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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 109 records · Page 6

Quantification of storage required for preserving frequency security in wind‐integrated systems

Abstract The penetration of wind power generation into the power grid has been accelerated in recent times due to the aggressive emission targets set by governments and other regulatory authorities. Although wind power has the advantage of being environment‐friendly, wind as a resource is intermittent in nature. In addition, wind power contributes little inertia to the system as most wind turbines are connected to the grid via power electronic converters. These negative aspects of wind power pose serious challenges to the frequency security of power systems as penetration increases. In this work, an approach is proposed where an energy storage system (ESS) is used to mitigate frequency security issues of wind‐integrated systems. ESSs are well equipped to supply virtual inertia to the grid due to their fast‐acting nature, thus replenishing some of the energy storage capability of displaced inertial generation. In this work, a probabilistic approach is proposed to estimate the amount of inertia required by a system to ensure frequency security. Reduction in total system inertia due to the displacement of conventional synchronous generation by wind power generation is considered in this approach, while also taking into account the loss of inertia due to forced outages of conventional units. Monte Carlo simulation is employed for implementing the probabilistic estimation of system inertia. An ESS is then sized appropriately, using the system swing equation, to compensate for the lost inertia. The uncertainty associated with wind energy is modeled into the framework using an autoregressive moving average technique. Effects of increasing the system peak load and changing the wind profile on the expected system inertia are studied to illustrate various factors that might affect system frequency security. The proposed method is validated using the IEEE 39‐bus test system.

17 WIND ENERGY↗

Investigating event-shape methods in the search for the chiral magnetic effect in relativistic heavy ion collisions

The chiral magnetic effect (CME) is a phenomenon in which electric charge is separated by a strong magnetic field from local domains of chirality imbalance and parity violation in quantum chromodynamics. The CME-sensitive observable, the charge-dependent three-point azimuthal correlator Δ⁢𝛾 , is contaminated by a major physics background proportional to the particle's elliptic flow anisotropy 𝑣 2 . Event-shape engineering (ESE) binning events in dynamical fluctuations of 𝑣 2 and event-shape selection (ESS) binning events in statistical fluctuations of 𝑣 2 are two methods to search for the CME by projecting Δ⁢𝛾 to the measured anisotropy 𝑣 2 = 0 intercept. Here, we conduct a systematic study of these two methods using physics models as well as toy model simulations. It is observed that the ESE method fulfills the general premise of measuring the CME but is statistically hungry. It is found that the intercept from the ESS method depends on the details of the event content, such as the mixtures of background-contributing sources, because of statistical fluctuations of intertwining variables used in the method, and is thus not practically useful to measure the CME.

Relativistic heavy-ion collisions↗

Voltage Restoration in Microgrids using Temporal Logic Specifications

This paper proposes an energy storage controller synthesis method for voltage restoration in microgrids with respect to temporal logic specifications (TLSs). TLSs is introduced in this paper as a formalism to control the voltage variation of a critical bus against an operational bounds over time. The power system with synchronous generator (SG) connected to a critical load bus is modeled as a set of differential-algebraic equations and a simplified analytical model is derived to describe the voltage variation of this critical bus. The control objective is to schedule an optimal control input signal from a supportive energy storage system (ESS) connected to the critical bus, such that the voltage variation of the latter satisfies the TLSs, such as a finite-time restoration. The proposed control is verified on a lumped distribution system model. With this control diagram, supportive controllers can be designed to make voltage behaviors comply with grid codes and avoid unnecessary relay actions.

Taousser, Fatima Zohra↗

Techno-Economic Impact of Partial String Failure in Multi-string Energy Storage Systems

Electric utilities and large industrial/commercial customers, which integrate multi-MW multi-string energy storage systems (ESS), are typically at a significant risk of string failure. This results in the loss of system performance and capacity. In order to evaluate the accurate costs and benefits associated with a particular battery system, it is essential to incorporate the costs associated with battery string failure and, as a result, reduced capacity. This report analyzes how the economic losses can be estimated based on market rules and ESS availability. A framework for calculation of economic losses is developed and implemented with an illustrative string failure case for Independent System Operator (ISO-NE) forward capacity market. Further scenarios and case studies are analyzed by varying the probability of string failure as well as the capacity bid into the market. These scenarios are used to assess the variability of economic losses and the impact of string failure on the final realized benefits from the battery's market participation.

Fotedar, Vanshika↗

Discrete and Integrated Solutions for Hybrid PV Plants Without Momentary Cessation in Low SCR and High Penetration PE Grids

With the increased penetration of power electronic (PE) based loads and sources, advanced solutions may be required for the enhancement of grid stability in regions with low short circuit ratio (SCR) and high penetration PE grids. The requirement of advanced solutions arises from the gradual paradigm shift of the electric grid from the traditional electric machine dominant system to a high penetration of PE-based system. One of the major challenges with such systems in recent times is the momentary cessation during alternating current (ac) grid transmission faults. During momentary cessation, PE-based resources cease to operate, thus creating probable reliability challenges for the grid. In this paper, potential feasible options to provide continuity of operation during such scenarios are presented. The options are considered through identifying upgrades in existing and upcoming discrete development of photovoltaic (PV) and energy storage systems (ESS) termed as discrete hybrid PV plants. Additionally, an advanced concept of integrated development of PV and ESS connecting to ac transmission grid links called multi-port autonomous reconfigurable solar power plant (MARS) is evaluated. The developed new solutions are evaluated for different grid use cases and scenarios in PSCAD.

Marthi, Phani Ratna Vanamali↗

Virtual Synchronous Generator Control of Multi-port Autonomous Reconfigurable Solar Plants (MARS)

Multi-port autonomous reconfigurable solar power plant (MARS) is an integrated concept for integration of solar photovoltaic (PV) and energy storage systems (ESS) to transmission alternating current (ac) grid and high-voltage direct current (HVdc) links. The integrated development incorporates advanced control methods to provide enhanced grid ancillary services such as fast frequency responses and dynamic voltage support. In this paper, the virtual synchronous generator (VSG) control algorithm of MARS is discussed. The proposed VSG-based control enables enhanced synthetic inertial response and flexible frequency response characteristics of hybrid PV and ESS power plants in accordance with grid ancillary service requirements. Multi-port power electronics interface allows controlled emergency power support from MARS to local transmission ac grid and remote grid through the HVdc link. The performance of VSG control is validated using a reduced-order model of MARS in Simulink. Methods for estimating grid ancillary service capabilities of MARS are also discussed.

Pan, Jiuping↗

Deep Reinforcement Scheduling of Energy Storage Systems for Real-time Voltage Regulation in Unbalanced LV Networks with High PV Penetration

The ever-growing higher penetration of distributed energy resources (DERs) in low-voltage (LV) distribution systems brings both opportunities and challenges to voltage support and regulation. This paper proposes a deep reinforcement learning (DRL)-based scheduling scheme of energy storage systems (ESSs) to mitigate system voltage deviations in unbalanced LV distribution networks. The ESS-based voltage regulation problem is formulated as a multi-stage quadratic stochastic program, with the objective of minimizing the expected total daily voltage regulation cost while satisfying operational constraints. While existing voltage regulation methods are mostly focused on onetime- step control, this paper explores a day-horizon systemwide voltage regulation problem. In other words, the size of action and state spaces are extremely high-dimensional and need to be delicately handled. Furthermore, in order to overcome the difficulty of modeling uncertainties and develop a realtime solution, a learn-to-schedule feedback control framework is proposed by adapting the problem to a model-free DRL setting. The proposed algorithm is tested on a customized 6-bus system and a modified IEEE 34-bus system. Simulation results validate the effectiveness and near-optimality of voltage regulation by ESS in comparison with a deterministic quadratic program solution.

Wang, Shengyi↗

Improved PV System Control Strategies to Reduce Power Management Costs in Nanogrids

An improved PV system control method is proposed to reduce nanogrid operation costs in this paper. A model including it various components such as photovoltaic (PV) systems, energy storage systems (ESSs), gateways, and household loads is considered with the constraints of the ESS, PV irradiance from real data, and household load. We designed an optimal economic dispatch strategy with an improved PV system control method. Combining the proposed optimal economic dispatch and PV system control strategies, it can improve the control performance for both transient and steady-state responses thereby enabling the maximum power to be extracted from the PV. Consequently, the PV power is maximized, which allows the ESS to use less power and sell the surplus to external power sources, which means the proposed method decreases the nanogrid operation costs. Furthermore, this performance is verified via nanogrid simulations and PV experimental kit.

PV system control↗

High Throughput Electrochemical Screening of Phosphate-Rich Nonflammable Electrolytes in Lithium-Ion Batteries

Frequent fires and explosions in lithium-ion batteries (LIBs) used in grid energy storage systems (ESS) highlight the necessity of revisiting nonflammable phosphate electrolytes as alternatives to the currently used flammable carbonates. However, previous studies have shown the difficulty of integrating phosphate solvents into LIB electrolytes due to compatibility issues with graphite. In this work, we developed a high-throughput (HTP) electrochemical characterization method, akin to pH test paper, to rapidly screen potential phosphate electrolytes and graphite materials. Through HTP screening, we identified 101 promising combinations out of 1,740. This number was reduced to 26 after testing in Li/Graphite half cells. The optimized phosphate-rich electrolyte (60 v% phosphate) with cosolvents demonstrated 300 stable cycles at 0.1 C in Graphite/LiFePO 4 (LFP) full cells with thick electrodes (∼3.0 mAh cm −2 ), surpassing prior research findings. This unique HTP method provides a powerful tool to expedite the development of safe LIBs for ESS applications.

25 ENERGY STORAGE↗

The Power and Energy Storage Systems Toolbox -- PSTess v.1.0

The Power and Energy Storage Systems Toolbox (PSTess) is a MATLAB-based computing package for dynamic simulation and analysis of utility-scale battery storage systems. This codebase is a fork of the Power Systems Toolbox Version 3.0, developed at Rensselaer Polytechnic Institute (RPI) and Cherry Tree Scientific Software. While PSTess shares a common lineage with PST, it is a substantially different application. As the name implies, the main distinguishing characteristic of PSTess is its ability to model inverter-based energy storage systems (ESS). The model that enables this is called ess.m, and it serves the dual role of representing ESS operational constraints and the generator/converter interface. With PSTess, the generator/converter interface is modeled as a controllable current source with the ability to modulate both active and reactive current. The model ess.m permits four-quadrant modulation, which allows it to represent a wide variety of inverter-based resources beyond energy storage when paired with an appropriate supplemental control model. Examples include utility-scale photovoltaic (PV) power plants, type 4 wind plants, and static synchronous compensators (STATCOM). This capability is especially useful for modeling hybrid plants that combine energy storage with renewable resources. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8322 O

Elliott, RyanT.↗

Probabilistic Grid Reliability Analysis with Energy Storage Systems

SAND2025-12025O The Probabilistic Grid Reliability Analysis with Energy Storage Systems (ProGRESS) software tool is an open-source tool for assessing the resource adequacy of the evolving electric power grid integrated with energy storage systems (ESS). This tool uses a simulation engine to create diverse scenarios that test the limits of the modern power grid consisting of a high-volume ESS and variable energy resources (VER). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nguyen, Tu↗

Dataset for "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantification" Willard et al. (2025).

This data release provides all data and code used in the paper " "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantifications" Willard et al. (2025)" to model stream temperature, evaluate, and assess results. The associated manuscript explores the effect of different ensemble construction techniques across different common machine learning (ML) architectures for predictions in unmonitored basins. Modeling was done using long short-term memory (LSTM), gated recurrent unit (GRU), temporal convolution network (TCN), and extreme gradient boosting (XGBoost) models, and stream site coverage spans 1362 locations across the conterminous United States. The ensemble construction techniques investigated include ensemble by random weight initialization, differing hyperparameters, different random subsets of training data, different subselections of input features, different architectures, and Monte Carlo Dropout. The data is organized into these items items:Code repository and data for the paper " "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantifications" Willard et al. (2025).Code: stream_temp_ml_regionalization.zip contains the code repositoryData to run the code:- data_dir.zip -- contains all files that should be moved to the "DATA_DIR" variable defined in the "set_env_vars.sh" script in the code repository- metadata_dir.zip -- contains all files that should be moved to the "METADATA_DIR" variable defined in the "set_env_vars.sh" script in the code repositoryData produced by the code and used in the paper:- outputs_dir.zip - contains model output and results (outputs_dir/results), model weights (outputs_dir/models), and all other outputs used for the paper including feature importances.To cite this code, please use the following BibTeX or MLA entries:bibtex:@misc{willard2025streamensembles,author = {Jared Willard and Charuleka Varadharajan},title = {Dataset for "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantification"},year = {2024},doi = {10.15485/2527393},publisher = {ESS-DIVE Repository},url = {https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2527393}}MLA: Willard, Jared, et al. Dataset for "Machine Learning Ensembles Can Enhance Hydrologic Predictions and Uncertainty Quantification". 2025. ESS-DIVE Repository, doi:10.15485/2448016.

54 ENVIRONMENTAL SCIENCES↗

Model data for a watershed-scale study in the Portage River Basin (OH) examining the effects of subsurface drainage on the hydrologic response of an agricultural watershed.

This study builds on Rathore et al. (2024, WRR) and investigates the role of artificial tile-drainage on various aspects of watershed hydrological response, with a particular focus on peakflow. The model-data for the original modeling-focused paper (Rathore et al., 2024, WRR) is archived at Rathore et al. (2024, ESS-DIVE). Hence, this model-data archive provides scripts that are specific to this study that includes model updates, processing and analysis scripts. For details and models files of original model, readers are referred to Rathore et al. (2024, ESS-DIVE). The key difference between the model configuration in this study and Rathore et al. (2024, WRR) is that the tile drains are applied to the entire domain, to study the impact of tile-drains on different aspects of hydrological response. Additional scenario considering intensified precipitation after a dry period was also simulated. The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts.

54 ENVIRONMENTAL SCIENCES↗

Development and Analysis of Control Strategies for a 1 MW/3.2 MWh Energy Storage System at Avista Utilities

This report documents the work performed by Pacific Northwest National Laboratory (PNNL) and Washington State University (WSU) supporting an effort to develop control strategies for a 1 MW/3.2 MWh energy storage system (ESS) at Avista Utilities (Avista). The ESS project is funded though the Washington Clean Energy Fund (CEF) program administered by the Washington State Department of Commerce (DOC). A tri-party Cooperative Research and Development Agreement (CRADA), namely the CRADA 360, was created in 2015 to facilitate this work.

25 ENERGY STORAGE↗

The Power and Energy Storage Systems Toolbox–PSTess (V1.0)

This document describes the Power and Energy Storage Systems Toolbox for MATLAB, abbreviated as PSTess. This computing package is a fork of the Power Systems Toolbox (PST). PST was originally developed at Rensselaer Polytechnic Institute (RPI) and later upgraded by Dr. Graham Rogers at Cherry Tree Scientific Software. While PSTess shares a common lineage with PST Version 3.0, it is a substantially different application. This document supplements the main PST manual by describing the features and models that are unique to PSTess. As the name implies, the main distinguishing characteristic of PSTess is its ability to model inverter-based energy storage systems (ESS). The model that enables this is called ess.m , and it serves the dual role of representing ESS operational constraints and the generator/converter interface. As in the WECC REGC_A model, the generator/converter interface is modeled as a controllable current source with the ability to modulate both real and reactive current. The model ess.m permits four-quadrant modulation, which allows it to represent a wide variety of inverter-based resources beyond energy storage when paired with an appropriate supplemental control model. Examples include utility-scale photovoltaic (PV) power plants, Type 4 wind plants, and static synchronous compensators (STATCOM). This capability is especially useful for modeling hybrid plants that combine energy storage with renewable resources or FACTS devices.

97 MATHEMATICS AND COMPUTING↗

IDEAS-Watersheds FY21 Annual Report for July 1, 2020-June 30, 2021

Watersheds play a critical role in our water supply infrastructure and require sustainable management in a changing environment. Sustainable management of watershed systems and their interaction with the built environment rely on understanding the hydrologic and biogeochemical processes that control watershed system dynamics and water availability and quality. The overarching objective of the U.S. Department of Energy’s (DOE’s) Environmental System Science (ESS) program is to advance a robust, predictive understanding of how watersheds function and respond to perturbations as integrated hydrobiogeochemical systems. ESS supports a network of watershed testbeds within the United States where national laboratories and university partners work in interdisciplinary teams to advance watershed system science for energy.

54 ENVIRONMENTAL SCIENCES↗

Safe Electrolytes for Batteries

The demand for reliable and safe lithium-ion batteries (LIBs) for electric vehicles (EVs) and energy storage systems (ESS) necessitates the exploration of nonflammable phosphorus-based electrolytes as alternatives to the traditional flammable carbonate-based ones. However, integrating phosphorus-based electrolyte poses challenges, including capacity fading and compatibility issues with graphite material. Here, a high-throughput (HTP) electrochemical characterization method, similar to PH test paper, is introduced to fast screen compatible phosphorus-based electrolyte for use with graphite. Among 1,740 combinations of phosphorus-based electrolytes and graphite materials, 101 promising combinations are identified for further evaluation. These identified phosphorus-based electrolytes and graphite materials are evaluated and optimized in Li/Graphite half-cells and Graphite/LiFePO 4 (LFP) full-cells using commercial-level electrodes. The desolvation energy of a complex with one Li+ and four solvent molecules of phosphate or carbonate is calculated by density functional theory (DFT). Key parameters such as viscosity, ionic conductivity, and flammability of the electrolytes are thoroughly tested and optimized. The modified phosphate-dominant electrolyte (2 M LiFSI TEP/DME/EC (6/2/2, volume ratio) + 5 wt.% VEC + 5 wt.% FEC) demonstrates excellent thermal stability with lithiated graphite and showcases superior cycling performance in the Graphite/LFP full cell, surpassing prior research findings in phosphate-dominant electrolytes. By the rapid HTP screening and identification of compatible electrolyte-graphite combinations, this approach contributes to expediting the development of safer LIBs for EVs and ESS.

25 ENERGY STORAGE↗

Lithium-Ion Battery Design for Grid-Scale Energy Storage App

A software that delivers parameters from energy storage system (ESS) to container, rack, module and single cell design, as well as data analysis on arbitrage energy and frequency regulation of ESS in different regions, has been developed. The Lithium-ion Battery Design for Grid-scale Energy Storage App V1.0 has the capability to output the system, module and cell design with the energy, power, capacity, group method, cost of single cell, and single cell test protocol which break down from input energy storage system data in different regions. The default chemistry of the battery is LiFePO4 and graphite. The energy density of the graphite/LiFePO 4 pouch cell ranges from 100 Wh/kg to 200 Wh/Kg in the software. Graphite/LiFePO 4 pouch cell (up to 1Ah in lab) manufacturing line is also built and can be used to evaluate the test protocol, moreover, for electrolyte evaluation in other ESMI seedling projects. The software enables rapid prototyping to accelerate energy storage research, development, and manufacturing.

Liu, Dianying↗