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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Hourly Electricity Demand Profiles for Each County in the Contiguous United States

This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. (2) Weighted averages of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector Annual county-level retail sales are estimated by aggregating utility-reported sales to the state level and allocating the results to counties according to each county's share of state population. Annual county-level direct use is calculated by aggregating power plant-reported direct use values. Annual county-level on-site consumption of DPV-generated electricity is estimated by aggregating utility-reported net metering data to determine the amount of DPV-generated electricity sold back to the grid for each state, subtracting those values from modeled state-level DPV generation estimates, and allocating the results to counties according to each county's share of statewide modeled DPV generation. The open-source Python code used to develop this dataset is available at "Historical Load Data Repository" link below.

14 SOLAR ENERGY↗

NASA NTRS2020

Design and Test of an Electromechanical Rover Tether for the Exploration of Vertical Lunar Pit

Moon Diver is a proposed mission to land and deploy an extreme-terrain, tethered rover for the exploration of Tranquillitatis Pit, a large vertical cave entrance into the subsurface of Earth’s Moon. By leveraging a supportive tether, the Axel rover, developed by NASA’s Jet Propulsion Laboratory, would perform a controlled descent into the pit and deploy instruments along the pit wall. The purpose of this mission concept is to study a volcanic secondary crust as a function of depth in order to determine formation processes and chemical makeup. The lifeline of the mission would be the tether, which provides power from, and communication to the top-side lander. Critically, the tether also serves as mechanical support between the suspended rover and the lander, which acts as an anchor. While space tethers have been deployed both in orbit and terrestrially, the use of the proposed tether is unlike any known in the literature; the tether must come into contact with the terrain while under load. With respect to the environment, the tether must also survive abrasion from glassy regolith and volcanic rocks, bending around sharp edges, thermal extremes, and exposure to full spectrum ultra-violet (UV) radiation, all while reliably transferring up to 100 W of power and 1 Mbps of data. Furthermore, since the Axel rover pays out tether from an internal spool, the tether’s diameter must be minimized to increase spool capacity, allowing for up to a 300-m traverse while also meeting static and dynamic strength requirements. This paper covers several phases of the tether’s initial development, including i) a trade study of structure and materials with consideration for space heritage, ii) selected design justification, and iii) results from tests on prototype tethers looking into mechanical, electrical, and environmental properties, including exposure to rock regolith abrasion, load profiles at temperature, and degradation due to UV exposure while exposed to vacuum. Finally, we provide insights and lessons learned from lab and field tests, which inform our continued effort to design a tether capable of surviving rugged, lunar conditions.

Nensas, Issa↗

DOE OSTI2024

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↗

DOE OSTI2021

Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems

Major technological advancements and recent policy support are improving the outlook for heavy-duty truck electrification in the United States. In particular, short-haul operations (=200 miles (=322 km)) are prevalent and early candidates for plug-in electric vehicles (EVs) given their short, predictable routes and return-to-base applications, which allows vehicles to recharge when off shift at their depots. Although previous studies investigated the impacts of added electrical loads on distribution systems, which included light-duty EVs, the implications for heavy-duty EV charging are underexplored. Here we summarize the causes, costs and lead times of distribution system upgrades anticipated for depot charging. We also developed synthetic depot charging load profiles for heavy-duty trucks from real-world operating schedules, and found that charging requirements are met at common light-duty EV charging rates (=100 kW per vehicle). Finally, we applied depot charging load profiles to 36 distribution real-world substations, which showed that most can accommodate high levels of heavy-duty EV charging without upgrades.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

A Modified Sequence-to-point HVAC Load Disaggregation Algorithm

This paper presents a modified sequence-to-point (S2P) algorithm for disaggregating the heat, ventilation, and air conditioning (HVAC) load from the total building electricity consumption. The original S2P model is convolutional neural network (CNN) based, which uses load profiles as inputs. We propose three modifications. First, the input convolution layer is changed from 1D to 2D so that normalized temperature profiles are also used inputs to the S2P model. Second, a drop-out layer is added to improve adaptability and generalizability so that the model trained in one area can be transferred to other geographical areas without labelled HVAC data. Third, a fine-tuning process is proposed for areas with a small amount of labelled HVAC data so that the pre-trained S2P model can be fine-tuned to achieve higher disaggregation accuracy (i.e., better transferability) in other areas. The model is first trained and tested using smart meter and sub-metered HVAC data collected in Austin, Texas. Then, the trained model is tested on two other areas: Boulder, Colorado and San Diego, California. Simulation results show that the proposed modified S2P algorithm outperforms the original S2P model and the support-vector machine based approach in accuracy, adaptability, and transferability.

Ye, Kai↗

DOE OSTI2020

DC Fast Charging Infrastructure for Electrified Road Trips

To assess DC fast charging station network required for electrified road trips by 2030 in California, a new charging infrastructure simulation tool/model, EVI-Pro (Electric Vehicle Infrastructure Projection) RoadTrip, has been developed. In contrast to the existing EVI-Pro model that is primarily for short-distance travels, EVI-Pro RoadTrip is exclusively focused on road trips (long-distance travels, 100 or miles per day per vehicle). Also, the charging paradigm or strategy is different. EVI-Pro RoadTrip is built upon waypoint charging, in which vehicles are forced to stop to charge or replenish the on-board batteries, along the routes between origins and destinations. On the other hand, EVI-Pro is based on destination charging, in which charging is conducted when vehicles are parked in destinations (e.g., work, home). EVI-Pro RoadTrip takes coordinate-level origin and destination data for road trips (intra-state as well as domestic or international out-of-state) and estimates energy consumption and charging needs along the routes between origins and destinations on a minute-by-minute resolution. Based on charging demands for electrified road trips across the state, the optimal locations of charging stations are determined accounting for preferred land use types (e.g., commercial areas) and station service area (e.g., 5 or less miles). Based on station-by-station charging load profiles, the required number of plugs/connectors is estimated for each station and entire state. By comparing hosting capacity of the electric grid (circuit-level) and the charging load output from EVI-Pro RoadTrip, capacity deficit is also evaluated.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗

DOE OSTI2026

Estimated Hourly Electricity Demand Profiles for Each County in the Contiguous United States

In this data descriptor, we present hourly electricity demand estimates for each county in the contiguous United States from 2016 to 2023. The demand profiles represent the sum of two components for each county. The first is the weighted average of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. The second is the weighted average of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Analyzing School Bus Electrification in Richmond, Virginia

School buses are an essential component of the transportation infrastructure, serving as a lifeline for students across the globe. However, the widespread use of diesel school buses has raised concerns about the health impact on millions of students exposed to harmful emissions daily. Recognizing this issue, school districts worldwide are urgently seeking cleaner energy alternatives. Electric school buses emerge as an environmentally friendly and sustainable option, fostering a healthier environment for both students and communities. However, school bus electrification faces the challenges of high upfront cost, cumbersome charging management, and constraints from power grids. To help school bus operators address those challenges, this study presents a data-driven analysis for school bus electrification. This study considered a real-world school bus system in Richmond, VA, and developed a mathematical programming model to analyze the system design, charging strategies, and charging load profiles for the electrification scenario. The study evaluated different charging strategies based on model outcomes, aiming to optimize efficiency and effectiveness. Ultimately, this research generated electric school bus charging demand profiles under various scenarios, shedding light on the feasibility and implications of transitioning to electric-powered school buses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

End-Use Savings Shapes Upgrade Package Documentation: Wall and Roof Insulation, New Windows, LED Lighting, HP-RTU and ASHP-Boiler

Building on the successfully completed effort to calibrate and validate the U.S. Department of Energy’s ResStock™ and ComStock™ models over the past 3 years, the objective of this work is to produce national data sets that empower analysts working for federal, state, utility, city, and manufacturer stakeholders to answer a broad range of analysis questions. The goal of this work is to develop energy efficiency, electrification, and demand flexibility enduse load shapes (electricity, gas, propane, or fuel oil) that cover a majority of the high-impact, market-ready (or nearly market-ready) upgrade measures, or upgrades. “Measures” refers to energy efficiency variables that can be applied to buildings during modeling. An end-use savings shape is the difference in energy consumption between a baseline building and a building with an energy efficiency, electrification, or demand flexibility upgrade applied. It results in a time-series profile that is broken down by end use and fuel (electricity or on-site gas, propane, or fuel oil use) at each time step.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Low-temperature solar thermal-power systems for residential electricity supply under various seasonal and climate conditions

In this work, the performance of low-temperature (<100 degrees C) solar thermal-power systems to satisfy residential electric loads was analyzed. The solar-driven system was designed to provide a fraction of the total electricity demand in a complementary operation with the electric grid. The analysis was conducted for an coperation during seven days each season, considering real solar and climate variables and residential loads at different climate zones in the United States. The efficiency of the system strongly depends on the solar radiation profile and the ambient temperature. Maximum efficiencies of around 9.5% were obtained in the cold and marine climate zones due to the high solar energy input and low heat dissipation temperatures. In these two zones, the system could supply more than 98% of the electricity demand all seasons. At mixed-humid and hot-humid regions, the system supplied around 50% of the electric load in three of the four seasons, but it only supplies about 27% of the electricity needs in the mixed-humid zone during summer and hot-humid zone during winter. The effect of the solar collector field area and the tank volume was also analyzed. In general, larger solar fields positively impact the efficiency. However, the impact of the tank volume varies depending on the solar radiation profile and the load requirements. Average efficiencies for the seven-day operation can be larger than 6% with a proper selection of the solar collector area and tank volume for an Organic Rankine Cycle with a capacity of about 2.6 kW. Finally, an economic analysis of the system was conducted, and the results were compared with a solar PV + battery system of similar capacity. It is expected that the cost for the analyzed solar-thermal system decreases in the coming years with the increased interest on low temperature applications.

14 SOLAR ENERGY↗

DOE OSTI2020

Levelized Cost of Charging Electric Vehicles

This data set includes the levelized cost of charging (LCOC) and lifetime fuel cost savings (LFCS) values as reported in "Levelized Cost of Charging of Electric Vehicles in the United States." Values are reported at the state and national levels for battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). The data set also includes the four annual direct current fast charging (DCFC) station load profiles used to approximate the levelized cost of DCFC charging. Each profile provides 15-min resolved power requirements for one full year. Borlaug, B., Salisbury, S., Gerdes, M., and Muratori, M., Levelized Cost of Charging Electric Vehicles in the United States, Joule (2020), https://doi.org/10.1016/j.joule.2020.05.013.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Levelized Cost of Charging Electric Vehicles

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Stochastic Virtual Battery Modeling of Uncertain Electrical Loads using Variational Autoencoder

Effective utilization of flexible loads for grid services, while satisfying end-user preferences and constraints, requires an accurate estimation of the aggregated predictive flexibility offered by the electrical loads. Recently, there have been efforts to quantify the predictive flexibility of thermostatic loads (e.g. residential air-conditioners, electric water-heaters) using the notion of virtual battery (VB), whose state evolution is governed by a first order dynamics including self-dissipation rate, and power and energy capacities. Identifying the VB model parameters for a collection of thermostatic loads, however, is challenging primarily due to uncertainties and lack of information regarding the end-user behavior, underlying device models and parameters. In this paper, we propose a \textit{variational autoencoder}-based deep learning algorithm to identify the parameters of the VB model. Using available sensors and meters data, the proposed algorithm generates not only point estimates of the VB parameters, but also confidence intervals around those values. Effectiveness of the proposed frameworks is demonstrated on a collection of electric water-heater loads, whose operation is driven by uncertain water usage profiles.

virtual battery, deep learning algorithms↗

NASA NTRS2018

Advanced Stirling Convertor Control Unit Testing at NASA Glenn Research Center in the Radioisotope Power Systems System Integration Laboratory

Future NASA missions could include long-duration flyby, orbital, lander, or rover applications where generating power from sunlight may be limited. Radioisotope power systems (RPSs) provide a dependable power source for missions where inadequate sunlight or operational requirements make other power systems impractical. Over the past 16 years, NASA Glenn Research Center has been supporting the development of RPSs. The advanced Stirling radioisotope generator (ASRG) utilized a pair of advanced Stirling convertors (ASCs). Although flight development of the ASRG has been canceled, much of the technology and hardware continued development and testing to guide future activities. Specifically, a controller for the convertor(s) is an integral part of a Stirling-based RPS. For the ASRG design, the controller maintains stable operation of the convertors, regulates the alternating current produced by the linear alternator of the convertor, provides a specified direct-current output voltage for the spacecraft, and synchronizes the piston motion of the two convertors to minimize vibration as well as manage and maintain operation with a stable piston amplitude and hot-end temperature. It not only provides power to the spacecraft but also must regulate convertor operation to avoid damage to internal components and maintain safe thermal conditions after fueling. Lockheed Martin Coherent Technologies, Inc., has designed, developed, and tested an ASC control unit engineering development unit (ACU EDU) to support this effort. GRC used the ACU EDU as part of its nonnuclear representation of a RPS that also consists of a Dual advanced Stirling convertor simulator (DASCS), and associated support equipment to perform a test in the Radioisotope Power Systems System Integration Laboratory (RSIL). The RSIL was designed and built with flexibility to evaluate hardware utilizing RPS technology. The RSIL provides insight into the electrical interactions between as many as three radioisotope power generators, associated control strategies, and typical electric system loads. The first phase of testing included a DASCS that was developed by Johns Hopkins University Applied Physics Laboratory and simulates the operation and electrical behavior of a pair of ASCs in real time via a combination of hardware and software. Testing included the following spacecraft electrical energy storage configurations: capacitor, battery, and supercapacitor. Testing of the DASCS and ACU in each energy storage configuration included simulation of a typical mission profile and transient voltage and current data during load turnon and turnoff. Testing for these devices also included the initiation of several system faults such as short circuits, electrical bus overvoltage, undervoltage, and a "dead bus" recovery to restore normal power operations. The goal of this testing was to verify operation of the ACU(s) when connected to a spacecraft electrical bus. The results of these tests are presented here.

General↗

NASA NTRS2017

Advanced Stirling Convertor Control Unit Testing at NASA Glenn Research Center in the Radioisotope Power Systems System Integration Laboratory

Future NASA missions could include establishing Lunar or Martian base camps, exploring Jupiters moons and travelling beyond where generating power from sunlight may be limited. Radioisotope Power Systems (RPS) provide a dependable power source for missions where inadequate sunlight or operational requirements make other power systems impractical. Over the past decade, NASA Glenn Research Center (GRC) has been supporting the development of RPSs. The Advanced Stirling Radioisotope Generator (ASRG) utilized a pair of Advanced Stirling Convertors (ASC). While flight development of the ASRG has been cancelled, much of the technology and hardware continued development and testing to guide future activities. Specifically, a controller for the convertor(s) is an integral part of a Stirling-based RPS. For the ASRG design, the controller maintains stable operation of the convertors, regulates the alternating current produced by the linear alternator of the convertor, provides a specified direct current output voltage for the spacecraft, synchronizes the piston motion of the two convertors in order to minimize vibration as well as manage and maintain operation with a stable piston amplitude and hot end temperature. It not only provides power to the spacecraft but also must regulate convertor operation to avoid damage to internal components and maintain safe thermal conditions after fueling. Lockheed Martin Coherent Technologies has designed, developed and tested an Engineering Development Unit (EDU) Advanced Stirling Convertor Control Unit (ACU) to support this effort. GRC used the ACU EDU as part of its non-nuclear representation of a RPS which also consists of a pair of Dual Advanced Stirling Convertor Simulator (DASCS), and associated support equipment to perform a test in the Radioisotope Power Systems System Integration Laboratory (RSIL). The RSIL was designed and built to evaluate hardware utilizing RPS technology. The RSIL provides insight into the electrical interactions between as many as 3 radioisotope power generators, associated control strategies, and typical electric system loads. The first phase of testing included a DASCS which was developed by Johns Hopkins UniversityApplied Physics Laboratory and simulates the operation and electrical behavior of a pair of ASCs in real time via a combination of hardware and software. Testing included the following spacecraft electrical energy storage configurations: capacitive, battery, and supercapacitor. Testing of the DASCS and ACU in each energy storage configuration included simulation of a typical mission profile, and transient voltage and current data during load turn-on/turn-off. Testing for these devices also included the initiation of several system faults such as short circuits, electrical bus over-voltage, under-voltage and a dead bus recovery to restore normal power operations. The goal of this testing was to verify operation of the ACU(s) when connected to a spacecraft electrical bus.

Dugala, Gina M.↗

DOE OSTI2025

Monitoring Home Electrical Power Consumption Patterns Using Secondary Wireless Meters

This report presents analysis of high-temporal-resolution whole-house electrical consumption data obtained from 17 residential buildings located in the Denver metro and Aspen regions of Colorado as well as survey data collected from the participants related to building characteristics and equipment types.

14 SOLAR ENERGY↗

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 OSTI2025

Backup power or bill savings? How electricity tariffs impact residential solar-plus-storage usage in the United States

Adoption of paired solar-plus-storage systems has accelerated in recent years, driven by both the demand for backup power and a desire to manage utility bills. Tradeoffs between those two uses can arise through the reserve setting on the battery storage system, which serves to maintain a minimum state of charge in case of a power interruption. Our paper applies an economic framework to evaluate this tradeoff in terms of changes in bill savings and customer reliability value across reserve levels, considering how those tradeoffs depend on the underlying electricity rate structure and levels. The analysis is based on a representative set of load profiles, solar profiles, tariff designs, and stochastic power interruption events across ten different regions in the United States. We find that the opportunity cost of holding storage capacity in reserve, in terms of foregone bill reductions, outweighs any gains in reliability value from mitigated power interruptions in the majority of customer situations. Higher storage reserve levels increase total customer value only in specific circumstances, such as for customers with inferior reliability (10x average interruptions), with a very high value of lost load ($50/kWh), and with tariff or interconnection rules that disallow grid charging. However, even this result is dampened when considering tariff designs with higher price differentials that increase the opportunity cost of holding storage in reserve (e.g. import/export or time-of-use rates). Allowing grid charging in tariffs essentially eliminates the necessity to hold any storage in reserve in all sensitivity cases explored.

Electric resilience↗