Search NASA⌕ Search

SEARCH · Search NASA

Results for “SOLAR SIMULATION”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

Semiconductor‐Electrocatalyst Contacts: Theory, Experiment, and Applications to Solar Water Photoelectrolysis

The goal of the work supported by this program was to use new types of photoelectrochemical experiments, supported by simulation and theory, to develop an improved microscopic picture of electron transfer in combined semiconductor|catalyst|solution (sem|cat|sol) systems. An emphasis was placed on developing techniques which can directly characterize electronic interfacial phenomena without first assuming a junction model. We then aimed to illustrate the design principles that enhance interfacial processes and enable high-efficiency devices. Our work thus provides deep insight into the processes that, in general, use light to drive chemical reactions.

14 SOLAR ENERGY↗

Constraining solar electron number density via neutrino flavor data at Borexino

Understanding the physics of the deep solar interior, and the more exotic environs of core-collapse supernovae (CCSN) and binary neutron-star (NS) mergers, is of keen interest in many avenues of research. To date, this physics is based largely on simulations via forward integration. While these simulations provide valuable constraints, it could be insightful to adopt the "inverse approach" as a point of comparison. Within this paradigm, parameters of the solar interior are not output based on an assumed model, but rather are inferred based on real data. Here, we take the specific case of solar electron number density, which historically is taken as output from the standard solar model. We show how one may arrive at an independent constraint on that density profile based on available neutrino flavor data from the Earth-based Borexino experiment. The inference technique's ability to offer a unique lens on physics can be extended to other datasets, and to analogous questions for CCSN and NS mergers, albeit with simulated data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Photoelectrode Durability in Two- versus Three-Electrode Configurations: Understanding the Impact of Circuit Configuration on Water-Splitting Stability

Device durability remains a significant challenge in photoelectrochemical (PEC) water splitting under ambient conditions. Yet, a lack of understanding of the test configuration and applied bias effects continue to hinder progress. In this study, we differentiate two-electrode (2E) and three-electrode (3E) configurations for evaluating PEC material durability, focusing particularly on their impacts on photoabsorber solid-state operating conditions. Our results underscore the fallacy of inferring 2E device stability from durability measurements performed solely in 3E configurations. Unmeasured and often misunderstood total circuit bias in 3E tests moderates material degradation, leading to the overestimation of photoelectrode stability compared to short-circuit operation. We demonstrate how the photoabsorber's operating voltage critically governs charge separation, surface stability, and degradation mechanisms during PEC operation. With these findings, we propose a standardized framework for conducting more reliable 3E durability experiments that simulate unassisted performance to help accelerate the development of robust, stable materials for solar-driven water splitting.

08 HYDROGEN↗

Optimal Management of Grid-Interactive Efficient Buildings via Safe Reinforcement Learning

Reinforcement learning (RL)-based methods have achieved significant success in managing grid-interactive efficient buildings (GEBs). However, RL does not carry intrinsic guarantees of constraint satisfaction, which may lead to severe safety consequences. Besides, in GEB control applications, most existing safe RL approaches rely only on the regularisation parameters in neural networks or penalty of rewards, which often encounter challenges with parameter tuning and lead to catastrophic constraint violations. To provide enforced safety guarantees in controlling GEBs, this paper designs a physics-inspired safe RL method whose decision-making is enhanced through safe interaction with the environment. Different energy resources in GEBs are optimally managed to minimize energy costs and maximize customer comfort. The proposed approach can achieve strict constraint guarantees based on prior knowledge of a set of developed hard steady-state rules. Simulations on the optimal management of GEBs, including heating, ventilation, and air conditioning (HVAC), solar photovoltaics, and energy storage systems, demonstrate the effectiveness of the proposed approach.

Huo, Xiang↗

Control and Real-Time Simulation of Microgrids with EV Fast-Charging and Grid-Forming Resources

Fast charging stations (FCSs) for electric vehicles (EVs) can behave as constant power loads, which is problematic for the operation of grid-forming (GFM) inverter-based resources (IBRs). To tackle this problem, this paper proposes a control suite that makes FCSs responsive to ac voltage and frequency disturbances. To test the performance of the FCS controls, the paper also sets forth theory to compensate for time-delays appearing in the real-time simulation of microgrid models divided into several central processing units (CPUs). Furthermore, these contributions are showcased via multi-CPU real-time simulations of a faulted microgrid having EV FCSs and GFM IBRs powered by photovoltaic solar arrays as well as power hardware-in-the-loop experiments. These contributions are significant to address NERC recommendations and IEEE standards.

14 SOLAR ENERGY↗

Transforming Windows from Energy Liabilities to Zero-Energy Assets: Next-Generation Solutions for Buildings

Windows have traditionally contributed to a building's HVAC load, but they can also become a source of net energy gain or even operate as zero-energy components. For heating applications, highly insulating windows can harness more solar heat than the energy lost through them, transforming windows from energy liabilities to assets. Dynamic glazings provide further benefits by regulating solar heat gain, reducing cooling loads in summer and heating demands in winter. This simulation study focuses on developing the next generation of zero-energy windows (ZEW) for residential new construction. Through annual energy simulations across climate zones 1-8, ZEW performance benchmarks were established based on current code-level buildings, and we've identified the regions where meeting ZEW standards are most achievable. This work evaluates both static and dynamic window technologies, assessing their effects on annual energy use and cost. Key findings demonstrate that ZEW performance is achievable across diverse climate zones, with specific regional requirements. Most climate zones from 3-8 can achieve ZEW with specific configurations, while some warm climates (1-2) appear challenging for ZEW implementation. Climate zones 4-6 consistently allow for zero energy window implementation, offering multiple pathways through either static or dynamic window technologies. Colder climate zones (7-8) ZEW products allow for higher SHGC values while requiring low U-values.

Yu, Lili↗

Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S.

Weather data plays a critical role in renewable energy analysis. Compared to using multiple Actual Meteorological Years, simulations using a single typical year require significantly fewer computational resources. Previous efforts to create typical weather datasets for renewable energy analysis either lack justified or optimized strategies for selecting and weighting different weather parameters or are limited to a few specific locations. Here, in this study, we developed a dataset comprising Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for over 2000 locations across the U.S., based on data from NASA's POWER project. The strategies for creating TSYs and TWYs were optimized based on the simulated outputs of various PV systems and wind turbines in 16 representative cities. This dataset provides an efficient means for the rapid evaluation and optimization of renewable energy systems throughout the entire U.S. Additionally, the optimal strategies identified in this study can be directly applied to create near-optimal TSYs and TWYs for most locations worldwide. However, readers can also employ the optimization approach presented in this work to develop optimal strategies tailored for particular regions.

NASA POWER↗

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

How to Build an Empirical Speed Distribution for Dark Matter in the Solar Neighborhood

The dark matter flux in a direct detection experiment depends on its local speed distribution. This distribution has been inferred from simulations of Milky Way–like galaxies, but such models serve only as proxies, given that no simulation directly captures the detailed evolution of our own Galaxy. This motivates alternative approaches that obtain this distribution directly from observations. In this work, we utilize 98 Milky Way analogues from the TNG50 simulation to develop and validate a procedure for inferring the dark matter speed distribution using the kinematics of nearby stars. We find that the dark matter that originated from old mergers, plus that from recent nonluminous accretions, is well described by a Maxwell–Boltzmann speed distribution centered at the local standard-of-rest velocity. Meanwhile, recently accreted dark matter from massive mergers has speeds that can be traced from the associated stellar debris of these events. The stellar populations systematically underestimate the velocity dispersion of their dark matter counterparts, but a simple kinematic boost brings the two into good alignment. Using the TNG50 host galaxies, we demonstrate that combining these two contributions provides an accurate reconstruction of the local dark matter speeds. As an application of the procedure to our own Galaxy, we utilize stellar kinematic data from Gaia to quantify how the dark matter remnants from the Milky Way’s last major merger impact its speed distribution in the solar neighborhood.

Shpigel, Tal [Princeton Univ., NJ (United States)]↗

Physics-driven Explosions of Stripped High-mass Stars: Synthetic Light Curves and Spectra of Stripped-envelope Supernovae with Broad Light Curves

Stripped-envelope supernovae (SESNe) represent a significant fraction of core-collapse supernovae, arising from massive stars that have shed their hydrogen and, in some cases, helium envelopes. The origins and explosion mechanisms of SESNe remain a topic of active investigation. In this work, we employ radiative-transfer simulations to model the light curves and spectra of a set of explosions of single, solar-metallicity, massive Wolf–Rayet stars with ejecta masses ranging from 4 to 11 M ⊙ , which were computed from a turbulence-aided and neutrino-driven explosion mechanism. We analyze these synthetic observables to explore the impact of varying ejecta mass and helium content on observable features. We find that the light curve shape of these progenitors with high ejecta masses is consistent with observed SESNe with broad light curves but not the peak luminosities. The commonly used analytic formula based on rising bolometric light curves overestimates the ejecta mass of these high-initial-mass progenitor explosions by a factor of up to 2.6. In contrast, the calibrated method by Haynie et al., which relies on late-time decay tails, reduces uncertainties to an average of 20% within the calibrated ejecta mass range. Spectroscopically, the He I 1.083 μm line remains prominent even in models with as little as 0.02 M ⊙ of helium. However, the strength of the optical He I lines is not directly proportional to the helium mass but instead depends on a complex interplay of factors such as the 56 Ni distribution, composition, and radiation field. Thus, producing realistic helium features requires detailed radiative transfer simulations for each new hydrodynamic model.

79 ASTRONOMY AND ASTROPHYSICS↗

Rotation‐Controlled Diurnal Evolution of Uranus' Asymmetric Bow Shock at Equinox

Uranus possesses the most extreme magnetic and rotational geometry in the solar system, resulting in a uniquely dynamic and asymmetric interaction between its magnetosphere and the solar wind. Here we investigate the diurnal evolution of the Uranian bow shock (BS) at equinox using global multifluid magnetohydrodynamic simulations constrained by Voyager 2 observations. The BS structure and variability are quantified using the stand‐off distance, terminator distance, flaring parameter, and BS parameter, enabling a systematic assessment of its global asymmetry over one planetary rotation. Our results show that the BS exhibits pronounced diurnal asymmetry that is primarily controlled by planetary rotation. Even under steady upstream solar wind conditions, the BS undergoes periodic expansion and contraction, reflecting rotation‐driven reconfiguration of the planetary magnetospheric topology. This diurnal modulation represents a remarkably large asymmetry in planetary BS geometry within the solar system. These results establish planetary rotation as the intrinsic primary driver of Uranus' BS dynamics at equinox and provide essential constraints for the design and formulation of future space missions to the ice giants. These findings also offer a unique framework for understanding shock physics in the abundant population of ice‐giant exoplanets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Experimental Validation of a Module Cell Cracking Model

The What's Cracking app can predict how changes in crystalline silicon photovoltaic (PV) module materials, design, and mounting affect its susceptibility for cell fracture under uniform loading. This work has experimentally validated the app. A set of commercial crystalline silicon PV modules was obtained for this study. The modules were uniformly loaded at three different mounting points, and their subsequent cell fractures were recorded. A large sample size allowed for the development of an experimental statistical model for cell fracture. Here, the comparison of the experiment to predictions from the app is in excellent agreement. Both experimental and modeling results also elucidate how moving the module mounting points toward the center of the module increases the probability of cell fracture.

14 SOLAR ENERGY↗

Parametric Instability of Alfvén Waves and Wave Packets in Periodic and Open Systems

The parametric decay instability of Alfvén waves has been widely studied, but few investigations have examined wave packets of finite size and the effect of different boundary conditions on the growth rate. In this paper, we perform a linear analysis of circular and arc-polarized wave trains and wave packets in periodic and open boundary systems in a low- β plasma. We find that both types of wave are 3–5 times more stable in open boundary conditions compared to periodic. Additionally, once the wave packet width ℓ becomes smaller than the system size L , the growth rate decreases nearly with a power law γ ∝ ℓ / L . This study demonstrates that the stability of a pump wave cannot be separated from the laboratory settings, and that the growth rate of daughter waves depends on the conditions downstream and upstream of the pump wave and on the fraction of volume it fills. Our results can explain simulations and experiments of localized Alfvén waves. They also suggest that Alfvénic fluctuations in the solar wind, including sharp impulses known as switchbacks, can be more stable than traditional theory suggests depending on wind conditions.

Alfven waves↗

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services: Preprint

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

closed-loop validation↗

Bias‐Dependent Quantum Efficiency Reveals Recombination Pathways in Thin Film Solar Cells

Identifying where recombination predominantly occurs—whether at the front interface, back interface, or throughout the bulk—is crucial for optimizing CdSeTe solar cells and many other photovoltaic device architectures. Here, a simple and effective diagnostic is demonstrated: measuring external quantum efficiency (QE) under varying forward biases. The drift–diffusion simulations reveal that each recombination pathway leaves a distinct bias-induced signature in the normalized QE: a progressive drop at long wavelengths for back-limited devices, a short-wavelength decline for front-limited devices, and a relatively uniform decrease across all wavelengths for bulk-limited devices. These predictions are validated with experiments on As-doped and Cu-doped CdSeTe devices, with and without passivation layers or different front buffers. In each case, the observed bias-dependent QE spectral changes align with the simulated recombination map. Because this method uses standard QE instrumentation, it offers a broadly accessible and cost-efficient means to diagnose recombination pathways—extending beyond CdSeTe to other thin-film and emerging solar cell technologies. By pinpointing recombination bottlenecks, researchers and manufacturers can strategically refine doping profiles, passivation schemes, and interface designs to further improve device performance.

CdTe↗

Comparative Analysis of Rear Irradiance Modeling Methods for Bifacial PV Systems on Single-Axis Trackers Under Varying Albedo Conditions

This study compares three rear-side irradiance modeling methods for bifacial PV systems on single-axis trackers: (i) the 2D View Factor (VF) model in PVsyst(R), (ii) the open-source PVFactors VF model, and (iii) the Ray Tracing (RT) technique using bifacial_radiance. Simulations were benchmarked against field measurements from a pilot PV plant with rear-side sensors at the torque tube height. Results show that all models underestimated the non-uniformity of rear irradiance along the module length and overestimated the total rear irradiance incident on the module. However, since bifacial gain represents only a fraction of the system's total energy, the resulting energy yield differences among methods remained within +- 2 % of measured values, which is typical for such simulations. While the overall energy impact is limited, this study characterizes the specific limitations of each modeling approach, supporting further improvements in bifacial PV performance assessment methods.

14 SOLAR ENERGY↗

Model Formulations: Integrating Distributed Energy Resources (DER) using Advanced Unit Commitment Models and DER Aggregation Methodologies

A distribution energy resource aggregator (DERA) constitutes a group of distribution energy resources with small generation capacities which meet the threshold to participate in the electricity wholesale market. This document provides the proposed DERA model formulation that will be implemented in the SCUC simulation’s architecture for the SCUC-DER project. Different economical assessment methodologies have been developed to incorporated bids for individual distributed resources, which include solar cost dispatch and cost model, BESS opportunity cost offer algorithm, and price sensitive demand response model. Detailed methods are proposed to aggregate individual cost offers to a DERA cost curve to bid in SCUC market while three methods are proposed to simulate DER actual dispatch. Based on the DERA models in this document, the SCUC-DER project will be able to assess the impacts of DERA on the distribution system’s operation and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗