Andreas Pfeiffer
email: pfeiffer@rwth-aachen.de

Matthias Jarke
email: jarke@dbis.rwth-aachen.de

Digital Transformation Within the Emobility Market-Learnings and Insights from Early Market Development

Keywords: Digitization, Digital Transformation, Digitalization, Emobility, Business Model, Business Model Generation, Layered Modular Architecture

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Introduction

Following the ongoing discussion on issues and potentials of digital transformation (DT), one has to conclude that digitalization is dramatically changing market transactions and jeopardizing existing business models [START_REF] Hamidian | DigITalisierung-Status quo[END_REF][START_REF] Hungerland | The digital economy (No. 21e). Strategy 2030-Wealth and Life in the Next Generation[END_REF]. Leveraging the power of digitalization business models have to be innovated quickly and flexibly to survive and compete in the long term [START_REF] Carayannis | Business model innovation as lever of organizational sustainability[END_REF][START_REF] Kagermann | Change Through Digitization-Value Creation in the Age of Industry 4.0[END_REF][START_REF] Kane | Strategy, not Technology, Drives Digital Transformation[END_REF]. Therefore, companies necessarily have to decide whether or not they want to be able to use information technology as an enabler and initiator within the development and transformation of existing and new businesses (Lusch and Nambisian, 2015). Not surprisingly, information systems science ranks research on business models and the impact of information and communication technology (ICT) on business models as a priority task. This task includes questions on ICT's transformative nature, the following impact on industrialization as well as new product and service models. Furthermore, IT support for developing and managing business models is addressed by means of substantiation of conceptual models, graphical representations and the design of software tools for supporting business model development [START_REF] Veit | Business models[END_REF]. Out of managerial perspective research should answer the question how to identify digitization opportunities, risks and costs. Furthermore, the leverage of digitalization opportunities with regard to customer value propositions, remodeling business operations and enlarging business model scope and scale by identifying new customer channels and entering new markets. Answers can only be found by respecting the distinct nature of digitalization which is a sound basis for generativity as well as evoking high complexity in product, services and network partnerships. The ongoing emobility market development, which shows an increasing electric vehicle (EV) market coverage, is an excellent field of investigation for studying the generative potential of digitization and DT. Within a kind of greenfield new technological solutions with a high proportion of digitalized artifacts are introduced into an ecosystem where market participants from different origins, like the automotive, energy, transport and ICT industries, try to stake out their claim. Furthermore, complex digital issues in introducing new technology in "smart energy and transport markets" have to be overcome across industries' borders. Incumbents like the big car manufacturers are under pressure by market entrants that see cars as digital technology platforms and have digital technology at their core [START_REF] Johansson | Ecosystem Changes in the Automotive Industry: Electric Vehicles and the Increased Importance of Network Business Models[END_REF]. Although emobility is currently a market niche, it is already obviously influencing the existing means of transport and underlying business models. Emobility market development shows new technical and digital solutions, creating new business partnerships and encouraging the discussion of existing mobility habits and associated business models. In addition, the convergence of the trend of digitalization, the offer of hybrid products (e.g., product service systems) as well as the role of network partnerships can justifiably be examined in this field of business [START_REF] Fazel | Akzeptanz von Elektromobilität: Entwicklung und Validierung eines Modells unter Berücksichtigung der Nutzungsform des Carsharing[END_REF][START_REF] Westphal | Steigerung der Attraktivität von Elektroautomobilendurch neue Produkt-Service-Kombinationen[END_REF].

As a first research outcome, this paper presents a generic classification of digital artifact integration in electric vehicle supply equipment (EVSE) and resulting possibilities for emobility service provider (EMSP) to develop business models. Furthermore, the study recommends utilization of the LMA for identification of digital technology enhanced business services. Additionally, the results strongly support the assumption that EMSP value creation, capturing and business model sustainability are highly reliant on the grade of digitalization within the business model. Finally, LMA and Service-oriented Architecture (SOA)-concept are proposed to enhance business model generation in digitally transforming ecosystems.

Methods

This research is based on design science [START_REF] Hevner | Design science in information systems research[END_REF]) and the design science research methodology [START_REF] Peffers | A design science research methodology for information systems research[END_REF]. A case study was conducted in autumn 2015 including a set of workshops. These were focused on investigating new business models for emobility products and services deployment based on EVSE and digitalization opportunities. In a first step, the deployment of EVSE at the industry-partner side was analyzed from early 2009 up to mid-2015 utilizing an adoption of the business model canvas (BMC) method [START_REF] Osterwalder | Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers[END_REF]. The used adoption of BMC was focused on an elaboration of general services and infrastructure (physical, personnel, digital) relations as well as the related value proposition evolution over time.

This was meant to be the starting point for future business model development as an EMSP. Reflecting the emobility market situation up to 2015, emobility service provider EMSP business is defined as a combination of charging-services operators' (CSO) and charging-services providers' (CSP) business. An EMSP thereby is a company running its own EVSE network and providing charging and information services for EVs regardless of whether they provide these services within their own or in foreign EVSE networks. By delivering these services, they create value for EV B2C and B2B users and in value chains through B2B2C network business.

State of the art

The theoretical basis is enabled by an extensive review of the literature on digital artifacts, digital technology and digitalization. This supports the conceptual arguments and addresses the objective to derive insights into "digital nature" and their influence on business model generation. Therefore, as an important precondition, the state of the art regarding the nature of digital artifacts and digital technology has been analyzed. Furthermore, the literature on DT is evaluated to work out relations, impacts and opportunities for business models and business model generation. A general definition of a business model and a simple but effective classification model will be the conceptual bases for evaluation of digital technology's impact on business model opportunities within the emobility market development. In this section, the distinct characteristics of digital artifacts, the LMA of digital technology, the core design principles of digital technology as well as a definition for digital infrastructures will be introduced. This will be the basis for the definition of "digitalization" and help to back the understanding of digitalization of business models by providing an understanding and facilitating possibilities through form-giving structures of digitized physical products and services.

Digital Artifacts and Digital Nature

In the context of studying digital artifacts and digital technology, it is important to distinguish them from physical artifacts. With their theory on the nature and identity of technological objects, Faulkner and Runde (2013) presented a well-proven sound basis for identifying digital artifacts, their distinct attributes and design principles. They argue that objects are beside others, such as events and properties, basic kinds of entities.

Regarding them as "structured continuants," they see objects as structured and composed of distinct elements. Technological objects are seen as a subset of objects that is specified by the function assigned to it by members of the human community.

Digitization, Digital Technology and Layered Modular Architecture

Based on this theory, we divide digital technology into digitized and digital artifacts.

The second one stands for nonmaterial, nonhuman technological objects that fulfill all mentioned characteristics of nonmaterial technological objecthood. They result from "digitization" in the narrow sense, i.e., "the encoding of analog information into digital format" [START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF]. Nonetheless, the combination of nonmaterial and material technological objects in the sense of e.g., an iphone application used on an iphone is a digital technology insofar as nonmaterial objects can be embedded into material technological objects. We call the technical process of embedding digital artifacts into material technological objects "digitization" in the broader sense. The results are called digitized or sometimes also referred as digitalized artifacts [START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF]. Consequently, digitized artifacts can be defined as the assemblages of digital and physical artifacts that are recognized as an end product to meet customer needs. Examples of digitized artifacts are everyday consumer products like mobiles and ebooks, but also a full range of industrial equipment, textile or car production robots. As mentioned, digital technology will be further on understood as both digital and digitized artifact, which is seen as a structured and organized arrangement of material and nonmaterial technological objects consisting of computing, communication, interaction and information technologies [START_REF] Bharadwaj | Digital business strategy: toward a next generation of insights[END_REF]. Furthermore, digital technology can be used as an enabling medium for designing and providing digital services offerings [START_REF] Chowdhury | Service Logic in Digitalized Product Platforms -A Study of Digital Service Innovation in the Vehicle Industry[END_REF]. It should be emphasized that according to Yoo et al. ( 2010) the incorporation of digital objects causes physical objects to adopt the characteristics of digital artifacts [START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF], whereby these digitized objects are characterized by distinct trajectories of material and digital artifacts, meaning that the entity no longer follows one unified line of development. Insofar understanding digital, nondigital systems as well as the management of decoupled systems increases the complexity of the development and maintenance of business models within digitally transforming ecosystems (Bharadwaj et al.,201). This can be taken as a key enabler for digitization of technological objects and perfectly describes digital nature's configuration. LMA facilitates the separation of material and nonmaterial entities. It maintains an interoperability among the components by a hierarchical dependence between the layers (see Figure 1). The LMA is designed by four loosely connected but interdependent layers: device, network, service and content. The device layer contains two kinds of technological objects. First, physical hardware units like computer hardware. Second, nonmaterial objects like operating systems providing control and maintenance of the physical machine functionality as well as connecting interfaces to the network layer. Similar to the device layer, the network layer consists of material as well as nonmaterial technological objects, providing a sublayer for physical transport like cables and radio spectrum as well as a sublayer for logical transmission with nonmaterial objects like network standards. The service layer enables direct interaction with users through application programs featuring functionality, like creating or consuming content. The highest layer comprises data like text, sounds or images as well as metadata and directory information about e.g., content's origin and ownership [START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF]. Following Yoo et al., predigital technology is featured by tightly coupled entities (such as books, analog telephone), or as in the case of purely physical or mechanical products (such as mechanical timers, powerlines, sockets) layers do not even exist. Digital technology facilitates through the separation of the four layers a free and individual design in between the different layer levels [START_REF] Nylén | Digital innovation and changing identities: investigating organizational implications of digitalization[END_REF]. Digital technology is delivered intentionally incomplete with temporary bindings across the four layers. It is thereby following the procrastination principle, holding that a digital artifact "should not be designed to do anything that can be taken care of by its users" [START_REF] Zittrain | The future of the internet-and how to stop it[END_REF].

The open and dynamic breeding ground of digital technology, their catalyzing LMA, the fluid character of digital content and a rapid diffusion through the internet triggers unprecedented opportunities of generativity [START_REF] Kallinikos | The ambivalent ontology of digital artifacts[END_REF][START_REF] Zittrain | The generative internet[END_REF].

Generativity here refers to the "overall capacity of a technology to produce unprompted change driven by large, varied, and uncoordinated audiences" [START_REF] Zittrain | The generative internet[END_REF], which creates abundant opportunities for innovating products, services [START_REF] Boland | Wakes of innovation in project networks: The case of digital 3-D representations in architecture, engineering, and construction[END_REF][START_REF] Tilson | Research commentary-digital infrastructures: the missing IS research agenda[END_REF][START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF][START_REF] Zittrain | The generative internet[END_REF] and business models carrying out these innovations and themselves being influenced by "digital nature".

Digitalization and Digital Innovation

After having emphasized the distinct characteristics of digital artifacts, digitization and thereby the nature of digital technology as well as the generativity that is created by digital technology, there is a solid conceptual basis for understanding the impact and challenges for an industry facing digitalization. After having clarified the notion DT, digital innovation and the distinct relation between both notions will be elaborated. Innovation is "a new idea, device, or method," as well as "the act or process of introducing new ideas, devices, or methods" (Meriam-Webster dictionary). Innovation of a new idea, device or method enabled by digital technologies is covered by the notion digital innovation. Further digital innovation includes the process of introduction of just these [START_REF] Yoo | Organizing for innovation in the digitized world[END_REF]. However, we see an innovational character is a sufficient, but not necessary, condition to digitalization. This means that, from the perspective of the sociotechnical microsystem, every DT is conjunct with a kind of novelty due to introduction of new technological artifacts, changing value propositions, operational processes or business model architecture. Nevertheless, an innovation has to cover novelty characteristics to the macro level. DT thereby is not forced to cover the characteristics of innovation. DT can also be performed by a sociotechnical process of introducing well-known digital technology or digitized processes into new fields of application.

Business Model Concept

With the dot.com era came a discussion about and on the concept of business models in science and applied science literature popular. Management scholars tried to find out how business works and how value is created, especially because billions of dollars had been spent on "business models" that later turned out to fail (DaSilva et al., 2014). Since then, researchers and practitioners have made a considerable number of attempts to define, describe and operationalize the business model concept [START_REF] Fielt | Conceptualising business models: Definitions, frameworks and classifications[END_REF]Petrikana et al., 2015). Nevertheless, there does not exist a commonly accepted definition of business models and their conceptual components. Furthermore, the concept boundaries of application differ according to context and conditions [START_REF] Fielt | Conceptualising business models: Definitions, frameworks and classifications[END_REF]. Following Fielt's comprehensive study on business model definitions and concept elements, a business model can be defined out of a generic and holistic point of view in the way that "[it] describes the value logic of an organization in terms of how it creates and captures customer value and can be concisely represented by an interrelated set of elements that address the customer, value proposition, organizational architecture and economics dimensions" [START_REF] Fielt | Conceptualising business models: Definitions, frameworks and classifications[END_REF]

Results

Taking the described role of business models into account, an in-depth analysis of digital technology capabilities and their relation to business model capacities was conducted. As mentioned, the analysis was performed as an over-time evaluation of business development at an Austrian first mover EMSP. It was part of the business model analysis and development process that was meant to guide the company's emobility strategy 2020. In a kind of bottom-up approach, EVSE hard-and software development cycle was structurally captured in the LMA and mapped to the accessible functions within the "EVSE service layer". Onwards it was analyzed to identify physical as well as ICTrelated services using a business model as a model to reflect business value creation and capture opportunities and evolutionary prospects through digitized EVSE technology (see Figure 2).

Digitizing EV Supply Equipment

The starting point of the investigation was the analysis of an EVSE. As a connection point between the EV, energy grid and transport infrastructure, an EVSE is part of the infrastructure to supply a vehicle's battery with energy. It is used to connect EVs to the energy grid and transfer energy from the grid into the car or back. An EVSE is physically connected to parking lots and an essential part of EV transport systems.

Based on an "EV charging use case" for charging EVs on public and semi-public ground, identified functions of the EVSE were mapped in the "EVSE service layer". Existing or generated information assets were afterwards mapped into the "EVSE content layer" to discover content-based service development opportunities. "Energy charging" is the basic physical service that is promoted by an EVSE. To support charging with higher supply power, a rudimentary ICT has to be embedded into the EVSE support "type 2 and Combined Charging Systems (CCS) charging". From historical reflection, it was deduced that a "geoinformation service" as a basic ICT service was established to inform EV drivers about charging possibilities' location and capabilities. Media disruption of the service was performed manually by transferring geoinformation and technical configuration of the EVSE into central registers on websites (see lemnet.org). Later on, in higher stages of integration, this service was part of EVSE management systems. Adding remote ICT management capabilities and embedding communication facilities (Global System for Mobile Communications (GSM) and network protocols) into EVSE (see types 4 and 5) has to be noted as an important step in digitization of EVSE. Interconnection of EVSE bridges the layers of LMA and enables the development of various content-related ICT services as well as ICT-enriched physical services. The automated transfer of geoinformation (e.g., in the first stage as Excel-extractions) as well as "digital authorization services" of customers are a kind of ICT service to ease use of infrastructure. Authorizations for charging are necessary to ensure legal safety issues as well as economic basics. Without ICT, these had to be performed, e.g., by hardware keys or coins. ICT allows in the first step (EVSE type 3) the handling of, e.g., RFID-access cards later on (EVSE types 4 and 5), purely digital authorization via SMS gateways or other internet-based services. This allows a variety of digital "payment services" e.g., usage-based pricing, prepaid or pay-as-you-go models. Digitizing EVSE with interconnection to a central system further enables physical "infrastructure maintenance services" optimization by transferring use or failure notice to the system. Based on this, information maintenance workflows can be performed along with real-time failure or pricing information transfer to customers' devices as well as "EVSE reservation services". Embedding "webservice interaction" capabilities unleashes alongside easy integration of state-of-the-art internal management systems (e.g., demand side and energy management, customer interaction centers, workflow management systems) the possibility seamlessly to interact with third-party systems and thereby a controlled management of EVSE by business partners. Not surprisingly, one can find out by analyzing the content layer that data utilization and information retrieving is highly dependent on the underlying layers. In particular, information assets are lost when EVSE that is not interconnected is used, whereby use of an insular EMSP management with no online connection at least bears possibilities of utilization analysis and usage-based pricing on a subscription base. Through loosely coupling the layer's accessible content that is stored once online, the real potential of digitization can be fully leveraged. E.g., geodata in combination with utilization and availability can be used by third-party services for new value creation in a smart grids context or route planning services within the EV. At the least, it has to be determined that the data are available, compatible and valid. In summary, it can be noted that by embedding digital technology regarding layer independence and using open standards, the variety of services performed or enabled through EVSE rises exponentially. Open standards bridging the first two layers enable an individual design in between the layers and thereby a new product and service development in and with the upper layers (e.g., maintenance optimization, smart energy integration).

Digitalization of Emobility Service Provider Business Model

Focusing on EMSP business, the elaboration of the described technology-based LMA "service layer" was the starting point for a technology-based approach describing generic business models. Following the assumed business model definition, the focused elements for modeling were value creation and value capture. Without conducting an in-detail business model development process, the identified "EVSE service layer" was transferred into value creation core business process services enabled by EVSE functionality. Categorized in material, ICT-related basic and comfort business services (including customer handling), they describe constituent characteristics of the value-creation process of EMSP firms. Thereby, digitization's influence on business model digitalization opportunities in value creation was elaborated and transferred in five generic EMSP business models. Furthermore, related value capture models, flexibility of revenue model change were applied, reflecting technological possibilities. Last but not least, business model scalability and scopability as well as capital expenditure (CAPEX) and operational expenditure (OPEX) were analyzed under the ceteris paribus clause in relation to ICT impact.

The key service to generate customer value in an EV charging use case is the "energy supply" service. To make this service available, physical value generation is needed in the sense of deployment and maintenance of EVSE facilities providing energy supply for EVs. Physical services within the field of "smart grid integration" e.g., grid stabilization, are allocated in comfort physical services with a high degree of ICT impact.

Nonphysical values are purely digital information services (e.g., EVSE geoinformation). These services are in general attached to CSO business, which can further be expanded to create value within B2B2C relations by providing CSO service for third parties [START_REF] Madina | Methodology for assessing electric vehicle charging infrastructure business models[END_REF]. Within this application, EMSP is the supplier to other EMSP or Smart Energy Providers (SEP). SEP act within the smart energy business, optimizing demand and supply within energy networks. Physical services are, beside the basic services, comfort services e.g., active-or demand-side management by managing EV energy consumption [START_REF] Giordano | A business case for Smart Grid technologies: A systemic perspective[END_REF]. Furthermore, ICT-related services like "emobility marketplace connectivity" facilitate third-party customer authorization and media-disruption free data exchange for billing and settlement of transactions [START_REF] Pfeiffer | An E-Clearinghouse for Energy and Infrastructure Services in E-Mobility[END_REF]. Following the general market development and the forerunning business activities of the evaluated industry partner in the beginning of 2009, five generic business models have been deduced (see Figure 3). These correlate in high degree with EVSE digitization.

Simple Business Model "EVSE type 1 and 2".

Early business models (models 1 and 2) were focused on value creation with physical services accompanied by very simple, not usage-based revenue models. Scalability and scopability of these models is low because the switching cost to guarantee better service quality or setting up new services is very high. Digital assets like geoinformation and usage-based prices cannot be leveraged. CAPEX is quite low, due to the very simple infrastructure and no or little investment in ICT necessity. OPEX for these business models is high in the sense of EVSE check-up and sanity-testing due to the cost of having personnel monitoring the infrastructure in the field. Even more, the reliability of EVSE is very low whereby customer satisfaction is low e.g., customers drive to EVSE that are out of order because no online information is available. The cost of usage-oriented price models and optimization of authorization handling in business model 3 forced the embedding of EVSE type 3 technology. While this allowed more flexibility in the refinement of the revenue model, CAPEX and OPEX rose due to ICT integration without enabling further compensation through additional services or customer attraction. Quality of service optimization by integration of digitally guided maintenance on a basic level (e.g., using age of EVSE in combination with usage information) within the system were likely to be achieved.

High Business Model "EVSE type 4".

The next step in the development was models using type 4 EVSE technology, which enabled intra-connected EVSE and application communication. These types of business models offer on the one hand optimization of customer handling on physical as well as digital bases e.g., through integration into company workflows, direct user registration and online status information on the website. On the other hand, quality of service on EVSE sites could be optimized by real-time status information and automation of maintenance workflows. Arising communication costs could easily be recouped through active maintenance management. Nevertheless, these kinds of business models are limited by an insular setup, not realizing opportunities of generating value through ICT-based integration of partner services as well as being unable to seamlessly offer their services in other application fields (e.g., traffic management, smart grid integration). EVSE type 4-based business models have flexible revenue models, an optimized OPEX situation and are under conditions of state-of-the-art ICT architectures, e.g., webservice technologies, characterized by a medium scalability and the business scope can be expanded with medium effort. This in particular is because of having no need to change EVSE in the field that were already equipped with ICT-communication facilities.

High+ Business Model "EVSE type 5".

State-of-the-art business models facilitating EVSE type 5 technology can be classified as highly flexible in scaling business and broadening the scope of business activities in other fields and markets. Leveraging the possibilities of a digital nature, they achieve unprecedented opportunities for offering new ICT-based products and services by associating their physical and digital assets with their own or network partners' services.

While being based on ICT-embedded EVSE they take advantage of LMA architecture, being able to combine any content with any service and device e.g., integrating proved ecommerce techniques into the emobility market. The key enabler is the interconnection of EVSE as devices with a modular EVSE management system supporting loosely coupled standardized interfaces to other systems. This local, decentralized intelligence can be combined with central management systems' capabilities to fulfill smart grid integration services, e.g., to manage charging of EVs' fluctuating infeed from renewable energy sources [START_REF] Giordano | A business case for Smart Grid technologies: A systemic perspective[END_REF]. Even more integration into traffic systems is required to fulfill local authority or car sharing companies' needs in managing parking areas and charging facilities (Beutel et al., 2104). Services like seamless digital customer handling, dynamic pricing, fulfillment of legal informational requirements or the integration of state-of-the-art direct payment possibilities lead to higher customer satisfaction, product differentiation and optimized OPEX. By integration of third-party processes in the value chain up-and downstream, highly efficient interaction with network partners as well as with B2B customers is guaranteed. Finally, even a B2B2C business in the sense of realization of purely CSO business is possible, reducing endcustomer handling obstacles and enabling core business-focused strategies while delivering a high quality and efficient CSO service. Overall, this EVSE type 5 empowers very flexible and different revenue flows from a multitude of resources and customers.

Discussion

This paper has examined the opportunities of digitized technology for business model development and business transformation. The basis was an in-depth analysis of the historical development of ICT-enhanced infrastructure in the emobility charging market based on an application of digital technology's LMA. Originating from the digitization of EVSE, five generic business model types were conducted and analyzed. In a first step, the LMA service layer's digital technology-based services were transferred into a business model description. Value creation as a core element was described by core business process service elements. Further on, value-capturing opportunities and business model evolution prospects were deduced based on the elaborated business process services. Value capturing was therefore categorized into a revenue model, business scope and scale, as well as OPEX and CAPEX of the business model. The investigation showed that basic customer needs-charging services-can be fulfilled by any of the EVSE-based EMSP business model approaches. However-from the customers' perspective-the quality of service and value-added services (e.g., real-time geoinformation) as well as the flexibility of payment and contractual models rises by using digitized EVSE equipment. These effects are ceteris paribus accompanied by higher CAPEX for investment into ICT (EVSE and backend systems). Further, by implementing EVSE type 4 and higher technology, lower OPEX can be achieved through digitally optimized manual processes, e.g., by preventive maintenance or remote assistance.

From the industry partners' perspective, the higher investment in digital EVSE technology and ICT backend systems thereby can be significantly compensated by minimizing manual services processes in the field. In addition to the just mentioned values for customers' quality and flexibility perception and business models' cost structures, further benefits can be achieved. Digital technology-based service enhancement enables higher flexibility of the revenue model (e.g., usage-based tariffs, geoinformation services for third parties) as well as a higher scalability and scopability of the business model itself. As EMSP business models are operating in the emobility market, there are various opportunities for promoting value-added services in the transport and energy market. This underlines the assumption that the digital nature makes product and service boundaries become fluid [START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF]. In the current case, it descends as the digital offspring of EVSE type 5's digital nature. This type of "charging system" is creating unprecedented possibilities for product and service innovation e.g., by promoting services in the energy and transport system (e.g., information services and smartgrid services). Thereby, insights from digital technology's influence on business deployment over time are gained. This provides a fertile ground for deducing learning for future business generation in the emobility market at a highly digitized point of intersection between smart transport and energy markets. Furthermore, it demonstrates the generative character of digital technology and the exploratory design of LMA utilized as a basis for an advanced business modeling in digitized market settings. Applying the LMA's "service layer" within businesses' value proposition design, unprecedented possibilities are generated by digital technology becoming Thus, e.g., already identified customers' issues can be solved (e.g., "Is the EVSE I'm heading for available?," "I want to pay-as-I-go!") or customers' needs that they do not even know (e.g., "Energy price optimization by energy market optimized charging") can be addressed by digital technology-based services. Using EVSE type 5 technology, existing digital services from other fields of application can easily be involved to solve these issues, which brings time-to-market and cost-structure advantages (e.g., use of Google maps and integration of PayPal payment services). Moreover, other fields of application and customers can be addressed, expanding the scope and scale of EMSP business models by detection of EVSE-based business services. Last but not least, the observations suggest gaps in existing business modeling approaches and underling theoretical interpretation schemes of economic exchange in the digital era. It indicates that business modeling within digitized market setups should facilitate LMA and a service architecture-based approach to identify profitable value creation and capturing opportunities. These are often rather characterized by "immaterial" than "material" values and a transcending value creation process. Following the structure of a LMA, the generative digital nature can be leveraged and transferred into business models carrying digital technology into reality. In accordance with the elaborated digital nature, we see flexibility, loose coupling of elements, granularity and modularity as key design principles for business models. Therefore, future directions of research may lead to the application of the "Service-Oriented Architecture" (SOA) concept into business modeling approaches to facilitate value identification through service-oriented business modeling. Taking digital nature-here especially the LMA-and business model concept's service perspective into account, the SOA concept seems to deliver compatible components and methods for analyzing, developing and managing business models in digitally transforming ecosystems. The SOA concept is strictly based on the principles of modularity and granularity. These are fundamental elements of digital nature's generative matrix, enabling better maintenance and development of existing business models, identification of new offerings through flexible recombination of services as well as the exploration of business network partnership by using well-proven SOA methods. SOA's design principles of modularity, loose coupling and standards foster digital technology capabilities: reusability, distributiveness and interoperability [START_REF] Luthria | Service-Oriented Architecture as a Driver of Dynamic Capabilities for Achieving Organizational Agility[END_REF][START_REF] Mueller | Understanding the economic potential of service-oriented architecture[END_REF]. Because of its exploratory character, the study was limited in several aspects by focusing on EVSE technology and analyzing EMSP business models. Thereby, simplifications regarding automotive and energy market integration were applied. For instance, the analysis was conducted reflecting the grid and EV as "black boxes" with interfaces to use EVSE as a physically connected point of grid and EV to deliver and acquire possible services and vice versa. Besides this digital technology, like battery management systems, smart grid management systems, navigation systems or mobile smartphone applications were assumed as ways to interact with the infrastructure but not being part of the investigation. Furthermore, customer's willingness to pay for quality of service and value-added services was not part of the investigation as well as strategic issues regarding customer accountability in B2B2C relationships were neglected.

Last but not least, data security and privacy as well as regulatory requirements should be examined in further research.

Fig. 1 .

 1 Fig. 1. Layered Modular Architecture (Source: Yoo et al., 2010)

Figure 2

 2 illustrates with five types of EVSE and interacting ICT components that influence the loosely coupled LMA layers by digitization of EVSE on service capacities and information utilization. Thereby, utilization of LMA and acknowledgment of the digital nature in the sense of editability, interactivity, openness and distributiveness enable recombination of EVSE and systems as well as interactions with third-party services. By this, innovation can evolve very fast, like adding state-of-the-art webservice-based payment methods to an EVSE without influencing or even touching first-and second-layer technology. From an industry partner's perspective, this has a great influence on customer friendliness and economic efficiency by having no need to work on infrastructure in the field.

Fig. 2 .

 2 Fig. 2. Layered Modular Architecture Electric Vehicle Supply Equipment (Source: own diagram)

Fig. 3 .

 3 Fig. 3. Generic Emobility Service Provider Business Models (Source: own diagram)

  Technological objects can be separated into two categories, material and nonmaterial technological objects. The first possesses a physical mode of being, like office chairs and flipcharts, which have properties of location, mass, shape and volume. Nonmaterial technological objects have a nonphysical mode of being and thus are "aspatial." Non-

	designs and bitstrings, such as computer files. In sum, Faulkner and Runde (2013) pre-that they are transient assemblies of functions, information items or components dis-
	sent three criteria for nonmaterial technological objecthood: continuants combined with seminated over digital ecosystems. Insofar as they are not bonded to an obvious entity
	structure, an agentive function imposed by human communities and a nonphysical and in being distributed the existence of various combinations of digital objects of the
	mode of being. same kind is possible. By this they are borderless, fluid and crucially transfigurable
	An important implication of nonmaterial technological objects is that they may be dis-tinct from material and other nonmaterial "bearers". For instance, bitstrings as a collec-tion of 1s and 0s as such have no spatial attributes and rely on material technological objects, like computers or other nonmaterial objects, like operating systems, to be usa-(Kallinikos et al., 2013). Kallinikos et al. further argue that digital artifacts "are further supported by the modu-larity and granularity of the ecosystems in which digital objects are embedded". In this context, digital artifacts are from Kallinikos et al.'s point of view associated with the
	ble. However, they possess a particular technical identity like material objects. Tech-nical identity thereby depends on the community in which it is "used and/or appropri-ately referenced if (1) it has assigned to it the function associated with that technical concept of modularity in means of objects being relatively independently organized in blocks that constitute a system by "a wider yet loosely coupled network of functional relationships". These blocks are mediated through interfaces that can serve a broad identity, and (2) its structure is such that it is generally able to perform that function" (Faulkner and Runde, 2013). Kallinikos et al. (2013) introduce four significant attributes of these technological non-describe the specific nature of digital objects or what we call the "digital nature". Ex-material objects that they describe as "digital artifacts qua objects". These attributes spectrum of functions. The granularity of digital objects refers to the ingredients from which blocks are made and describes "the minute size and resilience of the elementary units or items by which a digital object is constituted" (Kallinikos et al., 2013).
	amining the ambivalent ontology of digital artifacts, Kallinikos et al. give a broad over-
	view of the existing literature on the ontology and properties of digital artifacts within IS research, concluding that "digital artifacts are intentionally incomplete and perpetu-ally in the making" and "[] they lack the plenitude and stability afforded by tradi-tional items and devices" (Kallinikos et al., 2013).
	Kallinikos et al. elaborate through their studies that digital artifacts can be distinguished
	from physical objects by their editability, interactivity, reprogrammability/ openness
	and distributiveness. The first three attributes concern the operations by which digital
	objects are put together (editability, interactivity, reprogrammability) and the last two
	the ecology of relations within which these operations are embedded (openness, dis-
	tributiveness).
	Editability thereby concerns the possibility to change a digital object constantly by re-
	organizing the constituent elements, by deleting or adding new elements or by modify-
	ing individual elements of the object. Hereby, the logical structure that governs the
	object and the mechanisms of information production and processing are not interfered
	with.
	Digital artifacts are interactive in the sense of offering alternative possibilities of a con-
	tingent nature to activate their embedded functions or to discover the encapsulated in-
	formation items. Interaction does not need to invoke change or modification of the ob-ject. This is facilitated by the "responsive and loosely bundled nature of the items that make up digital objects" (Kallinikos et al., 2013).
	Openness and reprogrammability of digital artifacts describe the accessibility and mod-
	ifiability by other digital objects that are not the ones governing their own behavior.
	This means that the logical structure of digital artifacts can be modified by other objects
	than the ones that govern and manage the mechanisms of information production and
	processing. Thereby, openness is closely tied to the interoperable character of digital
	material, nonhuman technological objects are called syntactic entities and are com-artifacts.
	posed of symbols that are formed by syntactic and semantic rules of the language in As the result of openness and interoperability, digital artifacts are hardly ever contained
	which they are couched. Examples of syntactic entities are research articles, product within a single source or institution. Thus, they are classified as distributive in the sense

  [START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF] in part or as a whole by transformation of individual habits, organizational as well as operational structures through digital technology, including digital artifacts themselves. This can be characterized by a significant change in nature and focus of the business activities needed to acquire new capabilities or markets, and fundamental changes in tasks to leverage competitive advantages[START_REF] Bounfour | Digital Futures, Digital Transformation[END_REF][START_REF] Lucas | Impactful research on transformational information technology: An opportunity to inform new audiences[END_REF]. Following this view, digitalization and DT can be understood synonymously. Hereby, it should be stressed, that digitization and digital technology provide the basis for digitalization and resulting opportunities for improvements of ecosystems' viability. These chances must be transferred into the context of ecosystems (i.e., systems of actors, technology, institutions, information, etc.) to capture value from digitization. Furthermore, the differentiation between digitization and digitalization is underlined by highlighting the sociotechnical perspective, the processual character and the impact on social entities (consumers and producers) and institutions (organizations and markets). In addition, a thorough understanding of digitalization's influence on processes, organizational forms, relationships, user's product or service experience, market coverage, customers and the overall disruptive impact of digitalization is covered[START_REF] Lucas | Impactful research on transformational information technology: An opportunity to inform new audiences[END_REF]. Surely, conjured up by the distinct nature of digital artifacts, digitalization bears generativity and thereby unpredictable combinations of products, services, ways of operating businesses as well as business models carrying out these combinations into a market, creating a good seed ground for innovation[START_REF] Bharadwaj | Digital business strategy: toward a next generation of insights[END_REF][START_REF] Henfridsson | Managing technological change in the digital age: the role of architectural frames[END_REF][START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF][START_REF] Yoo | Organizing for innovation in the digitized world[END_REF].

This phenomenon has recently been intensively discussed in applied managerial literature and science but surprisingly enough a commonly accepted or clear definition and understanding are still missing

[START_REF] Bounfour | Digital Futures, Digital Transformation[END_REF][START_REF] Hanelt | Digital Transformation of Primarily Physical Industries-Exploring the Impact of Digital Trends on Business Models of Automobile Manufacturers[END_REF]

. Besides being mistakenly used as a synonym for digitization-which is, as already shown, a technical process of embedding digital technology into technological objects or the encoding of analog information into digital format-it is often discoursed in context to DT and digital innovation without clarifying the precise relationship between the notions. Applied managerial literature tries simply to describe DT as "the use of new digital technologies (social media, mobile, analytics or embedded devices) to enable major business improvements (such as enhancing customer experience, streamlining operations or creating new business models)"

(Fitzgerald et al., 2013)

.For sure, this definition can be seen as a very operational and holistic target identification. More precisely, Tilson et al. (2010) characterize digitalization as "a sociotechnical process of applying digitized techniques to broader social and institutional contexts that render digital technologies infrastructural"

(Tilson et al., 2010, p. 749)

. Consistently,

[START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF]

point out that by digitalization is meant "the transformation of sociotechnical structures that were previously mediated by non-digital artifacts or relationships into ones that are mediated by digitized artifacts and relationships. Digitalization goes beyond a mere technical process of encoding diverse types of analog information in digital format (i.e., "digitization") and involves organizing new sociotechnical structures with digitized artifacts as well as the changes in artifacts themselves"

[START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF]

. Hence, the notion of digitalization includes the transformational digital nature as "a marked change in form, nature, or appearance" affecting individuals, firms, economies and societies

[START_REF] Lucas | Impactful research on transformational information technology: An opportunity to inform new audiences[END_REF]

  . This definition follows major and well-accepted focal firms' oriented research and practitioner streams (e.g., Chesbrough, 2007; Johnson, 2010; Osterwalder and Pigneur, 2010) explicitly focusing on customer value creation. It understands value delivery included in the value creation process, because "[the] separation of creating value and delivering value [is seen] as a supply-side perspective focusing on producers adding value. Customer (use) value cannot be created without involving the user and considering the use context"[START_REF] Fielt | Conceptualising business models: Definitions, frameworks and classifications[END_REF].As an instrument for strategic analysis and planning, business models are used to explain value chains or lately even more value networks from the perspective of a focal firm in an aggregated form and describe how activities are combined to execute a firm's strategy(Petrinka et al., 2014). Understanding a business model in this form, they can be seen as "reflections of the realized strategy" (Casadesus-Masanell and Ricart, 2010)and as what a company is actually delivering at a certain time. Therefore, business strategy and business models are closely interlinked as business models are part of the strategy work and execution[START_REF] Demil | Business model evolution: in search of dynamic consistency[END_REF]. It is commonly accepted that a firm not only can use the business model concept for reasoning about different busi-

ness models. Even more different business models can be executed in coexistence within a company's strategic portfolio

[START_REF] Trkman | A business model approach to supply chain management[END_REF]

. Thereby, a "business model as a model" is a relevant and useful "manipulable instrument" to help scholars and managers in reflecting what a firm does or could do to create and capture value. Furthermore, it can change its existing models to fit with changes in technology or market conditions (Baden-Fuller and Haeflinger, 2013).

  The later stages of developing type 5 technology enable an enrichment of EMSP business models by promoting new services based on already existing technology in the field. Furthermore, it has to be stated that the digital nature obviously can make its generativity significantly stronger through implementation of open, accessible, interoperable and interconnected technology following the LMA architecture model bringing the layers' borders. To safeguard the business model's sustainability and create a future-proof setup, industry partners' experience suggests strongly that ICT should be embedded at least with state-of-the-art technology acknowledging the LMA. This means to force layer independence, which is not regarded within EVSE for types 1 to 3. In the current case, it is an interconnected infrastructure setup as in types 4 and 5 EVSE based on webservice technology. It has been experienced that it is highly costly and inhibits quick-to-market strategies with solid blocks of soft-and hardware. Even more practice has shown that dump EVSE as well as closed-shop infrastructure systems (up to EVSE type 3) lower business model development possibilities by forcing high changing cost at EVSE deployment sites accompanied by high complexity of managing the different trajectory paths of digital and physical technologies in the field.Overall this paper demonstrates the applicability of digital technology's LMA in the context of business model development. In the current case it was possible to deduct business models value creation and capturing elements based on technology choice. The generic set of EMSP business models can be taken as an impressive proof of digital technology's generative influence on business model's variety. This can be characterized by a high combinability of offerings creating crucially "transfigurable" business models. In line with[START_REF] Yoo | Research commentary-The new organizing logic of digital innovation: An agenda for information systems research[END_REF] it has been shown that the digital transformation in the emobility market setup profoundly influences value creation and capturing options. Digital technology passes on its "digital nature" and business models apparently tend to take shape of borderless, fluid and crucially transfigurable entities. In digitally transforming ecosystems business relevant digital artifacts transmit their inherent appearance to business models. These take over the specific characteristics of editability, interactivity, openness and distributiveness evoking generativity and thereby unpredictable combinations of value creation and capturing. More precisely, it should be stressed in this context that business models are more flexible and future-proof building on digital technology which follows the loosely coupled LMA. Business models utilizing this "digital abstraction layer" enable a mix-and-match of digitized resources (e.g., content, services and material technology) paving the way for generative value creation. This leads to business models transcending industry, product and service borders. Hereby, these business models are prepared to fulfill future customer's needs through evolutionary recombination of existing business model com-

	overview on digital technology and business development from 2009 till 2015.
	6	Conclusion and Outlook
	ponents (e.g., digital and non-digital resources, partnerships). Following this logic
	means to question established views on business model design and business strategy to
	cope with and proactively utilize changes in scale, scope, speed and sources of value
	through digitization (Bharadwaj et al., 2013; Lusch and Nambisan, 2015; Barret et al.,
	2015)
	This study is exploratory in three senses. Being based on the expert knowledge and
	experiences of a pioneering company in the young field of emobility, it provides an


Hans Schermeyer
email: hans.schermeyer@kit.edu

Michael Studer

Manuel Ruppert

Wolf Fichtner

Understanding distribution grid congestion caused by electricity generation from renewables

Keywords: Distribution grid, congestion management, renewable energy 1

Worldwide the increasing amount of electricity from renewable energy sources (RES-E) is challenging the way how electricity systems traditionally work. While conventional power plants used to be located close to major demand centers, a great share of the RES-E capacity installed over the last years is located far away from areas of high demand. In various countries with a strong growth of RES-E this causes an increasing amount of grid congestion both on the transmission and distribution level, for example in Germany.

In this work we analyze congestion events in the distribution grid caused by RES-E feed-in and the resulting curtailment. The analysis is applied to an exemplary distribution grid in Northern Germany which faces frequent curtailment. We characterize observed curtailment events with regard to extent, length and frequency and illustrate the importance of location within the grid. The results are relevant for research on how to decrease curtailment and thus increase RES-E utilization within the distribution grid. Our goal is to provide detailed insights on the occurrence of RES-E curtailment to enable research on how to allocate a more efficient dispatch within congested grid areas and on technologies that can contribute to alleviating congestion.

Introduction

The continuous expansion of renewable energy in the German electricity sector leads to an increasingly decentralized generation portfolio, requiring far-reaching adaptions to the transmission and distribution grids. However, the grid does not expand as fast as the renewable distributed generation capacity (DG), resulting in DG-curtailment due to grid congestion [START_REF] Ecofys | Einspeisemanagement in Schleswig-Holstein[END_REF][START_REF]Monitoringberichte 2009 -2015[END_REF][START_REF]Quartalsbericht zu Netz-und Systemsicherheitsmaßnahmen[END_REF][START_REF]Agriculture, the Environment and Rural Areas Schleswig-Holstein (MELUR): Abregelung von Strom aus Erneuerbaren Energien und daraus resultierende Entschädigungsansprüche in den Jahren[END_REF]. Despite the German Renewable Energy Act, which requires conventional generation capacity to shut down first during congestion, the curtailment of DG increased tremendously over recent years (Fig. 1). As a consequence, an increasing amount of potentially generated electricity from renewable energy sources (RES-E), a clean resource and basically free of marginal costs when wind and photovoltaics are concerned, remains unused.

Fig. 1 shows the ongoing trend of increasing curtailment of RES-E over the recent years. In 2014 alone, the same amount of energy was curtailed as it had been during the years 2009 through 2013 in aggregation. This trend is continuing in 2015, as curtailment in the first three quarters of the year has already exceeded 2014's total value. The majority of curtailment concerns wind onshore power plants (85%), followed by photovoltaic (9%) and biomass plants (6%), averaged over the curtailment in 2009 through the third quarter 2015. Almost the entire sum of curtailed energy is evoked by activities on the distribution grid level, where most of the installed capacity of RES-E is connected to the grid. The most recent report on curtailment by the German Federal Network Agency splits the entity of curtailed energy by 92,2% to the distribution grid and 7,8% to the transmission grid [START_REF]Quartalsbericht 2015 zu Netz-und Systemsicherheitsmaßnahmen[END_REF].

The Federal Network Agency has acknowledged recent developments by increasing the frequency of their monitoring reports on grid and system stabilizing measures from a yearly to a quarterly basis. Even though these public figures are vital to get an overall understanding of the current development, quarterly figures per federal state, are insufficient for in-depth analyses. In order to investigate congestion events and develop solutions for improving congestion management measures, researchers require detailed information about occurring congestion events and resulting amounts of curtailment in a high temporal and geographical resolution.

Two reports on behalf of the Ministry of Energy, Agriculture, the Environment and Rural Areas in Schleswig-Holstein and on behalf of the German Federal Ministry for Economic Affairs and Energy, published in December 2012 and July 2014, conducted more detailed analyses of curtailment activities [START_REF]Smart Energy made in Germany[END_REF][START_REF]Agriculture, the Environment and Rural Areas Schleswig-Holstein (MELUR): Abregelung von Strom aus Erneuerbaren Energien und daraus resultierende Entschädigungsansprüche in den Jahren[END_REF]. By comparing up to three different approaches, both papers emphasize the importance of a suitable method to avoid high over-or underestimations when analyzing curtailment. Furthermore, the analyses of these papers show that several databases have to be combined to allow more detailed analyses including a high temporal and spatial resolution. [START_REF] Ecofys | Einspeisemanagement in Schleswig-Holstein[END_REF][START_REF]Smart Energy made in Germany[END_REF][START_REF]Vorbereitung des EEG-Erfahrungsberichts 2014 -Vorhaben IIe[END_REF][START_REF]Agriculture, the Environment and Rural Areas Schleswig-Holstein (MELUR): Abregelung von Strom aus Erneuerbaren Energien und daraus resultierende Entschädigungsansprüche in den Jahren[END_REF] The strong increase of curtailed renewable energy urges for a better understanding of this development in order to develop effective counter-measures. Considering both, the steep increase in 2014 and 2015 as well as the limited temporal and spatial resolution of data in available publications, additional research on this topic is essential. Based on recent research on modelling techniques for distribution grids at the Chair of Energy Economics, Institute for Industrial Production, KIT [START_REF] Ringler | Distributed Energy systems, Market integration, Optimization. Produktion und Energie[END_REF] this paper analyzes a concrete distribution grid covering the federal state Schleswig-Holstein (SH). The amount of curtailed energy in this grid area accounts for roughly half of the total curtailed energy in Germany [START_REF]Agriculture, the Environment and Rural Areas Schleswig-Holstein (MELUR): Abregelung von Strom aus Erneuerbaren Energien und daraus resultierende Entschädigungsansprüche in den Jahren[END_REF].

In order to develop an in-depth understanding of grid congestions and curtailment measures, a temporally and spatially high-resolved database is essential. This allows the disaggregated characterization of the spatial distribution as well as of the frequency and duration of curtailment events. However, currently available data sources cannot fulfill these requirements.

Filling this gap, the proposed method in this paper combines various databases in order to overcome the lack of highly disaggregated data and conducts an in-depth analysis on curtailment activities. The insights provided by the application to the high voltage distribution grid of SH in this work can support the planning of effective grid expansion measures as well as the development and implementation of more cost-efficient alternatives like demand side management or the coupling of the power and heat market.

Methodology and Data

The goal of this paper is the analysis of curtailment activities caused by grid congestions in the considered distribution grid with a high temporal and spatial resolution. In the given case, a high temporal resolution is defined as one-minute intervals. Considering the network structure of a power grid, a spatial disaggregation on the substation level of the underlying electricity grid seems appropriate. Having generated a high resolved database on grid congestion events, the data set can not only be used in order to characterize curtailment activities from a holistic perspective, but also to analyze specific regions over the course of the last years in detail. Due to the large portion of wind energy among the amount of total curtailed energy of roughly 90% [START_REF]Agriculture, the Environment and Rural Areas Schleswig-Holstein (MELUR): Abregelung von Strom aus Erneuerbaren Energien und daraus resultierende Entschädigungsansprüche in den Jahren[END_REF], our approach focusses on wind power and neglects curtailment from other RES-E. The computation of this high resolution database requires the consolidation of several data sources (Fig. 2). Firstly, information about historic curtailment events is essential. Grid operators are obliged to publish information about their feed-in management activities. Looking at the distribution grid level, the quality of available data on curtailment events has significantly improved since 2014: The spatial resolution has increased from substation-level to DG plant-level stating the time interval and reduction level for each curtailment event on a one-minute temporal resolution.

Secondly, detailed plant data is necessary to conclude from the curtailment event data to the spatial distribution and the extent of curtailed energy. Plant data includes geo information, commissioning date and nominal power of all wind power plants in SH.

Finally, the spatial structure of the underlying high voltage distribution grid is crucial in order to match published curtailment events on substation level with affected wind power plants and vice versa. The grid infrastructure was approximated from the overpass-turbo interface [START_REF]Overpass turbo: Grid structure based on Overpass Turbo Interface of OpenStreetMap[END_REF] which relies on data from the OpenStreetMap project.

Fig. 2. Consolidation of different data sources to generate high resolution database (own diagram)

The result of the data consolidation is a database consisting of a grid-node specific time series quantifying curtailed energy on a one-minute resolution. In the following, we describe how the one-minute curtailment signals from single wind turbines are aggregated on a substation level and for the whole distribution grid modelled in this work.

Allocation of wind power plants to distribution grid nodes

In order to aggregate curtailment on a grid node level, we need to know the individual unit's connection to the grid. Since no information is available about where single wind power plants (WPP) are connected to the grid, a heuristic approach based on the location of plants and grid nodes is applied: We assume that WPP are connected to the nearest grid node (Fig. 3). In cases there are several nodes within a plant's vicinity, we only take those into account that do have curtailment events in their record.

In our analyses, a single curtailment event is defined as the action of reducing the maximum feed-in of an arbitrary number of wind plants at a single grid node for an arbitrary duration to a level strictly smaller than 100%. Acknowledging the uncertainty from the above mentioned heuristic approach for the allocation of WPP to grid nodes, we rule out grid nodes that contribute less than 0.1% of the total curtailed energy per year for the computation of the key figures below. Therefore, curtailment events, caused by a single plant allocated to the wrong node, are filtered out.

Calculation of curtailment on a nodal basis

The available publications about curtailment name only the affected plant and duration of the curtailment and not the amount of curtailed energy. In order to calculate the curtailed energy, it requires the potential electricity generation of each plant during curtailment, as if there was no curtailment. A very simple approach would be to use the rated turbine capacity as proxy for the generation potential during curtailment events. However, it can be considered very unlikely for all WPP to be generating at nominal power at the same time, even during times of curtailment when high wind speeds occur. The power duration curve of any wind power portfolio tends to change with increasing portfolio size in such a way that high capacity factors become less likely (Fig. 4). Fig. 4. Schematic power duration curve of a spatial distributed wind power plant portfolio [START_REF]Power Duration Curves of Wind Power Plants[END_REF] Therefore, we apply a hypothetical feed-in-level during curtailment below the rated turbine capacity in the following. We assume that curtailment activities take place during hours with the highest generation level of WPP. To quantify the potential power generation during those hours, we employ the concept of the maximum amplitude of renewable supply (MARS) (compare [START_REF] Schermeyer | Review and Extension of Suitability Assessment Indicators of Weather Model Output for Analyzing Decentralized Energy Systems[END_REF]):

= 1 ( -) � |� 1 ≤ 2 ≤ ⋯ ≤ ≤ ⋯ ≤ �; = � ∈ ℕ| ≤ 100 � ; < 100 (1)
1 … denote the elements of a curtailment-event time series and the number of elements within the time series. The α-quantile is defined as the ratio of time steps with curtailment to the total number of time steps.

The subsequent calculation of the MARS requires the wind generation time series of the analyzed wind portfolio. This data is not available for the grid area of SH-Netz. However, it is available for the wind portfolio within each of the four German transmission grid operators. We choose the WPP portfolio of the transmission grid operator Tennet, which is the transmission grid operator covering SH. The area covered of Tennet's grid is significantly larger than SH and the wind portfolio has a much greater capacity (12.288MW [START_REF]EEG-Anlagenregister[END_REF] vs. 3.373MW [START_REF]MELUR): Energiewende und Klimaschutz in Schleswig-Holstein. Ziele, Maßnahmen und Monitoring[END_REF] in 2012), but no better data of a more similar WPP portfolio are available to us. Hence, the hereby calculated MARS should be regarded as a rough approximation.

The resulting equation to compute the curtailed energy Wn,t is shown in [START_REF]EEG-Anlagenregister[END_REF]. It incorporates the reduction level Ln,t at node n and time step t, the nominal power Pmax,I of the respective WPP as well as MARSnorm which is the MARS normalized by the aggregated rated capacity of the underlying WPP-portfolio.

, = ��1 -, � * * , 60 =1 * (2)

Results

By applying the above explained method to the introduced data sources, time series with a high temporal and spatial resolution representing the historic curtailment events in SH are generated. This chapter summarizes these results, presenting insights on the characteristics of renewable curtailment in a German distribution grid.

One key result of this paper is the spatial representation of curtailment events. Table 1 summarizes the main findings on the temporal characteristics of curtailment events. The results clearly show an upward trend in renewable curtailment during the years 2012 till 2015. The number of curtailment events has almost increased by 400% from 2012 to 2015 while the number of affected nodes has more than tripled. Therefore, not only more nodes are affected, but also the average number of events per node has increased. At the same time the average duration of a single curtailment event has risen from less than two hours to 14.6 hours. Fig. 5 shows the frequency distribution of the duration of curtailment events for the years 2014 and 2015. In 2014, almost a third of the curtailment events had been shorter than two hours while more than 80 % of all events are in the time interval with a maximum of 12 hours. Less than 10 % of the events lasted for longer than a whole day. In 2015, the share of events that were shorter than two hours decreased to 22 % while almost a third of the events were longer than 12 hours. In addition, the number of curtailment events that lasted longer than a day increased significantly. The results of the evaluations summarized in Table 1 and Fig. 5 identify two significant drivers of the observed, steep increase in curtailed energy presented in Fig. 1: Both the total number of curtailment events and the duration of the events are growing over time.

While Table 1 represents different metrics to characterize the duration of curtailment events, Table 2 summarizes the amount of curtailed energy resulting from the computations and gives reference values for validation. In the first scenario "High", the curtailed energy is computed based on the nominal power for all curtailment events. This scenario overestimates the reference values in two out of 4 scenarios. For 2013 and 2014, the scenario reaches less curtailment than reported and for 2012 it almost reaches the published level, despite assuming that all WPP would run at rated capacity during all curtailment events in this scenario. This is a surprising result and suggests that either the published data on curtailment events for the years 2012-2014 miss quite a few of curtailment events or the published sum of curtailment for those years is flawed. The "High" scenario overestimates the curtailment for 2015 as expected.

The second scenario "Realistic" uses the MARS based on the power duration curve of the Tennet WPP-portfolio (application of Tennet WPP portfolio discussed above in section 2). While applying the MARS increases the difference between calculated and published yearly curtailment-sums in 2012-2014, it yields a tremendous improvement for 2015. As expected, the MARS based on the Tennet portfolio is smaller than the fitted MARS for SH, which was calculated in such a way that applying it would yield exactly the published values. This does not come as a surprise, since the much greater wind portfolio in the Tennet region produces far less extreme values compared to a smaller portfolio or even single wind parks (compare Fig. 4). Hence, the MARS based on a large wind portfolio tends to be smaller than a MARS based on a small wind portfolio. This is confirmed by the underestimation of our results presented in Table 2. While the fitted MARS in 2015 of 0,56 appears to be in a realistic magnitude, values greater than the Tennet-based MARS or even greater than 1 suggest missing or wrong data input. Fitted MARS (to match reference value)

[-] 0,95

While applying the fitted MARS would lead to the yearly sum of the calculated time series to match the published values, it would also distort the amplitude of events. The following assessment of results is based on the curtailment time series applying the normalized MARS of the "Realistic" scenario and not the fitted MARS. We presume the missing curtailed energy to stem from unreported curtailment events rather than a higher generation level expressed through the fitted MARS. This poses an important assumption when regarding the results.

A helpful representation of time series data for energy systems analysts is the power duration curve or curtailment duration curve in this case (Fig. 6). Comparing the depicted curves for the years 2012 to 2015, two trends become obvious:

• The number of hours per year during which curtailment activities take place are strongly increasing. The number of affected hours rises from roughly 1,000 hours per year in 2012 and 2013 to more than 4,000 hours in 2015.

• Simultaneously, the average curtailed energy per hour has significantly increased. In 2015, curtailment events with up to 1,400 MW of curtailment occur. These insights are valuable when developing alternative applications for excess power in case of grid congestions. Power-to-gas and power-to-heat technologies can use excess electricity to synthesize gas or produce heat [START_REF]Smart Energy made in Germany[END_REF]. These technologies can be applied to substitute fossil fuels in other energy sectors by using the excess electricity from curtailment. While this might not have been economically feasible thus far, the increasing number of hours during the year with curtailment events occurring potentially offer a much higher utilization of those assets than in the past. For example, a power-to-heat unit with 400 MW power input, could have used electricity from curtailment during 2.000 hours of the year 2015, given a location within the grid where it can help alleviate the majority of congestion events. Fig. 6. Curtailment duration curve of wind power in Schleswig-Holstein (own calculation) Fig. 7 shows the distribution of the simulated curtailment of renewable energy at the ten most affected grid nodes of the analyzed grid during winter 2015. These results help to identify those areas that are most affected by curtailment and to pinpoint locations where grid supporting infrastructure would add the most value (e.g. storage, power-to-heat, power-to-gas, etc.).

Critical discussion and Outlook

Over the last few years, we observed a steep increase in the curtailment of renewable energy in Germany. Almost half of the curtailment occurs within one distribution grid in Northern Germany, the grid that we are looking into in this work (SH Netz). Despite the rising problem of grid congestions and the resulting curtailments of renewable energy, foremost wind power plants, there have only been few analyses on characteristics of these feed-in management activities.

This paper contributes to this discussion by conducting in-depth analyses of curtailment events within the distribution grid region of Schleswig Holstein, disaggregating the curtailment events on a high temporal and spatial dimension. This enables researchers working on the integration of renewables to get a better understanding of feed-in management activities and the resulting curtailment of renewables. While our results represent a step towards more transparency and data on curtailment of renewable energy, there is still much uncertainty present in our approach:

The public data available on the electricity grid infrastructure that we were looking at in this work is sparse and non-official. Our analysis and results of the years 2012-2013 rely heavily on the assumptions for capacity allocation. The spatial allocation of wind power plants to respective substations is purely done based on distances and ignores the fact that new substations, built only for the purpose of additional wind energy integration, will presumably have more capacity allocated to them. In addition, we focus in our presented approach on wind power curtailment, which represents roughly 90% of all curtailment, and neglect the remaining curtailment which adds additional uncertainty to our results. Furthermore, we used data from 50Hertz as a substitute, due to missing generation data of the Schleswig Holstein wind portfolio, to approximate the theoretical generation potential of wind power during curtailment events as the maximum amplitude of renewable supply.

Our results show that the increased amount of curtailed energy is caused by both an increase in the number of curtailment events as well as an increasing duration per event. From 2012 to 2015, the number of affected grid nodes facing curtailment within the distribution grid has risen from 12 to over 40 according to our analysis. The presented curtailment duration curves illustrate the growing potential for technologies that are able to utilize electricity that is subject to curtailment otherwise. Based in the right location, those technologies are gaining more and more hours of potential utilization.

We expect the increase in curtailment to continue over the course of the next years. Only when the extensive grid expansion projects currently under construction and in planning go online, we expect a reduction of curtailed electricity from renewable energy sources. However, the development over the past years shows that the grid expansion will likely not meet the pace of renewable expansion. Both congestion on the distribution and the transmission grid level have been increasing, leading to a growing amount of RES-E curtailment. Thus, alternative options to grid expansion, like storage, power-to-gas, power-to-heat and demand-side-management gain in importance and should be made applicable for grid congestion in distribution grids through regulation.

Fig. 1 .

 1 Fig. 1. Development of curtailed energy between 2009 and 2015 in Germany [GWh] [8-10] 1

  Curtailment Events:• Geographic information:─ Until 2014: affected substation ─ Since 2014: affected power plant• Time interval • Reduction level [%]Source:[START_REF] Netz | Regionen mit Einspeisemanagement[END_REF] high-resolution curtailment time series Curtailed Plants:• Geo coordinates • Commissioning date • Nominal power [kW]Source:[START_REF]EEG-Anlagenregister[END_REF] Grid Data• Geo coordinates of nodes • Normalized power ratio Source:[START_REF]Overpass turbo: Grid structure based on Overpass Turbo Interface of OpenStreetMap[END_REF]

Fig. 3 .

 3 Fig. 3. Illustrative grid structure and spatial distribution of wind power plants in SH (own diagram)

Fig. 5 .

 5 Fig. 5. Frequency distribution of the duration of curtailment events for the year 2014 on the left and 2015 on the right (own calculation)

Fig. 7 .

 7 Fig. 7. Curtailed energy at the ten most affected nodes for a time period in winter 2015 (own calculation)

Table 1 .

 1 Key figures of curtailment events at wind power plants in the grid of SH-Netz between 2012 and 2015 (based on model input introduced in section 2)

	Key Figures	Unit 2012	2013	2014	2015
	Curtailment events	#	1.039	433	2,500	4,258
	Affected nodes	#	12	10	41	43
	Summarized duration of curtailment events	[h/a] 1.761 1.101 20.901 62.047
	Average duration per curtailment event	[h]	1,7	2,5	8,4	14,6
	Average total duration per year at affected nodes	[h/a]	147	110	510	1.443
	Maximum total duration per year at affected nodes [h/a]	561	341	1.780	4.335

Table 2 .

 2 Calculation of curtailed energy based on the normalized power ratio (own calculation)

	2012	2013	2014	2015

Data for Q3/Q4 2015 was extrapolated from Q1/Q2 2015.

Due date at August 2015