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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
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 OSTI2025

Existing Methods for Grid Strength Assessment and Role of Hydropower in Future Grids

The power system is undergoing rapid evolution with increasing penetration of inverter-based resources (IBRs), large loads, microgrids, and power electronic devices. Ensuring reliable and stable operation of the modern power grid is a multi-faceted challenge that requires detailed understanding of this complex system. Dynamic stability is a major concern in maintaining the security of power grids as the generation mixes and large loads transitions to include high shares of power electronic devices. The operation of IBRs in regions with low system strength and higher grid impedances has been found to be the main reason behind many of the power system instabilities that manifest themselves in various types of oscillations and interactions that, if not properly addressed and damped, can jeopardize the reliable operation of the power system. Weak grid conditions compound such stability problems, particularly when many IBRs operate in proximity to and connect to weak power grids. Therefore, it is important to assess grid strength for planning, integration and operation of IBRs for a given power system. In this report, we aim to understand and classify existing methodologies for grid strength assessment, along with their limitations and future needs. Further, we aim to utilize the huge untapped potential in utilizing hydro energy resources in addressing some of the pertinent challenges of grid strength and reliable operation of modern power systems. Hydropower, historically valued for its flexibility and dispatchability, now faces new constraints due to reduced share of synchronous machines in the generation mix and seasonal variability of available water resources. Yet, these same plants present untapped potential beyond energy generation - notably, as providers of critical grid services. This report explores how hydropower plants, particularly through operation as synchronous condensers, can play a pivotal role in strengthening the grid amid evolving system dynamics.

13 HYDRO ENERGY↗
DOE OSTI2022

Validation of Power Distribution Models using Load Flow Analysis in an ADMS Environment

Electric utilities are facing the need for better monitoring, analysis, and control of their distribution systems. An accurate mathematical model is a key to both the development of cutting-edge, scalable model-based algorithms and the assessment of emerging technologies such as distributed energy resources (DER) for grid planning and operation. However, the constantly evolving nature of power distribution systems poses challenges to maintaining accurate models. In this paper, we propose a novel load flow based approach to validate power distribution models. Networked equipment models described according to the Common Information Model (CIM) standard and a measurement model are used to formulate the distribution load flow problem. First, a system admittance matrix (Ybus) is derived from device-level CIM parameters. Next, the operational parameters (dynamic Ybus and nodal injections) are extracted from the measurement model using sensor configuration and equipment state. An iterative power flow method is then used to compute nodal voltages and branch flows that are compared against the measurement data to find any inconsistencies in the networked equipment model. This approach is implemented within GridAPPS-D, an open-source standards-based platform for advanced distribution management system (ADMS) application development, and demonstrated on the IEEE 13-bus, 123-bus, and 8500-node test feeders.

Common information model, model validation, power ↗
NASA NTRS2005

International Space Station Electric Power System Performance Code-SPACE

The System Power Analysis for Capability Evaluation (SPACE) software analyzes and predicts the minute-by-minute state of the International Space Station (ISS) electrical power system (EPS) for upcoming missions as well as EPS power generation capacity as a function of ISS configuration and orbital conditions. In order to complete the Certification of Flight Readiness (CoFR) process in which the mission is certified for flight each ISS System must thoroughly assess every proposed mission to verify that the system will support the planned mission operations; SPACE is the sole tool used to conduct these assessments for the power system capability. SPACE is an integrated power system model that incorporates a variety of modules tied together with integration routines and graphical output. The modules include orbit mechanics, solar array pointing/shadowing/thermal and electrical, battery performance, and power management and distribution performance. These modules are tightly integrated within a flexible architecture featuring data-file-driven configurations, source- or load-driven operation, and event scripting. SPACE also predicts the amount of power available for a given system configuration, spacecraft orientation, solar-array-pointing conditions, orbit, and the like. In the source-driven mode, the model must assure that energy balance is achieved, meaning that energy removed from the batteries must be restored (or balanced) each and every orbit. This entails an optimization scheme to ensure that energy balance is maintained without violating any other constraints.

Hojnicki, Jeffrey↗
DOE OSTI2021

The Regional Energy Deployment System (ReEDS): An Open-Access Model for the North American Electricity System

The Regional Energy Deployment System (ReEDS) model is NREL’s flagship capacity expansion planning tool for the electric power sector in North America. Originally developed in 2001, ReEDS has been used primarily by NREL researchers to conduct high-profile analysis of the potential evolution of the electricity system. In September 2019, the core model is being released for public use. In this presentation, we provide an overview of the model architecture, key model features, data sources, lessons learned, and sample model results for the North American electric power system.

42 ENGINEERING↗
DOE OSTI2022

ReNew100: Reliable Power System Operation with 100% Renewable Generation

The ReNew100 project has developed and demonstrated an operator support system (OSS) to operate power systems with 100% renewable power generation from inverter-based resources (IBRs) like wind and solar that significantly reduces the risk of widespread power outages in a simulated operational environment at Technology Readiness Level (TRL) 6. The OSS achieves resilient operation for power systems under changing operation modes including varying combinations of conventional and renewable generation, including cases with 100% renewable generation from wind and solar IBRs. The OSS continuously monitors the N-1 security of the power system, which refers to the ability of the power systems to survive single outages of power system elements, like the loss of a generator or a power line, without causing widespread power outages beyond those expected and planned for. If the OSS identifies that the system is not N-1 secure, an automatic Controller Parameter Optimization (CoPO) developed within Renew100 is activated to optimize the N-1 security of the system by tuning controller parameters within different assets like batteries, wind, and solar plants. The core innovation of ReNew100 is the development of this CoPO as well as the demonstration of the OSS for a real-time simulation of the Hawai'i Island power system. Moreover, Renew100 has developed new model calibration techniques for dynamic power system models and demonstrated them for Hawai'i Island.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A New Hybrid Quantum-Classical Algorithm for Solving the Unit Commitment Problem

Solving problems related to planning and operations of large-scale power systems is challenging on classical computers due to their inherent nature as mixed-integer and nonlinear problems. Quantum computing provides new avenues to approach these problems. We develop a hybrid quantum-classical algorithm for the Unit Commitment (UC) problem in power systems which aims at minimizing the total cost while optimally allocating generating units to meet the hourly demand of the power loads. The hybrid algorithm combines a variational quantum algorithm (VQA) with a classical Benders-type heuristic. The resulting algorithm computes approximate solutions to UC in three stages: i) a collection of UC vectors capable meeting the power demand with lowest possible operating costs is generated based on VQA; ii) a classical sequential least squares programming (SLSQP) routine is leveraged to find the optimal power level corresponding to a predetermined number of candidate vectors; iii) in the last stage, the approximate solution of UC along with generating units power level combination is given. To demonstrate the effectiveness of the presented method, three different systems with 3 generating units, 10 generating units, and 26 generating units were tested for different time periods. In addition, convergence of the hybrid quantum-classical algorithm for select time periods is proven out on IonQ's Forte system.

Aboumrad, Willie [IonQ, Inc]↗
DOE OSTI2021

Improving Short Term Predictability of Hydrologic Models with Deep Learning

Focal Area: Focal Area 2. Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI driven model/component/parameterization selection). Science Challenge: A major challenge exists in the lack of reliable predictive modeling of water-cycle extremes using macro-scale hydrologic models that are driven by atmospheric climate data. This causes a critical knowledge gap in understanding the magnitudes, probabilities, and severity of droughts, rainfall, and flooding. Improved understanding of these extreme events requires more accurate modeling at high spatial and temporal resolutions. This shortcoming is especially apparent when complex couplings between atmospheric quantities and engineered systems emerge, such as during extreme precipitation or drought events and at intersections of atmospheric-land-fluvial-ocean systems. Added complexity around representing operations of engineered infrastructure leads to a limited capability to analyze the temporal and spatial implications of compounding extreme events across inland and coastal regions. This results in profound challenges for water and power systems operators, agriculture production, and regional infrastructure planning. The science challenge can be summarized as How can we use AI/ML to improve short term predictability of extreme water-cycle events and associated risk, especially compounding events and extreme rainfall patterns that result in flooding, to inland and coastal communities under different climate scenarios?

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Liquid metal magnetohydrodynamics (LMMHD) technology transfer feasibility study. Volume 1: Summary

The potential application of liquid metal magnetohydrodynamics (LMMHD) to central station utility power generation through the period to 1990 is examined. Included are: (1) a description of LMMHD and a review of its development status, (2) LMMHD preliminary design for application to central station utility power generation, (3) evaluation of LMMHD in comparison with conventional and other advanced power generation systems and (4) a technology development plan. One of the major conclusions found is that the most economic and technically feasible application of LMMHD is a topping cycle to a steam plant, taking advantage of high temperatures available but not usable by the steam cycle.

Phen, R. L.↗
NASA NTRS1999

Deployment of Autonomous GPS Stations in Marie Byrd Land, Antarctica

During the 1998-1999 Antarctic field season, we installed three autonomous GPS stations in Marie Byrd Land, West Antarctica to measure glacio-isostatic rebound and rates of spreading across the West Antarctic Rift System. The systems collect data throughout the entire year and therefore must function during the warm, relatively mild summer, and cold, harsh winters. They are powered by gel cell batteries that are charged by wind and solar power. The system includes dual data logging capability. We log data at 5 minute intervals within the receiver and at 30 second intervals to a serial data logger. We do not require 365 days of continuous data for well determined crustal velocities, but rather long periods (greater than 24 hours) of continuous data distributed throughout the year. Therefore, for simplicity, we designed the system to accept occasional data interruptions. The batteries, in addition to supplying power, act as a thermal capacitive heat storage device to help regulate the temperatures within the system. This storage system absorbs the majority of the 10-15 watts of power from the receiver and 5 watts from the data logger which helps to maintain temperature for long periods of time. Power is switched off when the temperature within the system enclosure reaches 50'C and is reconnected at 20 C. If battery voltage drops too low the batteries will freeze. Therefore, we cut the power off when the batteries drop to a low voltage of 12.45V. Power is restored at 13.2V. The temperature and power hysteresis allows for a minimum of several days of data to be collected before system shutdowns. A check of all three stations in late January 1999 indicated that the thermal and power control systems are performing as expected. We plan to implement satellite telemetry to the systems during the 2000-2001 season following a year of development.

Donnellan, Andrea↗
NASA NTRS2013

Lunar Simulants, Analogues, and Standards: Needs and Realities for Mission Technologies Development

Integration of In-Situ Resource Utilization (ISRU) capabilities into missions present both challenges as well as benefits for future missions to the Moon and Mars. However, since ISRU systems and capabilities have not flown, mission planners have been hesitant to include ISRU capabilities in mission critical roles, thereby significantly reducing the benefits that ISRU can provide in mission mass and cost reductions. For ISRU systems to provide products and services to 'customers' such as life support, propulsion, and power systems, close development of requirements, hardware, and operations between ISRU and these systems are required. To address these development and incorporation challenges, NASA and csA initiated a series of analog field test demonstrations at sites in Hawaii. Two tests completed in November of 2008 and February of 2010 have demonstrate all the critical steps in operating ISRU systems on the lunar surface at relevant mission scales as well as integration with power and propulsion systems. The third field test planned for July 2012 will demonstrate that a mission to the lunar poles to locate and characterize ice and other volatiles is possible in a highly integrated mission with multiple space agencies. These analog field tests have shown that not only are ISRU systems feasible at relevant mission scales, that they can be successfully integrated into mission architectures.

Sibille, Laurent↗
DOE OSTI2025

Managing Increased Electric Vehicle Shares on Bulk Power Systems

The convergence of transportation electrification, other load growth, and the integration of many power sector technologies presents a complex planning problem requiring realistic, region-specific modeling and analysis to ensure the power system can support new loads quickly and affordably.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1986

Space power system scheduling using an expert system

A most pressing problem in space exploration is timely spacecraft power system sequence generation, which requires the scheduling of a set of loads given a set of resource constraints. This is particularly important after an anomaly or failure. This paper discusses the power scheduling problem and how the software program, Plan-It, can be used as a consultant for scheduling power system activities. Modeling of power activities, human interface, and two of the many strategies used by Plan-It are discussed. Preliminary results showing the development of a conflict-free sequence from an initial sequence with conflicts is presented. It shows that a 4-day schedule can be generated in a matter of a few minutes, which provides sufficient time in many cases to aid the crew in the replanning of loads and generation use following a failure or anomaly.

Bahrami, K. A.↗
DOE OSTI2020

A Tradeoff Analysis of Series / Parallel Three-Phase Converter Topologies for Wireless Extreme Chargers

In this paper, extreme fast charging (XFC) technology is studied considering the charge rates of 300 kW for wireless power transfer (WPT) applications. Tradeoff analysis of series and parallel connection of three-phase WPT system are presented by comparisons of voltage and current stresses on power electronics active / passive components. In addition, star (Y) / delta (Δ) connection configurations for three-phase wireless power transfer coupling coils are analyzed with series and LCC resonant compensation circuits. The system series and parallel connection controllability is also reviewed considering voltage and current balance techniques with output control. In a conclusion of evaluation analysis, it is revealed that each component of 300 kW wireless charging network must be designed for high fast charging system and the overall system operation need to be strategically planned for high power charging and infrastructure deployment.

Asa, Erdem↗
NASA NTRS2018

Dynamic Radioisotope Power Systems

NASA's dynamic power convertor development in support of high-efficiency RPS is progressing as planned, and shows promise. Ongoing research utilizing existing hardware supports viability of dynamic power conversion for Radioisotope Power Systems.

Oriti, Salvatore↗
NASA NTRS2014

Gas Turbine Energy Conversion Systems for Nuclear Power Plants Applicable to LiFTR Liquid Fluoride Thorium Reactor Technology

This panel plans to cover thermal energy and electric power production issues facing our nation and the world over the next decades, with relevant technologies ranging from near term to mid-and far term.Although the main focus will be on ground based plants to provide baseload electric power, energy conversion systems (ECS) for space are also included, with solar- or nuclear energy sources for output power levels ranging tens of Watts to kilo-Watts for unmanned spacecraft, and eventual mega-Watts for lunar outposts and planetary surface colonies. Implications of these technologies on future terrestrial energy systems, combined with advanced fracking, are touched upon.Thorium based reactors, and nuclear fusion along with suitable gas turbine energy conversion systems (ECS) will also be considered by the panelists. The characteristics of the above mentioned ECS will be described, both in terms of their overall energy utilization effectiveness and also with regard to climactic effects due to exhaust emissions.

Energy Conversion↗
NASA NTRS1983

Electric power - Looking at regenerative systems

Photovoltaic solar array technology dominates NASA space station planning for the late 1980s, although the reduction of fabrication costs and the extension of service life for such arrays remain essential goals for research and development. Attention is given to concentrator arrays, in which highly reflective surfaces concentrate solar energy onto the solar cells. Two types of concentrator arrays are under consideration: one with a low geometric concentration ratio which after reflector losses can produce about 5 suns at the cell surface, and the other with a Cassegrainian concentrator that produces a flux level of 100 suns on the cell surface. Costs are reduced from the $300/W for planar arrays to $250/W and as little as $100/W, respectively, in 1982 dollars. The storage of electrical energy by means of novel battery systems is also considered.

Miller, J. L.↗