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DOE OSTI2024

Experiences and Lessons from Field Demonstration of Grid-forming Inverter in An AC Microgrid

The validation of GFM control strategies through simulation and hardware demonstration is important before their large-scale deployments in the real grid. Considering the importance of testing and validation, several works have explored the GFM inverter’s capability to blackstart a microgrid, synchronize and share loads, and interact with various types of generation sources and loads present in the grid. Herein, this paper complements the existing works by presenting the results and analysis of a field demonstration in an actual AC microgrid. The capability of a three-level neutral point clamped (NPC) GFM inverter equipped with a recursive feedback type of non-linear device level control to operate with PV source on its DC input and off-the-shelf PVGFL inverters and EV chargers of different kinds on the AC side is explored. The analysis and conclusions drawn would inform the readers to make better decisions during the field demonstration process.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Experimental study of a thermal energy storage-integrated heat pump system for load shifting in space cooling and heating

This study experimentally investigates an all-season thermal energy storage-integrated heat pump (TES-HP) system developed to enhance building energy efficiency and support grid-interactive operation through load shifting in both cooling and heating. A 4-ton commercial rooftop air-source heat pump was modified by integrating a hydronic thermal energy storage (TES) unit containing a phase change material (PCM) with a melting temperature of 22.0 °C. The system employs two reversing valves and three electronic expansion valves to enable six operating modes, including normal, TES charging, and TES discharging in both cooling and heating seasons. A subcooling-controlled electronic expansion valve was implemented to mitigate refrigerant maldistribution caused by unequal internal volumes among the heat exchangers. Compared with a baseline heat pump, the TES-HP reduced power consumption by 30–50% during cooling at an ambient temperature of 40.6 °C, and by up to 60% during heating at −15.0 °C, while maintaining high performance under cold-climate conditions. Additionaly to experimental evaluation, a simplified annualized on-peak analysis was conducted to compare the TES-HP with the baseline system, indicating an on-peak electricity reduction of approximately 876 kWhₑ per unit per year and associated on-peak cost savings under time-of-use pricing. These results demonstrate that the TES-HP effectively decouples HP operation from adverse ambient conditions, improving flexibility, resilience, and energy efficiency. This work advances prior research by experimentally proving the integration of PCM-based TES for a year-round, load-flexible HVAC operation.

42 ENGINEERING↗

DOE OSTI2024

Grid-connected heat pump water heater benefits for low-income households in the Southeastern United States

Energy efficient heat pump water heaters (HPWHs) reduce customer energy costs; grid-connected controls further increase HPWH value by enabling energy storage and shifting demand to cheaper, off-peak periods. However, a HPWH’s first cost premium can put it out of reach for low-income customers. This paper will present results of an ongoing study exploring the benefits of load shifting HPWHs for 24 low-income households, aiming to support increased product deployment in this demographic. The study uses EcoPort modules to shift HPWH load for a study sample consisting primarily of low-income adults and seniors in North Carolina. Building upon prior studies, the study’s HPWH operating schedules are designed to maximize shifted energy and minimize participant electricity costs based on local time-of-use rates. The study documents load profiles of grid-connected HPWHs in a less-studied demographic group and explores how certain groups may have particularly flexible loads due to their unique usage profiles. The results are relevant for HPWH product performance in the Southeast. The study will quantify HPWH load shifting performance during North Carolina’s hot summer, temperate shoulder, and occasionally sub-freezing winter seasons, and the study includes installations in conditioned, semi-conditioned, and unconditioned spaces. Finally, study results will also explore how controlled HPWHs can provide value to the regional grid by reducing seasonal peaks via demand response. Lessons learned include HPWH acceptance for low-income and senior users, best practices for maintaining HPWH connectivity among users without prior product experience, and strategies to leverage remote monitoring to ensure optimal operation and enhance HPWH reliability.

Urigwe, Daniela↗

DOE OSTI2026

A Physical Model Enhanced Data Driven Method for High-Resolution Residential Load Profile Generation

Residential buildings account for significant energy consumption, creating opportunities to offer grid services. As electric utilities seek to implement effective system operation strategies, understanding residential energy consumption patterns becomes essential; However, the time intervals of load profiles measured by utilities' smart meters are typically from 15 minutes to 60 minutes. The low-resolution data make it hard to extract appliance-level load information, which is critical for providing grid services. This paper presents a load profile generator designed to produce synthetic load profiles for residential buildings that emphasizes the importance of accurate representations of realistic energy consumption patterns. The generator takes realistic low-resolution residential load measurements and weather data as inputs, producing 1-minute interval profiles that match the characteristics of the original profiles. Further, this generator can be used to populate load profiles in areas where actual measurements are limited to improve the ability of utilities to analyze their distribution systems. By providing more high-resolution residential building load profiles, this tool supports electric utilities to enhance their residential building load control strategies and improve overall grid stability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Hybrid Power Plants for Energy Resilience: A Case Study

As renewable energy technologies are increasingly adopted, they pose an opportunity to improve the sustainability and resilience of distributed grids, especially when their design and operation is coordinated as a hybrid power plant. When included in hybrid power plants, distributed wind turbines in particular have the potential to enhance the resilience of distributed grids in areas with good wind resource, due to their ability to provide more consistent generation and ancillary services as compared to photo-voltaic (PV) solar panels. Despite this benefit, U.S. distributed wind adoption is lower than other comparable renewable energy technologies. In this study, we seek to demonstrate how hybrid power plants that include distributed wind turbines can contribute to distribution grid resilience by meeting loads (especially critical loads) more consistently, increasing reserve capacity, and providing value to customers during outages. To demonstrate these contributions, we integrate three separate frameworks and apply them to a case study in a rural electric cooperative in Iowa. Through this case study, we simulate and compare hybrid power plant design and operation during two hazard events: a tornado that causes a 48-hour distribution outage and a winter weather event that causes a 6-hour generation outage. The inclusion of a hybrid power plant that leverages 1) increased battery duration and 2) advanced forecasting and dispatch strategies that reserve capacity leading up to a hazard event best reduce lost loads as well as diesel consumption that would otherwise be used to meet those loads during short- and long-duration hazard events. Depending on the hybrid power plant capacity and operation, we find that the outage mitigation value of a hybrid power plant (measured in value to customers to avoid an outage and avoided lost revenues for the utility) is significant in both hazard events; adding wind, solar, and battery assets to the existing system adds about $50-$100M in avoided lost load and at least $4-$8k in utility value in the tornado hazard event, and $570k-$2.2M in avoided lost load and at least $220-$650 in utility value in the winter hazard scenario. In both the tornado and winter hazard scenarios, optimizing the operation of the hybrid system for resilience can lend similar value as increasing battery duration by 5 MWh for the lower capacity systems considered.

17 WIND ENERGY↗

DOE OSTI2024

Advanced Protection for Microgrids and DER in Secondary Networks and Meshed Distribution Systems

Although there are increasing numbers of distributed energy resources (DERs) and microgrids being deployed, current IEEE and utility standards generally strictly limit their interconnection inside secondary networks. Secondary networks are low-voltage meshed (non-radial) distribution systems that create redundancy in the path from the main grid source to each load. This redundancy provides a high level of immunity to disruptions in the distribution system, and thus extremely high reliability of electric power service. There are two main types of secondary networks, called grid and spot secondary networks, both of which are used worldwide. In the future, primary networks in distribution systems that might include looped or meshed distribution systems at the primary-voltage (medium-voltage) level may also become common as a means for improving distribution reliability and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

California Price Response Potential Study

California's energy landscape is undergoing a significant transformation, driven by the increasing integration of renewable energy sources, the increased adoption of distributed energy resources, the electrification of end-use loads, and the growing need for grid efficiency. To address these challenges, recent revisions to the State’s Load Management Standards (LMS) require all of California’s large utilities and community choice aggregators (CCAs) to offer dynamic electricity pricing options to customers by 2027. Dynamic pricing, which involves varying electricity rates based on real-time supply and demand conditions, offers a promising solution for optimizing grid operations, reducing costs, and incentivizing efficient use of grid capacity. Effective implementation of dynamic pricing requires understanding the potential impacts on customer bills, system load, and the cost-effectiveness of automation technologies. This study aims to evaluate the load response of various end-use devices to hourly dynamic prices. The end-uses studied here are space cooling, space heating, water heating, crop irrigation, pool and spa pumps, and electric vehicle (EV) charging, all for both residential and commercial applications, except for crop irrigation. In 2030, these end uses are forecasted to account for 18% of annual electricity demand in the state, but 40% of demand in the peak net load hour. By modeling possible price-responsive load dispatch algorithms and assessing the resulting impacts on both individual bills and the overall grid, we seek to inform policymakers and utilities about the potential benefits and challenges associated with dynamic pricing, and considerations for the design of dynamic pricing tariffs. Additionally, we will explore the cost effectiveness of adopting automation technologies to enable devices to respond more effectively to real-time price signals. This study considers a range of price profiles, accounting for differences across utilities and customer classes, and presents scenarios for dynamic price design via variation in the percentage of total customer electric costs that are allocated dynamically (versus constituting a fixed portion of the hourly volumetric price). We present results focused primarily on 2030, forecasting electricity prices under both low and high-cost scenarios, to inform longer-term tariff design considerations. We design tariffs by starting with 2019 prices that were calculated according to CalFUSE guidance (CPUC, 2022) and that have been used in recent studies; these prices are all-in volumetric rates that vary by utility and are revenue-neutral to each customer class. They are developed by considering six electricity cost components that are allocated hourly based on system load indicators (gross and net load, and wholesale prices). These prices are forecasted to 2030 for low and high cost scenarios, considering recent trends in total electricity costs with and without years of substantial wildfire mitigation investments. These tariffs, which allocate all costs on an hourly basis, are considered our “Full” dynamic tariff design scenario, while two additional scenarios explore allocating a portion of costs as a flat volumetric charge: the “Medium” scenario allocates 50% of revenue dynamically (and keeps 50% flat), while the “Mild” scenario allocates 20% of revenue dynamically. The 20% dynamic allocation on the Mild scenario aims to represent a case where only the marginal operating costs of the grid are included in the dynamic price.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

EV Stock and Load Forecasting for HECO [Slides]

This presentation covers the work completed for the HECO Forecasting Department for the Electric Vehicle Stock and Load Forecast for Integrated Grid Planning project. This project uses a suite of detailed analytical tools developed by the National Laboratory of the Rockies, including TEMPO and EVI-Pro, to develop future scenarios to 2050 of county-level electric vehicle adoption and associated annual hourly charging load profiles for the state of Hawaii.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Enabling Grid-Forming Control Under Unbalanced Conditions

Standalone microgrids often experience unbalanced loading and faults, which can cause grid-forming control designed for balanced conditions to produce oscillatory responses. To address this issue, a compact time-domain transformation appropriate for inverter control is proposed, allowing the conversion of unbalanced three-phase signals to positive and negative synchronous reference frames. This transformation supports the development of a grid-forming control with fault ride-through, featuring frequency and voltage droop controllers and nested current and voltage control loops that seamlessly integrate an enhanced current limiter. The effectiveness of the proposed control and transformation is demonstrated through analytical results and electromagnetic transient simulation.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Optimal Electric Vehicle Charging and Discharging Strategies Under DER Compensation Programs: Preprint

The adoption of electric vehicles (EVs) is becoming increasingly popular because of environmental concerns, the greater availability of models, and increased cost-competitiveness with gas vehicles. Because EVs have both charging and discharging capabilities, they provide great potential to help electric utilities with grid operation. When the grid demand is high, EVs can discharge to the grid to reduce the peak load, and vice versa; therefore, electric utilities have designed different policies to encourage EV charging station operators to charge or discharge at certain time periods. The New York State Public Service Commission established the Value of Distributed Energy Resources (VDER), or the Value Stack, to compensate for energy created by distributed energy resources, including EVs. This paper presents an optimization-based approach to identify the "golden hours" and "golden spots," i.e., the effective time periods and geographic locations for EV charging station operators to charge or discharge under the VDER program that can provide them the highest benefit. The proposed methodology can be applied to other compensation mechanisms and distribution systems as well. By working with industry partner NineDot Energy, realistic charging station information is used in this study, and the proposed approach is tested on a distribution feeder. The results from this study can help electric utilities and EV charging station operators determine the ideal charging/discharging time and the ideal locations for the charging station(s) in their distribution systems to achieve maximized benefit.

electric vehicle↗

DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗

DOE OSTI2024

Dispatching Grid-Forming Inverters in Grid-Connected and Islanded Mode: Preprint

This paper explores the dispatch-ability of grid-forming (GFM) inverters in grid-connected and islanded mode. Grid-forming (GFM) inverters usually use droop control to automatically share power with other GFM sources (inverters and synchronous generator (SG)) and follow the change of the load demand. However, they can be dispatched like their grid-following (GFL) counterparts to output the target active and reactive power. This will help the grid operator better manage their inverter-based resources (IBRs) for improved operation efficiency and reliability. Therefore, this paper proposes an innovative concept of dispatching GFM sources (inverters and SG) to output the target power for both grid-connected and islanded mode by adjusting their droop intercepts. The fundamental principle of doing so is that the GFM inverter's active and reactive power is dictated by its frequency and voltage, thus, dispatching active and reactve power of a GFM inverter can be achieved through dispatching its frequency and voltage. Moreover, the concept distinguishes the dispatch rules for grid-connected and islanded mode. Finally, the concept is validated with an example microgrid system with two GFM inverters, one diesel generator, one grid-following inverter and loads in both grid-connected and islanded mode. This pioneering work results in a practical guidance for power system energy management system (EMS) development to control a future grid with GFM and GFL inverters.

droop control↗

DOE OSTI2024

Dispatching Grid-Forming Inverters in Grid-Connected and Islanded Mode

This paper explores the dispatchability of grid-forming (GFM) inverters in grid-connected and islanded mode. An innovative concept of dispatching GFM sources (inverters and synchronous generators) is proposed to output the target power by adjusting their droop intercepts. The fundamental principle is that the GFM inverter's active and reactive power is dictated by its frequency and voltage, and thus dispatching the active and reactive power of a GFM inverter can be achieved through dispatching its frequency and voltage. The concept is validated with an example microgrid system with two GFM inverters, one diesel generator, one GFL inverter, and the load in both grid-connected and islanded mode. This pioneering work results in practical guidance for the development of energy management systems for future electric grids with GFM and GFL inverters. The key findings are summarized as follows: 1) The GFM inverters can be dispatched through frequency and voltage droop intercepts to output the target power; 2) The dispatch rule for grid-connected and islanded mode is slightly different.

dispatch GFM inverter↗

DOE OSTI2026

Small Nuclear Reactors for Maritime Ports

Maritime ports are entering a period of sharply rising electricity demand as operations are electrified, shore power adoption grows, and energy-intensive industries expand near ports. This report evaluates the feasibility of small nuclear reactors at U.S. ports, which could offer stable baseload power and reduced dependence on regional grids. The report describes the current state of advanced reactor technologies and other factors important for future deployment such as safety and operations, siting requirements, regulatory environments and policy, and other co-benefit considerations. A structured evaluation across a diverse group of U.S. ports highlights the wide variation in feasibility. Fifteen ports were analyzed through port interviews and data collection to assess the port-specific conditions that most impact advanced reactor deployment. The analysis found that the most feasible ports for deployment have favorable geotechnical stability, supportive regulatory environments, and substantial energy loads in a grid-constrained environment. Additionally, an initial reactor size matching was done for the ports based on their reported energy consumption across different modes of operation. However, further analysis and detailed data will be required in the future to determine the optimal reactor-port matching. The economic viability to adopt this technology will be dictated by competitive cost of nuclear-generated electricity compared to other alternatives. Overall, small nuclear reactors present a promising but highly site-dependent pathway for ports seeking resilient, high-capacity energy solutions that support future energy demands. This report identifies key areas for future research and highlights ports that warrant further evaluation to assess the viability of small nuclear reactor implementation. By establishing these priorities, the analysis provides support for the development of informed strategies for potential advanced nuclear technology deployment. The inclusion of ports in this report does not imply their endorsement of nuclear energy generation, and the authors are grateful for the information, expertise, and perspectives they contributed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Proactive Regulatory Approaches to Electrification and Load Growth: Pre-read Document to Support the July 10-11 th Workshop

This document summarizes objectives and context related to a DOE-funded workshop on proactive regulatory approaches to electrification and load growth. It briefly summarizes some of the regulatory barriers to pursuing a proactive approach and some of the risks associated with such an approach. It then summarizes a selection of recent utility proposals and public utility commission actions related to proactive approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Optimizing Power Line Undergrounding Decisions under Varying Wildfire Risk and Weather Scenarios

Abstract—The threat of wildfire ignitions from electric power equipment has led utilities to increasingly turn to preemptive power shutoffs, which, while effective in reducing grid-induced wildfire risk, can cause significant load loss. Undergrounding power lines is an alternative strategy for preventing grid-induced wildfires. However, undergrounding lines is costly, so an efficient undergrounding plan must balance reductions in wildfire risk and load loss with the cost of undergrounding lines. We propose a robust optimization model to identify which power lines to underground to maximize load served while limiting wildfire risk across a range of wildfire risk and weather scenarios. Since solving this problem may be computationally heavy for large power grids and many operating scenarios, we present a delayed constraint generation algorithm to iteratively add scenarios until an optimal solution is found. We evaluate the performance of this framework on the RTS-GMLC with scenarios representing a year of operating conditions and compare it with a stochastic programming formulation. Our results indicate that our undergrounding model is successful in reducing load shed and risk compared to baseline cases in which no mitigation action is taken and only power shutoffs are implemented (no undergrounding). The robust formulation also reduces more load shed than the stochastic formulation in the most extreme scenarios. Index Terms—grid resilience, optimization, transmission systems, underground power lines, wildfire risk.

Taylor, S. [Department of Electrical and Computer ↗

DOE OSTI2026

District-Scale Analysis of Electricity Load and Strategies to Improve Energy Reliability Using Prototype District Models

Projected increases in electricity demand in the U.S. highlight the urgent need for effective load management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗