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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The value of long-duration energy storage under various grid conditions in a zero-emissions future

Long-duration energy storage (LDES) is a key resource in enabling zero-emissions electricity grids but its role within different types of grids is not well understood. Using the Switch capacity expansion model, we model a zero-emissions Western Interconnect with high geographical resolution to understand the value of LDES under 39 scenarios with different generation mixes, transmission expansion, storage costs, and storage mandates. We find that a) LDES is particularly valuable in majority wind-powered regions and regions with diminishing hydropower generation, b) seasonal operation of storage becomes cost-effective if storage capital costs fall below US$\$$5 kWh −1 , and c) mandating the installation of enough LDES to enable year-long storage cycles would reduce electricity prices during times of high demand by over 70%. Given the asset and resource diversity of the Western Interconnect, our results can provide grid planners in many regions with guidance on how LDES impacts and is impacted by energy storage mandates, investments in LDES research and development, and generation mix and transmission expansion decisions.

25 ENERGY STORAGE↗
DOE OSTI2023

Optimal Dispatch for the US Virgin Islands to Increase Renewable Rates in Saint Croix

The US Virgin Islands, like many other small island nations, face significant challenges related to its energy supply. Their dependency on imported fossil fuels not only drives up energy costs, but also contributes to different environmental problems. Nevertheless, their generally sunny and windy climate makes this archipelago an ideal location for renewable energy development. Increasing the use of sources such as wind, and solar can help reduce their energy dependency, lower their levelized cost of electricity, and improve the health and wellbeing of local communities. In this paper, an optimal dispatcher is employed to analyze the implications on energy security of employing different technology options according to the plans of the local system operator. In this context, short term stability is ensured by inserting operational constraints in the energy management system based on stability analysis developed in PSCAD. The results highlight the usefulness of integrating PV and battery system, while further analysis are required to justify integrating wind power.

energy islands↗
DOE OSTI2020

Modeling and Harmonic Stability of MMC-HVDC With Passive Circulating Current Filters

A modular multilevel converter (MMC) is an emerging converter technology widely used in wind power applications using high-voltage direct current (HVDC) transmission, and it has been largely investigated in medium-voltage solar harvesting as well as electric motor drives. Different from studies dealing with active circulating current control loops, this paper focuses on impedance modeling and harmonic stability studies for MMCs with passive circulating current filters (PCCFs). A power stage circuit including a PCCF is transformed and remodeled to obtain small-signal formulations. This transformation leads to additional high-order matrix computing complexity due to the added impedance subnetwork matrix from the PCCF as well as relevant crossed-frequency impacts. To simplify the computational burden, the proposed model aims to solve one arm equation instead of all six MMC arm equations. To achieve this result, additional challenges occur when the MMC is connected to a renewable energy source instead of the grid voltage, where low-level zero-sequence components might exist in the neutral point of three phases, especially in the case of no integrated advanced modular voltage balancing control, which prevents computational simplification. To overcome this challenge, further impedance matrix adjustments are conducted in this paper to theoretically suppress the impact of zero-sequence harmonics when obtaining small-signal impedance, taking into account the frequency coupling effect. Finally, simulations are carried out to validate the developed impedance model under different operating scenarios. Harmonic stability case studies of MMCs with PCCFs connected to renewable energy current sources are also presented, where frequency-domain stability analyses based on Bode diagrams are compared to time-domain simulation waveforms and FFTs, which validate the effectiveness of the proposed impedance model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Pricing Strategy of Electric Vehicle Aggregators Based on Locational Marginal Price to Minimize Photovoltaic (PV) Curtailment

The global climate crisis demands urgent action to mitigate global warming. Using renewable energy sources, such as solar and wind power, for electricity generation is crucial. This shift from centralized to distributed power systems, however, brings challenges, including voltage fluctuations and renewable energy curtailment. The rapid growth of the electric vehicle (EV) industry adds complexity, increasing overall electricity demand and straining the power supply during peak charging times. This paper proposes a scheduling strategy for EV aggregators to reduce renewable energy curtailment and stabilize grid operation by strategically scheduling EV charging. Using Multi -Agent Transport Simulation (MATSim), a traffic simulation tool, EV driving data in Denver, Colorado, USA, were modeled. The EV aggregator adjusts charging fees based on locational marginal prices, encouraging EVs to charge at different stations according to pricing. Simulations on an IEEE 33-bus system with distributed energy resources and EV charging stations validate the proposed algorithm, demonstrating its effectiveness in reducing curtailment by 12.55% and stabilizing grid operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

AI-Based EMT Dynamic Model of PV Systems

Several electromagnetic transient (EMT) dynamic modeling methods are available to model systems like photovoltaic (PV) plants, wind power plants, variable-speed drives, among others. The methods include: (a) physics-based models and (b) data-driven models. The physics-based dynamic models may include high-fidelity switched system model and average-value model that both require the control algorithms included in the models. However, manufacturers typically prefer to provide black-box models to avoid disclosing proprietary. One of the solutions to prevent disclosing control algorithms is the use of data-driven dynamic EMT models of PV systems. In this paper, data-driven dynamic EMT model based on artificial intelligence (AI) algorithms are presented. The AI algorithms evaluated include convolutional neural networks, recurrent neural networks, and nonlinear auto-regressive exogenous model. Automation in generating data and training these models is also discussed in this paper. The results generated by the best AI algorithms have been observed to be greater than 95 % accurate.

Debnath, Suman↗
DOE OSTI2026

Operational Simulation of Multi-Functional Charging Station for Sustainable Transportation

As transportation systems move toward electrification and decarbonization, multifunctional charging stations (MFCS) are emerging as key infrastructure for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs). This paper presents a simulation model of an MFCS that integrates solar photovoltaic (PV), wind power, battery storage, hydrogen (\mathrm{H}_{2}) production, dual-pressure \mathrm{H}_{2} storage, fuel cells, and dynamic grid interactions. The model simulates daily operations using 5 -minute resolution data to capture realtime variability in renewable energy (RE), demand, and electricity prices. A flexible dispatch algorithm dynamically allocates energy for EV charging, \mathrm{H}_{2} production, storage, and grid transactions while respecting system constraints. Results show that the MFCS effectively prioritizes RE usage, minimizes waste, meets diverse energy demands, and achieves net operational profit. The model serves as a valuable decision-support tool for designing and optimizing integrated clean energy hubs for zero-emission transportation.

Gbadegoye, Jeremiah [University of Tennessee, Knox↗
DOE OSTI2020

Thermal Energy Storage Using Solid Particles for Long-Duration Energy Storage

The rapid growth of renewable energy increases the importance of economically firming the electricity supply from variable solar photovoltaic- and wind-power generators. Energy storage will be the key to manage variability and to bridge the generation gap over time scales of hours or days for high renewable grid integration. The integration of renewable power and storage of excess electricity has several significant and positive impacts including: 1) expanding the renewable energy portion of total electricity generation, 2) improving the peak-load response, and 3) coordinating the electricity supply and demand over the grid. Long-duration energy storage can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Several energy storage methods are deployed or under development, including mechanical, chemical or electrochemical, and thermal energy storage (TES). Comparing their economic potential for different scales and applications helps identify suitable technology to support high renewable grid integration. Despite the progress of TES technologies developed and deployed with concentrating solar power (CSP) systems, TES has been undervalued for its potential role in electric energy storage. This paper introduces TES methods applicable to grid energy storage and particularly focuses on solid-particle-based TES to serve the purpose of long-duration energy storage (LDES). The objective of this paper is to present a standalone particle-based TES system for electric storage and to show the potential of TES systems for LDES applications over other energy storage methods such as batteries, compressed-air energy storage, or pumped-storage hydropower.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2022

GIST (Grid Impedance Scan Tool) [SWR-22-73]

NREL has developed GIST (Grid Impedance Scan Tool) to scan the impedance response of inverter-based resources such as land-based and offshore wind power plants, solar power plants, etc., from their electromagnetic transient simulation models to evaluate their impact on grid stability. GIST can scan impedance response of inverter-based resources from vendor-supplied black-box simulation models without requiring internal proprietary details, enabling detailed stability analysis of power systems with high levels of inverter-based generation.

Shah, Shahil↗
DOE OSTI2021

REopt Lite Geothermal Heat Pump Design Requirements

This document describes the design requirements for the geothermal heat pump (GHP) module being added to the existing REopt Lite web tool. This document describes the purpose, users, and functional requirements to which the modified web tool shall conform. This document will be revised, as required, throughout the development phase with consensus between the Department of Energy (DOE) Geothermal Technologies Office (GTO) and NREL. The GHP module will expand existing REopt Lite capabilities to include techno-economic optimization of GHP systems, either stand alone, or integrated with the other existing technology types, namely solar photovoltaics (PV), wind power, battery energy storage, thermal energy storage, combined hear and power (CHP), and absorption chiller. Included in this submission are links to the REopt Lite web tool and open-source Git-Hub page. The REopt Lite tool can also be accessed directly via the NREL Developer Network. A link is also provided for the REopt report that overviews the module's capabilities.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Hydrolytic Softening of Ocean Water for Carbon Dioxide Removal

This project provided the proof of concept testing for hydrolytic softening, a process for ocean carbon dioxide removal (CDR) based on precipitation softening, where the hydrated lime used to initiate carbonate precipitation is regenerated using a low-energy thermochemical cycle. These proof of concept tests demonstrated each key step of the hydrolytic CDR process including: 1) precipitation of dissolved carbon dioxide from seawater using hydrated lime, 2) decomposing the precipitated calcium carbonate to separate a high-purity stream of carbon dioxide, and 3) regenerating hydrated lime from the decomposition products to complete the cycle. The experimental results were used as the basis for a chemical process model of hydrolytic CDR, which was then used to estimate the techno-economic performance of a conceptual full-scale system. Results included a total energy consumption estimate of 248 kJ per mole of separated and compressed CO 2 . The predicted levelized cost of ocean CDR using hydrolytic softening could reach the Department of Energy’s Carbon Negative Shot target of $\$$100/tCO 2 assuming optimally-sited wind power resources with a power cost of $\$$26/MWh. If developed further, hydrolytic CDR could be a near-term, scalable, and cost-effective method to draw down legacy carbon dioxide emissions that have been absorbed in the oceans. Offshore operations would create highly skilled jobs directly at the CDR facilities in addition to supporting a wider network of coastal service providers and their communities.

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

Analyzing the Effects of Atmospheric Turbulent Fluctuations on the Wake Structure of Wind Turbines and Their Blade Vibrational Dynamics

In recent trends, a rising demand for renewable energy has driven wind turbines to larger proportions, where lighter blade designs are often adopted to reduce the costs associated with logistics and production. This causes modern utility-scale wind turbine blades to be inherently more flexible, and their amplified aeroelastic sensitivity results in complex multi-physics reactions to variant atmospheric conditions, including dynamic patterns of aerodynamic loading at the rotor and vortex structure evolutions within the wake. In this paper, we analyze the influence of inflow variance for wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex wake interactions for a range of flexible NRT blade variations, operating in differing conditions of variant atmospheric flow. CODEF solutions of turbine operation in Steady-In-The-Average (SITA) wind conditions are compared to SITA wind conditions featuring a controlled gust-like pulse overimposed, to isolate the effects of typical wind fluctuations. Finally, simulations of realistic time-varying wind conditions from SWiFT meteorological tower measurements are compared to the solutions of SITA wind conditions. These increasingly complex atmospheric inflow variations are tested to show the differing effects evoked by various patterns of spatiotemporal atmospheric flow fluctuations. An analysis is presented for solutions of wind turbine aeroelastic response and vortex wake evolution, to elucidate the consequences of variant inflow, which pertain to wind turbine dynamics at an individual and farm-collective scale. The comparisons of simulated farm flow for SITA and measured fluctuating wind conditions show that certain regions of the wake contain up to a 12% difference in normalized axial velocity, due to the introduction of wind fluctuations. The findings of this study prove valuable for practical applications in wind farm control and optimization strategies, with particular significance for modern utility-scale wind power plants operating in variant atmospheric conditions.

Farrell, Alayna (ORCID:000000023555720X)↗
DOE OSTI2025

Modeling and Analysis of Wind Turbine Wake Vortex Evolution Due to Time-Constant Spatial Variations in Atmospheric Flow

Modern utility-scale wind turbines are evolving toward larger, lighter, and more flexible designs to meet the growing demand for renewable energy while minimizing logistical costs. However, these advancements in lightweight design result in heightened aeroelastic sensitivity, leading to complex interactions which affect the rotor’s capacity to withstand aerodynamic loading and the cascading effects that manifest in the wake’s vortex-structure evolution under variable atmospheric conditions. In this paper, we analyze the influence of stream-wise fluctuating atmospheric flow conditions on wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex–wake interactions for a range of conditions with spatially variant atmospheric flow. CODEF solutions for turbine operation in wind conditions featuring only one parameter fluctuation are compared to wind conditions with several wind parameter variations in combination. By isolating individual inflow variations and comparing them to multi-parameter scenarios, we determine the contributions of each atmospheric factor to rotor dynamics, wake evolution, and downstream wind farm interactions. The purpose of this paper is to analyze the effects of spatial variations in atmospheric flow on the topological evolution of wind turbine vortex wakes, which constitutes a gap in the current understanding of wind turbine wake dynamics. The insights gained from this study are particularly valuable for the development of wind farm control strategies aimed at mitigating the adverse effects of wake interactions, enhancing energy capture, and improving the overall stability of wind farm operations. With these insights, we aim to contribute to the development of modeling and simulation tools to optimize utility-scale wind power plants operating in diverse atmospheric environments.

Farrell, Alayna (ORCID:000000023555720X)↗
DOE OSTI2026

Impact of atmospheric turbulence on performance and loads of wind turbines: knowledge gaps and research challenges

Wind energy harvesting from the atmosphere takes place in the atmospheric boundary layer. The boundary layer shear and buoyancy create three-dimensional turbulent eddies spanning a range of scales that form a continuous forward cascade of kinetic energy to the smallest scales of motion where energy is dissipated. Large-scale atmospheric circulations modulate the boundary layer turbulence, characterized by coherence and intermittency. As wind turbines grow in size and the integrated control of both turbines and wind farms spans greater distances, the relationship between the scales of atmospheric turbulence and the design and operation of wind energy facilities has entered new territory. The boundary layer turbulence impacts both wind turbine power production and turbine loads. Optimizing wind turbine and wind farm performance requires an understanding of how turbulence affects both wind turbine efficiency and reliability. While the characteristics of atmospheric boundary layer turbulence have been observed and studied in detail over the last few decades, there are still significant gaps in our understanding of the impact of turbulence on wind power resources and wind farm operations. This paper outlines the current state of turbulence research relevant to wind energy applications and points to gaps in our knowledge that need to be addressed to effectively utilize wind resources.

Kosović, Branko [Johns Hopkins Univ., Baltimore, M↗
DOE OSTI2025

Energy 101 - Wind [Slides]

The Energy 101: Wind presentation, developed for the Energy Technology Innovation Partnership Project (ETIPP), provides an overview of wind energy. It covers fundamental concepts, technologies, considerations, case studies, and additional resources.

17 WIND ENERGY↗
DOE OSTI2021

Metal-Organic Framework-based Luminescent Sensors for Rare Earth Elements

Rare earth elements (REEs) are crucial for many applications and are particularly important in wind power and electric vehicle technologies, spurring projected demand increases for REEs in coming decades. However, the REE supply is restricted by a monopolistic global marketplace, tedious and costly processing steps for REE production, and environmental hazards associated with mining and processing. Coal and coal-utilization byproducts have emerged as potential domestic sources for REEs, however REE production from these sources is currently hindered by slow and expensive characterization techniques. Here, we demonstrate that metal-organic framework (MOF)-based sensitizers can effectively serve as luminescent sensors capable of rapidly detecting and distinguishing part-per-billion concentration levels of emissive REEs, including terbium, europium, dysprosium, samarium, neodymium, and ytterbium. Importantly, we demonstrate that the MOF structure plays a significant role in tuning the selectivity of the MOF for REEs in acidic environments, an essential step towards deployment in various REE-rich process streams. As a proof-of-concept, we demonstrate sensitive and reversible detection of REEs using a portable fiber-optic spectrometer

Crawford, Scott↗
DOE OSTI2023

High-Resolution Southeast Asia Wind Resource Data Set

Well informed decision-making is a key part of integrating variable renewable energy into the global energy marketplace. USAID and NREL, through the Advanced Energy Partnership for Asia, are expanding access to critical resource data by providing free, high-fidelity time-series wind resource data for Southeast Asia through the RE Data Explorer platform. This brief highlights the development of the Southeast Asia wind resource data set and discusses the impacts of this data.

Advanced Energy Partnership for Asia↗
DOE OSTI2023

WAVES (Wind Asset Value Estimation System) [SWR-23-81]

The Wind Asset Value Estimation System (WAVES) model is a coupling framework for core NREL techno economic analysis software models to estimate capital expenditures (ORBIT), operational expenditures (WOMBAT), and energy production (FLORIS) for offshore wind power plants. Existing workflows to couple the three models for lifecycle performance and cost estimation require a large amount of manual and error-prone setup to combine both shared inputs and dependent outputs, as such WAVES's primary functionality is to wrap the core logic for running standard modeling workflows to ensure shared settings and entangled results are correctly and efficiently combined every time. SEE ALSO: https://pypi.org/project/WAVES/

Hammond, Robert↗