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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
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DOE OSTI2024

Managing changes in peak demand from building and transportation electrification with energy efficiency [Slides]

The Department of Energy funded Berkeley Lab to provide technical assistance to two municipal utilities on how energy efficiency and demand flexibility can mitigate the peak demand impacts of building and transportation electrification. Berkeley Lab worked with these utilities, Sacramento Municipal Utility District (SMUD) and Fort Collins Utilities, to identify research questions that supported their planning needs. For both utilities, Berkeley Lab developed scenario-based load forecasts that considered baseline and high-efficiency building electrification. For SMUD, the forecast also explored the sensitivity of peak demand to extreme weather (a winter cold snap) at the system-level. For Fort Collins Utilities, the forecast addressed the impacts of low, medium, and high levels of building and transportation technology adoption on select distribution feeders. Berkeley Lab is also developing a guidance document for utilities that will draw on lessons learned from the technical assistance and provide a framework for conducting similar analyses.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Optimal Operation of Residential High Performance Water Heater for Reduction of Electricity Cost and Peak Demand Through Field Validation

Water heating accounts for about 18% of a typical US home’s energy use. Modern water heaters have enabled control options through APIs, offering customers the opportunity to reduce their energy cost and peak demand by dynamically adjusting settings. A water heater’s capacity to store energy using its storage tank makes it an asset for peak demand reduction and energy cost savings. For this reason, a mixed-integer linear programming model is proposed to minimize the energy cost of a high-performance water heater while also reducing the peak demand of the residential household under a time-of-use utility rate by dynamically changing the water heater’s running mode. Specifically, a multi-objective optimization model is formulated to determine the mode settings of the water heater considering hot water use, time-of-use rate, and peak demand limit of the residential household. The mode settings are associated with different dead bands of water temperature for triggering on/off action of the heat pump and heating element. A 66-gal hybrid electric high performance water heater was used for numerical simulation and practical experiments. The simulation results were well aligned with measurements of practical experiments, validating the soundness of the thermodynamic model. In addition, reductions of energy cost, enabling affordability, and reducing peak demand are demonstrated. The research team also developed a software framework with dashboards to automatically and continuously monitor and manage devices.

Liu, Guodong [ORNL] (ORCID:0000000213498608)↗
DOE OSTI2026

Geothermal-integrated thermally anisotropic building envelope for energy and peak-demand reduction

Buildings consume large amounts of energy for heating and cooling, while peak electricity demand places significant stress on the power grid. This paper presents a reduced-order co-simulation framework and load-oriented supervisory control strategy for a geothermal-integrated thermally anisotropic building envelope with a ground loop (TABE+GL). In TABE+GL, a hydronic loop embedded in the building envelope is directly coupled with a geothermal ground loop, allowing for bidirectional heat exchange between the envelope, the ground, and the indoor environment. A hybrid co-simulation framework was established by coupling a reduced-order resistor–capacitor (RC) thermal network model with EnergyPlus augmented with GHEDesigner modules. The RC model generated feasible heat flux options under three operating modes, and EnergyPlus predicted sensible loads, energy use, and pump energy demand. At each simulation step, a supervisory control algorithm selected the optimal loop configuration and duty factor that maximizes useful TABE geothermal utilization without exceeding the predicted sensible load, thereby avoiding overheating or cooling. Case studies were conducted for Los Angeles, California, Charleston, South Carolina, and Denver, Colorado. Results showed that the proposed framework reduced HVAC electricity consumption by 43%–67%, natural gas use for space heating by 11%–38%, and peak electricity demand by 43%–88%. These results highlight the potential of combining reduced-order envelope modeling, direct geothermal coupling, and load-oriented supervisory control to improve whole building energy performance and reduce peak demand across diverse weather conditions.

Howard, Daniel [Southern Adventist University]↗
DOE OSTI2026

Characterizing peak electricity demand for U.S. households: an assessment of end-use loads and demand factors

Understanding household peak electricity demand is critical to evaluate the technical need for electrical infrastructure upgrades. This study characterizes peak loads for existing and new equipment using metered data from a convenience sample of 11,940 U.S. dwellings from four sources, including 911 from two sources with end-use metering. After standardized data cleaning and labeling, we derived descriptive statistics for key metrics, such as maximum demand and demand factors, and developed predictive models relating 60- to 15-min demand for the National Electrical Code (NEC). Mean 15-min maximum demand was 9.7 kW (median 9.0 kW; IQR 7.0–11.5 kW, 95% CI 9.6–9.8 kW), indicating spare capacity in 98% of homes with hypothetical 100 A panels. Maximum demand increased with floor area and number of high-demand loads. Dwelling maximum demand was driven by higher-power, longer-duration heating appliances and vehicle charging, while most user-operated appliances contributed little. Demand factors are used to account for how most devices contribute less than their rated power to maximum demand. Existing load mean demand factors (28%; median 10%; IQR 0–58%; CI 28–29%) were higher than those for new loads (21%; median 7%; IQR 0–35%; CI 20–21%), because new loads changed the timing and magnitude of maximum demand. New high-demand loads had higher than average demand factors (40–60%). Whole dwelling demand factors support the NEC's 40% assumption, but they challenge its conservative 100% treatment of new HVAC. We propose a data-driven 50% demand factor for new equipment, which would align with metered data, improve affordability, and modernize electrical codes.

Appliances↗
DOE OSTI2026

Energy Storage and the Law of Averages: How Storage Can Make Electricity More Affordable

The electric grid is planned, built, and operated to satisfy peak demand. But because peak demand only occurs for a few hours per year, customers end up paying full price for grid infrastructure that is only used for a small fraction of the year—an increasingly expensive proposition as peak demand continues to grow and more infrastructure is required to meet it. The emergence of cost-competitive energy storage technologies in recent years, however, offers the potential for a grid that is planned, built, and operated based on average demand. By strategically siting and operating energy storage throughout the electric grid, excess generation in low-demand periods can be captured and stored near customers, which then reduces the amount of electricity that needs to be generated and moved through the transmission and distribution systems during high-demand periods. This paper describes these potential benefits, supported by real-world examples of energy storage projects that have created cost savings, which points to the potential for profound and far-reaching reductions in the cost of electricity if energy storage technologies are deployed at scale throughout the electric grid. These examples will be of use to system planners and operators, utility regulators, decision makers, and stakeholders in those processes as they look for opportunities to reduce the cost of electricity in their respective systems and jurisdictions.

25 ENERGY STORAGE↗
DOE OSTI2024

How the U.S. Power Grid Kept the Lights on in Summer 2024

Maintaining the reliability of the bulk power system, which supplies and transmits electricity, is a critical priority of electric grid planners, operators, and regulators. As demand for electricity increases and the U.S. resource mix changes, how grid operators meet peak demand is changing. In summer 2024, grid operators in all regions maintained enough capacity to keep the lights and air conditioners on during periods of peak demand, even as older generators have been retired. And, an increasing number of regions used more solar and storage to meet peak demand. In this publication, we describe grid operations on the highest demand day in ERCOT and a few other regions and how solar and storage in particular worked together to help meet peak demand.

14 SOLAR ENERGY↗
DOE OSTI2025

Techno-Economic Analysis for the Addition of Thermal Energy Storage to a Campus With Existing Battery Storage

Rising global temperatures and increasing energy demands pose significant challenges for energy management, particularly in institutional and commercial settings. As cooling needs grow, campuses must balance operational efficiency, cost control, and grid stability. Energy storage solutions, such as thermal energy storage (TES) systems, offer a promising approach to shifting energy consumption from peak to off-peak periods, alleviating peak demand, reducing utility costs, and enhancing grid resilience. When integrated with existing battery energy storage systems (BESS), TES can further optimize load management and improve energy savings, especially in buildings with diverse energy needs. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills, which already operates a BESS. We assess three TES sizing strategies—full storage, load leveling, and peak demand limiting—by modeling and simulations based on historical energy loads. Our findings show that we can control TES systems to complement BESS operation, with campus-level load leveling providing the greatest cost savings by reducing peak demands. Furthermore, the study also evaluates the long-term economic viability of TES, considering installation costs, energy savings, and payback periods under varying tariffs. This research offers practical guidance for institutions seeking to enhance energy resilience and reduce operational costs through energy storage solutions.

25 ENERGY STORAGE↗
DOE OSTI2024

Long-term impact of electrification and retrofits of the U.S residential building in diverse locations

The U.S. buildings sector contributes 30% of operational carbon emissions, with residential buildings accounting for 56%. Reducing residential carbon emissions is crucial for achieving net-zero carbon goal. While many studies examine energy efficiency retrofit (EER) and electrification, few explore their long-term impacts across diverse climates and dynamic grid clean energy penetrations, as well as their economic effects on households. Here, this study proposes a method to assess how EER and electrification affect long-term decarbonization and economics across different climates, focusing on carbon emissions, energy burden (the percentage of household income spent on energy), and payback period in four locations: Tampa, San Diego, Denver, and Great Falls. The study also introduces the concept of implicit energy burden by considering investment costs. Results show that while electrification can reduce long-term emissions with increased clean energy penetration, it may not always achieve decarbonization due to mismatches between clean energy availability and demand. In cooling-dominant locations, electrification lowers energy burden and peak demand, but in heating-dominant locations, it increases energy burden to 8.24%, raises peak demand by 632.78%, and shifts it from summer to winter. After integrating investment costs, the implicit energy burden can reach 8.35% in cold climates. For already highly electrified buildings in Denver and Great Falls, the payback period of EER measures can be shortened by up to 48.98%. The study highlights a tradeoff between decarbonization and energy burden alleviation, showing that while EER measures can reduce the energy burden, they only achieve one-quarter of the carbon emission reduction of electrification.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Evaluating the Impact of Managed EV Charging for Reliable Operation of Bulk Power Systems with High Non-Dispatchable Generation

The growth of electric vehicles (EVs) and variable-generation (VG) sources introduces new challenges for power-system operations. This study introduces a modeling framework and evaluates five EV charging strategies under projected 2040 grid conditions in the Evergy service territory with high non-dispatchable generation. Using realistic EV behavior and generation models, their impacts on system peak demand, ramp rate, and reserve capacity are evaluated. Results show that only the peak-avoidance strategy effectively reduces system peak demand, while decentralized strategies-particularly cost based dynamic charging-can exacerbate peaks due to synchronized user behavior. However, ramp-rate minimization strategy significantly reduce the stress on dispatchable generation achieving the lowest maximum absolute ramp rate (MARR) (56.81 MW) and lowest reserve requirement (2.39 GW). In contrast, unmanaged and TOU random strategies increase the stress on dispatchable generation sources with increased MARR and reserve requirements. These findings highlight the importance of coordinated, system-aware managed charging strategies to ensure reliable and affordable grid operation in the presence of EVs and VG sources.

14 - SOLAR ENERGY↗
DOE OSTI2025

Techno-Economic Analysis for the Addition of a Thermal Energy Storage System to a Central Plant

Increasing energy demand and rising peak loads present significant challenges for energy management in commercial and institutional settings. As climate change drives greater cooling needs, central plants must navigate the complex tradeoffs between operational efficiency, cost control, and grid stability. Thermal energy storage (TES) systems offer a viable solution by shifting energy consumption from peak to off-peak periods, thereby reducing peak demand, lowering utility expenses, and improving grid resilience. However, the success of TES implementation hinges on appropriate system sizing, effective control strategies, and alignment with local utility rate structures. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills. Drawing on historical load profiles and utility tariffs, we assess three TES sizing approaches and their corresponding control strategies from both energy and economic perspectives. This article utilizes a model-based approach to assess the impact of TES sizing and control strategies on the techno-economic feasibility of integrating TES into an existing central plant. The models employed for this analysis were calibrated using 4 years of historical data. Here, the results demonstrated that utility tariffs and the campus's operational profiles dictate the most feasible sizing and control methods. The findings offer valuable insights for institutions and commercial building managers exploring sustainable energy solutions. By demonstrating how optimized TES strategies can improve operational efficiency while achieving financial savings, this study highlights the potential for TES to align performance with cost effectiveness in real-world applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Rewarding Grid-Friendly Behavior: Estimating the Potential Bill Reduction and Load Shifting Benefits of Dynamic Prices

Shifting electric load from times of peak demand can be a key strategy to slow price growth as reducing peak demand avoids the cost of upgrading generation, transmission and distribution infrastructure. Utilities are releasing time-varying prices, such as time of use rates or dynamic prices, to incentivize grid-friendly load shifting. New dynamic price programs provide insight into the true cost of operating electricity grids and the potential economic benefits of load shifting. Program developers and device manufacturers need to understand the economic opportunities in terms of 1) the variation in prices across hours, days, and seasons; 2) the change in utility bills for customers who don’t shift load; and 3) the potential load shifted and economic value of different technologies if manufacturers or aggregators deploy price-responsive controls. This paper estimates possible impacts of dynamic price adoption and load shifting controls if customers paid the dynamic rate from one pilot program. Statistical analysis of historical prices identified annual and seasonal metrics as well as representative price curves for each circuit in the pilot. Simulations for residential technologies with price-responsive controls including unitary heat pump water heaters, central multifamily heat pump water heaters, heating & cooling + storage systems, and pool pumps estimated the potential impacts of highly dynamic prices both with and without load shifting controls. Results showed the potential to reduce electricity costs on representative days by 42-94% and reduce consumption during times of high electricity prices by 63-100% compared to baseline operation for those flex-friendly devices.

Grant, Peter↗
DOE OSTI2024

Residential Water Heating Demand Side Management (DSM) - South Africa

The electricity crisis in South Africa has deteriorated significantly, with the country experiencing frequent and prolonged rolling blackouts. These outages have severe economic repercussions, leading to decreased growth and productivity. Demand Side Management (DSM), particularly focusing on electric water heaters due to their significant energy consumption and peak demand contribution, is identified as a key strategy. The study aims to assess opportunities for DSM programs targeting water heating to reduce energy consumption and peak demand. It entails developing a bottom-up simulation model to establish a baseline scenario of water heating electricity load demand in 2023 and 2033, identifying technologies for energy reduction, estimating the impacts of a selected number of measures and providing recommendations to inform policy makers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Performance Characterization of InCharge™ ICE-66 V2X Bidirectional DC Fast Charger

Vehicle-to-grid (V2G) technology extends the role of Plug-in Hybrid Vehicle’s (PHEV) and Battery Electric Vehicle’s (BEV) batteries beyond transportation by enabling bidirectional power transfer between the vehicle's onboard energy storage and the utility grid. Modern battery-powered vehicles are equipped with high-capacity battery packs that remain stationary and underutilized for the majority of their operational life. A vehicle used for daily commuting may be parked and connected to charging infrastructure for 18–20 hours per day, representing a significant untapped energy resource. When considered at scale, the aggregated storage capacity of a modest fleet of 10–15 vehicles within a single parking facility can reach the MWh range, sufficient to partially offset peak demand for a mid-size commercial building or contribute meaningful ancillary services to the local grid. The ability to charge during off-peak periods when electricity prices are low and discharge during peak demand when prices are high positions EV batteries as distributed energy arbitrage assets, with the potential to offset vehicle ownership and charging costs. Beyond energy arbitrage, V2G-capable assets can provide ancillary grid services through active and reactive power injections. Active power supports grid frequency regulation, while reactive power supports local voltage regulation. Together, these capabilities establish V2G as a technically promising and economically relevant pathway toward greater integration of battery-powered vehicles into the broader energy system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Field testing and validation of a low-cost MPC for demand flexibility for grid-interactive K-12 schools

K-12 school buildings account for the highest energy consumption within the public sector. Implementing advanced HVAC controls in grid-interactive K-12 schools could bring substantial economic advantages and grid flexibility. Our previous study demonstrated that a low-cost model predictive control (MPC) solution, which coordinates multiple packaged units, can enable demand flexibility without major hardware upgrades. However, a significant gap remains between academic pilots and market-ready scalable solutions. This paper extends the previous single-site pilot to a multi-site demonstration involving three school campuses (95 total units) through a commercial technology transfer process. Addressing the challenge of verifying performance with sparse field data, we present a new statistical approach using Bayesian methods to estimate the MPC’s effect on peak demand. Unlike traditional methods, this approach robustly quantifies uncertainty in non-normal, limited datasets. The results confirm the solution’s replicability, achieving a 21.6–38.9% reduction in HVAC peak demand (10.8–22.1% at the site-level) with > 98% probability across diverse locations. Finally, we document critical barriers to scaling software-as-a-service (SaaS) solutions–such as API instability and diverse legacy systems–and offer practical strategies to accelerate the commercial adoption of grid-interactive efficient buildings.

Ham, Sang Woo↗
DOE OSTI2026

Project Phase 1 Report: Reducing Data Center Peak Cooling Demand and Energy Costs With Cold Underground Thermal Energy Storage (Cold UTES)

Cold Underground Thermal Energy Storage (Cold UTES) is an ultra-long duration grid energy storage technology. With Cold-UTES, low-cost grid power is converted to cold thermal energy and stored in the native subsurface rock at the point of use. Cold UTES is one approach within the general category of engineered geothermal systems. Cold UTES for peak-hour cooling of data centers (DCs) was studied for deployment in Maricopa County, Arizona and Loudoun County, Virgina using thermal storage capacities from 4 GWh-th to over 1,000 GWh-th (>1 Terawatt-hour). The two sites have different power and transmission systems, available grid energy resources, daily and seasonal load profiles, weather conditions, and grid regulatory requirements. The study results indicate high value for both locations and because of this, likely indicates value across most of the US and the world. The basis of the study was a 1,000 MW-e hourly electric use of DC computing and auxiliary loads, which was modeled as 1 GW-th of thermal load to a dry cooled heat rejection system - i.e. a cooling system that does not consume water. The electric power required for cooling the DC varies as the air temperature changes. In cold weather only the dry-coolers are used, with an electrical load for cooling load as low as 10 MW-e. In hot summer hours, chillers and dry- coolers are required, which raises the electrical load for cooling load to as much as 300 MW-e. The continuous and peak cooling electrical loads result in a grid interconnection requirement of no less than 1,300 MW-e. From both a grid and thermal design modeling perspective the 1.3 GW-e could either be a single facility or result from the total load at multiple sites.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Reducing Data Center Peak Cooling Demand and Energy Costs with Underground Thermal Energy Storage (UTES)

By recent estimates, data center energy demands are projected to consume between 6.7% and 12% of U.S. annual electricity generation by the year 2028, driven primarily by expanded demands from cloud services, big data analytics, and Artificial Intelligence (AI) (Shehabi et al., 2024). As much as 40% of data center total energy consumption are loads associated with the site infrastructure cooling systems, and these are often highly water consumptive (Aljbour et al., 2024). For energy system planners, this presents significant challenges to meeting and managing the anticipated loads, and especially the peak loads of projected data center deployments. Geothermal technologies offer two unique solutions to these challenges: 1) by serving loads through the deployment of new conventional and/or next-generation geothermal power technologies such as EGS and 2) through an often-overlooked opportunity to reduce data center peak cooling loads. The latter is the focus of this paper which explores Cold Underground Thermal Energy Storage ("Cold UTES") as an emerging industrial-scale geothermal cooling solution. This cooling solution is energy efficient, non-water-consumptive, and utilizes long duration energy storage (LDES) on both diurnal and seasonal time scales. Cold UTES has the potential to also function as a virtual power plant (VPP). The US Department of Energy's Geothermal Technologies Office is supporting R&D to understand the grid and system-wide value, costs, and impacts of deploying this emergent cooling solution at scale.

AI↗
DOE OSTI2025

Getting brighter: Impacts of improved day-ahead solar forecasts in high-solar, high-storage electricity systems

This paper analyzes the impacts of improved day-ahead solar forecasts on costs and dispatch in the solar-rich Southeast U.S. It uses an optimized high-solar, high-storage resource portfolio in which solar generation capacity accounts for 45 % of total installed capacity (34 %–36 % of generation) and energy storage capacity (43 GW) is equivalent to 33 % of peak demand. In a base scenario, improved day-ahead solar forecasts reduce production costs by $\$87$ million per year ($\$0.13$ per MWh load, $2023$$). This level of savings is within the range or lower than earlier studies of solar forecast improvements at lower levels of solar generation (<25 % of total generation). In this study, solar expansion was accompanied by two important sources of flexibility for managing solar forecast error: energy storage and day-ahead solar curtailment. Furthermore, the analysis finds that regional coordination complements day-ahead solar forecast improvements while natural gas commitment flexibility is a substitute for forecast improvements, as the improved solar forecast leads to sub-optimal commitment of thermal units. Day-ahead solar forecast improvements reduce reserves required to manage forecast error by 30 %. Fewer reserves to manage large, infrequent solar forecast errors could be an important benefit of improved solar forecasts.

14 SOLAR ENERGY↗
DOE OSTI2025

Scalability and Effectiveness of Smart Charge Management

The rise in electric vehicle (EV) adoption presents growing challenges for power grids, particularly from simultaneous residential charging, which can cause voltage fluctuations and increase feeder peak loads. Baltimore Gas and Electric (BGE), with support from the U.S. Department of Energy, initiated a pilot program to evaluate managed residential EV charging through Smart Charge Management (SCM). This study analyzes real-world charging behavior data from the pilot and feeder-level base loads from BGE to simulate residential charging scenarios through 2035 across the Washington, DC–Baltimore region. Grid impacts under unmanaged charging are compared to three SCM strategies: TOU-immediate, TOU-distributed, and Load Balancing. Results show that the magnitude of peak reduction is highly feeder-dependent. Some feeders achieve reductions of more than 40% at high enrollment levels, while others show improvements closer to 10–15%. This heterogeneity reflects differences in baseline feeder load shapes, EV penetration, and plug-in behavior across customers. Results also highlight trade-offs between shifting load away from peak periods and minimizing secondary demand peaks, offering practical insights for future utility program design.

Electric vehicle↗