 Potential assessment of a parabolic trough solar thermal power plant considering hourly analysis: ANN-based approachT.E. Boukelia, O. Arslan and M.S. Mecibah Renewable Energy, 2017, vol. 105, issue C, 324-333 Abstract: One of the major challenges of developing and growing of parabolic trough solar thermal power plants (PTSTPPs) is enhancing the techno-economic performance. The goal of this study is to develop a unique artificial neural network (ANN) model that gives the best approach to predict the levelized cost of electricity (LCOE) of two different PTSTPPs integrated with thermal energy storage and fuel backup system; the first one is using thermic oil as primary heat transfer fluid in the solar field, while the other one is based on molten salt. By this way, the optimum designs of the two plants were determined in the LCOE analysis by using the obtained weights and biases of the best ANN topology. The techno-economic potentials of using molten salt in comparison to thermic oil of the two optimized plants were investigated considering both hourly and annual performances. Keywords: Artificial neural network; Levelized cost of electricity; Molten salt; Parabolic trough solar thermal power plant; Thermic oil (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:105:y:2017:i:c:p:324-333 DOI: 10.1016/j.renene.2016.12.081 Access Statistics for this article Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides More articles in Renewable Energy from Elsevier |
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