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A dynamic model for predicting solar plant performance and optimum control

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  • Chaabene, M.
  • Annabi, M.

Abstract

Planning over the intermediate and long terms for the operation of solar energy systems must be based on the use of measured data and performance models of system components. We present a dynamic model for predicting the thermal performance of a low-temperature solar power plant. We analyse the optimal control regime for energy management. Validation of the model was performed on a large solar plant located in the north of Tunisia. The results showed good agreement between measured and model values. During the cold season, the plant efficiency increases considerably when a greenhouse is connected to the power plant.

Suggested Citation

  • Chaabene, M. & Annabi, M., 1997. "A dynamic model for predicting solar plant performance and optimum control," Energy, Elsevier, vol. 22(6), pages 567-578.
    • Handle: RePEc:eee:energy:v:22:y:1997:i:6:p:567-578
    DOI: 10.1016/S0360-5442(96)00141-7
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    Cited by:

    1. Sabarathinam Srinivasan & Suresh Kumarasamy & Zacharias E. Andreadakis & Pedro G. Lind, 2023. "Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey," Energies, MDPI, vol. 16(14), pages 1-56, July.
    2. Shamshirgaran, Seyed Reza & Khalaji Assadi, Morteza & Badescu, Viorel & Al-Kayiem, Hussain H., 2018. "Upper limits for the work extraction by nanofluid-filled selective flat-plate solar collectors," Energy, Elsevier, vol. 160(C), pages 875-885.
    3. Seyed Reza Shamshirgaran & Hussain H. Al-Kayiem & Korada V. Sharma & Mostafa Ghasemi, 2020. "State of the Art of Techno-Economics of Nanofluid-Laden Flat-Plate Solar Collectors for Sustainable Accomplishment," Sustainability, MDPI, vol. 12(21), pages 1-52, November.
    4. Mawire, A. & McPherson, M., 2008. "Experimental characterisation of a thermal energy storage system using temperature and power controlled charging," Renewable Energy, Elsevier, vol. 33(4), pages 682-693.
    5. Chaabene, Maher & Ben Ammar, Mohsen, 2008. "Neuro-fuzzy dynamic model with Kalman filter to forecast irradiance and temperature for solar energy systems," Renewable Energy, Elsevier, vol. 33(7), pages 1435-1443.

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