Detailed Physical Trough Model for NREL's Solar Advisor Model [electronic resource] : Preprint
- Washington, D.C. : United States. Dept. of Energy, 2010.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- 11 : digital, PDF file
- Additional Creators:
- National Renewable Energy Laboratory (U.S.)
United States. Department of Energy
United States. Department of Energy. Office of Scientific and Technical Information
- Solar Advisor Model (SAM) is a free software package made available by the National Renewable Energy Laboratory (NREL), Sandia National Laboratory, and the US Department of Energy. SAM contains hourly system performance and economic models for concentrating solar power (CSP) systems, photovoltaic, solar hot-water, and generic fuel-use technologies. Versions of SAM prior to 2010 included only the parabolic trough model based on Excelergy. This model uses top-level empirical performance curves to characterize plant behavior, and thus is limited in predictive capability for new technologies or component configurations. To address this and other functionality challenges, a new trough model; derived from physical first principles was commissioned to supplement the Excelergy-based empirical model. This new 'physical model' approaches the task of characterizing the performance of the whole parabolic trough plant by replacing empirical curve-fit relationships with more detailed calculations where practical. The resulting model matches the annual performance of the SAM empirical model (which has been previously verified with plant data) while maintaining run-times compatible with parametric analysis, adding additional flexibility in modeled system configurations, and providing more detailed performance calculations in the solar field, power block, piping, and storage subsystems.
- Published through SciTech Connect.
Presented at SolarPACES 2010, 21-24 September 2010, Perpignan, France.
Wagner, M. J.; Blair, N.; Dobos, A.
- Funding Information:
View MARC record | catkey: 14795618