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Results for “Electric Vehicle Grid Integration”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

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↗
DOE OSTI2026

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↗
DOE OSTI2022

Transforming Energy Through Sustainable Mobility: Expanding Low-Carbon Transportation R&D Solutions

As the nation's premier laboratory for cutting-edge transportation decarbonization research and development solutions, the National Renewable Energy Laboratory (NREL) pioneers the creation and deployment of sustainable mobility technologies and strategies, with a focus on slashing transportation sector greenhouse gas emissions and combatting climate change. Trucks, planes, cargo ships, and other difficult-to-decarbonize vehicles are part of this essential transition for the transportation sector, which is currently the nation's largest source of the greenhouse gas emissions. NREL provides the scientific building blocks needed to spur innovation through multifaceted analysis, research, and engineering. This work acts as a catalyst to help industry bring affordable, high-performance, energy-efficient, and low-emission modes of transport and related infrastructure to market sooner. Our researchers collaborate closely with academic, government, and industry partners to design better batteries, drivetrains, and engines. They develop technologies for high-power charging, thermal management, energy storage, and power electronics. They are also reimagining fuels and combustion while creating sustainable lightweight materials. Unbiased expert guidance - backed by credible data and analysis, tools, and scientific rigor - empowers partners to make informed decisions about sustainable transportation. NREL recognizes that communities with limited mobility options face reduced access to employment opportunities, health care, and education, lowering overall quality of life. Alongside partners, NREL experts are creating transportation solutions that meet community-identified needs and increase mobility equity in historically underserved and overburdened communities. Rather than providing a one-size-fits-all solution, we take an interdisciplinary approach to mobility equity that considers the needs and challenges of diverse groups, maximizing benefits at the individual, community, and societal levels.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure; A Nationwide Assessment

Ambitious federal clean goals, along with historic investment in American manufacturing, have put the United States on track to see 30-42 million light-duty electric vehicles (EVs) on the road by 2030. Now, a groundbreaking study from the National Renewable Energy Laboratory (NREL) has estimated the EV charging infrastructure needed nationwide to support a sweeping transition to electrified transportation. The study, titled "The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure," estimates the number, type, and location of the chargers needed to create a comprehensive network of EV charging infrastructure. Its use of proprietary NREL software tools and sophisticated analysis have resulted in a nationwide infrastructure needs assessment with a never-before-seen level of detail - one that takes into account the different ways Americans travel, from running errands to taking road trips, and can adjust to changing circumstances as EV adoption rates change over time.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2016

Integrating PEVs with Renewables and the Grid

This presentation is an overview of NREL's Electric Vehicle Grid Integration (EVGI) efforts toward integrating Plug-in Electric Vehicles (PEVs) with renewable energy and the grid. Efforts include managed charging, local power quality, emergency backup power, and bi-directional power flow. Discussion of future vehicle-related activities under the Grid Modernization Initiative by the Multi-Lab EV Smart Grid Working Group.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Energy Systems Decarbonization: Perspectives on Electric Vehicles and Grid Integration

The imperative for strong and rapid emissions reductions to mitigate global warming and enhance air quality necessitates a transition to net-zero emissions. This shift requires significant changes throughout the entire energy supply-demand ecosystems, tailored to various sectors. Transportation stands as the least-diversified energy sector and the largest source of U.S. GHG emissions. As the primary catalyst for vehicle decarbonization when paired with clean electricity, electric vehicles (EVs) will play a pivotal role in the future. EVs are poised to drive substantial growth in electricity demand and presents a unique opportunity to provide demand-side flexibility that is crucial for future renewable-dominated electricity systems. Smart integration of EVs can strengthen the grid, reducing costs and enhancing resilience. At NREL, laying the scientific groundwork to actualize this vision: our research is finding ways for EVs to support grid planning and operations across several timescales and to fully exploit the synergies between EVs and renewables.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2016

EV-Grid Integration (EVGI) Control and System Implementation - Research Overview

Plug-in electric vehicles (PEVs) are being increasingly adopted in industry today. Microgrid applications of PEVs require the development of charging and discharging algorithms and individual characterization of vehicles including the on-board chargers and vehicle mobility. This study summarizes the capabilities of the Electric Vehicle Grid Integration (EVGI) Team at NREL and underlines different recent projects of the Team. Our studies include V1G, V2G, and V2H control of PEVs as well as test and analysis of stationary and dynamic wireless power transfer (WPT) systems. The presentation also includes the future scope of study which implements real-time simulation of PEVs in a microgrid scenario. The capabilities at Vehicle Testing and Integration Facility (VTIF) and Energy Systems Integration Facility (ESIF) were described within the scope of the EVGI research.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Integrating Electric Vehicles into the Grid

Historically, transportation and power systems operated independently, but the rise of electric vehicles is transforming this relationship. In the United States, EV demands are expected to become the largest source of electricity load growth, posing challenges for the grid if not properly managed. This presentation highlights how managed charging strategies and strategic infrastructure deployment can integrate EVs into the power system to enhance grid efficiency and support renewable energy.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗
DOE OSTI2024

An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies

The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.

Computer Science↗
DOE OSTI2025

Plug-in Electric Vehicle Charging Response Characterization for Grid Integration: Implications for Smart Charge Management

The rapid expansion of plug-in electric vehicles (PEVs) has created a unique challenge for electrical grids due to their significant power demand. At the same time, PEVs also create a unique opportunity to ease their own burden on the power grid, as they create a growing fleet of distributed energy resources capable of providing grid services such as demand response, frequency regulation, and renewable balancing. For aggregators and grid operators to effectively integrate PEVs into grid management, it is essential to first understand and characterize how they would respond in such situations. This study examines 25 models of PEVs across 25 makes, spanning model years from 2013 to 2025, to characterize their responses to the basic controls used in vehicle-grid integration (VGI): stopping, starting, and modulating the charge rate. Each vehicle was tested in a controlled laboratory setting to evaluate its performance in response to varying the maximum allowable current via the SAE J1772 control pilot signal, as well as its response to wake-up commands outlined in SAE J1772. Results show measurable differences across vehicle makes in the accuracy, latency, and precision with which PEVs respond to changes in ampacity, as well as varying sleep and wake-up behavior. The test results show that all vehicles respond to changes in ampacity, though with varying accuracy, precision, latency, and resolution. Wake-up behavior also differs across makes and models. These findings indicate that effective grid integration strategies must account for these differences. The results provide a foundation for understanding current vehicle behavior and advancing smart-charging methods while also highlighting the need for further testing, broader standardization, and manufacturer collaboration to ensure the successful integration of PEVs into the electrical grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Optimized Integration of Electric Vehicles in Low Voltage Distribution Grids

All over the world the reduction of greenhouse gas (GHG) emissions, especially in the transportation sector, becomes more and more important. Electric vehicles will be one of the key factors to mitigate GHG emissions due to their higher efficiency in contrast to internal combustion engine vehicles. On the other hand, uncoordinated charging will put more strain on electrical distribution grids and possible congestions in the grid become more likely. In this paper, we analyze the impact of uncoordinated charging, as well as optimization-based coordination strategies on the voltage stability and phase unbalances of a representative European semi-urban low voltage grid. Therefore, we model the low voltage grid as a three-phase system and take realistic arrival and departure times of the electric vehicle fleet into account. Subsequently, we compare different coordinated charging strategies with regard to their optimization objectives, e.g., cost reduction or GHG emissions reduction. Results show that possible congestion problems can be solved by coordinated charging. Additionally, depending on the objective, the costs can be reduced by more than 50% and the GHG emissions by around 40%.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Framework for Evaluating Grid Readiness for Integrating Electric Vehicles and Utility Scale Storage in India

Electric vehicles (EVs) and distributed solar are poised to grow substantially in India in the coming years following ambitious Government of India targets. The localized impact of these changes, both in terms of infrastructure investments and demand patterns, are not well understood, nor are tools for this type of analysis readily available. This paper describes the development of a framework that can analyze network readiness in terms of feeder impacts for distributed energy resources (DERs) including growing EV penetration, and the potential solutions introduced by utility-scale battery energy storage systems (BESSs). The building blocks of the feeder analysis require multiple data sets to be compiled into a usable network model. The work is driven by feeder head and distribution transformer (DT) loading data along with all the technical specifications and schematics of distribution feeders. These measured data sets are conditioned to remove any afflictions, and the cleaned load profiles are used to perform multi-year quasi-static time-series power flow analyses on detailed three-phase feeder models. EVs translated to grid-tied loads are represented with aggregated EV demand profile estimates based on possible charging scenarios in residential sector, and in workplace and/or public charging stations. Finally, BESSs are evaluated for their cost-effectiveness in the framework through an initial screening that includes the benefits of grid service applications to mitigate present and future overloading scenarios. The outcomes from this framework are expected to help utilities gauge the readiness of their distribution grid for integrating an increasing number of EVs as well as load growth during a projected multi-year time horizon, where BESSs can contribute in making the grid more reliable.

electric vehicles↗
DOE OSTI2017

Electric vehicle station equipment for grid-integrated vehicles

Methods, systems, and apparatus transferring power between the grid and an electric vehicle are disclosed. The apparatus may include at least one vehicle communication port for interfacing with electric vehicle equipment (EVE) and a processor coupled to the at least one vehicle communication port to establish communication with the EVE, receive EVE attributes from the EVE, and transmit electric vehicle station equipment (EVSE) attributes to the EVE. Power may be transferred between the grid and the electric vehicle by maintaining EVSE attributes, establishing communication with the EVE, and transmitting the EVSE maintained attributes to the EVE.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Quantifying the flexibility of hydrogen production systems to support large-scale renewable energy integration

Hydrogen is a flexible energy carrier that can be produced in various ways and support a variety of applications including industrial processes, energy storage and electricity production, and can serve as an alternative transportation fuel. Hydrogen can be integrated in multiple energy sectors and has the potential to increase overall energy system flexibility, improve energy security, and reduce environmental impact. In this paper, the interactions between fuel cell electric vehicles (FCEVs), hydrogen production facilities, and the electric power grid are explored. The flexibility of hydrogen production systems can create synergistic opportunities to better integrate renewable sources into the electricity system. To quantify this potential, we project the hourly system-wide balancing challenges in California out to 2025 as more renewables are deployed and electricity demand continues to grow. Passenger FCEV adoption and refueling behavior are modeled in detail to spatially and temporally resolve the hydrogen demand. We then quantify the system-wide balancing benefits of controlling hydrogen production from water electrolysis to mitigate renewable intermittency, without compromising the mobility needs of FCEV drivers. Finally, a control algorithm that can achieve different objectives, including peak shaving, valley filling, and ramping mitigation is proposed. Here, our results show that oversizing electrolyzers can provide considerable benefits to mitigate renewable intermittency, while also supporting the deployment of hydrogen vehicles to help decarbonize the transportation sector.

08 HYDROGEN↗
DOE OSTI2024

Development of a Hardware-in-The-Loop Testbed for a Decentralized, Data-Driven Electric Vehicle Charging Control Algorithm

This study presents the design of an electric vehicle (EV)-grid integration (EVGI) hardware test-bed to implement smart EV charging algorithms. Here, the proposed test-bed also allows to create different grid events via flexible integration of other power hardware (e.g., controllable loads and battery energy storage systems) and test their impacts on EV charging. The design uses a real-time digital simulator to realize a complex distribution grid model with primary and secondary networks. A grid simulator physically realizes the selected nodes of the simulated grid to power an actual EV, forming a hardware-in-the-loop (HIL) test setup. The EV-grid integration is demonstrated based on the custom hardware and software implementation of the J1772 charging protocol using dSPACE MicroLabBox, operating as a custom EV Supply Equipment (EVSE). The HIL test-bed features a novel testing platform for accurate implementation and analysis of scalable charging algorithms. To this end, a data-driven, decentralized, model-free charging controller based on the Additive Increase and Multiplicative Decrease (AIMD) algorithm is presented and validated on an EV using the HIL test-bed. We tested the proposed algorithm under various case studies, and presented a comparison study with an existing droop-based, decentralized charging solution. The results showed that the EV successfully performed charging commands generated by the EVSE and regulated its charging power to effectively reduce the system loading caused by high EV penetration.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI-XFC)

GEMINI-XFC will use first-of-a-kind integrated high-fidelity grid and transport modeling to identify effective pathways for widespread electrification, to design and evaluate integrated vehicle-grid control schemes, and to optimize electric vehicle integration at a full regional scale with individual customer resolution. Control variables will include: Charging station design and planning (where and what kind of charging stations); EV route scheduling considering grid "status"; and Dispatch of behind-the-meter energy storage and legacy voltage control actuators (on-load tap changes, voltage regulators, capacitors).

DIRECT ENERGY CONVERSION,POWER TRANSMISSION AND DI↗
DOE OSTI2019

Mesoscopic approach to modeling electric vehicle fleets based upon driving activity data to investigate recharge strategies’ impact on grid loads

This paper presents a mesoscopic model to populate a set of sub-fleets of battery electric vehicles (BEVs) that simulates how grid power demand changes with varied mixes of different charging strategies. The proposed model considers real driving activities of vehicles based on the National Household Travel Survey (NHTS) and various charging strategies while parked (at home and in other locations). To be easily scaled to any fleet size, a mesoscopic model is implemented, where BEVs with the same physical properties and driving schedules and clustered together into sub-fleets. The degree of granularity is explored for stable results. Monte Carlo simulations were run to demonstrate the potential of this model's use in grid loads under various charging strategies. Furthermore, an example cost function was optimized to demonstrate finding optimal allocations of charging strategies.

Electric Vehicles, Grid Integration, Monte Carlo S↗
DOE OSTI2025

CyberMESA: Evaluation Procedures and Metrics for Charging Infrastructure Cybersecurity

A report detailing the cybersecurity evaluation and assessment procedures for EV charging infrastructure. This report is authored by three national lab contributors. INL, PNNL, NRL. The grid integration of Electric Vehicle Charging Infrastructure (EVCI) is a large and complex system of systems (SoS) made up of components from many manufacturers and integrated by various companies responsible for their operation and maintenance. This complexity makes it challenging to implement security standards like IEC 62443 across the entire infrastructure. This document aims to aid in the vulnerability assessments of individual devices, such as Electric Vehicle Supply Equipment (EVSE), to support vendors in adopting and implementing security standards such as UL 2900, NIST SP 800-53 and Common Criteria (CC) (ISO/IEC 15408). This document serves as a guide to help evaluate the cybersecurity posture of EVCI assets. It aims to provide a consistent method for evaluating EVCI, enabling cybersecurity research teams to systematically test a wide range of electric vehicle (EV) assets. The target audiences include cybersecurity research teams, vendor development teams, automotive OEMs, and third-party evaluators.

24 POWER TRANSMISSION AND DISTRIBUTION↗