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Cooling performances time series of CSP plants: Calculation and analysis using regression and ANN models

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  • Boukelia, T.E.
  • Ghellab, A.
  • Laouafi, A.
  • Bouraoui, A.
  • Kabar, Y.

Abstract

Concentrating solar power (CSP) plants use large quantities of water, for different processes such as cycle makeup and cooling. Thus, the estimation of cooling performances in such kind of plants is highly required. On the other hand, yearly round simulations of cooling performances of these plants require many calculations, data analysis, and time consuming. In this regard, empirical models and artificial neural networks (ANN) can be good alternatives in this topic. Therefore, the two main aims of this study are: (1) to compare the cooling performances, including water usage and power consumption for cooling of different CSP layouts, and (2) to develop regression and ANN models () to estimate these performances during the whole year, without passing through a detailed modelling.

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  • Boukelia, T.E. & Ghellab, A. & Laouafi, A. & Bouraoui, A. & Kabar, Y., 2020. "Cooling performances time series of CSP plants: Calculation and analysis using regression and ANN models," Renewable Energy, Elsevier, vol. 157(C), pages 809-827.
    • Handle: RePEc:eee:renene:v:157:y:2020:i:c:p:809-827
    DOI: 10.1016/j.renene.2020.05.012
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    2. Feng, Chenjia & Shao, Chengcheng & Wang, Xifan, 2021. "CSP clustering in unit commitment for power system production cost modeling," Renewable Energy, Elsevier, vol. 168(C), pages 1217-1228.
    3. Boukelia, T.E. & Arslan, O. & Djimli, S. & Kabar, Y., 2023. "ORC fluids selection for a bottoming binary geothermal power plant integrated with a CSP plant," Energy, Elsevier, vol. 265(C).

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