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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Malfunction of Television Camera Monitor on Command Module

The command module television camera monitor exhibited loss of horizontal synchronization during the initial usage. This condition cleared and performance of the monitor was normal until the press conference telecast during the transearth coast phase. At that time, the monitor had the same horizontal synchronization problem reported during the initial usage. The horizontal hold control adjustment would not correct the condition. The monitor was turned off for approximately 5 minutes, then turned back on, after which the monitor's picture was normal. The loss of horizontal synchronization was most likely caused by either an intermittent condition in the precision voltage regulator circuit assembly in the low voltage power supply, or the shift of the stable range of the horizontal potentiometer setting when warming up after turn-on.

Source record↗
NASA NTRS1987

Ferroresonant flux coupled battery charger

A battery charger for incorporation into an electric-powered vehicle is disclosed. The charger includes a ferroresonant voltage-regulating circuit for providing an output voltage proportional to the frequency of an input AC voltage. A high frequency converter converts a DC voltage supplied, for example, from a rectifier connected to a standard AC outlet, to a controlled frequency AC voltage which is supplied to the input of the ferroresonant circuit. The ferroresonant circuit includes an output, a saturable core transformer connected across the output, and a first linear inductor and a capacitor connected in series across the saturable core transformer and tuned to resonate at the third harmonic of the AC voltage from the high frequency converter. The ferroresonant circuit further includes a second linear inductor connected between the input of the ferroresonant circuit and the saturable core transformer. The output voltage from the ferroresonant circuit is rectified and applied across a pair of output terminals adapted to be connected to the battery to be charged. A feedback circuit compares the voltage across the output terminals with a reference voltage and controls the frequency of the AC voltage produced by the high frequency converter to maintain the voltage across the output terminals at a predetermined value. The second linear inductor provides a highly reactive load in the event of a fault across the output terminals to render the charger short-circuit proof.

McLyman, Colonel W. T.↗
DOE OSTI2020

Multi-Level Optimal Power Flow Solver in Large Distribution Networks: Preprint

Solving optimal power flow (OPF) problem for large distribution networks incurs high computational complexity. We consider a large multi-phase distribution networks of tree topology with deep penetration of active devices. We divide the network into collaborating areas featuring subtree topology and subareas featuring subsubtree topology. We design a multi-level implementation of the primal-dual gradient algorithm for solving the voltage regulation OPF problems while preserving nodal voltage information and topological information within areas and subareas. Numerical results on a 4,521-node system verifies that the proposed algorithm can significantly improve computational speed without compromising any optimality.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

Performance Evaluation of Distributed Energy Resource Management Systems Using Software- and Hardware-in-the-Loop

Distributed energy resource management systems (DERMS) are an important emerging technology for coordinating distributed energy resources (DERs) integrated in power distribution networks. These solutions implement a software platform to monitor, control, and coordinate DERs in real time to provide aggregate grid services to the electric utility or distribution system operator. To move DERMS technology forward, research and performance validation in a laboratory environment are needed to ensure proper function of DERMS prior to field deployment. This presentation presents a generic hardware-in-the-loop (HIL) platform to evaluate performance of DERMS using software-in-the-loop (SIL) and power HIL. The platform provides realistic testing in a laboratory environment, including accurate modeling of full-scale distribution systems, DERMS software controllers, and at-power distributed energy resources (DERs), such as solar and battery inverters. Two case studies are presented to demonstrate how the platform can be used independently as an integrated development and validation approach for different projects. Laboratory testing results are included to showcase the voltage regulation performance of each study and the benefits of implementing such a platform for DERMS evaluation.

DERMS↗
DOE OSTI2022

Multi-Agent Deep Reinforcement Learning for Realistic Distribution System Voltage Control Using PV Inverters

Over the last few decades, the deployment of distributed solar photovoltaic (PV) systems has increased consistently. High PV penetration could cause adverse effects on the grid, such as voltage violations. This paper proposes a new distributed soft actor-critic based multi-agent deep reinforcement learning (SAC-MADRL) control solution to minimize the PV real power curtailment while keeping the grid voltage in an acceptable range. New reward functions have been designed to coordinate different agents during the learning process, yielding improved convergence. Comparison results with other control methods on a real feeder in western Colorado U.S. with 80% penetration of PVs demonstrate that the proposed method has better capability of effectively regulating voltage while minimizing the PV real power curtailment.

distribution system↗
NASA NTRS2009

Irradiation with molecular hydrogen as an accelerated total dose hardness assurance test method for bipolar linear circuits

High dose rate irradiation with hydrogen stress is proposed as an accelerated total dose test method for bipolar linear circuits. The method is validated across process and circuit technologies with five parts that are commonly used in space: a comparator (LM193 from National Semi-conductor), a voltage regulator (HSYE-117 RH from Intersil), a voltage reference (LT1019 from Linear Technology), a JFET input op amp (OP42 from Analog Devices) and a temperature transducer (AD590 from Analog Devices). The testing technique could rapidly establish an upper bound to the low dose rate response of parts in space and help with the part selection process in the design phase of a mission. The technology dependence and the viability of this technique are qualitatively explored using a physical model describing the dose rate response and the effect of hydrogen in bipolar technologies. The model uses four core processes: 1) space charge effects, 2) free electron/hole pair recombination, hole-hydrogen defect reactions in the oxides and 4) proton depassivation of dangling bonds at the Si/SiO2 interface. Radiation hardness assurance implications are discussed.

Pease, Ron↗
DOE OSTI2020

Impact of High PV Penetration on Voltage Stability

Photovoltaics (PV) are becoming increasingly relevant in modern power systems. With this increase also comes reliability concerns as photovoltaics behave differently than conventional generators. One reliability concern is voltage stability. In this paper, voltage stability of the Austin area in the Electric Reliability Council of Texas (ERCOT) system is studied using dynamic models with varying levels of photovoltaic penetration. The base case is set at 0% renewable penetration. Additional cases include 15% wind penetration and up to 65% photovoltaic penetration. The study results show that voltage/var control capacity is critical to voltage stability, which PV lacks. Voltage regulation of photovoltaics may cause over-voltage and voltage collapse may be more abrupt under high regional photovoltaic penetration.

Till, Jeremy↗
DOE OSTI2021

Deep Reinforcement Learning Enabled Physical-Model-Free Two-Timescale Voltage Control Method for Active Distribution Systems

Active distribution networks are being challenged by frequent and rapid voltage violations due to renewable energy integration. Conventional model-based voltage control methods rely on accurate parameters of the distribution networks, which are difficult to achieve in practice. This paper proposes a novel physical-model-free two-timescale voltage control framework for active distribution systems. To achieve fast control of PV inverters, the whole network is first partitioned into several subnetworks using voltage-reactive power sensitivity. Then, the scheduling of PV inverters in the multiple sub-networks is formulated as Markov games and solved by a multi-agent soft actor-critic (MASAC) algorithm, where each subnetwork is modeled as an intelligent agent. All agents are trained in a centralized manner to learn a coordinated strategy while being executed based on only local information for fast response. For the slower time-scale control, OLTCs and switched capacitors are coordinated by a single agent-based SAC algorithm using the global information with considering control behaviors of the inverters. Particularly, the two-level agents are trained concurrently with information exchange according to the reward signal calculated from the data-driven surrogate model. Comparative tests with different benchmark methods on IEEE 33-and 123-bus systems and 342-node low voltage distribution system demonstrate that the proposed method can effectively mitigate the fast voltage violations and achieve systematical coordination of different voltage regulation assets without the knowledge of accurate system model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Distribution Grid Management in the Presence of Distributed Energy Resources

The global concerns over climate change, government policies, and incentives in support of distributed energy resources (DERs) are accelerating the growth of DERs in distribution networks. The growth in DER penetration levels can create various issues such as over/under voltages, reverse power flows, overloading, and protection miscoordination. State-of-the-art grid automation solutions such as advanced distribution management systems (ADMS) and distributed energy resource management systems (DERMS) can leverage the DERs to improve distribution grid operations. The ADMS offers advanced grid management functions such as Volt-VAR optimization (VVO), fault management, and outage management to the distribution operator to improve situational awareness and optimize network operations. The DERMS solutions aggregate the small-scale BTM DERs to provide grid services including demand response, voltage regulation, and situational awareness. In this presentation, distribution grid management approaches in the presence of DERs using ADMS and DERMS will be discussed.

ADMS↗
DOE OSTI2020

Optimal Energy Dispatch of Distributed PVs for the Next Generation of Distribution Management Systems

Advanced Distribution Management Systems (ADMS) are being widely adopted by electric utilities for managing and optimizing the operations of their distribution systems. Distributed photovoltaic (DPV) systems with smart inverters can be controlled to adjust active power and reactive power outputs, and they are envisioned to become a part of (centrally or distributed) controllable assets managed by the ADMS for optimizing grid operations. This paper proposes an optimal energy dispatch strategy controlling DPV systems for regulating distribution voltages and achieving conservation voltage reduction. A convex optimization model is proposed with the use of linearized power flow, and the gradient projection algorithm is used to solve the optimal active power and reactive power outputs of smart inverters. The proposed optimal energy dispatch is implemented using an open-source ADMS platform, and simulation results have demonstrated the effectiveness of the proposed approach on improving distribution grid operations.

42 ENGINEERING↗
DOE OSTI2024

Online Model-Free DER Dispatch Via Adaptive Voltage Sensitivity Estimation and Chance Constrained Programming

This paper proposes an online data-driven distributed energy resource management system (DERMS) for distribution system optimal DER dispatch as well as voltage regulation. Here, the key innovation is to leverage the Local Sensitivity Factor (LSF) for transforming the DER control into a computationally efficient linear programming (LP) problem. By taking real-time measurements, the estimation of LSF eliminates the need for an accurate distribution system model as well as full nodal load information, which is difficult to achieve in practice. A robust recursive least squares method is also developed to ensure the robust estimation of LSF, which is initialized using reasonable values from model-derived LSFs. This allows the system to adapt to changing operational conditions effectively. A scenario-based, chance-constrained framework is further employed to ensure voltage remains within acceptable limits in the presence of measurement and estimation uncertainties. Test results on a real-world, 759-node distribution network located in western Colorado, U.S., validate the effectiveness and robustness of the proposed control approach and demonstrate its superior performance as compared to alternative methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Multi-Task Reinforcement Learning for Distribution System Voltage Control With Topology Changes

This letter proposes a multi-task deep reinforcement learning (DRL) approach for distribution system voltage regulation considering topology changes via PV smart inverter control. The key idea is to encode the topology as an additional state for the DRL and leverage the multi-task learning scheme for joint learning of all task control policies. Unlike other DRL-based methods, our approach is robust to different topologies. Comparison results on the modified IEEE 123-node system demonstrate the enhanced robustness of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Visibility-enhanced model-free deep reinforcement learning algorithm for voltage control in realistic distribution systems using smart inverters

Increasing integration of distributed solar photovoltaic (PV) into distribution networks could result in adverse effects on grid operation. Traditional model-based control algorithms require accurate model information that is difficult to acquire and thus are challenging to implement in practice. Here, this paper proposes a surrogate model-enabled grid visibility scheme to empower deep reinforcement learning (DRL) approach for distribution network voltage regulation using PV inverters with minimal system knowledge. In contrast to existing DRL methods, this paper presents and corroborates the adverse impact of missing load information on DRL performance and, based on this finding, proposes a surrogate model methodology to impute load information utilizing observable data. Additionally, a multi-fidelity neural network is utilized to construct the DRL training environment, chosen for its efficient data utilization and enhanced robustness to data uncertainty. The feasibility and effectiveness of the proposed algorithm are assessed by considering DRL testing across varying degrees of observable load information and diverse training environments on a realistic power system.

14 SOLAR ENERGY↗
DOE OSTI2020

Performance Evaluation of Distributed Energy Resources Management System via Advanced Hardware-in-the-Loop Simulation: Preprint

This paper presents an advanced hardware-in-the-loop (HIL) platform to evaluate the performance of voltage regulation coordinated across advanced distribution management systems (ADMS), distributed energy management system (DERMS), and DERs. The HIL platform provides realistic laboratory testing, including accurate modeling of the real-world distribution system from a utility partner, real controller (ADMS and DERMs) and power (DERs) hardware, and standard communications protocols. The test results show proper functionalities of the integrated platform and performance of the peak load management of coordinated control systems. Based on the laboratory testing, the utility can set up the same grid automation system to manage DERs to achieve system-level control and operation objectives (e.g., peak load management), thus derisking potential issues (e.g., instability) for field deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Innovative Pathways to Net Zero Emissions: Subnational Strategies for Distributed Solar Deployment to Improve Grid Quality and Reduce Energy Costs in Argentina

Through Net Zero World, the National Renewable Energy Laboratory (NREL), the National Energy Secretariat of Argentina, La Pampa's Energy and Mining Secretariat, Pampetrol, and the Administracion Provincial de Energia de La Pampa (APELP) conducted an integrated analysis of the power system of the La Pampa province in Argentina. The study assessed the impact that solar and battery energy storage systems could have on the region grid's reliability and electricity costs, providing insights into long-term decarbonization strategies across Argentina. The analysis demonstrated that these systems are expected not only to help with decarbonization efforts but also to bolster grid resiliency, reduce line losses, and improve voltage regulation while lowering electricity costs. The paper offers a replicable framework for similar studies across other Argentine provinces, which could inform a national grid reliability plan and promote regional coordination. Such coordination will play a key role in supporting a nationwide clean energy transition as Argentina increases its share of renewable energy. By coordinating subnational energy plans with national strategies, Argentina can secure a resilient clean energy future, leveraging the substantial renewable resources available across its provinces.

14 SOLAR ENERGY↗
DOE OSTI2023

Adaptive primal–dual control for distributed energy resource management

With the increased adoption of distributed energy resources (DERs) in distribution networks, their coordinated control with a DER management system (DERMS) that provides grid services (e.g., voltage regulation, virtual power plant) is becoming more necessary. One particular type of DERMS using primal–dual control has recently been found to be very effective at providing multiple grid services among an aggregation of DERs; however, the main parameter, the primal–dual step size, must be manually tuned for the DERMS to be effective, which can take a considerable amount of engineering time and labor. To this end, we design a simple method that self-tunes the step size(s) and adapts it to changing system conditions. Additionally, it gives the DER management operator the ability to prioritize among possibly competing grid services. Here we evaluate the automatic tuning method on a simulation model of a real-world feeder in Colorado with data obtained from an electric utility. Through a variety of scenarios, we demonstrate that the DERMS with automatically and adaptively tuned step sizes provides higher-quality grid services than a DERMS with a manually tuned step size.

24 POWER TRANSMISSION AND DISTRIBUTION↗