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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Demonstrating solarpilot ’s Python Application Programmable Interface Through Heliostat Optimal Aimpoint Strategy Use Case

solarpilot is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. solarpilot was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s System Advisor Model (SAM) in a simplified format. Prior means for user interaction with solarpilot have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This article presents a new, full-featured, python-based application programmable interface (API) for solarpilot, which we hereafter refer to as CoPylot. CoPylot enables python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. CoPylot’s enables CSP researchers to perform analysis that was previously not possible through solarpilot’s existing interfaces. This article discusses the capabilities of CoPylot and presents a use case wherein we populate a model that obtains optimal solar field aiming strategies.

14 SOLAR ENERGY↗
DOE OSTI2017

LK Scripting Language [SWR-16-07]

The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL’s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Version 3.0+ toolkit.

Source record↗
DOE OSTI2018

Continuous Silicon Consolidation and Reduction

The goal of the Department of Energy’s (DOE’s) Sunshot program is to increase the adaptability of photovoltaic (PV) solar power generation by reducing the cost of power generation. The cost of polysilicon is one of several factors affecting the costs of a solar power module. The National Renewable Energy Laboratory (NREL) assumes module manufacturing costs (all-in vertically integrated module production) of 0.63 (cents)/Wdc (2015 NREL data). If the NREL polysilicon costs are replaced by the SRI International (SRI) polysilicon costs, the module manufacturing costs are reduced to 0.58 (cents)/Wdc (2015 basis) i.e., reduction of 0.05 (cents)/Wdc. The NREL cost model (System Advisor Module, SAM) is based on $20/kg of blended polysilicon silicon cost. The Continuous Silicon Consolidation and Reduction (CoSiRC) process is estimated to produce polysilicon at 8.06 (dollars)/kg. In addition, SRI’s CoSiRC process introduces a commercially viable path to recycle and reclaim kerf loss silicon fines that would otherwise go to a landfill, thereby reducing a precious resource from going to waste. The results of this project demonstrate that SRI’s silicon production process that uses a reduction reaction can be successfully integrated with a kerf loss reclaiming process. The combined process was first demonstrated at lab scale and then fit to a bench-scale process. Leveraging the industrial expertise of the commercial partners, it is feasible to adapt industrial-scale equipment for SRI’s CoSiRC process.

14 SOLAR ENERGY↗
DOE OSTI2025

U.S. Agrivoltaics Irradiance Database

This is a foundational data set for research and deployment of agrivoltaics, which is the co-location of agriculture and solar power plants on the same land. This irradiance and shading dataset can be utilized to determine the suitability of agrivoltaics configurations for a given region and crop-type. The data is hourly, 4x4 km resolution across the contiguous United States and Hawaii. It is calculated from the National Solar Radiation Database sites, using the System Advisor Model (SAM) to simulate the shading patterns for 10 common agrivoltaics configurations. Sunlight availability data is reported for 10 locations on the ground between adjacent rows of solar panels, as well as averaged across areas of interest such as the average irradiance in the edge-to-edge open area or across 3-6 planting beds. Other available metrics include the input meteorological data from the NSRDB (e.g. global horizontal irradiance, wind speed, etc.) and estimates for comparing energy and agricultural characteristic across the 10 configurations, including power output per acre or per kW installed capacity and farmable land area per acre.

14 SOLAR ENERGY↗
DOE OSTI2023

Distributed clean energy opportunities for US oil refinery operations

The oil and gas industry is increasingly seeking operational improvements to reduce costs and emissions while improving resilience. This study describes techno-economic analysis of opportunities for distributed energy resources that could be integrated to support oil and gas companies’ economic, environmental, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics, wind turbines, battery energy storage, landfill gas, biomass, municipal solid waste-to-energy, solar steam for process heat, combined heat and power, and electrolyzers for hydrogen production at two hypothetical refineries, one located in Louisiana and the other in southern California. These technologies could reduce the sites’ consumption of grid electricity and/or natural gas and thus can help reduce emissions. This study employs the ReOPT tool and System Advisor Model to evaluate the techno-economic potential for clean energy technologies to support refineries in achieving energy goals, including energy cost savings, resiliency, and emissions reductions. Results indicate that the associated costs of emissions reductions via several distributed clean energy technologies are competitive with other emissions reduction strategies such as energy efficiency, reducing flaring, direct carbon capture and sequestration, and markets under certain conditions. There are also cost beneficial opportunities for the use of renewable energy for refining, especially for resilience, depending on local conditions such as resources and utility costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Progress & Frontiers in PV Performance

PowerPoint slides for a presentation given at Solar Power International 2016. Presentation includes System Advisor Model (SAM) introduction and battery modeling, bifacial PV modules and modeling, shade modeling and module level power electronics (MLPE), degradation rates, and PVWatts updates and validation.

14 SOLAR ENERGY↗
DOE OSTI2016

LK Scripting Language

The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL’s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Version 3.0+ toolkit.

Source record↗
DOE OSTI2021

Technoeconomic Cost Analysis of NREL Concentrating Solar Power Gen3 Liquid Pathway: Preprint

The National Renewable Energy Laboratory is leading the liquid (molten salt) power tower pathway for the U.S. Department of Energy's concentrating solar power Gen3 initiative. The Gen3 liquid pathway required updated designs to three major components: the tower and receiver, the thermal energy storage (TES) tanks, and the power cycle. We assume a 100 MWe net system output and used the System Advisor Model (SAM) to complete a technoeconomic cost analysis of the Gen3 liquid pathway design and estimate its LCOE. This paper summarizes the methodology and results of that analysis.

chloride salt↗
DOE OSTI2023

Variability in Diurnal and Seasonal Ambient Conditions on Geothermal Plant Performance and Cost: Preprint

Geothermal plant performance is bounded by the second law efficiency, which accounts for the quantity of exergy that can be converted into useful work. This in turn is dependent on the geothermal resource temperature and the temperature of the heat sink (i.e., the ambient temperature). In this study we show that ambient temperature variability on a diurnal and seasonal basis can affect performance and cost estimations for geothermal plants. We have utilized the updated System Advisor Model (SAM) to assess nine geothermal sites with existing resource capacities across three climate zones. Our analysis shows that both evaporatively-cooled flash and air-cooled binary cycle plants are affected by temperature, with a slightly higher effect in EGS binary sites. By assuming an ambient (wet bulb) temperature baseline of 15.6 degrees C (60 degrees F) and comparing baseline results to those from site-specific data we observe up to 15% underestimation of plant performance and up to 20% overestimation of cost.

ambient temperature↗
DOE OSTI2025

Impact Analysis of Utility-Scale Energy Storage on the ERCOT Grid in Reducing Renewable Generation Curtailments and Emissions

This paper explores the solutions for minimizing renewable energy (RE) curtailment in the Texas Electric Reliability Council of Texas (ERCOT) grid. By utilizing current and future planning data from ERCOT and the System Advisor Model from the National Renewable Energy Laboratory, we examine how future renewable energy (RE) initiatives, combined with utility-scale energy storage, can reduce CO2 emissions while reshaping Texas’s energy mix. The study projects the energy landscape from 2023 to 2033, considering the planned phase-out of fossil fuel plants and the integration of new wind/solar projects. By comparing emissions under different load scenarios, with and without storage, we demonstrate storage’s role in optimizing RE utilization. The findings of this paper provide actionable guidance for energy stakeholders, underscoring the need to expand wind and solar projects with strategic storage solutions to maximize Texas's RE capacity and substantially reduce CO2 emissions.

14 SOLAR ENERGY↗
DOE OSTI2021

Techno-economic Analysis of Novel PV Plant Designs for Extreme Cost Reductions

A techno-economic analysis is underway examining the cost and performance of future large-scale photovoltaic (PV) plant components, including bifacial modules, tandem modules, increased plant voltage architectures, and module-level power electronics. Integration of these components into PV plant designs is compared with current PV technologies based on levelized cost of electricity (LCOE). Baseline models are developed and validated against recorded PV plant performance data. Expected cost and performance data of future PV technologies are incorporated into the baseline models. An evolutionary algorithm is utilized to optimize PV plant configuration, technology combination, and LCOE. Furthermore, this paper focuses on the bifacial module analysis.

14 SOLAR ENERGY↗
DOE OSTI2018

Validation of Photovoltaic Modeling Tool HelioScope Against Measured Data

HelioScope is a cloud-based solar design software developed by Folsom Labs to model arrays based on physical design. Folsom Labs received a grant from the Department of Energy for the National Renewable Energy Laboratory to validate the performance of HelioScope's simulation engine against measured PV system performance. This study builds upon previous validation work by NREL of multiple other PV modeling tools, using the same fixed-tilt systems with available system specifications. HelioScope designs were set up using the same system specifications and concurrent weather data as were used in previous studies. The predicted performance results from the simulations were compared with measured data and to performance predictions by other PV modeling tools.

14 SOLAR ENERGY↗
DOE OSTI2026

HelioScope Energy Performance Modeling Validation: Cooperative Research and Development Final Report, CRADA Number CRD-17-00685

HelioScope is a unique solar design and energy performance modeling tool that bridges the worlds of research and industry, bringing the most rigorous methods from the performance modeling community to thousands of solar developers of all backgrounds. However, many financial institutions and municipalities are hesitant to accept the energy production modeling results of HelioScope (including shading losses) in place of costly, time-intensive, and/or redundant methods due to lack of vetting from a respected institution like NREL. We expect that the proposed validation exercises will give municipalities and financial institutions the comfort needed to incorporate HelioScope into their operations, thereby significantly reducing the needs of existing and potential HelioScope users' to otherwise obtain information that HelioScope produces automatically. Folsom Labs was selected for a Small Business Voucher from the U.S. Department of Energy for the National Renewable Energy Laboratory to validate the performance of HelioScope’s simulation engine against measured PV system performance.

14 SOLAR ENERGY↗
DOE OSTI2021

Hybrid Solar Heat Generation Modelling and Cases: Preprint

Renewable thermal energy systems (RTES) harness renewable energy sources to provide services for space heating and cooling, district heating, domestic hot water, and industrial process heat (IPH). The use of low-pressure steam generated by the combustion of fossil fuels is common today to provide process heat for industrial facilities. Solar IPH (SIPH) technologies could economically replace the steam or heat needs at many industrial sites by providing high-temperature pressurized hot water, a heat transfer fluid (HTF) such as synthetic-oil, or direct steam (Kurup and Turchi, 2015). RTES could be hybridized with technology options or combined with the existing heat supply (e.g. fuels), to give options for targeted IPH application and the reduction of fuel consumption. This work has tested hybrid system modelling approaches. Initial results show when a natural gas (NG) burner that feeds an IPH application of 300°C, has both air and NG streams pre-heated with a solar field/RTES exit temperature of 180°C (via an HTF), a 13% NG offset is possible. NG offsets reach up to 26%, when the RTES exit temperatures are at 300°C for a given annual capacity factor of 24%. This can be even higher with addition of thermal energy storage (TES).

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Validation of Multiple Tools for Flat Plate Photovoltaic Modeling Against Measured Data

This report expands upon a previous work by the same authors, published in the 40th IEEE Photovoltaic Specialists conference. In this validation study, comprehensive analysis is performed on nine photovoltaic systems for which NREL could obtain detailed performance data and specifications, including three utility-scale systems and six commercial scale systems. Multiple photovoltaic performance modeling tools were used to model these nine systems, and the error of each tool was analyzed compared to quality-controlled measured performance data. This study shows that, excluding identified outliers, all tools achieve annual errors within +/-8% and hourly root mean squared errors less than 7% for all systems. It is further shown using SAM that module model and irradiance input choices can change the annual error with respect to measured data by as much as 6.6% for these nine systems, although all combinations examined still fall within an annual error range of +/-8.5%. Additionally, a seasonal variation in monthly error is shown for all tools. Finally, the effects of irradiance data uncertainty and the use of default loss assumptions on annual error are explored, and two approaches to reduce the error inherent in photovoltaic modeling are proposed.

14 SOLAR ENERGY↗