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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Renewable Energy at NASA's Johnson Space Center

NASA's Johnson Space Center has implemented a great number of renewable energy systems. Renewable energy systems are necessary to research and implement if we humans are expected to continue to grow and thrive on this planet. These systems generate energy using renewable sources - water, wind, sun - things that we will not run out of. Johnson Space Center is helping to pave the way by installing and studying various renewable energy systems. The objective of this report will be to examine the completed renewable energy projects at NASA's Johnson Space Center for a time span of ten years, beginning in 2003 and ending in early 2014. This report will analyze the success of each project based on actual vs. projected savings and actual vs. projected efficiency. Additionally, both positive and negative experiences are documented so that lessons may be learned from past experiences. NASA is incorporating renewable energy wherever it can, including into buildings. According to the 2012 JSC Annual Sustainability Report, there are 321,660 square feet of green building space on JSC's campus. The two projects discussed here are major contributors to that statistic. These buildings were designed to meet various Leadership in Energy and Environmental Design (LEED) Certification criteria. LEED Certified buildings use 30 to 50 percent less energy and water compared to non-LEED buildings. The objectives of this project were to examine data from the renewable energy systems in two of the green buildings onsite - Building 12 and Building 20. In Building 12, data was examined from the solar photovoltaic arrays. In Building 20, data was examined from the solar water heater system. By examining the data from the two buildings, it could be determined if the renewable energy systems are operating efficiently. Objectives In Building 12, the data from the solar photovoltaic arrays shows that the system is continuously collecting energy from the sun, as shown by the graph below. Building 12 has two solar inverters, located on the second floor, that collected the data from the solar photovoltaic arrays. The data displayed here is the total energy produced by the system. These are cumulative amounts, so the last point on the graph shows all of the energy collected from the system since the start of its operation. The data shown here was manually collected from the solar inverters. However, the data is also automatically recorded through EBI. Through analysis of both sets of data it was determined that the EBI data was faulty. For example, from the manually collected data it can be determined that a total of 73 kWh of energy was collected between the dates of 1/16/2014 – 1/22/2014. The EBI data reports that approximately 17800 kWh of energy was collected during the same time frame. Not only does this exceed the time frame examined, but it also exceeds the total energy collected from the start of collection as recorded from the inverters. This leads to the belief that there is a malfunction with the automatic recording of the energy. In Building 20, data was examined from the solar water heater dating back many months and found that the pump for the solar water heater system was not operating properly, as exhibited in the graph shown below. The pump operates on a solar energy system, meaning that it collects energy throughout the day from the sun. Because of this, the system would stop operating shortly after the sun set because of a lack of sunlight. At that point, the graph should show a zero flow rate, but as exhibited in the graph below, that is not the case. It is clearly shown that the pump is continuously operating, even during the night. It was also observed that the majority of the time the pump would not turn on at all, despite good weather conditions. This led to the conclusion that the pump is malfunctioning, and needs to be examined and fixed.

McDowall, Lindsay↗
NASA NTRS2015

Enhancing the NASA Prediction of Worldwide Energy Resource Web Data Delivery System with Geographic Information System (GIS) Capabilities

Renewable energy technologies are changing the face of the world's energy market. Currently, these technologies are being incorporated within existing structures to increase energy efficiency. Crucial to the success of the emerging renewable market is the availability of accurate, global solar radiation, and meteorology data. This poster traces the history of the development of an effort to distribute data parameters from NASA's research for use in the energy sector applications spanning from renewable energy to energy efficiency. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings.

Chandler, William S.↗
DOE OSTI2023

Solar Energy from a Big Picture Perspective to Nanoscale Insights via TOF-SIMS

The world is undergoing a rapid transformation in the ways that we generate and store energy. This has been driven not only by concerns about the climate but by simple economic factors due to the dramatic cost decreases in wind in solar power. In most places of the world where one would now want to build a new power plant, the cheapest option is to use wind of solar for power generation. Abundant clean energy when the sun shines most is driving new research for daily and seasonal energy storage in many different technologies. Here, we will briefly these discuss energy trends as a whole, before diving into our recent contributions to the field using time-of-flight secondary-ion mass spectrometry (TOF-SIMS) to improve the performance and reliability of solar cells.

14 SOLAR ENERGY↗
DOE OSTI2024

Evaluation of the Turbine Integrated Mortality Reduction (TIMR SM ) Technology as a Smart Curtailment Approach (Final Summary Report)

Wind energy is a crucial technology for achieving net-zero emissions by 2050. However, the growth and deployment of wind energy in North America have led to the deaths of many bat species due to operating wind turbines. Hundreds of thousands of bats are estimated to die at wind turbines annually in North America. Operational minimization, which includes feathering turbine blades and curtailment, has been documented to reduce bat fatality effectively. Curtailment refers to altering turbine operation based on wind speed, time of year, temperature, sensors, and activity models. However, when turbines are curtailed, they do not generate power, resulting in energy loss and revenue for wind energy facilities. The Electric Power Research Institute (EPRI) funded the development of Turbine Integrated Mortality Reduction (TIM SM ) Technology, which curtails turbine operation when bats are detected. The initial TIMR system research showed promising results, with an 85% reduction in overall bat fatalities and a 91% reduction for the little brown bat. However, these results were based on a single site during one fall season, and it was unclear if similar results could be replicated at other wind energy facilities. This research aimed to validate the TIMR system results from the prior field study at a second site in the U.S., estimate the power production and reduction in bat mortality at turbines with installed TIMR systems relative to blanket curtailment and fully operational turbines, test the TIMR system in two calendar years and during the summer and fall periods, and evaluate the operational and commercial characteristics of the TIMR system for potential wind industry adoption. The study was conducted at a 500.9-MW wind energy facility in southeast Adair County, Iowa. Three experimental treatments were involved in this randomized block design study: TIMR, Curtailment at 5.0 m/s, and Normal Operation. In 2021, three treatments were used at 18 turbines, expanding to four treatments across 36 turbines in 2022. The TIMR system worked as designed throughout the entire study; however, because of unexpected wind turbine operational challenges in 2021, there was not sufficient sample size to evaluate the treatment differences. In 2022, there were significant differences in fatality levels between treatment types and normal operating turbines. Curtailment at 5.0 m/s reduced fatalities by 30.8% compared to normal operations, and TIMR decreased fatalities by 48.6% compared to normal operations. Two different methods were used to evaluate the differences in energy loss for each treatment. The TIMR system resulted in 1.3% to 1.6 % annual energy loss in 2021 and 1.0% to 1.2 % in 2022. The Curtailment at 5.0 m/s resulted in 0.6% to 0.8 % annual energy loss in 2021 and 0.5% to 0.6 % in 2022. The project achieved all the stated objectives and demonstrated that TIMR is an effective technology that balances bat fatality reduction with energy generation. The results will support the deployment of TIMR and other acoustic sensor-based technologies. The research provides valuable insights into the impact of different treatments on fatality rates and energy outputs, contributing to the ongoing efforts to mitigate the environmental impact of wind energy.

17 WIND ENERGY↗
DOE OSTI2022

Evaluating Grid Strength under Uncertain Renewable Generation

The increasing displacement of synchronous generators with renewable resources such as wind and solar via power electronic interfaces causes a reduction in short-circuit strength and weak grid issues. The variation and uncertainty of renewable energy increase challenges for identifying weak grid conditions. This paper proposes an efficient method to analyze the impact of uncertain renewable energy on grid strength. The proposed method uses the probabilistic collocation method (PCM) to approximate the results of grid strength assessment under uncertain renewable generation, in order to reduce computational burden without compromising result accuracy when compared with traditional Monte Carlo simulation (MCS). To improve the accuracy of the approximation results, the proposed method integrates the K-means clustering technique with PCM to select the approximation samples of input variables. The efficacy of the proposed method is demonstrated by comparison with MCS on the modified IEEE 9-bus system and modified IEEE 39-bus system with multiple renewable generators.

grid strength↗
DOE OSTI2020

Exploring Renewable Energy Opportunities in Select Southeast Asian Countries: A Geospatial Analysis of the Levelized Cost of Energy of Utility-Scale Wind and Solar Photovoltaics

The costs of renewable energy-based electricity generation have fallen precipitously in recent years to levels that are increasingly competitive with traditional generation such as fossil fuel-based generation. As these costs become increasingly competitive, private developers, policymakers, and energy system planners are searching for opportunities to harness high-quality renewable energy resources. Developing economies are setting ambitious targets and exploring how cost-effective, grid-connected renewable energy options can help power economic growth and meet growing electricity demands. This includes the member states of the Association of Southeast Asian Nations (ASEAN) that are determined to reach a target of 23% of renewable energy in the region's total primary energy supply by 2025. A critical gap to identifying opportunities and scaling up renewable energy is the lack of quality data and analyses to support decisions on the investment and deployment of renewables - including wind and solar photovoltaics (PV). This work supports decision making by providing high-quality data and spatial analysis of the cost of utility-scale wind and solar PV generation in select countries of Southeast Asia - specifically, the ASEAN member states. Generation costs are expressed as the levelized cost of energy (LCOE) - a commonly used metric that represents the net present value of the unit cost of electricity during the lifetime of a particular electricity generation technology. This is the first spatial estimate of LCOE for these technologies within the ASEAN member states - providing insights into the roles that renewable energy resource quality and other factors may play in generation costs.

14 SOLAR ENERGY↗
DOE OSTI2021

Renewable energy analysis in indigenous communities using bottom-up demand prediction

This paper provides a methodology for the holistic analysis of hybrid renewable energy systems in rural communities. Electric demand is an important component for modeling and analysis of renewable energy systems. Typically, electric demand data is not available due to the internal privacy policies of utility providers. Therefore, this study proposes the use of bottom-up approaches for the development of the electric demand profile, considering the general homogeneity of residential and commercial buildings in rural communities. As a test case, this study develops the electric demand profile and investigates the technical and environmental feasibility of a hybrid renewable energy system for the New Town community on the Fort Berthold Indian Reservation (FBIR) in North Dakota. This study conducts the hybrid renewable energy system’s analysis by developing scripts in the LK scripting language and integrating System Advisor Model software’s open-source modules for modeling of renewable energy systems. Here, the results for the validation testbed of this study show that hybrid renewable resources have higher ratios of energy used for self-consumption to the total energy generated compared to stand-alone wind and PV farms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

American WAKE experimeNt (AWAKEN)

The American WAKE experimeNt (AWAKEN) is an international multi-institutional wind energy field campaign to better understand wake losses within operational wind farms. Wake interactions are among the least understood physical interactions in wind plants today, leading to unexpected power and profit losses. For example, Ørsted, the world’s largest offshore wind farm developer, recently announced a downward revision in energy estimates across their energy generation portfolio, primarily caused by underprediction of energy losses from wind farm blockage and wakes. In their announcement, they noted that the standard industry models used for their original energy estimates were inaccurate, and this was likely an industry-wide issue. To help further improve and validate wind plant models across scales from individual turbines as well as interfarm interactions between plants, new observations, such as those planned for AWAKEN, are critical. These model improvements will enable both improved layout and more optimal operation of wind farms with greater power production and improved reliability, ultimately leading to lower wind energy costs.

17 WIND ENERGY↗
DOE OSTI2022

Modeling Needs to Support the Reconstruction Strategy of Ukraine

Ukraine has been facing difficult times. Russia started a full-scale invasion on February 24, 2022, and has caused huge human and infrastructure losses. As a result of the invasion, more than 8 million people left their homes. The Russian army has targeted Ukrainian energy sources, destroying or damaging over 50% of thermal power generation capacity (coal and gas), 30% of solar generation, and 90% of wind generation. The Russians are also threatening Ukrainian energy security, as they currently control the Zaporizhzhia nuclear power plant – Europe’s largest. In addition, Russia has destroyed 121,000 buildings, including 5,300 multistory buildings - more buildings than Ukraine built during the past five years. The occupiers destroyed or damaged 343 district heat boiler stations (destroyed 12 / damaged 331) and 8 CHPs (destroyed 4/ damaged 4). There is no doubt that Ukraine will be able to protect its sovereignty and restore its territorial integrity; however, this will be a long process. The Government of Ukraine needs to simultaneously focus on many issues, from waging war to the restoration of electricity, water, and heat supply in the territories close to the front line. In addition to these time-sensitive issues, the government also needs to plan a long term multi-sector strategy for the reconstruction of Ukraine’s economy. Ukraine initiated a broad-based political process for recovery at the International Ukraine Recovery Conference (URC 2022) in Lugano, Switzerland. Prior to URC 2022, Ukraine applied for EU membership on February 28 and was granted the status of candidate country by the European Council on June 23, 2022. More than 40 nations are fully committed to supporting Ukraine throughout its path from early to long-term recovery. In addition, these countries link a successful recovery to Ukraine’s European future (URC, 2022a). The reconstruction process will be long. The government also recognizes that it is not enough to build energy infrastructure back – it should be built back better. The government is committed to building a more sustainable and cleaner energy sector. Energy modeling can provide important insights into paths to decarbonize Ukraine’s economy while rebuilding it after the war. Pacific Northwest National Laboratory (PNNL) and the Institute for Economics and Forecasting of the National Academy of Sciences of Ukraine (IEF) work on modeling decarbonization scenarios in the energy sector of Ukraine. The teams focus on the heat sector, which includes district heat, autonomous and individual heating, and energy consumption by final energy consumption sectors, including buildings. Since the teams use world-class integrated assessment models, other sectors will be analyzed as well. The purpose of the document is to describe the needs of key Ukrainian ministries in modeling the reconstruction process. The scope of this document is limited to modeling energy consumption by the power and heat sectors, final energy consumption by buildings, and GHG emissions from these two sectors. The rest of this policy memo is organized as follows. After this introduction, Chapter 2 discusses key provisions of the reconstruction strategy with a focus on energy, buildings, heat supply, environment, and European integration aspirations. Section 3 provides an overview of recent developments and key decisions of the Government of Ukraine in the area of energy efficiency and decarbonization. Finally, Section 4 provides key suggestions on how PNNL and IEF can help the Government of Ukraine in developing strategic documents.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

A Multi-Fidelity Gaussian Process Regression Method for Probabilistic Wind Farm Power Curve Estimation

Accurate estimation of the power curve for wind turbines or wind farms is crucial to ensure their efficient operation and management. However, conventional methods for power curve estimation rely either on expensive and infrequent measurements or on low-quality numerical simulations. Moreover, the majority of previous studies on power curve estimation for wind turbines or wind farms focused on deterministic estimation, which provides a point estimate of the relationship between wind speed and power generation. Nevertheless, the deterministic approach fails to consider the inherent uncertainty associated with wind energy production resulting from varying turbine characteristics. This can lead to inaccurate power generation estimation and suboptimal decisions regarding energy management. In this paper, a kernel density estimation (KDE) based Multi-Fidelity Gaussian Process Regression (MFGPR) model is proposed to fuse theoretical power curve data and the ground true measurements to create a mapping of wind speed and wind power. By conducting a case study on an actual wind farm in China, the efficacy of the proposed MFGPR model was demonstrated in characterizing the variability of wind power. The probabilistic MFGPR model was also able to generate confidence intervals that encompassed the measured power, thereby improving the accuracy and confidence in wind power estimation or wind resource assessment. Overall, the proposed MFGPR model offers a reliable approach to integrate high-fidelity ground measurements and theoretical power curve data, resulting in precise wind resource assessment and power estimation.

Gaussian process regression↗
DOE OSTI2025

Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts

This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. As a result, this research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.

17 WIND ENERGY↗
DOE OSTI2022

Cyber-Physical Resiliency for Wind Power Generation

During the next three years, wind power generation is expected to add more generation capacity to the national electrical grid than any other energy sector. With new wind turbine designs rated power over 10 MW and wind farms reaching over 1 GW capacities, the consequences of cyber-attacks on wind power generation are becoming increasingly more critical. Moreover, the known vulnerabilities of wind turbine control systems and the potential damaging effects of intrusions, motivate an urgent protection improvement for the wind power generation sector. This program has developed a variety of new adaptive defense technologies that enable wind power generation systems to survive sophisticated cyberattacks by enhancing the control systems capabilities of detection, localization, and accommodation. The introduction of these technologies in the on-shore and the emerging off-shore market will result in a significantly more reliable and secure wind power infrastructure.

17 WIND ENERGY↗
DOE OSTI2023

Multistage robust optimization for the day-ahead scheduling of hybrid thermal-hydro-wind-solar systems

The integration of large-scale uncertain and uncontrollable wind and solar power generation has brought new challenges to the operations of modern power systems. In a power system with abundant water resources, hydroelectric generation with high operational flexibility is a powerful tool to promote a higher penetration of wind and solar power generation. In this paper, we study the day-ahead scheduling of a thermal-hydro-wind-solar power system. The uncertainties of renewable energy generation, including uncertain natural water inflow and wind/solar power output, are taken into consideration. We explore how the operational flexibility of hydroelectric generation and the coordination of thermal-hydro power can be utilized to hedge against uncertain wind/solar power under a multistage robust optimization (MRO) framework. To address the computational issue, mixed decision rules are employed to reformulate the original MRO model with a multi-level structure into a bi-level one. Column-and-constraint generation (C &CG) algorithm is extended into the MRO case to solve the bi-level model. The proposed optimization approach is tested in three real-world cases. Furthermore, the computational results demonstrate the capability of hydroelectric generation to promote the accommodation of uncertain wind and solar power.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Advanced Microstructured BaTiO 3 -Embedded PVDF–HFP/PEO Film for Enhanced Triboelectric Interface in Self-Sufficient Energy Generation and Sensing

The global reliance on fossil fuels and natural gas has largely dominated the energy production field, but due to finite resource depletion and escalating greenhouse gas emissions, the immediate exploration of sustainable energy alternatives to mitigate climate change and ensure resource security has been a major concern. There has been extensive research into other more renewable methods of energy production, such as wind and hydropower. Of these current energy generation types, there are many areas of untapped potential from the mechanical movements generated ambiently not only in the large scale of power generation but also on a smaller scale. The piezoelectric and triboelectric effects are phenomena where these ambient mechanical movements can generate electrical energy. Developing a hybrid system that leverages both mechanical stress and surface charges presents an ideal opportunity to exploit these untapped energy sources. Producing a hybrid PVDF–HFP/PEO film with perovskite BaTiO 3 (BTO) enables ambient power harvesting from both mechanical movement and surface charge. The optimized cell produced a potential of up to 15 V and a current of 200 nA with a 68 kΩ resistor, a substantial increase from a base system with an average of 2.1 V and 40 nA. These hybrid TENGs offer significant potential for energy harvesting in small-scale applications, such as health monitoring devices and indicators in electric circuits.

Ybarra, Rigobert [University of Texas Rio Grande V↗
DOE OSTI2025

Workshop Report: Rural Electric Cooperative Distributed Energy Resource Business Model Development Workshops

The United States' energy future is being shaped by decades of technology innovation, rapidly changing consumer requirements, and governmental focus on securing reliable, low-cost energy sources. With expanded electrification and increased emphasis on grid reliability coupled with the heightened complexity and risks associated with transmission infrastructure, the use of distributed energy resources (DERs) is more commonly being considered a safe, efficient, and cost-effective way to maintain grid resilience and reliability. Amidst improvements in performance, decreasing costs, and unprecedented federal policy support for DERs, electric cooperatives are considering new opportunities to use these assets to ensure secure and reliable operations for millions of customers. In light of these developments, a series of workshops were held to collaborate on the development of business models for DERs in rural electric cooperative ecosystems. The first workshop was held July 11, 2024, at the Tri-State Generation and Transmission Association Inc. headquarters in Westminster, Colorado (hereafter referred to as the "Tri-State Workshop"). The second workshop was hosted by PNGC Power on Oct. 9, 2024, in Portland, Oregon (hereafter referred to as the "PNGC Power Workshop"). These workshops convened representatives from G&Ts, distribution cooperatives,2 the energy industry, the financial community, the U.S. government, national and regional organizations, and national laboratories to share perspectives on the unique needs, challenges, and opportunities that they face as DERs are further integrated into the grid. The workshops were designed to address the following objectives: (1) develop the enabling attributes of electric cooperative DER business models, (2) explore pathways for generating community benefits from these assets, and (3) identify technical challenges and market risks for DERs in rural electric cooperative service territories. This report outlines key findings and major themes identified by workshop participants that federal agencies, G&Ts, distribution cooperatives, and other entities can consider to advance electric cooperative DER business models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Inter-Area Oscillation Damping with Type-5 Wind Power Plant

This paper investigates the potential of using brushless excitation (BLE) for not only riding through the fault but also to damp inter-area power oscillation with the help of a synchronous generator (SG) used in Type 5 Wind Power Plant (WPP). In BLE, an auxiliary synchronous generator (ASG) behaving like an exciter is coupled and driven by the rotor of the main SG. The BLE's field current's ASG is fed by two separate loops of the automatic voltage regulator (AVR) and power system stabilizer (PSS). The AVR system implements a control loop to regulate the generator terminal voltage, VT. For the PSS, the kinetic energy of the wind turbine is utilized according to the estimated rotational speed of the synchronous generator shaft of the SG. It may mitigate the necessity of any curtailment of active power for damping. The effectiveness of the proposed control scheme is verified with a three-phase short circuit fault in a two-area power system.

brushless↗
DOE OSTI2023

Inter-Area Oscillation Damping with Type-5 Wind Power Plant: Preprint

This paper investigates the potential of using brushless excitation (BLE) for not only riding through the fault but also to damp inter-area power oscillation with the help of a synchronous generator (SG) used in Type 5 Wind Power Plant (WPP). In BLE, an auxiliary synchronous generator (ASG) behaving like an exciter is coupled and driven by the rotor of the main SG. The BLE's field current's ASG is fed by two separate loops of the automatic voltage regulator (AVR) and Power System Stabilizer (PSS). The AVR system implements a control loop to regulate the generator terminal voltage, VT. For the PSS, the kinetic energy of the wind turbine is utilized according to the estimated rotational speed of the synchronous generator shaft of the SG. It mitigates the necessity of any curtailment of active power for damping. The effectiveness of the proposed control scheme is verified with a three-phase short circuit fault in a two-area power system.

brushless↗