Edgar M Silva

Luís Gomes

João Rodrigues
email: ‡jf.rodrigues@campus.fct.unl.pt

Pedro Maló

A Model-based Approach for Resource Constrained Devices Energy Test and Simulation

Keywords: Internet of Things (IoT), Wireless Sensor Networks (WSN), Power Consumption, Simulation, Model Driven Engineering (MDE)

The constant evolution in communication technologies, has improved during the last decades the interaction between systems/devices/things/etc. Internet-of-Things (IoT) has become the last trend pushing forward in this direction, connecting all 'things', creating a sensing world around all of us. Although, IoT technologies, solutions, systems have to be proven/tested before deployment in the real settings. These decentralized systems normally use low power devices with small processing and storage capabilities, with roles mainly of sensing and data transmission. Until now, tests and energy simulation focus on wireless communications, since it has been identified as the main energy consuming module. This paper presents the acquisition and simulation of energy consumption by a single device, focused on all hardware components and not only in the communication, due to the new adopted solutions that do not rely so much in the communication (e.g. subscription). In this sense, a methodology capable of retrieving real and simulated energy consumption results from/for a single device is presented, relying on a model based approach (software, hardware, energy and simulation models) and on a precise energy consumption assessment system. It is also presented a Resource Constrained Device Model, capable of representing the available hardware in a device, and a circuit to retrieve more accurate energy consumption readings.

Introduction

Advances in microelectronic technologies have brought small and cheap devices, leading to highly heterogeneous environments. Manufacturers are engaged in developing devices for different purposes addressing different application domains and services to target different Internet-of-Things (IoT) deployments [START_REF] Silva | IoT Testbed Business Model[END_REF].

These deployments, such as Smart Cities, Domotics (Smart Buildings), etc., follow standards from Internet-of-Things (IoT), a global infrastructure for a more aware society, through advance services by interconnecting things, physical and virtually, based on existing and evolving interoperable information and communication technologies [START_REF] Vermesan | Internet of Things -From Research and Innovation to Market Deployment[END_REF].

These systems normally use low power devices with small processing and storage capabilities, with roles mainly of sensing and data transmission, making full use of services to all kinds of applications, whilst ensuring fulfillment of all its requirements.

The major requirement for these devices is low-power operation, an extended lifetime, which leads to the actual problem, energy consumption. This work aims to understand in which ways is possible to estimate the power consumption, going through some existent solutions performing both acquisition and simulation of energy consumption by a single device. Looking forward to improve these methods, a methodology capable of retrieving real and simulated energy consumption results from/for a single device is presented, relying on a model based approach.

Cloud-based Engineering solutions for Internet-of-Things

Nowadays, is possible to produce small and cheap devices, with computation, sensing and wireless communication capabilities. Thanks to advances made, Wireless Sensor Networks (WSN) offer technology support for a wide range of potential applications [START_REF] Moschitta | Power Consumption Assessment in Wireless Sensor Networks[END_REF].

The relation with Cloud-based Engineering Systems can be established with base on the typical topology adopted in these systems. Considering a large number of nodes, and according to the type of sensing equipment, each device performs its task, collecting information and then, via subscription or periodically transmitting data, through a route to one or more collection points, called sink nodes. This unit gathers all data, making it available outside the WSN, exactly as other well-known Cloudbased systems [START_REF] Dâmaso | Evaluating the Power Consumption of Wireless Sensor Network Applications Using Models[END_REF].

One possibility is the paradigm expansion to a collaborative online platform, positioning itself on the cloud's information layer where all data is available to all interested entities. This will allow, for example, resource allocation strategies to reduce computational requirements for each user and also models exchange, creating a remote platform for energy testing [START_REF] Wei | A game-theoretic method of fair resource allocation for cloud computing services[END_REF]. A Model-based approach which allows users to share tailored models for each System Under Test and to request a remote simulation of such system is illustrated in

Simulations

Database

Models Results

Decentralized Processing Unit

System Under Test

User Front End HW/ SW/ App Models Fig. 1. As simulations require high computational resources, remote effort allocation is the major advantage, saving local execution time while waiting for results.

Background Research

Over the last years Internet-of-Things (IoT) has moved from being a futuristic vision, to an increasing reality. It is a dynamic global network infrastructure, with selfconfiguring capabilities based on standards and interoperable communication protocols, where physical and virtual 'things' have identities, physical attributes and virtual personalities [START_REF] Silva | IoT Testbed Business Model[END_REF].

In order to realize the vision of the IoT, Wireless Sensor Networks (WSN) position themselves as a virtual layer where the information about the physical world can be accessed by any computational system [START_REF] Alcaraz | Wireless Sensor Networks and the Internet of Things: Do We Need a Complete Integration?[END_REF]. On the physical side, WSN are formed by a number of devices, spatially distributed, in autonomous and cooperative monitoring of physical or environmental conditions [START_REF] Asorey-Cacheda | On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies[END_REF].

One of the main challenges is to take into account the energy constraints of such devices, which aim to have a low-power operation, something that is difficult to predict during applications development [START_REF] Somov | A Methodology for Power Consumption Evaluation of Wireless Sensor Networks[END_REF]. For such task, power consumption analysis is a vital step to evaluate the performance of these devices. The following sections present a brief review of such approaches.

Power Consumption Analysis

The distributed nature of WSN, based on the interaction between software and hardware components, makes it less easy to correctly design and develop such systems. Power consumption is the main concern at this stage, with several methods proposed in a while, which aim to investigate this phenomenon. As a result, these strategies may help the prediction of the expected lifetime, just before deployment, providing to application developers useful recommendations to optimize energy consumption [START_REF] Asorey-Cacheda | On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies[END_REF].

The two most common approaches for power consumption analysis are based on direct measurement, and on usage of simulation models. While measurement is a more accurate strategy for power consumption evaluation, it is known to have some limitations, as it turns to be very costly, tedious or even not practical, considering the typical topology of a network, with a large number of devices [START_REF] Dâmaso | Evaluating the Power Consumption of Wireless Sensor Network Applications Using Models[END_REF]. Due to this complexity, measurements taken on a single node are often generalized to the entire network when considering similar tasks and performed by homogeneous platforms. A common solution is measuring and monitoring the absorbed current, using a single resistor setup, placed between the power supply unit and the Device Under Test (DUT). Applying Ohm's law for the voltage drop across the resistor, current is measured. As this is an indirect measuring method, some of its accuracy limitations may put the process results at risk. Moreover, this also restricts the general consumption measurement on the device, making impossible to understand which components are draining current [START_REF] Moschitta | Power Consumption Assessment in Wireless Sensor Networks[END_REF].

It is known that in comparison with other peripherals, radio modules are the source for greatest usage of energy so a way to understand the current drainage is by running applications that make use of a single component at a time, in order to generate its own energy profile. Combining the data collected for each application, simulation models may be generated for future testing, turning the scenario a little less complex.

Simulators

Simulation is the quickest way to test code and systems, before running it on the target hardware. Some simulation tools provide power consumption estimation, becoming a useful resource for performance analysis, when coupled with proper measurement techniques, keeping into account possible limitations on data acquisition [START_REF] Moschitta | Power Consumption Assessment in Wireless Sensor Networks[END_REF]. There are several simulators, each with its own features and limitations. Avrora is widely used for WSN specific simulation, providing discrete-event simulation up to thousands of nodes. Although, it does not provide extensions besides from AVRMCU cores [START_REF] Somov | A Methodology for Power Consumption Evaluation of Wireless Sensor Networks[END_REF]. With the addition of an energy model, power profiling and lifetime prediction are enabled [START_REF] Landsiedel | Accurate prediction of power consumption in sensor networks[END_REF]. Bundled with Contiki OS, Cooja (http://contiki-os.org) is a useful tool to simulate such architecture, supporting emulation of platforms with TI-MSP430 or AtmelAVR micro-controllers, allowing heterogeneous networks emulation, supporting power consumption estimation [10]. MSPSim [START_REF] Eriksson | MSPsim -an Extensible Simulator for MSP430-equipped Sensor Boards[END_REF] can emulate TI-MSP430 micro-controller based devices from the instruction level, optimizing applications debugging process, and offering power consumption estimation, compatible with Contiki OS and TinyOS (http://tinyos.net). NS-2, from Network Simulator (http://nsnam.org), is a discrete-event simulator for general purpose, running up to 100 nodes. However, NS-2 cannot simulate power consumption in WSN [START_REF] Somov | A Methodology for Power Consumption Evaluation of Wireless Sensor Networks[END_REF]. PowerTossim (http://eecs.harvard.edu) is an extension to TOSSIM, which is a simulation environment included in TinyOS's framework. However, as TOSSIM only supports MICAz (http://moog-crossbow.net) hardware platform, the applying scope is reduced. Somov is the less tailored simulator as it offers power estimation of WSN applications for arbitrary hardware platforms, by separately defining the possible states of each component, having its performance and energy consumption data associated [START_REF] Dâmaso | Evaluating the Power Consumption of Wireless Sensor Network Applications Using Models[END_REF].

Model Driven Engineering (MDE) Approaches

With the sustained increase of technology, models are becoming more and more attractive to manage systems complexity, by simplifying design processes and formalization [START_REF] Hausmann | Model-based discovery of Web services[END_REF]. MDE's vision follows a unification principle, "everything is a model" (i.e. all can be modelled, programs, services, etc.), similar to the object technology basic principle, "everything is an object".

Another key initiative in MDE approaches is the Model Driven Architecture (MDA), an Object Management Group (OMG) initiative, which offers modelling support at different levels of abstraction [START_REF] Management Group | MDA Guide Version 1.0.1[END_REF]. MDA specifies a standard-based architecture for models, organized around three different abstraction levels, providing guidelines to structure the specifications [START_REF] Management Group | MDA Guide Version 1.0.1[END_REF][14]: Computation Independent Model (CIM), Platform Independent Model (PIM) and Platform Specific Model (PSM).

The CIM is a level for the domain practitioners, in which systems requirements as well as the environment are specified with specific domain vocabulary, bridging the gap between domain experts and the development experts [START_REF] Management Group | MDA Guide Version 1.0.1[END_REF].

The PIM level deals with system formal specification, structural as functional. Abstracts technical details, focusing on system operation itself rather on how operations will be carried out. PSM level gathers technical and engineering details from a specific platform, combining it with the system specification from PIM level.

Hypothesis

From the early background research, some of the most important features and constraints of WSN devices were identified. It was possible to understand some weaknesses in existent solutions for behavior emulation and power consumption analysis (via simulation and direct measuring). As a result, the main question of this paper is: Would a model-based approach, combined with precise measuring and simulation, provide more accurate results, being able to solve the known weaknesses on other previous attempts to assess the power consumption? This is the starting point for the proposed solution, which will make use of the presented concepts, such as simulation, direct measuring and model driven engineering.

Proposed Solution

Starting with an overview of the developed architecture, in terms of direct measuring, a fine tuned reading circuit coupled to a processing unit aiming to output reliable data will be use. The circuit supplies the processing unit with the voltage and current readings, while this block, through oversampling [START_REF] Corporation | Enhancing ADC resolution by oversampling[END_REF], outputs what we call real lab tests. This approach leads to a precise result, since the oversampling method adds bits of resolution to the typical 12bit result. specifications. In the end, is argued that this architecture will generate accurate results, since it is supplied with reliable information.

Energy Analysis

To perform realistic tests (real laboratory tests) a circuit was design to simultaneous retrieve the current and power consumed by the Device Under Test (DUT). This circuit (in principle) is not much different from other proposals found in the scientific community, as presented previously in Chapter 3.3.

Although, some changes were added to allow a more precise analysis of the current and power consumed. When looking to the power ranges needed to maintain an IoT device running (battery case) is possible to guarantee that a device will not work with half of the maximum supplied power, i.e. if the maximum power is 3.3V the device will not work with less than 1.65V, normally the range is between 3.3V and 2.6V. In the case of the DUT has an infinite capacity power supply, power provided to the device is almost constant with small fluctuations. Therefore the capability to change the power value passed to the processing unit was added, allowing the analysis of the total power supplied (maintaining the Uref equals to zero) or, for instance, half of the power supplied (maintaining Uref = U/2) which increases the precision in one bit (by hardware).

In the current case a very common Rsense arrangement is used (built with very small resistors in terms of value to not interfere with current consumed), but with two particularities. First, is possible to change Rsense resistor value (through a jumper's settlement to a better Rsense accommodation regarding the current consumed by the DUT). Second, the analyzed Rsense current is divided into two different signals that then will go to the processing unit. The first signal called CurrentDown is the current with a gain of two, and the second called CurrentTop is the current minus a Uref also with a gain of two. This separation increases the current signal precision in one more bit (by hardware).

Resource Constrained Device Meta-Model

As previously seen, the presented architecture follows a model based approach, in which a set of models (software, hardware and real lab energy consumption) is provided to the simulation module, so an automatic simulation can be performed based on all the information provided. Regarding the software Meta-Model which defines the software model, is basically dependent of the programming language used. At this point the architecture uses the C and nesC Meta-Model since they are the more common programming languages used by the IoT development community [START_REF] Lajara | Power Consumption Analysis of Operating Systems for Wireless Sensor Networks[END_REF].

Unlike the programming languages, that presents well defined Meta-Models or grammars, a hardware Meta-Model capable of representing a device is still missing. In this sense, and based in the work developed in [START_REF]Cuteloop "Customer in the Loop: Using Networked Devices enabled Intelligence for Proactive Customers Integration as Drivers of Integrated Enterprise[END_REF] a Resource Constrained Device Meta-Model (RCDM) is proposed to describe the hardware components available in a device, see RCDM provides a way to formally describe a device in terms of its hardware components. A device is composed by at least one module, that module can contain one or several components, e.g. a microcontroller as a processing unit, memory, AD/DA converters, etc. Each component is defined by one or more properties, identified by a name and with a type. The property type can be of two kinds, single or an aggregation of properties. A single property is used for instance when referring to a microcontroller architecture type (e.g. RISC, CISC). An aggregation property is used when referring to a combination of several properties, for example a radio transmission range which can be defined through, out or indoor environment, maximum range, distance unit.

Experiments (Definition)

The experiment definition starts with a selection of the devices to be tested. As most of the available products on the market share the same operating specifications, in terms of power supply, we were able to design and build a printed circuit board with the measuring circuit, capable of measure and monitor the power consumption.

Following the architecture presented in section 5, each system under test will be coupled with this circuit for data collection and analysis. By running a series of tests, we expect to achieve solid results to validate the supporting theory of this approach.

Device Selection

By reviewing the market share for IoT solutions, a survey was accomplished regarding complete devices specifications, identifying a set of hardware platforms as a good starting point for energy testing.

Being compatible with both TinyOS and Contiki operating systems, the adopted designs are TelosB (http://tinyos.stanford.edu) based devices by AdvanticSYS (http://advanticsys.com) and IRIS based devices by MEMSIC (http://memsic.com). The main goal of this survey is to gather multiple combinations of the most relevant parts, such as microcontrollers, memory, transceivers and sensing units. Including devices with similar features, we aim to set a solid platform for further comparison, as it will include results from a wider group of hardware.

The following table presents the first devices to be tested. Similar tasks will be performed on each device, as tailored applications will run on them. This will allow tracing the energy consumption, helping to confirm the effects of different clock speeds, program flash, memory, and radio units in the final consumption. Devices featuring external sensing units will be coupled with sensor boards in order to perform the tests. The selection consists in AdvanticSYS EM1000, SE1000 and MEMSIC MTS400. We decided to include this hardware in order to estimate a wider range of hardware and to study the external sensing power consumption phenomena.

Device Testing

With the previous devices selection, is completed the System Under Test definition to be tested by developing a group of simple applications with a common objectivecollect and analyze, at each time, the energy consumption from a single component.

The combination of these applications with the chosen platforms is expected to allow the creation of the respective energy models for each device, improving the further model-based approaches for energy testing on the proposed solution.

Conclusion

The Internet-of-Things is here to stay: IoT deployments abound, more IoT-related technologies appear and new IoT centralized apps are launched each day. With this new paradigm, decentralized systems benefit from resource constrained devices sensing capabilities, improving the overall system with environment awareness.

To engineer such systems, some concerns should be considered regarding energy consumption. The hardware selection has to be made wisely but also the applications code development has to be analyzed to achieve better efficiency results, locally (device/system) as well as globally (network/overall system).

This work proposes an architecture capable of retrieving real and simulated energy consumption results from/for a single device, relying on a model based approach (software, hardware, energy and simulation models) and on a precise energy consumption assessment system. It is also presented a Resource Constrained Device Model, capable of representing the available hardware in a device, and a circuit to retrieve more precise energy consumption readings.

With this methodology is possible to analyze the performance of a certain application in several hardware platforms and using different programming language. Provides important information regarding energy consumption, and consequently allows the developer to make a more conscious choice on how to implement his solution and/or improvements.

As future work, exhaustive energy consumption tests will be carry out on the selected devices, using different applications to allow the development of precise simulation models.

Fig. 1 .

 1 Fig. 1. Example of Cloud-based platform for collaborative simulation.

Fig. 2 .

 2 Fig. 2. Complete Architecture for Model-based Energy Testing/Simulation.With the precise feedback result, a model-based simulator can emulate the device behavior by using its meta-models, representing the hardware, software and energy

Fig. 3 .

 3 Fig. 3. Energy Measuring Circuit.

  Fig 4.

Fig. 4 .

 4 Fig. 4. Resource Constrained Device Meta-Model (RCDM).

Fig. 5 .

 5 Fig. 5. Energy Measuring Board.

Table 1 .

 1 Selected Devices for Energy Test/Simulation.


María Mercedes Ruiz-Cortés

Isabel Milanés-Montero

Fermín Barrero-González

Enrique Romero-Cadaval

Analysis of Causes and Effects of Harmonic Distortion in Electric Power Systems and Solutions to Comply with International Standards Regarding Power Quality

Keywords: Power quality, disturbances, simulation models, harmonics

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Nowadays, there are countless loads which need power supply to work both in industries and in the tertiary and domestic sector. This fact has turned the electric power system into a fundamental cornerstone for economic and social development. For this reason, it is essential that power quality is as adequate as possible and keeps the voltage waveform within acceptable limits in terms of RMS value and frequency.

These parameters do not remain indefinitely in their nominal values because the electric system is not ideal. It may be affected in its normal operation unintentionally by electromagnetic signals called disturbances. These disturbances can be external to the power grid (due to lightning, natural disasters, accidents, etc) or internal to it, like large industrial receptors and even small power loads. In addition, the proliferation of electronic devices connected to the grid in recent years has made this problem worse.

These facts explain why power quality has gained relevance in the last decades. As a result, standards and regulations regarding power quality have being developed in order to establish acceptable values which guarantee a suitable electric supply.

An interesting approach to move forward in research about disturbances which affect the electric power system is based on examining their possible causes. In this way, this paper focuses on analyzing by simulation the implications of the presence of harmonic disturbances in the electric power system. Moreover, among the solutions to improve power quality, this paper exposes the importance, in the context of future Smart Grids, of designing cloud-based devices which enable consumers to monitor power quality parameters locally in their household, and upload that data to an Internet service to produce a crowdsourced perspective on power quality.

Contribution to Cloud-based Engineering Systems

Cloud computing, considered as the real-time delivery of IT infrastructure, services and software over the Internet or an internal web-based infrastructure, is an important tool for improving the power quality from a global perspective. Monitoring and collecting data allows determining the presence of disturbances, analyzing their causes and measuring their effects. But above all, cloud computing enables to make decisions about which solutions to implement to minimize the effects regarding poor power quality or reliability. In addition, stored data allows having information for predicting the occurrence of disturbances, in order to anticipate the causes.

One of the challenges of the future Smart Grid is to enable the active participation of consumers to modify electricity purchasing patterns and behaviours. It can be achieved via power quality monitoring in their household. These data would allow having cloud-based information of consumptions and the data processing will provide information as the interaction with neighbors regarding power quality. It will also help to make decisions to reduce power quality problems. In this way, the Open Power Quality research project carried out in the University of Hawaii [START_REF] Johnson | Enabling active participation in the Smart Grid through crowdsourced power quality data[END_REF] has demonstrated how the combination of a low-cost hardware and cloud-based software allows the consumers to monitor some parameters regarding power quality in their homes and upload that data to an Internet service. This project proposes a crowsourced approach in which collection of data is made by consumers and is analyzed oriented toward the needs of consumers.

Another feature of the Smart Grid is to meet user demand for power quality and provide users with an optimal variety of power quality and price program. According to it, power quality monitoring and the development of a power quality information platform to manage the collected data and evaluate results is an important issue. Besides, another challenge of Smart Grid is the user-friendly and intelligent interaction between the customers and the power provider, trying to meet user needs with the best power quality and reliability. Trying to fulfill these challenges, a power quality unified information platform based on cloud computing Software-as-a-Service (SaaS) model is proposed in [START_REF] Liu | Research and implementation of power quality unified information platform based on SaaS model[END_REF]. It promotes information sharing and friendly interaction between both power provider and consumers.

As an example of usable collaboration and interaction between consumers, in this paper a solution to eliminate the effect of harmonic distortion and the appearance of parallel resonance is proposed. The solution is as simple as using transformers of specific vector groups by consumers connected to the same Point of Common Coupling (PCC). However, this solution is impossible to implement without monitoring locally and exchanging that information between users. It shows the importance of developing cloud-based platforms in order to get the power quality requirements of the future Smart Grid.

State of the Art

The use of simulation tools has become an interesting method to analyze disturbances which affect the electric power system and contribute to the study of power quality. In [START_REF] Tan | Simulation of power quality events using Simulink model[END_REF] a set of five simulation models is presented to simulate various power quality events in a distribution system using the SimPowerSystems blockset, like voltage sag, transient, notches and harmonics.

The operation of some industrial loads that cause pollution on the electric power system is also simulated in the literature. In [START_REF] Zamora | Simulation by MATLAB/Simulink of active filters for reducing THD created by industrial systems[END_REF] a steel plant and an underground traction system are simulated and an active filter is installed in order to mitigate the voltage harmonic distortion. In [START_REF] Vahabzadeh | Use of Unified Power Quality Conditioner In Khoozestan-Iran steel complex network, a case study[END_REF] the authors propose a steel plant using induction furnaces model and present a Unified Power Quality Conditioner (UPQC) to compensate possible voltage problems. Meanwhile, in [START_REF] Tavakkoli | A Simulink study of electric arc furnace power quality improvement by using STATCOM[END_REF] the electric arc furnace is modelled with a Static Compensator (STATCOM) to improve the power quality, while in [START_REF] Bhonsle | Design and analysis of composite filter for power quality improvement of electric arc furnace[END_REF], a composite filter is employed in order to reduce harmonics, voltage flicker and imbalance. Electrified railway is another industrial non-linear load simulated in [START_REF] Zaeim | Gain-scheduling adaptive control of the STATCOM for electrified railway systems using PSO[END_REF], with a STATCOM with PSO-implemented controller to suppress harmonic distortion, voltage fluctuations and to compensate reactive power. In [START_REF] Baseri | Compensating procedures for power quality amplification of AC electrified railway systems using FACTS[END_REF], electrified railway systems are analyzed too using several types of Flexible AC Transmission Systems (FACTS) for power quality improvements.

In the same way, in [START_REF] Suárez | Analysis of the Harmonic Distortion and the Effects of Attenuation and Diversity in Residential Areas[END_REF] harmonic currents demanded by some non-linear household devices are simulated and different kind of faults and harmonic pollution brought by power electronic devices in power system are also simulated in [START_REF] Zhu | Modelling and Simulation of PQ Disturbance Based on Matlab[END_REF]. The authors of [START_REF] Thapar | Investigation of power quality categorization and simulating its impact on sensitive electronic equipment[END_REF] expose a categorization of power quality events and show a simulation model to validate the impact of power quality on sensitive equipment. Finally, the purpose of [START_REF] Sivakoti | Power Quality Improvement in Distribution System Using D-Statcom in Transmission Lines[END_REF] is to present a solution to voltage sags/swell, harmonic distortion and low power factor using Distribution Static Compensator (D-STATCOM), showing its effectiveness through a simulation model.

Simulation Case Studied

This paper focuses on simulating a cause of harmonic distortion in an electric power system, checking one of its worst effects and proposing a solution based on exchanging information about harmonic consumption between users. The simulation model is shown in Fig. 1 and the parameters are collected in Table 1. It is a threephase low voltage electric power system modeled as a voltage source and a series grid impedance. In the PCC it is connected a linear resistive-inductive load with a capacitor bank in parallel in order to improve locally the power factor. At the same point, there are two non-linear loads, which are non-controlled three-phase rectifiers connected to the PCC via isolation transformers. The capacitor bank and non-linear loads have breakers in series in order to be able to simulate the behavior of the system when these devices are connected or not.

Causes

The main cause of harmonic distortion is the use of power electronic devices. The simulation model shown in Fig. 1 includes two three-phase rectifiers, demanding a current (downstream the transformers) with the waveform displayed in Fig. 2(a) with THD of 16.94% and dominant harmonics 5th and 7th (see harmonic spectrum in Fig. 2(b)).

Effects

Harmonics are responsible of many problems in electric power systems. The simulation model developed in this paper (Fig. 1) allows observing one of the effects caused by harmonics: resonance between capacitor banks for power factor correction and grid inductances, which amplifies the existing harmonics. Fig. 1 represents a distribution power system that feeds a linear load connected to the same PCC as the three-phase rectifiers. In this case, breaker 1 is on and breaker 3 is off, so only the upper rectifier is considered. The linear load has a capacitor bank that is connected to the system after 0.5 seconds, in order to correct the power factor. Simulation results are exposed in Fig. 3 and Fig. 4. These figures show the waveforms of PCC voltage in Fig. 3(a) and network current in Fig. 3(b), and how their distortion gets worse when the capacitor bank is connected to the system. As it can be seen, Fig. 4(a) indicates that the voltage has a THD of 14.59% before the connection of the capacitor bank. This fact is a consequence of the harmonic emission caused by the rectifier, distorting the waveform of the current to a THD=10.48% (Fig. 4(a)). However, after the connection of the capacitor bank, voltage THD grows up to 25.44% and current THD to 20.67%, as Fig. 4(b) shows. This increase of THD is due to the remarkable rise of the value of 5th harmonic, because a parallel resonance occurs at a frequency near 250 Hz. In this way, 5th harmonic rises from 27.19 V to 52.73 V in the case of PCC voltage and from 33.26 A to 64.51 A in the case of grid current. The 7th harmonic is also modified by parallel resonance, although less than 5th harmonic; it grows up to 12.12 V to 32.04 V for PCC voltage and from 10.59 A to 28 A in the grid current.

Solutions

The problems caused by harmonics can be mitigated by different solutions. This paper presents a solution to eliminate the dominant harmonics in the modeled system, that is, 5th and 7th harmonics. In case of two similar non-linear loads at the same PCC, instead of connecting them directly to the grid, they are connected via transformers with different connections. The implemented solution consists of the association in parallel of a Dy transformer with the Yy transformer that feeds the three-phase rectifier previously analyzed, as it can be noted in Fig. 1. The Dy transformer feeds another three-phase rectifier with an identical load than the first rectifier, and introduces a phase difference of 30º in the demanded current by the second rectifier. Therefore, the demanded currents by both rectifiers upstream the transformers are 30º out of phase between them, as Fig. 5(a) shows. Thus, the sum of both currents makes 5th and 7th harmonics to be cancelled; hence the current that flows in the system under these conditions (after 1 second of simulation) is much more similar to a sine wave (Fig. 5(b)). As a result, the waveform of voltage in PCC has been improved too (Fig. 5(c)). The harmonic spectra of both signals demonstrate the elimination of 5th and 7th harmonics and how their THD have been reduced to 7.07% in the case of the voltage and to 1.57% in the case of the network current, as Fig. 6

Conclusions and Further Work

The development of simulation models to analyze disturbances in the electric power system has become an interesting research method for improving power quality. In this paper, a simulation model has been proposed to confirm a cause of harmonics, the use of rectifiers connected to the network, and one of its effects, the appearance of parallel resonance between capacitor banks and the grid impedance. In addition, it has been simulated a possible solution to eliminate the 5th and 7th harmonics through a special coupling of transformers, as an example of collaboration between consumers through cloud-based computing. As further work, it is proposed to develop a prototype to validate experimentally the results obtained by simulation and to implement more simulation models to analyze causes, effects and solutions of other type of disturbances.

Fig. 1 .

 1 Fig. 1. Simulink model used to simulate causes, effects and solutions of harmonics.

Table 1 .

 1 Parameters values used in the simulation model. rectifier dc voltage (V) 900 Capacitor bank capacitance (mF) 0.779 Three-phase rectifier resistive load P (kW) 500 Linear load active power (kW) 60 Three-phase rectifier capacitive load C (mF) 0.1

Fig. 2 .

 2 Fig. 2. Simulation results of the current demanded by three-phase rectifier: (a) waveform; (b) harmonic spectrum.

Fig. 3 .Fig. 4 .

 34 Fig. 3. Simulation results before and after resonance effect: (a) waveform of voltage in PCC; (b) waveform of network current.

Fig. 5 .Fig. 6 .

 56 Fig. 5. Simulation results after implementing the solution: (a) waveform of current upstream in each transformer; (b) waveform of network current; (c) waveform of voltage in PCC.


Eduardo Eusébio
email: eaeusbio@deea.isel.ipl.pt

Mário Jorge De Sousa

Ventim Neves
email: ventim@uninova.pt

Jorge Sousa
email: jsousa@deea.isel.ipl.pt

De

Mário

Risk Analysis and Behavior of Electricity Portfolio Aggregator

Keywords: Aggregation, Risk analysis, Portfolio optimization, Load profiles

de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Electricity generation nowadays presents a greater number of challenges related to reliability, sustainability and security of supply. The use of renewable resources in power generation has been adopted in most OECD countries as an answer to the climate change problems originated by the burning of fossil fuels in the traditional thermal plants to supply the ongoing increase in electricity demand. Portugal has been considered a pioneer country in electricity production from renewable sources and, in 2010, 52% of the electricity consumed came from renewable sources [START_REF] Hossain | Evolution of Smart Grid and Some Pertinent Issues[END_REF].

In terms of the economic model, the electricity industry has evolved from a vertically integrated state-owned monopoly company (not subjected to the normal rules of competition) to a liberalized market where generators and consumers have the opportunity to freely negotiate the purchase and sale of electricity. The liberalization of the electricity market in Portugal to allow entry of independent power producers with long term contracts and the creation of active wholesale and retail markets came in a later stage.

The importance of reducing the level of consumption is very strong. Nowadays the actual economic situation affects all the participants in the sector [2], consumers, producers and "prosumers", many hypotheses to decrease the bill to pay for electricity are considered, such as different energy suppliers, control load programs, load forecasting, smart-grid, smart-metering and smart-box.

This new electrical concepts allows the medium, small consumers and producers to integrate the satisfaction of the power system because they adopted the new distributed generation paradigm, opposed to the traditional power system, composed by medium and large power plants [START_REF] Hossain | Evolution of Smart Grid and Some Pertinent Issues[END_REF] The small passive consumer evolves to an active player, participating in the generation of electricity and the provision of network services. In this context, both aggregators and companies can bring their customers, consumers, producers, consumers and traders to market [3] [4].

In a future with the smart-grids and smart-metering, the development of a new challenge in electric system has occurred, how to integrate these new consumers/producers, known as "prosumers", in this contest a new partner arises in the aggregator company.

Purpose

The scope of this paper is to show how an aggregator company with a portfolio of customers, consumers, producers and "prosumers", can adequately manage its selection of customers in terms of risk and profitability, computing his values. To achieve this purpose presents an adaptation of the theory of investment portfolios introduced in 1952 by Harry Markowitz.

The module CAEM-PA-Commercial Agents in the Electricity Market -Portfolio Aggregator, was created especially to deal with this type of non-financial assets. CAEM-PA gives the values of profitability and portfolio risk for the current portfolio, minimum variance point of portfolio and the layout of the efficient frontier where the optimal portfolios are located. Finally, the simulator computes the best optimum directions, in case the aggregator intends to increase the number of assets, thus allowing him, under negotiation conditions with an hypothetical future customer, to elaborate an adequate price proposal for energy sell.

The module CAEM-PA, also allows to view the matrix of variance-covariance between the assets in the portfolio, and the electrical interpretations that can be done.

Outline

This paper is organized as follows; Section I, provides an introduction on power systems, expected developments and presents the new concepts of aggregators and "prosumers". The second section relates to the topic under study, "Technological Innovation for Cloud-based Engineering Systems". In Section III, following a literature study is made. Some techniques for portfolio evaluation are presented as well as a vision of the future in electrical distribution, regarding in particular the distributed energy resources. Section IV, Presents the methodologies applied to the study and characterizes the assets of the portfolio, consumers, producers and "prosumers", an explanation of the mathematical treatment used to obtain the behavior, risk and profitability, of the aggregator company is also included. Section V, a case study of the portfolio aggregator is developed with the help of the CAEM-PA module. Finally in section VI, the paper ends with some conclusions.

Benefits from Cloud-based Engineering Systems

The new business relationship in the market presented in this study is based in a contractual relationship established between the aggregator and their customers.

Aggregator companies can use the cloud in their businesses as a way to help them expand their current commercial offerings without major investments.

Another important aspect is the effect of the cloud on small and medium size enterprises, the cloud allows them to have unrestricted access to certain geographic locations, which due to cost limitations would not have access, giving them an ability to act globally with a significant reduction in overhead cost.

The cloud also allows overcoming language barriers through centralized translation services and increases entrepreneurship, providing businesses and their collaborators the opportunity to exchange ideas, develop products quickly and economically.

Background

Portfolio Theory

The Portfolio Theory has its origins in the scientific article Portfolio Selection of Nobel Economy Harry Markowitz, a result of his doctoral dissertation [START_REF] Markovitz | Founders of modern finance: their Portfolio Selection[END_REF]. In this article, Markowitz addresses the choice of portfolios of financial assets with uncertain future value, following a criterion completely new at the time: the expected return criterion, variance of returns.

The return was considered to be the only important aspect on an investment without taking account their variability. But in fact, we observe in financial markets that investors consider different portfolios with a variety of assets portfolio without considering only the return that was suggested.

Markowitz intuited that different choices of investors and diversification were based on two notions distinct: the notion of trade-off between return and risk of investments and the notion of interaction between the returns of different assets.

Markowitz then suggests that the return of asset must have two reference measures: its expected value and its risk [START_REF] Markovitz | Portfolio Efficient: Efficient Diversification of Investments[END_REF].

Commercial Agents, Aggregators

Networks of the future based on smart-grids concept evolution have great flexibility, and assume an involvement of the end users known by active demand [7] [8]. This new concept of dealing with energy level consumption, decreasing his level because the aggregator tries to optimize the load diagrams of its customers in order to create an aggregator global load diagram more smooth, more friendly to the systems operation. Charges like water heaters, electric radiators, heat pumps, battery EV's, can be controlled, via communication with "energy box" installed in the customers home. [START_REF] Piette | Development and Evaluation of Fully Automated Demand Response in Large Facilities[END_REF][10] [START_REF] Hadley | Potential Impacts of Plug-in Hybrid Electric Vehicles on Regional Power Generation[END_REF].

An aggregator provides its customers with energy marketing services, see Fig. 2, giving them access to market prices by adding a significant number of loads, at the same time grants the aggregator power negotiation in the electricity market [START_REF] Eusébio | Commercial agent's portfolio optimization in electricity markets[END_REF] [START_REF] Bollen | Adapting Electricity Networks to a Sustainable Energy System[END_REF].

The aggregator makes an energy balance at the level of customers, who have contract with him, including forecasting consumption to meet energy produced and introduced into the distribution system, performing a service of high value to the system operator [START_REF] Lambert | Business Models for an Aggregator-Is an aggregator economically sustainable on Gotland?[END_REF].

The action of the aggregator between his customers (consumers, producers and "prosumers"), and the grid operator, can reduce or adequate the consumption to the production in an active way, that contributes to decrease the dependence from imported electricity and increases the participation of the renewable energy in the local energy mix [START_REF] Lambert | Business Models for an Aggregator-Is an aggregator economically sustainable on Gotland?[END_REF]. The cooperation between aggregator and customers promotes environmental benefits.

Modeling Methodology

The customer portfolio module simulator, that includes several consumers, producers and "prosumers", with aggregator contract for energy supply and purchase, consists in three modules the CAEM-PA (portfolio evaluation), the EMT (energy negotiated) and the FLPP (energy and price forecast).

The CAEM-PA, main inputs are the historical data series of the customer, the contracted prices for sale and/or energy purchase predefined in the contract terms are indispensable; all this information is available (input) allowing, with appropriate treatment, obtain the output (risk, profitability, efficient frontier...), as depicted in Fig. 1. In this paper the principal module of the complete scheme simulator is presented in Fig. 2, with the inputs and outputs of the module CAEM-PA. The profitability and risk of the portfolio for one entire week, 168 periods (hours), are computed, according to equation 1, and for its calculation a set of different scenarios of energy and prices are considered.

( ) = ( ) × =1 (1)
Where E(Rp) profitability of portfolio P, E(Ri) profitability of customer i, in the set of scenarios, and wi the weight of customer in portfolio P, n is the number of customers in portfolio P, finally, i is the type of customers in portfolio.

= 2 (2)
Where σP is the risk or volatility of the portfolio P.

2 = 2 =1 2 + , = +1 -1 =1 (3)
Where σ 2 P is the variance of the portfolio P, σ 2 i is the variance of client i, wi and wj are the weights of the customers in the portfolio and σi,j the covariance between the customers i and j , and n the total number of different type of customers. The efficient frontier of the portfolio is obtained with equations 4 and 5.

min 2 = 2 =1 2 + , = +1 -1 =1 (4)
.

(

) =1 ≥ ( ) =1 = 1 0 ≤ ≤ 1 = 1, 2, 3, … . . , max ( #) = ( ) =1 (5)
.

2 =1 2 + , = +1 -1 =1 ≤ $ 2 =1 = 1 0 ≤ ≤ 1 = 1, 2, 3, … . . ,

Case Study

The case study presented in this research is based on a set of customers as shown on Table 1. Different customer profiles, in one week time horizon, are considered, an example as depicted in Fig. 3. Fig. 4 shows the risk and profitability for the minimum variance point of the customer's portfolio, with risk and profitability value in the left side. The efficient frontier to the customer's portfolio is depicted on the right side.

Conclusions

The module CAEM-PA, of the simulator, is able to deal and model an aggregator customer's portfolio; this tool computes profitability, risk, draws the efficient frontier, localization of the minimum variance point, position on the risk and profitability plan of customer's current portfolio. Besides, for all the significant points it is given the weight of the specific customer type on customer's portfolio composition.

The CAEM-PA, also discusses the increase of the customers number portfolio without any initial client. The aggregator achieves with this tool an important knowledge to create price proposals for negotiation process with potential new customers. In further works, the importance of the variance-covariance matrix is discussed, and the simulator allows to create an historical data with risk and profitability which is useful for VaR (value at risk) computation, as well as the energy quantities traded are developed by the Energy Management Transactions module.

Fig. 1 .

 1 Fig.1. Simulator scheme, main inputs, intermediate data, outputs, for portfolio aggregator, risk and profitability estimation.

Fig. 2 .

 2 Fig.2. Commercial Agents Electricity Market -Portfolio Aggregator, inputs and outputs.

Fig. 3 .

 3 Fig.3. Load diagrams: a) Small photovoltaic producer and b) Small residential consumer.

Fig. 4 .

 4 Fig. 4. Outputs of the module CAEM-PA, a) Minimum variance point with risk/ profitability, b) Efficient frontier of customer portfolio.

Fig. 5

 5 Fig.5shows the risk and profitability for optimum points of customers portfolio, as well as the possible evolution points of customers portfolio when new customers are included, depicted in the left side. A global vision with indication of the composition, weights of the assets, in percentage of the total for the new customer's portfolio composition, is depicted on the right side.

Fig. 5 .

 5 Fig. 5. a) Risk and profitability for the optimum points in de frontier and best points without discard any customer, b) Customers portfolio composition, and weights, for the referred best points.

Table 1 .

 1 Type of customer's portfolio and individual, weight, profitability and risk

		Type	Weight	Profitability	Risk
	Customer A	Consumer	10	42,51	0,47
	Customer B	Consumer	1	39,98	0,46
	Customer C	Consumer	2	39,45	0,48
	Customer D	Consumer	5	39,99	0,46
	Customer E	Consumer	5	32,51	0,55
	Customer F	Consumer	5	39,37	0,47
	Customer G	Consumer	2	37,48	0,52
	Customer H	Consumer	1	39,78	0,47
	Customer I	Producer	1	13,55	0,66
	Customer J	Producer	5	39,74	0,50
	Customer K	Prosumer	10	1,00	1,10
	Customer L	Prosumer	10	22,14	2,09
	Customer M	Prosumer	5	27,37	0,76


Nuno Amaro

Luís Casimiro

João Murta Pina

João Martins
email: jf.martins@fct.unl.pt

José Maria Ceballos

Combined Operation of an Unified Power Quality Conditioner and a Superconducting Magnetic Energy Storage System for Power Quality Improvement

Keywords: SMES, UPQC, Power Quality

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In modern electric grids, power quality is a very important topic, considering the high dissemination of microprocessors and electronic devices, which require a highly stable power connection. In this context, power quality faults like voltage sags/swells, frequency oscillations and harmonic distortion, amongst others, must be minimized or, if possible, eliminated [START_REF]EURELECTRIC: Power Quality in European Electricity Supply Networks[END_REF]. Amongst the several classes of devices that overcome power quality issues, active power filters already play an important role and are expected to be the main contributor to deal with such problems in the future, due to their flexibility [START_REF] Akagi | New trends in active filters for power conditioning[END_REF]. The Unified Power Quality Conditioner (UPQC) is one of the most flexible devices because it consists of a combination of a series and a shunt active power filters, allowing a simultaneous compensation of voltage and current [START_REF] Akagi | Instantaneous Power Theory and Applications to Power Conditioning[END_REF]. The two filters (series and shunt) are connected by means of a DC link with a capacitor. The capacitor is a very important element because it stores energy allowing the DC voltage to maintain a required level, which is determinant in the overall system performance [START_REF]Power Electronics Handbook[END_REF].

Superconducting Magnetic Energy Storage (SMES) systems are one class of devices based on the phenomena of superconductivity that are expected to have more applications in power systems [START_REF] Amaro | SUPERCONDUCTING MAGNETIC ENERGY STORAGE -A Technological Contribute to Smart Grid Concept Implementation[END_REF] [START_REF] Xiao | Development of the World's First HTS Power Substation[END_REF]. By means of a superconducting coil it is possible to store energy and use it whenever it is necessary. Although these devices have a lower energy density when compared to other energy storage systems (like batteries), their power density is very high and the device can be fully discharged in a few milliseconds. This characteristic makes the SMES a power device instead of an energy device [START_REF] Tixador | First Tests of a 800 kJ HTS SMES[END_REF]. SMES can thus be used to address power quality issues and several projects are already running in this area, including voltage sags/swells compensation [START_REF] Kim | 3 MJ/750 kVA SMES System for Improving Power Quality[END_REF], mitigation of frequency oscillations [START_REF] Xian | Minimize frequency fluctuations of isolated power system with wind farm by using superconducting magnetic energy storage[END_REF] and UPS applications [START_REF] Aware | SMES for Protection of Distributed Critical Loads[END_REF][START_REF] Tixador | Design and First Tests of a 800 kJ HTS SMES[END_REF].

The integration of SMES and FACTS (Flexible AC Transmission System) devices has already been discussed and there are several possible advantages in doing it [START_REF] Torre | Improving power delivery through the application of superconducting magnetic energy storage (SMES)[END_REF]. The main advantage resides in the fact that with an SMES it is possible to add real energy storage capabilities to the whole system (SMES + FACTS device), which will increase its performance and applicability [START_REF] Chen | Detailed Modeling of Superconducting Magnetic Energy Storage (SMES) System[END_REF]. Since FACTS devices already contain a DC link, the overall cost of the SMES unit becomes lower because its Power Converter System (PCS) becomes simpler. In fact, the PCS becomes only a chopper converter connected to the DC link, eliminating the necessity to have a bidirectional power converter (rectifier and inverter) in the SMES. Some studies also indicate that through the addition of a SMES unit, it is possible to decrease the power rating of the FACTS device, also decreasing its costs [START_REF]West Coast Utility Transmission Benefits Of Superconducting Magnetic Energy Storage[END_REF].

Considering the various advantages in adding a SMES unit to a FACTS device, a system consisting of an UPQC with a SMES unit connected to its DC link is presented in this work. The system was designed to overcome two different power quality issues: voltage sags and harmonic distortion. Matlab/Simulink simulations are presented to mitigate the aforementioned power quality issues.

Relation to Cloud-based Engineering Systems

The evolution in power systems through the last years is leading to the creation of a new intelligent power grid usually known as Smart Grid [START_REF]Smart Grids -Technology Roadmap[END_REF]. In this new concept of power grid, both energy and information are expected to flow up-and downstream. With the increasing penetration of microprocessors and electronics the requirements for energy quality are also increasing and it is necessary to have full monitoring and control of the grid [START_REF] Ipakchi | Grid of the future[END_REF]. In such context, devices that increase power quality acquire great importance in power systems. This paper aims to contribute to the application of such devices, by presenting a hybrid device, which not only has power quality enhancement capabilities but also provides the possibility to storage energy. Such devices must be fully controllable and their successful dissemination also depends on the success of cloud-based software for security and operation control [START_REF] Zhang | Next-Generation Monitoring, Analysis, and Control for the Future Smart Control Center[END_REF]. In this sense, and considering that all devices present in future power systems are expected to communicate with each other, cloud-based engineering systems are of great importance if smart grids are to be successfully implemented [START_REF] Markovic | Smart power grid and cloud computing[END_REF][START_REF] Yigit | Cloud Computing for Smart Grid applications[END_REF].

System Description

The studied system is schematized in Fig. 1. The series active filter is connected close to the power source and the shunt filter close to the load. Although a different configuration could be chosen, this one allows a better controllability of the DC link voltage [START_REF] Nielsen | A Detailed Comparison of System Topologies for Dynamic Voltage Restorers[END_REF], which in this case is beneficial because there is the SMES unit connected to this link. The shunt filter converter must be bidirectional in order to allow a full controllability of the DC voltage.

UPQC

The UPQC is a very complete device, regarding its ability to deal with power quality issues. The combination of a series and a shunt active filters allows control of current and voltage. Both filters are connected through a DC link that contains a capacitor. The DC voltage in this link must be maintained at a certain level in order to allow full controllability of the system, and to charge the superconducting coil of the SMES unit. The implemented UPQC and its controller are shown in Fig. 2. The pulse width modulation (PWM) signals for the two converters in the series and shunt active power filters are generated according to voltage and current reference signals, respectively. The reference signal for the current in the shunt active power filter is generated following a Synchronous Reference Frame method [START_REF]Power Electronics Handbook[END_REF]. The reference signal (used to generate the PWM signal) of the voltage in the series power filter is generated by a "feedforward" control method, comparing the voltage of the filter to a defined reference value. The DC link capacitor, CDC, has a value of 20 µF, calculated following the formulation presented in [START_REF] Teke | Unified Power Quality Conditioner: Design, Simulation and Experimental Analysis[END_REF].

Power

SMES

A SMES system is composed of three main sub-systems: a superconducting coil, which stores energy in its magnetic field, a Power Converter System (PCS) responsible for the exchange of energy between the coil and the grid where it connects and a Control System (CS) that manages energy exchanges. Fig. 3 depicts the usual system configuration.

Fig. 3 SMES system constitution.

The PCS system usually consist of a bidirectional power electronics interface (with rectifying and inverting capabilities). However, in this specific case, because the SMES is connected to a DC link, only a DC/DC converter is necessary (a chopper converter). The used SMES configuration is depicted in Fig. 4. The superconducting coil was simulated as simple inductance. In a real system, the total resistance of the system might be non-negligible (due to e.g. current leads or resistive contacts), but as a first approach it is not necessary to consider this resistance.

HTS Coil I DC V in + V in - S1 S2 Fig. 4. SMES unit
Since the PCS of the implemented SMES is rather simple when compared to a PCS when the SMES is connected to an AC grid, the control system also becomes simpler because it is only necessary to control the two power electronic switches (in this case IGBTs) that form the chopper converter. The control must allow three different operation modes: charge, discharge and persistent. Charge and discharge mode correspond to charging and discharging the superconducting coil, respectively, and the persistent mode corresponds to a situation where the coil is already fully charged and current flow is maintained in a continuous mode. The control of the switches S1 and S2 defines the operating mode: In a system where the SMES is operating alone, the control of the chopper is very straightforward. The system enters a charging mode till the current in the coil reaches the desired value and then the persistent mode is activated. The discharge mode is used when there is a fault in the grid. However, in the case of a joint operation with an UPQC, the control must take care of other situations as well. The UPQC has a DC link in which the DC value cannot decrease under a certain value, otherwise the shunt filter enters a non-controllable situation [START_REF] Teke | Unified Power Quality Conditioner: Design, Simulation and Experimental Analysis[END_REF]. This means that the charging process of the SMES must take into account the DC voltage value. The persistent and discharging modes operate in the same way as in a regular SMES system.

The main characteristics from the SMES unit simulated in this work are presented in table 1. Such characteristics were obtained following the method presented in [START_REF] Amaro | A Fast Algorithm for Initial Design of HTS Coils for SMES Applications[END_REF]. The maximum stored energy using this coil is 686 J. Using only the capacitor in the DC link of the UPQC, the maximum stored energy was 4.9 J, which strongly limits applications of this system. The addition of a SMES unit allowed greatly increasing stored energy, which means that the system can overcome different kinds (with longer duration) of power quality faults.

Simulation Results

To evaluate the UPQC+SMES system performance, Matlab/Simulink simulations were performed, considering two different kinds of power quality problems: voltage sags and harmonic distortion (addition of 5 th order harmonics). The simulated system is the one already depicted in Fig. 1.

Voltage Sags/Swells Compensation

Voltage sags of different levels were simulated using a three phase programmable voltage source in Simulink. Fig. 5 shows source and load voltages for a voltage sag of 50%, during two and a half cycles (50 ms). It is possible to see that the system successfully compensate the voltage sag, allowing maintaining voltage at the load during the whole period of the fault. The voltage in the DC link of the UPQC, which is used to charge the SMES coil, is shown in Fig. 6. The SMES is charged guaranteeing that voltage does not drops below a specific value, namely 700 V. This was chosen in order to have always a DC voltage above the minimum value that allows full controllability of the power filters, which in this case was calculated as 648 V, following the formulation presented in [START_REF] Teke | Unified Power Quality Conditioner: Design, Simulation and Experimental Analysis[END_REF]. The consecutive voltage drops shown in the figure correspond to the charging process of the SMES. During the charging process, current flows to the superconducting coil, decreasing the amount of power at the DC link, thus forcing the DC link voltage to go down. Fig. 6 also shows the evolution of the current in the SMES system, which decreases around 13 A in order to compensate the voltage sag (the SMES is in discharge mode during this time).

Harmonic Distortion Mitigation

Another important fault that can occur in a power grid is harmonic distortion. The programmable three phase voltage source from Simulink was again used to add a 5 th order harmonic with 0.25 pu content to the voltage signal. This corresponds to a THD of 14.92%. Voltages at source and load for this scenario can be seen in Fig. 7. The system can compensate the harmonic distortion and the load is barely affected by it. The THD at the load is 4.82% during the fault.

Conclusion

A combination of an UPQC and a SMES device was presented in this paper and simulation results indicate that the hybrid system can be used to overcome power quality issues in an electric grid. The addition of an SMES unit to the UPQC has several advantages: by adding energy store capabilities, the SMES increases the application range of the UPQC (in this example, the stored energy increased from 4.9 to 686 J). The overall cost of the UPQC device becomes lower because with the combination of a SMES its power rating decreases. Since the SMES is connected to a DC link, the PCS becomes less costly and the control system also becomes simpler. The control scheme of the full system is very similar to those of the two systems operating alone, with only the additional requirement on the DC voltage when charging the SMES coil.

Two different power quality faults (voltage sags and harmonic distortion of the 5 th order) were simulated and results indicate that the system can overcome those faults, without any noticeable change of voltage and current at the load. Such system can improve power quality in electric grids and thus has a very large spectrum of applications.

Fig. 1

 1 Fig. 1 Implemented system

Fig. 2

 2 Fig. 2 Implemented UPQC

•

  S1 and S2 closed: charging mode; • S1 open and S2 closed: persistent mode; • S1 and S2 open: discharging mode.

Fig. 5 .

 5 Fig. 5. Voltage sag compensation

Fig. 6 .

 6 Fig. 6. Voltage in the DC link and current at the SMES coil during a voltage sag

Fig. 7 .

 7 Fig. 7. Compensation of harmonic distortion in the system

Table 1 .

 1 Characteristics of the simulated SMES unit.

	Characteristic	Value
	Number of pancake coils	4
	Total inductance (H)	0.28
	Rated current value (A)	70
	Total length of SC tape (m)	800


Nuno Vilhena
email: n.vilhena@campus.fct.unl.pt

Pedro Arsénio
email: p.arsenio@campus.fct.unl.pt

João Murta-Pina

Anabela Gonçalves Pronto

Alfredo Álvarez
email: aalvarez@unex.es

Development of a Simulink Model of a Saturated Cores Superconducting Fault Current Limiter

Keywords: Fault current limiters, Saturated-Core fault current limiters, Modern power grids, Smart grids, Short-circuit currents, Superconductivity

Superconducting fault current limiters are considered as emerging devices for the advent of modern power grids. Those limiters as well as other electric power grid applications have been developed in the last years in order to support the increased penetration of dispersed generation. The development of such limiters requires new design tools that allows to simulate those devices in electrical power grids with different voltage ratings and characteristics. This work presents a methodology to simulate the behaviour of saturated core type limiters based on its characteristic curves. A prototype is tested to obtain its characteristic and then the methodology is implemented in Simulink. The simulation carried out by the proposed methodology is compared with a real test.

Introduction

Superconducting Fault Current Limiters (SFCL) have been considering as emerging and attractive devices enabling an increased integration of distributed generation sources in modern power grids, due to their ability to limit fault currents and thus helping to mitigate several operation problems that such grids can experience [START_REF] Moon | A Study on the Application of a Superconducting Fault Current Limiter for Energy Storage Protection in a Power Distribution System[END_REF].

Amongst all different topologies of inductive SFCL, the saturated cores topology [START_REF] Lee | Applications and Related Technology[END_REF], originally proposed in [START_REF] Raju | A Current Limiting Device Using Superconducting D.C. Bias Applications and Prospects[END_REF], involves the use of highly saturated iron cores that can be achieved by a high DC current flowing in a high temperature superconducting (HTS) coil. When the line current exceeds normal operation limits, e.g. due to a fault, the inductance increases abruptly, limiting the current through an inductive voltage drop. In this situation, the cores of the limiter alternate between saturated and unsaturated states.

In the last years, several projects were carried out using this topology. Zenergy Power Company operated a 15 kV three-phase limiter in the Southern California Edison substation and an 11 kV in CE Electric UK substation [START_REF] Moriconi | Development and Deployment of Saturated-Core Fault Current Limiters in Distribution and Transmission Substations[END_REF]. Other company, InnoPower, developed a 35 kV/ 90 MVA device [START_REF] Xin | Development of Core Fault Current Trans[END_REF]. InnoPower has also been testing a 220 kV/300 MVA [START_REF] Xin | Factory and Field Tests of a 220 kV/300 MVA Statured Iron-Core Superconducting Fault Current Limiter[END_REF].

Finite elements method (FEM) software packages are often used to simulate the performance of these devices [START_REF] Shahbazi | Finite analysis current limiter. 1st Conference on Electric Equipment Switching[END_REF]. However, simulating a SFCL with FEM software can take a considerable amount of time, from several hours to days or weeks, even when considering simple devices in very simple grids.

In order to reduce the simulation time and to simulate those devices in more complex grids, a numerical method that can be applied to perform fast dynamic simulations of saturated cores SFCL is proposed in this work and is implemented in Matlab/ Simulink. This methodology is based on the relationship between the linked flux with the primary of the device ψFCL and the line current iline. The dynamic behaviour of the SFCL is thus simulated based on this ψFCL-iline characteristic. This is an extension of the methodology proposed for transformer type SFCL [8-10] and presented in [START_REF] Vilhena | A methodology for modelling and simulation of saturated cores fault current limiters[END_REF] for saturated cores SFCL.

This work also constitutes one of several studies that needs to be addressed in order to answer the following research question:

Are there development methodologies and simulation tools of Saturated Cores Fault Current Limiters, allowing analysing its performance in power grids with different degrees of complexity, and thus contributing to sustained advent of technologies based on superconducting materials?

Integration of SFCL devices in power grids depends also on developing tools to simulate them under different conditions, such as PSCAD or others. This work provides a contribution for such developments.

Contribution for Technological Innovation for Cloud-based Engineering Systems

Electric energy demand has grown yearly, which means that there is a significant increase in the penetration of distributed generation (DG) to satisfy this increase in demand. To make a grid "smart" is essential to manage the future power grids especially from the usage of networked power devices. Smart Grids (SG) offer deep monitoring and controls of the grid but needs advanced analytics to analyse, to process and to storage the considerably big amount of data for safety efficient and reliable operational decisions. In order to project an efficient and scalable SG, solutions and services based on Cloud Computing must be incorporated [START_REF] Bitzer | Cloud computing framework for smart grid applications[END_REF].

In the energy domain, fail-safe power grids are foreseen, ensuring safety and power quality, supporting the coexistence of central and distributed generation, energy storage and bidirectional energy flow. SFCL exhibits several features that make them attractive in protecting network equipment as well as allowing improving network availability, contributing to assure fail-safe grids and thus robust and efficient SG [START_REF] Behzadirafi | Using Superconducting Fault Current Limiters to enhance the reliability of power transmission systems[END_REF].

Proposed Methodology based on SFCL Characteristic

The proposed methodology is based on the magnetic characteristic of the limiter which relates line current iline and linked flux with the primary ψFCL. This characteristic is able to describe the electromagnetic behaviour of the limiter. Equation 1shows the developed voltage drop at the terminals of the SFCL that is directly related with the SFCL characteristic.

dt t di di t d t i r dt t d t i r t u line SFCL line SFCL SFCL line SFCL SFCL ) ( ) ( ) ( ) ( ) ( ) ( ⋅ + ⋅ = + ⋅ = ψ ψ . ( 1
)
Knowing the characteristic of the SFCL, it is possible to develop an adequate computational model for power system simulation software (such as PSCAD or SimPowerSystems/Simulink), that do not rely on knowledge of circuit equations, which is practically unfeasible.

The first step of the methodology consists of determining the magnetic characteristic of the limiter ψFCL-iline. This characteristic may be determined by real tests. Using the characteristic obtained it is possible to implement the SFCL in Simulink, as a variable inductance. Thus, the limiter may be simulated in grids with different complexities and faster than recurring to FEM software.

Operation Principle of the Saturated Cores Fault Current Limiter

Several different geometries of this type of SFCL have been proposed. However the operation principle of the limiter remain the same [START_REF] Raju | A Current Limiting Device Using Superconducting D.C. Bias Applications and Prospects[END_REF]. Fig. 1 shows the basic elements of single-phase saturated cores SFCL.

Under normal operation, AC current in the AC coils creates a magnetic flux that is lower than the DC bias flux, remaining the iron cores highly saturated and making the impedance of the limiter negligible. However, when a fault occurs, the AC current increases abruptly, leading the cores out of magnetic saturation alternately. The line impedance is increased and the fault current is limited.

Experimental test to determination of the characteristic of the SFCL

In order to determine the characteristic of the limiter, experimental measurements were carried out.

Topology of the limiter and experimental apparatus

Fig. 2 shows the dimensions of the laboratory scale limiter used to develop the presented methodology. The core used for the tests was an EI iron core (instead of two separated cores). The AC coils are placed on the outer limbs and the DC biasing coil is placed in the inner limb (which has round cross section) of the core. The magnetic core provides closed magnetic paths for each outer limb. Therefore assure that both outer limbs are driven into deep saturation, their cross sections must be less than 50% of the inner limb core section. In the present case, the outer limbs cross section are 40% of the inner limb cross section. The test circuit comprises a voltage source ug, a line resistor RLine, a load RLoad, a circuit breaker S1 (used to simulate faults) and the SFCL. The AC coils are made of copper wire with 1.3 mm 2 cross section, 100 turns each. A 60 turns DC coil is built from 4 mm-wide first generation superconducting tape. Table 1 shows the parameters of the test grid. More detailed information can be found in [START_REF] Vilhena | A methodology for modelling and simulation of saturated cores fault current limiters[END_REF].

The core must be highly saturated in order to make the impedance of the limiter negligible in normal operation and, at the same time, can not be saturated too deeply since it can goes out the saturation, limiting the fault current. Thus, it is necessary to choose an adequate magneto motive force (MMF) value ensuring that all limbs of the core are saturated. Therefore, 35 A were chosen as DC current, corresponding to a MMF of 2100 A•turn.

Determination of the Characteristic of the SFCL

A test was carried out considering the parameters shown in Table 1. A fault was applied on the test circuit and data was acquired with a data acquisition board to a computer. Fig. 3 shows the individual characteristic ψFCL-iline, associated to each AC coil and the equivalent characteristic of the limiter, obtained by combining the previous ones. When line current is low, dψFCL/diline is also low, thus the line current flows with any limitation. In fault condition, a high dψFCL/diline is reached and an inductive voltage drop at the terminals of the limiter limits the line current.

Simulation of the FCL by the Developed Methodology

The presented methodology is based on the measured characteristic of the SFCL. A Simulink model of the SFCL was built based on its characteristic.

Model for the Dynamic Simulation of SFCL

To simulate the SFCL in Simulink was necessary to build a model that describes the SFCL behaviour according to Equation 1. The model may be built with a dependent current source that imposes a specific current in the line depending on the characteristic of the SFCL. The characteristic of the SFCL is function of linked flux and line current, thus if the linked flux is known the current that the SFCL should impose is also known. Equation 2shows how the linked flux may be calculated, by the integration of the voltage drop over the SFCL uFCL, and subtraction of the resistive voltage drop over the SFCL rFCL•iline. Fig. 4 shows the model in Simulink. The model is composed of a set of blocks that compute the linked flux according to Equation 2, a lookup table block (so-called Psi-i) that computes the current according to the linked flux with the primary of the SFCL, and a dependent current source block (so-called Inject SFCL current) which provides the current in the line.

dt t i
⋅ ⋅ - = ⇔ ⇔ ⋅ - = ⇔ + ⋅ = ∫ ) ) ( ) ( ( ) ( ) ( ) ( ) ( ) ( ) ( ) (

Evaluation of the Dynamic Behaviour of SFCL

To evaluate the behaviour of the SFCL using Simulink software, an electrical diagram was built. Fig. 5 shows this circuit, in the Simulink environment, which is composed of a voltage source, a line impedance, a load impedance, a circuit breaker and the SFCL. The achieved results from the proposed methodology were compared with real tests. Therefore, a simulation using this methodology and a real test were carried out considering ug=50 Vrms, Rline=1 Ω and Rload=20 Ω (to compare the simulation with the real test the line and load are considered purely resistive). The internal resistance of the SFCL is RSFCL=0.4 Ω. A short-circuit was applied around t=1.49 s and cleared around t=2.49 s.

Fig. 6 shows the evolution of the line current as a function time, measured and predicted by the proposed methodology. Both curves show similar behaviour and good agreement. The fault current was limited to around 75% of the prospective current.

Fig. 7 shows the voltage drop of the SFCL as a function of time. As depicted, when a fault occurs the voltage drop increases and the fault current is thus limited. At normal operation, the voltage drop is less than 10% of the voltage power source.

6

A methodology behaviour the saturated SFCL in an in The experimental advantage is a decrease times when compared simulating these devices in complex grids, which is one requisite of utilities. Future work passes by including DC current explicitly in the ψFCL-iline curve expression.

Fig. 1 .

 1 Fig. 1. Single-phase saturated cores SFCL conceptual diagram. It is composed of a HTS DC coil embracing the cores and two conventional AC coils connected in series with the line under protection wound on the outer limbs.

Fig. 2 .

 2 Fig. 2. Dimensions of the iron core of the limiter. All dimensions are in millimetres.

Fig. 3 .

 3 Fig. 3. Measured ψFCL-iline characteristic of each AC coil and calculated SFCL characteristic.

Fig. 4 .

 4 Fig. 4. Simulink model for the SFCL implementation.

Fig. 5 .

 5 Fig. 5. Test grid implemented in Simulink.

Fig. 6 .Fig. 7 .

 67 Fig. 6. Comparison between measured and predicted currents in the circuit under a fault. (a) the occurs (b) the removed.

Table 1 .

 1 Characteristics of the test grid.

	Grid	Description	Value
	ug (V)	Voltage source	100
	f (Hz)	Frequency of the electrical grid	50
	RLine (Ω)	Line resistance	1
	RLoad (Ω)	Load resistance	20
	IDC (A)	DC bias current


David Inácio

João Murta Pina

Mário Ventim Neves

Alfredo Álvarez

Disc Motor with Rotor Made of Aluminium or Polycrystalline High Temperature Superconductor

Keywords: High temperature superconducting motor, polycrystalline YBCO, axial flux disc motor

The discovery of the superconductivity and the understanding of electromagnetic properties of high temperature superconducting (HTS) materials allowed the optimization and development of several applications, such as electrical machines and drives. Electromechanical conversion devices based in HTS materials potentially allows for reduction in devices dimensions or performance improvement for the same active volume, when compared with their conventional ones.An axial disc motor with high temperature superconductor (HTS) material or conventional aluminium in the rotor and conventional armature has been designed and developed. This paper describes simulations and laboratory experiments performed at liquid nitrogen temperature (77 K) in order to analyze the motor's behaviour and its electromechanical characteristics and to define an electric equivalent circuit that allows describing its operation. From the obtained results it was observed that the tested HTS behaves as a conventional hysteresis motor even though with a different nature. On the other hand, the motor with aluminium rotor behaves as a conventional induction motor. In asynchronous regime, the HTS motor exhibits a constant torque, higher than the conventional aluminium one.

Introduction

In 1911, Kamerling Onnes found a new state of matter in mercury, which exhibited electric resistance when cooled bellow 4.2 K. This was named Superconductivity [START_REF] Kamerlingh-Onnes | The Superconductivity of Mercury[END_REF]. The interest in these materials was accentuated by the discovery of High Temperature Superconductors (HTS) possible to cool by relatively cheap liquid nitrogen (77 K). Research on these materials have lead to the optimization and development of several power systems. HTS material have been used e.g. in machines, both as tapes or bulk. The HTS YBCO compound (with a current density up to 10 7 A•cm -2 at liquid nitrogen temperature) has been applied in electrical machines, such as hysteresis [START_REF] Barnes | Finite difference modelling of bulk high temperature superconducting cylindrical hysteresis machines[END_REF], reluctance [START_REF] Kovalev | High output power electric motors with bulk HTS elements[END_REF], or trapped flux motors [START_REF] Miki | Influence of AC Magnetic Field on a Rotating Machine With Gd-Bulk HTS Field-Pole Magnets[END_REF]. The former present a complex behaviour, showing both synchronous and asynchronous regimes, similar to hysteresis conventional motors, although the operation principle is different [START_REF] Barnes | Finite difference modelling of bulk high temperature superconducting cylindrical hysteresis machines[END_REF]. The ability of trapping high magnetic flux, transporting high current densities, and its diamagnetism phenomena and hysteretic ability made HTS materials attractive, presenting reduced size and losses, for the same power, relatively to its conventional counterpart [START_REF] Inácio | Numerical and Experimental Comparison of Electromechanical Properties and Efficiency of HTS and Ferromagnetic Hysteresis Motors[END_REF]. This lead to the research question "does polycrystalline HTS hysteresis motors show better electromagnetic characteristics than aluminium ones?".

Relationship to Cloud-based Solutions

The study of an axial flux disc motor with the rotor in HTS polycrystalline material or aluminium , for several poles pairs configurations is preformed in this paper . All the obtained results could be shared in a cloud-based system allowing other researchers to perform analysis, and providing data backup an on-time data monitoring.

Developed Motor

Typically, the output power of rotating machine, Pout, may be expressed according to (1) [START_REF] Vajda | Requirements for the industrial application of superconducting rotating electrical machines[END_REF], where Bg,max is the maximum airgap flux density, Ag,max is the maximum stator linear current, Nmec is the rotor speed and V is the active volume. The use of superconducting materials allows a higher flux density in the airgap, increasing the developed power.

, max ,max out g s mec

P B A N V ∝ ⋅ ⋅ ⋅ (1)

Topology

The built disc motor, is composed by two 20 cm diameter conventional semi-stators with 24 slots, a coil pitch of 4 slots, 24 conventional cooper windings each one, a steel shaft, a 20 cm diameter rotor disc, which can be aluminium or YBCO, two support bearings and fixing screws. The mechanical transmission is carried by conventional bearings dryed by ultrasounds. Further details are given in [START_REF] Inácio | Conventional and HTS disc motor with pole variation control[END_REF].

Electromagnetic Characteristics

When stator is energized, it produces rotating magnetic field. This field magnetizes the rotor. For the aluminium rotor, the behaviour is known. For the HTS rotor, the field magnetizes the HTS material, which is penetrated with magnetic flux that is trapped in the pinning centres, inducing the same stator's poles number. Due to this, the superconductors' rotor rotates synchronous with stator field, acting as a magnet.

For load values lower than the maximum motor's torque, it runs with synchronous velocity. In steady state, there is a constant relative angle between the stator's and the rotor's magnetic field, which origins a constant motor torque proportional to the product of the amplitudes of two fields with the phase between them. For values of load higher than the maximum motor's torque, flux flow is present, and the motor runs with slip. The torque is proportional to the HTS materials losses.

Simulations

The motor was simulated with a commercial 2D finite elements program (Flux2D from Cedrat). The 2D limitation implied the simulation of a linearized version of the motor, considering longitudinal infinite continuous periodicity to avoid edge effects.

All the non-HTS materials, (copper, aluminium and steel) were defined using Flux2D libraries. The HTS material was parameterized based in the E-J power law, with the parameters indicated in Table 1. HTS motor was analysed for 1, 2 and 4 pole pairs. Transient dynamic simulations were performed. Motor startup is shown in Fig. 1 a), and force dependence on imposed velocity in Fig. 1 b), for no load conditions. From Fig. 1 a), it is possible to confirm that the motor with aluminium rotor exhibits an asynchronous behaviour while the motor with YBCO rotor presents synchronous behaviour. From Fig. 1 b) it is possible to conclude that both motor's developed a linear force proportional to the pole pairs, being higher for the YBCO motor, when compared with the aluminium. In YBCO motor, for synchronous speed the linear force tends to zero, due to the no-load assumed conditions.

Experimental Tests

In order to develop a model for the motor blocked-rotor, no-load and load tests were performed for aluminium motor while for the HTS rotor only blocked-rotor and load tests were performed, as this is a synchronous motor. The experimental apparatus consisted in a 3-phase power transformer; electrical and mechanical power measuring modules; and a DC machine, load cells and optical sensors for mechanical torque and speed measurements using the mechanical power module. During tests only the disc motor was immersed in liquid nitrogen inside a styrofoam box. All the apparatus are shown in Fig. 2.

The motor was supplied by a wye connected 23 V, 50 Hz source for 1, 2 and 4 pair poles configuration. The mechanical load was based in a DC generator (controlled by two DC power supplies and a control resistor) driven by the motors' shaft and feeding a resistive load. The classic equivalent electrical circuit of the motor with aluminium rotor is shown in Fig. 3. From [START_REF] Jung | Characteristic analysis of hysteresis-type Bi-2223 bulk motor with the use of equivalent circuit[END_REF], the HTS rotor's motor can be described using the equivalent electrical circuit present in Fig. 3, where rs, rr and rfe are the semi-stator's winding, the rotor's equivalent and the equivalent iron losses resistances while Xs, Xr and Xm are the semi-stator's, equivalent rotor's and magnetizing reactance's.1

Aluminium HTS (YBCO)

A R r r s r r B R       - s s r r 1 ( ) s r r - 1
Fig. 3. Equivalent circuit for Aluminium motor and HTS (YBCO) polycrystalline bulk motor.

Results from the blocked-rotor, no-load and load tests of the aluminium rotor (line current, I, line tension, Uc, the 3-phase electric power supplied, Pele, the measured torque, T, and the mechanical rotor's velocity, N,) were used to determine the parameters of the equivalent electrical circuit, and are synthesized in Table 2.

Concerning the HTS motor, parameters derivation was based in the parameters of aluminium motor since the HTS motor has the same semi-stators and supply system. The value of the magnetic losses, rfe, was calculated based upon a similar induction motor case and considered the same for the both cases. The theoretical analysis of the HTS motor, allowed defining the magnetization reactance, Xm, rotor's resistance, rr, and rotor's dispersion reactance, Xr, as indicated in (3) -( 5). The parameters used in (3) -( 5) are detailed in Table 3.

2 0 2 2 2 p l r r m N k X g i o ph w m ⋅ ⋅ ⋅ - ⋅ ⋅ ⋅ ⋅ = π µ ω (3) ( ) ( ) ( ) δ π
µ µ ω sin 2 2 0 2 2 2 p t r r m N k r r r i o ph w r ⋅ ⋅ ⋅ ⋅ - ⋅ ⋅ ⋅ ⋅ ⋅ = (4) ( ) ( ) ( ) δ π
µ µ ω cos 2 2 0 2 2 2 p t r r m N k X r r i o ph w r ⋅ ⋅ ⋅ ⋅ - ⋅ ⋅ ⋅ ⋅ ⋅ = (5)
The analysis of equivalent circuit present in Fig. 3, allows conclude that the input impedance, in Z , is given in (6), being s Z the stator's impedance, T Z the transversal impedance and r Z the rotor's impedance.

( ) (

)

     + ⋅ - + ⋅ = = + = + = r r r r m fe T s s s r T s in jX r s s r Z jX r Z jX r Z Z Z Z Z 1 // , // (6)
From the blocked rotor test, it's possible to obtain in Z . Solving [START_REF] Inácio | Numerical and Experimental Comparison of Electromechanical Properties and Efficiency of HTS and Ferromagnetic Hysteresis Motors[END_REF] in order to r Z it's possible to obtain the values of r µ and δ , which are present in Table 1. Using the values indicated in Table 3 and equations ( 3) -( 5) it's possible to predict the values of Xm, rr, and Xr. They are indicated in Table 2 for 2 and 4 poles. As is possible to observe, the impedance is inversely proportional to the square of the number of pair poles. For 8 poles the current "asked" to the power supply exceeds the maximum available (25 A). For that reason, we only perform the experimental tests for 2 and 4 poles. The theoretical electromechanical characteristics were computed, based on the experimentally obtained parameters and using the theoretical analysis above described, and compared with the experimentally obtained characteristics in tests. In Fig. 4 is shoed the comparison between the torque produced in the aluminium rotor's motor and YBCO rotor's motor. As is possible to observe, the experimental characteristics tend to evolutes coherent with the theoretically predicted ones.

Comparing with the simulated results, it's possible to conclude that the studied motor behaves as expected, however with lower values of torque. It is also important refer that the predicted quantities are related with the torque electrodynamically developed, or internal power, while the measured ones refer to the available quantities in the motor's shaft, which differ from the first ones by the mechanical losses. The main mechanical losses are the viscosity friction in the liquid nitrogen and the friction in the conventional bearings working at low temperature that should be included in the theoretical prediction.

Conclusions

Flux2D simulations allowed confirming that, for different configurations of poles, the HTS motor exhibits a synchronous behaviour in steady state and the developed force increase with the poles pair, inversely to synchronous speed. The comparison of simulated, experimental and theoretical results allows conclude that all the characteristics are consistent each them, being possible to observe both synchronous and asynchronous regimes of the HTS motor. The comparison of the developed torques between the aluminium and HTS rotors showed that even for insufficient operating conditions, due to current supply limitation, the motor in bipolar configuration with the HTS rotor a has a higher torque developed compared with the aluminium one. Nevertheless, in tetrapolar configuration, the developed torque in the former is lower when compared to the conventional motor.

Fig. 1 .

 1 Fig.1. Obtained FEM simulations for a) transitory dynamic and b) permanent regime conditions, for 1, 2 and 4 poles pairs in linear HTS and Aluminium motor, no load conditions.

Fig. 2 .

 2 Fig.2. Experimental apparatus for axial flux disc motor's tests.

Fig. 4 .

 4 Fig.4. Comparison between theoretical and experimental developed torque for aluminium rotor's motor (left side) and YBCO rotor's motor (right side).

Acknowledgments.

  The authors thank to CTS -UNINOVA and FCT (CTS multiannual funding -PIDDAC Program funds) for the financial support for the work.

Table 1 .

 1 Measured and predicted electrical parameters from experimental tests.

	Critical Electrical Field	Ec	10 -4 V⋅m -1
	Critical Current Density	Jc0	4,4x10 7 A⋅m -2
	Induction	B0 = B1	10 6 T
	Exponent	n	15
	Additional Resistivity	ρ0	10 -13 Ω⋅m -1

Table 2 .

 2 Measured and predicted electrical parameters from experimental tests.

	Parameter		Aluminium		YBCO (HTS)
	Polar Configuration	2	4	8	2	4
	rs [Ω]	0.25	0.25	0.25	0.25	0.25
	Xs [Ω]	0.317 0.346	0.325	0.317	0. 346
	Xr [Ω]	0.317 0.346	0.325	0.348	0.004
	rr [Ω]	0.038 0.045	0.039	0.371	0.134
	rfe [Ω]	40.2	41.7	46.1	40.2	41.7
	Xm [Ω]	52.79	12.95	3.26	52.02	13.01
	µ	r	--	--	--	0.0098	0.0103
	δ		--	--	--	46.85	88.29

Table 3 .

 3 Parameters of axial flux disc motor.

	Parameter		Value	Units
	Outer rotor's radius	ro	100	mm
	Inner rotor's radius	ri	10	mm
	Airgap	lg	5	mm
	Rotor's thickness	tr	10	mm
	Winding factor	kw	0.5	-
	Number of turns, per phase	Nph	528	turns
	Frequency	f	50	Hz
	Number of phases	m	3	-