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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Designing Advanced Electrolytes for High-Voltage High-Capacity Disordered Rocksalt Cathodes

Lithium (Li)-excess transition metal oxide materials which crystallize in the cation-disordered rock salt (DRX) structure are promising cathodes for realizing low-cost, high-energy-density Li batteries. However, the state-of-the-art electrolytes for Li-ion batteries cannot meet the high-voltage stability requirement for high-voltage DRX cathodes, thus new electrolytes are urgently demanded. It has been reported that the solvation structures and properties of the electrolytes critically influence the performance and stability of the batteries. In this study, the structure–property relationships of various electrolytes with different solvent-to-diluent ratios are systematically investigated through a combination of theoretical calculations and experimental tests and analyses. This approach guides the development of electrolytes with unique solvation structures and characteristics, exhibiting high voltage stability, and enhancing the formation of stable electrode/electrolyte interphases. These electrolytes enable the realization of Li||Li 1.094 Mn 0.676 Ti 0.228 O 2 (LMTO) DRX cells with improved performance compared to the conventional electrolyte. Specifically, Li||LMTO cells with the optimized advanced controlled-solvation electrolyte deliver higher specific capacity and longer cycle life compared to cells with the conventional electrolyte. Additionally, the investigation into the structure–property relationship provides a foundational basis for designing advanced electrolytes, which are crucial for the stable cycling of emerging high-voltage cathodes.

25 ENERGY STORAGE↗
DOE OSTI2021

Model-Free Voltage Control of Active Distribution System with PVs Using Surrogate Model-Based Deep Reinforcement Learning

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage control performance, but this is difficult to obtain in practice. This paper proposes a physical-model-free voltage control method based on a surrogate-model-enabled deep reinforcement learning approach. Specifically, a surrogate model is trained in a supervised manner using the recorded limited number of historical data to learn the relationship between the power injections and voltage fluctuations of each node. Then, the deep reinforcement learning algorithm is applied to learn an optimal control strategy from the experiences obtained by continuous interactions with the surrogate model. The proposed method can achieve physical-model-free control of unbalanced distribution network and inform real-time decisions to deal with fast voltage fluctuations caused by the rapid variation of PV generation. Simulation results on an unbalance IEEE 123-bus system show that the proposed method can achieve similar performance as that of perfect physical-model-based approaches while being advantageous over other traditional methods.

active distribution network↗
DOE OSTI2024

Multifunctional nitrile additives for inducing pseudo-concentration gel-polymer electrolyte: Enabling stable high-voltage lithium metal batteries

High-voltage lithium metal batteries (LMBs) are promising for next-generation high-energy storage systems. Unfortunately, their implementation has been severely plagued by the interfacial instability between the high-voltage cathodes/lithium metal (LM) anodes and electrolytes. To tackle these challenges, a novel nitrile additive, 1,4-dicyanobenzene (DCB) (Synonyms: terephthalonitrile), is added to the in situ polymerized pentaerythritol tetraacrylate-based gel polymer electrolyte (GPE). The DCB additive, as demonstrated both theoretically and experimentally, plays a crucial role in altering the Li+ coordinated solvation structure within the GPE. This alteration leads to the formation of a pseudo-concentrated electrolyte with a tightly packed Li+ cluster, expanding the electrochemical stability window of the electrolyte. Moreover, the DCB-included GPE significantly improves its compatibility with both LM anode and high-voltage cathode, attributed to the modified solvation structure and the generated LiF-rich electrolyte/electrode interphases. Accordingly, the GPE enables stable cyclic performance of LMBs based on a 4.9 V LiNi 0.5 Mn 1.5 O 4 cathode at a low relative negative/positive ratio of 4, achieving a high reversible capacity of 123.8 mAh g -1 with a capacity retention of 87.7% over 500 cycles at 0.5 C. This work provides new insights into enhancing the cyclability of high-voltage LMBs via the synergistic effect of additives and GPE.

25 ENERGY STORAGE↗
DOE OSTI2024

Multi-agent voltage control in distribution systems using GAN-DRL-based approach

Active distribution grids can experience voltage fluctuations and violations due to the high penetration of variable distributed energy resources (DERs). These problems might occur because of the uncertain and variable generation natures of these resources, especially solar photovoltaic resources, during panel shadowing scenarios. Volt-VAR control (VVC) is an efficient method that controls the reactive power set-points of the inverters to regulate the voltage of distribution grids. Although several VVC approaches have been proposed recently, the performance of these approaches degrades significantly if behind-the-meter solar generation data are unobservable/missing. Therefore, it is necessary to impute missing/unobservable PV data accurately to be utilized in VVC approaches. Further, this paper proposes a model-free, data-driven, centrally trained, and decentrally executed multi-agent deep reinforcement learning-based VVC architecture to regulate the voltage of distribution networks. A generative adversarial network (GAN) is incorporated to impute the unobservable PV data accurately, which improves the performance of the proposed control architecture. The proposed multi-agent-soft-actor–critic algorithm (MASAC)-based VVC technique utilizes the actual PV dataset as well as the imputed dataset from the GAN framework to learn the optimal coordinated control policy for controlling the optimal reactive power set-points of PV inverters. The effectiveness of the proposed approach is analyzed on a modified IEEE 34-bus test case with added PV inverters. The results are compared and analyzed with a base case model with no VVC and VVC with a local droop control approach, genetic algorithm optimization, and a centralized soft actor–critic-based approach. Moreover, the performance of the proposed approach is compared with that of a multi-agent VVC framework without using the PV generation data and load information as the system state. The results illustrate that the proposed method with more state input improves the voltage profile and reduces the power loss of the network across various loading and PV generation scenarios.

14 SOLAR ENERGY↗
DOE OSTI2022

Towards extreme fast charging of 4.6V LiCoO 2 via mitigating high-voltage kinetic hindrance

High-voltage LiCoO 2 (LCO) is an attractive cathode for ultra-high energy density lithium-ion batteries (LIBs) in the 3C markets. However, the sluggish lithium-ion diffusion at high voltage significantly hampers its rate capability. Herein, combining experiments with density functional theory (DFT) calculations, we demonstrate that the kinetic limitations can be mitigated by a facial Mg 2+ +Gd 3+ co-doping method. The as-prepared LCO shows significantly enhanced Li-ion diffusion mobility at high voltage, making more homogenous Li-ion de/intercalation at a high-rate charge/discharge process. The homogeneity enables the structural stability of LCO at a high-rate current density, inhibiting stress accumulation and irreversible phase transition. When used in combination with a Li metal anode, the doped LCO shows an extreme fast charging (XFC) capability, with a superior high capacity of 193.1 mAhg -1 even at the current density of 20C and high-rate capacity retention of 91.3% after 100 cycles at 5C. In conclusion, this work provides a new insight to prepare XFC high-voltage LCO cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2025

Critical Insights into Solvent Choice for High-Voltage Organosulfur Electrolytes

Organosulfur electrolytes are promising candidates for enabling high-voltage cathodes due to their superior oxidative stability compared to conventional carbonate-based systems. However, their viscous nature and inability to passivate the anode necessitate the use of passivating agents and diluents to achieve meaningful charge/discharge rates. In this study, we investigate the use of cyclic fluorinated carbonates (CFCs) to form passivating interphases on electrode surfaces, aiming to optimize electrolyte performance in high-voltage systems. Electrolyte formulations containing 1.2 M LiPF 6 in a CFC:sulfone:1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropylether (TTE) mixture (2/5/3 V/V/V) were assessed in full-cell configurations with a LiNi 0.8 Mn 0.1 Co 0.1 O 2 (FCG-NMC) cathode and a 4.5 V upper cutoff potential. The results reveal that 3-3-3-trifluoropropylene carbonate (TFPC) combined with ethyl methyl sulfone (EMS) optimizes electrolyte performance, resulting in lower resistance buildup and reduced capacity loss compared to commercial electrolytes. We also explore the failure mechanisms of several carbonate/sulfone mixtures and identify key considerations for electrolyte compatibility in high-voltage systems. TFPC enhances cycling stability and lowers overall cell resistance, while fluoroethylene carbonate (FEC) formulations, despite higher ionic conductivity, fail to form adequate passivation layers, leading to rapid capacity loss. Additionally, EMS provides superior physical properties that avoid common failure modes seen with other sulfone solvents like methyl isopropyl sulfone and tetramethylene sulfone. Furthermore, this study underscores the importance of carefully selecting passivating carbonates and sulfone solvents to improve electrolyte performance and expand the viability of high-voltage electrolyte systems.

LiNi0.8Mn0.1Co0.1O2 cathode↗
DOE OSTI2023

High-Voltage Potassium Hexacyanoferrate Cathode via High-Entropy and Potassium Incorporation for Stable Sodium-Ion Batteries

Prussian blue analogues (PBAs) used as sodium ion battery (SIB) cathodes are usually the focus of attention due to their three-dimensional open frame and high theoretical capacity. Nonetheless, the disadvantages of a low working voltage and inferior structural stability of PBAs prevent their further applications. Herein, we propose constructing the K x (MnFeCoNiCu)[Fe(CN) 6 ] (HE-K-PBA) cathode by high-entropy and potassium incorporation strategy to simultaneously realize high working voltage and cycling stability. In this study, the reaction mechanism of metal cations in HE-K-PBA are revealed by synchrotron radiation X-ray absorption spectroscopy (XAS), ex situ X-ray photoelectron spectroscopy (XPS), and in situ Raman spectra. We also investigate the entropy stabilization mechanism via finite element simulation, demonstrating that HE-K-PBA with small von Mises stress and weak structure strain can significantly mitigate the structural distortion. Benefit from the stable structure and everlasting K + (de)intercalation, the HE-K-PBA delivers high output voltage (3.46 V), good reversible capacity (120.5 mAh g –1 at 0.01 A g –1 ), and capacity retention of 90.4% after 1700 cycles at 1.0 A g –1 . Moreover, the assembled full cell and all-solid-state batteries with a stable median voltage of 3.29 V over 3000 cycles further demonstrate the application prospects of the HE-K-PBA cathode.

25 ENERGY STORAGE↗
DOE OSTI2020

Radio frequency and DC high voltage breakdown of high pressure helium, argon, and xenon

Motivated by the possibility of guiding daughter ions from double beta decay events to single-ion sensors for barium tagging, the NEXT collaboration is developing a program of R&D to test radio frequency (RF) carpets for ion transport in high pressure xenon gas. This would require carpet functionality in regimes at higher pressures than have been previously reported, implying correspondingly larger electrode voltages than in existing systems. This mode of operation appears plausible for contemporary RF-carpet geometries due to the higher predicted breakdown strength of high pressure xenon relative to low pressure helium, the working medium in most existing RF carpet devices. In this paper we present the first measurements of the high voltage dielectric strength of xenon gas at high pressure and at the relevant RF frequencies for ion transport (in the 10 MHz range), as well as new DC and RF measurements of the dielectric strengths of high pressure argon and helium gases at small gap sizes. We find breakdown voltages that are compatible with stable RF carpet operation given the gas, pressure, voltage, materials and geometry of interest.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Model-based Cyber-attack Detection for Voltage Source Converters in Island Microgrids

With the upgrading of communication and control in microgrids, cyber threats on the power converters are increasing. Here, in this paper, a novel model-based cyber-attack detection methodology is proposed for each voltage source converter in microgrids. The Harmonics State Space Matrix (H-Matrix) is used to build the closed-loop transfer function, providing model-based estimation with the grid voltage and control reference. Then, the space phase model (SPM) is used to calculate residual to detect cyber-attacks in voltage source converter (VSC). As controller and converter parameters are included in the H-matrix, the proposed method also could detect cyber-attacks when voltage fluctuation occurs in the grid. To verify the feasibility of the proposed method, several attacks targeting VSC in an islanded microgrid are simulated in MATLAB. Simulation and detection results are introduced to demonstrate the resilience and feasibility of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Inverter Controls for Smooth Transition Operation and Voltage Balancing of Networked Microgrids

With increasing penetrations of distributed energy resources (DERs), researchers have extensively studied the formation and networking of microgrids to improve reliability during distribution system outages. However, these operations might require DERs in the microgrids to switch between grid-following (GFL) and grid-forming (GFM) modes of operation. A smooth transition between the operation modes should be ensured to have a stable system operation and to avoid nuisance tripping. Additionally, as we network microgrids, inverter control schemes with voltage-balancing controls are needed for unbalanced distribution networks. This paper presents the design of a GFM and GFL capable inverter control scheme for reliable operation in networked microgrids with mechanisms for 1) smooth transition between the GFL and GFM modes, and 2) negative sequence voltage control for voltage balancing. Using electromagnetic transient (EMT) simulations, the control scheme is first tested on a simple two-source power system using a digital real-time simulator. Next, a real-world distribution feeder with unbalanced loading and multiple DERs is used to demonstrate stable operation during the networking of microgrids with voltage balance support.

distributed energy resources↗
DOE OSTI2021

Grid Voltage Control Analysis for Heavy-Duty Electric Vehicle Charging Stations

This paper presents an analysis of grid voltage control strategies for heavy-duty electric vehicle charging stations. The performance of three voltage control approaches—including power factor control, standardized volt-volt ampere reactive (VAR) curve control, and customized volt-VAR curve control—are investigated and evaluated for three different sizes of charging stations, including a single-port charging station, a midsized three-port charging station, and six-port travel center. The charging stations are placed on multiple locations of four different types of distribution systems to obtain a comprehensive performance analysis of the voltage control approaches under different scenarios. To quantitively compare the performance of the three voltage control approaches, a series of metrics are designed to quantify the performance and contribute to the comprehensive analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Anomaly Detection and Mitigation in FACTS-based Wide-Area Voltage Control Systems using Machine Learning

With the increasing deployment of Flexible AC Transmission System (FACTS) devices in wide-area voltage control systems (WAVCS) for achieving improved voltage stability of bulk power systems, the possibility for cyber attacks on these systems is also increasing. Successful stealthy cyber attacks that are difficult to detect by traditional informational technology (IT)-based cybersecurity solutions or threshold-based bad data detectors can lead to a voltage collapse in power grid. This paper presents the testbed-based attacks implementation and real-time evaluation of machine learning (ML) algorithm for detecting and mitigating stealthy cyber attacks on FACTS-based WAVCS on a hardware-in-the-loop (HIL) testbed. Initially, we discuss the implementation of a fuzzy logic controller (FLC) that controls a Static VAR Compensator (SVC) device deployed in a two-area four-machine Kundur power system for improving transient voltage stability. Later, the ML-based Anomaly Detection and Mitigation (ADM) system is implemented on the cyber-physical HIL testbed to detect and mitigate various stealthy cyber attacks, which are injected in real-time over the wide-area network (WAN). The experimental results show accurate and effective performance of ADM system in detecting and mitigating anomalies while keeping the grid stable and within the system operating limits, as defined by the North America Electric Reliability Corporation (NERC).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Autonomous Voltage Response for Distributed Energy Resources

An implementation of stable droop voltage response for distributed energy resources (DER) is described. The key point is to use a new “autonomously adjusting reference voltage” as described in IEEE Standard 1547-2018. Examples include battery voltage response, a photovoltaic inverter at the end of a long secondary circuit, and 18 photovoltaic inverters on a distribution lateral. Default inverter settings are proposed for DER that would mitigate voltage fluctuations, with or without communications.

Automatic voltage control, distributed power gener↗
DOE OSTI2024

Distributed Coordination of Networked Microgrids for Voltage Support in Bulk Power Grids

The increasing deployment of distributed energy resources (DERs) and microgrids (MGs) in power distribution systems has enabled the adjustment of reactive power consumption as seen at the substation, which can be used to provide voltage support for the bulk power system (BPS). Leveraging this new capability will provide greater resiliency to the power system as a whole. Here, the goal of this paper is to develop and compare three different algorithms, namely distributed optimal power flow, distributed consensus algorithm, and fully decentralized collaborative autonomy for unbalanced distribution systems for microgrid coordination. These algorithms use networked MGs to support the BPS voltage when a contingency at the bulk grid results in abnormally low voltages, which may be a precursor to voltage collapse. Our comparative analysis includes both qualitative and quantitative assessments of the three algorithms and a discussion of the trade-offs between the decentralized and distributed methods in normal and disrupted conditions. Each algorithm was evaluated on the modified IEEE 13-bus system and a real power distribution system at Chattanooga, Tennessee, that encompasses more than 4500 buses. Each algorithms excels differently and may be suited for different scenarios depending on the condition, operations, and priorities of the power and communication systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Voltage positioning using co-optimization of controllable grid assets in radial networks

With increasing penetration of solar PV, some distribution feeders are experiencing highly variable net-load flows and even reverse flows. To optimize distribution systems under such conditions, the scheduling of mechanical devices, such as OLTCs and capacitor banks, needs to take into account forecasted solar PV and actual grid conditions. However, these legacy switching assets are operated on a daily or hourly timescale, due to the wear and tear associated with mechanical switching, which makes them unsuitable for real-time control. Therefore, there is a natural timescale- separation between these slower mechanical assets and the responsive nature of inverter-based resources. In this paper, we present a network admissible convex formulation for holistically scheduling controllable grid assets to position voltage optimally against solar PV. An optimal hourly schedule is presented that utilizes mechanical resources to position the predicted voltages close to nominal values, while minimizing the use of inverter-based resources (i.e., DERs), making them available for control at a faster time-scale (after the uncertainty reveals itself). A convex, inner approximation of the OPF problem is adapted to a mixed-integer linear program that minimizes voltage deviations from nominal (i.e., maximizes voltage margins). Here, the resulting OPF solution respects all the network constraints and is, hence, robust against modeling simplifications. Simulation based analysis on IEEE distribution feeders validates the approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Probabilistic Voltage Sensitivity Analysis to Quantify Impact of High PV Penetration on Unbalanced Distribution System

From an operational and planning perspective, it is important to quantify the impact of increasing penetration of photovoltaics on the distribution system. Most existing impact assessment studies are scenario-based where derived results are scenario specific and not generalizable. Moreover, stochasticity in the temporal behavior of spatially distributed PVs requires a large number of scenarios that increase with the size of the network and the level of penetration. Therefore, we propose a new computationally efficient analytical framework of voltage sensitivity analysis that allows for stochastic analysis of voltage change due to random changes in PV generation. We first derive an analytical approximation for voltage change at any node of the network due to change in power at other nodes in an unbalanced distribution network. The quality of this approximation is reinforced via bounds on the approximation error. Then, we derive the probability distribution of voltage change at a certain node due to random changes in power injections/consumptions at multiple locations of the network. The accuracy of the proposed PVSA is illustrated using a modified version of the IEEE 37 bus test system. As a result, the proposed PVSA can serve as a powerful tool for proactive monitoring/control and ease the computational burden associated with perturbation based cybersecurity mechanisms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Tri-Sectional Approximation of the Shortest Path to Long-Term Voltage Stability Boundary with Distributed Energy Resources

Ensuring long-term voltage stability is critical for reliable operations of power grids. High share of distributed energy resources (DERs) can create complicated system operation modes that may invalidate the traditional long-term voltage stability analysis based on typical operation modes. To address this challenge, this paper investigates how to compute the shortest path to the voltage stability boundary in the DER aggregated load space with large dispersion. Instead of working in the Euclidean space, we establish the analysis and computations on the algebraic power flow manifold to better capture the curvature change of the shortest path along the direction of losing stability. A modified optimal control framework is presented for obtaining the ground-truth of the smooth shortest path on the manifold. To efficiently and accurately solve for the shortest path, we further leverage the geometric features of the power flow manifold and propose a tri-sectional approximation model that is scalable for large-scale systems. Several numerical examples, up to the 1354-bus system, with different DER penetration levels and high dimensional renewable power injection variations are evaluated. The simulation results demonstrate that the tri-sectional approximation achieves high accuracy and efficiency to approximate the shortest path to the voltage stability boundary.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Analytical Models of Frequency and Voltage in Large-Scale All-Inverter Power Systems

Low-order frequency response models for power systems have a decades-long history in optimization and control problems such as unit commitment, economic dispatch, and wide-area control. With a few exceptions, these models are built upon the Newtonian mechanics of synchronous generators, assuming that the frequency dynamics across a system are approximately homogeneous, and assume the dynamics of nodal voltages for most operating conditions are negligible, and thus are not directly computed at all buses. As a result, the use of system frequency models results in the systematic underestimation of frequency minimum nadir and maximum RoCoF, and provides no insight into the reactive power-voltage dynamics. This paper proposes a low-order model of both frequency and voltage response in grid-forming inverter-dominated power systems. The proposed model accounts for spatial-temporal variations in frequency and voltage behavior across a system and as a result, demonstrates the heterogeneity of frequency response in future renewable power systems. Electromagnetic transient (EMT) simulations are used to validate the utility, accuracy, and computational efficiency of these models, setting the basis for them to serve as fast, scalable alternatives to EMT simulation, especially when dealing with very large-scale systems, for both planning and operational studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗