EVs Grid Integration Business Scenarios

Distribution grid planning and operational principles for EV mass roll-out while enabling DER integration

Deliverable (D) No: 2.1

EVs Grid Integration Business Scenarios Author:

Carlos Madina

Version:

4.0

Date:

13.01.2014

www.PlanGridEV.eu

Confidential (Y/N): N The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No. 608957.

D2.1 EV-Grid Integration Business Scenarios

Title of the Deliverable

EV-Grid Integration Business Scenarios

WP number 2 Task title

WP title EV-Grid Integration through EV load management EV-Grid Integration Business Scenarios

Main Author Project partners involved

Carlos Madina / Tecnalia Carmen Calpe / RWE Giovanni Coppola / ENEL Mark Daly / ESB Raúl Rodríguez / Tecnalia Cristina Silvestri / ENEL Eduardo Zabala / Tecnalia Dr. Armin Gaul, Stefan Greve

Editors

WP leader ENEL

Type (Distribution level)  PU, Public  PP, Restricted to other program participants (including the Commission Services)  RE, Restricted to other a group specified by the consortium (including the Commission Services)  CO, Confidential, only for members of the consortium (including the Commission Services) Status  In Process  In Revision  Approved Further information

www.PlanGridEV.eu

150821_AG PlanGridEV_WP2_D2 1_v4 0_submitted_editor.docx


Executive Summary This deliverable D2.1 summarises the outcome from task T2.1, where the business scenarios for electric vehicles (EV) integration into low voltage (LV) and medium voltage (MV) electricity grid are defined. The business scenarios hereby described will be considered in the assessment and gap analysis (WP1) and will serve as a basis for further assessment and development in the project, more specifically, for the needs of the planning rules and operational methods to be taken into account in the planning tool (WP4), for the implementation of the operational procedures (WP5) and for the evaluation of best scenario business case and its economics (WP7). This preliminary work will be extended in task T3.2, where further scenarios will be analysed and considered in the planning tool. When aiming at integrating electric vehicles (EVs) in distribution grids, the distribution system operator (DSO) may opt for either reinforcing the grid or for managing the load (or a combination of both strategies). A number of business scenarios have been selected for the analysis, as presented in Table 1: Table 1: Summary of main characteristics of the different scenarios

Conventional Charge management

Type of charge management

Expected grid reinforcements Non EV-related EV-related Energy flow in EVs that are used to provide services Provider of the service Remuneration scheme

Type of power flow control for 1: Emergency constraint mgt. Forecasted constraint mgt. Real-time constraint mgt. Ancillary services for the TSO Energy trade DER integration

No

None Yes Yes

None

Safe Soft, fleetfocused

Proactive

Smart grid

Massive

Massive, local

Yes Minimal

Minimal No

No No

On/off

Grid  EV

None

EVSE Operator (fleet manager)

Centralised None None None None None

Centralised Centralised None None None None

None

ToU

On/off

Grid  EV

EVSE Operator/EVSP Regulated contract Centralised Decentralised None None None None

Charge modulation

Grid  EV EVSP

Competitive market

Centralised Decentralised Decentralised Decentralised Decentralised Decentralised

1

Centralised control means that the DSO is controlling the charge, while decentralised means that either the Electric Vehicle Supply Equipment (EVSE) Operator or the electric vehicle service provider (EVSP) are taking control.


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•

Conventional, where no load management is considered and EV integration must be faced through grid reinforcements and, generally, investing on widening the existing hosting capacity.

•

Safe, adding soft fleet-focused load management to the conventional grid reinforcements, possibly reducing the effort in widening the hosting capacity only through copper investments.

•

Proactive load management, dealing with massive EV penetration and, thus, minimizing the needs for grid reinforcements.

•

Smart grid, with a granular control of EVs load management that allows for optimisation of hosting capacity, additionally considering the local connection of distributed energy resources (DER) that can benefit from EV penetration, via a positive feedback loop.

Each of these scenarios will strongly be influenced by the regulatory conditions existing in each country. Governments and regulatory bodies should create a framework for personal and company relationships aiming at fostering and improving the aspects which are beneficial for society, such as justice, employment and environmental protection. Therefore, in the case of e-mobility, regulation should promote business models and permit their profitability under global sustainability concepts rather than hindering the EV penetration. Regulation may positively or negatively affect EV deployment in many ways. If regulation is not flexible enough, or the requirements to perform some of the roles are too demanding, business models that can help the electricity system as a whole may never happen. On the contrary, too loose requirements may result in risk for system security. A detailed analysis must be carried out to evaluate which kind of regulatory change and update is needed for an envisioned EV grid integration scenario to take place and let all business actors involved to implement their activities in a profitable way. Requirements should be coherent throughout Europe to allow for interoperability. However, in order to bring solutions to the market as soon as possible, it might be advisable to propose different implementation phases with different targets and requirement levels according to the real evolution of the EV market. Demand response (DR) services related to e-mobility would be traded in a single market, where System Operators would be procuring these services to simultaneously fulfil the following conditions: •

Increase DERs hosting capacity of low-voltage (LV) and medium-voltage (MV) electricity grid.

•

Avoid capital – intensive grid reinforcements, which have an impact on network tariff fees.

•

Sustain EVs loads uptake in the future.

In order to achieve this, many issues should be taken into account, including: •

Competition in electricity markets and in providing core/value-added services.

•

Simplicity or difficulty for electricity consumers to contribute to system operation: administrative barriers, easiness of market mechanisms, cost of participation in the markets.


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•

The setting up of conditions and technical pre-requirements to the EVs behaviour when connected to the network can help maintain system stability and use the EV to the purpose of large scale load management.

•

Remuneration to system operators for their investments in technology enabling large scale load management programmes.

Market should evolve to allow a broader spectrum of participants and mechanisms, for example related to demand participation In addition to regulatory issues, the actual impact of the scenarios will depend on the existing conditions of distribution grids. Although a more detailed analysis will be performed in WP3, a lightweight economic analysis has been performed to give an idea of the economic impact of the different scenarios in distribution grids. Due to the lack of disaggregated data, a country-wide estimation of the impact at the distribution level has been done, which may provide only a partial view of the potential of the scenarios, particularly in the case of the Smart grid scenario. Moreover, the costs of launching each scenario for the DSO must be assessed in more detail to get a better estimate of their potential impacts. Being one of the countries with the most ambitious EVSE installation targets and due to the availability of data, Spain has been taken as an example for the assessment of the economic impact. Under the assumptions considered for the analysis, the Conventional scenario would increase the total costs of the Spanish distribution systems by more than 1,300 million euro. The use of a Proactive scenario would reduce that amount in 19 million euro, with just 4 hours in which EV charging should be managed. By applying an equal distribution of benefits between the DSO, the EVSP (or the EVSE Operator) and EV customers, these latter will receive 3.25 € if they allow the charge to be controlled. As shown in Figure 1, the peak demand in the Smart grid scenario is reduced compared to the Conventional scenario. Therefore, this scenario can help reduce the required investments in distribution grids by about 10%, or about 600 million euro. This amount can then be used to remunerate EV customers (so that their total cost of ownership get more comparable to vehicles using fossil fuels) and EVSPs (so that their business becomes more profitable), incentivise DSOs to use smart operational procedures instead of building new lines and to reduce transmission and distribution (T&D) fees to be satisfied by all electricity consumers. In this scenario, a load management market will be established, so the payment will be based on competitive offers.


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Figure 1: Total demand in distribution grid in January 2020 (Smart grid scenario) For the benefits to be equally distributed (as in the Proactive scenario), the average price to be obtained by EV customers for allowing the EVSP, the EVSE Operator or the DSO to manage their charging must be about 106.51 €/MWh. On the contrary, if the price EV customers demand is the maximum price that can be offered in the Spanish wholesale market (180.30 €/MWh), they will get about 340 million euro and the DSO and the EVSP would get 130 million each.


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Table of contents Executive Summary ................................................................................................................................ 5 Table of contents ..................................................................................................................................... 9 List of figures ........................................................................................................................................ 10 List of tables .......................................................................................................................................... 11 Abbreviations and Acronyms ................................................................................................................ 12 1. Introduction ................................................................................................................................... 13 1.1. Scope and framework of the document ................................................................................. 13 1.2. Structure of the document ..................................................................................................... 15 2. Description of the scenarios .......................................................................................................... 16 2.1. Definition of actors in the business scenarios ....................................................................... 16 2.2. Conventional ......................................................................................................................... 18 2.3. Safe ........................................................................................................................................ 18 2.4. Proactive ................................................................................................................................ 19 2.5. Smart grid .............................................................................................................................. 19 2.6. Summary ............................................................................................................................... 20 3. Boundary conditions for EV integration scenarios........................................................................ 22 3.1. Classification of roles ............................................................................................................ 22 3.2. Market design ........................................................................................................................ 23 3.3. Network operation procedures .............................................................................................. 25 3.4. Remuneration scheme for the distribution activity................................................................ 26 3.5. Demand response .................................................................................................................. 27 3.6. EV infrastructure requirements and accessibility .................................................................. 28 3.7. Network regulation for final users......................................................................................... 28 4. Initial analysis of business scenarios ............................................................................................. 30 4.1. Introduction to e3value methodology .................................................................................... 30 4.2. Electricity demand in the distribution grid ............................................................................ 34 4.2.1. Demand in 2013 ............................................................................................................ 34 4.2.2. Demand in 2020 ............................................................................................................ 37 4.3. Conventional scenario ........................................................................................................... 38 4.4. Proactive scenario.................................................................................................................. 41 4.5. Smart grid scenario................................................................................................................ 44 5. Conclusions ................................................................................................................................... 48 6. References ..................................................................................................................................... 51 6.1. Project documents ................................................................................................................. 51 6.2. External documents ............................................................................................................... 51 7. Revisions ....................................................................................................................................... 56 7.1. Track changes ........................................................................................................................ 56


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List of figures FIGURE 1: TOTAL DEMAND IN DISTRIBUTION GRID IN JANUARY 2020 (SMART GRID SCENARIO) ....... 8 FIGURE 2: GENERAL ELECTRIC MOBILITY BUSINESS FRAMEWORK FOR PLANGRIDEV ................... 13 FIGURE 3: SIMPLE EXAMPLE OF AN E3VALUE MODEL .................................................................. 31 FIGURE 4: ELECTRICITY DEMAND IN SPANISH DISTRIBUTION GRIDS IN 2013 ................................ 36 FIGURE 5: ELECTRICITY DEMAND IN SPANISH DISTRIBUTION GRIDS IN JANUARY 2013.................. 37 FIGURE 6: ELECTRICITY DEMAND IN SPANISH DISTRIBUTION GRIDS IN JANUARY 2020 (WITHOUT EVS) .............................................................................................................................. 38 3

FIGURE 7: E VALUE MODEL FOR THE CONVENTIONAL SCENARIO ................................................. 39 FIGURE 8: EV CHARGE EVENT STATISTICS. SOURCE: GREEN EMOTION ...................................... 39 FIGURE 9: EV USAGE PATTERNS. SOURCE: GREEN EMOTION .................................................... 40 FIGURE 10: TOTAL DEMAND IN DISTRIBUTION GRID IN JANUARY 2020 (CONVENTIONAL SCENARIO)41 3

FIGURE 11: E VALUE MODEL FOR THE PROACTIVE SCENARIO ..................................................... 42 FIGURE 12: TOTAL DEMAND IN DISTRIBUTION GRID IN JANUARY 2020 (PROACTIVE SCENARIO) ..... 43 3

FIGURE 13: E VALUE MODEL FOR THE SMART GRID SCENARIO .................................................... 45 FIGURE 14: TOTAL DEMAND IN DISTRIBUTION GRID IN JANUARY 2020 (SMART GRID SCENARIO) ... 46


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List of tables TABLE 1: SUMMARY OF MAIN CHARACTERISTICS OF THE DIFFERENT SCENARIOS............................... 5 TABLE 2: ACRONYMS .................................................................................................................. 12 TABLE 3: SUMMARY OF MAIN CHARACTERISTICS OF THE DIFFERENT SCENARIOS............................. 21 TABLE 4: GRAPHICAL REPRESENTATION OF MAIN E3VALUE CONCEPTS........................................... 33 TABLE 5 ELECTRICITY CONSUMPTION PER CONSUMER GROUP IN SPAIN IN JUNE 2012 - MAY 2013 . 36


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Abbreviations and Acronyms

Table 2: Acronyms

Acronym BaU B2B B2C CSO DER DG DR DSO EU EV EVSE EVSP GSM IRR LV MV NPV O&M PWM RES R&D SLP ToU TSO T&D UCM V2G WP

Meaning Business as Usual Business to Business Business to Customer Charging Station Operator Distributed Energy Resources Distributed Generation Demand Response Distribution System Operator European Union Electric Vehicle Electric Vehicle Supply Equipment Electric Vehicle Service Provider Global System for Mobile communications Internal Rate of Return Low Voltage Medium Voltage Net Present Value Operation and Maintenance Pulse-Width Modulation Renewable Energy Sources Research and Development Synthetic Load Profiles Time of Use Transmission System Operator Transmission and Distribution Use Case Maps Vehicle to grid Work Package


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1. Introduction 1.1. Scope and framework of the document This deliverable D2.1 summarises the outcome from task T2.1, where the business scenarios for electric vehicles (EV) integration into low voltage (LV) and medium voltage (MV) electricity grid are considered, mainly based on the results of previous projects such as G4V [1] and Green eMotion [2]. The business scenarios hereby described will be considered in the assessment and gap analysis (WP1) and will serve as a basis for further assessment and development in the project, more specifically, for the needs of the planning rules and operational methods to be taken into account in the planning tool (WP4), for the implementation of the operational procedures (WP5) and for the evaluation of best scenario business case and its economics (WP7). The business scenarios are elaborated taking into account the general market framework as suggested by Eurelectric [3], from which the following architecture was elaborated, serving as the PlanGridEV business framework.

Figure 2: General electric mobility business framework for PlanGridEV


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Taking into account the roles and interactions depicted in Figure 2, PlanGridEV will assess different operational methods and planning rules that might be taken into account for sustaining EVs uptake through minimization of grid reinforcements and simultaneous increase of distributed energy resources (DER) hosting capacity. The scenarios hereby described take place in the context of roles and interactions depicted in Figure 2. Referring to such architecture, as an a priori condition, the charging station is field equipment, which provides electricity and access to general services (e.g. not only electricity) to the EVs and the final EV user. Each charging station is power supplied through the electricity network, typically at LV and MV 2 only, thus the Distribution System Operator (DSO) is the System Operator in charge of operating and maintaining the network itself. In such network renewable energy sources (RES) and other DER might be injected, both at LV and MV level. The customer has a business-to-consumer (B2C) relationship with an Electric Vehicle Service Provider (EVSP) allowing service access on a portfolio of charging stations owned by Charging 3 Station Operators (CSO) with whom the EVSP has a business-to-business (B2B) contract. According to different business models for the deployment of charging stations, the CSO might collapse in the role of either the EVSP (competitive deployment model) or the DSO (regulated deployment model), or it can even be an independent entity (fully unbundled deployment model). Two general electricity procurement processes might be established in this context: either the CSO might purchase the energy from an energy supplier and resell it to multiple EVSPs with whom it holds B2C relationships, or the EVSP might purchase energy from the supplier and resell it to final customers. Regardless of the energy procurement process that is established, which depends on the regulation of each EU Member State, the EVSP is the business actor trading core and value-added services with final customers. This means that, when it comes to advanced services such as smart charging, the EVSP is offering such a service after a B2B trade happening in the energy market, or a derivation of the energy market 4 (see section 3.2 hereby). According to this B2B trade, the DSO exposes a load management programme and EVSPs elaborate it in several charging programmes for their final customers. This way, the DSO procures a useful ancillary service when fulfilling its duties of operating and maintaining the LV and MV network.

2

Electricity distribution is a regulated activity, which is performed under a concession in a monopolistic environment. Therefore, all the statements in this report will be referring to the DSO as being a single actor in its concession area. Of course, those statements can be applied to all the DSOs in a broader scope (TSO area, country, EU…). 3

Charging Station Operator and Electric Vehicle Supply Equipment (EVSE) Operator are terms used in different context for the same actor. Both terms will be used in this report. 4

For the purpose of this document, please note that the terms load management and smart charging are equivalent descriptions of the same process in Proactive and Smart grid scenarios: load management is the business process from DSO perspective, while smart charging is the business processes as viewed from customer perspective. In Conventional and Safe scenarios, there is no smart charging happening, as no customer is involved, but only DSO perspective (in Safe scenario).


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This preliminary work will be initially extended in task T3.2, where further scenarios will be analysed and considered in the planning tool. The planning tool will be developed in work package (WP) 4 and novel operational procedures will be tested and performed in WP5. D2.1 will also constitute an input for the grid planning rules (WP6) and for the final business analysis (WP7). When aiming at integrating EVs in distribution grids, the DSO may opt for either reinforcing the grid or for managing the load (or a combination of both strategies). One of the main objectives of WP2, where this deliverable is included, is the identification of business scenarios and technical and economical requirements needed for EVs integration through active load management in LV/MV distribution grids. Therefore, by varying the weight of grid reinforcements and load management, a number of business scenarios have been selected for the analysis. Their description is based on the general framework depicted in Figure 2: •


•


•


•

Smart grid, with a granular control of EVs load management that allows for optimisation of hosting capacity, additionally considering the local connection of DER that can benefit from EV penetration, via a positive feedback loop.

D2.1 describes and analyses these four scenarios, focusing mainly on developing the last two, in order to assess the real benefit of the tools for such a smart integration of EVs. The aim of this deliverable is to be the reference framework for the rest of the project, rather than giving precise calculations.

1.2. Structure of the document D2.1 comprises the following main sections: •

Section 2 describes the four scenarios to be analysed.

•

Section 3 identifies and develops the main regulatory constraints for the EV use in providing services for the grid.

•

Section 4 develops the Proactive and the Smart grid scenarios, which are the ones involving the highest level of EV integration in the grid and IT-based automation and, hence, which are expected to offer the best business opportunities.


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2. Description of the scenarios This section describes the possible business scenarios of EV integration in the grid based on the whole value chain perspective and the analysis effort conducted mainly in G4V and Green eMotion FP7 projects, but it also leveraged the Eurelectric position paper [3]. The general idea is to establish a common basis for the research and development (R&D) effort to be established in this project with regard to the optimisation of EVs integration taking into account DER. The Smart grid and Proactive scenarios will be compared with other possible scenarios with lower proactivity of the DSO, i.e. Conventional and Safe. While all scenarios will be a reference for the whole project activities, Proactive and Smart grid scenarios will be the basis for the later work of this WP and subsequent tasks, including the definition of new operational procedures that might be implemented and supporting planning rules and impacting on the final analysis, roadmap and recommendations of WP7.

2.1. Definition of actors in the business scenarios In order to have a sound understanding of the scenarios and let them be a reference for the whole PlanGridEV project, it is advisable to define the actors taking part in the different alternatives. There are lots of working groups trying to define the framework for the future EV ecosystem. Unfortunately, each of them provides different definitions and names for the several actors and the roles they take in EV business models. The definitions below are based on those working groups and match the definitions used in the business models analysis in Green eMotion: •

Electric Vehicle Supply Equipment (EVSE) Operator: The standard ISO/IEC 15118 [4] defines an EVSE as “conductors, including the phase(s), neutral and protective earth conductors, the EV couplers, attached plugs, and all other accessories, devices, power outlets or apparatuses installed specifically for the purpose of delivering energy from the premises wiring to the EV and allowing communication between them as necessary. For this purpose the EVSE may also include communication to secondary actors”. The EVSE Operator is the business owning or managing the recharging infrastructure and guaranteeing an access to the distribution grid in order to let EVSE provide electricity to the final EV customer.

•

Electric Vehicle Service Provider (EVSP): The EVSP is the “legal entity that the customer has a contract with for all services related to the EV operation” (e-mobility provider in [4]). Therefore, an EVSP offers e-mobility services to EV customers, so that they can recharge their EVs, including the roaming service (eventually at any EVSE across Europe), or benefit from additional services while driving/charging. This provision of services, including the EV charging services (either at home, at work or at any other public parking location), is the feature that characterizes the EVSP.


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•

EV customers: An EV customer is the “party that consumes e-mobility services using an electric vehicle, including electricity and charging services” [3] and the “person or legal entity using the vehicle and providing information about driving needs and consequently influences charging patterns” [4]. EV customers obtain e-mobility services by means of a contract with an EVSP.

•

Distribution System Operator (DSO): The DSO is “a natural or legal person responsible for operating, ensuring the maintenance of and, if necessary, developing the distribution system in a given area and, where applicable, its interconnections with other systems and for ensuring the long-term ability of the system to meet reasonable demands for the distribution of electricity” [5].

•

Transmission System Operator (TSO): The TSO is a natural or legal person responsible for operating, ensuring the maintenance of and, if necessary, developing the transmission system in a given area and, where applicable, its interconnections with other systems, and for ensuring the long term ability of the system to meet reasonable demands for the transmission of electricity. In addition, the TSO shall be responsible for managing electricity flows on the system, taking into account exchanges with other interconnected systems. To that end, the TSO shall be responsible for ensuring a secure, reliable and efficient electricity system and, in that context, for ensuring the availability of all necessary ancillary services, including those provided by demand response (DR), insofar as such availability is independent from any other transmission system with which its system is interconnected [5].

•

Electricity retailer: Electricity retailers are “the present and future companies that hold licenses (or are active on the market – not all countries have licenses) to sell electricity that they produce themselves or purchase on the electricity markets to end users, with whom they have power contracts with fixed locations for the supply” [3].

•

Electricity Market Operator: The Electricity Market Operator is “the unique power exchange of trades for the actual delivery of energy that receives the bids from the Balance Responsible Parties that have a contract to bid. The Market Operator determines the market energy price for the Market Balance Area after applying technical constraints from the System Operator. It may also establish the price for the reconciliation within a Metering Grid Area” [6]. As a result, the market operator is responsible for managing the wholesale electricity market, for calculating the market price and for clearing all market transactions.

•

Telecommunication Providers: The electric mobility system needs to be able to communicate in order to exchange information. This is often carried out wirelessly, e.g. over Global System for Mobile communications (GSM) or 3G. Therefore, infrastructure to enable the communication between the EV, the EVSE infrastructure (charging stations, battery switch stations, etc.) and back-end services need to be provided. Herewith, it becomes obvious that communication standards are crucial for a fully functional system, which enables access to any company that adopts the standard.

•

Metering Operator: It is “the party responsible for metering duties allowing a consumer to purchase electricity on the supply market through the distribution grid. In most countries the role is played by the DSO. The metering information is critical to enable pay-per-use payment models when considered for e-mobility” [3].


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Other actors defined in Green eMotion, such as the Clearing House or the Marketplace Operator are not of interest for PlanGridEV, so their definitions are not presented here, even if they are valuable to perform service interoperability use cases across different EV charging infrastructure.

2.2. Conventional The Conventional scenario is based on the traditional “build and forget” approach to cope with new or increasing electricity demand. This is somehow a business-as-usual (BaU) approach to a new kind of load, such as the one represented by an EV. Under this assumption, the DSO will reinforce the grid when needed, regardless of the e-mobility uptake, and EV customers will be able to charge their EVs as soon as they arrive to the charging spot and without any limitation on the power to be demanded (and, hence, they will not be offered a fee discount as they would in the Proactive or Smart grid scenarios). Therefore, EVs, EVSE Operators and EVSPs will not provide any service to the DSO or other actors (TSO, electricity retailers…). However, in emergency situations, the DSO will be able to cut off the charging by remotely disconnecting the portion of the grid where the relevant EVSEs are located. The communication between EVSE Operators and the DSO is not in place in this scenario

2.3. Safe In the Safe scenario, the DSO will still use grid reinforcements to cope with electricity demand increases due to increasing EV penetration, but it will also use some soft, fleet-focuses load management to reduce the investments, establishing B2B relationships to implement load management programmes, both with EVSE Operators and with fleets operators or other generic businesses having electric fleets and willing to participate to such load management programme. The aim is to reduce the grid reinforcements required as a result of EVs, by establishing a minimum control signal for EVs charging, which could be time of use (ToU) tariffs for grid access fees. This way, the expected electricity demand increase resulting from EV charging can be shifted towards periods when traditional electricity demand is lower and, thus, reduce the need for grid reinforcements. As a result, the DSO indirectly affects the time in which EVs are charged (the fleet manager, which is also assumed to be the EVSE Operator decides the charging time), but there is no limitation over the power to be demanded. In addition, such a scenario only involves a B2B load management process, as there is no final customer involved, and neither a general purpose EVSP. Based on its medium-term forecasts, the DSO will be able to update ToU prices as required (every year, every quarter…) to try to influence the fleet charging processes, so that they still take place in low demand periods or at any time in which they do not create congestion in the grid. In addition, ToU can also include the possibility for the DSO to remotely control the charging process when it forecasts a constraint in the network (due to extreme climate conditions, problems in the distribution grid…).


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This direct control is expected to happen very seldom and it will be communicated in advance to the EVSE Operator (no real-time control). In this scenario, there is a communication between EVSE Operators, fleet operators and the DSO. As in the conventional scenario, the DSO will be able to remotely disconnect EVSEs in emergency situations, but a specific request of relevant EVSEs can be forwarded to the EVSE Operator in this case.

2.4. Proactive In the Proactive scenario, the DSO will make a massive use of EVs load management, not only to try to avoid grid reinforcements linked to the demand increase resulting from EV, but also to reduce the investments needed to cope with traditional electricity demand increase. In this case, there is a direct involvement of EVSPs and their final customers. The DSO will sign contracts with EVSE Operators or EVSP, so that these provide constraint management services to DSO. The characteristics of the service, the certification process to be a provider of the service, the conditions to provide the service and the remuneration for the service will be established in advance, so that all potential providers know not only the framework conditions, but also their remuneration. This allows EV customers to access discounts in charging fees, trading their time flexibility and degrees of freedom with savings during the charging process. Following the request by the DSO, the EVSP (in combination with the EVSE Operator) will start or stop the charging process of the EVs, in order to solve either forecasted or pseudo real-time constraints. The charging process will be modulated according to the implementation method set forth by each EVSE Operator, which will operate the charging process according to the programme scheduled by the EVSP, who takes into account both the requests of the DSO and the constraints of EV customers. This scenario requires an advanced communication and pseudo real-time business process to be put in place between the DSO, the EVSP and the EVSE Operator. Moreover, the load management programme is now at the B2C level, so the acceptance of EV customers is key here. When there is an emergency situation, the DSO will still be able to remotely stop the EV charging process through a direct communication with the EVSE Operator. The load management is implemented via a digital control signal (ON/OFF scheme).

2.5. Smart grid The smart-grid load management scenario is the most advanced one. In this case, a demand response (DR) market will be established, where the EVSPs can enter to offer several types of services to the DSO.


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The DSO will procure such services, not only to ease the EVs load burden and avoid grid reinforcements, but also, and particularly, to promote EVs as an optimisation tool to aggregate volatile demand, which is feasible for an ad-hoc engineering of DER injection at MV and LV levels of the electricity grid. The DSO will procure DR services coping with its constraints, where the framework conditions (characteristics of the service, certification process, conditions to provide it…) are known in advance, as in the Proactive scenario. The remuneration, however, will be based on competitive market mechanisms. The aim of this market is to avoid any reinforcement in the grid (both due to EVs and to traditional electricity demand increase) and simultaneously enhance DER hosting capacity. The EV customer is key in this scenario, where a smart charging plan is used, which possibly will generate true value for RES producers (and the society as a whole) by increasing the delivery of electricity locally produced from RES. In addition, another regulated market could be established (either by the DSO itself or the TSO) to provide ancillary services to the TSO. This market will also have publicly available rules and conditions, which are known in advance, but whose remuneration is based on competition between the service providers. Likewise, electricity retailers and DER producers will also establish their own markets or participate in the above markets, in order to use EVSPs either to improve the performance in energy markets or to maximize the output of RES and other DER units. Regardless of the service they provide, EVSPs will modulate the charging process (not just a digital signal, e.g. ON/OFF) of their EV customers and they will also potentially be able to use vehicle-to-grid (V2G) capabilities in the future. The control will always be made by the EVSP, except in the case of emergency situations in the distribution grid, where the DSO will directly control the charging process, as in the rest of scenarios. This scenario requires an advanced communication and pseudo real-time business process to be put in place between the DSO, the EVSP and the EVSE Operator. Besides, like in the previous case, load management programme is now at B2C level and, thus, the acceptance of final customer is again key. The load management is implemented in order to locally generate value, more than in the Proactive scenario, and the load management is now more granular, allowing for load modulation beyond ON/OFF control signal used in Proactive. This allows a deeper control of the load flexibility that potentially can be gathered and aggregated.

2.6. Summary Table 3 summarises the main characteristics and differences between the individual scenarios, as defined in the sections before. These services, that can be eventually offered, have been obtained from different outcomes in the framework of the Green eMotion project [7] and discussed and were agreed in the General Assembly of PlanGridEV.


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Table 3: Summary of main characteristics of the different scenarios

Conventional Charge management

Type of charge management

Expected grid reinforcements Non EV-related EV-related Energy flow in EVs that are used to provide services Provider of the service Remuneration scheme

Type of power flow control for 5: Emergency constraint mgt. Forecasted constraint mgt. Real-time constraint mgt. Ancillary services for the TSO Energy trade DER integration

No

None Yes Yes

None

Safe Soft, fleetfocused

Proactive

Smart grid

Massive

Massive, local

Yes Minimal

Minimal No

No No

On/off

Grid  EV

On/off

Grid  EV

None

EVSE Operator (fleet manager)

EVSE Operator/EVSP Regulated contract

Centralised None None None None None

Centralised Centralised None None None None

Centralised Decentralised None None None None

None

ToU

Charge modulation

Grid  EV EVSP

Competitive market Centralised Decentralised Decentralised Decentralised Decentralised Decentralised

5

Centralised control means that the DSO is controlling the charge, while decentralised means that either the EVSE Operator or the EVSP are taking control.


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3. Boundary conditions for EV integration scenarios Governments and regulatory bodies should create a framework for personal and company relationships aiming at fostering and improving the aspects which are beneficial for a society, such as justice, employment and environmental protection. Therefore, in the case of e-mobility, regulation should promote business models and permit their profitability under global sustainability concepts rather than hindering the EV penetration. Regulation may positively or negatively affect EV deployment in many ways, some of which are presented in this chapter. A more detailed description of the impact of regulation can be found in [D1.1]. Regulatory issues related to the EV grid integration business scenarios described in this document will be further analysed, concerning the Smart grid scenario, during the evolution of task T2.2 and task T2.3, together with technical and economic requirements. This chapter therefore gives an overview of the impact that regulation may have on the boundary conditions to the implementation of Smart grid scenario that will be further developed in tasks T2.2 and T2.3.

3.1. Classification of roles In many cases, regulation establishes a number of roles which can be performed by different actors, and any new entrant in the market must fulfil one and only one of them. This might be a problem when new business models are envisaged, since it may require the performance of more than one of those roles by the same actor, or might require significant changes in the roles mandated by regulation. For example, Spanish regulation defined three main types of liberalised actors [8]: •

Electric energy producers: persons or legal entities in charge of generating electric energy, for their own consumption or for third parties, and of building, operating and maintaining power plants.

•

Electricity retailers: business societies that acquire energy to sell them to consumers, other system actors or to accomplish international exchange operations.

•

Consumers: persons or legal entities buying electricity for their own consumption. They can buy it directly at the market or to suppliers.

Under these definitions, one parking lot manager who wants to offer charging service to EVs would not be allowed to do so, because (i) it does not generate electricity, (ii) it acquires energy not only to sell it to consumers, and (iii) it does not buy all the electricity for its own consumption. As a result, regulation had to be changed to add a new actor, the charge manager (or Gestor de Recarga), who is a business society that, being consumer, is entitled to re-sell energy both for energy charge services and for energy storage, for a better management of the electrical system.


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In addition, regulation also defines the rights and duties for each role. However, some business models may require that one of the actors addresses more than one. If regulation is not flexible enough, or the requirements to perform some of the roles are too demanding, business models that can help the electricity system as a whole may never happen (e.g. if the regulation does not remunerate DSOs for launching demand response programmes, they will not have an incentive to do it – on the contrary, they will have an incentive to oppose to it if their remuneration is based on the amount of kWh circulating in their grids – even if they could reduce fuel imports, CO2 emissions, grid losses, etc.). On the contrary, too loose requirements may result in risk for system security. A detailed analysis must be carried out to evaluate which kind of regulatory change and update is needed for an envisioned EV grid integration scenario to take place and let all the actors involved in the business implement their activities in a profitable way. Another important point is that requirements should be coherent throughout Europe to allow for interoperability. However, in order to bring solutions to the market as soon as possible, it might be advisable to propose different implementation phases with different targets and requirement levels according to the real evolution of the EV market. WP 7 will dive into such analysis.

3.2. Market design Market design is country-specific, even if most regions deploy similar structures today, including dayahead markets, intra-day or hour-ahead markets, bilateral contracts, futures markets, balancing markets and markets for other ancillary services. Electricity market rules establish, among others, the requirements for stakeholders to participate in business exchange activities related to electricity purchase and sale. These requirements include the administrative procedures to be followed by applicants that want to participate in the market, as well as the technical, legal and economic guarantees that they need to demonstrate. When liberalisation started, markets were designed for big-sized producers and consumers. Therefore, the requirements for participating in wholesale markets are tailored to these big players and, even if they do not legally prevent the participation of small-sized consumers and producers, small actors often need the support of some intermediaries (demand or generation aggregators, virtual power plants, representatives in the market, EVSPs…), which may pose an important entrance barrier for them. This situation is even more difficult in balancing markets and in markets for other ancillary services. These markets are usually managed by the TSO to keep system stability at transmission level. Due to the big impact that a problem in the transmission system may have, the economic volume of these markets is also huge but, due to the strong technical requirements that balancing and ancillary services demand, TSOs’ requirements for participating are also more demanding than in day-ahead and other electricity trading markets, which makes it even more difficult for DER (and potentially for EVs) to participate in them.


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An example of this situation can be found in the main balancing markets in Spain: •

Primary regulation [9]: all production plants must be able to alter their nominal power in a 1.5%, as a response to defined frequency variations in an automated way. This service is obligatory for all power plants and it is not remunerated.

•

Secondary regulation [10]: some power plants modify their nominal power to restore system frequency after an event has taken place. The service is provided by regulation areas, which are made up by power plants that respond to orders of an automated control generation centre. Only the power plants entitled by the TSO can be included in a regulation area and, although both conventional power plants and manageable distributed generation power plants are eligible to be part of a regulation area, they must be able to respond in 100 seconds and the minimum secondary regulation offer is 5 MW, which makes conventional power plants more likely to be selected as service providers. The day before real operation, regulation areas offer secondary regulation reserve (capacity to ramp up or down) and the TSO contracts the amount (MW) needed, while, in real-time, the TSO requests them to modify their output to provide the secondary regulation energy (MWh). The TSO remunerates regulation areas both for the reserve and for the energy effectively provided.

•

Tertiary regulation [10]: all power plants must make offers to adapt their schedule of power in order to restore the resources deployed as secondary reserve. The power plants that want to provide this service must obtain the accreditation by the TSO, must offer a minimum regulation of 10 MW and must be able to provide the required regulation in 15 minutes and to maintain it, at least, during two consecutive hours, so, again, the service is more suitable for big power plants. The remuneration is based on the regulation energy that the TSO request them to provide in realtime.

•

Interruptible load [11]: Big consumers are requested to reduce their consumption when primary, secondary and tertiary regulations are not able to restore the system balance. High voltage (more than 1 kV) electricity consumers that can reduce, at least, 5 MW in any hour of the year can sign a contract with the TSO to become providers of the service. The conditions of the contract, including the types of load reductions, the warning times and the remuneration are standard and publicly available. Like in the cases above, this service is tailored to big players, but, on the contrary to the rest of the services, this is explicitly only available for them.

As shown, current market designs descend from those created in the monopolistic era and their main features have changed slightly since then, principally due to the high reliability that these schemes have historically provided to system operators. Aspects as demand and, in general, DER participation have today limited impact in operation and planning. However, the presently increasing penetration of distributed generation and the benefits of an increased participation of small consumers create the conditions that advise to evolve towards newer market design concepts, where these small-scale participants help improve the efficiency of the overall system. In addition, an optimum interaction between the electrical system, EVs and other DER means (including storage systems and low capacity generation and demand assets) would allow innovative business models to take place, as well as an evolution towards more efficient and sustainable networks.


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On the other hand, existing regulation gives strong power to the TSO, so, in case of any new market were created for small-scale actors, it is likely that its management would be given to the TSO, and not to the DSO. A mandate is being prepared at European level to avoid TSOs intervening in distribution networks. The TSOs would send power (active and reactive) settings to distribution networks connection points and the DSO would decide the actions to be taken (operation). In order to give stronger power to DSOs, two aspects are of paramount importance: •

The DSO must guarantee non-discriminatory and fair conditions for all potential service providers, which can be made by establishing public and transparent network operation procedures (section 3.3).

•

The remuneration scheme for the DSO must reflect the societal benefits of using smart grid-type operation procedures and not just focus on investments in lines and transformers (section 3.4).

3.3. Network operation procedures In many countries, the operation procedures for transmission networks are clearly defined in regulation and are made publicly available. Such operation procedures might take enormous advantage due to the availability of business processes capable of allowing large-scale load management of EVs. These procedures do not only establish the way in which system operators manage their systems, but also define the requirements to be met by parties who want to be connected to their systems (producers, consumers…). In addition, these procedures define the types of ancillary services for the system operators, the conditions under which they will contract/buy the services and how the remuneration will be calculated (fixed in advance, or through clearly defined market mechanisms). However, the procedures for the operation of distribution networks are not always as established as the ones for transmission grids. For example, the distribution network operation procedures are in the proposal stage in Spain, so they do not have legislative status yet [12], whereas in Italy and other countries there are already legal frameworks for network operation procedures. Nevertheless, the evolving distribution smart grid concept might require the following transmission network example and agreeing upon some general procedures for distribution networks. The importance of system operation procedures lies in the fact that the technical requirements set by the system operator could affect the characteristics of electric vehicles in order to control some aspects of their behaviour with respect to the network. This could be performed in the same way that it is currently done with other distributed generation (DG) assets (voltage dip ride-through capability, requirement for EVSE to be connected to a control centre…). Likewise, other characteristics could be requested to EVs if considered beneficial for network support, such as automatic frequency response (when the frequency of the network decreases under certain level EVs should stop consuming energy; or above certain frequency level, they should withdraw electricity from the network, if possible) or even V2G (this is not expected to have much influence in the short term but a demand increase in the absence of intelligent charging might be possible closer in time.


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In general, all requirements which are considered to be relevant for network stability should become minimum obligations imposed on assets connected to the grid and/or stakeholders participating in regulated business environment. Nevertheless, as always, these should be carefully observed in order not to hinder EV related business models. A definition of rules in parallel to market penetration speed of these new technologies is something to be considered.

3.4. Remuneration scheme for the distribution activity Network operators are the main responsible parties for system efficiency and their business model is based on operation and maintenance of the network with quality requirements fixed by national authorities, in compliance with EU targets. They plan and operate network assets on a daily basis, both from the service provision and business management points of view. As a regulated activity, system operation is remunerated for the compliance of some defined objectives, which certainly condition the business strategy of system operators. Therefore, it would be very important to define energy efficiency activities as eligible for compensation and with clear and appropriate procedures. Smart grid scenario as defined in section 2.5 goes in this direction, foreseeing the need of remunerated business process that will be detailed in task T2.2 in order to allow the system operators to generate value across the value chain from load management programmes. The distribution activity remuneration criteria should seek to incentivise the improvement of management efficiency, technical and economic efficiency and power quality, as well as the reduction of electrical losses in distribution networks and the rise of DER hosting capacity via a large-scale DR programme. Distribution companies should be remunerated for the investments necessary to guarantee an efficient electricity distribution at the lowest cost. Even if other aspects such as demand-side management, the use of storage, load reduction and, in general, the efficient management of the network are currently encouraged by legislative documents, the economic compensation derived from applying such strategies is not clearly defined. This is an important point for system operators in order to put in place strategies of this kind. In order to encourage DSOs to purchase DR services in the e-mobility business, in addition to technical aspects, economic implications have to be clearly defined, so as to achieve an efficient planning of network development and to design an effective portfolio of operational strategies suitable for an optimum management of the system. Task T2.3 will further develop this requirement. Incentives favouring a more environmentally friendly use of resources might be required to define EVs’ charging profile according to the current generation mix and the availability of local DERs. In some cases and depending on the country, periods with higher level of renewable energy might be cheaper for final users and, in these situations, electricity prices become a “sustainable” reference to plan EV charging periods. However, this might not always be the case or, at least, not for system operators. Therefore, there should be some incentive helping them manage the flexible load for the sake of environmental adequacy, as long as this represents a cost increase in the operation activity.


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Clearly, system operators need economic analyses to compare different available investment or management options. However, regulation should help internalise the social benefits of environmentally friendly solutions from an economic perspective, so that not only investment costs or monetary benefits count when network operation and planning solutions are adopted. WP7 will investigate the economic feasibility, among others, of Smart grid scenario defined in section 2.5.

3.5. Demand response One way for EVs to contribute to network operation is through DR strategies, as envisaged in the Smart grid scenario described in section 2.5. The fact that EVs remain most of the time parked and that they could stay connected to the network during this time makes them good candidates for offering demand flexibility. In addition, their storage capabilities and V2G characteristics expand the range of services they could offer in the long term, when these technologies become widespread. Since EVs represent small size loads, the demand aggregation turns out to be a remarkable option for them. Such services should be provided by EVSPs and procured by System Operators. As deeply analysed in previous FP7 initiatives, including ADDRESS [13] and Green eMotion [2], DR clients are normally system operators, which use these strategies as network operation tools, allowing them to defer the investments required to cope with demand peak increase. However, DSOs and TSOs are affected by regulated business rules and, therefore, they need to proceed under regulated procedures, which might not be adequately updated to allow DR programmes to take place. DR is principally appealing in electricity systems with tight security margins regarding installed power capacity versus peak demand ratio. This way, electricity price variations are appreciable (which lead to the profitability of DR schemes for final users and, thus, to an increase of DR penetration), while at the same time, system operators profit from deferring grid investments. As a result, DR strategies are more common in the USA and Australia, but there is evidence building up of business interest in the European Union (EU) as well. Actually, most EU Member States have legal provisions to regulate the use of demand management tools, which include ToU tariffs (night tariff or several price step tariffs) and interruptible load contracts (normally addressed to big size industrial consumers. The United Kingdom, which precedes most EU countries in this field, has even implemented demand markets. In the case of EVs, the ISO/IEC 15118 [4] will include the communication between the EV and the EVSE as a working standard, which will offer the possibility to negotiate a charging schedule between the EV and the EVSP or the DSO, considering EV user preferences, network constraints, energy price, etc. This standard is currently under development and it is not implemented yet in most EVs or EVSEs. However, load management of EVs is possible with EVSEs that are already compliant to the pulse-width modulation (PWM) mechanism foreseen in IEC 61851 [14] and equipped with uplink communication protocol able to include load management programmes. More details on the technical requirements for the implementation of Smart grid scenario can be found in [D2.2] and in the evolution of task T2.2.


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Although some steps have been completed up to now, regulation needs to be improved to increase the DR participation of EVs and small electricity consumers in general. Demand management might be a significant mechanism in the smart grid framework and regulation should be developed in order to consider its deployment under network security, efficiency and economic parameters. Where demand is not considered as a mean to provide flexibility to the systems or its implementation aspects are not defined clearly enough, regulation should be adapted in order to permit system operators to apply these strategies. In addition, other aspects, such as the EV infrastructure requirements (section 3.6) and network regulation for final users (section 3.7) must also be taken into account. Although requirements should be coherent throughout Europe to permit interoperability, in order to bring solutions to the market as soon as possible, it might be advisable to propose different implementation phases with different targets and requirement levels according to the real evolution of the EV market.

3.6. EV infrastructure requirements and accessibility Since EV infrastructure is connected to the distribution network, it will be affected by low voltage codes, which define the requirements that electrical installations should fulfil in order to comply with issues such as security, reliability, quality and standardised solutions. For example, the Spanish LV code is currently being revised in order to include a new technical instruction for allowing EVSE installation and its proper use for advances scenarios [15]. Regulation is key to show the way in which equipment should be installed, as well as the requirements to cover the most basic technical aspects of EVSEs. Technical requirements of EVSEs for allowing Smart grid scenario will be detailed in task T2.2. However, strict requirements may involve too high costs, too long administrative processes or raise other type of barriers affecting final users, such as those that could be caused by e.g. the need of receiving the approval of all the neighbours in order to accomplish a charge point installation in common residential areas. Therefore the field equipment features, although needed to implement advanced scenarios, should never be a barrier to technological adoption.

3.7. Network regulation for final users Final users need easy and affordable solutions to help them step into the EV world and possibly access advanced services, like smart charging. Infrastructure accessibility (section 3.6), market access (section 3.2) and incentives for the purchase of EVs are actions pushing in this direction. The regulation for self-consumption might be another tool to facilitate the connection of EVs to the network. An easy procedure to connect a vehicle to the network and perform V2G might motivate end users’ to provide services to the system.


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Unfortunately, that is not the case in Spain. As presented in section 3.1, DG owners have to play two roles in the electricity supply chain, because they generate electricity (so they must be electric energy producers) and they also consume it (so they must be consumers). The enormous tariff deficit existing in Spain (regulated grid access fees have not been enough to cover system costs since the beginning of the millennium) resulted in the removal of the feed-in tariff system for new DG in early 2012 and in the review of the remuneration for the existing units since mid-2013. In order to provide an alternative for new plants, a piece of regulation to establish the conditions for self-consumption is currently under preparation [16]. A beneficial point of the proposal is that consumers which are willing to install an electricity generation system in their premises will have just to inform the distribution operator in their area about that fact and comply with existing connection requirements [17]. However, these requirements are not as simple as probably wished by end-users. Besides, consumers would need to pay a network usage fee for the electricity they generate (in addition to the one they must pay for the electricity they consume), so that they end up paying much more network fees than regular consumers. An adaptation of this legal document addressing mobile connection specificities could be also beneficial for EV users, which, under certain circumstances, might offer services to the network without the need of an intermediary, such as the aggregator, and following simple procedures. In Italy, it is currently under discussion the possibility of performing power contracts that might not be fixed for EVSEs, allowing EVSE Operator to manage flexible power contracts according to the real usage patterns. Contract types are another service that can help consumers to charge their EVs more efficiently. In most of the cases, contracts between suppliers and end-users are not part of the regulation. However, these are normally affected by network access tariffs, which are part of the regulatory definition of the electricity system. ToU tariffs and location related prices could be an option for DSOs in order to translate the system costs to final customers on a more realistic way. A similar case would be that of EV services. Tariffs affecting services sale might have a great impact on final users’ involvement in system support. Tariff design, including administrative procedures, purchase and sale prices, simplicity of schemes, etc. might play a very important role in attracting consumers to behave more efficiently in the energy context. The smart phone market and some DR contracts might give examples for EV related tariff designs, both for electricity purchase and service sale. It is crucial that the customer can be engaged in clear load management programmes, exploiting a favourable regulation. Also this kind of boundary conditions will be further exploited in task T2.3.


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4. Initial analysis of business scenarios As the number of EV increases, their impact in the distribution grid will also increase, so the DSO will need to adapt either the grid (by investing in grid reinforcements) or its operational procedures (by going to a smarter operation of the grid), according to the different scenarios presented in previous sections. One of the most important scenario selection criteria will be the economic performance of each alternative. This economic performance will be assessed by considering a base case (conventional scenario) will be considered and, afterwards, it will be compared to other alternatives. EVs do not have a significant impact in distribution grids yet, due to its low penetration rates [18]. Hence, in order to estimate the potential costs of EV penetration for DSOs, the likely situation in 2020 will be taken as a basis. Currently, EU mandate for the installation of public charging points is based on the hypothesis of having 4 million BEV and PHEV circulating in EU Member States by 2020 [19]. In addition to regulatory issues presented in chapter 3, the actual impact of the scenarios will depend on the existing conditions of distribution grids. Although a more detailed analysis will be performed in WP3, a lightweight economic analysis has been performed to give an idea of the economic impact of the different scenarios in distribution grids. Due to the lack of disaggregated data, a country-wide estimation of the impact at the distribution level has been done, which may provide only a partial view of the potential of the scenarios, particularly in the case of the Smart grid scenario. Being one of the countries with the most ambitious EVSE installation targets [19], and due to the availability of data, Spain has been taken as an example for the assessment of the economic impact.

4.1. Introduction to e3value methodology Although there is no common definition for the term business model, in general, a business model describes the rationale of how an organization creates, delivers and captures value [20]. Therefore, a business model should look into many aspects of the business developer and its environment. Instead of focusing on how an individual company can make money, we must look at the business model through which a company can earn money and assess the impact that such business model has in the rest of market participants. The consideration of the environment of the business developer is even more important in the case of partially regulated sectors, which is the case of the electricity supply chain. In particular, the impact of the business model in regulated parties is of paramount importance. If such effect is negative, either those parties or the regulatory authority can prevent the business model to be carried out. As a result, business models about market integration of EVs must be analysed as the networked businesses they are, where many actors interrelate with each other. The analysis of networked business models through traditional methods may result either time-consuming, or oblige to perform simplifications that usually hide important implications of the business for some of the involved actors.


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3

In order to overcome such problems, the e value methodology [21] was created and adapted to the world of distributed generation and other DER [22]. This methodology provides a pre-defined template to describe the business idea at hand, together with a financial analysis, based on investment and operational cash-flow perspective, and a scenario approach. Moreover, the methodology offers a common understanding of the business case for all the stakeholders involved in it, by using a shared and well-defined terminology. The methodology uses, on the one hand, well established business modelling methodologies for networked enterprises and, on the other hand, traditional economic investment assessment techniques such as calculation of net present value (NPV) and internal rate of return (IRR). The main features of the methodology are that it presents the whole picture of the business case and that it focuses on the concept of economic value. This way, the business cases are represented graphically, showing all the actors which are needed to run the business model (including the business developers, regulated actors and competitors) and the economic relationships between them. 3

The e value methodology provides modelling concepts for showing which parties exchange objects of economic value with whom, and what they expect in return. The conceptualisation of a business idea can be graphically represented in a rigorous and structured way, as Figure 3 shows:

Figure 3: Simple example of an e3value model 3

The most important concepts of the e value methodology are listed below:


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•

Actor: An actor is perceived by its environment as an independent economic (and often also legal) entity. An actor makes a profit or increases its utility. In a sound and sustainable business model each actor should be capable of making profit. In electric systems, there is a common set of actors, such as producer, distribution system operator, transmission system operator, government, supplier, balancing groups, energy service companies, metering companies…

•

Value Activity: The electricity sector performs several value activities, namely, generation, transmission, distribution, supply, system operation…

•

Value Object: Actors exchange value objects, which are services, products, money, or even consumer experiences. The important point is that a value object is of value for at least one actor.

•

Value Port: An actor uses a value port to show to its environment that it intends to provide or request value objects. The concept of ports enables us to abstract away from the internal business processes, and to focus only on how external actors and other components of the business model can be ‘plugged in’.

•

Value Offering: A value offering models what an actor offers or requests from its environment. The closely related concept ‘value interface’ (see below) models an offering to the actor’s environment and the reciprocal incoming offering, while the value offering models a set of equally directed value ports exchanging value objects. It is to model e.g. bundling: the situation that some objects are of value only in combination for an actor.

•

Value Interface: Actors have one or more value interfaces, grouping individual value offerings. A value interface shows the value object an actor is willing to exchange in return for another value object via its ports. The exchange of value objects cannot be divided at the level of the value interface.

•

Value Exchange: A value exchange is used to connect two value ports with each other. It represents one or more potential trades of value objects between value ports.

•

Market Segment: The market segment shows a set of actors that, for all of their value interfaces, give the same economic value to objects.

The concepts above can be used to model value exchanges between actors or market segments, but do not give the idea of which value activities or value exchanges must take place, so that some other value activities or value exchanges can also take place. In other words, they do not represent the order in which value exchanges must take place. To that end, some other concepts used in an existing scenario technique called Use Case Maps (UCM), are presented below: •

Scenario path: A scenario path consists of one or more segments related by connection elements and start and stop stimuli. A path indicates via which value interfaces objects of value must be exchanged, as a result of a start stimulus, or as a result of exchanges via other value interfaces.

•

Stimulus: A scenario path starts with a start stimulus, which represents a consumer need. The last segment(s) of a scenario path is connected to a stop stimulus. A stop stimulus indicates that the scenario path ends.


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•

Segment: A scenario path has one or more segments. Segments are used to relate value interfaces with each other (e.g. via connection elements) to show that an exchange on one value interface causes an exchange on another value interface.

•

Connection: Connections are used to relate individual segments. Each fork splits a scenario path into two or more sub-paths, while each join collapses sub-paths into a single path. In AND forks/joins, all incoming and outgoing paths have the same number of occurrences, while in OR forks (joins) the number of occurrences of the incoming (outgoing) path equals the addition of the number of occurrences of the outgoing (incoming) sub-paths. An implosion (AND connection with only one incoming and one outgoing port) shows a change in the number of occurrences within a sub-path. 3

Table 4 below shows the graphical representation of the main e value concepts. Table 4: Graphical representation of main e3value concepts

Concept

Graphical representation

Concept

Actor

Market segment

Value port

Value interface

Value object

Value exchange

Start stimulus

End stimulus

AND fork/join

OR fork/join

Segment

Graphical representation

Implosion

3

The goal of the e value modelling methodology is to evaluate a business idea, and discover a business scenario, feasible for every stakeholder. A business scenario consists of the business model and the scenario path. The business model is a set of value objects, exchanged between value activities, performed by different actors or market segments. 3

One of the main features of the e value modelling methodology is that it is a conceptual modelling approach, and that it focuses on the concept of economic value as a central conceptual modelling construct. A conceptual modelling approach facilitates the creation of a better shared understanding and agreement between actors on a service or product to be offered.


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Besides, this approach allows for the evaluation of a business value model, in order to assess whether the business model is profitable for all the stakeholders involved. The intention is not to give precise calculations about the profit to expect, but rather to build confidence on the commercial viability of the business model, by exploiting what-if scenarios to evaluate the changes in business profitability as a result of changes in economic conditions of its environment. An actor is perceived by his environment as an economically independent entity. Hence, an actor must be able to be profitable after a reasonable period of time or to increase value for itself. A business model can only succeed if all involved actors regard it as a profitable idea. All involved actors should benefit from the business idea, and the only way to check it is to include all of them in the value model. 3

The e value graphs present the monetary exchanges between the different parties (one of the items exchanged by actors is always money). Only monetary exchanges which happen several times are represented, which means that investments are not included in the graphical models, since the aim of the graph is to obtain the cash-flows for the different actors within defined time-horizons. The time-horizon for cash-flow calculation depends on market arrangement; if market prices and imbalance prices change every hour, cash-flows are calculated every hour; if prices change more often, cash-flows will be calculated accordingly. Cash-flows are then added up to obtain the annual cash-flow, in order to compare it with the required investment, through traditional methods for valuating investments, such as the NPV or the IRR. The graphs created with this methodology (such as Figure 3) do not present temporary sequences of exchanges, but the sequence to satisfy one or various needs of one or some actors. For example, in the case of a customer buying a good from a retailer (Figure 3), the graph would show that the customer gets the good from the retailer, who gets it from a wholesaler, who gets it from a manufacturer. Of course, the temporary sequence would be that the wholesaler buys the good from the manufacturer, the retailer buys it from the wholesaler and the consumer buys it from the retailer, but that is not important for this analysis. 3

More information about e value can be found in [21], [23] and [24].

4.2. Electricity demand in the distribution grid 4.2.1. Demand in 2013 An estimation of the demand at distribution level for Spain has been used as the reference data for the electricity demand. This actual information can also be easily extrapolated to any other country or situation. Such estimation was built upon the synthetic load profiles (SLP) for 2013 [25], for the different types of LV consumers. It is important to note that these profiles refer to the expected electricity demand during 2013, and not the actual demand, because not all the data are available yet. In Spain, there are 5 main types of transmission and distribution (T&D) tariffs, also referred to as access fees ([26] and [27]):


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•

2.0: Tariff for consumers connected to a voltage level not higher than 1 kV, and whose contracted power does not exceed 10 kW. It is further divided into: o

2.0 A: Flat tariff.

o

2.0 DHA: Two-period tariff.

o

2.0 DHS: Three-period tariff.

•

2.1: Tariff for consumers connected to a voltage level not higher than 1 kV, and whose contracted power is between 10 kW and 15 kW. It is also divided in the same 1, 2 and 3-period options as in the case above.

•

3.0 A: Tariff for consumers connected to a voltage level not higher than 1 kV, and whose contracted power is higher than 15 kW. It is a three-period tariff.

•

3.1 A: Tariff for consumers connected to a voltage level which is between 1 kV and 36 kV, and whose contracted power is lower than 450 kW. It is a three-period tariff.

•

6 A: Tariff for consumers connected to a voltage level which is 1 kV or higher, and whose contracted power is equal or greater than 450 kW. It is a six-period tariff. Depending on the connection voltage level, it is divided into 5 categories: o

6.1 A: Connection level between 1 and 36 kV.

o

6.2 A: Connection level between 36 kV and 72.5 kV.

o

6.3 A: Connection level between 72.5 kV and 145 kV.

o

6.4 A: Connection level equal or greater than 145 kV.

o

6.5 A: International interconnections.

By looking at this tariff structure, the simplest approach to calculate the demand at distribution level would be to add the demands for LV tariffs (2.0, 2.1 and 3.0) and for the tariffs below 36 kV (3.1 and 6.1). However, the consumers with six-period tariffs must have hourly metering, so the SLPs for these 6 consumers are not published and cannot be used to calculate the distribution demand. Therefore, it has been assumed that the demand at distribution is made up by the addition of tariffs 2.X and 3.X. As in the case of the SLPs, there is no real data for the total consumption in 2013 for the different types of consumers because the year has not finished yet. Therefore, the latest available data has been taken (consumption between June 2012 and May 2013, in GWh [28]):

6

The SLPs are used for billing purposes for those consumers who do not have hourly metering.


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Table 5 Electricity consumption per consumer group in Spain in June 2012 - May 2013

2.0/2.1 A 67,649

Consumption per T&D access fee (GWh) 2.0/2.1 DHA 3.0/3.1 A 2.0/2.1 DHS 10,212 50,133 3

By multiplying the SLPs by the annual consumption, the hourly consumption for each type of consumer is obtained and, by adding them, also the hourly consumption at distribution level, as Figure 4 shows.

Figure 4: Electricity demand in Spanish distribution grids in 2013 The month with the highest electricity consumption peaks is January, so it is represented in Figure 5. The annual hourly peak results to be 25,733 MWh.


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Figure 5: Electricity demand in Spanish distribution grids in January 2013 On the other hand, the distribution costs are expected to be about 5,418 million euro in 2013 [28]. According to the Spanish regulator [29], the costs linked to satisfying peak demand are about 88.5% of the total, which means that being able to distribute 25,733 MWh costs Spanish consumers about 4,795 million euro.

4.2.2. Demand in 2020 At this moment, we are facing a world-wide crisis, which, in the case of Spain, is especially strong. As a result, electricity demand is declining in the last years. However, in order to make a medium-term outlook, we should consider that demand will increase again in the next years. The average annual electricity demand increase in Spain during the period 2003-2008 was 3.5% [30]. By assuming the same demand profile as in 2013, but increasing total energy consumption by 3.5% per year, the expected hourly demands at distribution level in 2020 can be calculated. In this case, the annual hourly peak in 2020 becomes 32,740 MWh (red line in Figure 6) and there are 910 hours in which the distribution demand in 2020 is higher than the distribution peak in 2013 (blue line in Figure 6). If the distribution grid were not upgraded, the energy that would be lost on an annual basis would be 2,281,116 MWh (this is the amount of energy that exceeds the peak demand in 2013).


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Figure 6: Electricity demand in Spanish distribution grids in January 2020 (without EVs)

4.3. Conventional scenario In the Conventional scenario, the DSO builds as many lines, transformers and distribution grid equipment as needed in order to cope with the expected demand increases. Therefore, in this scenario, EVs will charge whenever and as much energy as they want to. EV customers will buy the EV charging service from the EVSP who, in return, will buy the charging 7 service from the EVSE Operator (roaming of charging service [3] ). The EVSE Operator will buy electricity from and electricity retailer, who will pay for T&D fees to the DSO and for electricity itself to some other actor in the traditional electricity supply system. In order to provide their services, both the EVSP and the EVSE Operator will need to pay for communications every time there is a charging event by EV customers. All these money transactions are presented in Figure 7, which is based on the 3 e value methodology (see section 4.1) and on the work done in Green eMotion Task 9.3.

7

In the “roaming of charging service” scenario, the electricity retailer is chosen by the EVSE Operator, which sells the charging service including electricity, whereas in the “roaming of electricity and service scenario”, the consumed electricity is purchased from an electricity retailer chosen by the EVSP, the price requested by the EVSE Operator does not include the price of electricity. For simplicity reasons, the first alternative has been chosen for the graphical representation of the load management scenarios, but the other alternative is also possible and, if the price to be charged by the EVSP is properly designed, results are equivalent.


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3

Figure 7: e value model for the Conventional scenario The average mileage in Europe is about 14,000 km/year [31]. By assuming an average 150 Wh/km ratio [32], annual consumption would be 2,100 kWh (5.75 kWh/day). The data collected in Green eMotion demo regions [33] suggest a lower consumption, as Figure 8 shows:

Figure 8: EV charge event statistics. Source: Green eMotion Therefore, it will be assumed that daily consumption is 5 kWh and that charging patterns follow the distribution shown in Figure 9 [33].


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Figure 9: EV usage patterns. Source: Green eMotion According to the EU [19], Spain must install 824,000 private charging spots in 2020, so it could be assumed that there will be the same amount of EVs in 2020. However, some other reports [34] reduce that figure to about 100,000 EVs. In order to be conservative, an average of both figures will be considered (462,000 EVs in Spain in 2020, about 2% of the existing fleet in 2011 [35]). This figure is consistent with the recommendations of the Transport Committee [36] and the proposal to have 10% of the charging spots publicly available [19]. Based on this EV charging demand distribution and on the rest of the assumptions presented so far, the EV charging hourly demand can be obtained. By adding the EV demand to the traditional electricity demand, the distribution grid situation in this conventional scenario can be modelled. Figure 10 presents the electricity demand in the distribution grid in the conventional scenario in January 2020.


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Figure 10: Total demand in distribution grid in January 2020 (Conventional scenario) In this case, the peak demand becomes 32,839 MWh and there are 969 hours in which demand is higher than the 2013 peak. Based on the distribution costs for 2013, it can be assumed that meeting this peak demand would cost about 6,119 million euro in 2020 (2013 value), i.e. about 1,324 million euro more than in 2013.

4.4. Proactive scenario In order to assess the potential for the different scenarios, only the Proactive and the Smart grid scenarios will be considered, because they are the ones involving the highest level of EV integration in the grid and IT-based automation and, hence, which are expected to offer the best business opportunities. In the Proactive scenario, the charging activities of EVs are managed in a way that no demand increase related to EV takes place. This way, when the DSO expects that the electricity demand for EV charging will exceed the 2020 peak (32,740 MWh), EV charging will not take place at that time, but it will be shifted to low-demand periods (from midnight to 8 a.m.). The DSO estimates, on a daily basis, the amount of energy that will be exceeding the 32,740 MWh threshold and it asks either the EVSE Operator or the EVSP to distribute it equally in the first 8 hours of the day. This way, the DSO avoids problems in the distribution grid, so it will be willing to pay for the service to whoever provides the service. 3

The e value model for this scenario is the one presented in Figure 11.


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3

Figure 11: e value model for the Proactive scenario Under the assumptions made, EV charging must be managed in 4 hours (see Figure 10, where the only 4 hours in which demand in the conventional scenario is higher than the 2020 peak can be identified) and the amount of energy to be shifted will be 399 MWh. The new distribution demand profile is presented in Figure 12.


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Figure 12: Total demand in distribution grid in January 2020 (Proactive scenario) Based on the distribution costs for 2013, it can be assumed that the additional investment costs for the 8 distribution system are 6,101 million in the Proactive scenario. This means that the DSO can save about 19 million euro, compared to the Conventional scenario. However, the DSO will need to invest in an EV demand forecasting tool and in the communication infrastructure to be able to communicate with the EVSE Operator or the EVSP. If the operation and maintenance (O&M) costs and the annuitized investment of these systems can be assumed to be 1 9 million euro , the DSO will still be able to save 18 million euro per year. By assuming that the benefits are equally distributed among the whole value chain: •

The DSO would save 6 million euro per year, and would use the remaining 12 million euro to pay for the constraint management service. In this case, the most likely situation is that the DSO would pay a fixed annual amount to the provider of the service, and there would be no specific payment for managing the constraint itself.

8

The savings will actually be a benefit for the electricity system as a whole. The regulation will need to be properly designed, in order to make an effective allocation of these savings to the DSOs, EV customers and to other electricity consumers, as discussed in Chapter 3. 9 The costs for these systems are very strongly linked to the specification of the requirements they need to fulfil. Since the aim of this deliverable is not to give precise calculations, a very rough estimate has been made here. A more detailed estimation of these costs will be made in WP3.


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•

•

Depending on the manager of the service: o

If the service is managed by EVSE Operators, they could keep 3 million euro per year and use the rest (9 million euro) to offer a discount in the amount to be charged to EVSPs, as long as they allow EVSE Operators to control de charge. Then, EVSPs would keep another 3 million euro and use the remaining amount (6 million euro) to remunerate EV customers.

o

On the contrary, if the managers of the service are EVSPs, they would keep 6 million euro, and would use the other 6 million to remunerate EV customers.

EV customers would receive 6 million euro for allowing either the EVSE Operator or the EVSP to control the charging of their vehicle. This might be done: o

If EV customers pay a fixed amount per charge (regardless of the amount of kWh they charge), their EVSP can offer a discount in the EV charging service, when the charging must be managed. In this case, each controlled charging would receive a discount of:

6 𝑚𝑚𝑚𝑚𝑚𝑚𝑚 € 1 ∗ 462,000 𝐸𝐸 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 4 𝑒𝑒𝑒𝑒𝑒𝑒 = 𝟑. 𝟐𝟐 €/𝑬𝑬 𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪. 𝒆𝒆𝒆𝒆𝒆

𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑓𝑓𝑓 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎 = o

If EV customers pay for EV charging on a per-kWh basis, the controlled charging price would receive a discount of:

𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑓𝑓𝑓 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑐ℎ𝑎𝑎𝑎𝑎𝑎𝑎 =

6 𝑚𝑚𝑚𝑚𝑚𝑚𝑚 € = 𝟏𝟏, 𝟎𝟎𝟎 €/𝑴𝑴𝑴 399 𝑀𝑀ℎ

By looking at the results, it seems more likely that the payment is made per event, so that customers get a payment (or a discount over EV charging cost) of 3.25 € every time the DSO needs to have their charge controlled.

4.5. Smart grid scenario In the Smart grid scenario, the charging of EVs is managed in a way that there is no demand increase related to EV and the increase resulting from traditional electricity demand can be reduced. The DSO will arrange a load management market where EVSPs can offer EV charge management or V2G, demand aggregators can offer DR services by managing their non-EV related electricity demand and DER producers can offer electricity production capabilities in order to avoid problems in the distribution grid.


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As PlanGridEV focuses on EV charging management and the aim of this deliverable is to set up the framework for more detailed analyses (WP3), it will be assumed that any type of management is 10 provided by the EVSP, by using the capabilities of EV customers . 3

Therefore, the e value model for this scenario is the one presented in Figure 13.

3

Figure 13: e value model for the smart grid scenario If the DSO wants to have the same peak in the distribution system as in 2013, the distribution demand peak must not exceed 25,733 MWh. In order to reach such reduction, EV customers would need to feed up to 6,300 MWh in some specific hours. However, if we assume that only slow charging will take place, the amount to be demanded by EV customers is limited to 1,700 MWh (462,000 customers * 230 V * 16 A * 1 h). In this case, the distribution system peak demand can only be reduced to 29,605 MWh.

10

Therefore, it will be as if all the management would be obtained by using V2G capabilities or demand side management. However, the result would be the same if they reduced DER generation in super off-peak periods to increase it in peak periods, e.g. by using a thermal storage to switch off a micro-CHP unit at night and have it running at full load in the evening.


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The DSO estimates the demand in its system for each hour of the day. Then, it calculates the amount of energy that would exceed the objective of 29,605 MWh and distributes it among the first 8 hours of the day, so that in none of them EVs demand more than 1,700 MWh. By applying this algorithm to the demand presented in Figure 10, there are 763 hours in which demand must be managed. The total amount of energy to be managed is 1,877,728 MWh. The new distribution demand profile is presented in Figure 14.

Figure 14: Total demand in distribution grid in January 2020 (Smart grid scenario) Taking the distribution costs for 2013 as a basis, it can be assumed that the additional investment costs for the distribution system are just 722 M€, which means 603 million euro less than in the Conventional scenario. However, as in the Proactive scenario, the DSO will need to invest in an EV demand forecasting tool and in the communication infrastructure to be able to communicate with the EVSP. In addition, in the Smart grid scenario, the DSO will need to invest in the equipment needed to launch the constraint management market, and its operational costs will also increase. Likewise, the use of non-EV related DR will also increase the costs for the DSO. If the cost of all these systems (O&M and annuitized investment) can be assumed to be 3 million euro, the DSO will still be able to save 600 million euro per year. By assuming that the benefits are equally distributed among the whole value chain:


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•

The DSO would save 200 million euro per year, and it would use the remaining 400 million euro to pay for the constraint management service. Being a competitive market, the remuneration cost cannot be known in advance, so what the DSO would actually be saving would be the amount not requested in the market by EVSPs.

•

If the EVSPs can get in the market 400 million euro, they can keep 200 million euro and share the other half with EV customers. As in the case of the DSO, the ones who would actually fix the price for EVSPs’ offers would be EV customers.

•

EV customers would receive 200 million euro, i.e. about 432.90 euro per year and per customer. Being a competitive market, the most likely case would be the one in which constraint management is offered on a per-kWh basis. In this case, the average price they could obtain would be 106.51 €/MWh.

Or, in another way, if the price that EV customers obtain in the constraint management market is the maximum price that market agents can offer in the Spanish wholesale market (180.30 €/MWh, [37]), the total remuneration for them would be about 338.55 million euro, so there would still be another 261,45 million euro to be shared between the DSO and the EVSP.


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5. Conclusions When aiming at integrating EVs in distribution grids, the DSO may opt for either reinforcing the grid or for managing the load (or a combination of both strategies). A number of business scenarios have been selected for the analysis: •


•


•


•

Smart grid, with a granular control of EVs load management that allows for optimisation of hosting capacity, additionally considering the local connection of DER that can benefit from EV penetration, via a positive feedback loop.

Each of them will strongly be influenced by the regulatory conditions existing in each country. Governments and regulatory bodies should create a framework for personal and company relationships aiming at fostering and improving the aspects which are beneficial for a society, such as justice, employment and environmental protection. Therefore, in the case of e-mobility, regulation should promote business models and permit their profitability under global sustainability concepts rather than hindering the EV penetration. Regulation may positively or negatively affect EV deployment in many ways. If regulation is not flexible enough, or the requirements to perform some of the roles are too demanding, business models that can help the electricity system as a whole may never happen. On the contrary, too loose requirements may result in risk for system security. A detailed analysis must be carried out to evaluate which kind of regulatory change and update is needed for an envisioned EV grid integration scenario to take place and let all business actors involved to implement their activities in a profitable way. Requirements should be coherent throughout Europe to allow for interoperability. However, in order to bring solutions to the market as soon as possible, it might be advisable to propose different implementation phases with different targets and requirement levels according to the real evolution of the EV market. Demand-side management services related to e-mobility would be traded in a single market, where System Operators would be procuring these services to simultaneously fulfil the following conditions: •

Increase DERs hosting capacity of LV and MV electricity grid.

•

Avoid capital – intensive grid reinforcements, which have an impact on network tariff fees.

•

Sustain EVs loads uptake in the future.


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In order to achieve this, many issues should be taken into account, including: •

Competition in electricity markets and in providing core/value-added services.

•

Simplicity or difficulty for electricity consumers to contribute to system operation: administrative barriers, easiness of market mechanisms, cost of participation in the markets.

•

The setting up of conditions and technical pre-requirements to the EVs behaviour when connected to the network can help maintain system stability and use the EV to the purpose of large scale load management.

•

Remuneration to system operators for their investments in technology enabling large scale load management programmes.

Market should evolve to allow a broader spectrum of participants and mechanisms, for example related to demand participation. In addition to regulatory issues, the actual impact of the scenarios will depend on the existing conditions of distribution grids. Although a more detailed analysis will be performed in WP3, a lightweight economic analysis has been performed to give an idea of the economic impact of the different scenarios in distribution grids. Due to the lack of disaggregated data, a country-wide estimation of the impact at the distribution level has been done, which may provide only a partial view of the potential of the scenarios, particularly in the case of the Smart grid scenario. Moreover, the costs of launching each scenario for the DSO must be assessed in more detail to get a better estimate of their potential impacts. Under the assumptions considered for the analysis presented in this report, the Conventional scenario would increase the distribution system costs in more than 1,300 million euro. The use of a Proactive scenario would reduce that amount in 19 million euro, with just 4 hours in which EV charging should be managed. By applying an equal distribution of benefits between the DSO, the EVSP (or the EVSE Operator) and EV customers, these latter would receive about 3.25 € for allowing their charge to be controlled. The way in which the peak reduction in the Smart grid scenario is obtained will depend on the conditions of each specific distribution grid. Therefore, the alternatives to obtain the peak reduction range from creating demand side management markets for non-EV related electricity demand, the use of local DER to reduce the need for electricity flow in distribution grids (in this case, EV charging could be managed so that it meets DER production, instead of reducing demand peak), or by using EV’s V2G capabilities. This scenario can help reduce the required investments in distribution grids by about 10%, or about 600 million euro. This amount can then be used to remunerate EV customers (so that their total cost of ownership get more comparable to vehicles using fossil fuels) and EVSPs (so that their business becomes more profitable), incentivise DSOs to use smart operational procedures instead of building new lines and to reduce T&D fees to be satisfied by all electricity consumers. In this scenario, a load management market will be established, so the payment will be based on competitive offers.


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For the benefits to be equally distributed (as in the Proactive scenario), the average price to be obtained by EV customers for allowing the EVSP, the EVSE Operator or the DSO to manage their charging must be about 106.51 €/MWh. On the contrary, if the price EV customers demand is the maximum price that can be offered in the Spanish wholesale market (180.30 €/MWh), they will get about 340 million euro and the DSO and the EVSP would get 130 million each.


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6. References 6.1. Project documents [DOW] – Description of Work. [D1.1] – Deliverable 1.1, Current requirements, regulatory gaps and expected benefits (AIT). [D2.2] – Deliverable 2.2, Technical Requirements for tools/methods for smart grid integration of EVs (ENEL). [GA] – Grant Agreement.

6.2. External documents [1] G4V project website: http://www.g4v.eu/ [access in December 2013]. [2] Green eMotion project website: http://www.greenemotion-project.eu/ [access in December 2013]. [3] Eurelectric, Deploying publicly accessible charging infrastructure for electric vehicles: how to organise the market?. Eurelectric Concept Paper. July 2013. Available on-line at: http://www.eurelectric.org/media/84461/0702_emobility_market_model_final-2013-030-0501-01e.pdf [access in December 2013]. [4] International Organization for Standardization (ISO), ISO 15118-1:2013, Road vehicles - Vehicle to grid communication interface – Part 1: General information and use-case definition. International Standard. 16 April 2013. Available on-line at: http://www.iso.org/iso/catalogue_detail.htm?csnumber=55365 [access in December 2013]. [5] The European Parliament and The Council of the European Union, Directive 2009/72/EC of European Parliament and of the council of 13 July 2009 concerning common rules for the internal market in electricity and repealing Directive 2003/54/EC. Official Journal of the European Union, http://eurL211/55, 14 August 2009. Available on-line at: lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2009:211:0055:0093:EN:PDF [access in December 2013]. [6] European Network of Transmission System Operators for Electricity (ENTSO-E), The harmonised electricity market role model – Version 2011-01. December 2012. Available on-line at: http://www.ebix.org/Documents/role_model_v2011_01.pdf [access in December 2013]. [7] Coppola G. et al. Recommendations on grid-supporting opportunities for EVs, Green eMotion project deliverable 4.2. 15 November 2012. Available on-line at: http://www.greenemotionproject.eu/upload/pdf/deliverables/D4.2_Recommendations_on_gridsupporting_opportunities_of_EVs_V1.2_March2013.pdf [access in December 2013].


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[8] Spanish State Leadership, Ley 54/1997, de 27 de noviembre, del sector eléctrico. (Spanish electricity sector law). Official State Gazette, num. 285, 28 November 1997, p.35097-35126. Updated version (last update in 31 October 2013) available (only in Spanish) on-line at: http://noticias.juridicas.com/base_datos/Admin/l54-1997.html [access in December 2013]. [9] Spanish Ministry of Industry and Energy, Resolución de 30 de julio de 1998, de la secretaría de estado de energía y recursos minerales, por la que se aprueba un conjunto de procedimientos de carácter técnico e instrumental necesarios para realizar la adecuada gestión técnica del sistema eléctrico. Official State Gazette, num. 197, 18 August 198, p.28158-28183. Available (only in Spanish) on-line at: http://www.boe.es/boe/dias/1998/08/18/pdfs/A28158-28183.pdf [access in December 2013]. [10] Spanish Ministry of Industry, Energy and Tourism, Resolución de 18 de mayo de 2009, de la Secretaría de Estado de Energía, por la que se aprueban los procedimientos de operación del sistema 1.6, 3.1, 3.2, 3.3, 3.7, 7.2, 7.3 y 9 para su adaptación a la nueva normativa eléctrica. Official State Gazette, num. 129, 28 May 2009, p.44302-44443. Available (only in Spanish) online at: http://www.boe.es/boe/dias/2009/05/28/pdfs/BOE-A-2009-8813.pdf [access in December 2013]. [11] Spanish Ministry of Industry, Energy and Tourism, Resolución de 27 de febrero de 2008, de la secretaría general de energía, por la que se aprueban los procedimientos de operación 14.9 “liquidación y facturación del servicio de interrumpibilidad prestado por consumidores que adquieren su energía en el mercado de producción” y 15.1 “Servicio de gestión de la demanda de interrumpibilidad”. Official State Gazette, num. 61, 11 March 2008, p.14359-14364. Available (only in Spanish) on-line at: http://www.boe.es/boe/dias/2008/03/11/pdfs/A14359-14364.pdf [access in December 2013]. [12] Spanish National Energy Commission (CNE), Propuesta de procedimientos de operación básicos de las redes de distribución de energía eléctrica. 23 July 2009. Available (only in Spanish) on-line at: http://www.cne.es/cne/doc/publicaciones/cne112_09.pdf [access in December 2013]. [13] ADDRESS project website: http://www.addressfp7.org/ [access in December 2013]. [14] International Electrotechnical Commission (IEC), IEC 61851-1, Electric vehicle conductive charging system - Part 1: General requirements. International Standard. 25 November 2010. Available on-line at: http://webstore.iec.ch/webstore/webstore.nsf/Artnum_PK/44636 [access in December 2013]. [15] Spanish Ministry of Industry, Energy and Tourism, Proyecto de Real Decreto por el que se establecen los requisitos y las condiciones técnicas básicas de la infraestructura necesaria para posibilitar la recarga efectiva y segura de los vehículos eléctricos y a tal efecto se aprueba la ITC-BT 52 “instalaciones con fines especiales. Infraestructura para la recarga de vehículos eléctricos” y se modifican otras instrucciones técnicas complementarias del reglamento electrotécnico para baja tensión. 18 April 2012. Available (only in Spanish) on-line at: http://www.copitile.es/copitileon/documentacion/InstruccionesJCyL/Borrador%20ITCBT_52%2023042012.pdf [access in December 2013].


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[16] Spanish Ministry of Industry, Energy and Tourism, Propuesta de Real Decreto por el que se establece la regulación de las condiciones administrativas, técnicas y económicas de las modalidades de suministro de energía eléctrica con autoconsumo y de producción con autoconsumo. 18 July 2013. Available (only in Spanish) on-line at: [access in http://www.aeeolica.org/uploads/CCE-_Propuesta_RD_AUTOCONSUMO.pdf December 2013]. [17] Spanish Ministry of Industry, Energy and Tourism, Real Decreto 1699/2011, de 18 de noviembre, por el que se regula la conexión a red de instalaciones de producción de energía eléctrica de pequeña potencia. Official State Gazette, num. 295, 8 December 2011, p.130033-130064. Available (only in Spanish) on-line at: http://www.boe.es/boe/dias/2011/12/08/pdfs/BOE-A-201119242.pdf [access in December 2013]. [18] International Energy Agency (IEA), Global EV Outlook – Understanding the Electric Vehicle Landscape to 2020. April 2013. Available on-line at: http://www.iea.org/topics/transport/electricvehiclesinitiative/EVI_GEO_2013_FullReport.PDF [access in December 2013]. [19] European Commission (EC), Proposal for a Directive of the European Parliament and of the Council on the deployment of alternative fuels infrastructure. COM(2013) 18 final, Brussels, 24 http://eurJanuary 2013. Available on-line at: lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2013:0018:FIN:EN:PDF [access in December 2013]. [20] Osterwalder A.et al., Business Model Generation, John Wiley & Sons, 2010, ISBN: 978-047087641-1 3

[21] e value methodology website: http://e3value.few.vu.nl [access in December 2013]. [22] BUSMOD project website: http://e3value.few.vu.nl/projects/ourprojects/busmod/ [access in December 2013]. [23] Gordijn J., Value-based Requirements Engineering – Exploring Innovative e-Commerce Ideas. PhD. Thesis. Amsterdam, 25 June 2002. Available on-line at: http://e3value.few.vu.nl/docs/bibtex/pdf/GordijnVBRE2002.pdf [access in December 2013]. [24] Kartseva V. et al., Distributed Generation Business Modelling. 2 April 2004. Available on-line at: http://e3value.few.vu.nl/docs/misc/VUA_DGB_WP05_01_01.pdf [access in December 2013]. [25] Spanish Ministry of Industry, Energy and Tourism, Resolución de 27 de diciembre de 2012, de la Dirección General de Política Energética y Minas, por la que se aprueba el perfil de consumo y el método de cálculo a efectos de liquidación de energía, aplicables para aquellos consumidores tipo 4 y tipo 5 que no dispongan de registro horario de consumo, así como aquellos que han pasado de ser tipo 4 a tipo 3, según el Real Decreto 1110/2007, de 24 de agosto, por el que se aprueba el reglamento unificado de puntos de medida del sistema eléctrico, para el año 2013. Official State Gazette, num. 313, 29 December 2012, p.89084-89259. Available on-line at: http://www.boe.es/boe/dias/2012/12/29/pdfs/BOE-A-2012-15708.pdf [access in December 2013].


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[26] Spanish Ministry of Economy, Real Decreto 1164/2001, de 26 de octubre, por el que se establecen tarifas de acceso a las redes de transporte y distribución de energía eléctrica. Official State Gazette, num. 268, 8 November 2001, p.40618-40629. Updated version (last update in 8 December 2011) available (only in Spanish) on-line at: http://noticias.juridicas.com/base_datos/Admin/rd1164-2001.html [access in December 2013]. [27] Spanish Ministry of Industry, Energy and Tourism, Real Decreto 647/2011, de 9 de mayo, por el que se regula la actividad de gestor de cargas del sistema para la realización de servicios de recarga energética. Official State Gazette, num. 122, 23 May 2011, p.51098-51113. Available (only in Spanish) on-line at: http://www.boe.es/boe/dias/2011/05/23/pdfs/BOE-A-2011-8910.pdf [access in December 2013]. [28] Spanish National Energy Commission (CNE), Boletín Mensual de Indicadores Eléctricos y Económicos – Septiembre 2013. Available (only in Spanish) on-line at: http://www.cne.es/cne/doc/publicaciones/iap_indicadores-Sep13V2.pdf [access in December 2013]. [29] Spanish National Energy Commission (CNE), Metodología de Asignación de costes a los peajes de acceso eléctricos – Consulta pública. 14 June 2012. Available (only in Spanish) on-line at: [access in http://www.cne.es/cne/doc/publicaciones/cne_cp_metodologia_asignacion.pdf December 2013]. [30] Red Eléctrica de España (REE), Informe del Sistema Eléctrico Español – 2012. 12 June 2013. Available (only in Spanish) on-line at: [access in http://www.ree.es/sites/default/files/downloadable/inf_sis_elec_ree_2012_v2.pdf December 2013]. [31] European Automobile Manufacturer’s Association (ACEA), Vehicles in use. On-line news. Available at: http://www.acea.be/news/news_detail/vehicles_in_use [access in December 2013]. [32] Nissan, Leaf Brochure. Available on-line [access http://www.nissan.co.uk/content/dam/services/gb/brochure/Leaf+Brochure.pdf December 2013].

at: in

[33] Brady J, et al., Data Collection and Analysis in Green eMotion. External Stakeholder Report. 17 June 2013. [34] Hasset B. et al., Evaluation of the impact that a progressive deployment of EV will provoke on electricity demand, steady state operation, market issues, generation schedules and on the volume of carbon emissions – Electric vehicle penetration scenarios in Germany, UK, Spain, Portugal and Greece. 21 February 2011. Available on-line at: http://www.evmerge.eu/images/stories/uploads/MERGE_D32_EV_penetration_scenarios.pdf [access in December 2013]. [35] European Automobile Manufacturer’s Association (ACEA), The Automobile Industry Pocket Guide – 2013. Available on-line at: http://www.acea.be/images/uploads/files/POCKET_GUIDE_13.pdf [access in December 2013]


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[36] European Parliament, Alternative fuel stations; Transport Committee backs draft law to expand http://www.europarl.europa.eu/news/es/newsnetworks. On-line news. Available at: room/content/20131125IPR26108/html/Alternative-fuel-stations-Transport-MEPs-back-draft-lawto-expand-networks [access in December 2013]. [37] Spanish Ministry of Industry, Energy and Tourism, Resolución de 1 de agosto de 2013, de la Secretaría de Estado de Energía, por la que se aprueban las reglas de funcionamiento del mercado diario e intradiario de producción de energía eléctrica y el cambio de hora de cierre del mercado diario. Official State Gazette, num. 190, 9 August 2013, p.58231-58393. Available (only in Spanish) on-line at: http://www.boe.es/boe/dias/2013/08/09/pdfs/BOE-A-2013-8826.pdf [access in December 2013].


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7. Revisions 7.1. Track changes Name

Version

Carlos Madina

Date (dd.mm.yyyy) 05.12.2013

Eduardo Zabala

18.12.2013

AIT

Carlos Madina Armin Gaul

11.12.2013

18.12.2013 13.01.2014

1.0

Changes Subject of change Creation of the document

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3.0

Overall review

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1.1 2.0 4.0

Review of 1.0

Integration of review 1.1 Final and approved


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