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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An Advanced Cooling Device for Concentrated Photovoltaic Systems

Concentrated photovoltaics (CPV) have the potential to significantly enhance the energy conversion utilization of solar panels and reduce solar generation costs, making them a crucial area of advancement in solar power generation technology. However, the concentration of sunlight can lead to overheating of solar panels, resulting in a notable reduction in both the efficiency of solar power generation and the lifespan of the panels. This challenge remains the predominant technical hurdle that hinders the application of concentrated photovoltaic power generation technology. In this study, we propose a new cooling method for concentrated photovoltaic power generation systems via an integrated approach of incorporating Phase-Change Thermal Storage (PCTS) and Thermoelectric Generator (TEG) technology. This new method not only enhances the overall system's electricity generation efficiency but also effectively resolves the technical challenge of concentrated photovoltaic panel overheating issues, ensuring the continuity of concentrated photovoltaic power generation and extending the lifespan of solar panels and their components. In order to make full use of the wasted heat generated by photovoltaic power generation and effectively improve the power generation efficiency of the system, this work developed a phase change heat storage device based on a phase change material. This device uses the temperature difference between day and night to recover wasted heat from photovoltaic power generation. Through integration with the thermoelectric power generation system, thermal energy can be converted into electrical energy. In addition, the Peltier effect of thermoelectric materials is used to construct a photovoltaic panel overheating protection system, which significantly improves the reliability and service life of the system.

Gou, Yimeng↗
NASA NTRSDate not supplied

Design of a Dynamic Radioisotope Power System Generator Testbed

The Dynamic Radioisotope Power System (DRPS) Testbed is a configurable laboratory test article designed to demonstrate the latest topology of a dynamic radioisotope power system generator. It utilizes an array of Stirling convertors arranged around a centrally located heat source that is radiantly coupled to the convertor hot ends. The Testbed is designed to dissipate all the waste heat through the housing and is outfitted with means for auxiliary cooling methods as well. During the past three years, the team at NASA’s Glenn Research Center (GRC) has been designing and analyzing the various aspects of the DRPS Testbed. Currently, the parts for the Testbed are being manufactured, and the team is focusing on developing the test stand, supporting hardware, and assembly and operation procedures in preparation for the anticipated first operation of the DRPS Testbed in summer of 2022.

Generator↗
DOE OSTI2020

Induced Markov chain for wind farm generation forecasting

Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.

17 WIND ENERGY↗
NASA NTRS2009

NASA Missions Enabled by Space Nuclear Systems

This viewgraph presentation reviews NASA Space Missions that are enabled by Space Nuclear Systems. The topics include: 1) Space Nuclear System Applications; 2) Trade Space for Electric Power Systems; 3) Power Generation Specific Energy Trade Space; 4) Radioisotope Power Generation; 5) Radioisotope Missions; 6) Fission Power Generation; 7) Solar Powered Lunar Outpost; 8) Fission Powered Lunar Outpost; 9) Fission Electric Power Generation; and 10) Fission Nuclear Thermal Propulsion.

Scott, John H.↗
DOE OSTI2020

Predicting Solar Plant Generation with Machine Learning Techniques

Accurately predicting power generation for PV sites is critical for prioritizing relevant operations & maintenance activities, thereby extending the lifetime of a system and improving profit margins. A number of factors influence power generation at PV sites, including local weather, shading and soiling losses, design of modules, DC mismatches, and degradation over time. Other external factors such as curtailment and grid outages can also have a notable impact on power generation. Machine learning techniques can be used to provide more accurate predictions of PV power production by accounting for important weather and climate information neglected by current industry methods. This article will cover the deficiencies of those methods and will show how machine learning can dramatically improve power generation predictions.

14 SOLAR ENERGY↗
DOE OSTI2025

CLEAP Project: OR-SAGE Analysis for MT, UT, and CO States

The OR-SAGE tool is designed to use industry-accepted practices in screening sites and then employ the proper array of data sources through the considerable computational capabilities of GIS technology available at ORNL. The tool was developed to screen the potential for NPP siting on a national and regional basis. However, because of the tool granularity, it is often focused specifically on the immediate area around user sites of interest. If data center siting parameters can be added to OR-SAGE, the ability to evaluate data center siting on a localized scale will be beneficial.1 More than 60 data sets have been collected and processed by ORNL to develop exclusionary, avoidance, and suitability criteria for screening sites for a variety of power generation types, including nuclear power plants. Available site evaluation parameters include population density, slope, seismic activity, proximity to cooling-water sources, proximity to hazard facilities, avoidance of protected lands and floodplains, susceptibility to landslide hazards, and many others. All siting parameters should be considered as flags to inform siting decisions and should not be used to rule in or rule out any NPP site. Once data center siting parameters are identified, appropriate data sets will be collected and processed. The OR-SAGE process is very versatile. Essentially, OR-SAGE is a visual, relational database. The database partitions the contiguous United States, a total of 720 million hectares (~1.8 billion acres), into 100-m by 100-m (1 hectare or ~2.5 acre) cells. The database is tracking just under 700 million individual land cells. Successive suitability criterion is applied to each cell in the database. User-specified thresholds can be applied to each siting parameter data layer. In this manner, a variety of scenarios can be quickly and thoroughly evaluated. Data can be added and/or revised within OR-SAGE to address user interests. Siting security assessment capability is currently being added to OR-SAGE. Security is expected to be of concern at data centers whether it is collocated with a nuclear power generating technology or not. If data center is collocated with a nuclear power generating source, the security threat attractiveness level of both will likely increase. It will be of additional benefit if a potential data center site is also assessed for security vulnerability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Large Format Composite Additive Manufacturing for Low-Head Hydropower

Hydropower with a small elevation change from inlet to outlet, known as “low-head” hydropower, is a relatively untapped resource for reliable green power generation. One major barrier to entry is the cost of the components needed to generate the power. Each installation site is unique, with various head levels, flow rates, and other unique site characteristics that drive up the cost of development and installation. As a result, custom-made components are necessary because the sites are intrinsically inefficient. However, customized parts are generally more expensive to manufacture than ready-made parts. Often times, the cost of custom-made components is so high that the low-head hydropower installation becomes non-viable. Additive manufacturing offers the ability to make custom components, ideal for one-off applications, at low costs that are well suited for the needs of low-head hydropower. Indirect additive manufacturing, such as making tools or dies rather than end use components, can also be used to make low-cost composite tooling as needed for these custom applications. This paper explores the use of additive manufacturing, both directly and indirectly, to produce the components of a turbine system for a low-head hydropower site. The parts were designed to form a unique modular system, which saves time for future designs and iterations. The system has operated for more than three years without failure at a test site in Wisconsin, USA. This work serves as a basis for future application of AM to low-head systems, in which the modular components can be customized for each unique hydropower installation.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Technology for Bayton-cycle powerplants using solar and nuclear energy

Brayton cycle gas turbines have the potential to use either solar heat or nuclear reactors for generating from tens of kilowatts to tens of megawatts of power in space, all this from a single technology for the power generating system. Their development for solar energy dynamic power generation for the space station could be the first step in an evolution of such powerplants for a very wide range of applications. At the low power level of only 10 kWe, a power generating system has already demonstrated overall efficiency of 0.29 and operated 38 000 hr. Tests of improved components show that these components would raise that efficiency to 0.32, a value twice that demonstrated by any alternate concept. Because of this high efficiency, solar Brayton cycle power generators offer the potential to increase power per unit of solar collector area to levels exceeding four times that from photovoltaic powerplants using present technology for silicon solar cells. The technologies for solar mirrors and heat receivers are reviewed and assessed. This Brayton technology for solar powerplants is equally suitable for use with the nuclear reactors. The available long time creep data on the tantalum alloy ASTAR-811C show that such Brayton cycles can evolve to cycle peak temperatures of 1500 K (2240 F). And this same technology can be extended to generate 10 to 100 MW in space by exploiting existing technology for terrestrial gas turbines in the fields of both aircraft propulsion and stationary power generation.

English, R. E.↗
DOE OSTI2023

A net-zero emissions strategy for China’s power sector using carbon-capture utilization and storage

Decarbonized power systems are critical to mitigate climate change, yet methods to achieve a reliable and resilient near-zero power system are still under exploration. This study develops an hourly power system simulation model considering high-resolution geological constraints for carbon-capture-utilization-and-storage to explore the optimal solution for a reliable and resilient near-zero power system. This is applied to 31 provinces in China by simulating 10,450 scenarios combining different electricity storage durations and interprovincial transmission capacities, with various shares of abated fossil power with carbon-capture-utilization-and-storage. Here, we show that allowing up to 20% abated fossil fuel power generation in the power system could reduce the national total power shortage rate by up to 9.0 percentages in 2050 compared with a zero fossil fuel system. A lowest-cost scenario with 16% abated fossil fuel power generation in the system even causes 2.5% lower investment costs in the network (or $16.8 billion), and also increases system resilience by reducing power shortage during extreme climatic events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Neural Networks-Based Inverter Control: Modeling and Adaptive Optimization for Smart Distribution Networks

The optimal voltage control of inverter-based resources, especially under the high penetration of solar photovoltaics, is critical to the stability of the distribution power system. However, the computational complexity as well as the coordinated operation performance of the voltage control optimization in the distribution power system limits the real-time applications. To mitigate this issue, a model-free based adaptive optimal control scheme for the smart inverter is proposed to maximize the active power generation, minimize the power loss, and maintain the bus voltages in smart distribution networks. An inverter-based optimization model for coordinated operation is first established, considering the uncertainties of renewable power generation. Subsequently, by collecting the data and control strategies, the neural networks (NNs) based algorithm is proposed to efficiently predict the best possible control strategy. The main objective of this scheme is to accurately predict candidate optimal solutions with near-negligible feasibility and optimization gaps, with the advantage of avoiding complicated iteration-based numerical algorithms. Thereafter, the co-simulation among OpenDSS, MATLAB, and Python is set up to fully take advantage of the three individual software. Experiments are conducted based on different control parameter characteristics and structures of NNs. Finally, the results reveal that an average mean squared error of 0.013 and 1 ms response time are achieved, which is lower than some state-of-the-art methods.

42 ENGINEERING↗
DOE OSTI2026

PSH Assessment and Site Identification [Slides]

NLR's Pumped Storage Hydropower (PSH) geospatial and cost model algorithms are applied to the Chemehuevi Reservation to assess the potential for PSH within the reservation. The algorithm identifies both "open-loop" PSH opportunities formed by constructing a new reservoir within the reservation paired with bordering Lake Havasu and "closed-loop" systems formed by two new reservoirs within the reservation. Options range from 28 to 538 MW of electrical generation power at maximum generation and 10 hours of storage. CAPEX is estimates as 4422 2022 $\$$/kW of generating power, which is meaningfully higher than the lowest cost systems identified in NLR's national scale assessments. Further economic analysis is needed to fully evaluate whether this would be an attractive option to meet the Chemehuevi Reservation's goals.

25 ENERGY STORAGE↗
NASA NTRS1986

High voltage characteristics of the electrodynamic tether and the generation of power and propulsion

The Tethered Satellite System (TSS) will deploy and retrieve a satellite from the Space Shuttle orbiter with a tether of up to 100 km in length attached between the satellite and the orbiter. The characteristics of the TSS which are related to high voltages, electrical currents, energy storage, power, and the generation of plasma waves are described. A number of specific features of the tether system of importance in assessing the operational characteristics of the electrodynamic TSS are identified.

Williamson, P. R.↗
DOE OSTI2023

Pathway for decarbonizing residential building operations in the US and China beyond the mid-century

With global carbon budget targets looming, residential buildings in top economies must become carbon neutral as soon as possible to reserve more emission space for emerging carbon-emitting economies. This study is the first to compare the operational decarbonization process of China’s and the United States (US) residential buildings from 2000 to 2060 by combining the end-use emission model with the decomposing structural decomposition (DSD) method and Monte Carlo simulation. The results show that from 2001 to 2020 China decarbonized 1544 mega-tons of carbon dioxide (MtCO 2 ) and the US decarbonized 1848 MtCO 2 . In the business-as-usual scenario, China will hit its emission peak in 2031 (±3) with 934 (±61) MtCO 2 , while the US will maintain a lock-in level of 736 (±133) MtCO 2 since the 2030s. In the decarbonization scenario, operational carbon neutrality for residential buildings in 2060 is promoted by an increase in clean power generation proportion, building-integrated power generation level, building electrification level, and a reduction in end-use energy intensity, which will contribute 34.4 %, 21.4 %, 14.3 %, and 29.9 % in China and 32.9 %, 33.1 %, 8.2 %, and 25.8 % in the US, respectively. Especially, building-integrated power generation in China only costs about 40 % of what it costs in the US. Besides, high-decarbonization strategies for residential building operations are proposed as references for governments to formulate targeted climate policies. Overall, this study offers data benchmarks for buildings’ carbon neutrality of top economies to further promote synergistic carbon neutrality with the buildings of emerging economies in the age of Post COP27.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2002

A Systems Model for Power Technology Assessment

A computer model is under continuing development at NASA Glenn Research Center that enables first-order assessments of space power technology. The model, an evolution of NASA Glenn's Array Design Assessment Model (ADAM), is an Excel workbook that consists of numerous spreadsheets containing power technology performance data and sizing algorithms. Underlying the model is a number of databases that contain default values for various power generation, energy storage and power management and distribution component parameters. These databases are actively maintained by a team of systems analysts so that they contain state-of-art data as well as the most recent technology performance projections. Sizing of the power subsystems can be accomplished either by using an assumed mass specific power (W/kg) or energy (Wh/kg) or by a bottoms-up calculation that accounts for individual component performance and masses. The power generation, energy storage and power management and distribution subsystems are sized for given mission requirements for a baseline case and up to three alternatives. This allows four different power systems to be sized and compared using consistent assumptions and sizing algorithms. The component sizing models contained in the workbook are modular so that they can be easily maintained and updated. All significant input values have default values loaded from the databases that can be over-written by the user. The default data and sizing algorithms for each of the power subsystems are described in some detail. The user interface and workbook navigational features are also discussed. Finally, an example study case that illustrates the model's capability is presented.

Hoffman, David J.↗
DOE OSTI2020

Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M)

The second Wind Forecast Improvement Project (WFIP2) is a multi-agency field campaign held in the Columbia Gorge area (October 2015 - March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well-known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT&M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011 - August 2012). The RT&M was designed to explicitly measure the skill of NWP models at forecasting wind ramp events. Here we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and 3 lidars, and to forecasts from the High Resolution Rapid Refresh (HRRR), 3-km, and from the High Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of ramp events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.

Djalalova, Irina V.↗
NASA NTRS2015

Modular Stirling Radioisotope Generator

High efficiency radioisotope power generators will play an important role in future NASA space exploration missions. Stirling Radioisotope Generators (SRG) have been identified as a candidate generator technology capable of providing mission designers with an efficient, high specific power electrical generator. SRGs high conversion efficiency has the potential to extend the limited Pu-238 supply when compared with current Radioisotope Thermoelectric Generators (RTG). Due to budgetary constraints, the Advanced Stirling Radioisotope Generator (ASRG) was canceled in the fall of 2013. Over the past year a joint study by NASA and DOE called the Nuclear Power Assessment Study (NPAS) recommended that Stirling technologies continue to be explored. During the mission studies of the NPAS, spare SRGs were sometimes required to meet mission power system reliability requirements. This led to an additional mass penalty and increased isotope consumption levied on certain SRG-based missions. In an attempt to remove the spare power system, a new generator architecture is considered which could increase the reliability of a Stirling generator and provide a more fault-tolerant power system. This new generator called the Modular Stirling Radioisotope Generator (MSRG) employs multiple parallel Stirling convertor/controller strings, all of which share the heat from the General Purpose Heat Source (GPHS) modules. For this design, generators utilizing one to eight GPHS modules were analyzed, which provide about 50 to 450 watts DC to the spacecraft, respectively. Four Stirling convertors are arranged around each GPHS module resulting in from 4 to 32 Stirling/controller strings. The convertors are balanced either individually or in pairs, and are radiatively coupled to the GPHS modules. Heat is rejected through the housing/radiator which is similar in construction to the ASRG. Mass and power analysis for these systems indicate that specific power may be slightly lower than the ASRG and similar to the MMRTG. However, the reliability should be significantly increased compared to ASRG.

Stirling Cycle↗