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At least 703 records · Page 39

All sources NASA NTRS DOE OSTI

DOE OSTI2019

A BI-LEVEL APPROACH TO FUTURE POWER SYSTEM CO-OPTIMIZATION WITH HIGH PENETRATION OF RENEWABLE ENERGY AND RESPONSIVE DEMAND

Electricity generation accounts for nearly half of the total CO2 emissions in the United States. For this reason, the development and integration of renewable resources will play an essential role in achieving the societal objective of mitigating climate change through reduction of greenhouse gas emissions. In conjunction with the environmental benefits of renewable energy, the most common renewable sources, such as wind and solar, also increase the uncertainties surrounding generation in power systems, which adds significant challenges to the system operation and planning. The uncertainties and forecasting errors surrounding renewable generation are normally addressed through the use of reserves from traditional generators. At greater levels of renewable penetration, sufficient generator reserves may not be available or economically viable. In contrast, the promise of demand-side resources in this arena lies in the spatially widespread availability, rapid response potential, and lower cost of features that already exist in the system. However, the challenge of responsive demand arises from the need to understand, manage, and incentivize a very large number of resources to participate effectively in efficient operation of the complex power system. Since demand response comes from the distribution system, microgrids as the basic building blocks of future distribution systems will be a critical environment for the study of demand response. To support integration of microgrids with flexible loads in future power systems, the operational mode of power systems will need to evolve. Therefore, it is going to be critical to have new and efficient co-optimization methods for coordination of the various power market participants and the scheduling of resources in the power systems of the future. Motivated by the rapid increase in renewable penetration, the need for effective demand response programs, and a changing system structure, this dissertation seeks to define a new strategy that supports co-optimization of various participants in power systems with emphasis on high renewable penetration and demand response. This strategy has three components; 1) an exploration of the capabilities of different types of demand response programs in a microgrid, 2) development and implementation of a bi-level framework for co-optimization of the main grid with high renewable penetration and a microgrid with demand response capabilities, and 3) expansion of the bi-level framework from a microgrid to a general distribution system to explore the advantages of the bi-level co-optimization approach over the traditional optimization approach. Conclusions of this work illustrate that the stochastic rolling horizon approach could effectively manage the operation of a microgrid with various demand response programs. In addition, the bi-level approach is a promising co-optimization framework for the transmission and distribution levels that could increase system renewable penetration and reduce operation costs. Compared to the traditional framework, the bi-level framework yields more equitable cost sharing patterns among the market participants as well as better support for the power system evolution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Impact of Increased Inverter-Based Resources on Power System Small-Signal Stability

The transformation of the power system to include more distributed energy resources (DER) implies an increase in the number of inverter-based resources deployed on the grid. Envisioning future scenarios, this paper presents a small-signal stability analysis for a power grid comprising synchronous generators and inverter-based resources. Three types of inverter control are considered: grid following, droop-controlled grid forming, and virtual oscillator control grid forming. Although small-signal stability of power systems is a widely studied topic, systematic analysis of mixed machine-inverter systems with detailed control models at various inverter levels are limited. This paper addresses the gap with numerical simulations tailored to the IEEE 39-bus system. Results show the system may become unstable at high inverter level of grid-following inverters, and grid-forming inverter control can potentially improve system stability, thereby enabling very high level of DERs.

grid-following inverter↗

DOE OSTI2011

Designing power system simulators for the smart grid: combining controls, communications, and electro-mechanical dynamics

Open source software has a leading role in research on simulation technology for electrical power systems. Research simulators demonstrate new features for which there is nascent but growing demand not yet provided for by commercial simulators. Of particular interest is the inclusion of models of software-intensive and communication-intensive controls in simulations of power system transients. This paper describes two features of the ORNL power system simulator that help it meet this need. First is its use of discrete event simulation for all aspects of the model: control, communication, and electro-mechanical dynamics. Second is an interoperability interface that enables the ORNL power system simulator to be integrated with existing, discrete event simulators of digital communication systems. The paper concludes with a brief discussion of how these aspects of the ORNL power system simulator might be inserted into production-grade simulation tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1988

Extended SP-100 reactor power systems capability

The SP-100 space nuclear power system development program and the NASA Civil Space Technology Initiative (CSTI) are discussed. The advanced technologies being developed for the CSTI high capacity nuclear reactor power system are outlined. The relationship between the CSTI and the Pathfinder project is considered.

Bloomfield, H. S.↗

NASA NTRS1985

Controlling Solar-Power Systems With Distributed Processors

System undergoing development uses distributed microprocessors to monitor and control photovoltaic power system. Equipment increases life expectancy and reliability of power system and decreases costs. Adapted to vehicular, residential, and commercial solar and nonsolar power systems. Equipment especially desirable in systems with overall power levels above few kilowatts.

Imamura, M. S.↗

DOE OSTI2025

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

Machine learning (ML) and artificial intelligence (AI) algorithms offer valuable tools for the analysis and interpretation of large datasets. These tools have the capability to uncover insights that may not be readily apparent within these datasets. In recent years, the integration of ML and AI has become increasingly prevalent in various applications within the power system domain. One of the earliest instances of machine learning in power systems can be traced back to demand forecasting, where artificial neural networks were employed for short-term load forecasting. In contemporary power systems, an abundance of high-resolution geospatial and temporal data is generated at various time intervals, ranging from sub-seconds (Phasor Measurement Units or PMUs) to seconds (Supervisory Control and Data Acquisition or SCADA), minutes (Process Information or PI), and extending to days, months, and years. These datasets contain valuable information concerning system reliability and performance. This information holds the potential to offer critical insights into system operations, as well as solutions for predicting and mitigating contingencies to prevent cascading outages. Despite the immense power of machine learning tools, system operators, planners, and utilities often exhibit hesitancy in fully embracing AI-enabled system operations and planning. This cautious approach persists, even as numerous diverse applications of machine learning continue to emerge in the realm of power systems. In this chapter, our focus will delve deep into ML and AI applications tailored for power systems. These applications aim to furnish system operators with enhanced situational awareness and augment their decision-making capabilities, especially during challenging operating conditions. Specific areas of interest encompass root cause analyses of electricity market datasets and the strategic selection of representative samples from vast power system databases for training ML/AI models. Finally, the chapter will conclude with a short discussion on the future of ML/AI in power systems and possible directions that the industry is moving towards.

power system applications, machine learning (ML), ↗

DOE OSTI2018

Constant Rate Production: DOE Approach to Meeting NASA Needs for Radioisotope Power Systems for Nuclear-Enabled Launches

The use of radioisotope power systems (RPSs) for nuclear-enabled National Aeronautics and Space Administration (NASA) missions is made possible through a long-standing arrangement between the Department of Energy (DOE) and NASA. The requirements for the power system come from NASA, but DOE performs the procurement, fueling, testing, and delivery. A challenge has been interplay between the schedule for RPS availability from DOE versus the schedule for competitively selected missions. By mutual agreement, the actual operations to procure an RPS and prepare it for fueling have always been delayed until the final selection of a mission. The timeline for a New Frontiers–class mission leaves approximately 5 to 6 years from the time of final mission selection to the actual launch date. The number of RPSs used for a New Frontiers–class mission can be one to three units. If one or two units are needed, the timeline from the decision point to the launch date is a challenge, but it is achievable. The activities taking place include manufacturing the power system, producing the fuel, and performing the assembly/testing and delivery operations. If the mission selected requires three RPSs, the logistics of accomplishing all activities during the 5–6 years is problematic. The challenge involves obtaining the necessary resources for plutonium production, heat source production, and assembly/testing operations. Typically, the time between RPS-enabled missions requires staffing reduction down to 65%–75% of peak staffing levels to reduce costs. Coupling the ~2 year duration needed for hiring, training, and obtaining the appropriate security clearances for the required staff with the requirement for the RPS to arrive at Kennedy Space Center 6 months before the launch erodes much of the 5–6 years available to comfortably support the use of three RPSs. To provide better support for NASA RPS missions, a different approach for the production of heat sources was devised—constant rate production. This involves a higher level of base capability at DOE national laboratories to provide a stabilized workforce. This will enable 10–15 heat sources to be produced annually and placed into a stable intermediate form to enable storage for up to several years leading to quick production of general purpose heat source modules when a mission is selected. The upfront production of 238 Pu is maintained so material is constantly in the pipeline. Production of key specialized components is also maintained using this model.

42 ENGINEERING↗

NASA NTRS1989

The Environment-Power System Analysis Tool development program

The Environment Power System Analysis Tool (EPSAT) is being developed to provide engineers with the ability to assess the effects of a broad range of environmental interactions on space power systems. A unique user-interface-data-dictionary code architecture oversees a collection of existing and future environmental modeling codes (e.g., neutral density) and physical interaction models (e.g., sheath ionization). The user-interface presents the engineer with tables, graphs, and plots which, under supervision of the data dictionary, are automatically updated in response to parameter change. EPSAT thus provides the engineer with a comprehensive and responsive environmental assessment tool and the scientist with a framework into which new environmental or physical models can be easily incorporated.

Jongeward, Gary A.↗

NASA NTRS1992

Fault-tolerant adaptive control for load-following in static space nuclear power systems

The possible use of a dual-loop model-based adaptive control system for load following in static space nuclear power systems is investigated. The proposed approach has thus far been applied only to a thermoelectric space nuclear power system but is equally applicable to other static space nuclear power systems such as thermionic systems.

Parlos, Alexander G.↗

DOE OSTI2019

Operation of a High Renewable Penetrated Power System With CSP Plants: A Look-Ahead Stochastic Unit Commitment Model

The integration of variable renewable energy (VRE) generation, i.e., wind power and solar photovoltaic, brings significant uncertainty for the power system operation. Different with VRE techniques, concentrating solar power (CSP) is an appealing renewable generation technology due to its dispatch ability through the use of thermal energy storage and is thus expected to play a significant role in high renewable energy penetrated power systems. In this paper, we propose a look-ahead stochastic unit commitment model to operate power systems with CSP under high renewable energy penetration. It has a three-stage structure. The first stage optimizes the operational decisions in a day-ahead framework based on forecasts; the second stage minimizes the expected generation cost for possible realizations in the real time; and the third stage accounts for look-ahead operation in future operating days. This paper has a dual purpose: first, exploring how CSP plants operate in high renewable penetrated power systems; and second, analyzing the benefits of CSP in accommodating VRE generation. A case study on a modified IEEE RTS-79 system with actual solar and wind power data is provided to validate the proposed method.

14 SOLAR ENERGY↗

DOE OSTI2016

Fundamental Corrosion Studies in High-Temperature Molten Salt Systems for Next Generation Concentrated Solar Power Systems

The objective of this project is to increase Concentrated Solar Power (CSP) system lifetime through characterization of corrosion mechanisms in heat transfer systems and identification of materials and corrosion resistance methods applicable at temperatures above 850°C. Coupling of experimental methods with thermodynamic and kinetic modeling has given greater insight into the corrosion phenomena and enabled modeling of the corrosion in molten chloride heat transfer systems. The project has been identified the selective oxidation of Cr along the grain boundaries of high Cr content alloys as the principle corrosion mechanisms occurring in CSP systems. The corrosion rate was also found to be mass transfer limited by diffusion of chromium chlorides along the grain boundaries. It was shown that the corrosion could be increased by adding naturally convective flow to mechanism using a thermosiphon. A reaction mechanism has been proposed for selective oxidation of Cr that is driven by the electrochemical potential difference between the Ni crucible for immersion testing and the alloy coupon. This driving force will be similar to the differences caused by having varying Ni content or Cr content throughout a heat transfer system. It could also mimic the differences in electrochemical potential between various parts of the system that are at different temperatures. The reaction mechanism consists of an initiation step due to system impurities and a set of propagation steps that results in formation of a NiCr alloy at the crucible that drives corrosion and selective oxidation of Cr from the alloy. The presences of chromium chlorides in the salt are also essential to the corrosion mechanism to transport the Cr. The formation of a NiCr alloy on the crucible surface with no contact between the alloy coupons and the crucible provides support to this mechanism of having corrosion reactions occurring at both the alloy and the crucible. The thermodynamics of this reaction mechanism have been modeled and were shown to be galvanic. A corrosion model has been developed based on this mechanism and has been implemented in CFD so that it can be used to predict corrosion in a wide variety of system geometries. The model was validated using the thermosiphon data and dimensionless analysis. The corrosion rates of the samples were modeled to within 10% percent of the experimental values. The model has been extended to include the effect of Mg corrosion inhibitor on the corrosion rate in the system. The use of Mg as a metallic corrosion inhibitor has been demonstrated as a method to reduce the corrosion rate of alloys in molten chlorides to below 15 microns per year. Mg is an effective corrosion inhibitor at concentrations as low as 0.3 mol%. Corrosion potential monitoring experiments have shown that the Mg lowers the corrosion potential for the alloy below the equilibrium potential for Cr oxidation and thus prevents corrosion. Experiments have been performed on the ability of Mg to inhibit corrosion in realistic environments that include lower purity salts and welded and stressed alloys. The results have shown that for all these scenarios the corrosion can be reduced to meet the DOE targets. The electrochemical monitoring of Mg for process control has also been demonstrated.

14 SOLAR ENERGY↗

NASA NTRS1992

Comparison of all-electric secondary power systems for civil subsonic transports

Three separate studies have shown operational, weight, and cost advantages for commercial subsonic transport aircraft using an all-electric secondary power system. The first study in 1982 showed that all-electric secondary power systems produced the second largest benefit compared to four other technology upgrades. The second study in 1985 showed a 10 percent weight and fuel savings using an all-electric high frequency (20 kHz) secondary power system. The last study in 1991 showed a 2 percent weight savings using today's technology (400 Hz) in an all-electric secondary power system. This paper will compare the 20 kHz and 400 Hz studies, analyze the 2 to 10 percent difference in weight savings and comment on the common benefits of the all-electric secondary power system.

Renz, David D.↗

DOE OSTI2020

Power system resilience through defender-attacker-defender models with uncertainty: an overview

Protecting and fortifying a power system to make it resilient is an important and hard problem to solve. The interaction between defenders and attackers, the availability of information and the complexity of power system require carefully selecting models and presenting the underlying assumptions. Trilevel defender-attacker-defender models have been developed to investigate the resilience of power systems. In this paper, we review trilevel models in power system application, with the aim of demonstrating the accessibility and applicability of these complex optimization formulations and discussing the underlying assumptions from these models. In particular, we highlight modeling choices, algorithmic details, and how operational and information uncertainty affects resilience versus the traditional complete-knowledge-based optimal solutions. We also describe other similar relevant models which lack such uncertainty and discuss insights on how to address operational, attacker, and defender related uncertainties in future research efforts.

multi-level optimization, defender-attacker-defend↗

DOE OSTI2020

Adaptive Power System Emergency Control using Deep Reinforcement Learning

Power system emergency control is generally regarded as the final safety net for grid security and resiliency. Existing emergency control schemes are usually designed off-line based on either the conceived “worst” case scenarios or a few typical operation scenarios. These schemes are facing significant adaptiveness and robustness issues as increasing uncertainties and variations occur in modern electrical grids. To address these challenges, for the first time, this paper proposes a novel adaptive emergency control scheme using deep reinforcement learning (DRL), by leveraging the high-dimensional feature extraction and non-linear generalization capabilities DRL has for complex systems with high-dimensional variations. Furthermore, an open-source platform named DeepGrid has been designed for the first time to assist the DRL development and benchmarking processes in power system emergency control. Details of the platform, DRL, and emergency control schemes that use dynamic braking or under-voltage load shedding are presented. Extensive case studies performed in both two-area four-machine system and IEEE 39-Bus system have demonstrated the excellent performance and robustness of the proposed schemes.

Deep reinforcement learning, emergency control, lo↗

NASA NTRS1997

Spacecraft power system architecture to mitigate spacecraft charging effects

A power system architecture for a spacecraft and a method of a power supply for a spacecraft are presented which take advantage of the reduced plasma interaction associated with positive ground high voltage photovoltaic arrays and provide a negative ground power supply for electrical loads of the spacecraft. They efficiently convert and regulate power to the load bus and reduce power system mass and complexity. The system and method ground the positive terminal of the solar arrays to the spacecraft hull, and using a power converter to invert the electric sign, permit a negative ground for the electrical distribution bus and electrical components. A number of variations including a load management system and a battery management system having charging and recharging devices are presented.

Manner, David B.↗

NASA NTRS1983

Advanced electrical power system technology for the all electric aircraft

The application of advanced electric power system technology to an all electric airplane results in an estimated reduction of the total takeoff gross weight of over 23,000 pounds for a large airplane. This will result in a 5 to 10 percent reduction in direct operating costs (DOC). Critical to this savings is the basic electrical power system component technology. These advanced electrical power components will provide a solid foundation for the materials, devices, circuits, and subsystems needed to satisfy the unique requirements of advanced all electric aircraft power systems. The program for the development of advanced electrical power component technology is described. The program is divided into five generic areas: semiconductor devices (transistors, thyristors, and diodes); conductors (materials and transmission lines); dielectrics; magnetic devices; and load management devices. Examples of progress in each of the five areas are discussed. Bipolar power transistors up to 1000 V at 100 A with a gain of 10 and a 0.5 microsec rise and fall time are presented. A class of semiconductor devices with a possibility of switching up to 100 kV is described. Solid state power controllers for load management at 120 to 1000 V and power levels to 25 kW were developed along with a 25 kW, 20 kHz transformer weighing only 3.2 kg.

Finke, R. C.↗

NASA NTRS1983

Advanced electrical power system technology for the all electric aircraft

Finke, R. C.↗

NASA NTRS1992

Phase change energy storage for solar dynamic power systems

This paper presents the results of a transient computer simulation that was developed to study phase change energy storage techniques for Space Station Freedom (SSF) solar dynamic (SD) power systems. Such SD systems may be used in future growth SSF configurations. Two solar dynamic options are considered in this paper: Brayton and Rankine. Model elements consist of a single node receiver and concentrator, and takes into account overall heat engine efficiency and power distribution characteristics. The simulation not only computes the energy stored in the receiver phase change material (PCM), but also the amount of the PCM required for various combinations of load demands and power system mission constraints. For a solar dynamic power system in low earth orbit, the amount of stored PCM energy is calculated by balancing the solar energy input and the energy consumed by the loads corrected by an overall system efficiency. The model assumes an average 75 kW SD power system load profile which is connected to user loads via dedicated power distribution channels. The model then calculates the stored energy in the receiver and subsequently estimates the quantity of PCM necessary to meet peaking and contingency requirements. The model can also be used to conduct trade studies on the performance of SD power systems using different storage materials.

Chiaramonte, F. P.↗