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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hillsborough County Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. Hillsborough County used the Clear Sky Decision Support Toolkit to analyze solar + storage as an additional resiliency feature at its Brandon Support Operation Complex (BSOC). During normal operations, the BSOC houses water utility administration services and workspaces for water and wastewater engineers, facilities maintenance, and environmental management staff. During emergency management activation, the BSOC serves as an emergency hub for Emergency Support Function 3 (ESF-3), which includes public utilities, public works, and engineering staff support members. The BSOC is designated as a critical facility by the County.

14 SOLAR ENERGY↗
DOE OSTI2021

Parcel-Scale Assessment of Rooftop Solar Technical Potential

Understanding the potential for rooftop solar and other distributed energy resources (DERs) to contribute to power system planning is increasingly relevant for cities, utilities, and other planning entities. Such planning efforts typically require an estimate of technical potential, or the feasible technology potential independent of economic considerations. Currently, best-in-class rooftop solar technical potential methods use Light Detection and Ranging (LiDAR) data which can identify each roof plane tilt, azimuth, and unshaded area. However, LiDAR data is not universally available and, even when available, obtaining and processing this data can be expensive. In contrast, parcel-level data is easy to use and widely available as it is generated by jurisdictions to levy property taxes. Such data universally reports building footprint area, which is highly correlated with roof area suitable (developable) for rooftop solar. Moreover, parcel data identifies building end-use, tenure, and other building characteristics not provided by LiDAR. To explore the feasibility of using parcel data to assess technical potential more broadly, we compare estimates using parcel data in Orlando, Florida (HIFLD 2020) to those generated using LiDAR data (Koebrich et al. 2021). We find that the parcel-based method results in accurate technical potential estimates at a block and city-scale, though only after accounting for shading and other factors that derate developable roof area. The results of this study demonstrate a scalable, low-effort approach to assess rooftop solar technical potential for every city and community in the U.S.

census blocks↗
DOE OSTI2025

Assessment of Climate Change Impacts on Renewable Energy Resources in Western North America

We examine a 25 km resolution climate model dataset to evaluate how regional climate change impacts solar and wind energy under a high-emission scenario. Our study considers the Western Electricity Coordinating Council (WECC) region, which covers the western United States and southwestern Canada, focusing specifically on locations with existing solar and wind infrastructure. First, we conduct a historical model comparison of solar and wind energy capacity factors to highlight model uncertainties across the study area. Using future climate projections, we then assess the seasonal patterns of solar and wind capacity factors for three timeframes: historical, mid-century, and end of century. Additionally, we estimate the frequency of solar and wind resource droughts during these periods for the entire WECC and its five operational subregions, finding that certain subregions are more susceptible to energy droughts due to limited renewable resources. Finally, we present day-ahead capacity factor forecasts to support energy storage planning and provide estimates of offshore wind energy capacity within the WECC. Our results indicate that offshore wind capacity factors are nearly twice as high as onshore values, with less seasonal variation, which suggests that offshore wind could offer a more consistent renewable energy supply in the future.

climate change↗
DOE OSTI2021

The Renewable Energy Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling

The Renewable Energy Potential (reV) model is a platform for detailed assessment of renewable energy (RE) resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP) and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for assessment of resource potential, technical potential and supply curves at varying levels of detail. The platform runs on NREL's High Performance Computing system, providing scalable and efficient performance from a single location all the way up to continental scales, for a single year or decades of time series resource data. Coupled with NREL's System Advisor Model (SAM), reV supports resource assessment from 5-minute to hourly temporal resolution and provides for analysis of long-term (i.e., year-on-year) variability of RE generation (e.g., interannual variability and exceedance probabilities). Technical potential is measured as a function of resource potential and limitations put on developable land area defined by the user. For example, the user can limit development by land ownership, terrain, land use/cover, and urban areas, as well as custom inputs. Technology, grid interconnection and operation costs, based on the latest market data and future projections, are also embedded in the model. The supply curve module is a spatial sorting algorithm based on plant siting, grid interconnection cost, and regional competition, which provides a geographically discrete estimate of levelized cost of electricity (LCOE) and supply (i.e., capacity) for specific renewable technologies. The reV model currently provides broad coverage across North America, South and Central Asia, South America and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.

13 HYDRO ENERGY↗
DOE OSTI2020

reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]

The Renewable Energy Potential (reV) model is a platform for the detailed assessment of renewable energy resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP), and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for the assessment of resource potential, technical potential, and supply curves at varying levels of detail. The platform runs on the National Renewable Energy Laboratory’s (NREL’s) high-performance computing system, providing scalable and efficient performance from a single location up to a continent, for a single year or decades of time-series resource data. Coupled with NREL’s System Advisor Model (SAM), reV supports resource assessments from 5-minute to hourly temporal resolutions and supports the analysis of long-term (i.e., year-on-year) variability of renewable generation (e.g., interannual variability and exceedance probabilities).

Maclaurin, Galen↗
DOE OSTI2022

Hydro-battery Hybrids – A Case for Holistic Assessment of Hybrid Energy Systems

With increasing penetration of renewable energy resources like solar and wind, the flexibility offered by the hydropower generation facilities would be instrumental in providing grid reliability. However, hydropower’s capabilities are often constrained to meet asset management targets and environmental flow requirements. To meet these necessary requisites while simultaneously being able to utilize hydropower’s full potential, hydro plus battery hybrids offer a logical solution. However it is often challenging to make the case for economic feasibility of hydro-battery hybrids at the required scale of battery storage. To that end, this paper proposes a multi-objective optimization framework to maximize advantages of hydro-battery hybrid systems from three different avenues: new market opportunities, environmental benefits and machine wear and fatigue. Using an illustrative case study of a peaking plant, we simulate hydropower operations for with and without 120 MWh of battery storage for four different simulated flow patterns ranging from peaking operations to run-of-the-river operations and two intermediate flow patterns in between. The results demonstrate that hybridizing the hydropower plant can potentially generate additional revenue while simultaneously enable more environmental friendly operations and reduce the overall machine wear and tear.

Chalishazar, Vishvas H.↗
DOE OSTI2020

Energy Options Analysis Project (Final Report)

This Bear River Band of Rohnerville Rancheria (BRB) Energy Options Analysis Project provides a rigorous and comprehensive near-term renewable energy implementation plan that aligns with the BRB’s long term strategic vision of “zero net annual utility energy consumption.” Final recommendations were arrived at by following four key project phases:A gas and electricity load assessment was conducted for all existing buildings using historic consumption data, and projected loads of new or anticipated buildings using building designs. A renewable energy resource assessment was conducted that estimated the gross generation potential of solar and wind, constrained to areas that could potentially be developed. Other renewable generation technologies were not considered feasible to meet the loads of the BRB. Demand-side efficiency and fuel switching opportunities were identified that can reduce electrical and gas consumption. These opportunities were not integrated into the load assessment in order to provide a conservative implementation plan, but are recommended to be pursued in order to cost-optimize projects during a feasibility assessment. A strategic vision advisory committee was organized and consulted when iterating on the viability of possible projects. These project phases resulted in finalizing the following three solar PV projects for the near term, which also lay the foundation for a future community-scale or multiple-facility microgrid for added resiliency. Additional solar PV on the hillside south of the Tish-Non Community Center. Solar plus battery storage microgrid at the Pump & Play fuel station. Solar PV at the Casino.

14 SOLAR ENERGY↗
DOE OSTI2022

Insights into Methodologies and Operational Details of Resource Adequacy Assessment: A Case Study with Application to a Broader Flexibility Framework

Assessing and maintaining resource adequacy (RA) is a core pillar of power systems. However, recent changes in the physical makeup of these systems and the conditions under which these systems must operate have yielded a renewed interest in the methods, metrics, and assumptions that underpin RA assessments. In this paper, we systematically explore a wide range of RA modeling dimensions, including: the objective function and level of operational detail in the underlying model formulation; the quantity (look-ahead) and quality (accuracy) of data that is available for making operational decisions within those models; and the physical configuration of solar photovoltaics (PV) with battery storage hybrid resources. We apply a set of probabilistic RA tools and production cost modeling tools to a realistic test system based loosely on a future Electric Reliability Council of Texas power system dominated by solar PV resources. Under the assumptions of our system and models, we find that multi-stage probabilistic assessments may provide a more robust evaluation of RA by capturing a wider range of operational and system interactions, but this comes at a computational cost of 1-2 orders of magnitude longer run time depending on the specific configuration. In addition, the information on thermal generator availability impacts RA performance by an order of magnitude more than solar resource forecasts, which is driven by the comparatively larger magnitude of thermal outages than solar forecast errors within our test system. Lastly, the flexibility provided by hybrid and other resources can help reduce system load-shedding event frequencies and enable the system to be more robust to inaccurate forecast information, and alternative hybrid inverter sizes can impact RA levels by 1-2 orders of magnitude. Our results point to the importance of a broader flexibility framework to describe the interaction between (1) flexibility "supply" from both physical resource capabilities and operational constraints considered in the modeling, and (2) flexibility "demand" from forecast errors, thermal generator outages, and other sources of uncertainty, as well as their RA impacts. Results are likely sensitive to the system buildout explored; future work could consider additional system configurations and conditions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2023

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Enhancing building resilience in cold climates: Integrating heat pump technologies with renewable energy

As electrification advances and Cold Climate Heat Pump technology progresses, ensuring grid stability becomes increasingly critical for effective heating in cold climates. However, natural disasters, especially during winter, pose significant threats to grid stability, impacting the reliability of air-source heat pumps. Despite these challenges, the integration of renewable energy sources and storage solutions in heating systems has not been extensively studied within the context of resilience. Here, this paper delves into the literature on renewable-powered heat pumps to assess their potential in enhancing building resilience in U.S. cold climate zones, which are particularly susceptible to extreme weather and grid disruptions. By leveraging renewable sources—solar, geothermal, and water—in conjunction with heat pump technology and supported by thermal or battery storage, this approach aims to provide a dependable solution for maintaining indoor heating during grid failures. Our analysis begins with a review of various renewable energy sources suitable for heat pumps, followed by an exploration of their application in cold climate regions across the U.S., and discussions on potential integration strategies with heat pump systems. This study highlights the advantages and suitability of solar irradiance and geothermal resources, emphasizing the importance of tailored, site-specific assessments to maximize energy efficiency and resilience. Additionally, it outlines the economic and environmental considerations necessary for implementing such systems and identifies potential challenges and areas for future research to facilitate the broader integration of renewable energy in heating solutions for enhanced resilience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Model Formulations: Integrating Distributed Energy Resources (DER) using Advanced Unit Commitment Models and DER Aggregation Methodologies

A distribution energy resource aggregator (DERA) constitutes a group of distribution energy resources with small generation capacities which meet the threshold to participate in the electricity wholesale market. This document provides the proposed DERA model formulation that will be implemented in the SCUC simulation’s architecture for the SCUC-DER project. Different economical assessment methodologies have been developed to incorporated bids for individual distributed resources, which include solar cost dispatch and cost model, BESS opportunity cost offer algorithm, and price sensitive demand response model. Detailed methods are proposed to aggregate individual cost offers to a DERA cost curve to bid in SCUC market while three methods are proposed to simulate DER actual dispatch. Based on the DERA models in this document, the SCUC-DER project will be able to assess the impacts of DERA on the distribution system’s operation and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

American-Made Solar Prize: Edgeli Enables DER Integration (CRADA 615) (Final Report)

The purpose of this project was to demonstrate how granular time series data and automated data transformation, and impact assessment tools could speed interconnection approvals for distributed energy resource projects of various types and sizes. Types included community solar, rooftop solar, and EV charging projects. Using software routines to automate the transformation of data (e.g. GIS) to a network database and power flow model then applying scenarios to create hourly (8760) hosting capacity values and voltage and thermal impacts for specific projects, we were able to demonstrate the feasibility of quickly assembling and analyzing key utility data sets for interconnection purposes. The outcomes of this effort will become the foundation for future work that will enhance and encapsulate the software components developed as part of this project, into web services (e.g. APIs) that can be integrated into queue management systems and automate interconnection screening processes.

14 SOLAR ENERGY↗
DOE OSTI2025

Data for "Implications of Zoning Ordinances for Rural Utility-Scale Solar Deployment and Power System Decarbonization in the Great Lakes Region".

This dataset includes the Energy Zoning Database and geographic shapefiles used to identify suitable rural areas for utility-scale solar development. Additionally, it contains the input data required for the capacity expansion model, including information on existing electric generators and their associated costs, solar resource potential, and transmission infrastructure data. These datasets collectively support the analysis presented in the paper, ensuring a comprehensive assessment of zoning regulations, land suitability, and the economic and technical feasibility of solar deployment in rural areas.

Owusu-Obeng, Papa Yaw (ORCID:0000000334385183)↗
DOE OSTI2025

Makah Tribe Strategic Energy Plan

The U.S. Department of Energy’s (DOE) Energy Transitions Initiative Partnership Project (ETIPP) connects remote and island communities, regional partners, and the DOE national laboratories to support communities as they seek to build resilience in their energy systems. The Makah Tribe faces several energy challenges, including frequent power outages and the potential for an extended outage due to an earthquake or tsunami. The Tribe joined ETIPP in 2022 to address those challenges, seeking to build energy resilience and sovereignty in the community. The Makah Tribe, Spark Northwest, the Pacific Northwest National Laboratory (PNNL), and the National Renewable Energy Laboratory (NREL) collaborated to develop a strategic energy plan as part of the second cohort of ETIPP communities. The long-term energy vision of the Makah Tribe includes increasing energy efficiency in the community, improving energy management capacity, and developing the renewable energy generation and storage sufficient to independently power the Reservation for one year. Additionally, the ETIPP team worked with Makah leadership, staff, and community members to identify a set of community priorities, values, and goals to guide energy development as the Tribe takes the incremental steps toward their vision for energy sovereignty. Those energy values include ecosystem-based management, energy sovereignty and project ownership, workforce development and capacity, economic opportunity, community wellbeing and priorities, and emergency disaster resilience. To understand what would be needed for a year for energy independence, the PNNL team conducted an assessment to determine the current energy usage of the Tribe and also modeled several scenarios for future energy use. Using the energy usage values, the team estimated how two types of renewable energy technology, specifically locally deployed solar and small-scale wind, could contribute towards the energy independence goal. The energy baseline and resource assessment produced the following key findings:

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis

This paper examines the impacts of design, operational, and end-of-life (EOL) waste pathways’ parameters on material circularity in silicon solar photovoltaic (PV) modules. Dynamic material flow analysis (DMFA) quantifies time-series material flows through systems’ life cycle stages to identify hotspots of waste generation, estimate resource needs in the future, and guide sustainable material management. We introduce a DMFA framework based on U.S. electricity demand for the period 2000-2100 to assess stocks and flows of bulk PV materials (i.e., solar glass and aluminum frames). We apply the model to a range of scenarios to understand how material demands depend on selected PV-related parameters, different material circularity strategies, and recent module design trends (e.g., bifacials, large-format-high power modules). Our results enable advanced planning for future materials needs and provide insight into potential opportunities to minimize material waste.

circular economy↗