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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Electric Access System Enhancement (EASE): Assessment of a Distributed Energy Resource Management System for Enabling Dynamic Hosting Capacity

The Electric Access System Enhancement (EASE) project demonstrated a scalable, interoperable, and cost-effective means of integrating high penetration of distributed energy resources (DERs). The control architecture developed leveraged a Distributed Energy Resource Management System, Distribution System Operator for transacting energy, and 3rd Party DER Aggregator platform. The project identified ways to enhance the customer interconnection process to the grid and improve access to information from DERs and optimize the usage of DERs to provide energy services in a simulated day-ahead shadow market while maintain grid reliability. By integrating these capabilities into a scalable system of systems, the DSO can effectively balance DER generation and customer demand on the distribution network. This capability allows the grid to host more DER than traditionally possible on wires alone. Hosting more DER has the added benefit of supplying increased demand growth, sometimes beyond the capacity limits of the distribution network itself. This is known as a dynamic hosting capacity, which could help utilities manage the forecasted growth in electricity demand as California switch to electric vehicles and appliances. This could help to establish energy storage and PV generation as a “pseudo firm” generation resource mix if managed appropriately and provide sufficient resource adequacy for distribution capacity upgrade deferrals.

14 SOLAR ENERGY↗
DOE OSTI2022

System Study: Emergency Power System 1998-2020

This report presents an unreliability evaluation of the emergency power system (EPS) at 104 U.S. commercial nuclear power plants. Demand, run hours, and failure data from 1998 through 2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. Statistically significant decreasing trends were identified in the industry-wide estimates of EPS system start-only mission as well as EPS system unreliability (8-hour mission).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

System Study: Emergency Power System 1998-2022

This report presents an unreliability evaluation of the emergency power system (EPS) at 93 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the industry-wide estimates of EPS system start-only unreliability, but a highly statistically significant decreasing trend was identified in the industry-wide estimates of EPS system 8-hour mission unreliability.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

System Study: Emergency Power System 1998-2024

This report presents an unreliability evaluation of the emergency power system (EPS) at 93 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998 to 2024 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the industry-wide estimates of EPS system start-only unreliability, but a statistically significant decreasing trend was identified in the industry-wide estimates of EPS system 24-hour mission unreliability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A novel open-source cultivation system helps establish the first full cycle chemosynthetic symbiosis model system involving the giant ciliate Zoothamnium niveum

Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate Zoothamnium niveum and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory. While it is experimentally tractable and presents a promising model system, it currently lacks an open-source, simple, and standardized cultivation setup. Following the FABricated Ecosystems (EcoFABs) model, we leveraged 3D printing and polydimethylsiloxane (PDMS) casting to develop simple flow-through cultivation chambers that can be produced and adopted by any laboratory. The streamlined manufacturing process reduces production time by 86% and cuts cost by tenfold compared to the previous system. Benchmarking using previously established optimal growth conditions, the new open-source cultivation system proves stable, efficient, more autonomous, and promotes a more prolific growth of the symbiosis. For the first time, starting from single cells, we successfully cultivated the symbiosis in flow-through chambers for 20 days, spanning multiple generations of colonies that remained symbiotic. They were transferred from chamber to chamber enabling long-term cultivation and eliminating the need for continuous field sampling. The chambers, optimized for live imaging, allowed detailed observation of the synchronized growth between the host and symbiont. Highlighting the benefit of this new system, we here describe a new step in the first hours of development where the host pauses growth, expels a coat, before resuming growth, hinting at a putative symbiont selection mechanism early in the colony life cycle. With this simple, open-source, cultivation setup, Z. niveum holds promises for comparative studies, standardization of research and wide adoption by the symbiosis research community.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Applying NASA’s Human Systems Integration Methodology in Implementing Voice-Control of Future Spacecraft Systems

Through the NASA Artemis program, a new era of space exploration will serve to lead humanity towards sustained lunar exploration in preparation for the next giant leap-human exploration of Mars. These crewed spacecraft and habitats will require more automation and autonomy to support these complex missions. Crew size will be small and therefore a more efficient command and control input method is desired. Speech recognition along with visual or auditory feedback is an alternative, providing an extra pair of hands and eyes for the crew. Yet, speech recognition demands a highly integrated development approach to ensure a successful system implementation. To ensure the voice control application is developed correctly will require a Human Systems Integration (HSI) approach. This paper provides an insight into the development of a speech/voice control application for a spacecraft system that encompasses automation and autonomy through an HSI approach. Results of the voice control experiment of the Space Shuttle camera system are provided as lessons learned about using voice control on a spacecraft. Limitations and challenges of the technology are addressed as well as how HSI along with Human Readiness Level can help successfully develop voice control command and control systems.

Systems Engineering↗
DOE OSTI2018

Composite Robust $H_\infty$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer

Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbance rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.

42 ENGINEERING↗
DOE OSTI2019

Power System Dynamic State Estimation: Motivations, Definitions, Methodologies and Future Work

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.

task force, dynamic state estimation, Parameter Es↗
DOE OSTI2022

PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems: Preprint

We present the PowerGridworld software package to provide users with a light-weight, modular, and customizable framework for creating power systems-focused, multi-agent gym environments that readily integrate with existing training frameworks for reinforcement learning (RL). While many frameworks exist for training multi-agent (MA) RL policies, none exist to rapidly prototype and develop the environments themselves, especially in the context of heterogeneous (composite, multi-device) power systems where power flow solutions are required to define grid-level variables and costs. PowerGridworld is an open-source software package that helps to fill this gap. To highlight PowerGridworld's key features, we present two case studies and demonstrate learning multi-agent RL policies using both OpenAI's MADDPG and RLLib's PPO algorithms where, in both cases, at least some subset of agents incorporate elements of the power flow solution at each time step as part of their reward (negative cost) structures.

MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Ecosystem-Level Biomimicry for the Built Environment: Adopting Systems Ecology Principles for the Control of Heterogeneous Energy Systems

This paper presents, to our knowledge, the first system-level engineering study to bio-mimic the cybernetics and flow dynamics of energy resources in natural ecosystems for the control of heterogeneous energy infrastructures in the built environment. To this end, we introduce a novel Biomimetic Pulsing State (BPS) control that functionally mimics mature ecosystems. A preliminary Modelica-based case study features a single-family residential building with electrical and HVAC subsystems. The BPS control objective is to minimize the energy exchange between the building and the grid for the purposes of future self-supporting buildings and grid stability. The building contains PV, a wind turbine, a battery storage system, and a fan coil/heat pump HVAC system served by an ambient district energy network. Evaluating the control performance (BPS vs. constant setpoint) over several renewable energy scenarios (net importer, net zero, net exporter), simulation results show how the building's HVAC system can dynamically adjust its electrical load and temperatures to the electrical system's net energy status in real-time with BPS control. As a net importer, the heat pump consumed 29% less energy and its peak power reduced by 15% with BPS control compared to the constant setpoint case, with the zone air temperature 1 degree C lower on average. As a net exporter, the heat pump effectively consumed the same energy, but the peak power increased by 34% with BPS control, while the zone air temperature was 1 degree C higher when renewable energy was abundant, preheating the home. BPS and constant setpoint control produced comparable results under a net zero scenario. While further evaluation is essential, BPS control may help communities meet their sustainability and resiliency targets as they transition towards fully distributed and renewable energy grids.

biomimicry↗
DOE OSTI2017

Sensitivity analysis on chaotic dynamical systems by Non-Intrusive Least Squares Shadowing (NILSS)

This paper develops the Non-Intrusive Least Squares Shadowing (NILSS) method, which computes the sensitivity for long-time averaged objectives in chaotic dynamical systems. In NILSS, we represent a tangent solution by a linear combination of one inhomogeneous tangent solution and several homogeneous tangent solutions. Next, we solve a least squares problem using this representation; thus, the resulting solution can be used for computing sensitivities. NILSS is easy to implement with existing solvers. In addition, for chaotic systems with many degrees of freedom but few unstable modes, NILSS has a low computational cost. NILSS is applied to two chaotic PDE systems: the Lorenz 63 system and a CFD simulation of flow over a backward-facing step. In both cases, the sensitivities computed by NILSS reflect the trends in the long-time averaged objectives of dynamical systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Chapter 8. Hybrid Biological–Inorganic Systems for CO 2 Conversion to Fuels

The biological reduction of CO 2 into organic carbon is integral to the formation and maintenance of all life on earth. An urgent need to mitigate the effects of CO 2 on our atmosphere has provided an imperative to exploit biological CO 2 fixation for the conversion of CO2 into valuable and energy rich fuels. Photosynthesis uses only sunlight, water, and CO2 as starting materials to form all biomass.

CO2 Conversion to Fuels↗
DOE OSTI2017

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems]

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whose sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.

42 ENGINEERING↗
DOE OSTI2014

Sensitivity Analysis of Wind Plant Performance to Key Turbine Design Parameters: A Systems Engineering Approach; Preprint

This paper introduces the development of a new software framework for research, design, and development of wind energy systems which is meant to 1) represent a full wind plant including all physical and nonphysical assets and associated costs up to the point of grid interconnection, 2) allow use of interchangeable models of varying fidelity for different aspects of the system, and 3) support system level multidisciplinary analyses and optimizations. This paper describes the design of the overall software capability and applies it to a global sensitivity analysis of wind turbine and plant performance and cost. The analysis was performed using three different model configurations involving different levels of fidelity, which illustrate how increasing fidelity can preserve important system interactions that build up to overall system performance and cost. Analyses were performed for a reference wind plant based on the National Renewable Energy Laboratory's 5-MW reference turbine at a mid-Atlantic offshore location within the United States.

17 WIND ENERGY↗
DOE OSTI2023

AI-Based Faster-Than-Real-Time Stability Assessment of Large Power Systems with Applications on WECC System

Achieving clean energy goals will require significant advances in regard to addressing the computational needs for next-generation renewable-dominated power grids. One critical obstacle that lies in the way of transitioning today’s power grid to a renewable-dominated power grid is the lack of a faster-than-real-time stability assessment technology for operating a fast-changing power grid. This paper proposes an artificial intelligence (AI) -based method that predicts the system’s stability margin information (e.g., the frequency nadir in the frequency stability assessment and the critical clearing time (CCT) value in the transient stability assessment) directly from the system operating conditions without performing the conventional time-consuming time-domain simulations over detailed dynamic models. Since the AI method shifts the majority of the computational burden to offline training, the online evaluation is extremely fast. This paper has tested the AI-based stability assessment method using multiple dispatch cases that are converted and tuned from actual dispatch cases of the Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. The results show that the AI-based method could accurately predict the stability margin of such a large power system in less than 0.2 milliseconds using the offline-trained AI agent. Therefore, the proposed method has great potential to achieve faster-than-real-time stability assessment for practical large power systems while preserving sufficient accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

New Strategies for Time Delay Estimation during System Calibration for UAV-Based GNSS/INS-Assisted Imaging Systems

The need for accurate 3D spatial information is growing rapidly in many of today’s key industries, such as precision agriculture, emergency management, infrastructure monitoring, and defense. Unmanned aerial vehicles (UAVs) equipped with global navigation satellite systems/inertial navigation systems (GNSS/INS) and consumer-grade digital imaging sensors are capable of providing accurate 3D spatial information at a relatively low cost. However, with the use of consumer-grade sensors, system calibration is critical for accurate 3D reconstruction. In this study, ‘consumer-grade’ refers to cameras that require system calibration by the user instead of by the manufacturer or other high-end laboratory settings, as well as relatively low-cost GNSS/INS units. In addition to classical spatial system calibration, many consumer-grade sensors also need temporal calibration for accurate 3D reconstruction. This study examines the accuracy impact of time delay in the synchronization between the GNSS/INS unit and cameras on-board UAV-based mapping systems. After reviewing existing strategies, this study presents two approaches (direct and indirect) to correct for time delay between GNSS/INS recorded event markers and actual time of image exposure. Our results show that both approaches are capable of handling and correcting this time delay, with the direct approach being more rigorous. When a time delay exists and the direct or indirect approach is applied, horizontal accuracy of 1–3 times the ground sampling distance (GSD) can be achieved without either the use of any ground control points (GCPs) or adjusting the original GNSS/INS trajectory information.

47 OTHER INSTRUMENTATION↗