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The demand for electric vehicle supply equipment (EVSE) is increasing because of the rapid shift toward electric transport. Introducing EVSE on a large scale into the power grid can increase power demand volatility, negatively affecting frequency stability. A viable solution to this challenge is the development of smart charging technologies capable of performing frequency regulation. This paper presents an experimental proof of concept for a new frequency regulation method for EVSE utilizing a distributed control architecture. The architecture dynamically adjusts the contribution of electric vehicles (EVs) to frequency regulation response based on the charging urgency assigned by the EV users. The method is demonstrated with two Renault ZOEs responding to frequency fluctuation with a combined power range of 6 kW in the frequency range of 50.1 to 49.9 Hz. The results confirm consistent power sharing and effective frequency regulation, with the system controlling the engagement of the EVs in frequency regulation based on priority. The delay and accuracy analyses reveal a fast and accurate response, with the cross-correlation indicating an 8.48 s delay and an average undershoot of 0.17 kW. In the conclusions, the paper discusses prospective improvements and outlines future research directions for integrating EVs as service providers.

The increasing penetration of electric vehicles (EVs) in the power system has raised concerns regarding the management of charging sessions to prevent systems from overloading. This paper proposes a distributed control method of EV clusters that enables controllers to make decisions independently, using only commonly broadcasted signals. Additionally, the method also includes a user-based power scheduling mechanism that prioritizes EVs based on their respective energy needs and time availability. A power-constrained system is considered for the case studies, where the system is only capable of charging one EV with maximum power. Simulation results demonstrate that the system effectively accommodates and schedules multiple EVs to charge simultaneously in a restricted environment without compromising user satisfaction. In instances of communication loss, the system demonstrates the capability to sustain the charging process through resource reallocation. The method is characterized by its distributed and autonomous nature, which ensures both robustness and effective operation.

The present deliverable D2.3 presents the modelling framework and research backbone to the development of Vehicle-to-Everything (V2X) strategies for the demonstration activities in Denmark as part of the EV4EU project. The charging infrastructure at both locations of the Danish demo (Risø and Campus Bornholm) is identical and comprises six Alternating Current (AC) chargers with two connectors (dual outlet) providing 11 kW charging power each. The twelve charge points are connected to the grid with a maximum cluster power limit of 43 kW. The developed V2X strategies aim to provide a seamless integration of the charging infrastructure in the electricity system and serve two main purposes. Firstly, they ensure the compliance with the grid connection limit, as the cluster limit of 43 kW is lower than the sum of the rated power of all charge points. Secondly, they utilize the flexibility of charging processes to provide services both behind and in front of the meter. The modelling framework comprised forecast models to predict the Electric Vehicle (EV) charging demand, as well as the expected generation from local Renewable Energy Sources (RES). The forecast models were integrated in the control models developed within the scope of this work. Moreover, users of the charging infrastructure at the Danish demo sites can provide their estimated departure time and energy needs via an app, which is taken into account in the decision-making process. The control models facilitate the coordination of EV charging, which offers the possibility to provide services to local and external grids. This is tested through a set of different scenarios and control objectives. The conducted simulations utilize actual Photovoltaic (PV) production and EV charging data from winter and summer weeks in Denmark. It is shown that the proposed control methods achieve the compliance with local grid connection limits and are further able to provide demand response to Distribution Sys

The deliverable Business models centred in the V2X value chain aims to present new state-of-the-art business models developed within the EV4EU project. The study is centred on the countries of the EV4EU project members (Denmark, Greece, Portugal, and Slovenia), considering stakeholders and local specifics that influence the development and deployment of V2X services. However, most of the business models can be applied in other countries and regions. The proposed Business Models focus on Vehicle-to-Everything (V2X) technology and propose and implement user-centric V2X management strategies following bottom-up approach. They provide benefits to the main stakeholders and investigate value to the entire V2X value chain to set the stage for the mass deployment of electric vehicles. This document presents a description of the methodology used to develop the proposed Business Models, namely the Value Proposition Design that uses Business Model Canvas and Value Proposition Canvas as adopted due to its adequacy to represent business based on services. The process started with the five initial business models outlined in the project proposal. During the iterative business model development, twelve business models were created, namely TSO services for RES curtailment management, Sharing Charging Business Model, Electric Vehicle Fleet Management Services, Distribution System Operator Flexibility Services - Voltage Regulation via price signals, Virtual Power Plant Business Model, Flexibility Services operated by Distribution System Operator Business Model, Vehicle-to-Everything Stations Business Model, Distribution System Operators bound by Flexible Capacity Contract, Business Model for Charging Point Operators, Business Model for Cloud Platform Manager operating the Open V2X Management Platform, Business Model for Private Parking Lot Managers, and Business Model for Public Parking Lot Managers. Furthermore, the deliverable Business models centred in t

The Control Strategies for V2X Integration in Buildings deliverable presents decision-making models capable of integrating Vehicle-to-Everything (V2X) in the optimal energy management of buildings with local generation capabilities. The developed control methods will be considered in the Portuguese demonstrator of the EV4EU project, in São Miguel Island, Azores, and the Danish demonstrator, in the island of Bornholm, Denmark, to test the benefits of smart charging techniques. Both developed control frameworks rely on collecting and utilizing historical data (on building load, photovoltaic (PV) production and Electric Vehicle (EV) data) for forecasting purposes. The Danish framework utilizes a forecasting-assisted rolling-horizon optimisation approach, while the Portuguese framework utilizes a daily planning stage (which determines a predefined goal), followed by the real-time operation stage. The control objective in the Danish case is to optimally manage EV charging for minimizing energy costs while respecting a reduced line limit for the aggregated EV charging power, while for the Portuguese case various scenarios are considered, whose objective, apart from minimizing energy costs, is the activation of grid services, specifically targeting smaller islanded systems, such as the one in Azores. The developed strategies were tested on a number of simulation scenarios which relied on historical data from the sites and a few available sources to replace the missing EV data because during the execution of the task the demonstration sites were not yet operational. Simulation results showed that the inclusion of forecasts and an optimisation-based control approach can bring substantial economic benefits and reduce peak power, thus reducing the required grid connection size for the chargers. Additionally, those preliminary results indicate that the added benefit of using sophisticated forecasting techniques is rather low, pointing at the use of s

This deliverable assesses the impact of several key performance indicators (KPIs) for the demonstration activities carried out in Use Cases (UCs) 4 and 5 in the Lighthouse Island of Bornholm. Use Case 4 demonstrated the feasibility of a DC microgrid acting as a hybrid fast charging station for electric vehicles. This deployed intervention featured a novel battery system architecture and a photovoltaic installation, and was located at an educational institute in Rønne on Bornholm over a period of 15 months. This report gathers the main numerical outcomes and analyses the impact on key metrics such as EV charging fulfillment, carbon emission reduction, and self sufficiency. Over the entire demonstration phase with this hybrid charging station (HCS), 2008 EV charging sessions were recorded, amounting to a total charged energy of 21.8 MWh. An overall proportion of 37.7% of the energy delivered to EVs was provided by the local PV system, defining the system’s self-sufficiency. Furthermore, 90% of the total energy provided by the local PV system was utilized for EV charging, defining the system’s self-consumption. The operational CO2 emissions of the HCS amounted to 2092 kgCO2, which is a reduction of around 1 ton CO2 compared to a charging system without local PV system (3,094 kgCO2), and a reduction of 14.5 tons CO2 compared to the emissions caused by ICE vehicles (17,649 kgCO2). Use Case 5 aimed at demonstrating flexibility aspects of distributed generation units to support the electrical, thermal, and transportation sectors. The focus of the investigation has been a biogas plant located in Aakirkeby, Bornholm, both for simulation studies and experimental tests. Moreover, the controllability of other distributed generation units, such as wind and solar PV, has been experimentally assessed within the demonstration activities. The last part was concerned with more hypothetical scenarios o

Vehicle-to-everything (V2X) use cases (UCs) repository is the final output of the work conducted in task 1.5 - Use case specifications of the Horizon Europe EV4EU project, led by INESC ID. This task aimed to define the specifications of the business UCs (BUCs), addressing the business relationships between different stakeholders. These BUCs will be tested in the EV4EU project demonstration sites. The deliverable D1.5 aims to present the V2X UCs repository and to provide the direct link to the file. Electric vehicles (EVs) are emerging as a solution to reduce the impact of transportation sector in the environment. Several challenges need to be addressed during the transition between traditional internal combustion engine vehicles to new electric ones. One of the challenges of the EV mass adoption is the integration in power systems. The use of EVs will increase the energy demand and the peak consumption. However, EVs also introduce a new source of flexibility that can be managed by system operators both at transmission and distribution levels. Considering the different roles of the stakeholders, we developed a V2X UCs repository with seven BUCs based on the new business models defined in deliverable D1.4 - Business models centred in the V2X value chain, and the needs and goals of the EVEU demonstrators. The proposed BUCs follow the standard methodology proposed by International Electrotechnical Commission (IEC), allowing a faster replicability and adoption by different stakeholders. The BUCs identified were: BUC1) Participation of V2X in Electricity Markets through a Virtual Power Plant, BUC2) System level V2X/Renewable Energy Resources (RES) Coordination, BUC3) Participation of V2X in Explicit Demand Response to Congestion Management Service, BUC4) Participation of V2X in Implicit DR to voltage control and V2X/RES coordination in distribution system, BUC5) Participation of V2X Managers in Dynamic Contracts to support DSO operation, BUC6) Participat

With the increasing electrification of transport and heating and the associated uptake of both electric vehicles (EVs) and heat pumps, distribution system operators (DSOs) face significant operational challenges such as congestion and/or voltage violations. At the same time, the proliferation of distributed generation (primarily PV) at the distribution level creates new challenges (such as potential overvoltage) and opportunities. Due to this strong increase in both local consumption and generation, DSOs need measures to enhance their operational flexibility and align flexible consumption units with the intermittent, variable, and stochastic renewable generation. Deliverable D4.2 Scheduling and Real-Time Operation Strategies to Control V2X Flexibilities first reviews various DSO flexibility mechanisms ranging from use-of-system tariffs to market-based approaches. The focus of this work is on examining the rationale and functioning behind flexible capacity contracts and variable grid tariffs, focusing on electric vehicles as flexible loads. Variable tariffs can be used to steer flexible consumption and achieve a more efficient network operation compared to their flat counterpart. However, they cannot guarantee that network constraint violations will not occur. For this reason, they are complemented by flexible capacity contracts, which limit the consumption of users (in return for financial compensation) and provide operational guarantees. A detailed description of both mechanisms is provided, while illustrative examples showcase how they can be used by DSOs. Further, a formalised methodology in terms of designing variable grid tariffs in the presence of a local flexibility market using capacity contracts is developed. The synergies achieved by combining both mechanisms are showcased. In addition, the interaction between the DSO and charge point operators (CPOs) that aggregate the flexibility of individual EVs is detailed with a review of currently

This deliverable consolidates the final specifications for the Use Cases (UCs) to be demonstrated in Denmark. The deployment plan includes an initial assessment of the current infrastructure at both locations, i.e., Risø and Campus Bornholm. Risø is a research campus of the Technical University of Denmark (DTU) and located in Roskilde, while Campus Bornholm is an educational institute in the main town Rønne on the island of Bornholm. Based on the assessment of both locations, the present document presents a detailed description of hardware and software that will be implemented, and the associated construction works required for their deployment. The Electric Vehicle (EV) charging infrastructure is identical at both locations and comprises six Alternating Current (AC) chargers (22 kW), respectively. Each of the six AC chargers has two outlets, providing the opportunity for twelve EVs to be connected at the same time. The charging infrastructure is integrated via a 43 kW grid connection, and operated through a load management system enabling the maintenance of aggregated consumption below a specified threshold. This offers various benefits, e.g., preventing component overloading or the provision of both local and external services, such as peak shaving, increasing self-sufficiency, and frequency control. Each charger deployed in this project is equipped with a controller that enables the charger to make autonomous control decisions. This facilitates distributed control schemes where all chargers are provided with global quantities, such as the cluster reference power and the actual cluster consumption, based on which all chargers individually control their respective charging session to collectively meet the cluster requirements. Users of the charging infrastructure will start their charging sessions through an app, which is developed as part of the EV4EU project. The app allows the user to provide key inputs, such as the anticipated parking

This deliverable D6.5 outlines the replication action plans based on the results of the demonstration activities performed in UC4 and UC5 within the Lighthouse Island Bornholm. UC4 investigated the transition to DC microgrids, while UC5 focuses on local bio-based economies supporting the electrical, thermal, and transport systems. The island of Bornholm anticipates a substantial increase in electric vehicles (EVs), projected to grow from the current 350 EVs (2022) to 5600 EVs by 2030, and 28,000 EVs by 2050. To meet the rising charging demand in the upcoming years, a sufficient network of public charging infrastructure is required. While the demand for high-power chargers (> 100 kW) in Bornholm is comparatively lower than in other Danish municipalities, the island will still require three high-power chargers by 2030, 16 by 2040, and 21 by 2050. UC 4 focused on the demonstration of a DC microgrid comprising a 314 kWh battery system, two connectors for EV high-power charging at 175 kW each, a 61 kWp PV installation, and an inverter serving as an interface to the local 43 kW distribution grid. Deliverable D6.5 summarizes key insights from more than one year of operation with this Hybrid Charging System (HCS) and evaluates the performance based on various key performance indicators (KPIs). Subsequently, a replication study for UC4 is conducted that projects the deployment of multiple HCSs across the island to meet the targets for public high-power chargers. The replication plan of UC4 will ultimately increase the PV capacity installed in Bornholm’s HCSs by 1.3 MW by 2050, generating 1.4 GWh of renewable energy annually. The integrated batteries in the HCSs play a crucial role, providing a total storage capacity of 6.6 MWh. This storage capacity enables the utilization of 58 % of the PV energy directly for EV charging, with the surplus being exported to the grid. Furthermore, the batteries facilitate the seamless integration of high-power chargers into Bornho

To secure balanced operation of electric networks and mitigate costly grid reinforcements, distributed generation (DG) units play a role in providing flexibility activation services. This paper analyses high-resolution measurements and reports lessons learnt from experimental active power control (APC) of installed DG units – two PV plants, a wind farm, and a biogas plant – in operation on the Danish island of Bornholm. The paper evaluates how quickly these units can respond to flexibility requests and how accurate and precise their output is when following specific active power setpoints. This assessment helps exploring the potential of DG units in providing grid services, either standalone or as part of a virtual power plant, within existing technology standards. The experiments demonstrate satisfactory performance of DG units when receiving APC requests, with PV inverters and biogas generators exhibiting high accuracy (mean deviation from setpoints of ± 0.1% and ± 0.15%, respectively). Furthermore, when subject to power limitation requests, PV inverters and wind turbines show less variation in their responses (± 0.05% and ± 0.6%, respectively) compared to biogas generators (± 0.1%). The results further highlight the significance of appropriately tuning internal control settings within DG units to ensure continuous flexible operation and avoid undesirable dynamics.

The transition from fossil-based to fully renewable energy systems requires innovative actions and extensive testing of new solutions. Battery energy storage systems (BESSs) are sought to be of key importance for integrating variable renewable energy sources (vRES) into the grid, and help improving the flexibility of power systems. As part of the H2020 Insulae project, an innovative reconfigurable battery system has been developed in Denmark and installed in a DC hybrid charging station (HCS) located on the island of Bornholm. Besides the BESS itself, the HCS consists of a 61 kWp photovoltaic (PV) system, one grid-connected three-phase bi-directional inverter interfacing to the local AC distribution grid, and two electric vehicle (EV) fast chargers. This paper gathers the operational results and lessons learned from more than a year of demonstration, subject to high observability of all single units. The demonstration provides hands-on experience with the operation of this novel battery design embedded in a hybrid charging station. Throughout the operation period, 2008 EV charging sessions were recorded, amounting to a total charged energy of 21.8 MWh. An overall proportion of 37.7% of this energy was provided by the local PV system, defining the system’s self-sufficiency. Similarly, 90% of the PV energy was utilized for EV charging, defining the system’s self-consumption. Furthermore, the results showcase that the energy management system (EMS) specifically utilized time windows of low spot prices to import energy in periods of low PV production or high EV demand, thus, reducing operating costs. While the design of the HCS is promising, the paper discusses the drawbacks of the implemented EMS, and suggests potential improvements. Finally, the architecture of the HCS prototype is compared to three alternative layouts with respect to both operating and investment costs.

Uncoordinated charging of electric vehicle (EV) clusters can lead to unanticipated surges in demand that strain the grid, hence reducing its reliability. To address this challenge, this paper proposes a semi-distributed control method for EV clusters charging where the decision process takes place locally, rather than relying on an external controller. The method ensures that charging demand can be fulfilled while achieving several goals, including following local renewable energy generation, pausing charging for transformer protection, and continuing charging progress in the absence of external information. The proposed method is validated through simulations and experimental tests during a public demonstration. The results demonstrate the functionality of the control method and show that it can effectively manage the charging of a cluster of EVs while reducing strain on the power grid.