Electric vehicle as a service (EVaaS):applications, challenges and enablers

Under the vehicle-to-grid (V2G) concept, electric vehicles (EVs) can be deployed as loads to absorb excess production or as distributed energy resources to supply part of their stored energy back to the grid. This paper overviews the technologies, technical components and system requirements needed for EV deployment. Electric vehicle as a service (EVaaS) exploits V2G technology to develop a system where suitable EVs within the distribution network are chosen individually or in aggregate to exchange energy with the grid, individual customers or both. The EVaaS framework is introduced, and interactions among EVaaS subsystems such as EV batteries, charging stations, loads and advanced metering infrastructure are studied. The communication infrastructure and processing facilities that enable data and information exchange between EVs and the grid are reviewed. Different strategies for EV charging/discharging and their impact on the distribution grid are reviewed. Several market designs that incentivize energy trading in V2G environments are discussed. The benefits of V2G are studied from the perspectives of ancillary services, supporting of renewables and the environment. The challenges to V2G are studied with respect to battery degradation, energy conversion losses and effects on distribution system

Network-Aware Electric Vehicle Coordination for Vehicle-to-Anything Value Stacking Considering Uncertainties

The increased adoption of electric vehicles (EVs) has led to the development of vehicle-to-anything (V2X) technologies, including vehicle-to-home (V2H), vehicle-to-grid (V2G), and energy trading of EVs in the local grid. The EV coordination can provide value to the grid and generate benefits for EVs. However, network constraints and uncertainties in renewable energy and demand pose significant challenges to EV coordination and restrict the realization of these benefits. This paper develops a rolling-horizon optimization problem for V2X value stacking to fully unlock the value of EV coordination, considering power network constraints (such as voltage limits) and uncertainties in the energy system. By coordinating EVs to perform V2H, V2G, and energy trading, our approach exploits the most valuable services in real-time. We also analyze the expected extra costs caused by the prediction errors to evaluate the impact of uncertainties on V2X value stacking. We validate our value-stacking model using real data from Australia's National Electricity Market (NEM), ISO New England (ISO-NE), and New York ISO (NY-ISO) in the US. The results show that V2X value stacking achieves significant benefits to EVs through energy cost reduction. The uncertainty in the load has a higher impact on the value-stacking performance than PV generation, indicating the importance of load prediction.Comment: The 59th annual IEEE Industrial and Commercial Power System Technical Conference (I&CPS 2023

Final report – Johan Cruijff ArenA Operational Pilot: Johan Cruijff ArenA Case Study

The Johan Cruijff ArenA (JC ArenA) is a big events location in Amsterdam, where national and international football matches, concerts and music festivals take place for up to 68,000 visitors. The JC ArenA is already one of the most sustainable, multi-functional stadia in the world and is realizing even more inspiring smart energy solutions for the venue, it’s visitors and neighbourhood. The JC ArenA presents a complex testbed for innovative energy services, with a consumption of electricity comparable to a district of 2700 households. Thanks to the 1 MWp solar installation on the roof of the venue, the JC ArenA already produces around 8% of the electricity it needs, the rest is by certified regional wind energy. Within the Seev4-City project the JC ArenA has invested in a 3 MW/2.8 MWh battery energy storage system, 14 EV charging stations and one V2G charging unit. The plan was to construct the 2.8 MWh battery with 148 2nd life electric car batteries, but at the moment of realisation there were not enough 2nd life EV batteries available, so 40% is 2nd life. The JC ArenA experienced compatibility issues installing a mix of new and second-life batteries. Balancing the second-life batteries with the new batteries proved far more difficult than expected because an older battery is acting different compared to new batteries. The EV-based battery energy storage system is unique in that it combines for the first time several applications and services in parallel. Main use is for grid services like Frequency Containment Reserve, along with peak shaving, back-up services, V2G support and optimization of PV integration. By integrating the solar panels, the energy storage system and the (bi-directional) EV chargers electric vehicles can power events and be charged with clean energy through the JC ArenA’s Energy Services. These and other experiences and results can serve as a development model for other stadiums worldwide and for use of 2nd life EV batteries. The results of the Seev4-City project are also given in three Key Performance Indicators (KPI): reduction of CO2-emission, increase of energy autonomy and reduction in peak demand. The results for the JC ArenA are summarised in the table below. The year 2017 is taken as reference, as most data is available for this year. The CO2 reductions are far above target thanks to the use of the battery energy storage system for FCR services, as this saves on the use of fossil energy by fossil power plants. Some smaller savings are by replacement of ICE by EV. Energy autonomy is increased by better spreading of the PV generated, over 6 instead of 4 of the 10 transformers of the JC ArenA, so less PV is going to the public grid. A peak reduction of 0.3 MW (10%) is possible by optimal use of the battery energy storage system during the main events with the highest electricity demand

A robust vehicle to grid aggregation framework for electric vehicles charging cost minimization and for smart grid regulation

In this paper, we propose an optimal hierarchical bi-directional aggregation algorithm for the electric vehicles (EVs) integration in the smart grid (SG) using Vehicle to Grid (V2G) technology through a network of Charging Stations (CSs). The proposed model forecasts the power demand and performs Day-ahead (DA) load scheduling in the SG by optimizing EVs charging/discharging tasks. This method uses EVs and CSs as the voltage and frequency stabilizing tools in the SG. Before penetrating EVs in the V2G mode, this algorithm determines the on arrival EVs State of Charge (SOC) at CS, obtains projected park/departure time information from EV owners, evaluates their battery degradation cost prior to charging. After obtaining all necessary data, it either uses EV in the V2G mode to regulates the SG or charge it according to the owner request but, it ensure desired SOC on departure. The robustness of the proposed algorithm has been tested by using IEEE-32 Bus-Bars based power distribution in which EVs are integrated through five CSs. Two intense case studies have been carried out for the appropriate performance validation of the proposed algorithm. Simulations are performed using electricity pricing data from PJM and to test the EVs behaviour 3 types of EVs having different specifications are penetrated. Simulation results have proved that the proposed model is capable of integrating EVs in the voltage and frequency stabilization and it also simultaneously minimizes approximately $1500 in term of charging cost for EVs contributing in the V2G mode each day. Particularly, during peak hours this algorithm provides effective grid stabilization services.info:eu-repo/semantics/publishedVersio

SEEV4City INTERIM 'Summary of the State of the Art' report

This report summarizes the state-of-the-art on plug-in and full battery electric vehicles (EVs), smart charging and vehicle to grid (V2G) charging. This is in relation to the technology development, the role of EVs in CO2 reduction, their impact on the energy system as a whole, plus potential business models, services and policies to further promote the use of EV smart charging and V2G, relevant to the SEEV4-City project

Demand Side Management of Electric Vehicles in Smart Grids: A survey on strategies, challenges, modeling, and optimization

The shift of transportation technology from internal combustion engine (ICE) based vehicles to electricvehicles (EVs) in recent times due to their lower emissions, fuel costs, and greater efficiency hasbrought EV technology to the forefront of the electric power distribution systems due to theirability to interact with the grid through vehicle-to-grid (V2G) infrastructure. The greater adoptionof EVs presents an ideal use-case scenario of EVs acting as power dispatch, storage, and ancillaryservice-providing units. This EV aspect can be utilized more in the current smart grid (SG) scenarioby incorporating demand-side management (DSM) through EV integration. The integration of EVswith DSM techniques is hurdled with various issues and challenges addressed throughout thisliterature review. The various research conducted on EV-DSM programs has been surveyed. This reviewarticle focuses on the issues, solutions, and challenges, with suggestions on modeling the charginginfrastructure to suit DSM applications, and optimization aspects of EV-DSM are addressed separatelyto enhance the EV-DSM operation. Gaps in current research and possible research directions have beendiscussed extensively to present a comprehensive insight into the current status of DSM programsemployed with EV integration. This extensive review of EV-DSM will facilitate all the researchersto initiate research for superior and efficient energy management and EV scheduling strategies andmitigate the issues faced by system uncertainty modeling, variations, and constraints

A reference architecture for cloud-edge meta-operating systems enabling cross-domain, data-intensive, ML-assisted applications: architectural overview and key concepts

Future data-intensive intelligent applications are required to traverse across the cloudto-edge-to-IoT continuum, where cloud and edge resources elegantly coordinate, alongside sensor networks and data. However, current technical solutions can only partially handle the data outburst associated with the IoT proliferation experienced in recent years, mainly due to their hierarchical architectures. In this context, this paper presents a reference architecture of a meta-operating system (RAMOS), targeted to enable a dynamic, distributed and trusted continuum which will be capable of facilitating the next-generation smart applications at the edge. RAMOS is domain-agnostic, capable of supporting heterogeneous devices in various network environments. Furthermore, the proposed architecture possesses the ability to place the data at the origin in a secure and trusted manner. Based on a layered structure, the building blocks of RAMOS are thoroughly described, and the interconnection and coordination between them is fully presented. Furthermore, illustration of how the proposed reference architecture and its characteristics could fit in potential key industrial and societal applications, which in the future will require more power at the edge, is provided in five practical scenarios, focusing on the distributed intelligence and privacy preservation principles promoted by RAMOS, as well as the concept of environmental footprint minimization. Finally, the business potential of an open edge ecosystem and the societal impacts of climate net neutrality are also illustrated.For UPC authors: this research was funded by the Spanish Ministry of Science, Innovation and Universities and FEDER, grant number PID2021-124463OB-100.Peer ReviewedPostprint (published version