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Packages of Distributed Energy Technologies Demonstrating Demand Flexibility at Community Scale

The combination of increased electric load growth across all sectors, deferred electrical infrastructure investment, and other factors resulting in variable electric power supply, has created technical challenges to maintaining a resilient and reliable grid. Many federal, regional, and local efforts are in play to modernize the electric grid, including advancing building technologies and distributed energy resources (DERs) that are utilizing smarter controls to become responsive to both occupant and grid needs. This report reviews ten pilot projects demonstrating how groups of buildings combined with behind-the-meter (BTM) DERs such as electric vehicle (EV) charging, battery storage, flexible HVAC and domestic hot water systems, and photovoltaic systems can reliably and cost effectively provide grid services. Each of the ten pilot projects aim to deliver both energy efficiency and demand flexibility (DF) while supporting load growth. The ten demonstration teams are piloting flexible DER packages across diverse communities of residential and commercial buildings to address a variety of regional grid needs. The outcomes of these pilot projects will be used to inform future scaling through utility program development. This paper characterizes the ten teams, showcasing the decision-making process used by each group to develop their packages (Section 2), the grid services they plan to deliver (Section 3), the types of DER packages selected for deployment within building sectors (Section 4) and trends between building sector, DER types, and grid services In order to achieve community scale benefits, the pilot projects must utilize aggregated control mechanisms for coordinating buildings and DERs together. Several types of coordinated control architectures have evolved amongst the teams, influenced by use type, existing market conditions, and integration type. Three coordinated controls architectures have been characterized, highlighting their use cases, benefits, challenges, and tradeoffs in their design. These insights can aid utilities, control vendors, and developers in scaling community-level energy systems (Paul, 2024). Ultimately, the technology packages selected by the ten teams will be coordinated to provide power system services, also known as grid services. Insights from these demonstrations will be useful for grid operators, regulators, aggregators and other stakeholders as they look to deploy demand flexible resources as grid services in the future. The grid services that each team is targeting for demonstration are described in Section 3 and Section 4. Methods for evaluating the grid services have been described in the paper Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER (MacDonald, 2023). To identify technology packages for demonstration, Section 2 shows that project teams used a range of analysis approaches, including building energy modeling, AMI data analysis, cost-benefit frameworks, and utility pilot data. Some teams emphasized technical modeling to quantify grid impacts and demand reduction potential, while others prioritized economic evaluations, stakeholder input, or exploratory pilots to inform deployment decisions. This diversity reflects the need to tailor selection methods to project goals, available data, and organizational context. Section 5 discusses trends between the DER technologies deployed and the grid service provisions from each team. Residential buildings (multifamily and single family) lean towards technologies that enhance energy efficiency (e.g. weatherization upgrades, smart thermostats) and onsite power generation integration (e.g. solar PV). Commercial building demonstrations prioritize technologies that ensure operational reliability (e.g. battery storage) and centralized energy management systems and optimization solutions. Teams that are deploying controllable storage-based technologies are more likely to provide grid services that require a near real-time response. Teams incorporating load shifting technologies like smart thermostats with HEMs are likely to include energy markets participation and customer bill management offerings. Campus demonstrations are adopting diverse sets of DERs to emphasize renewable generation, paired with centralized control. This section also describes technologies that were considered during project planning but ultimately excluded from final deployment. These demonstrations reveal that effective DER package design should be tailored to building type, customer segment, and construction vintage. Multifamily buildings benefit from centralized HVAC upgrades and supervisory controls, while single-family homes are well-suited for individualized technologies like solar, storage, and smart home energy monitors. Commercial and campus settings prioritize EMIS integration and load optimization. New construction enables cost-effective integration of DER-ready infrastructure, whereas retrofits require deployments aligned with owner and tenant value streams. For utility program planners, early coordination with developers and building owners, paired with segmented and modular program offerings, can improve adoption, scalability, and grid impact.

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Multi-layered Energy Management Framework for Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, and Forecast Uncertainties

To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is however challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This paper, therefore, proposes a multi-layered multi-time scale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. In the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy and yields optimal scheduling of the energy resources on a rolling horizon basis, thereby considering the long-term forecast errors. A lower dispatch layer (LDL) takes the short-term forecast errors into account during the real-time operation of the XFCS. Per the latest research, monthly demand charges can be as high as 90% of the total monthly bills for EV fast charging stations; to this end, this paper takes the first attempt at the reduction of demand charges cost by considering the trade-off between the energy cost and monthly demand charges. Contrasting literature, this work allocates an energy reserve in the BESS stored energy to deal with the impact of short-term forecast errors on the optimized real-time operation of the XFCS. Moreover, degradation modeling considers the trade-off between short-term benefits and long-term BESS life degradation. As a result, case studies and a comparative analysis prove the efficacy of the proposed framework.

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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↗

V2XConnect: Harmonizing the Landscape of Bidirectional Charging Codes, Standards, and Communication Protocols

The utility grid is constantly evolving with new generation sources and diverse loads from backup generators, backup batteries, rooftop photovoltaics (PV), and flexible charging loads. Each of these technologies presents consumers with an opportunity to work with their local utility to promote grid stability, reliability, and affordability. Through a wide range of programs, utilities are incentivizing the use of these resources to benefit the grid. However, especially for devices with inverters that supply power back to the grid, it is important that these assets comply with local grid codes to ensure human safety, power quality, and grid reliability. One of the most promising of these new technologies is the bidirectional electric vehicle (EV) coupled with bidirectional electric vehicle supply equipment (EVSE). This report introduces the technologies that enable bidirectional charging and how these systems operate. It then outlines the necessary interconnection codes and industry standards that govern the operations of grid-tied inverters, including those in bidirectional charging. A key challenge is then outlined from the complex landscape of communication protocols and proprietary systems designed to coordinate these grid assets. Finally, a single gateway solution is proposed to harmonize communications between all assets across an entire site for a cohesive response to grid codes and utility programs that is flexible enough to support a range of market options.

33 ADVANCED PROPULSION SYSTEMS↗

EMOS (Energy Management Optimization System) [SWR-21-46]

EMOS software performs a real-time hierarchal optimal control for energy systems like multi-port electric vehicles charging site with distributed energy resources (DERs) and energy storage systems (ESSs). It gathers information in real-time from electric vehicles, power grid, and DERs, solves a multi-objective energy management optimization problem, and output setpoint for chargers, ESS converters, DERs converters, and grid converters. The software incorporates a novel integration of two control tasks: a) An Energy Management Optimization (EMO), which is the brain of EMOS controller that gathers information in real-time from EVs [e.g., battery size, state-of-charge (SOC), desired SOC, and charge acceptance curve], grid (e.g., electricity price, allowed feeder capacity, ramp rate limit, and reactive power), and DERs (e.g., prediction for solar generation for PV systems). It solves a control optimization problem in real-time to find optimal setpoint for ESSs power dispatch, EVs charging rate, and grid inverters. The objectives are to (1) minimize the charging cost considering grid energy, demand charges, and battery energy, (2) minimize charging time to meet fast charging criterion, (3) keep high energy level on ESSs at the end of an operating period, while satisfying constraints related to grid, EVs, and power converters. b) Real-Time Energy Management System (RT-EMS) is a rule-based algorithm that has faster response than EMO. It receives optimal setpoint from EMO and actual measurements from the system and modify the setpoint to compensate for any fast disturbance in the system, until a new optimum solution is received. Fast disturbances may include vehicle connect/disconnect, unpredicted variation in DERs profiles, variation in grid voltage, errors in PV generation prediction, and others. In addition, RT-EMS regulates voltage at point of common coupling (PCC) by managing reactive power of grid converters.

Mohamed, Ahmed↗

Electric Vehicle Charging Management in Smart Energy Communities to Increase Renewable Energy Hosting Capacity

Abnormal climates due to global warming have emerged as a big concern in the global community. To mitigate climate change and achieve sustainability, distributed energy resources (DERs), including solar and wind, have been recently deployed in power systems. As the penetration level of DERs has increased, however, it caused a multitude of issues in the power systems, such as voltage fluctuation in the distribution network limiting renewable hosting capacity. On the other hand, the electric vehicle (EV) industry is rapidly growing to facilitate the transition to a carbon-neutral community, illuminating the potential of EVs as a flexible grid asset to mitigate some of the issues and improve grid operation, if properly exploited. To explore the potential of EVs, this paper proposes an EV scheduling strategy. By using an optimal EV charging scheduling proposed, distribution system operators (DSOs) can minimize their operating costs and stably operate the system with a high level of DERs. To validate the method, a modified IEEE 33-bus system with DERs is developed. The case study shows the proposed scheduling strategizes EV charging to reduce the cost of PV curtailment. In the study, the method outperforms the renewable-only case with curtailment by 4.97% in DSO cost. It also demonstrates its potential to increase the renewable hosting capacity by harmonizing EV charging with renewables.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

Fast, Controllable, and Modular Solid-State Circuit Breaker Design for Battery Management Systems

Electric power grid is experiencing a growing number of distributed and inertia-free generation resources. To facilitate the growing generation and load demands, and ensure stable operation, energy storage systems, especially behind-themeter-storage (BTMS), have emerged as a potential candidate. BTMS plays a vital role in the grid storage sector and supports high power charging for EVs. However, the potential of thermal runaway and associated safety concerns in the batteries can hamper their widespread adoption. In this work, we provide a solution for a fast and controllable discharge of a cell that was identified as a stressful/faulty, in the battery pack, and fast circuit breaking leveraging the Solid-State Circuit Breaker (SSCB) technology which provides active control over the cell connection as opposed to conventional passive solutions. Testing on the simulation platform successfully validated the concept, demonstrating its efficacy. Controlled discharge testing with 20Ah LiFePO4 Lithium Iron Phosphate (LFP) cells from 1C-10C current rate on the hardware prototype corroborated simulation results, demonstrating design feasibility and providing essential data for its performance and thermal characteristics, while also revealing limitations that inform areas for further optimization.

33 ADVANCED PROPULSION SYSTEMS↗

There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure

In March 2021, the cumulative sale of plug-in electric vehicles (PEVs), including plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV), reached 1.8 million in the United States (Argonne National Laboratory 2021). However, PEV adoption is still in its infancy; its market share has just reached around 3% of new light-duty vehicle (LDV) sales by the end of 2020 (Alliance for Automotive Innovation 2021). Current trends suggest that PEV market share in the United States is increasing. The U.S. Energy Information Administration's (EIA's) 2020 Annual Energy Outlook forecasts PEV registrations to exceed 8 million vehicles by 2030 (AEO 2020). PEV adoption is expected to be led by states that are regulating the sale of zero emission vehicles (ZEVs) (California Air Resources Board). California continues to push for more aggressive ZEV regulations; the state recently issued an executive order aimed at 100% of LDV sales being ZEVs by 2035 (Office of Governor Newsom). At the federal level, the Biden administration has shown great ambition in encouraging broader electric vehicle (EV) adoption, including setting the goal of installing 500,000 new chargers nationwide (The White House 2021). Access to charging infrastructure is consistently cited as one of the primary barriers to the increased sale of PHEVs and BEVs (Carley et al. 2019). In the United States, PEV charging options are often described using a pyramid structure, with residential charging as the foundation, workplace charging in the middle, and public charging on top (Figure 1). The existing electricity system, which generates, transmits, and distributes electric fuel to residential households, has helped PEVs partially overcome the "chicken and egg" conundrum that has haunted other alternative fuels. Viable home access to electric charging is also an important equity issue, because non-residential PEV charging options (e.g., workplace or public charging stations) are generally more expensive. Households without residential charging access may experience higher total cost of PEV ownership if non-residential charging options are more costly.

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Lessons Learned from the Clean Energy to Communities (C2C) Peer-Learning Cohort on Planning and Funding for Electric Vehicle Charging Infrastructure Deployment

From June to December 2023, the U.S. Department of Energy (DOE) National Renewable Energy Laboratory (NREL) partnered with World Resources Institute (WRI) to run a peer-learning cohort for local governments on Planning and Funding for Electric Vehicle Charging Infrastructure Deployment. This cohort effort, funded by DOE's Clean Energy to Communities Program, paired 15 local and regional governments with Clean Cities and Communities coalitions to translate cohort learnings to local context and conduct activities that brought participants closer developing of public electric vehicle charging infrastructure plans. This document shares key takeaways, lessons learned, and resources from the six-month cohort.

ADVANCED PROPULSION SYSTEMS↗

EVs@Scale Lab Consortium High-Power Charging Pillar Deep-Dive Technical Meeting

Managed under the the U.S. Department of Energy (DOE)-funded EVs@Scale Consortium, the High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project aims to create an experimental platform for integration and control approaches in a direct current (DC), distribution-based high-power charging (HPC) system. The eCHIP project addresses the crucial need to design and validate efficient, low-cost, reliable, and interoperable solutions for a DC-coupled charging hub ("DC hub" for short). This report explains the design, development, and implementation process of an experimental platform for the DC hub. DC distribution holds significant potential for enhancing the operation of an HPC station architecture. However, there are challenges in establishing a DC hub, including interoperability, commoditization, distributed energy resource integration, stability, DC protection, and a lack of common system-level controllers. To address these challenges, a testing setup is required that accommodates commercial off-the-shelf (COTS) products, as well as novel, in-house designed solutions, to evaluate different use cases at rated power and voltage levels. The developed proof-of-concept charging platform and open-source SEMS allow the development and testing of various controllers and chargers from different vendors. The DC hub platform integrated EVs, an ESS, a PV system, and building load to demonstrate the flexibility of the platform. The open-source SEMS controlled the devices within the hub using a rule-based implementation, realizing available standards.

ADVANCED PROPULSION SYSTEMS↗

EVs@Scale Next-Gen Profiles - Fleet Utilization 2024

As part of the U.S. Department of Energy’s EVs@Scale initiative, the Next-Gen Profiles (NGP) project provides a comprehensive, data-driven analysis of electric vehicle (EV) and electric vehicle supply equipment (EVSE) operations across real-world fleet deployments. This paper presents findings from the NGP’s Fleet Utilization study, which investigates operational behavior and asset usage across seventeen EV fleets and two EVSE fleets, encompassing a wide range of vehicle types and use cases. Data collected from diverse sources—varying in format and temporal resolution—are first reformatted into a unified structure. From this harmonized dataset, a suite of rigorously defined performance metrics is calculated at an hourly cadence, enabling consistent cross-comparison of charging, routing, and other key operational behaviors. Amid rapidly increasing EV adoption and growing demands for energy-efficient fleet operations, the analysis reveals clear utilization trends—including diurnal and weekly activity cycles, differences in short versus long charging session dependencies, and route-specific energy usage patterns. These findings highlight the need for tailored infrastructure strategies and the deployment of advanced energy management systems, such as Distributed Energy Resource Management Systems (DERMS) and Site Energy Management Systems (SEMS), which can optimize charging schedules and mitigate peak loads. By leveraging anonymized, harmonized datasets and standardized metrics, this study offers critical insights into fleet behavior and performance, providing a foundation to improve operational efficiency, reduce costs, and enable the scalable deployment of electrified transportation.

Wells, Landon↗

Cybersecurity for Fast Charging EV Infrastructure

The integration of electric vehicles (EVs) into electric grid operations can potentially leave the grid vulnerable to cyberattacks from both legacy and new equipment and protocols, including extreme fast-charging infrastructure. This paper introduces a co-simulation platform to perform cyber vulnerability analysis of EV charging infrastructure and its dependencies on communications and control systems. Grid impact scenarios through linkages to power system simulation tools such as OpenDSS and vehicle infrastructure-specific attack paths are discussed. An adaptive platform that assists with predicting and solving evolving cybersecurity challenges is demonstrated with a cyber-energy emulation that accelerates the analysis of cyberattacks and system behavior.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

EVSE DERMS Controls [SWR-26-010]

An MQTT (Message Queuing Telemetry Transport) and OCPP (Open Charge Point Protocol) based remote smart charging controller framework for AC Electric Vehicle Supply Equipments (EVSEs). The code in this repo allows for the National Laboratory of the Rockies (NLR) controls to interface with the real Distributed Energy Resource Management System (DERMS) and EVSEs in NLR's ESIF Optimization and Control Laboratory (OCL). Different charge management algorithms can be tested to determine which power allocation method is most effective with the overall goal of demonstrating clear and well documented test results as well as providing functional control algorithms which could be utilized to provide effective smart charge management (SCM) at EV charging stations. Different power allocation methods are programmed in lab_demo_controller.py and include allocation based on first come first served, equal sharing, state of charge (SOC), priority factors, and behind the meter control methods.

Panossian, Nadia [National Laboratory of the Rocki↗

Electrifying High-Efficiency Future Communities: Impact on Energy, Emissions, and Grid

To combat climate change and meet decarbonization goals, the building sector is improving energy efficiency and electrifying end uses to reduce carbon emissions from fossil fuels. All-electric buildings are becoming a trend among new constructions, introducing opportunities for decarbonization but also technical challenges and research gaps. For instance, further investigation is needed to understand how the adoption of energy efficiency measures (EEMs) and distributed energy resources (DERs) in all-electric communities would affect energy consumption, carbon emissions, and grid planning. This paper presents a case study of a mixed-use, all-electric community located in Denver, Colorado. We use URBANopt TM , a physics-based urban energy modeling platform to model the community and then evaluate the impact of EEMs and DERs (i.e., photovoltaics [PV], electric vehicles [EVs], and batteries) on the community's energy usage, carbon emissions, and peak demand. The results show that adding EEMs and PV led to both energy consumption and carbon emissions reductions across all building types. However, we saw fairly limited impact of EEMs and PV on buildings' peak demand in our case. Additionally, due to overnight EV charging activities and higher grid carbon intensity at night, the carbon emissions in multifamily buildings have a noticeable increase compared to scenarios without vehicles. Finally, the addition of batteries helped reduce peak demand by 11%-29%. The modeling workflow and evaluation methods can be applied to similar communities to evaluate their performance and the effect of integrating EEMs and DERs.

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Development and Evaluation of Distributed Energy Resource Device Models: Electric Vehicles, Electric Water Heaters, and Commercial Refrigeration Systems

In order to validate distributed energy resource (DER) models operated with grid services in the GMLC 1.4.2 team’s February (GMLC 2019a) and July (GMLC 2019b) reports, a test and measurement program using actual DER devices was conducted by national laboratories for three devices: (1) electric vehicles (EVs), (2) water heaters, and (3) commercial refrigeration. Test procedures were developed and carried out to identify the mathematical models and their parameters that describe the operational function, characterize the physics, and obey transient response of the devices. This report focuses on the experimental results obtained to develop and verify simulations of three specific EV models. This section summarizes elements of the mathematical model and shows the necessity data collected from the EVs while charging and discharging (driving). In the course of the study, we found it necessary to make some modifications to the model to deal with observed transient behavior. Section 1.2 details the model assumptions and equations, Section 1.3 provides details of the EVs tested, Section 1.4 outlines the test procedures developed for the projects, and Section 1.5 presents the experimental results obtained for the three different EVs tested and how these results compare to the models running the same test profiles.

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Power System Operational Impacts of Electric Vehicle Dynamic Wireless Charging

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts.

dynamic wireless power transfer↗

An integrated transportation-power system model for a decarbonizing world

Rising demand for electricity from electric vehicles (EVs) will require new paradigms to guarantee reliable and low-cost electricity. This study couples an agent-based travel demand simulator and an electricity grid model to assess the economic costs of supplying power to meet EVs' added demand across the Chicago region. Results suggest that shifting from personal EVs to a fleet of shared, fully-automated all-electric vehicles (SAEVs) could lower per-mile emissions, congestion, and embodied vehicle and charging infrastructure emissions. Further, the results should compel policymakers to shift the cost of providing power onto commercial customers, like electric ride-hail fleets, through price-indexed electricity prices, which can shift charging to off-peak periods or away from resource-scarce hours.

Integrated modeling↗