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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Dynamic Distribution System Restoration Strategy for Resilience Enhancement: Preprint

In electric power distribution systems, distributed energy re-sources (DERs) can act as controllable power sources and support utility operators to minimize power outages after ex-treme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influ-ences of extreme events and the capabilities of DERs are dy-namic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/disturbance information and the availabil-ity of DERs. In this paper, we propose a new dynamic distribu-tion system restoration strategy to enhance system resilience against potential hazards. An efficient reconfiguration algo-rithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER opera-tion setpoints based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Enhanced Oblique Decision Tree Enabled Policy Extraction for Deep Reinforcement Learning in Power System Emergency Control

Deep reinforcement learning (DRL) algorithms have successfully solved many challenging problems in various power system control scenarios. However, their decision-making process is usually regarded as black-boxes. Furthermore, how DRL models interact with human intelligence remains an open problem. Thus, this paper proposes a policy extraction framework to extract a complex DRL model into an explainable policy. This framework includes three parts: 1) DRL training and data generation. We train an agent for a specific control task and generate data, which contains the control policy of the agent. 2) Policy extraction. We propose an information gain rate based weighted oblique decision tree (IGR-WODT) for DRL policy extraction. 3) Policy evaluation. We define three metrics to evaluate the performance of the proposed approach. A case study for the under-voltage load shedding problem shows that the IGR-WODT presents a performance enhancement compared with DRL, weighted oblique decision tree, and univariate decision tree. The proposed policy extraction method could provide an intuitive explanation of the neural network decision-making process to the dispatchers when making final decisions on power grid operation. Also, the resulted rule-based controller could replace the deep neural network-based controller in many field edge devices with limited computing resources, providing comparable performance.

deep reinforcement learning↗
DOE OSTI2025

Enabling Technology for Energy Sustainability: Power Electronic Converter Control for Renewables

To ensure high penetration of renewable energy sources into power grids, their interfacing inverters need to be designed to provide grid support functions. Important grid support functions include frequency and voltage support. To this end, the research community has recently invested heavily on grid-forming control pilot projects. Grid forming control aims to replace traditional grid following control, which is based on phase-locked loop and can achieve decoupled real and reactive power control. Here, in this article, we review the state-of-the-art grid following and forming technology and point out some deficiencies in dynamic performance in the widely adopted grid-forming control design. We also examine how to ensure that the vector control capable of decoupled real and reactive power regulation can also be achieved in the grid forming design. This type of design has been prototyped and shown great potential to enable retrofitting of large amounts of grid-following controllers through purely software algorithm update. The technology ensures reliable operation of power grids with high penetration of IBRs, thereby further reducing fossil fueled energy sources and cut down carbon emission.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Robust Adaptive Control for Large-scale Inverter-based Resources with Partial and Complete Loss of Inverters

This article proposes an approach to address the current and the aggregated active power control challenge for large-scale inverter-based resources subjected to partially or completely loss of inverters and grid voltage variations. To address this problem, a distributed active power mechanism is proposed which generates desired inverters current. Then an adaptive mechanism distributes the voltage control input automatically between inverters in response to the partial or complete loss of inverters. An L2-gain-based controller is designed for each inverter to track the desired current and rejects the grid voltage disturbance. Here, simulation results show a significant robust tracking for collective active power and current.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Dynamic Restoration Strategy for Distribution System Resilience Enhancement

In electric power distribution systems, distributed energy resources (DERs) can act as controllable power sources and support utility operators to minimize power outages after extreme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influences of extreme events and the capabilities of DERs are dynamic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/disturbance information and the availability of DERs. In this paper, we propose a new dynamic restoration strategy for distribution systems to enhance system resilience against potential hazards. An efficient reconfiguration algorithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER operation set points based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

US 2023/0182605 A1 Network constraint energy management system for electric vehicle depot charging and scheduling

Network constraint energy management system for electric vehicle (EV) depot charging and scheduling. In an embodiment, a power schedule is received from an economic dispatch application for a charging depot comprising EV charging station(s) and distributed energy resource(s). The power schedule may be simulated on a distribution network model of the charging depot, according to load flow analysis, to determine whether any grid-code violations occur. In response to the detection of violation(s), a constraint may be generated for each violating node, and the economic dispatch application may be re-executed with the constraint(s) to produce a new power schedule, until no violations are detected. When not all load demand can be satisfied by the power schedule, a charging schedule may be adjusted to ensure that critical energy requirements are satisfied. The final power and charging schedules may be used to schedule and control power generation and charging in the charging depot.

Hafiz, Faeza↗
DOE OSTI2022

Benchmarking Real-Time Control Platforms Using a Matlab/Simulink Coder with Applications in the Control of DC/AC Switched Power Converters

In the control of DC/AC switched power converters (SPC), one of the most important aspects to be considered is the selection of the real-time control platform. The real-time control platform must be able to meet the high performance efficiency and regulation requirements of the DC/AC SPC, as these typically operate at switching frequencies in the order of kHz to MHz. For this reason, the hardware characteristics of the ADC and PWM, and the processing capacity of the real-time control platform are of vital importance when implementing advanced digital controllers that maintain voltage and current levels within regulatory standards. In this context, we aimed to perform a comparative study of the computation times of different real-time control platforms when implementing different control strategies for DC/AC switched power converters. We also analyzed the impact of the real-time control platforms on the THD of the voltages generated by the DC/AC switched power converters. With the help of this paper, researchers and developers will have criteria to select which real-time control platform to use in real-time control for DC/AC SPC applications.

42 ENGINEERING↗
DOE OSTI2022

SIW21-95: Hybridizing Synchronous Condensers with Grid-Forming Battery Energy Storage Systems

One of the main challenges associated with deployment of high shares of inverter-based resources (IBRs) in power grid is not only reduced system inertia but also degrading system strength that may cause severe stability impacts. A minimum level of system strength is needed for the power system to remain stable under normal conditions and to return to a steady state condition following a system disturbance. Significant system strength reduction is expected in almost all planned areas for solar and wind generation deployment. Synchronous condensers (SC) have been considered as one main technology to address the system strength issues for the areas with high levels of IBRs. SCs can help improving reliability and resiliency of power system but they do not provide the full range of services needed by power systems for reliable and economic integration of high shares of inverter-coupled variable generation such as PV generation. Services related to active power controls cannot be provided by SCs due to lack of prime mover. Even for provision of reactive power SCs have certain constraints based on their thermal and stability limits. NREL has been conducting research on a hybridized concept that combines SCs with grid forming (GFM) battery energy storage systems (BESS). This super flexible AC transmission system (SuperFACTS) that combines these two technologies in a single plant under the same controller offers a unique scalable set of services to the power system at all levels (transmission, sub-transmission, distribution, islands and isolated microgrids). Depending on use cases, SuperFACTS can be controlled to provide fully dispatchable and flexible operation using energy storage component, provide a full range of existing and future ancillary and reliability services to the grid (similar or better than conventional sources), maintain adequate levels of grid strength and inertia, and provide fault current for proper operation of protection systems. Therefore, this economic and easy to commercialize solution has potential for significant impacts on certain segments of global energy sector. All types of gird services (market based, reliability and resiliency) can be provided by SuperFACTS plants. GFM BESS can act as a self-black start source for each SuperFACTS module, which in turn can act a black start resource for co-located PV and wind power plants, segments of transmission and distribution networks, for conventional power plants, etc. The issue of in-rush currents during black start is addressed by overcurrent capability of SCs. In this paper we describe the results of modeling for SuperFACTS concept.

grid forming↗
DOE OSTI2021

Data-Driven Multi-agent Deep Reinforcement Learning for Distribution System Decentralized Voltage Control with High Penetration of PVs

This paper proposes a novel model-free/data-driven centralized training and decentralized execution multi-agent deep reinforcement learning (MADRL) framework for distribution system voltage control with high penetration of PVs. The proposed MADRL can coordinate both the real and reactive power control of PVs with existing static var compensators and battery storage systems. Unlike the existing DRL-based voltage control methods, our proposed method does not rely on a system model during both the training and execution stages. This is achieved by developing a new interaction scheme between the surrogate modeling of the original system and the multi-agent soft actor critic (MASAC) MADRL algorithm. In particular, the sparse pseudo-Gaussian process with a few-shots of measurements is utilized to construct the surrogate model of the original environment, i.e., power flow model. This is a data-driven process and no model parameters are needed. Furthermore, the MASAC enabled MADRL allows to achieve better scalability by dividing the original system into different voltage control regions with the aid of real and reactive power sensitivities to voltage, where each region is treated as an agent. This also serves as the foundation for the centralized training and decentralized execution, thus significantly reducing the communication requirements as only local measurements are required for control. Comparative results with other alternatives on the IEEE 123-nodes and 342-nodes systems demonstrate the superiority of the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2022

Unleashing the Frequency: Multi-Megawatt Demonstration of 100% Renewable Power Systems with Decentralized Communication-Less Control Scheme

Power systems, which range in size from small microgrids to island systems to large regional grids, are typically managed by a central controller that requires complex communication methods and can be unreliable and pose cyber security risks in certain applications, especially when controlling a larger number of nodes. We propose an inherently robust, scalable method of integration using multiple energy storage systems and distributed energy resources, which does not require any means of dedicated communication. This method moves beyond the paradigm of controlling grid frequency at a fixed value (e.g., 60 Hz), instead allowing the frequency to fluctuate within certain limits (e.g., 59.6-60.4 Hz). With a greater operating range, the frequency can carry necessary information from energy storage systems to highly variable distributed energy resources like photovoltaics, wind, hydro, etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Cascaded systems and methods for controlling energy use during a demand limiting period

A cascaded control system is configured to control power consumption of a building during a demand limiting period. The cascaded control system includes an energy use setpoint generator and a feedback controller. The energy use setpoint generator is configured to use energy pricing data and measurements of a variable condition within the building to generate an energy use setpoint during the demand limiting period. The feedback controller is configured to use a difference between the energy use setpoint and a measured energy use to generate a control signal for building equipment that operate to affect the variable condition within the building during the demand limiting period.

Wenzel, Michael J.↗
DOE OSTI2022

Bending as a control knob for the electronic and optical properties of phosphorene nanoribbons

We have assessed mechanical bending as a powerful controlling tool for the electronic structure and optical properties of phosphorene nanoribbons. We use state-of-the-art density functional approximations in our work. The overall performance of the recently developed meta-generalized gradient approximation (meta-GGA) mTASK [Phys. Rev. Materials 5, 063803 (2021)] functional establishes the method as a useful alternative to the screened hybrid HSE06 for better band gaps of phosphorene nanoribbons. We present a detailed analysis to interpret the optical absorption of bent phosphorene nanoribbons using the GW-Bethe-Salpeter approximation. Finally, we demonstrate the important role of the unoccupied in-gap state and conclude that this in-gap state in armchair nanoribbons introduced by bending can significantly affect the properties of low-energy excitons and add some useful opportunities for applications in optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Online Dynamic Cyber-Attack Diagnosis in Power Electronics Systems Based on Few-Shot Learning

With increasing exposure to software-based sensing and control, power electronics systems are facing higher risks of cyber-physical attacks. To ensure system stability and minimize potential economic losses, it is critical to monitor the operating states and detect those attacks at the early stage. However, anomaly detection and diagnosis of attacks are still challenging, especially when labeled anomaly data is difficult or even infeasible to obtain. To overcome this problem, we propose a Few-Shot Learning (FSL) based approach for cyber-attack diagnosis leveraging the waveform data. To the best of our knowledge, this work is the first attempt at leveraging FSL for cyber-attack diagnosis in power electronics systems. Extensive experimental results demonstrate that our proposed approach can achieve comparable diagnosis accuracy with the state-of-the-art data-driven methods using less than 0.04% of the training samples.

Li, Qi↗
DOE OSTI2022

A Novel Modular, Reconfigurable Battery Energy Storage System: Design, Control, and Experimentation

This paper presents a novel modular, reconfigurable battery energy storage system. The proposed design is characterized by a tight integration of reconfigurable power switches and DC/DC converters. This characteristic enables isolation of faulty cells from the system and allows fine power control for individual cells toward optimal system-level performance. An optimal power management approach is developed to extensively exploit the merits of the proposed design. Based on receding-horizon convex optimization, this approach aims to minimize the total power losses in charging/discharging while allocating the power in line with each cell’s condition to achieve state of-charge (SoC) and temperature balancing. By appropriate design, the approach manages to regulate the power of a cell across its full SoC range and guarantee the feasibility of the optimization problem. Here, we perform extensive simulations and further develop a lab-scale prototype to validate the proposed system design and power management approach.

25 ENERGY STORAGE↗
DOE OSTI2020

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

Grid operators are now considering using distributed energy resources (DERs) to provide distribution voltage regulation rather than installing costly voltage regulation hardware. DER devices include multiple adjustable reactive power control functions, so grid operators have the difficult decision of selecting the best operating mode and settings for the DER. In this work, we develop a novel state estimation-based particle swarm optimization (PSO) for distribution voltage regulation using DER-reactive power setpoints and establish a methodology to validate and compare it against alternative DER control technologies (volt–VAR (VV), extremum seeking control (ESC)) in increasingly higher fidelity environments. Distribution system real-time simulations with virtualized and power hardware-in-the-loop (PHIL)-interfaced DER equipment were run to evaluate the implementations and select the best voltage regulation technique. Each method improved the distribution system voltage profile; VV did not reach the global optimum but the PSO and ESC methods optimized the reactive power contributions of multiple DER devices to approach the optimal solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Impact of toroidal magnetic field direction on integrated ELM-stable operation and divertor power exhaust via boron powder injection in EAST

We report the first in-depth comparison of the impact of toroidal magnetic field direction on solid boron injection used for Edge-Localized Mode (ELM) control, power exhaust, and core high-Z impurity control in the Experimental Advanced Superconducting Tokamak. With favorable ion ∇B drift towards the upper X-point in an upper-single-null configuration, boron injection effectively suppresses ELMs, produces a detachment of the inner divertor target, and leads to improved energy confinement. ELM suppression in this configuration is accompanied by the excitation of an Edge Harmonic Mode. In contrast, with unfavorable ion ∇B drift away from the upper X-point, boron injection also suppresses ELMs but leads to a more symmetric detachment state of both the inner and outer divertor targets, while plasma energy confinement is slightly degraded despite similar boron injection levels; a different low-frequency coherent mode without multiple harmonics is observed. Measurements from toroidally separated views show that the divertor response to boron injection is essentially toroidally symmetric, supporting the use of two-dimensional SOLPS-ITER modeling with a toroidally uniform impurity source. These experimental observations are qualitatively consistent with SOLPS-ITER simulations, which highlight the critical role of E × B drift effects in setting the Bt-dependent in–out asymmetry of detachment and in asymmetrically transporting particles and injected impurities within the scrape-off layer and private-flux region. These findings underscore the importance of drift physics and real-time wall conditioning in controlling low-Z impurity transport and optimizing edge solutions for integrated, ELM-stable, high-performance tokamak operation.

E × B drift↗
DOE OSTI2022

Semiconductor: Supply Chain Deep Dive Assessment

In February 2021, President Biden signed Executive Order (EO) 14017, “America’s Supply Chains,” directing seven executive agencies to evaluate the resilience and security of the nation’s critical supply chains and to craft strategies for six industrial bases that underpin America’s economic and national security. See Sec. 3(b) of E.O. 14017. As part of the one-year response to EO 14017, the U.S. Department of Energy (DOE), through the national laboratories, conducted evaluations of the supply chains that encompass the Energy Sector Industrial Base, with a particular focus on technologies required to decarbonize the U.S. by 2050. This report focuses on one of these technologies, semiconductors, both conventional and wide bandgap (WBG) power electronics (PE). As noted in the 100-Day report, conventional semiconductors are a keystone technology that are essential for the operation of nearly every electronic device, including those that are critical to decarbonization, such as electric vehicles (EVs), industrial and building applications, and electricity generation and end use. In addition, power electronics have been applied to industrial equipment to improve energy efficiency and enhance controllability. Power electronics have also been used to improve the reliability of data centers and critical infrastructure, including the stabilization of the electric grid while subjected to disturbances. Increasingly, power electronics are being used to integrate renewable energy and battery storage systems, enabling new grid services and the development of microgrids. It is estimated that 30% of the electricity used in the U.S. passes through power electronic devices, and studies suggest that this number could reach 80% as power electronics are deployed in more markets. Nearly all forms of electrified transportation will depend on power electronics. Power electronic systems utilize high-capacity semiconductor devices at their core. The continued growth in power electronics depends on sustained innovation in the semiconductor industry.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Design, Deployment, and Characterization of the World’s First Flexible Large Power Transformer

GE Research and its partner Prolec GE have designed, built and deployed in the field the world’s first flexible power transformer. The flexible power transformer is a transmission class 3-phase autotransformer configurable in impedance and in voltage which allows it to serve as a universal spare for multiple units in a given fleet. However, the key innovation in this new concept is the online adjustable leakage impedance which allows the transformer to change its impedance without interrupting the transmission line operation. The flexible power transformer can be designed with up to three low voltage transmission class ratings and up to 12 impedance values changeable both online and offline. This report provides an overview of the design, manufacturing, testing, and commissioning of the 165kV, 60MVA prototype built including the results of the field performance validation tests. The prototype was specified in collaboration with Cooperative Energy, the utility host. It was designed and tested in the factory according to IEEE standard C57.12.00 and followed all protocols for transportation, installation, and commissioning of a power transformer. In addition to the prototype, a flexible protection system capable of automatically adjusting its settings upon the transformer impedance was also developed and deployed in the for testing and validation. On September 3, 2021 the prototype was energized in Cooperative Energy’s substation in Columbia, Mississippi to become the world’s first flexible power transformer in operation. Its performances and impact on the grid operation were demonstrated through different field tests. Results obtained confirm that the impedance of the flexible transformer can be varied under load through its full range, from 4.3% to 9.3%, without adverse impacts on the line operation, the protection system, the transformer stability and health condition. Results also proved that the flexible transformer is very effective in controlling power transfer through the line or load sharing between units operating in parallel. Indeed, it was proven that higher impedances decrease the thruput power of the transformer while lower impedances increase it. Up to 26MW was controllable on a line loading of 45MVA. It was also possible to demonstrate that the variation of the transformer impedance has no effect on the circulating current between units in parallel, except a minor transient during the impedance change. It was also proven that the flexible protection relay can update its protection settings automatically when the impedance change was detected. The prototype has operated continuously for more than 12 months now with a peak load exceeding 50MVA corresponding to >80% of its ONAN power rating. No alarm, trip or sign of failure has been reported by the utility. In addition to the development and deployment of the flexible transformer prototype, investigations were carried out on new nanodielectric fluids to replace the mineral oil used in power transformers with the goal of reducing their footprint and weight. The key parameters that were targeted for improvement included the breakdown voltage to reduce clearances between windings and tank hence the footprint; viscosity and thermal conductivity to increase the cooling efficiency and therefore to reduce the winding material. Several nanodielectric mixtures with mineral oil including with alumina (Al2O3), titania (TiO2) and Borum Nitrate (BN) with different surfactants have been analyzed and tested. Unfortunately, despite encouraging results no nanofluid candidate has been found viable to replace mineral oil. With the formulations tested, breakdown voltages are generally similar to mineral oil at lower particle contents and worse at higher particle contents. Viscosity appreciably increased at particles concertation over 2 wt% and thermal conductivity increased slightly at 5wt% and appears to be 10-15% higher at 10 wt% particle content. It is recommended to continue investigations to find solutions that can help increase the power density of future flexible power transformers. Flexible power transformers can significantly help the future power grid by providing more flexibility and resiliency. Indeed, by providing voltage and impedance flexibility, flexible power transformers reduce the need for multiple spares, hence inventory costs for utilities. With their online controllable impedance, they can provide support to the grid and help manage short-circuit currents, power flow, line congestion, and grid stability which will become more important with higher penetrations of intermittent renewable resources. During the field validation tests, it was demonstrated that up to 26MW was controllable on a line loading of 45MVA when the transformer impedance was varied from its minimum to its maximum range. Also, with the impedance range, the short-circuit currents could be reduced by up to 38% at the load side of the transformer. With its controllable impedance, flexible transformers can be used in future strategies of grid resilience to help better prepare the grid to face forecasted severe events including storms, heat waves and contingencies. The flexible power transformers can also find role in other applications including high voltage transmission cables such as offshore wind farms where solutions for energizing the cables and managing the reactive power are of critical importance. The designed flexible power transformer is now fully validated and ready for commercialization. Further analysis on the benefits of flexible power transformers for grid stability and short-circuit management including current limiting capability, reclosure and line restoration, control of inrush current, sizing of flexible AC components (FACTS) would help its rapid adoption by the industry.

24 POWER TRANSMISSION AND DISTRIBUTION↗