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Aspects of the present disclosure include anonymous, asynchronous, and randomized control schemes for distributed energy resources (DERs). Such control schemes may include packetized energy management (PEM) control schemes for managing DERs that may provide near-optimal tracking performance under imperfect information and consumer quality of service (QoS) constraints.
Buildings account for more than 70% of U.S. electricity use and at least one-third of U.S. economy-wide CO2 emissions. Changing the timing and overall amount of electricity consumption in buildings would significantly reduce energy costs to consumers and facilitate the transition to a decarbonized economy. Grid-interactive efficient buildings (GEBs) incorporate energy efficiency, smart technologies, and active use of distributed energy resources (DERs) to provide these benefits. As the link between the customer and the power system, utilities are central to widespread deployment of GEBs. Yet, despite the significant cost savings and operational benefits of GEBs for utilities, deployment has remained limited. This paper explores emerging models for enabling utilities to facilitate GEB adoption. Building off foundational research conducted to develop the U.S. DOE’s A National Roadmap for Grid-Interactive Efficient Buildings, we describe the most novel recent examples of ways in which utilities and regulators have made demand-side innovation a win for both the customer and the utility. Emerging concepts include: (1) performance incentive mechanisms to align GEB deployment with utility financial motivations, (2) the use of subscription pricing (i.e., fixed monthly bills) to promote load flexibility and energy efficiency, (3) rate-basing utility-controlled behind-the-meter assets, and (4) coupling energy efficiency and load flexibility with electrification proposals to ensure that customer benefits are maximized. The paper concludes with a discussion about prospects for widespread GEB deployment and utilization by utilities, and how to scale efforts.
This paper identifies likely drivers of building efficiency over the next ten years and expectations for how efficiency markets may evolve over this period. To prepare these predictions, we conducted an extensive literature review, interviewed 22 experts, reviewed legislation and executive orders in 12 states, and implemented a detailed questionnaire completed by 41 efficiency practitioners. The two most important drivers revealed by our research are (1) public policies and regulations, particularly those associated with climate change mitigation and adaptation and (2) the cost of energy relative to the cost of delivering efficiency. Other important drivers are technology changes, economic conditions, social priorities, and industry (including utility) business practices for increasing the uptake of efficiency in buildings. Our research indicates that efficiency markets will increasingly focus on supporting building decarbonization and enabling demand flexibility through the use of controls in grid-interactive efficient buildings and communities. Efficiency improvements for specific technologies (e.g., heat pumps, controls, and windows) and technological advances not specific to energy technologies (e.g., interoperability, artificial intelligence, and universal internet access) will improve the efficacy of efficiency measures and actions. Marketing of efficient products and services will increasingly focus on grid services, decarbonization, non-energy benefits for consumers, and integration with other distributed energy resources (DERs). We anticipate increased investment in disadvantaged and historically underserved communities, recognizing the social, health, and safety benefits of efficient energy usage and remediating historical biases. Lastly, we predict that while state and local government actions will vary, jurisdictions will increase their efficiency goals overall.
Energy efficient, connected, grid-interactive, smart and flexible buildings are key to decarbonization, lowering energy use and improving the nation’s electricity grid. The U.S. Department of Energy’s Connected Communities initiative works to demonstrate how coordinated groups of highly efficient buildings combined with other distributed energy resources (DERs), such as electric vehicle (EV) charging, batteries, storage, demand response and photovoltaic (PV) generation can reliably and cost-effectively serve as grid assets by strategically deploying efficiency and demand flexibility while reducing carbon emissions. In 2021, DOE competitively awarded $61 million to a diverse portfolio of 10 pilot projects to promote grid-interactive efficient buildings (GEBs) working together to reliably and cost-effectively serve as grid assets while decarbonizing. Two of the main tenets of the program are measuring the communities’ energy and carbon performance and understanding how to replicate project successes in other communities. This paper begins with a discussion of what Connected Communities are (including a brief history) and their many benefits, including reduced carbon emissions and increased building efficiency and demand flexibility. Next, it provides an overview of the 10 projects, highlighting the diversity of approaches to measure success and replicate the projects: geographic locations; building types; utility, regulatory, market environments; and building vintages that will be used to test the ability of buildings to serve as grid resources. It concludes with a discussion of anticipated project impacts and the metrics that will be used to evaluate the Connected Communities projects.
With the progressing electrification of the transportation sector, the source of carbon emissions is gradually shifting from fossil fuel to grid electricity because of electric vehicles (EVs). The carbon intensity of the grid can fluctuate significantly within hours due to the time-varying power generation mix. Therefore, shifting EV charging loads to cleaner hours in response to the carbon intensity signals can reduce carbon emissions. Existing EV charging control methods typically consider the electricity price or the available generation by distributed energy resources (e.g., photovoltaics) to inform decision-making. Such methods tend to reduce energy costs but may neglect the environmental impact of EV charging activities. We propose and compare four carbon emission responsive EV charging controllers with various control rules. The proposed controllers are evaluated based on simulation experiments using metrics such as carbon emission reduction potential, state of charge (SOC) at departure, and peak demand. We found that the need of EV owners to have full batteries at departure could lead to an emission increase when the curtailed EV charge was compensated before departure. Further, up to 12.7% of carbon emission reduction can be achieved if the EV owners reduce the target SOC at departure by less than 15%.
Developing an Energy Service Interface (ESI) specification requires engaging a community of stakeholders including grid operators, Information and Communication Technology implementors, integrators, and finally standards bodies who will define an interface that respects and boundaries of ownership and roles of responsibility in order to activate millions of Distributed Energy Resource for the provision of grid services. By applying Interoperability Maturity Model Criteria and ESI principles to common grid-DER service use cases, the Grid Modernization Lab Consortium team will engage subject matter experts to develop a specification, with an eventual goal of informing development of ESI compliant profiles or standards. The ESI Specification is intended to specify the characteristics, attributes, or qualities that need to be addressed in ESI compliant standards or profiles. This includes addressing interoperability criteria and the service-performance style of the interface.
Irrigation systems in the United States are some of the oldest continually utilized infrastructure in existence today, with some systems exceeding 100 years in age. They are operated to meet farming demands but are managed through a balance of varying influence: policies limiting water usage, stakeholder interests, and environmental impacts. Irrigation modernization is defined as a set of activities that update and improve existing irrigation systems, including, but not limited to improving water quantity, development of distributed energy resources for surrounding communities, ecosystem services, and improved agricultural yields. Modernizing an existing irrigation system can enable stakeholders to combat changing environmental and population demands but is difficult because the complexity involved in determining the potential benefits and consequences of irrigation modernization is high. We are combining a large amount of various geospatial, tabular, and temporal data with subject matter expertise into a decision support engine that will enable stakeholders to determine the benefits and consequences of irrigation modernization in their irrigation systems. A web-based GIS will allow the user to construct the modifications out of a palette of modernization options, which will be sent to the analytics engine for computations, and back to the web client for a graphical display and comparison of relevant metrics. Our development process involves four phases: 1) identify mechanisms of modernization, 2) identify data requirements, data streams, first principles and applicable algorithms necessary to quantify modernization mechanisms, 3) create ‘modules’ for each modernization mechanism, these modules will form the decision support engine, each capable of performing independently but can also inform other modules when needed, 4) Merge the decision support engine with a user interface, capable of ingesting user inputs and returning insights into the impacts of a modernization project as they relate to economic, environmental, monetary, and energy generation. Once complete, it is our intention that this tool will be fundamental in irrigation modernization projects, providing a strong analytical basis from which stakeholders can quickly make informed decisions regarding project development.
Since 2019, the National Renewable Energy Laboratory (NREL) has collaborated with IEDO's Combined Heat and Power (CHP) Deployment Program and the CHP Technical Assistance Partnerships (TAPs) to expand the capabilities of NREL's publicly available REopt® tool for techno-economic analysis of on-site energy. As a result, capabilities to analyze heating and cooling loads and serve those loads with CHP were added to the REopt tool in 2021. Currently, NREL is using REopt to evaluate the economics and feasibility of deploying distributed energy resources at sites of 3-5 manufacturers. The analysis is based on location, site-specific load data, customized utility bill analysis, and other criteria such as resilience needs and decarbonization targets. The objectives of the current effort are to (1) assist manufacturers with analyzing on-site energy options, including CHP, solar photovoltaics (PV), wind, and battery storage, (2) validate the capabilities and use of REopt to provide technical assistance to manufacturers, and (3) publish case studies showcasing the engagement, key takeaways, and lessons learned. Future work is expected to include additional REopt capabilities for evaluating other technologies to reduce scope 1 emissions, such as electrifying process heating loads, using carbon-free fuels, and other clean heat strategies.
The U.S. has set the climate goal to achieve net-zero greenhouse gas emissions by 2050. District-scale solutions, which include scale-specific opportunities for energy and emissions savings, can be investigated and implemented to help accelerate decarbonization and progress toward this goal. However, there is currently a lack of district-scale models of buildings and community energy systems that can be used to evaluate potential district-scale technologies and strategies across a range of representative community types. This initial work aims to define and develop prototype district models that can be adapted to support the planning, design, and operation of buildings and energy systems in districts considering the complexity and interactions of diverse building loads, weather impacts, distributed energy resources (e.g., PV, EV, electric and thermal energy storage), electric and thermal grid systems, and pricing signals. An overall workflow for developing these prototype district models is established. Stakeholders and potential users of the prototype district models provided technical feedback. The specifications of the selected high priority districts were defined and documented in a scorecard format. An example prototype district model was implemented with the URBANoptTM platform workflows. A case study was performed to demonstrate the model application.
A hybrid power generation system is formed by the combination of an energy storage system (ESS) and a rotating synchronous power generator (SPG). Energy is stored in or released from the ESS in response to measurements of the at least one angle parameter, selected from rotor, torque, or power angle of the SPG, to provide active frequency damping of electrical power output. The control of ESS energy exchange increases the stabilizing impact of the SPG inertia on the frequency of electricity in an electrical network or power grid. The hybrid power generation system can have an effective equal area criterion for stability limit that is greater than that of the SPG operating without the ESS. The hybrid power generation system can enable the electrical network to have a greater proportion of variable or distributed energy resource (DER) power generation systems without otherwise exceeding stability limits.
With the support of DOE's Vehicle Technologies Office and the DOE/DOT Joint Office (JO), NREL has applied the EVI-X modeling suite to conduct a National Electric Vehicle Infrastructure Needs Assessment. This report considers a 2030 scenario in which 30-42 million light-duty electric vehicles are on the road (including plug-in hybrids). We consider the needs of vehicles used for typical daily driving, drivers without access to residential charging, corridor charging supporting long-distance travel, and ride-hailing electrification. We find that a national network of 28 million charging ports (including public and private infrastructure) will be necessary in our mid adoption scenario. This result is framed as a conservative estimate as the assumed costs include charging equipment and installation but exclude the cost of grid upgrades and distributed energy resources.
The Power Electronics for Electrolyzer Applications to Enable Grid Services project aims to develop smart converter for dedicated electrolyzer applications to enable grid services via standardization of control interfaces between hydrogen electrolyzer system low-level controls and power converter controls. The project provides additional revenue source for electrolyzer through participation in grid services and reduces the cost of deployment and controls integration through standardization and risk due to supply-chain issues. It also enables the adoption of green hydrogen via standardizing the integration of energy storage, renewables, and distributed energy resources. Furthermore, the work provides a controlled validation environment to evaluate scalable integration solution for hydrogen production technologies, improves overall reliability and maintainability of the electrolyzer system for grid applications, and directly contributes to DOE HFTO's "Hydrogen Shot" goal.
Unintentional islanding (UI) of a circuit of distributed energy resources (DERs) may leave area electrical power systems (EPS), external to the DER circuit, energized. Thus, UI detection methods have been developed to detect unintentional islanding and trigger a UI response. However, individual UI detection methods have various deficiencies. Thus, a consensus-based UI detection process is disclosed that builds a consensus from multiple UI detection sources, optionally implementing different UI detection methods. The redundancy in this consensus-based UI detection process provides robust, sensitive, selective, and cybersecure UI detection for the entire DER circuit. For example, the consensus-based UI detection process may eliminate or reduce non-detection zones, avoid false positives, thwart cyber-attacks, and/or the like.
Advanced Distribution Management Systems not generally optimize over the entire feeder because there are few high-fidelity distribution circuit models and real-time distribution-connected sensors are rare. The limited observability at the distribution level makes it difficult to globally optimize distribution operations and issue control setpoints to power systems equipment or Distributed Energy Resources (DER) to perform grid-support services. For example, setpoints can be issued to DER based on results from an optimization module that incorporates a static or time-series feeder simulation. Feeder simulation initial conditions are populated with photovoltaic (PV) and load forecasts, state estimation results, and/or digital twin measurements or state output. The real-time (RT) digital twin runs a model of the feeder to generate state estimation pseudo-measurements since there are limited live feeder measurements.
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.
Typically, distribution system planning processes do not explicitly incorporate energy equity considerations, such as identifying consumers most affected by energy costs and determining how investments in the distribution system can address existing energy burden imbalances. This paper proposes a novel optimal transport (OT)-based method to improve the energy burden distribution of consumers. The approach involves the strategic siting and sizing of solar PV in order to assist customers with high energy burden and improve the overall energy burden distribution of the community. The desired energy burden distribution is defined using the equal distribution equivalent (EDE) concept. The OT-based method is then used to estimate the distributed solar PV capacity to be installed at various locations and the tariffs to be adjusted, all while improving the energy burden distribution and providing valuable insights into distributed generation (DG) planning. The results on IEEE 37 bus test system demonstrate how DG planning, considering EDE and OT, can help reduce the energy burden of low-income consumers. Additionally, the approach also reveals optimal tariff adjustments needed to ensure revenue neutrality for distribution utilities.
The Cyber-Informed Engineering (CIE) Guide for States provides state energy offices, public utility commissions, and partner organizations with a structured framework for integrating cyber-resilient engineering practices into energy planning, grantmaking, interconnection processes, and workforce development. As grid digitalization and the adoption of distributed energy resources accelerate, states face expanding cyber-physical risks that traditional cybersecurity measures alone cannot fully address. CIE offers a proactive, consequence-focused engineering methodology that emphasizes eliminating or mitigating high-impact failure modes through design, physical controls, and operational safeguards. The guide outlines the 12 core CIE principles, demonstrates their application through state-focused use cases—including grant evaluation rubrics, interconnection reviews, allow-list development, and training programs—and provides practical tools such as scoring frameworks, impact assessment methods, and implementation checklists. It also highlights pathways for state–utility collaboration and opportunities for technical assistance from national laboratories. By adopting CIE, states can enhance grid reliability, reduce lifecycle costs, strengthen supply-chain assurance, and foster a security-aware engineering culture that aligns with broader resilience and modernization goals. November 2025
The Cyber-Informed Engineering (CIE) Guide for States provides state energy offices, public utility commissions, and partner organizations with a structured framework for integrating cyber-resilient engineering practices into energy planning, grantmaking, interconnection processes, and workforce development. As grid digitalization and the adoption of distributed energy resources accelerate, states face expanding cyber-physical risks that traditional cybersecurity measures alone cannot fully address. CIE offers a proactive, consequence-focused engineering methodology that emphasizes eliminating or mitigating high-impact failure modes through design, physical controls, and operational safeguards. The guide outlines the 12 core CIE principles, demonstrates their application through state-focused use cases—including grant evaluation rubrics, interconnection reviews, allow-list development, and training programs—and provides practical tools such as scoring frameworks, impact assessment methods, and implementation checklists. It also highlights pathways for state–utility collaboration and opportunities for technical assistance from national laboratories. By adopting CIE, states can enhance grid reliability, reduce lifecycle costs, strengthen supply-chain assurance, and foster a security-aware engineering culture that aligns with broader resilience and modernization goals. November 2025