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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Conformal PEDOT Coating Enables Ultra-High-Voltage and High-Temperature Operation for Single-Crystal Ni-Rich Cathodes

Single-crystal Ni-rich Li[Ni x Mn y Co 1-x-y ]O 2 (SC-NMC) cathodes represent a promising approach to mitigate the cracking issue of conventional polycrystalline cathodes. However, many reported SC-NMC cathodes still suffer from unsatisfactory cycling stability, particularly under high charge cutoff voltage and/or elevated temperature. Herein, we report an ultraconformal and durable poly(3,4-ethylenedioxythiophene) (PEDOT) coating for SC-NMC cathodes using an oxidative chemical vapor deposition (oCVD) technique, which significantly improves their high-voltage (4.6 V) and high-temperature operation resiliency. The PEDOT coated SC LiNi 0.83 Mn 0.1 Co 0.07 O 2 (SC-NMC83) delivers an impressive capacity retention rate of 96.7% and 89.5% after 100 and 200 cycles, respectively. Significantly, even after calendar aging at 45 degrees C and 4.6 V, the coated cathode can still retain 85.3% (in comparison with 59.6% for the bare one) of the initial capacity after 100 cycles at a 0.5 C rate. Synchrotron X-ray experiments and interface characterization collectively reveal that the conformal PEDOT coating not only effectively stabilizes the crystallographic structure and maintains the integrity of the particles but also significantly suppresses the electrolyte's corrosion, resulting in improved electrochemical/thermal stability. Our findings highlight the promise of an oCVD PEDOT coating for single-crystal Ni-rich cathodes to meet the grand challenge of high-energy batteries under extreme conditions.

25 ENERGY STORAGE↗
DOE OSTI2026

High-Voltage Sodium–Metal Batteries with Asymmetric Fluoroalkoxylated Organoborate Anion Chemistry

The high reactivity of sodium (Na) metal restricts its compatibility to ether-based electrolytes, while the poor oxidative stability of ethers precludes their coupling to high-voltage cathodes, fundamentally limiting the operating voltage and energy density of sodium–metal batteries (SMBs). We present here a coordination-asymmetry strategy to reconcile this thermodynamic mismatch by generating in situ an asymmetric fluoroalkoxylated organoborate anion, [FB(OCH(CF 3 ) 2 ) 3 ] − (BOF – ), via a Lewis acid–base adduct reaction in ether electrolyte. The asymmetric ligand architecture differentiates oxidative and fluorination pathways: oxidizable B–O moieties mediate controlled interfacial reconstruction, whereas the terminal B–F units supply fluorine for chemical passivation. This self-adaptive chemistry yields nanoscale, conformal, compositionally graded interphases: a boron-oxide/boron-oxycarbide-rich cathode-electrolyte interphase (CEI) that mitigates ether oxidation and a bilayered inorganic–organic solid–electrolyte interphase (SEI) that regulates Na deposition. The nanostructured interphases enable highly reversible Na plating/stripping with an average Coulombic efficiency (CE) of 99.98% and sustain stable 4.3 V operation of anode-free SMBs in oxidation-prone ether electrolytes. Furthermore, this work establishes asymmetric boron coordination as a molecular-level design principle for creating chemically adaptive interphases that overcome the redox asymmetry in energy-dense electrochemical systems.

Anions↗
DOE OSTI2022

Additive engineering for robust interphases to stabilize high-Ni layered structures at ultra-high voltage of 4.8 V

Nickel-rich layered cathode materials promise high energy density for next-generation batteries when coupled with lithium metal anodes. However, the practical capacities accessible are far less than the theoretical values due to their structural instability during cycling, especially when charged at high voltages. Here we demonstrate that stable cycling with an ultra-high cut-off voltage of 4.8 V can be realized by using an appropriate amount of lithium difluorophosphate in a common commercial electrolyte. The Li||LiNi 0.76 Mn 0.14 Co 0.10 O 2 cell retains 97% of the initial capacity (235 mAh g -1 ) after 200 cycles. The cycling stability is ascribed to the robust interphase on the cathode. It is formed by lithium difluorophosphate decomposition, which is facilitated by the catalytic effect of transition metals. The decomposition products (Li 3 PO 4 and LiF) form a protective interphase. This suppresses transition metal dissolution and cathode surface reconstruction. It also facilitates uniform Li distribution within the cathode, effectively mitigating the strain and crack formation.

25 ENERGY STORAGE↗
DOE OSTI2024

Electrochemical reactivity and passivation of organic electrolytes at spinel MgCrMnO 4 cathode interfaces for rechargeable high voltage magnesium-ion batteries

Magnesium transition metal oxides such as MgCr 2−x Mn x O 4 are promising high-voltage and high-capacity cathode materials for rechargeable magnesium batteries (RMBs). Understanding and improving the chemical and electrochemical stability of the cathode–electrolyte interface (CEI) has been the primary technical emphasis to enable this category of cathode materials, which has been significantly underexplored. Herein, in this study, we focus on investigating the fundamental mechanism of parasitic reactions at the charged surface of the high-voltage MgCrMnO 4 model cathode with different organic electrolytes. The aim is to reveal the underlying effect of anions and solvents responsible for the passivation behavior of the cathode by using three exemplary anions: [(CF 3 SO 2 ) 2 N] − (TFSI − ), Al[OC(CF 3 ) 3 ] 4 − (TPFA − ), and [CB 11 H 12 ] − (MC) and three solvents: diglyme (G2), triglyme (G3), and 3-methoxypropylamine (MPA). High precision leakage current measurements during potentiostatic hold reveal that the electrolyte solvent chemistry has a more profound impact than anion's on the passivation of the MgCrMnO 4 cathode surface during deintercalation of Mg 2+ . X-ray photoelectron spectroscopy exhibits the differences in CEI composition. Amine solvents like MPA show poor passivation due to a higher degree of solvent decomposition, while the thin and anion-derived CEI in glyme-based electrolytes is directly linked with the better passivation behavior on the cathode. Furthermore, we leverage the knowledge from these findings to modify the electrolyte structure by adding a solvent additive, with the goal of reducing the parasitic reaction.

25 ENERGY STORAGE↗
DOE OSTI2025

Sizing and Location Selection of Medium‐Voltage Back‐to‐Back Converters for DER‐Dominated Distribution Systems

Medium‐voltage back‐to‐back (MVB2B) converters can connect two distribution systems and quantifiably transfer power between them. This function can enable the MVB2B converter to exchange distributed energy resource (DER)‐generated power between two systems and bring significant value to enhancing distribution system DER adoption. Our previous work analysed and demonstrated the value MVB2B converter can bring to DER integration. As continuous work, this paper presents a methodology that helps address the MVB2B converter sizing and location selection problem in distribution systems with high DER penetrations. The proposed methodology aims to address three critical problems for MVB2B converter implementation in the real world: (1) which distribution systems are better to be connected, (2) what converter size is appropriate for connecting the distribution systems, and (3) where the optimal connection points are in the systems for connecting the MVB2B converter. The proposed methodology has been demonstrated by case studies that include various scenarios involving distribution systems with different dominated load types and high photovoltaic penetrations. The results demonstrate that selecting the optimal converter size based on net revenue and time of return considerations leads to a balance between maximizing energy savings and minimizing financial payback periods. Furthermore, feeder pair selection based on load profile standard deviation effectively identifies systems that derive the greatest value from MVB2B integration. Finally, an optimized connection point selection approach using a voltage load sensitivity matrix ensures minimal system impact while facilitating efficient power exchange. These findings provide practical insights for the real‐world deployment of MVB2B converters to enhance DER hosting capacity and improve grid resilience.

14 SOLAR ENERGY↗
DOE OSTI2021

Voltage cycling process for the electroconversion of biomass-derived polyols

Electrification of chemical reactions is crucial to fundamentally transform our society that is still heavily dependent on fossil resources and unsustainable practices. In addition, electrochemistry-based approaches offer a unique way of catalyzing reactions by the fast and continuous alteration of applied potentials, unlike traditional thermal processes. In this work, we show how the continuous cyclic application of electrode potential allows Pt nanoparticles to electrooxidize biomass-derived polyols with turnover frequency improved by orders of magnitude compared with the usual rates at fixed potential conditions. Moreover, secondary alcohol oxidation is enhanced, with a ketoses-to-aldoses ratio increased up to sixfold. The idea has been translated into the construction of a symmetric single-compartment system in a two-electrode configuration. Its operation via voltage cycling demonstrates high-rate sorbitol electrolysis with the formation of H 2 as a desired coproduct at operating voltages below 1.4 V. The devised method presents a potential approach to using renewable electricity to drive chemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Wideband precision stabilization of the -18.6kV retarding voltage for the KATRIN spectrometer

The Karlsruhe Tritium Neutrino Experiment (KATRIN) measures the effective electron anti-neutrino mass with an unprecedented design sensitivity of 0.2 eV (90 % C.L.). In this experiment, the energy spectrum of beta electrons near the tritium decay endpoint is analyzed with a highly accurate spectrometer. To reach the KATRIN sensitivity target, the retarding voltage of this spectrometer must be stable to the ppm (1 × 10 -6 ) level and well known on various time scales (μs up to months), for values around -18.6 kV. A custom-designed high-voltage regulation system mitigates the impact of interference sources in the absence of a closed electric shield around the large spectrometer vessel. In this article, we describe the regulation system and its integration into the KATRIN setup. Independent monitoring methods demonstrate a stability within 2 ppm, exceeding KATRIN's specifications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Modular Isolated Soft-Switching Medium Voltage String Inverter for Large-Scale PV Farm

This paper presents a single-stage modular isolated soft-switching medium voltage string inverter (MVSI) with tri-port configuration to interconnect PV and storage to medium voltage (MV) grid. The modular MVSI provides advanced functionalities such as energy storage elements integration without additional converters, connection to MV grid resulting in lower distribution losses in the PV farm, high-frequency galvanic isolation, independent control of PV, storage and grid power, high modularity and scalability. The topology of the MVSI, operation principle and model-predictive priority-switching (MPPS) control to achieve fast dynamic balancing across stacked modules are discussed. The independent power control is validated in PLECS simulation and the operation of stacked MVSI with MPPS control is verified through Hardware-in-the-loop (HIL) simulation. Here, the hardware prototype of 25 kVA MVSI building block is developed. 18 kW experimental results of single building block verifying tri-ports operation and 20 kW experimental results of two modules stacked operation are presented. A clean sinusoidal waveform with negligibly low THD in both tests is obtained. A low dv/dt of <; 1kV/us and soft-switching are achieved.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous- enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗
DOE OSTI2023

Comprehensive Efficiency Analysis of Seven-Switch Current-Source Inverter Based on Voltage-Boost Function and Genetic Algorithm

This paper investigates the voltage-boost features of the emerging seven-switch current-source inverter (H7-CSI) to improve the efficiency of the CSI-based motor drive system. The switching transient and power loss model of the H7-CSI topology during voltage-boost operation are analyzed in detail. The effects of the boost function on the switching and conduction loss of the H7-CSI topology are investigated. A genetic algorithm has been introduced that makes it possible to optimize the H7-CSI’s modulation index to minimize its power loss. Experimental results for the H7-CSI unit show that this optimization can reduce the power loss by 10.6%.

42 ENGINEERING↗
DOE OSTI2022

Time Sequence Machine Learning-Based Data Intrusion Detection for Smart Voltage Source Converter-Enabled Power Grid

Smart inverters of distributed energy resources can enable cloud computing, condition monitoring, result visualization, remote control, and peer-to-peer energy trading in advanced power systems. However, the advent of data injection attacks in the communication architecture can alter measurement characteristics of power grids and have devastating consequences. In this article, we propose a time sequence machine learning-based anomaly detection methodology for detecting cyber intrusion into control signal setpoints and dc voltage signal measurement bias of the voltage source converter (VSC) in wind generators. We first investigated the effects of four types of denial of service, tampering signal, and stealthy-type data intrusion attacks on smart VSCs and overall wind farms. We then proposed a novel time sequence machine learning-based intrusion detection framework that can be implemented to detect different cyberattacks in the VSCs. The performance of the proposed framework has been compared with that of autoencoder and clustering-based intrusion detection framework. The proposed framework was validated by using the IEEE 39 bus power system in the presence of four wind farms in different locations. Using several metrics for intrusion detection performance, we validated the effectiveness of the proposed framework.

42 ENGINEERING↗
DOE OSTI2021

Equalization of Intensity-Modulated Fiber-Optic Voltage Sensors for Power Distribution Systems

We test fiber-optic voltage sensors based on optical reflection from a piezoelectric transducer. Our specific devices possess a 2 kHz fundamental resonance, and we verify a readily usable frequency band from approximately 10 Hz to 3 kHz, with a dynamic range of 60 dB for a detection system integrating over this entire band. Additionally, we demonstrate a digital signal processing approach to equalize the measured frequency response, enabling accurate retrieval of short-pulse inputs. These results suggest the value and applicability of intensity-modulated fiber-optic voltage sensors for measuring both steady-state waveforms and broadband transients which, coupled with the straightforward and compact design of the sensors, should make them effective tools in electric grid monitoring.

42 ENGINEERING↗
DOE OSTI2021

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops a machine learning based approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurement. The machine learning model is developed by using random forest algorithm. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

advanced metering infrastructure↗
DOE OSTI2023

Load Shedding for Voltage Regulation With Probabilistic Agent Compliance

With the increased observability and controllability of distribution systems, the share of behind-the-meter systems is trending upwards rapidly. As a consequence, the impact of human behaviors on system performance can no longer be ignored and should be reflected in the energy management system models. In this paper, we discuss the problem of distribution system voltage control by active power curtailment where the agent compliance of the load curtailment signal is probabilistic. We discuss the modeling of the optimal voltage control problem with probabilistic agent compliance as a chance-constrained optimization problem, its tractable safe approximation using convex restriction, and a scenario-based mixed-integer reformulation as well as the associated solution method based on augmented Lagrangian method. The numerical simulation on IEEE test system validates the effectiveness of the proposed approach in obtaining high-quality feasible load curtailment signal with low computational cost, which makes it a viable tool for real time decision making.

augmented Lagrangian method↗
DOE OSTI2023

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a two-agent soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak demand reduction. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operations to enhance control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment and reduce peak load demand from feeder's head.

deep reinforcement learning↗
DOE OSTI2023

A Voltage Inference Framework for Real-Time Observability in Active Distribution Grids

Active distribution grids are gaining traction to meet the growing environmental, socio-economic, and sustainability targets. Various advanced smart grid technologies facilitate the integration of Distributed Energy Resources (DERs) by supporting the bi-directional power flow. The limited observability of distribution grids, primarily related to their location at the very edge of power system infrastructure, brings challenges to optimal grid management. Moreover, only a limited number of measurements at regular intervals are usually available. This paper presents a novel inference framework, referred to as “Voltage Inference”, to overcome the observability issues. The proposed framework employs a prediction step based on the Multivariate Taylor series approximation, followed by a corrector step that minimizes the estimation error to infer the otherwise unknown voltages from the available measurements. Furthermore, numerical results on the IEEE 13-bus test feeder validate the accuracy and computational performance of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Online Model-Free Chance-Constrained Distribution System Voltage Control Using DERs

This paper proposes an online data-driven distributed energy resource management system (DERMS) optimization method using chance-constrained formulation to address distribution system voltage regulation. This is achieved via the local sensitivity factor (LSF)-enabled reformulation of the DER control into a linear programming (LP) problem, which is easy and computationally efficient to solve. The LSF is estimated using online measurements and does not need the assumption of node load information. The latter is usually required for existing optimization-based methods but is difficult to obtain in practice. To mitigate measurement uncertainties, a scenario-based chance-constrained formulation is constructed. Compared with other control methods, the results carried out in a realistic distribution system show that the proposed method can effectively eliminate voltage violation issues.

chance-constrained optimization↗
DOE OSTI2021

Voltage-Matched Strings using 3-Terminal Tandems: Fundamentals and End Losses

Strings constructed from 3-terminal tandem (3TT) cells can provide some of the performance benefits of voltage-matching with less cell complexity than strings based on 4-terminal tandem cells. However, the circuitry for a 3TT string can become more complex, making circuit analysis more challenging. Here we illustrate the essential features of single-polarity voltage-matched (VM) 3TT strings using representative examples. End losses are intrinsic to this type of string, but can be reduced by minimizing m and n in the Vtop/Vbot VM ratio m/n, and further mitigated by increasing the string length. This analysis agrees with preliminary experimental results.

3TT↗