236 0.421 229 0.390		76 77	-10 -34	128 0.332 119 7000 158 0.477 120	180 259	570 0.382 513 0.415
	35		6000 111	217 0.455		78	-69	6000 165 0.412 121	269	512 0.381
	Frequency 36 37 38 39	4000 5000 43 66 46 3000 46		254 0.434 260 0.385 274 0.415 X 291 0.417	Y	79 80 81 82	-84 -102 -6 -4	No. Bus 4000 5000 166 0.336 122 Coordinates 275 164 0.361 123 284 Frequency 165 0.382 124 293 X 3000 178 0.332 125 350	Y	P(kW), 522 0.345 522 0.357 511 0.456 pf=0.95 507 0.473
	1 40	2000 48		0 306 0.361	0	83	0	5	24 205 0.347 126 170 2000	357	4.61 500 0.392
	2 41	1000 50		0 373 0.355	5	84	0	3	25 230 0.454 127 190 1000	373	4.68 505 0.426
	3 4 5 6 42 43	0 0 0 5 Figure IV-C-4: Histogram of the annual energy of centralized battery energy storage-15 0 26 5 4.32 35 0 27 30 4.48 45 0 28 50 5 4.97 29 70 CeBES (Algo1-left, Algo2-right) 5.47 5.52 -5 -4 -3 -2 -1 0 1 2 3 4 65 362 0.374 85 8 247 0.451 128 409 500 0.416 0 kWh kWh -5 -4 -3 -2 -1 0 1 3 4 0 66 371 0.397 86 7 289 0.469 129 422 500 0.349
	7						30		5	4.03	30	90	5.40
	is given as follows: 8 50 9 70 10 90 11 110 12 130 Appendix IV-No. Coordinates P(kW), 5 5 5 5 5 13 150 5 Bus pf=0.95 X Y 14 170 5 1 0 0 0 15 190 5 2 4 40 0 16 5 15 3 8 80 0 17 30 15 4 12 120 0 18 50 15 5 16 160 0 6 20 200 0	4.89 6.12 4.72 5.19 5.26 No. 5.20 Bus 5.04 44 4.68 45 5.18 46 5.13 47 5.09 48 49	31 32 33 34 35 Coordinates P(kW), 110 130 150 170 190 36 5 pf=0.95 X Y 37 30 68 382 0.317 38 50 100 365 0.433 39 70 66 419 0.431 40 90 59 459 0.389 41 110 59 482 0.499 103 463 0.453	No. Bus 87 88 89 90 91 92	2 ( / km Ω 5.50 4.99 5.08 5.37 Coordinates P(kW), ,50Hz) 5.47 pf=0.95 X Y 6.30 13 0.372 4.51 0 0.389 5.06 11 0.494 5.22 13 0.357 4.41 21 0.426 4.24 20 0.359
	abcn 19 Z 7 20 8 21 9 22 10 23 11 12	-	240	0.1743 0.7338 0.0493 0.6613 0.0493 0.6396 0.0493 0.6613 0.0493 0.6613 0.1743 0.7338 0.0493 0.6613 0.0493 0.6396 0.0493 0.6396 0.0493 0.6613 0.1743 0.7338 0.0493 0.6613 0.0493 0.6613 0.0493 j j j j j j j j j j j j j j + + + + + + + + + + + 70 15 5.31 42 130 5.08 24 =  240 0 50 121 460 0.420 93 -77 0.439   90 15 4.91 43 150 4.64 28 280 0 51 134 464 0.405 94 -17 0.358   110 15 4.40 44 170 5.00 32 320 0 52 137 419 0.459 95 39 0.410    130 15 5.53 45 190 4.51 36 360 0 53 151 411 0.389 96 -14 0.416 + + + 0.6396 0.0493 0.6613 0.1743 0.7338 j j   + +  150 15 40 400 0 54 164 419 0.434 97 -15 0.448 5.36  44 440 0 55 182 471 0.428 98 31 0.321
	Z	acn 13 -14 15 16 17 18	240	0.1743 0.7338 0 0.0493 0.6396 0.0493 0.6613 0 0 0 0 0.0493 0.6396 0 0.1743 0.7338 0.0493 0.6613 0.0493 0.6613 0 0.0493 0.6613 0.1743 0.7338 j j j j j j j j j + + + 48  490 0 56 177 461 0.444 99 33   88 490 0 57 185 426 0.408 100 -8    128 490 0 58 185 418 0.444 101 33 =   + + 168 490 0 59 196 412 0.423 102 45 +   + + +  208 490 0 60 220 406 0.393 103 48  248 490 0 61 239 467 0.422 104 51	0.424 0.365 0.437 0.357 0.304 0.465
			19					288	490	0	62	267	399 0.464 105	51	0.430
	Z	240 20 an -21 22 23 24 25	=	0.1743 0.7338 0 0 0.0493 0.6613 0 0 0 0 0 0 0 0 0.0493 0.6613 0 0 0.1743 0.7338 j j j j + + 328   490 0 63 354 469 0.411 106    368 490 0 64 372 472 0.434 107   408 490 0 65 423 473 0.437 108   18 63 0.296 66 -61 24 0.292 109  + +  25 87 0.360 67 -27 32 0.369 110  24 115 0.420 68 -5 38 0.445 111	53 82 65 72 75 74	0.369 0.437 0.428 0.364 0.358 0.501
			26					25	131 0.365	69	-8	43	0.446 112	80	0.313
			27					87	116 0.376	70	-12	50	0.381 113	106	0.435
			28					108	113 0.372	71	-10	57	0.333 114	119	0.389
			29					41	153 0.399	72	-9	63	0.371 115	158	0.396
			30					38	196 0.398	73	-17	72	0.435 116	168	0.382
	Vannak VAI, Grenoble INP / G2Elab	Page 136

Table IV -

 IV G-1 Summary of simulation results at the end of planning for rural area-case De jour en jour, les consommations d'énergies ont continuellement augmenté dans le monde en raison de crossant d'habitants avec les styles de vie plus confortables. Nous développerons générations distribuées à petite échelle (intégration de PV et stockage) au réseau de distribution basse tension afin d'encourager le gouvernement cambodgien et les distributeurs d'électricité avec ces sources. Par ailleurs, afin d'appliquer la conception de planification du réseau de distribution basse tension, il faut comprendre le fond du réseau électrique tel que sa situation actuelle et son évolution, ainsi que l'architecture du réseau de distribution basse tension au Cambodge. La première partie de ce chapitre présentera la situation actuelle du réseau électrique au Cambodge. Dans la deuxième partie, nous fournirons la structure du réseau de distribution basse tension au deux zones différentes (i.e. rural et urbain). Enfin, nous détaillons le principe de la planification du réseau de distribution dans la dernière partie de ce chapitre. Dans ce chapitre, nous avons commencé par le contexte et le fond du réseau électrique au Cambodge. Il a été souligné qu'il y a environ 75 % de la production propre et que les 25 % restants sont importés des pays voisins, même si le Cambodge a le potentiel élevé de

	1. Introduction générale 1.2. Objectifs
	study 1.1. Contexte Pour réussir ces objectifs du contexte de travail, cette thèse étudie de novelles
	Parameters méthodologies pour dessiner les réseaux de distribution basse tension avec intégration de W/O-PV-DeBES-With-PV With-PV-DeBES-With-PV-DeBES CeBES sources d'énergie renouvelables à petite échelle au Cambodge. Les objectifs principaux de
	CeBES Actuellement, les besoins d'énergie ont alerté en concernant la réduction des fossiles, thèse sont d'étudier la planification du réseau de distribution basse tension avec intégration
	Three single-phases PV[A-B-C] -[kWp] l'efficacité énergétique et les problèmes de réchauffement planétaire, ce qui conduit nos 0 [2.4,3.28,3.06] [2.4,3.28,3.06] de sources photovoltaïques et stockage et d'évaluer les solutions proposées prenant en [2.4,3.28,3.06] sociétés à chercher des sources d'énergies alternatives. Des sources d'énergie compte les problèmes d'incertitude associés aux charges électriques. Cette thèse
	Decentralized BES [kWh] renouvelables ont été proposées pour réduire la dépendance de combustible fossile en 0 0 contribuera à l'électrification cambodgienne sur l'horizon de planification à long terme. [13.73,13.09,18.37] [13.73,13.09,18.37] transformant l'énergie des ressources naturelles à l'énergie thermique et électrique. 1.3. Plan de thèse Active power 79.07 79.07 57.02 57.02 Aujourd'hui, les sources d'énergie renouvelables sont largement utilisées pour fournir de from grid [kW] Energy used 128.40 95.96 78.94 Dans le premier chapitre de cette thèse présentera la situation actuelle et l'évolution Résumé en français du réseau électrique, l'architecture du réseau de distribution basse tension pour les deux 60.46 [MWh/year] zones différentes (rural et urbain) et fournira également le principe de la planification du
	Autonomous time [%/year] Planification du réseau de distribution 37.5 (no load) 69.62 65.46 77.14 réseau de distribution au Cambodge.
	Number of hours with basse tension avec intégration de sources
	voltage problem (V<0.9pu)/day	3 photovoltaïques et stockage-cas du 3 0 0
		réseau du Cambodge
	Solar Home System (SHS) au Cambodge. Actuellement, environ 80 % de la population vit
	dans les zones rurales et 75 % des ménages vivent sans l'électricité même si ce pays a le PV est trouvé dans le réseau BT afin d'optimiser l'autonomie énergétique du réseau
	potentiel élevé de ressources renouvelables. Afin de répondre aux besoins de la population électrique. Ensuite, des algorithmes seront mis en place pour trouver l'emplacement
	et de la société pour l'électricité, le gouvernement cambodgien a établi la politique pour optimal et la capacité du BES qui sera intégré au réseau de distribution basse tension afin
	promouvoir et encourager le développement d'électricité ; tous les villages auront de de résoudre le problème de sous tension ainsi que son contrôle. En fin, l'analyse de techno-
	l'électricité d'ici 2020 et au moins 70 % des ménages auront accès à la qualité d'électricité économique sera effectuée pour comparer entre le renforcement du réseau et l'intégration
	d'ici 2030. En outre, les réseaux de distribution basse tension sont renforcés et expansés en de PV-BES.

l'énergie en tant que la génération distribuée connectée au réseau électrique. Les générations distribuées se situent à proximité des consommateurs, peuvent jouer un rôle important dans le réseau de distribution basse tension au futurs en raison de leurs impacts positifs potentiels sur l'amélioration de la fiabilité, la réduction des pertes, le support de tension et la réduction des émissions de CO2. Ainsi, l'intégration de la génération distribuée peut être considérée comme une option alternative attrayante pour la planification du réseau de distribution. Au Cambodge, l'électricité est récemment fournie par quatre sources principales, i.e. le diesel, l'hydroélectricité, le charbon et l'importation des pays voisins. Dans le plan directeur du développement du secteur de l'électricité du pays, le gouvernement cambodgien a défini l'hydroélectricité et le charbon comme les deux sources principales de production d'électricité. Les sources d'énergie renouvelables (i.e. photovoltaïques) déjà existent, mais elles sont petites et encore isolées du réseau national ; elles s'appellent le raison d'augmentation des charges électriques (i.e. croissance de la population et amélioration du standard de vie) ; ces points obligent le gouvernement cambodgien et les distributeurs d'électricité à effectuer la planification à la suite de ces problèmes actuels. Le deuxième chapitre détaillera le développement de la méthode de planification à long terme pour tacler le défi de l'incertitude des charges en zone urbaine. Dans cette partie, le nouvel algorithme sera développé pour chercher l'architecturer optimale de minimisation du coût d'investissement (CAPEX) et d'exploitation (OPEX) qui respecte l'ensemble de contraintes topologies et électriques (courant et tension). La programmation linéaire mixte en nombres entiers à contraintes quadratiques (PLMNECQ), le plus court chemin, first-fit bin-packing, et la méthode de Monte-Carlo seront utilisées pour résoudre ce problème. Le troisième chapitre portera sur l'extension de la zone de couverture de l'électricité avec deux solutions possibles : le renforcement du réseau et l'intégration de photovoltaïques (PV)-stockage d'énergie de la batterie (BES). Le maximum d'intégration Le dernier chapitre se concentrera sur la planification du réseau de distribution basse tension résidentielle BT pour les zones non électrifiées aux rural et urbain par l'architecture optimale et l'intégration de PV-BES des deux chapitres précédents. renouvelable. Actuellement, les lignes principales sont réparties en monophasée et triphasée le long des routes pour les zones rurales et sont presque triphasées pour les zones urbaines au Cambodge. Dans la planification traditionnelle, la génération locale n'est pas prise en compte ; il est donc intéressant d'étudier l'insertion de la génération locale, i.e. photovoltaïque (PV) et stockage d'énergie de la batterie (BES) dans la planification du réseau de distribution basse tension. Les contraintes prises en compte pour l'architecture optimale sont liées à la topologie et aux électrotechniques (i.e. tension et courant). Les

[REFE13] REFEDC, "Program for the development of rural electrification of Electricité Du Cambodge (EDC) through department of Rural Electrification Fund (REF),"

[Online]. Available: http://ref.gov.kh/page/home.

This assumption is made for testing the algorithms. The sensitivity of this parameter will have to be made in further studies.

Appendices

Acknowledgments Vannak VAI, Grenoble INP / G2ELab

Page i Acknowledgments

parameters of the LV distribution system are requested as input as well as information on non-electrified loads (location and peak power). For the 1 st proposed solution, the expansion/reinforcement of existing grid will be studied in order to solve the under voltage problem by sizing the minimum cable which respects the voltage and current constraints.

For this 2 nd proposed solution, we define the amount and location of the single-phase PV integration at households; in this chapter it is assumed that PVs will be connected to some customers having the highest load demand. Then the maximum power penetration of PVs will be sized according to PV-load curves and using an iterative technique which is described in section III.3.1.1. One decentralized BES is connected in the optimal location of the LV grid defined by a Genetic algorithm [IBA93] (see section III.3.2.1). The minimum capacity of the battery is found with an iterative technique. Then, the centralized BES at the MV/LV substation is sized to remove the reverse power flow and also to increase the

III.3.2.2.3 Decentralized control of BES

In rural LV distribution grids, particularly in developing countries, there are almost no information communication technology (ICT) components used to receive the data (current, voltage) in distance from the substation. In this primary study, we thus proposed a decentralized strategy to control the DeBES without using a large ICT system as depicted in Figure III-7. A simple measure of the voltage at the node where the DeBES is connected enable will control the charge and discharge of the battery provided that its state of charge remains between SoCmin and SoCmax. In section III.3.2.2.1, the DeBES has been located and size so as to solve the constraint of low-voltage. In that purpose, the maximal power injected by the battery has been determined at 19h, time where the worst low-voltage constraint appear. A load flow at 19h with this maximal discharge power enables to get the voltage at the battery node under which a low-voltage constraint will appear in the network. This voltage will be the set point voltage of the decentralized control of the battery called Vset. In other words, if the voltage at the DeBES node is higher or equal to Vset, the under voltage problem will not occur on whole system.

IV.3.2.2 Simulation results and discussion

IV.3.2.2.1 Optimal topology

The radial topology is performed by using the SP-FFBP algorithm. Figure IV-15 presents an optimal topology with load balancing (Pload-A :13.97 kW, Pload-B : 14.29 kW and Pload-C : 14.73 kW).

Appendix II-A: Simplified Carson's Equations

The simplified Carson's equations for calculating self and mutual series impedance of system are shown below.