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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evolution of Electric Sector Water Use Under Alternative Electricity Futures

Increasing competition for water resources in the United States could create future challenges for allocating and using thermal cooling water in the U.S. electric power sector. While thermal power plant retirements and the growth of wind and solar technologies can reduce national aggregate power sector cooling water use, local water constraints and growing demand for agricultural or municipal supply could create greater needs for higher-cost alternative water supplies such as groundwater or recycled wastewater. For some regions, these incentives could change future electricity planning and operational decisions. These relationships and impacts are studied here using the National Renewable Energy Laboratory (NREL) Regional Energy Deployment System (ReEDS), a national electric sector planning model that has recently been upgraded to include a highly detailed representation of thermal cooling water demand and supply. Thermal power technologies are differentiated by both cooling technology and water source type to track and constrain thermal cooling water use in a way that incorporates both physical and legal water considerations in the United States. This capability is exercised under a range of electricity sector futures with alternative technology costs, fuel prices, and water constraints to illustrate ways that U.S. electric sector water use could evolve under uncertain future electric sector drivers. In exploring changes to regional generation and transmission planning and operation, water requirements, and cost, we highlight the environmental and economic impacts of future power sector water decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Structure-performance relationships in lignin-based transesterification vitrimers: The role of lignin structural features

Lignin has been hailed as an ideal renewable alternative for petrochemical-based prepolymers in material synthesis for a sustainable and circular economy, due to its abundant aromatic network and high carbon content. However, the properties and performance of lignin-derived macromolecules are strongly influenced by the lignin itself. While numerous studies have explored the impact of lignin content on the thermomechanical performance of lignin-based vitrimers, literature on how the inherent structural features of lignin affect these properties is scanty. In this study, hardwood organosolv lignin was fractionated in ethyl acetate, ethanol, and acetone to obtain lignin fractions with varying structural characteristics. These fractions were then modified through carboxylation and crosslinked with epoxidized soybean oil (ESO) at a hydroxyl to epoxy group ratio of 1:1 to produce lignin-based transesterification vitrimers (LVs). The thermal properties (i.e. glass transition temperature and thermal stability), tensile strength, storage modulus, and stress relaxation behavior of the LVs were studied and carefully related to the structural features of lignin. The results revealed a positive relationship between strong hydroxyl content in modified lignin and the tensile strength (5.10–9.71 MPa), storage modulus (1099.4 – 1372.8 MPa), crosslinking density, and stress relaxation of the LVs. Additionally, both the storage modulus and tensile strength exhibited a positive relationship with the ratio of rigid linkages in modified lignin, while lignin molecular weight was found to significantly impact the thermal properties of LVs (i.e Tg and thermal stability). This study not only highlights the valorization of lignin in vitrimer synthesis but also provide insights for designing lignin-based materials with tailored properties for specific applications.

Bio-based polymer↗
DOE OSTI2024

Machine learning for the redox potential prediction of molecules in organic redox flow battery

Here, organic redox flow batteries (ORFB) are recognized as an innovative technology for the large-scale storage of renewable energy. The redox potential of organic redox-active molecules plays a vital role in their performance. Advanced screening techniques like high-throughput experiment and machine learning (ML) have significantly enhanced organic material performance and transformed the field of ORFB. However, the scarcity of experimental data poses a considerable challenge for ML model development in this domain. In our study, we developed lightweight graph-based Gaussian process regression (GPR) models with GPU-accelerated marginalized graph kernel and hybrid kernel to predict the redox potentials of organic redox-active molecules for ORFBs, specifically focusing on small datasets. To evaluate model accuracy, we created a new experimental database of organic redox-active molecules by the data from hundreds of published papers and assembled previous computational datasets. We also considered some key parameters, such as pH conditions and solvent type, to assess their impact on redox potential prediction. Our GPR model predicted redox potentials with high accuracy across all datasets using minimal training data. The study provides powerful tools for molecule screening and design and delivers valuable guidance on designing training datasets for costly experiments.

25 ENERGY STORAGE↗
DOE OSTI2021

Compact ammonia reforming at low temperature using catalytic membrane reactors

Ammonia is a leading carrier for the storage and transport of renewable hydrogen, but its deployment requires scalable technologies for efficient decomposition and purification. In this work, we report on the efficient delivery of high purity hydrogen from ammonia decomposition using a catalytic membrane reactor (CMR). Improvements to the electroless plating process reduced the Pd membrane thickness by >35%, resulting in commensurate increases in hydrogen permeance without sacrificing selectivity. To increase throughput a commercial Ru/Al 2 O 3 catalyst was added to the lumen, and the CMR could process ammonia flowrates 10–50 times higher than an equivalent packed bed reactor while maintaining the same level of conversion. It is shown that the earth-abundant zeolite clinoptilolite could reduce ammonia impurities in the permeated H 2 to the levels required by PEM fuel cells (<25 ppb). Performance increased significantly across a >500-h durability test due to improvements in membrane permeability. Finally, the results show that CMRs are a viable technology for distributed production of hydrogen from ammonia.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Reduction of CO to Methanol with Recyclable Organic Hydrides

We report the reaction steps for the selective conversion of a transition metal carbonyl complex to a hydroxymethyl complex that releases methanol upon irradiation with visible light have been successfully quantified in acetonitrile solution with dihydrobenzimidazole organic hydride reductants. Dihydrobenzimidazole reductants have been shown to be inactive toward H 2 generation in the presence of a wide range of proton sources and have been regenerated electrochemically or photochemically. Specifically, the reaction of cis-[Ru(bpy) 2 (CO) 2 ] 2+ (bpy = 2,2'-bipyridine) with one equivalent of a dihydrobenzimidazole quantitatively yields a formyl complex, cis-[Ru(bpy) 2 (CO)(CHO)] + , and the corresponding benzimidazolium on a seconds time scale. Kinetic experiments revealed a first-order dependence on the benzimidazole hydride concentration and an unusually large kinetic isotope effect, inconsistent with direct hydride transfer and more likely to occur by an electron transfer-proton-coupled electron transfer (EΤ-PCET) or related mechanism. Further reduction/protonation of cis-[Ru(bpy) 2 (CO)(CHO)] + with two equivalents of the organic hydride yields the hydroxymethyl complex cis-[Ru(bpy) 2 (CO)(CH 2 OH)] + . Visible light excitation of cis-[Ru(bpy) 2 (CO)(CH 2 OH)] + in the presence of excess organic hydride was shown to yield free methanol. Identification and quantification of methanol as the sole CO reduction product was confirmed by 1 H NMR spectroscopy and gas chromatography. The high selectivity and mild reaction conditions suggest a viable approach for methanol production from CO, and from CO 2 through cascade catalysis, with renewable organic hydrides that bear similarities to Nature's NADPH/NADP + .

14 SOLAR ENERGY↗
DOE OSTI2025

Aluminosilicate-mediated C(sp 2 )–H alkylation of furans using allylic alcohols

Alkyl furans have a variety of applications and therefore numerous approaches exist for their synthesis. While these methods can be effective, there are various drawbacks largely associated with the waste generated. Herein we report a novel method for the direct coupling of readily available furans with allylic alcohols. These include terpenoid alcohols such as geraniol and prenol, which are readily available from renewable, bio-derived feedstocks. Furthermore, the reaction is facilitated using aluminosilicates, including zeolites. It was found that Y-type zeolites were highly effective at mediating the coupling with furan, giving the 2-alkylated furan high yields. While various allylic alcohols were effective for this reaction, the identity of the furan proved to have a drastic impact on reactivity. For substituted furans, the reaction proved most effective with an amorphous aluminosilicate and calculations later revealed potential key factors in further developing and generalizing this methodology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The Highly Integrated Vehicle Ecosystem (HIVE): A Platform for Managing the Operations of On-Demand Vehicle Fleets

This paper introduces the Highly Integrated Vehicle Ecosystem (HIVE), a transportation modeling tool developed by within the Center for Integrated Mobility Sciences (CIMS) group at the National Renewable Energy Laboratory (NREL). HIVE is an agent-based supply/demand model for Mobility on Demand (MoD) which mixes agent-based modeling and centralized dispatch for automated and human-driven fleets and ride hail passengers. Research questions using HIVE span multiple categories, including intelligent fleet planning (assessing fleet, battery, and infrastructure investment decisions), intelligent fleet control (charge management, vehicle dispatching) and strategic business model decision-making (depot-based full-time drivers versus gig-based drivers, human-driven versus automated). The components of the HIVE model are explained and then HIVE is demonstrated in a case study using demand data from the New York City Taxi & Limousine Commission data set.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Application of Machine Learning to Improve Biobased Glucaric Acid Production (CRADA 504)

The Agile Biofoundry (ABF) is a multi-national lab consortium funded by the DOE Bioenergy Technologies Office that has developed a biofoundry that enables the rapid deployment of bioproducts into the market. Working with four ABF laboratory members (National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), Lawrence Berkeley National Laboratory (LBNL), and Argonne National Laboratory (ANL)), Kalion will use advanced high throughput techniques, advanced analytics, and machine learning to optimize the production environment for glucaric acid. Low-cost, high-purity glucaric acid enables products in a wide range of fields to improve the chemical properties of products and applications ranging from water treatment, polymers & textiles, coatings, detergents, and pharmaceuticals. With its broad range of applications, glucaric acid has the potential to demonstrate how such bio-based materials offer great benefit to the US economy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Supporting Growth of a Skilled Workforce in the Building Energy Efficiency Industry (Final Technical Report)

The Interstate Renewable Energy Council (IREC), having worked for well over a decade to develop national networks and best practices focused on attracting and training high quality workers for the clean energy industries, sought to address shortfalls in skilled workers who build, retrofit, operate, and maintain energy efficient buildings. Through this project, IREC created and promoted a Green Buildings Career Map (GBCM)—a career awareness and recruitment tool—that seeks to boost the nationwide growth of workers entering the energy efficiency (EE) industry. Working with a team of subject matter experts and our partner organizations—Building Performance Association (BPA), Building Performance Institute (BPI), Community Action Partnership (CAP), and the National Institute of Building Sciences (NIBS)—IREC produced an interactive, engaging career map to attract and motivate individuals into pursuing careers in energy efficiency, and in support of the Weatherization Assistance Program. The GBCM was designed for a broad audience including educators, career advisors, employers, policymakers, workforce professionals, and jobseekers who may otherwise have little or no awareness of the exciting and rewarding opportunities within targeted industry sectors. Most individuals seeking careers do not know about the breadth of careers awaiting them in the built environment and the same is true for most career and guidance counselors, educators, and parents. The GBCM provides this broad audience with a vision of the myriad jobs that could lead to a long-standing career in energy efficiency. The GBCM describes diverse occupations across the EE industry, charts possible progression between those occupations, and identifies the training, skills, and credentials necessary to do them well.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Properties of Electronic Materials

This final technical report summarizes the research conducted under DOE Grant DE-SC0002623, "Properties of Electronic Materials," led by Principal Investigator Shengbai Zhang at Rensselaer Polytechnic Institute. Over the 16-year period, the project employed first-principles computational methods to investigate the structural, electronic, and dynamic properties of a wide range of electronic materials, with applications in energy technologies, optoelectronics, and data storage. Key areas included topological insulators, phase-change materials, graphene and two-dimensional systems, perovskites for photovoltaics, defect engineering in semiconductors, kagome lattices, and ultrafast carrier dynamics. The research resulted in 115 peer-reviewed publications, advancing fundamental understanding of material behaviors at the atomic scale and contributing to innovations in renewable energy, memory devices, and quantum materials. Findings have implications for improving energy efficiency, developing lead-free solar cells, and enabling high-speed data processing. The work has trained numerous graduate students and postdocs, fostering the next generation of computational materials scientists. The original goals were to develop theoretical models and computational tools to predict and optimize electronic properties of materials for energy applications. All objectives were accomplished, with no major departures from planned methodologies. Challenges in computational scaling were addressed through access to high-performance computing resources.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Review of Nanocarbon-Based Anode Materials for Lithium-Ion Batteries

Renewable and non-renewable energy harvesting and its storage are important components of our everyday economic processes. Lithium-ion batteries (LIBs), with their rechargeable features, high open-circuit voltage, and potential large energy capacities, are one of the ideal alternatives for addressing that endeavor. Despite their widespread use, improving LIBs’ performance, such as increasing energy density demand, stability, and safety, remains a significant problem. The anode is an important component in LIBs and determines battery performance. To achieve high-performance batteries, anode subsystems must have a high capacity for ion intercalation/adsorption, high efficiency during charging and discharging operations, minimal reactivity to the electrolyte, excellent cyclability, and non-toxic operation. Group IV elements (Si, Ge, and Sn), transition-metal oxides, nitrides, sulfides, and transition-metal carbonates have all been tested as LIB anode materials. However, these materials have low rate capability due to weak conductivity, dismal cyclability, and fast capacity fading owing to large volume expansion and severe electrode collapse during the cycle operations. Contrarily, carbon nanostructures (1D, 2D, and 3D) have the potential to be employed as anode materials for LIBs due to their large buffer space and Li-ion conductivity. However, their capacity is limited. Blending these two material types to create a conductive and flexible carbon supporting nanocomposite framework as an anode material for LIBs is regarded as one of the most beneficial techniques for improving stability, conductivity, and capacity. This review begins with a quick overview of LIB operations and performance measurement indexes. It then examines the recently reported synthesis methods of carbon-based nanostructured materials and the effects of their properties on high-performance anode materials for LIBs. These include composites made of 1D, 2D, and 3D nanocarbon structures and much higher Li storage-capacity nanostructured compounds (metals, transitional metal oxides, transition-metal sulfides, and other inorganic materials). The strategies employed to improve anode performance by leveraging the intrinsic features of individual constituents and their structural designs are examined. The review concludes with a summary and an outlook for future advancements in this research field.

25 ENERGY STORAGE↗
DOE OSTI2020

Environmental Permitting and Compliance Cost Reduction Strategies for the MHK Industry: Lessons Learned from Other Industries

The marine and hydrokinetic (MHK) industry plays a vital role in the U.S. clean energy strategy by providing a renewable, domestic energy source that may offset the need for traditional energy sources. The first MHK deployments in the U.S. have incurred very high permitting costs and long timelines for deploying projects, which increases project risk and discourages investment. A key challenge to advancing an economically competitive U.S. MHK industry is reducing the time and cost required for environmental permitting and compliance with government regulations. Other industries such as offshore oil and gas, offshore wind energy, subsea power and data cables, onshore wind energy, and solar energy facilities have all developed more robust permitting and compliance pathways that provide lessons for the MHK industry in the U.S. and may help inform the global consenting process. Based on in-depth review and research into each of the other industries, we describe the environmental permitting pathways, the main environmental concerns and types of monitoring typically associated with them, and factors that appear to have eased environmental permitting and compliance issues.

other industries↗
DOE OSTI2020

A High-resolution Regional Wave Resource Characterization For The U.S. West Coast

Objectives/Scope: Wave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies. Methods, Procedures, Process: The wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP’s Climate Forecast System Reanalysis (CFSR) product. Results, Observations, Conclusions: The standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model’s satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast. Novel/Additive Information: The results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA’s 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.

Wang, Taiping↗
DOE OSTI2024

Development & Experimental Validation of a Generalized Resistance-Capacitance Model for Numerical Simulation of Phase-Change Material Embedded Heat Exchangers

Latent heat thermal energy storage (LHTES) using phase change material (PCM) has attracted increased attention as a viable solution for overcoming the mismatch between energy supply and demand for renewable energy-based systems. PCM-embedded heat exchangers (PCM-HX) have the potential to significantly improve thermal performance due to high storage capacity and low temperature variation during the phase change process. Most models for simulating LHTES heat transfer use Computational Fluid Dynamics (CFD) simulations, which have high computational costs resulting from considering the complex and time-dependent physics relevant to PCM-HXs. In this paper, a Generalized Resistance Capacitance-based Model (GRCM) was developed to predict the thermal performance of arbitrary PCM-HXs in a computationally efficient manner without compromising modeling accuracy. The GRCM is exercised for three case studies: (i) verification for a single-slabbed finned PCM-HX, (ii) verification and validation for a copper foam/paraffin composite PCM-HX, and (iii) validation for a straight tube annular finned PCM-HX. The copper foam PCM-HX uses an electric heater at the top of HX, while the other two configurations utilize water as heat transfer fluid. For the single-slabbed finned PCM-HX melting case, the mean deviation in average PCM temperature predicted by the GRCM compared to the CFD model was between 0.56 – 0.73 K, with maximum temperature deviation of 2.68 K. For the HTF outlet temperature, the validation results showed that GRCM prediction matches very well with experimental data, with mean temperature deviation of 0.24 K during melting case, while for solidification case was 0.34 K. These results showcase the GRCM’s capability for accurately reproducing the thermal characteristics of PCM-HXs with considerably lower computational effort.

42 ENGINEERING↗
DOE OSTI2025

The Design of a Multiphase CO2 Turbine Test Facility

As the energy market continues to evolve with increased renewables, such as solar and wind energy, the need to balance energy demand with its availability has become increasingly more challenging. The country’s aggressive decarbonization goals in the upcoming decades will increase renewable energy market penetration, thus exacerbating the disparity between energy demand and renewable resource availability. Long-duration energy storage technologies, such as pumped thermal energy storage (PTES), are potential solutions to this challenge with high potential round-trip efficiency (RTE), no geological or geographical constraints, and low safety risks. The charge mode of a PTES system operates a heat pump cycle, converting input power to thermal energy in hot and cold reservoirs. Fundamentally, heat pumps are commonly used in daily life, but the operating conditions required by high RTE PTES systems are outside the design experience of these systems. The low-pressure side of the cycle for a supercritical CO2 (sCO2) PTES operates just above the vapor-dome and potentially drives the turbine to expand into the dome, resulting in multiphase operation in the rear stages of the turbine. This paper presents the design of the test facility for an advanced multiphase-tolerant sCO2 turbine for the heat pump of a PTES system. Heat rejection and pressure loss estimations for the multiphase sections of the test loop presented unforeseen challenges.

25 ENERGY STORAGE↗
DOE OSTI2026

A Comprehensive Greenhouse Gas Assessment of Biomass-Based Carbon Dioxide Removal and Storage

Biomass-based Carbon Removal and Storage (BiCRS) is a suite of technological pathways that provide a relatively affordable and high-potential way to remove carbon dioxide from the atmosphere and simultaneously re-purpose residual biomass. BiCRS technologies are individually optimized to different biomass feedstocks, temperatures and oxygen, with the primary goal of capturing a high percentage of biomass-derived carbon dioxide and storing it in permanent below-ground storage (i.e. geologic storage), and a secondary goal of producing renewable energy. The current standard for BiCRS life cycle assessments does not account for greenhouse gas (carbon dioxide, methane and nitrous oxide) fluxes from surface soil amendment of BiCRS byproducts (e.g. char, ash) and their alternate fates. This is partly due to a paucity of empirical data due to the novelty of BiCRS conversion technologies, the range in feedstocks, and the heterogeneity of soils to which they might be amended. To fill this gap in in the life-cycle assessment and provide a realistic range of parameters for a soil amendment component of the BiCRS life cycle assessment, we conducted an incubation experiment to measure soil carbon changes, microbial respiration, methane fluxes, and nitrous oxide fluxes from two different soils amended with char- and ash- byproducts from biomass after gasification to hydrogen, fast pyrolysis to bio-oil, and torrefaction. Our results suggest that nitrous oxide and methane emission or consumption from BiCRS char amendments to soil are context dependent. Nitrous oxide emissions from amendments are higher in soils with higher pH, whereas some char amendments to low pH soil can reduce N 2 O emissions relative to control. In contrast, methane is emitted from BiCRS char amended to low pH soil, but consumed or neutral relative to control when amended to high pH soil. We present carbon and nitrogen mass balance throughout the experiment to help understand short-term durability of BiCRS chars and their counterfactuals, and preliminary suggestions for revisions to the broader BiCRS Measurement, Reporting, and Verification framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Center for Lignocellulose Structure and Formation (CLSF)

Lignocellulose is the carbon- and energy-rich material synthesized by plants when they make secondary cell walls, e.g. in woody tissues. Plants annually convert gigatons of atmospheric CO 2 into these complex and useful biomaterials that comprise over half of all biological carbon on Earth. This biological conversion helps to reduce atmospheric CO 2 that contributes to climate change while generating renewable plant cell walls that are used commercially on a massive scale in the paper, timber and textile industries. Recent technical developments open new possibilities for use of modified wood and cellulose fibers as large-scale alternatives to steel, plastics, and other nonrenewable materials with high carbon footprints and energy inputs, as well as for generation of biofuels and bio-hydrogen. Despite the utility of plant-based biomaterials, many physical and biological aspects of cell wall structure and formation remain obscure, and this limits the current scope for engineering these renewable resources for greater utility.

09 BIOMASS FUELS↗
DOE OSTI2025

An interregional optimization approach for time series aggregation in continent-scale electricity system models

Modeling electric power systems with high shares of weather-dependent resources requires tradeoffs between temporal, spatial, and operational resolution. Many studies perform time series aggregation using clustering algorithms to reduce the temporal dimension, but when modeling continent-scale electricity systems that are large enough to contain multiple independent weather systems, this approach requires large numbers of representative periods to minimize errors in regional wind and solar capacity factors. Here, a new optimization-based approach for representative period selection and weighting is introduced that minimizes regional errors in average renewable capacity factors and electricity demand. The method delivers higher regional fidelity with fewer representative periods than alternative clustering methods when applied to wind, solar, and demand profiles for the contiguous United States. When representative periods are selected from multiple weather years, the optimized method reproduces regional averages with lower error than a complete 365-day time series from any single weather year. The method identifies only representative (as opposed to outlying) periods but can be combined with an iterative "stress period" identification approach to guide efficient decision-making considering both average and high-risk weather conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗