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At least 19 records

Key Performance Indicators for Vehicle Grid Integration

Electric vehicle (EV) sales account for a rapidly growing portion of the light-duty vehicle market and a portion of medium and heavy-duty fleet vehicles. However, in many locations, charging stations will require costly utility grid upgrades with long lead times. Today, there are a few methods of smart charge management (SCM) which can reduce the costs and wait times for electric vehicle supply equipment (EVSE) interconnection approvals, as well as reduce impacts of the charging stations on the grid and on EV driver transportation costs. It is crucial for the EV charging industry to understand the vehicle grid integration (VGI) requirements for EVSE to prevent adverse impacts from EVSE interconnections and assure that charging loads and interconnections are affordable.

33 - ADVANCED PROPULSION SYSTEMS↗

Communications Reliability for Vehicle Grid Integration

Electric Vehicles (EVs) adoption rate has been steadily increasing in the US leading to a growing number of charging stations including faster DC (Direct Current) chargers and slower Level 1 and Level 2 AC (Alternating Current) chargers. This increase in demand for electricity is further exacerbated by recent developments in Artificial Intelligence (AI) technology, advanced manufacturing, and digitization. These factors will require electric utilities to upgrade their infrastructure to keep up with the increasing electrical demand (especially during peak hours). An easy way to counteract the need for these upgrades is to shift a major chunk of active charge sessions (durations where there is energy transfer from charger to EV's propulsion battery) to off-peak hours thereby flattening the load curve and making the infrastructure more resilient. This concept is known as Smart Charge Management (SCM). EV owners also benefit from SCM since it lowers their charging costs and consequently their transportation costs by prioritizing charging during off-peak hours. SCM takes advantage of EV's capability to act as a controllable load or DER (Distributed Energy Resource). This report summarizes the reliability analysis performed on the communication required for two of these SCM use-cases. This analysis only focuses on SCM strategies for unidirectional charging (energy transfer from EVSE to EV or V1G) and not bidirectional charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A systematic solution to quantify economic values of vehicle grid integration

We report Vehicle-Grid-Integration (VGI) supplies one of the potential benefit extensions for electric vehicles (EVs) to make use of their parking time, which enables the EVs to provide grid services while still meeting consumer driving needs. However, the costs, benefits and risks of VGI still remain unclear, which limits the development of the VGI to promote the interaction between the EV and grid. In this study, we propose an integrated framework to quantify and utilize the aggregate flexibility of the EVs to supply the grid services in electricity markets. The integrated solution includes five sub-modules that cover end-to-end functionalities from individual EV energy consumption estimation to final monetary values calculation of providing grid services. Both wholesale market and local level charging management are formulated in the optimization module. A predictive control algorithm is proposed to allocate power to individual vehicles in real time, considering uncertainties from dispatch signal and travel behavior. Simulation results from 10,000 EVs indicate that the proposed optimization methods can significantly reduce the system cost in both wholesale market and retail market. Local tariff optimization reduces the electricity cost by 24.4% compared to uncontrolled charging. Wholesale market optimization results show that $\$$691 and $\$$255 revenues can be captured by each EV in ERCOT and CAISO markets per year, although with a conservative assumption on battery throughput cost at 0.16$\$$/kWh.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Impacts and emerging research opportunities in Vehicle-Grid Integration for transportation: A review

This review provides a comprehensive examination of Vehicle-Grid Integration (VGI) technologies and their impacts on transportation systems, with a particular emphasis on the transportation-energy nexus. It systematically explores how VGI affects key transportation applications such as charging infrastructure planning, electric vehicle (EV) routing, smart charging coordination, shared mobility, and dynamic pricing. By synthesizing recent literature from both transportation and energy systems perspectives, this study highlights how advanced methodologies, such as reinforcement learning, game theory, and optimization techniques, are used to model the complex interactions between EVs, mobility patterns, and distributed energy systems. Furthermore, the review also identifies critical challenges, including behavioral factors, data limitations, and system scalability. Drawing on these insights, the paper outlines emerging research opportunities to support the design of integrated, resilient, and user-centric VGI solutions that advance sustainable mobility and energy system efficiency.

Charging coordination↗

Smart Charge Management and Vehicle Grid Integration Deep Dive

The U.S. Department of Energy (DOE) Electric Vehicles at Scale Laboratory Consortium (EVs@Scale Lab Consortium) is accelerating research to support the establishment of a secure and scalable national network of charging infrastructure. Critical to this effort is an understanding of the potential grid impacts of EV charging and possible smart charge management (SCM) or vehicle-grid integration (VGI) capabilities that could mitigate these impacts. The EVs@Scale SCM/VGI Pillar is analyzing the impacts of EV charging and developing and demonstrating the capabilities of both SCM and VGI with many different vehicle use cases and grid scenarios. This deep dive discussion of the project encompasses the progress and future plans for the analysis components of the FUSE (Flexible charging to Unify the grid and transportation Sectors for Evs at scale) project.

ADVANCED PROPULSION SYSTEMS↗

The Future of Vehicle Grid Integration: Harnessing the Flexibility of EV Charging

This document lays out a shared vision for a beneficial, EV-integrated future where EVs are safely and securely connected, reliably served, and harmonized with the electric grid. It was developed as part of the U.S. Department of Energy’s (DOE) EVGrid Assist initiative. Stakeholder input was gathered through individual and collective conversations, including eight listening sessions with more than 100 participants representing utilities of different sizes and operating structures, manufacturers of vehicles and chargers, national associations, standards organizations, Tribes, fleet managers, consumer advocates, charging network operators, community-based organizations, utility regulators, consultants, vendors, labor, and environmental justice organizations. This document focuses on the future of electric on-road U.S. transportation, specifically the integration of light-duty vehicles (LDV) and medium- and heavy-duty vehicles (MHDV) and their charging infrastructure with the electric grid. However, many of the insights here may apply to electrifying other transportation modes, as well as other distributed energy resources (DER).

EVGrid Assist initiative, EV-integrated future, el↗

The Future of Vehicle Grid Integration: Harnessing the Flexibility of EV Charging

This document lays out a shared vision for a beneficial, EV-integrated future where EVs are safely and securely connected, reliably served, and harmonized with the electric grid. It was developed as part of the U.S. Department of Energy’s (DOE) EVGrid Assist initiative. Stakeholder input was gathered through individual and collective conversations, including eight listening sessions with more than 100 participants representing utilities of different sizes and operating structures, manufacturers of vehicles and chargers, national associations, standards organizations, Tribes, fleet managers, consumer advocates, charging network operators, community-based organizations, utility regulators, consultants, vendors, labor, and environmental justice organizations. This document focuses on the future of electric on-road U.S. transportation, specifically the integration of light-duty vehicles (LDV) and medium- and heavy-duty vehicles (MHDV) and their charging infrastructure with the electric grid. However, many of the insights here may apply to electrifying other transportation modes, as well as other distributed energy resources (DER).

EVGrid Assist initiative, EV-integrated future, el↗

A Vehicle-to-Grid planning framework incorporating electric vehicle user equilibrium and distribution network flexibility enhancement

The rapid surge in electric vehicle (EV) adoption, coupled with advancements in charging technologies, emphasizes the critical necessity for expanding EV recharging infrastructure. Simultaneously, the Distribution Network (DN) encounters escalating challenges in meeting charging demand during peak traffic periods. Consequently, there is a mounting demand for the deployment of innovative Vehicle-to-Grid (V2G) technologies to augment the DN’s flexibility in power dispatch and alleviate travel costs for EV users. Hence, this paper proposes an EV-user-equilibrium-(UE)-constrained V2G planning framework that enhances flexibility in the DN. The framework aims to ascertain the optimal placement and capacity of EV charging stations (EVCSs) and V2G charging piles within the Transportation Network (TN). It takes into account the equilibrium condition stemming from competitive EV charging and routing behaviors alongside the optimal expansion of DN energy resources to accommodate the electricity supplied by the V2G piles. This study commences by analyzing EV drivers’ travel decisions, considering the influence of charging and V2G pile locations and sizes. Subsequently, we tackle the Traffic Assignment Problem with User Equilibrium (TAP-UE) model to characterize the steady-state traffic flow distribution of EVs. Following this, we formulate the optimization model for the Coordinated Power and Transportation Network (CPTN), which encompasses the optimal expansion of DN facilities and traffic flow regulation under UE conditions. To mitigate the computational complexity associated with the V2G planning model, we introduce a series of linearization methods to obtain a manageable Mixed-Integer Linear Programming (MILP) solution. Finally, to validate the efficacy of our proposed planning framework, we apply it to two test systems, including a real-world case study. Through these case studies, we explore the necessity and potential benefits of V2G technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Smart Charging of Fleet and Personal Electric Vehicles through Joint Vehicle-to-Grid Optimization

As electric vehicle (EV) adoption accelerates, vehicle-to-grid (V2G) strategies offer advantages over unmanaged charging (V0G) by enhancing grid stability, reducing fleet operation costs, and supporting integration of variable generation resources. This research develops a day-ahead optimization framework linked with agent-based simulations to evaluate coordinated V2G participation by fleet and personal EVs under 5 energy-pricing settings in Austin, Texas. Three scenarios (V0G, fleet-only V2G, and joint-V2G) are examined, considering real-time price and grid profiles, health-damage costs, and operational constraints for both fleet and personal EVs. Results show how V2G scenarios shift fleet EV charging to mid-day while enabling strategic battery-discharge during evening peaks, mitigating grid stress and lowering EV energy costs. V2G delivers close to 80% energy-cost savings for a 2000-EV fleet in Austin on grid-stressed days, with 55% lower charging pollutant outputs. Joint-V2G amplifies system-level benefits by complementing fleet discharge, but smart-charging equipment costs can offset those benefits.

Electric vehicle↗

Vehicle-to-Grid Electric School Bus Commercialization Project

The Vehicle-to-Grid Electric School Bus Commercialization Project was chartered to advance the idea that the batteries in electric vehicles can play a valuable role in supporting the electric grid. As deployment of wind and solar generating resources accelerates to provide an ever-greater share of the nation’s electricity, concurrent investment in solutions that can offset their inherent intermittency will be necessary. Many types of energy storage systems have been proposed, and more than one type will find an economic fit in the grid of the future. Electric vehicle batteries have the potential to provide grid support services in an advantaged manner. The project’s method of exploring this proposition called for development and demonstration of a fleet of vehicle-to-grid (V2G) electric school buses. School buses were chosen because their energy storage capacity is large relative light-duty vehicles; they are typically domiciled in fleet settings; and the number of hours per year they are available for grid support services is high on an absolute basis (generally 80-85% of the hours in a year) and relative to other categories of medium- and heavy-duty vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

Electric Vehicle Standards – Grid Service Capabilities: Evaluation of IEEE 2030.13, SAE J3072, ISO 15118-2, ISO 15118-20, OCPP, IEC 61850-7-420, IEEE 2030.5, and OpenADR

This report examines a selection of standards associated with vehicle-grid-integration. The standards will be evaluated on their support for electric vehicles to provide/participate in component distributed energy resource grid services. Challenges associated with the deployments of the standards will also be discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Los Angeles Air Force Base Vehicle-to-Grid Demonstration (Final Project Report)

Electrification of non-tactical vehicle fleets represents a key efficiency and energy security objective for the United States Department of Defense. To achieve electrification, the department targeted vehicle-to-grid services as a way to decrease the overall cost of operating the vehicle fleet and achieve rough parity with traditional internal combustion engine vehicle fleets. This report describes efforts to aggregate a fleet of bi-directional electric vehicles and charging stations to provide regulation up and regulation down in the California Independent System Operator ancillary services market. A 29-vehicle electric vehicle demonstration fleet, consisting of mixed purpose and duty vehicles such as sedans, pickups, vans, and medium-duty trucks, was deployed at the Los Angeles Air Force base. The fleet provided frequency regulation to the California Independent System Operator’s wholesale electricity market to determine the capability of recouping some of the additional costs of procuring electric vehicles and their supporting infrastructure. Lawrence Berkeley National Laboratory, with its partner Kisensum, LLC, developed the fleet scheduling, optimization, and control software to allow the vehicle fleet at the air force base to participate in the ancillary services markets. This report focuses on the control software and market interactions, the significant challenges faced and solutions devised to address them, and examines the potential of using the electric vehicle fleet as an energy storage resource for the base buildings, an application known as vehicle-tobuilding, in providing demand response and emergency backup power. The report discusses key findings related to providing frequency regulation to the California Independent System Operator market, electric vehicle fleet performance, compatibility of varying resource parameters of vehicle fleet aggregation, the need for automated methods for communicating hour-ahead energy bidding, challenges related to battery capacity and charge/discharge rates, and monthly settlement revenue.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Grid Capacity – What is it, what determines it, does one number work, and how does it relate to electric vehicles?

Grid capacity is effectively how much power the system can reliably deliver, whether that is to serve loads (load service capacity) or accept generation (hosting capacity). Grid capacity can also mean different things at different scales. On the whole power system, grid capacity may be the maximum amount of power generation available. For a specific region, grid capacity may be limited by how much power the transmission and distribution lines can safely carry to that region. At the feeder level, it may be how much photovoltaic generation can be included before reliability or operations are impacted. At the end-use or residential level, grid capacity may be the size of the service breaker for that house.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Flexible Charging to Unify the Grid and Transportation Sectors for EVs at Scale (FUSE)

Electric vehicle (EV) adoption will expand beyond light-duty vehicles charging at lower-power public locations and family residences to include medium- and heavy-duty applications with more powerful charging at public stations and private depots. The Vehicle Grid Integration (VGI) and Smart Charge Management (SCM) pillar in EVs@Scale supports multiple projects. The FUSE project is developing and evaluating enabling technologies, charging solutions, and infrastructure design approaches to investigate the intricacies and potential benefits of vehicle grid integration and the application of smart charge management to charging of electric vehicles at scale. This presentation summarizes the findings of this research in 2024.

ADVANCED PROPULSION SYSTEMS↗

Impacts of Integrating Topology Reconfiguration and Vehicle-to-Grid Technologies on Distribution System Operation

Autonomous electric vehicles (AEVs) provide unique opportunities to cope with the uncertainties of distributed energy generation in distribution networks. But the effects are limited by both inherent radial topology and the behaviors of decentralized AEVs. As such, we investigate the potential benefits of dynamic distribution network reconfiguration (DDNR), taking into account AEVs' spatial-temporal availability and their charging demand. We propose a mixed integer programming model to optimally coordinate the charging/discharging of AEVs with DDNR, while satisfying AEVs' original travel plan. Numerical studies based on a test system overlaying the IEEE 33-node test feeder and Sioux Falls transportation network show that DDNR and AEV complement each other, which improves the operation of the distribution system. We also conduct sensitivity analyses on inputs including renewable fluctuation and AEVs penetration level.

33 ADVANCED PROPULSION SYSTEMS↗

Comprehensive Assessment of On-And Off-Board Vehicle-To-Grid Technology Performance and Impacts on Battery and the Grid

This project defined, developed, and tested the open standards-based requirements, engineering design and system integration of on and off-vehicle Vehicle-to-Grid technologies both on the grid and on the PEV, to assess their effectiveness in implementing the use cases that create value for the grid, which in turn, can be passed on to the ratepayers and the PEV owners. The project comprised of three key categories of work and four key sub-areas of work. The three key categories were: On-Vehicle V2G, Off-Vehicle V2G, and impact of V2G operation on the battery capacity degradation. The four key sub-areas of work under each of these categories were: defining requirements, implementing the technology, performing system integration testing, and estimating the value of each of the grid services under specific assumptions, on a per-vehicle and on an aggregated basis. The technical implementation demonstrated the validity of standards-based approach to grid integration that led to interoperability, in addition to assessing the operational details with grid constraints imposed at the transformer level. The technology implementation also identified the subtle gaps in the standards definition to close the feedback loop on the accuracy of the standards as written, which are being implemented as revisions to the appropriate protocols. The battery impacts assessment developed a test cycle that the batteries from a real PHEV were subjected to for both the mobility-only and mobility with V2G specific energy cycling. While the battery impact results show a clear incremental degradation in response to additional throughput for V2G application purposes, the amount of additional kWh that can be made available without exceeding the end-of-life capacity definition of the battery at its 10-year warranty period was found to be significant. Given that the PEV battery being exercised during testing was a PHEV battery (smaller energy capacity), and 44% of its usable energy (i.e., SOC) was utilized daily for V2G applications, the EVs with much larger batteries will fare much better, either in terms of extracting more value in terms of incremental kWh for V2G, or in terms of relative incremental degradation of the capacity through the battery lifespan. Further, this battery was the second-generation Lithium-Ion chemistry circa 2015, which is at least two generations ago. Continual improvements in electrochemistry and manufacturing techniques as well as on-board capacity will enable the future batteries to provide even more energy for non-mobility-related services. Finally, the valuation of V2G energy services at the premise, distribution, and the ISO/market level was carried out for both the on-vehicle and off-vehicle cases, to understand both the GHG mitigation and operational efficiency improvements in quantitative terms. The analysis indicates that between $\$400$ and $\$1400$ per year of total value to the grid can be realized. When netted of costs to implement V2G either on or off-vehicle, the net value is available to be shared between the ratepayers and the EV owners. Over the life of the EV, therefore, this value becomes significant and can easily provide both ratepayer and EV owner benefits more than the cost of the equipment, either on or off-board, in addition to providing GHG mitigation benefits both on the grid and on the mobility sides. For these benefits to accrue, the key learnings from both the on- and off-vehicle V2G parts of the project indicate the need for at-scale demonstrations through involvement of real EV owners to validate both the technical feasibility, interoperability, as well as real grid benefits by performing extensive data collection and analysis. This will help inform the grid planners, the program designs, and tariff designers, as well as automotive and equipment manufacturers how best to create their products to maximize grid, ratepayer, and EV owner value.

30 DIRECT ENERGY CONVERSION↗

Optimal Coordination of Electric Vehicles for Grid Services using Deep Reinforcement Learning

Recent research has shown the effectiveness of reinforcement learning (RL) in coordinating electric vehicles (EVs) with vehicle-to-grid capabilities for grid services. However, many of these studies rely on lookup table and deep Q-network techniques, which can be impractical when dealing with continuous states and actions. In addition, existing RL designs inadequately account for battery aging effects, EV user satisfaction, uncertain departure and arrival time, and trip distance, which may compromise effective coordination. This paper aims to bridge these gaps by developing an innovative deep deterministic policy gradient-based RL framework for optimal coordination of EVs. Case studies were carried out using a test system with 100 EVs, and numerical analysis results showed that the proposed RL framework can effectively coordinate EVs to maximize economic benefits and user satisfaction while ensuring the expected battery lifespan.

Das, Avijit↗