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At least 19 records

NASA's Radioisotope Power Systems - Plans

NASA's Radioisotope Power Systems (RPS) Program continues to plan and implement content to enable planetary exploration where such systems could be needed, and to prepare more advanced RPS technology for possible infusion into future power systems. The 2014-2015 period saw significant changes, and strong progress. Achievements of near-term objectives have enabled definition of a clear path forward in which payoffs from research investments and other sustaining efforts can be applied. The future implementation path is expected to yield a higher-performing thermoelectric generator design, a more isotope-fuel efficient system concept design, and a robust RPS infrastructure maintained effectively within both NASA and the Department of Energy. This paper describes recent work with an eye towards the future plans that result from these achievements.

Program

Representation and Impact of Water Head on Power System Planning and Operation

Representing water head information in power system model files, can provide a more realistic model of the system and thereby inform operation and planning personnel in the decision-making process. This article describes a procedure for modifying the power system model files (steady-state and dynamic) to represent water head information. Additionally, the impact of representing the water head on power system reliability studies including contingency analysis, cascading failure analysis and dynamic frequency response analysis has been investigated, using the modified power system models. This paper considers the detailed Western Electricity Coordination Council model during summer and winter conditions as the test system for the impact analysis. Results show that under reduced water head: 1) the number of critical voltage and branch flow violations increases; 2) chances of cascading failure and island formation increases; and 3) frequency nadir decreases as compared to those of the base cases where the water head information is not represented.

13 - HYDRO ENERGY

NASA's Radioisotope Power Systems Planning and Potential Future Systems Overview

The goal of NASA's Radioisotope Power Systems (RPS) Program is to make RPS ready and available to support the exploration of the solar system in environments where the use of conventional solar or chemical power generation is impractical or impossible to meet the needs of the missions. To meet this goal, the RPS Program, working closely with the Department of Energy, performs mission and system studies (such as the recently released Nuclear Power Assessment Study), assesses the readiness of promising technologies to infuse in future generators, assesses the sustainment of key RPS capabilities and knowledge, forecasts and tracks the Programs budgetary needs, and disseminates current information about RPS to the community of potential users. This process has been refined and used to determine the current content of the RPS Programs portfolio. This portfolio currently includes an effort to mature advanced thermoelectric technology for possible integration into an enhanced Multi-Mission Radioisotope Generator (eMMRTG), sustainment and production of the currently deployed MMRTG, and technology investments that could lead to a future Stirling Radioisotope Generator (SRG). This paper describes the program planning processes that have been used, the currently available MMRTG, and one of the potential future systems, the eMMRTG.

Radioisotope

NASA's Radioisotope Power Systems Planning and Potential Future Systems Overview

The goal of NASA's Radioisotope Power Systems (RPS) Program is to make RPS ready and available to support the exploration of the solar system in environments where the use of conventional solar or chemical power generation is impractical or impossible to meet the needs of the missions. To meet this goal, the RPS Program, working closely with the Department of Energy, performs mission and system studies (such as the recently released Nuclear Power Assessment Study), assesses the readiness of promising technologies to infuse in future generators, assesses the sustainment of key RPS capabilities and knowledge, forecasts and tracks the Program's budgetary needs, and disseminates current information about RPS to the community of potential users. This process has been refined and used to determine the current content of the RPS Program's portfolio. This portfolio currently includes an effort to mature advanced thermoelectric technology for possible integration into an enhanced Multi-Mission Radioisotope Generator (eMMRTG), sustainment and production of the currently deployed MMRTG, and technology investments that could lead to a future Stirling Radioisotope Generator (SRG). This paper describes the program planning processes that have been used, the currently available MMRTG, and one of the potential future systems, the eMMRTG.

Nuclear

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

24 POWER TRANSMISSION AND DISTRIBUTION

ASEAN Technical Exchange Workshop for System Operators, Regulators, and Policymakers

This presentation provides an in-depth exploration of power system planning, cross-border electricity trading, and battery energy storage systems (BESS), offering actionable insights for system operators, regulators, and policymakers. The first section delves into power system planning and analysis, focusing on capacity expansion models and resource adequacy studies, including their role in optimizing system efficiency, managing emissions, and addressing system reliability risks. Key considerations, such as integration of transmission into generation planning and the forecasting versus optimization of customer distributed energy resources (DER) technologies, are explored. The session highlights critical trade-offs in spatial granularity and model runtimes, as well as the feasibility of aligning distribution investments with capacity expansion efforts. The second section examines cross-border electricity trading, with an emphasis on resource adequacy concepts such as reliability targets, loss of load expectation (LOLE), and planning reserve margins (PRM). Case studies on reserve market design and coordination across US regions provide insights into improving reserve deliverability and managing interregional power balance and congestion. This section also addresses market-to-market congestion management, including advanced strategies for high-voltage direct current (HVDC) optimization and ancillary service delivery. Finally, the presentation covers the rapid evolution of Battery Energy Storage Systems (BESS), highlighting their operational growth, regulatory frameworks, and use cases in grid flexibility, energy storage, and reliability. The discussion focuses on the benefits of BESS for system stability, resilience, and integration of renewable energy, offering insights into its role as a vital component in the transition toward a more sustainable and flexible grid. Key performance parameters, such as throughput, round-trip efficiency, and state of charge, are also examined.

25 ENERGY STORAGE

Evolution of space power systems

NASA planning for large power systems (tens to hundreds of kilowatts) in space for the next decade is summarized. Applications requiring large amounts of power, the selection of solar photovoltaic as the primary power conversion approach, and the power technology base are explained. Large power systems, beginning with a Space Shuttle/Spacelab power augmentation kit and an orbitally stored Power Module, are described.

Freitag, R. F.

Short-Term Load Forecasting Considering EV Charging Loads with Prediction Interval Evaluation

Short-term load forecasting plays a critical role in power system planning and operation. Along with the electrification of various loads, electricity demands are becoming increasingly hard to predict. Notably, the recent rise in electric vehicles (EVs) has further contributed to this unpredictability. To address this issue, this paper proposes a probabilistic load forecasting strategy utilizing Gaussian process regression, structured in a day-ahead manner. While many works focus on deterministic prediction, probabilistic forecasting offers additional insights into variability and uncertainty, enabling more flexible and reliable operation for power systems. To enhance the accuracy of the load forecasting model, the inputs include features related to EV charging habits as well as commonly used weather information. The load forecasting results are evaluated using various metrics, including conventional ones that assess the accuracy of point forecasts, as well as additional metrics that test the reliability of prediction intervals. The proposed load forecasting method is finally tested on real residential power consumption data and EV charging data sampled from real-world sources. The results prove that the new features can greatly improve the performance of the load forecasting method.

electrical vehicle

Discrete versus continuous: Enhancing battery optimization in capacity expansion models

This study compares two battery modeling approaches for capacity expansion models: discrete-duration and continuous-duration formulations. In the discrete approach, battery duration is fixed, and power capacity is optimized. In the continuous approach, both power and energy capacities are decision variables, allowing storage duration to be optimized endogenously. Although both discrete-duration and continuous-duration battery formulations are used in long-term power system planning models, the literature has provided limited direct, systematic comparisons of their implications within a common modeling framework. To address this gap, this study implements both approaches in the Regional Energy Deployment System (ReEDS TM ) capacity expansion model using two resource adequacy methods, across a range of future system conditions, and with varying battery cost projections. Results show continuous-duration and high-resolution discrete approaches produce similar capacity expansion outcomes. The continuous formulation achieves faster runtimes compared to discrete-duration runs with many discrete-duration options. However, the discrete-duration approach allows users to choose to have limited fidelity for storage duration options, which in some cases can outperform the continuous formulation. The continuous formulation has the lowest overall system costs, indicating its ability to fine-tune storage duration to better meet specific system needs. This study's findings provide a side-by-side evaluation of discrete and continuous battery modeling approaches and offer guidance for improving the representation of real-world systems, flexibility, and computational efficiency for representing energy storage in long-term power system planning models.

25 ENERGY STORAGE

Impacts of Regional Coordination on Transmission Needs for Power System Resource Adequacy [Slides]

Resource adequacy (RA) is an important component of bulk power system reliability that addresses whether there are sufficient resources available to meet electricity demand at all times. RA analysis is used to assess whether the planned power system will provide reliable electricity to consumers while accounting for equipment outages, weather variability, and load uncertainty. Coordination between regions can enable resource sharing to meet RA needs if sufficient transmission capacity exists. Transmission's role in RA coordination can be particularly pronounced for large power systems like the U.S. electricity grid which contains geographically diverse demand and weather-dependent resources. Depending on the level of coordination desired, existing inter-regional transmission capacity may not be sufficient. This study is designed to assess optimal pathways for the development of inter-regional transmission in the U.S. under varying levels of RA coordination. Results can inform long-term grid infrastructure planning and provide insights into potential benefits of greater coordination for generation and transmission planning between regional U.S. power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Downscaled Earth System Model Data for Resilient Energy System Planning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. In this presentation, we explore the output characteristics of the dataset and various validation analyses. We also present and discuss plans for the integration of this data into power system planning models using a decision-making under deep uncertainty (DMDU) methodology.

97 MATHEMATICS AND COMPUTING

Solar simulator for solar dynamic space power system testing

Planned vacuum tank testing of a solar dynamic space power system requires a solar simulator. Several solar simulators were previously built and used for vacuum tank testing of various space systems. However, the apparent solar subtense angle, i.e., the angular size of the apparent sun as viewed from the experiment, of these solar simulators is too large to enable testing of solar dynamic systems. A new design was developed to satisfy the requirements of the solar dynamic testing. This design provides 1.8 kW/m(sup 2) onto a 4.5M diameter test area from a source that subtends only 1 deg, full cone angle. Key features that enable this improved performance are (1) elimination of the collimating mirror commonly used in solar simulators to transform the diverging beam into a parallel beam; (2) a redesigned lamp module that has increased efficiency; and (3) the use of a segmented reflective surface to combine beams from several individual lamp modules at the pseudosun. Each segment of this reflective surface has complex curvature to control the distribution of light. By developing a new solar simulator design for testing of the solar dynamic system instead of modifying current designs, the initial cost was cut in half, the efficiency was increased by 50 percent reducing the operating costs by one-third, and the volume occupied by the solar simulator was reduced by a factor of 10.

Jefferies, Kent S.

Energy Systems Integration Facility Stewardship Summary: Fiscal Year 2025

A summary of NLR's stewardship of the nationally unique Energy Systems Integration Facility (ESIF) highlighting performance metrics, capability upgrades, and examples of R&D impact. 2025 brought a national focus on energy and ESIF is meeting the moment. All eyes are on data centers and domestic manufacturing and bringing the benefits of artificial intelligence to power system planning and operations. In step with national priorities, ESIF is building out capabilities that advance secure, reliable, and affordable power. ESIF hosted 190 multidisciplinary research projects, 855 high-performance computer users, and collaborated with 81 partners from industry, academia, research, and federal agencies. These research projects resulted in an AI method for detecting high-impedance faults with 90% accuracy, a grid controls demonstration in Connecticut, power quality validation of CorePower's flagship inductor, and a cybersecurity assessment of potential rogue capabilities in digitally connected energy devices. Facility infrastructure improvements enhanced the thermal research network, the SCADA system, the cyber range, power hardware-in-the-loop testing, and more. With support from the U.S Department of Energy (DOE), the ESIF laboratories continue to deliver leading solutions for secure, reliable, and affordable power.

24 POWER TRANSMISSION AND DISTRIBUTION