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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Analysis of solar receiver flux distributions for US/Russian solar dynamic system demonstration on the MIR Space Station

The United States and Russia have agreed to jointly develop a solar dynamic (SD) system for flight demonstration on the Russian MIR space station starting in late 1997. Two important components of this SD system are the solar concentrator and heat receiver provided by Russia and the U.S., respectively. This paper describes optical analysis of the concentrator and solar flux predictions on target receiver surfaces. The optical analysis is performed using the code CIRCE2. These analyses account for finite sun size with limb darkening, concentrator surface slope and position errors, concentrator petal thermal deformation, gaps between petals, and the shading effect of the receiver support struts. The receiver spatial flux distributions are then combined with concentrator shadowing predictions. Geometric shadowing patterns are traced from the concentrator to the target receiver surfaces. These patterns vary with time depending on the chosen MIR flight attitude and orbital mechanics of the MIR spacecraft. The resulting predictions provide spatial and temporal receiver flux distributions for any specified mission profile. The impact these flux distributions have on receiver design and control of the Brayton engine are discussed.

Kerslake, Thomas W.↗
NASA NTRS1995

Analysis of Solar Receiver Flux Distributions for US/Russian Solar Dynamic System Demonstration on the MIR Space Station

Analyses have been performed at the NASA Lewis Research Center's Power Systems Project Office to support the design and development of the joint U.S./Russian Solar Dynamic Flight Demonstration Project. The optical analysis of the concentrator and solar flux predictions on target receiver surfaces have an important influence on receiver design and control of the Brayton engine.

Source record↗
DOE OSTI2019

Adaptive Voltage Regulation for Solar Power Inverters on Distribution Systems

The most recent version of IEEE 1547 has incorporated four reactive power control modes, including constant power factor, voltage-reactive power (Volt-Var), active power-reactive power and constant reactive power. These modes are specified to be mutually exclusive, and they don’t include every smart inverter function proposed by industry collaboration. In earlier work, we found that Volt-Var settings could be optimized but were sensitive to changes in the normal grid voltage. This sensitivity can be mitigated by combining Volt-Var with dynamic reactive current (DRC), but neither DRC nor combined modes appear in IEEE 1547. One problem with Volt-Var is the default dead-band; it mitigates the sensitivity to setpoint, but also limits the effectiveness in managing voltage fluctuations. There has been continued interest in tuning smart inverter functions locally, and in combining central with local control, but this process still requires extensive simulations. The goal is to find a default inverter setting that will effectively mitigate voltage fluctuations even as grid conditions change. It must be compatible with the current version of IEEE 1547. It should also be compatible with advanced control methods when available. Otherwise, it should not require communications, detailed engineering studies or field commissioning of custom settings. This would facilitate the integration of distributed solar in larger amounts. Adaptive voltage regulation (AVR) is a Volt-Var implementation, but with “autonomously adjusting” setpoint as described below Table 8 in IEEE 1547. Through simulation of a test system in OpenDSS, it was shown that AVR having a high gain and a time constant of 300 seconds could work well in any location. This mode and setting should be considered for a new universal default setting on smart inverters.

McDermott, Thomas E.↗
DOE OSTI2024

Cyber-Secure and Safe Operation of Solar Photovoltaic Power Distribution Systems

Solar photovoltaic (PV)-rich power distribution systems are networked Cyber-Physical Systems (CPS). These are control systems where multiple computing nodes and diverse intelligent agents interact with the physical world in real-time. However, the presence of networked components renders them vulnerable to potential cyber-attacks, cyber-intrusions, and other malicious events. This is because these systems depend on the measurements reported from their heterogeneous sensors. This makes them vulnerable to potential cyber-attacks where malicious agents can compromise the sensors or the communication networks carrying the sensor measurements. This paper proposes a novel methodology for enhancing the cyber-security and cyber-resilient post-attack safe operation of solar PV-rich power distribution systems against potential cyber-attacks through the Dynamic Watermarking (DW), using online system identification. The resiliency of the proposed technique is tested and validated with several attack scenarios on both a lab-scale 3kW grid-connected PV inverter and a Hardware-in-the-Loop (HiL) system. The proposed approach can be applied to other types of power distribution systems to enhance their cyber-secure and cyber-resilient safe operation. This paper thereby contributes to the field of cyber-security of Cyber-Physical Energy Systems (CPES).

Kim, Jaewon↗
NASA NTRS1978

Comparative evaluation of distributed-collector solar thermal electric power plants

Distributed-collector solar thermal-electric power plants are compared by projecting power plant economics of selected systems to the 1990-2000 timeframe. The approach taken is to evaluate the performance of the selected systems under the same weather conditions. Capital and operational costs are estimated for each system. Energy costs are calculated for different plant sizes based on the plant performance and the corresponding capital and maintenance costs. Optimum systems are then determined as the systems with the minimum energy costs for a given load factor. The optimum system is comprised of the best combination of subsystems which give the minimum energy cost for every plant size. Sensitivity analysis is done around the optimum point for various plant parameters.

Fujita, T.↗
NASA NTRS1989

Simplified calculation of solar flux distribution on the side wall of cylindrical cavity solar receivers

A simple solar flux calculation algorithm for a cylindrical cavity type solar receiver has been developed and implemented on an IBM PC-AT. Using cone optics, the contour error method is utilized to handle the slope error of a paraboloidal concentrator. The flux distribution on the side wall is calculated by integration of the energy incident from cones emanating from all the differential elements on the concentrator. The calculations are done for any set of dimensions and properties of the receiver and the concentrator, and account for any spillover on the aperture plate. The results of this algorithm compared excellently with those predicted by more complicated programs. Because of the utilization of axial symmetry and overall simplification, it is extremely fast. It can be esily extended to other axisymmetric receiver geometries.

Bhandari, P.↗
NASA NTRS1986

Distribution of solar wind implanted noble gases in lunar samples

The distribution of solar wind implanted noble gases in lunar samples depends on implantation energy, fluence, diffusion, radiation damage and erosion. It is known that at least the lighter rare gases are fractionated after implantation, but the redistribution processes, which mainly drive the losses, are not well understood. Some information about this one can get by looking at the concentration profiles of solar wind implanted He-4 measured by the Gas Ion Probe in single lunar grains. The observed profiles were divided in three groups. These groups are illustrated and briefly discussed.

Kiko, J.↗
NASA NTRS2012

Size Distributions of Solar Flares and Solar Energetic Particle Events

We suggest that the flatter size distribution of solar energetic proton (SEP) events relative to that of flare soft X-ray (SXR) events is primarily due to the fact that SEP flares are an energetic subset of all flares. Flares associated with gradual SEP events are characteristically accompanied by fast (much > 1000 km/s) coronal mass ejections (CMEs) that drive coronal/interplanetary shock waves. For the 1996-2005 interval, the slopes (alpha values) of power-law size distributions of the peak 1-8 Angs fluxes of SXR flares associated with (a) >10 MeV SEP events (with peak fluxes much > 1 pr/sq cm/s/sr) and (b) fast CMEs were approx 1.3-1.4 compared to approx 1.2 for the peak proton fluxes of >10 MeV SEP events and approx 2 for the peak 1-8 Angs fluxes of all SXR flares. The difference of approx 0.15 between the slopes of the distributions of SEP events and SEP SXR flares is consistent with the observed variation of SEP event peak flux with SXR peak flux.

Solar Flares↗
DOE OSTI2024

Boundary of the Distribution of Solar Wind Proton Beta versus Temperature Anisotropy

Abstract The frequency distribution of solar wind protons, measured in the vicinity of Earth’s orbit, is customarily plotted in ( β ∥ , T ⊥ / T ∥ ) phase space. Here, T ⊥ / T ∥ is the ratio of perpendicular and parallel temperatures, and β ∥ = 8 π nT ∥ / B 2 is the ratio of parallel thermal energy to background magnetic field energy, the so-called “parallel beta,” with ⊥ and ∥ denoting directions with respect to the ambient magnetic field. Such a frequency distribution, plotted as a two-dimensional histogram, forms a peculiar rhombic shape defined with an outer boundary in the said phase space. Past studies reveal that the threshold conditions for temperature anisotropy–driven plasma instability partially account for the boundary on the high- β ∥ side. The low- β ∥ side remains largely unexplained despite some efforts. Work by Vafin et al. recently showed that certain contours of collisional relaxation frequency, ν pp , when parameterized by T ⊥ / T ∥ and β ∥ , could match the overall shape of the left-hand boundary, thus suggesting that the collisional relaxation process might be closely related to the formation of the left-hand boundary. The present paper extends the analysis by Vafin et al. and carries out the dynamical computation of the collisional relaxation process for an ensemble of initial proton states with varying degrees of anisotropic temperatures. The final states of the relaxed protons are shown to closely match the observed boundary to the left of the ( β ∥ , T ⊥ / T ∥ ) phase space. When coupled with a similar set of calculations for the ensemble in the collective instability regime, it is found that the combined collisional/collective effects provide the baseline explanation for the observation.

Astronomy & Astrophysics↗
NASA NTRS2018

Generation of Kappa Distributions in Solar Wind at 1 au

We examine the generation of kappa distributions in the solar wind plasma near 1 au. Several mechanisms are mentioned in the literature, each characterized by a specific relationship between the solar wind plasma features, the interplanetary magnetic field (IMF), and the kappa index-the parameter that governs the kappa distributions. This relationship serves as a signature condition that helps the identification of the mechanism in the plasma. In general, a mechanism that generates kappa distributions involves a single or a series of stochastic or physical processes that induces local correlations among particles. We identify three fundamental solar wind plasma conditions that can generate kappa distributions, noted as (i) Debye shielding, (ii) frozen IMF, and (iii) temperature fluctuations, each one prevailing in different scales of solar wind plasma and magnetic field properties. Moreover, our findings show that the kappa distributions, and thus, their generating mechanisms, vary significantly with solar wind features: (i) the kappa index has different dependence on the solar wind speed for slow and fast modes, i.e., slow wind is characterized by a quasi-constant kappa index, K (is) approx. 4.3 +/- 0.7, while fast wind exhibits kappa indices that increase with bulk speed; (ii) the dispersion of magnetosonic waves is more effective for lower kappa indices (i.e., further from thermal equilibrium); and (iii) the kappa and polytropic indices are positively correlated, as it was anticipated by the theory.

Livadiotis, G.↗
DOE OSTI2022

National Community Solar Partnership (NCSP+) Resource List

NLR compiles and makes quarterly updates to this dataset of publications related to expanding access to solar through its support for the National Community Solar Partnership (NCSP+). The purpose of the list is to help NCSP+ partners and others to find relevant resources on community solar, low- and moderate-income residential rooftop solar + storage, community-serving commercial solar projects, microgrids, and distributed solar + storage aggregations such as virtual power plants serving low-income communities. Resource types include journal articles, reports, fact sheets, presentations, videos, datasets, modeling tools, webinars, and other formats. A web-based version of the database is available on the NCSP+ Data Hub at: https://openei.org/wiki/NCSP_Hub/Resources .

14 SOLAR ENERGY↗
NASA NTRS1990

Dual-peak solar cycle distribution of intense geomagnetic storms

This paper studies the features of the solar cycle distribution of intense storms (Dst) during cycles 20 and 21 (1965-1985). For these cycles, the distribution of intense storms (including moderate events for this time interval) in terms of Dst values below -50 nT, showed a dual-peak distribution, providing evidence for another enhancement of the intense storm distribution at the late ascending phase of the cycle. The origin of the dual-peak distribution of intense storms is associated with a similar dual-peak distribution obtained for large-amplitude and long-duration values of the negative Bz component of the IMF, computed for the interval 1970-1981.

Gonzalez, W. D.↗
DOE OSTI2022

Estimating the impacts of natural gas power generation growth on solar electricity development: PJM's evolving resource mix and ramping capability

Abstract Expansion of distributed solar photovoltaic (PV) and natural gas‐fired generation capacity in the United States has put a renewed spotlight on methods and tools for power system planning and grid modernization. This article investigates the impact of increasing natural gas‐fired electricity generation assets on installed distributed solar PV systems in the Pennsylvania–New Jersey–Maryland (PJM) Interconnection in the United States over the period 2008–2018. We developed an empirical dynamic panel data model using the system‐generalized method of moments (system‐GMM) estimation approach. The model accounts for the impact of past and current technical, market and policy changes over time, forecasting errors, and business cycles by controlling for PJM jurisdictions‐level effects and year fixed effects. Using an instrumental variable to control for endogeneity, we concluded that natural gas does not crowd out renewables like solar PV in the PJM capacity market; however, we also found considerable heterogeneity. Such heterogeneity was displayed in the relationship between solar PV systems and electricity prices. More interestingly, we found no evidence suggesting any relationship between distributed solar PV development and nuclear, coal, hydro, or electricity consumption. In addition, considering policy effects of state renewable portfolio standards, net energy metering, differences in the PJM market structure, and other demand and cost‐related factors proved important in assessing their impacts on solar PV generation capacity, including energy storage as a non‐wire alternative policy technique. This article is categorized under: Photovoltaics > Economics and Policy Fossil Fuels > Climate and Environment Energy Systems Economics > Economics and Policy

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A Clean Energy Deployment Baseline for the Energy Community and Low-Income Tax Credit Bonuses [Slides]

The Inflation Reduction Act of 2022 introduced, for the first time, place-based federal tax incentives for projects sited in “Energy Communities,” potentially changing the economic calculus of where projects are best sited. Storage projects can qualify for a 10-percentage-point bonus to the Investment Tax Credit (e.g., from 30% to 40%), while wind and solar projects may qualify for either the ITC bonus or a 10% bonus to the Production Tax Credit (e.g., from $\$27.5$ to $\$30.25$/MWh). Energy Communities are areas with historical ties to fossil fuel industries and above average unemployment levels (FFEU), with closed coal mines or power plants, or contaminated properties. They seek to identify locations across the US that could especially benefit from economic revitalization. This report explores how the new federal tax credit incentives are impacting clean energy deployment patterns and establishes historical baselines against which future changes can be compared. We include a few case studies of clean energy projects going specifically to areas that were recently impacted by coal power plant closures to provide concrete examples of investments in Energy Communities. However, this publication does not assess how much of the incentive benefits pass from clean energy developers to hosting communities, nor does it offer a comprehensive view of the economic effects of clean energy deployment on Energy Communities. Key highlights include: - As clean energy projects take multiple years to conceptualize and develop, it is likely too early to see shifts towards Energy Community locations either among newly built projects or those that entered interconnection queues in 2023. - Approximately 35% of onshore wind, 50% of solar, and 60% of storage capacity built in 2023 and the first half of 2024 are located in Energy Communities, making them likely eligible for bonus incentives. While these bonus incentives were not available to projects coming online before 2023, we used 2023 Energy Community definitions to classify whether past projects were built in what is now considered an Energy Community. The deployment levels for 2023-2024 are similar to recent years (2020-2022) for solar and storage but slightly lower for wind. - Clean energy capacity has surged in the interconnection queues over the last few years, with about 45-50% of both recently proposed and total queued capacity being located in Energy Communities. While the amount of capacity in Energy Communities has also grown, its relative share is either stable (solar and storage) or slightly lower (wind) among projects that entered the queue in 2023. - Clean energy projects can be built at lower costs in Energy Communities. The levelized cost of energy after incentives was on average $\$9$/MWh (24%) lower for solar projects and $\$2$/MWh (6%) lower for wind projects built in 2023, relative to projects not located in Energy Communities. Wholesale electricity values at Energy Community locations relative to the rest of the market vary by region. The average value was often higher for wind projects (-$\$3$ to $\$11$/MWh) but lower for solar projects (-$\$6$ to 0/MWh). - Distributed solar that is owned by commercial entities is eligible for the Energy Community bonus and also, potentially, a Low-Income Community bonus. Residential solar installations in qualifying Energy Communities that are third-party owned represent about 10% of the total residential market. Larger commercial and industrial solar installations in Energy Communities make up 17% of the total market in 2023. Nearly 2 GW of distributed solar was built in areas qualifying as Low-Income Communities in 2023, exceeding the available annual program cap of 700 MW. Continued tracking of these trends will be important for system planners, investors, and local communities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Comprehensive energy balance analysis of photon-enhanced thermionic power generation considering concentrated solar absorption distribution

The present article reports a comprehensive energy balance analysis of a photon-enhanced thermionic emission (PETE) device when it is used for concentrated solar power (CSP) generation. To this end, we consider a realistic PETE device composed of a boron-doped silicon emitter on glass and a phosphorus-doped diamond collector on tungsten separated by the interelectrode vacuum gap. Here, depth-dependent spectral solar absorption and its photovoltaic and photothermal energy conversion processes are rigorously calculated to predict the PETE power output and energy conversion efficiency. Our calculation predicts that when optimized, the power output of the considered PETE device can reach 1.6 W/cm 2 with the energy conversion efficiency of ~ 18% for 100× solar concentration, which is substantially lower than those predicted in previous works under ideal conditions. In addition, the photon-enhancement ratio is lower than 10 and decreases with the increasing solar concentration due to the photothermal heating of the emitter assembly, suggesting that PETE should be more suitable for lowto- medium CSP below ~ 100× concentration. These observations signify the importance of a rigorous energy balance analysis based on spectral and spatial solar absorption distribution for the accurate prediction of PETE power generation.

14 SOLAR ENERGY↗
NASA NTRS1979

Computed voltage distribution around Solar Electric Propulsion spacecraft

The paper uses the NASCAP computer code to compute voltage distributions around a Solar Electric Propulsion (SEP) spacecraft as it encounters an idealized geomagnetic substorm environment. Consideration is given to both a standard operating voltage and direct-drive voltage configuration. The computations are presented without thruster operations as well as with a simplified, simulated thruster-on representation for direct-drive configuration only. Finally, it is stressed that the computations seeking possible areas of concern in the spacecraft design are exploratory.

Stevens, N. J.↗