Search NASA⌕ Search

SEARCH · Search NASA

Results for “Energy Modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Organizational Influence on Supply Chain for Digital Energy Infrastructure: Business Models, and Policy Landscape

Significant investment is driving the essential modernization and digitization of U.S. energy infrastructure, but the United States faces a key challenge in this grid transformation: our renewable and clean energy supply chains have limited capacity to source necessary digital assets through U.S. or allied sources. Batteries and their associated power electronic interfaces are key components to delivering clean and more resilient energy delivery, providing much-needed fast ramping, emergency discharge, generation, and operations support to the electric grid. These services have grown to be invaluable over the past 10 years and will soon be an irreplaceable component of energy delivery. While there have been significant strides to move supply chains for raw and critical materials to U.S. and allied nations, the control and power electronic industry has lagged, in part because of lower cost margins. For example, the United States now has growing capacity to manufacture solar photovoltaic (PV) panels, but 90% of the inverters—which are essential to the conversion of DC to AC for grid connection and controls—are made in or source parts from the People’s Republic of China (PRC). While a global supply chain is beneficial for many economic and supply diversification reasons, presence of foreign entities of concern (FEOC) in a dominant role in this supply chain brings additional concerns for national security of infrastructure. The BESS relationship and new clean energy have features that warrant discussions and additional focus on impact for technology security, given their critical role. This review considers the impact and solutions for complex business and policy landscapes in clean energy supply chain, and the benefit trade-offs, focusing on the Battery Energy Storage System case study, and its complex organizational relationships across both the US, Allied countries and Foreign Entities of Concern. While many examples in this paper are presented on PRC focused manufacture, this could apply to any potentially adversarial relationship

25 - ENERGY STORAGE↗
DOE OSTI2026

Surrogate model evaluation and building energy benchmarking for commercial buildings

Building energy consumption benchmarking involves challenges associated with various energy patterns for different building types; heating, ventilating, and air-conditioning (HVAC) system types; and climates. Given significant variation in energy use patterns, accurate prediction of long-term energy use using surrogate models remains challenging. Multiple linear regression (MLR) is commonly used for building energy benchmarking because of its simple structure; however, it lacks accuracy compared to other black-box models. Although many studies have compared surrogate models and offer guidance on model selection based on metrics, they do not provide detailed analysis on improving the surrogate model accuracy. In this paper, we implement a surrogate model using polynomial ridge regression (i.e., MLR with interaction terms combined with ridge regularization) for small office and retail strip mall buildings across six HVAC system types and all climate zones, for electricity and natural gas in baseline and proposed scenarios. A simulation workflow is developed using OpenStudio TM /EnergyPlus TM to generate simulation data using measures over a wide range of efficiency inputs. Enhancements based on statistical insights are used for improving the model accuracy using filters, input transformations, and change points. Surrogate models achieved average coefficient of variation of the root mean squared error (CVRMSE) values of 2.17, 1.06, 2.05, and 3.26 for proposed electricity, proposed natural gas, baseline electricity, and baseline natural gas, respectively, with enhancements reducing CVRMSE by an average of 14.9% across all combinations. We provide model interpretation via Shapley additive explanations to determine which input variables most influence energy consumption and provide supportive arguments for enhancements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Impedance Emulation Control of Wave Energy Converters

Modeling and control of wave energy conversion (WEC) systems for maximum power extraction is challenging due to complex multiphysics that include fluids, mechanics, and machine drives. To uncover an intuitive model that clearly depicts WEC system operation, we utilize a force-current equivalent circuit framework which then enables us to design an impedance emulation control strategy. To provide context for our framework, we focus on a standard reference model-3 (RM3) point absorber device coupled to a permanent magnet synchronous generator. After the proposed extremum seeking controller is computed, we experimentally validate its performance on a platform that consists of two back-to-back connected inverters that emulate the WEC system.

wave energy conversion, impedance emulation, machi↗
DOE OSTI2026

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Quality Guidelines for Energy System Studies: Process Modeling Design Parameters

The National Energy Technology Laboratory (NETL) conducts systems analysis studies that require a large number of inputs, from ambient conditions to parameters for Aspen Plus ® (Aspen) process blocks. The sheer number of assumptions required makes it impractical to document all of them in each issued report. The purpose of the Quality Guidelines for Energy System Studies (QGESS) is to document the assumptions most commonly used in system analysis studies and the basis for those assumptions. In order to develop the systems analysis models presented in various NETL reports, significant vendor data have been obtained, and these data enhance the model outputs. Much of the vendor data obtained are considered proprietary and not suitable for public release or attribution to a specific vendor. As such, several sub-systems common in NETL reports and their process parameter data are not reported in this document to protect proprietary vendor information. The values and ranges of values presented in this report represent assumptions that have been made in previous studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Comprehensive Comparison of Methods for Evaluating Dispatch of Long-Duration Energy Storage in Power Systems Models

Long-duration energy storage (LDES) could play a pivotal role in the transformation of electricity grids with high shares of variable renewable energy (VRE) such as solar and wind. However, the weather-dependent nature of VRE introduces challenges for grid balancing and stability, which LDES - along with short-duration energy storage (SDES) - can help address. However, modeling LDES in production cost models (PCMs) is particularly challenging due to the need for high temporal resolution over extended optimization windows while preserving chronology, which ensures the alignment of energy storage operations with VRE generation over multi-day periods. This report compares traditional dispatch methods with advanced LDES dispatch strategies, such as the extended horizon approach, across different PCM platforms and examines tradeoffs and scalability. The comparison reveals that the traditional 1-day optimization horizon within the PCM leads to inefficient utilization of LDES. In contrast, extending the optimization horizon as much as possible significantly reduces curtailment and improves storage dispatch, especially in renewable-dense systems. There is also promise in using state-of-charge or end volume targets set by an external model, however this requires an additional modeling set and generally increases computational burden. This paper presents a comparison of these various methods in a number of power systems, showing algorithms initially in small test systems and scaling up to large, country-wide simulations. Overall, the research presents the trade-offs of various computational methods and illustrates how LDES may play an essential role in power systems of the future.

14 SOLAR ENERGY↗
DOE OSTI2024

Incorporating energy justice and equity objectives in power system models

Ensuring an equitable energy transition requires models and tools that can account for equity and energy justice goals. Power system models (PSMs) are widely used throughout industry, government, and academia to simulate or optimize the operations and planning of current and future electricity systems under different scenarios, parameter assumptions and policy frameworks. These models are important tools that allow users to understand how the power system may evolve under different future conditions, but importantly, they are also used to inform policy implementation and investment decisions across all aspects of the power system. However, existing models seldom include energy justice considerations and therefore energy justice priorities are not reflected in the policies and other decision-making processes that are informed by these models. The purpose of this review is to provide a framework that energy modelers can draw upon to integrate energy justice and equity goals into PSMs. To this end, 99 papers that examine the intersection of energy justice and power system models are summarized and ten core aspects of the power system that can impact energy justice outcomes, and therefore require new modeling approaches, are identified. This review then establishes key current practices, challenges, and opportunities associated with capturing energy justice considerations in power system models across these ten aspects. This review concludes by proposing four key research directions that should be pursued to improve the representation of energy justice and equity in power system modeling. Finally, this review also addresses challenges raised by United Nations Sustainable Development Goal 7, which aims to ensure affordable energy access to everyone and Sustainable Development Goal 13, which aims to take urgent action to address climate change.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Advancements on Multi-Fidelity Random Fourier Neural Networks: Application to Hurricane Modeling for Wind Energy

Multi-fidelity approaches are emerging as effective strategies in computational science to handle otherwise intractable tasks like Uncertainty Quantification (UQ), training of Machine Learning (ML) models, and optimization, for expensive high-fidelity applications in which the amount of available simulations or data is limited. The main idea is simple: large datasets generated for low-fidelity approximations of the problem at hand are fused with a much sparser dataset for the target (high-fidelity) system. In this paper, we build on our recent success in designing random Fourier Neural Networks (rFNNs) [1] to target problems arising in wind energy applications and in particular problems of interest for hurricane modeling. In this context, data for the high-fidelity models are limited and lower fidelity alternatives are needed. In this work, we introduce a novel multi-fidelity training approach for our rFNNs and demonstrate its use on a simple verification problem and on a hurricane modeling problem in which high-fidelity data are generated via Large-Eddy Simulations (LES), while low-fidelity data are given by a mesoscale model. Initial results demonstrate how the multi-fidelity training approach can improve the quality of the resulting surrogate.

Fourier Neural Networks↗
DOE OSTI2024

Conceptual Design of Integrated Energy Systems with Market Interaction Surrogate Models

Most integrated energy system (IES) optimization frameworks employ the price-taker approximation, which ignores important interactions with the market and can result in overestimated economic values. In this work, we propose a machine learning surrogate-assisted optimization framework to quantify IES/market interactions and thus go beyond price-taker. We use time series clustering to generate representative IES operation profiles for the optimization problem and use machine learning surrogate models to predict the IES/market interaction. We quantify the accuracy of the time series clustering and surrogate models in a case study to optimally retrofit a nuclear power plant with a polymer electrolyte membrane electrolyzer to co-produce electricity and hydrogen.

Chen, Xinhe↗
DOE OSTI2024

Conceptual Design of Integrated Energy Systems with Market Interaction Surrogate Models

Most integrated energy system (IES) optimization frameworks employ the price-taker approximation, which ignores important interactions with market and can result in overestimated economic values. In this work, we pro-pose a machine learning surrogate-assisted optimization framework to quantify the IES/market interactions and thus go beyond price taker. We use time series clustering to generate representative IES operation profiles for the IES optimization problem and use machine learning surrogate models to predict the IES/market interaction. We quantify the accuracy of the time series clustering and surrogate models in a case study to optimally retrofit a nuclear power plant with polymer electrolyte membrane electrolyzer to co-produce electricity and hydrogen.

Chen, Xinhe↗
DOE OSTI2024

The atmospheric effect of aerosols on future tropical cyclone frequency and precipitation in the Energy Exascale Earth System Model

This study uses experiments from the Energy Exascale Earth System Model (E3SM) to compare the influence on tropical cyclone (TC) activity of: (i) the atmospheric effect of aerosols under specified sea-surface temperatures (SSTs); and (ii) the net effect of greenhouse gases (GhGs) (including changes in SSTs). The experiments were performed using the CMIP6 Shared Socioeconomic Pathway SSP5-8.5 emissions scenario with GhG-induced SST warming specified and atmospheric aerosol effects simulated but without explicit ocean coupling. Insignificant changes in global TC frequency are found in response to the atmospheric effect of future aerosols and GhGs, as significant regional responses in TC frequency counteract each other. Future GhGs contribute to more frequent TCs in the North Atlantic, and reductions over the Northwestern Pacific and Southern Indian Ocean. The atmospheric effect of future aerosols drives more frequent TCs over the Northwestern Pacific and reductions over the Northeast Pacific and North Atlantic. Along with increases in TC intensity, global TC precipitation (TCP) is projected to increase by 52.8% (14.1%/K) due to the combined effect of future aerosols and GhGs. Although both forcings contribute to TCP increases (14.7–19.3% from reduced aerosols alone and 28.1–33.3% from increased GhGs alone), they lead to different responses in the spatial structure of TCP. TCP increases preferentially in the inner-core due to increased GhGs, whereas TCP decreases in the inner-core and increases in the outer-bands in response to the atmospheric effects of decreased aerosols. These changes are distinct from those caused by aerosol-induced SST changes, which have been considered in other studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hydrodynamic Modelling for Tidal Energy Kites: Cooperative Research and Development Final Report, CRADA Number CRD-24-30123

The primary goal of the work is to improve accuracy of hydrodynamic loads acting on the lifting surface of the kite turbine due to complex air-water-lifting body interaction in a low-order numerical model using high-fidelity numerical input. The result of this study will help the Participant better design control algorithms for the kite turbine so that the turbine can harvest more energy while maintaining stability of the platform as well as its reliability. The use of hydrodynamic coefficients/load components from computational fluid dynamic simulation will inform better inputs for a medium-fidelity dynamic model (specifically an OrcaFlex model) which is intended for use in rapid design iterations in the design process.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Scheduler Modeling of Distributed Energy Resources for Providing Ancillary Services

Distribution energy resources (DERs) have been integral components of modern power systems, and their capability to provide grid services has been widely studied. To promote the deployment of these resources in providing grid services in real-world utility operations, this paper proposes a day-ahead scheduler model for a distribution system connected DER plant. A certain amount of generation capacity of this DER plant is reserved for frequency services, and some ancillary services for the distribution system-including peak load reduction, voltage regulation, and power factor control-are integrated into the model. The model is tested on a real-world distribution system. From the simulation results, the energy and reserve schedule of the solar photovoltaic (PV) unit and battery energy storage system (BESS) can be determined, and voltage and power factor are well maintained. Additionally, in order to demonstrate the specific characteristics of the co-located and hybrid operation modes for the PV and BESS, these two modes are analyzed both theoretically and through real-time simulation. Simulation results show that most of PV's variability is transferred to the net power in the co-located mode, whereas it is transferred to the BESS in the hybrid mode. This proposed scheduler model and the comparison of co-located and hybrid modes can provide practical guidance for the applications of DER plant in the real-world utility.

14 SOLAR ENERGY↗
DOE OSTI2025

Development of an Interactive Valuation Model for Distributed Energy Resource Value: Cooperative Research and Development (Final Report)

The Oklahoma Office of the Secretary of Energy and Environment (OSEE) seeks to address perceived challenges and barriers to the deployment of distributed energy generation resources (DERs), including solar and other technologies, in the state of Oklahoma. The Scope of Work (SOW) associated with CRD-18-762 covers two tasks: (1) Interactive Valuation Model Requirements Document and (2) Consumer Protection Assessment. Follow-on work was completed under a separate CRADA (CRD-19-00788).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Hybrid Energy Resources Bidding Model (HERB) v1.0

The HERB Model provides a stochastic optimization framework for hybrid power plants (Storage plus Renewables) participating in day-ahead electricity markets. It considers uncertainty in market prices and renewable energy generation and generated risk-constrained price-quantity bid curves with limited, non-decreasing price steps.

Heleno, Miguel [Lawrence Berkeley National Laborat↗
DOE OSTI2026

The Energy Exascale Earth System Model Version 3: 2. Overview of the Coupled System

The Energy Exascale Earth System Model version 3 (E3SMv3) represents the latest advancement in Earth system modeling developed by the U.S. Department of Energy (DOE). Building upon previous versions, E3SMv3 introduces significant updates across its coupled components to enhance capability and improve fidelity. The atmosphere component incorporates advancements in chemistry, aerosol-cloud interactions, convection, and microphysics. The ocean features a new time-stepping scheme and a higher-resolution unstructured mesh with sub-ice-shelf cavities, while the sea ice model integrates advanced snow and ice physics for more realistic cryospheric simulations. The land model introduces prognostic vegetation dynamics and a new sub-grid topographic treatment of solar radiation. A new tri-grid configuration harmonizes the horizontal grids of the land and river components for improved process coupling. It is enabled by a new non-linear remapping between the atmosphere and land. E3SMv3 underwent extensive testing through a comprehensive simulation campaign, including pre-industrial control, idealized CO 2 experiments, and historical simulations spanning 1850–2024. The model demonstrates significant improvements in simulating the evolution of the historical surface temperature, particularly addressing the “pothole cooling” bias in earlier versions. Reduced aerosol-related forcing contributes to more realistic radiative forcing and better alignment with the observational record. Ocean heat content (OHC) and sea ice trends are also improved as a result.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Operational Parameter Database for Molten Salt Thermal Energy Storage Tank Modeling

The second generation of concentrated solar power (CSP) plants is characterized by the use of a central receiver (either cavity or external), two molten nitrate salt tanks (60 wt.% NaNO 3 and 40 wt.% KNO 3 ), and a steam Rankine power-generation cycle connected through a primary heat exchanger. Molten salt thermal energy storage (TES) tanks have been widely deployed in commercial CSP plants worldwide and have been essential for increasing plant dispatchability and capacity factor, while also reducing the levelized cost of electricity (LCOE). These systems enable energy storage at the gigawatt-hour scale, typically providing 6 to 17 hours of storage duration. Despite being a commercial technology, the multiple failures observed after only a few months or years of operation in plants around the world demonstrate the technology's relative infancy and highlight the need for further research to improve its reliability. The National Laboratory of the Rockies (NLR), in collaboration with industry partners and academic and research institutions, has been leading multiple projects funded by the U.S. Department of Energy (DOE). These projects focus on addressing molten salt tank failures by improving tank design and welding fabrication practices, evaluating new alloys and weld fillers, and providing guidelines for tank commissioning and safe operation. In particular, this report presents modeling results on the effect of key tank operation parameters during 60 minutes of operation, including the mass flow rate and temperature of the salt inflow, tank salt inventory temperature, and inventory level for a representative molten salt tank design. These results form a database of tank operation behaviors that captures the effects of each specific parameter during charging, charging/discharging, and discharging processes.

14 SOLAR ENERGY↗