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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 OSTI2023

Exploring for Superhot Geothermal Targets in Magmatic Settings: 2022 Field Campaign at Newberry Volcano

This paper presents preliminary results from a subset of work carried out as part of a multinational research project entitled DErisking Exploration for multiple geothermal Plays in magmatic ENvironments (DEEPEN), supported by the U.S. Department of Energy (DOE) and Geothermica, a joint effort by EU member states and associated countries. The DEEPEN project will develop a customized approach to exploration for supercritical and superhot geothermal plays in magmatic systems, which will be applied to two demonstration sites. This paper summarizes field activities carried out at the U.S. demonstration site, Newberry Volcano in central Oregon. The objective of this work effort is to refine the subsurface model of Newberry Volcano, with special focus on deeper zones including the magmatic plumbing system and other key geologic elements. New data collection included gravity and wideband magnetotelluric (MT) surveys, as well as reinstallation of a seismic network. The National Renewable Energy Laboratory (NREL) and Enthalpion Energy LLC (Enthalpion) worked with the Deschutes National Forest Fort Rock District to use a low ground disturbance method of MT deployment to collect MT data inside the caldera and other restricted areas inside the National Volcanic Monument. This opened these areas to geophysical exploration for the first time in decades. Sites along and adjacent to the south rim of the volcano constituted the primary survey objectives. A team from Lawrence Berkeley National Laboratory (LBNL), the U.S. Geological Survey (USGS), and AltaRock also began the process of reinstalling the seismic network from the AltaRock enhanced geothermal system (EGS) demonstration in anticipation of further development activities at the site. The data ingestion, reduction, and analysis phase of the project is ongoing. We are currently processing the MT and gravity data and are developing a new, highly GPU-accelerated, 3D joint MT and gravity inversion to better localize the south rim/south flank conductive target and better understand its relationship to deep heat, fluid sources, and surface extrusive features. Joint inversions, which have not yet been undertaken at Newberry, will allow us to obtain constraints on the geologic model that cannot be determined from each method in isolation, improving our ability to image key geologic features at depth.

geophysics↗

DOE OSTI2024

Design of Zone-Based Hierarchical Protection System for 100% Renewable Microgrids

Design of a reliable and secure protection system for a 100% renewable microgrid with only inverter-based resources (IBRs), is quite challenging. Most of the existing protection schemes in the state-of-the-art are suitable for microgrids with mixed-type of distributed energy resources (DERs) that covers both rotating machine-based DERs as well as IBR-based DERs, where the fault current level is moderately high. Due to drastic reduction in fault current level based on mode of operation and the variation of the low fault current level based on the operating level of the IBRs, the existing protection schemes face critical challenges, in case of a 100% renewable microgrid. This article proposes a zone-based hierarchical protection scheme that partitions a microgrid into various zones-of-protection and assigns speed-based hierarchical protection schemes in order to address the fundamental challenges of such microgrids. The performance of the proposed scheme is evaluated using time-domain simulation study on a microgrid test system. The results corroborates that the proposed hierarchical zone-based protection scheme exhibits enhanced reliability, security and dependability while tested with various fault cases (fault types, locations, and impedances), and non-fault cases during both grid-tied and islanded mode.

grid-forming inverter↗

DOE OSTI2022

Activating Opportunity Zones for Rapid Solar+Storage Deployment in Low Income Communities (Final Report)

Millions of Texans choose their own power provider, giving them the option to have low-cost and even renewable energy delivered through their retail electric plan. However, Texans with less disposable income often pay more for electricity and have limited access to green energy and emergency backup power even though the costs of solar and wind power are at record lows and continue to decline. The Powered for Good initiative aimed to help deliver clean, affordable, 100% renewable electricity to low-income households in Texas’s Competitive Retail Areas, where households can choose their electricity provider. Objectives: The primary goal of this project was to develop and validate one or more affordable solar+storage products (i.e., priced less than of $0.14/kWh) that Retail Electricity Providers (REP) can offer to LI households. The team achieved three objectives: 1. Investigate how to best reduce electricity costs and increase availability of emergency power for LI customers; 2. Build momentum for, and facilitate an approach to, a Texas-based pilot deployment of such solar+storage products, with a goal of greatly expanding this approach to a large segment of the LI population in Texas; 3. Provide the structural framework, finance model, and roadmap to potentially increase investment of solar+storage projects in LI communities across U.S. states when modified to meet their state-specific laws and regulations. The team evaluated the market of viable solutions for low-income Texans through interviews and focus groups with professionals and residents with lived experience. The team then piloted a low-cost retail electric product. Following the pilot, the team developed educational materials, including fact sheets, a Go Green Save Green interactive guide, and an Electricity Bill Analysis Tool. The team is now working to increase power resilience and reduce energy insecurity with micro solar and storage in partnership with local entities in the Harris County area. Key Findings: Informed by Powered for Good research, including the experiences on Texas residents and electricity system experts, the Powered for Good team developed a pilot that was implemented by Energy Well Texas, a new company formed in late 2020. The pilot featured a combination of a 100% clean residential energy offering delivered through the electrical grid plus a selection of batteries, lights and a solar panel that provided participants with varying levels of backup power. For the 8 customers who submitted previous bills, the Energy Well Texas pilot reduced energy bills by about 30%. In Houston, residents earning less than 30% of Area median Income (AMI) spend an average 13% of their income on energy or about $1,555 per year. Repeating the pilot results for these residents could yield $466 in savings per customer or about 4% of their income. While this will not end energy poverty, it is a big step toward that goal. The Powered for Good and Energy Well Texas teams are currently planning their post-pilot phase of service offerings.

14 SOLAR ENERGY↗

DOE OSTI2024

Design of Zone-Based Hierarchical Protection System for 100% Renewable Microgrids: Preprint

grid-forming inverter↗

DOE OSTI2023

A reduced-order modeling of a tubular solar reactor for long duration thermochemical energy storage

The storage of solar energy in a solid form, referred to as a “solar fuel”, can be achieved through a process known as endothermic solar thermochemistry. This process transforms the absorbed solar energy into a stable and retrievable form that can be stored for extended periods of time. This paper presents a low–order heat transfer model of a counter–current tubular falling bed reactor designed to produce thermally reduced magnesium manganese oxide pellets for long duration thermochemical energy storage. The energy required for the endothermic reduction was supplied by concentrated solar energy or renewable electricity via indirect heating of the gas and solid reactants flowing in a ceramic tube. The counter-current gas flow enhances the mixing of the solid particles with the heat recuperation zone, allowing the gas and particles to enter and exit the tubular reactor close to room temperature. Further, the reactor was vertically oriented and was heated circumferentially by an adjustable level heat flux along a finite segment of its length. The temperature distribution of the reactor in response to transient changes along the tube was modeled by considering conduction, convection, and radiation heat transfer. Governing equations for the heat transfer model were solved by discretizing the reactor tube into a finite number of control volumes and using an energy balance for the heat exchange between the reactor wall, gas, and particles within the control volume. The energy absorbed during this endothermic reaction was modeled numerically by fitting the data of the chemical conversion rate with the corresponding temperature of particles in the heating zone. The numerical model has been experimentally validated using a reactor prototype made of a 121.92 cm alumina tube heated by a 7kW electric tube–furnace. The alumina tube receives magnesium manganese oxide pellets of 3.66±0.516 mm in diameter from the top, and a counter–current gas flow from the bottom. The reactor wall temperature was monitored by six thermocouples installed along the reactor tube length. The experimental procedure was numerically simulated, and the temperature variation along the reactor tube was compared with a matrix of experimental runs for a range of particles mass flowrates (0.75–1.25g/s) and corresponding gas flowrates (36–65 SLPM). The reactor system was heated gradually from room temperature to a steady state temperature of 1673K, and then cooled down to room temperature. The heating and cooling processes were simulated, and the numerical and experimental results were compared throughout processes. The numerical model showed similar trends to the experimental results, with an error of 0.69 to 7.9% for the particle inlet and 0.7 to 7.9% for the gas inlet during steady-state operation. The proposed numerical model can be implemented as a simplified physical model to design a feedback control system to regulate reactor temperature.

14 SOLAR ENERGY↗

NASA NTRS2006

Phase II Testing of Liquid Cooling Garments Using a Sweating Manikin, Controlled by a Human Physiological Model

An Advanced Automotive Manikin (ADAM) developed at the National Renewable Energy Laboratory (NREL) is used to evaluate NASA's liquid cooling garments (LCGs) used in advanced space suits for extravehicular applications. The manikin has 120 separate heated/sweating zones and is controlled by a finite element physiological model of the human thermoregulatory system. Previous testing showed the thermal sensation and comfort followed the expected trends as the LCG inlet fluid temperature was changed. The Phase II test data demonstrates the repeatability of ADAM by retesting the baseline LCG. Skin and core temperature predictions using ADAM in an LCG/Arctic suit combination are compared to NASA physiological data to validate the manikin/model. Additional LCG configurations are assessed using the manikin and compared to the baseline LCG. Results can extend to other personal protective clothing, including HAZMAT suits, nuclear/biological/chemical protective suits, and fire protection suits.

Paul, Heather↗

NASA NTRS2011

Downscaling NASA Climatological Data to Produce Detailed Climate Zone Maps

The design of energy efficient sustainable buildings is heavily dependent on accurate long-term and near real-time local weather data. To varying degrees the current meteorological networks over the globe have been used to provide these data albeit often from sites far removed from the desired location. The national need is for access to weather and solar resource data accurate enough to use to develop preliminary building designs within a short proposal time limit, usually within 60 days. The NASA Prediction Of Worldwide Energy Resource (POWER) project was established by NASA to provide industry friendly access to globally distributed solar and meteorological data. As a result, the POWER web site (power.larc.nasa.gov) now provides global information on many renewable energy parameters and several buildings-related items but at a relatively coarse resolution. This paper describes a method of downscaling NASA atmospheric assimilation model results to higher resolution and maps those parameters to produce building climate zone maps using estimates of temperature and precipitation. The distribution of climate zones for North America with an emphasis on the Pacific Northwest for just one year shows very good correspondence to the currently defined distribution. The method has the potential to provide a consistent procedure for deriving climate zone information on a global basis that can be assessed for variability and updated more regularly.

Chandler, William S.↗

DOE OSTI2025

Optimizing district energy systems under uncertainty: Insights from a case study from Washington D.C., USA

This study investigates solutions for delivering affordable heating and cooling to a brownfield site, focusing on a case study in Washington, DC. Moving towards more diverse and resilient energy systems, we identify the optimal portfolio for a district energy system with diverse energy sources to meet the area’s energy demands. Our methodological approach integrates two detailed models: one calculating building-level energy demand and the other optimizing district energy technology choices based on their demand profiles, accounting for uncertainties in energy prices, policies, and other parameters. The results provide an economic comparison of district and individual supply options at the building level, emphasizing the flexibility district systems can offer to the electricity sector. District energy systems demonstrate cost-stabilization benefits amidst volatile energy prices and external uncertainties. For heating, district systems yield significant cost savings compared to individual solutions, driven by fuel flexibility and the use of local renewable energy sources. For cooling, district systems also show advantages, though individual systems may remain more cost-effective for smaller buildings. Additionally, district systems exhibit considerable flexibility on the heating side, as evidenced by variations in electricity consumption. We recommend future research to explore the relationship between the economics of district energy systems, particularly at the building level, and their flexibility potential for the electricity sector across diverse geographic contexts to reduce overall grid costs and promote grid reliability. This includes areas with distinct zoning laws, municipal priorities, utility structures, and funding mechanisms, such as the United States, and regions like Europe with pronounced electricity price volatility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Solar and Battery Storage Permitting and Siting Requirements - Solar Prize Round 7 (CRADA Final Report)

The purpose of this project is to identify local zoning ordinances, state permitting requirements, federal regulatory bottlenecks throughout the development process, and the potential to use Large Language Models (LLM) and aggregate permitting and interconnection data for commercial and industrial (C&I), community, and utility-scale solar photovoltaic (PV) and battery storage projects.

14 SOLAR ENERGY↗

DOE OSTI2025

Adsorption of REEs to Kaolinite via Ion Exchange and Surface Complexation as a Function of Water Chemistry

Rare earth elements (REEs) are critical components of modern technology behind renewable energy, transportation, and electronics but have a limited current supply. A substantial portion of global REE production relies on ion adsorption deposits. A high abundance of kaolinite in REE enrichment zones within these deposits suggests that kaolinite controls the subsurface migration of REEs. This study aimed to improve the current understanding of REE binding to kaolinite under varying water chemistry conditions. We conducted batch experiments with kaolinite (KGa-2) and three REEs (Nd, Dy, and Yb) at varying pH, electrolyte concentration, dissolved inorganic carbon (DIC), low molecular weight organic acids (citric and oxalic acids), and total REE concentration conditions. Increasing electrolyte concentration inhibits REE adsorption at pH < 7, suggesting that ion exchange contributes to adsorption at these pH values. DIC affects adsorption above pH 7–8 by forming strong aqueous complexes with heavy REEs. Citric acid decreases REE adsorption via aqueous complexation of REEs at pH > 5 but does not affect adsorption at pH < 5. The surface complexation model captures the main adsorption trends with two mechanisms: ion exchange on basal planes at pH < ∼6 and inner-sphere surface complexation to edge sites at pH > ∼6. Equilibrium constants for surface complexation increase in the order of Yb > Dy > Nd, indicating a higher strength of adsorption for heavy REEs. This study demonstrates how water chemistry conditions control the adsorption mechanisms that may determine the mobility of REEs in subsurface environments rich in kaolinite.

58 GEOSCIENCES↗

DOE OSTI2025

Adsorption of Rare Earth Elements to Kaolinite [dataset]

Rare earth elements (REEs) are critical components of modern technology behind renewable energy, transportation, and electronics but have a limited current supply. A substantial portion of global REE production relies on ion adsorption deposits. A high abundance of kaolinite in REE enrichment zones within these deposits suggests that kaolinite controls the subsurface migration of REEs. This study aimed to improve the current understanding of REE binding to kaolinite under varying water chemistry conditions. We conducted batch experiments with kaolinite (KGa-2) and three REEs (Nd, Dy, and Yb) at varying pH, electrolyte concentration, dissolved inorganic carbon (DIC), low molecular weight organic acids (citric and oxalic acids), and total REE concentration conditions. Increasing electrolyte concentration inhibits REE adsorption at pH 7, suggesting that ion exchange contributes to adsorption at these pH values. DIC affects adsorption above pH 7−8 by forming strong aqueous complexes with heavy REEs. Citric acid decreases REE adsorption via aqueous complexation of REEs at pH 5 but does not affect adsorption at pH 5. The surface complexation model captures the main adsorption trends with two mechanisms: ion exchange on basal planes at pH ∼6 and inner-sphere surface complexation to edge sites at pH ∼6. Equilibrium constants for surface complexation increase in the order of Yb Dy Nd, indicating a higher strength of adsorption for heavy REEs. This study demonstrates how water chemistry conditions control the adsorption mechanisms that may determine the mobility of REEs in subsurface environments rich in kaolinite.

58 GEOSCIENCES↗

NASA NTRS2019

Renewable Energy Contingencies in Power Systems: Concept and Case Study

This paper introduces the concept of renewable energy contingencies that represent long-term/extended variability of variable renewable energy (VRE) resources, namely, significant periods (e.g., days/weeks) of low wind/solar availability. These contingencies have not received much attention to date but are likely to emerge as a major issue in some countries such as India as the share of VRE increases. Using 38 years of climate model reanalysis data for wind over India, we demonstrate that low periods of wind contingency below long-term (Indian) national average of 5 m/s can extend for more than 100 days in several zones some of which are deploying large wind farms. Even in some of the best wind resource areas in India with long term average wind speed close to 7 m/s, low wind days (e.g., 5 m/s which is substantially below average) can extend up to 60 days. We propose a four-step methodology around a co-optimization based energy-ancillary services dispatch model to assess the impact of renewable contingency and implemented it for the state of Tamil Nadu, the most wind-rich state of India. We have estimated that annual renewable contingency cost impact of 5 GW additional wind in Tamil Nadu to be in the range of US$27-76 million pa. Planning analysis should embrace the concept of renewable contingency to recognize these costs and put in place necessary spinning reserve and back-up generation resources.

Mohar Chattopadhyay↗

DOE OSTI2025

Modeling receiver flux of commercial power tower concentrating solar power plants using ray tracing: a round-robin comparison of SolTrace, Solstice, and TieSOL

This study presents a multi-stage, cross-validation comparison of three software packages for Monte Carlo ray tracing (MCRT) applied to central tower concentrating solar power (CSP) systems. The three packages evaluated are: (1) SolTrace, an open-source tool developed by the National Renewable Energy Laboratory (NREL); (2) Solstice, an open-source program created by CNRS-PROMES and Meso-Star, with enhancements for CSP applications (called solsticepy) from the Australian National University; and (3) TieSOL, a commercial software developed by Tietronix. This investigation extends previous ray tracing comparisons by incorporating models of multi-facet heliostats within a commercial-scale solar field, taking into account zoned focal lengths and canting configurations. Receiver flux distributions were compared across the tools using a series of case studies, including single-heliostat scenarios, isolated blocking situations, and comprehensive full-field simulations. The case studies were designed to diagnose differences across the models at varying levels of complexity, and to identify and resolve discrepancies as additional parameters were introduced. Key factors examined in the analysis include sun positions, heliostat location, facet and canting focus, and aimpoint strategies. The comparison aims to improve the accuracy and reliability of these tools while providing benchmark cases for validating future optical modeling tools.

14 SOLAR ENERGY↗

DOE OSTI2023

Regional Carbon Emission Reduction Prediction via Retrofits of Commercial Buildings with a Case Study of US School Buildings in Hot Climates

Retrofitting commercial buildings has great potential to reduce carbon emissions as demonstrated by previous studies in some specific cities, but their regional carbon emission reduction potential is still unknown. Thus, we develop a method to predict the long-term regional carbon emission reduction potential by retrofitting commercial buildings. School buildings in hot climate zones in the continental U.S. are selected as an example. The results show that the aggregated carbon emission reduction potential of school buildings in that region reduces from 3.33 to 2.01 megatons from 2024 to 2050 due to the increased penetration of renewable energy.

building energy simulation↗

NASA NTRS2013

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

Chandler, William S.↗

NASA NTRSDate not supplied

NASA Power: Global Solar Insolation, Meteorological Parameter Data, and Web Services to Support Sustainable Building Design and Operations

The buildings industry is currently striving to adopt green solutions to make infrastructure more energy-efficient in order to meet the 2050 net-zero climate goals. This planning requires reliable environmental datasets that are crucial in designing, building, and maintaining our world’s-built environment, as well as other energy-related processes and investments. This webinar for the National Institute of Building Sciences provides an overview of NASA’s Prediction Of Worldwide Energy Resources (POWER) Project that informs decision-making and development for sustainable building design and operations by enabling public open discovery, efficient access, and convenient distribution of NASA’s Earth Observations and global atmospheric model datasets. POWER’s datastore is comprised of solar radiation and surface meteorology parameters, spanning nearly 40 years of hourly data, that are easily accessible via several access methods and tools to support three focus areas: 1) renewable energy deployment and management, 2) sustainable infrastructure, and 3) agroclimatology applications. POWER and NASA Earth Science both plan future data parameters, updated tools, and improved observations that could directly support U.S. and international sustainable development goals, climate strategies, and building information modeling. To this end, solar data from several NASA projects and meteorological data from NASA assimilation models have already been reformatted and disseminated to the public via a user-friendly web GIS-enabled based data portal through the POWER Project. POWER data is analysis-ready and accessible through an Application Programming Interface (API), ArcGIS Image Services, and the project’s Data Access Viewer enhanced (DAVe), an interactive online tool. The POWER DAVe also features data consistent with ASHRAE Climate Design Conditions and has developed web image services showing Building Climate Zones and their variability. Through those tools, the data can be downloaded into multiple formats that support the infrastructure community, including CSV and Energy Plus Weather (EPW). POWER’s entire data product catalog is available through Amazon Web Services (AWS) Open Data Registry (ODR) via a free and publicly accessible Simple Storage Service (S3). This webinar provides a full overview of the NASA POWER Project's data and services developed in collaboration with the sustainable infrastructure community. Examples of how the renewable energy and building communities have utilized POWER data products to make decisions and a preview of future data product expansion, including climate projections, and web services will also be provided. Additionally, use case stories from our broad community of users will be presented.

Paul W. Stackhouse↗

DOE OSTI2026

High-Resolution South American Wind Resource Data Downscaled with Generative Machine Learning Conditioned on Near-Surface Observations

High-resolution historical wind data was developed for the entirety of South America using the innovative Super-Resolution for Renewable Resource Data (sup3r) machine learning framework. The publicly available Sup3rWind South America dataset represents a significant advancement in wind resource data generation, leveraging generative machine learning conditioned on near-surface observations from the Meteorological Assimilation Data Ingest System (MADIS) to efficiently and accurately downscale coarse reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). This approach produces fine-scale, spatially and temporally coherent wind and meteorological fields hundreds of times more computationally efficient than traditional numerical weather modeling methods, enabling access to high-fidelity wind information across both continental and offshore regions. Sup3rWind South America builds on the earlier Sup3rWind Ukraine dataset through improvements in model architecture and outputs conditioned on near-surface observation inputs. As with the Ukraine data release, this dataset includes wind speed, wind direction, temperature, relative humidity, and pressure at a horizontal resolution of ~2 km, representing a 15x spatial enhancement relative to the 31 km ERA5 grid. Wind speed and direction are provided at 5-minute resolution, a 12x temporal refinement compared to the hourly ERA5 data, while temperature, relative humidity, and pressure remain at hourly resolution. The data covers all years from 2005 to 2024. Before downscaling, ERA5 inputs were bias-corrected using long-term monthly means and a limited number of quality-controlled observations to align large-scale statistics with regional conditions. The resulting dataset is the first publicly available high-resolution timeseries wind record that provides full spatial coverage of South America. Model validation demonstrates strong agreement with observations across several statistical metrics, consistent with other state-of-the-art high-resolution wind resource datasets. The potential applications of Sup3rWind South America span renewable energy resource assessment, energy system modeling, and grid resilience analysis. The 20-year record and high spatial and temporal resolution support accurate estimation of long-term energy yield and the economic feasibility of potential wind development sites. Continuous coverage across both continental and offshore regions enables comprehensive site prospecting within exclusive economic zones. The 2 km, 5-minute resolution data provide the spatial and temporal variability required for power system simulation, operational planning, and regional risk assessments.

17 WIND ENERGY↗