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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mountain waves can impact wind power generation

Abstract. Mountains can modify the weather downstream of the terrain. In particular, when stably stratified air ascends a mountain barrier, buoyancy perturbations develop. These perturbations can trigger mountain waves downstream of the mountains that can reach deep into the atmospheric boundary layer where wind turbines operate. Several such cases of mountain waves occurred during the Second Wind Forecast Improvement Project (WFIP2) in the Columbia River basin in the lee of the Cascade Range bounding the states of Washington and Oregon in the Pacific Northwest of the United States. Signals from the mountain waves appear in boundary layer sodar and lidar observations as well as in nacelle wind speeds and power observations from wind plants. Weather Research and Forecasting (WRF) model simulations also produce mountain waves and are compared to satellite, lidar, and sodar observations. Simulated mountain wave wavelengths and wave propagation speeds (group velocities) are analyzed using the fast Fourier transform. We found that not all mountain waves exhibit the same speed and conclude that the speed of propagation, magnitudes of wind speeds, or wavelengths are important parameters for forecasters to recognize the risk for mountain waves and associated large drops or surges in power. When analyzing wind farm power output and nacelle wind speeds, we found that even small oscillations in wind speed caused by mountain waves can induce oscillations between full-rated power of a wind farm and half of the power output, depending on the position of the mountain wave's crests and troughs. For the wind plant analyzed in this paper, mountain-wave-induced fluctuations translate to approximately 11 % of the total wind farm output being influenced by mountain waves. Oscillations in measured wind speeds agree well with WRF simulations in timing and magnitude. We conclude that mountain waves can impact wind turbine and wind farm power output and, therefore, should be considered in complex terrain when designing, building, and forecasting for wind farms.

17 WIND ENERGY↗
DOE OSTI2025

Scintillator based nuclear photovoltaic batteries for power generation at microwatts level

A nuclear photovoltaic battery uses scintillator to convert radiation into visible light, which is then collected by a photovoltaic (PV) cell to generate electricity. If the radiation is gamma-rays emitted from external sources, the battery may also be referred as gammavoltaic battery. In this study, a polycrystalline CdTe solar cell was optically coupled with a 2.0 cm × 2.0 cm × 1.0 cm Gadolinium Aluminum Gallium Garnet (GAGG) scintillator, and the resulting device was tested using intense gamma radiation fields from a Cs-137 (1.5 kRad/h) and a Co-60 (10 kRad/h) irradiator. Measurements with Cs-137 provided a maximum power output (P max ) of ~288 nW, with a short-circuit current density (J sc ) of ~1.22 μA/cm 2 and an open-circuit voltage (V oc ) of ~0.34 V. In contrast, Co-60 irradiator gave a P max of 1.5 μW, with a J sc of ~4.73 μA/cm 2 and a V oc of ~0.38 V. The CdTe was also paired with a Lutetium-Yttrium Oxyorthosilicate (LYSO) crystal and tested with the Cs-137 source. The experiment presents a scalable option to reach to higher power outputs by harvesting gamma radiation fields in many cases where high radiation field demands heavy shielding and is often regarded as unwanted waste.

25 ENERGY STORAGE↗
DOE OSTI2026

Technoeconomic Opportunity Analysis for Local Power Generation in Falls City, Nebraska

Falls City is a small community in Nebraska interested in understanding how energy from local energy systems could support the community's economic development planning. To address the current community needs and address the future energy demand technical assistance conducted through the Communities Local Energy Action Program (Communities LEAP) assessed the technical and economic opportunities of adding energy technologies to Falls City's municipally owned and operated electric utility system. The modeling performed considered the technical and economic feasibility of technologies using the System Advisor Model (SAM). The modeling explored three technology configurations using multiple years of historical weather and wholesale cost data (2015-2022 & a typical meteorological year), and two different wholesale escalation rates (0.3% and 2.5%). Wholesale energy prices were based on the Southwest Power Pool's (SPP) real-time energy market and the annual escalation rates of these rates based on historical SPP wholesale and national retail electricity price trends. Results from the modeling showed that at current CAPEX costs and SPP wholesale electricity costs no technology combination averaged across the scenarios run provide a positive net present value (NPV). External financial support, changes in market conditions, and additional revenue streams would help create more economically favorable projects. As conditions change re-evaluation may be necessary.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Integration and Optimization of a Waste Heat Driven Organic Rankine Cycle for Power Generation in Wastewater Treatment Plants

The study focuses on achieving energy self-sufficiency in Wastewater Treatment Plants by proposing a comprehensive model for integrating, sizing, and optimizing an Organic Rankine Cycle system. The Organic Rankine Cycle system is designed to utilize waste heat from the gensets at As Samra Wastewater Treatment Plant in Jordan, where it will contribute to the overall electrical energy supply of the plant. Real data from As Samra Wastewater Treatment Plant is used to model and calculate the available waste heat using TRNSYS® software. The Organic Rankine Cycle model is then developed using ASPEN PLUS® software to explore the impact of operational parameters and determine their optimal values for maximizing the plant's energy profile. An economic analysis is conducted to assess the feasibility of the proposed model, considering system components, installation, operation, and maintenance costs. To optimize the Organic Rankine Cycle system, the study employs the Multi-Output Support Vector Regression technique to capture nonlinear relationships between independent variables (fluid type, turbine inlet pressure, turbine inlet temperature, turbine outlet pressure, and mass flow rate) and dependent variables (pump power input, waste heat input, and turbine specific work). The Osprey optimization algorithm is used to address the multi-objective optimization problem, with the proposed Pareto-based Osprey Optimization Algorithm and the Multi-Objective Particle Swarm Optimization technique being employed to evaluate critical performance and economic parameters such as system thermal efficiency, net power output, and the levelized cost of electricity. The results of the optimization strategies indicate that the M-SVR model's prediction accuracy is significantly improved after parameter optimization, with the model returning high R 2 and low Mean Square Error values of 0.991 and 0.00216, respectively. The Pareto-Based Osprey Optimization Algorithm optimizer identifies the best working fluid as Isobutane/Isopentane in a ratio of 66:34, with optimal turbine inlet pressure and temperature of 15 bars and 218 °C, respectively. In conclusion, the Organic Rankine Cycle model at these optimal conditions achieves a cycle efficiency of 19.93% and an Levelized Cost of Electricity value of 0.0353 USD/kWh.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Transparent Refractory Aerogels for Efficient Spectral Control in High–Temperature Solar Power Generation

Although spectrally selective materials play a key role in existing and emerging solar thermal technologies, temperature-related degradation currently limits their use to below 700 °C in vacuum and even lower temperatures in air. Here a solar-transparent refractory aerogel that offers stable performance up to 800 °C in air is demonstrated, which is significantly greater than its silica counterpart. This improved stability is attributed to the formation of a refractory aluminum silicate phase, which is synthesized using a conformal single cycle of atomic layer deposition within the high-aspect-ratio pores of silica aerogels. Furthermore, based on direct heat loss measurements, the transparent refractory aerogel achieves a receiver efficiency of 75% at 100 suns and an absorber temperature of 700 °C, which is a 5% improvement over the state of the art. Transparent refractory aerogels may find widespread applicability in solar thermal technologies by enabling the use of lower-cost optical focusing systems and eliminating the need for highly evacuated receivers. In particular, a shift to higher operating temperatures while maintaining a high receiver efficiency can enable the use of advanced supercritical CO 2 power cycles and ultimately translate to an ≈10% (absolute) improvement in solar-to-electrical conversion efficiency relative to existing linear concentrating systems.

14 SOLAR ENERGY↗
DOE OSTI2021

Power Generation and Oxygen Transfer Analyses for Micro Hydro-Turbine Installed in Wastewater Treatment Aeration Tank

This study targets one of the major energy consumers in the U.S. It suggests a new mechanical system that can recover a portion of the energy in Wastewater Treatment Plants (WWTPs). The proposed system entails a hydro-turbine installed above the air diffuser in the aeration tank to extract the water-bubble current’s kinetic energy and converts it to electricity. Observing the optimum location of the turbine required multiple experiments where turbine height varies between 35% and 95% (water height percentages above the diffuser), while varying the airflow between 1.42 L/s (3 CFM) and 2.12 L/s (4.5 CFM) with a 0.24 L/s (0.5 CFM) increment. Additionally, three water heights of 38.1 cm (15*), 53.4 cm (21*), and 68.6 cm (27*) were considered to study the influence of the water height. It was noticed that the presence of the system has an adverse effect on the standard oxygen transfer efficiency (SOTE). Therefore, a small dual-blade propeller was installed right above the diffuser to directly mix the water in the bottom of the tank with the incoming air to enhance the SOTE. The results showed that the maximum reclaimed power was obtained where the hydro-turbine is installed at 65–80% above the diffuser. A reduction of up to 7.32% in SOTE was observed when the setup was placed inside the tank compared to the tank alone. The addition of the dual-blade propeller showed an increase in SOTE of 7.27% with a power loss of 6.21%, ensuring the aeration process was at its standards.

Energy & Fuels↗
DOE OSTI2026

Lithography-Free Mesa Isolation by Laser Ablation for Multijunction III-V Photovoltaic Space Power Generation

Eliminating photolithography from photovoltaic device processing is a significant opportunity for cost reduction and increased manufacturing throughput. In this work, we test femtosecond laser ablation and scribing as an alternative to contact photolithography and wet chemical etching for mesa isolation of multijunction devices. We demonstrate that upright multijunction devices isolated by using the laser as a scribe to cleave through the substrate had virtually no performance loss when compared to a baseline device processed with photolithography. By contrast, devices isolated by laser ablating through the active layers have performance losses that cannot be fully eliminated with postprocess etching. This demonstration of photolithography-free mesa isolation with no performance losses is promising as a pathway to less expensive and higher throughput III-V device manufacturing.

14 SOLAR ENERGY↗
DOE OSTI2022

Nanostructured carbon as highly efficient and stable anodes for ethylene production and power generation in protonic ceramic electrochemical cells

Protonic ceramic electrochemical cells (PCECs) have the potential in reducing the energy input and carbon emissions in ethylene production from ethane dehydrogenation. The performance of conventional perovskite-based anode materials for ethane conversion in PCECs is limited by their low active surface area and proneness to coke deposition. In this work, for the first time, we demonstrate the use of aligned carbon nanotube forests (CNTFs) as a novel anode material for an ethane fueled PCEC to co-produce ethylene and electricity. The CNTF electrode was grown on the electrolyte by the chemical vapor deposition (CVD) method. Highly dispersed iron carbide nanoparticles are formed in situ on the CNTFs during the CVD process, acting as highly active catalysts for ethane dehydrogenation. The novel PCECs show superior catalytic and electrochemical performances to that using conventional perovskite-based anodes. The cell also exhibits excellent durability and anti-coking abilities within 100 h test. This work showcases the promising application of nanostructured carbon, a new class of non-perovskite materials, as the multifunctional electrode materials for PCECs.

03 NATURAL GAS↗
DOE OSTI2021

Rotor blade imbalance fault detection for variable-speed marine current turbines via generator power signal analysis

Marine hydrokinetic (MHK) turbines extract renewable energy from oceanic environments. However, due to the harsh conditions that these turbines operate in, system performance naturally degrades over time. Thus, ensuring efficient condition-based maintenance is imperative towards guaranteeing reliable operation and reduced costs for marine hydrokinetic power. This work proposes a novel framework aimed at identifying and classifying the severity of rotor blade pitch imbalance faults experienced by marine current turbines (MCTs). In the framework, a Continuous Morlet Wavelet Transform (CMWT) is first utilized to acquire the wavelet coefficients encompassed within the 1P frequency range of the turbine's rotor shaft. From these coefficients, several statistical indices are tabulated into a six-dimensional feature space. Next, Principle Component Analysis (PCA) is employed on the resulting feature space for dimensionality reduction, and then the application of a K-Nearest Neighbor (KNN) machine learning algorithm is utilized for fault detection and severity classification. The effectiveness of the proposed framework is validated using a high-fidelity MCT numerical simulation platform, where results demonstrate that the presence of a pitch imbalance fault can be accurately detected 100% of the time and correctly classified based upon severity more than 97% of the time.

42 ENGINEERING↗