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A simulation model for predicting the performance of a solar photovoltaic system with alternating current loads

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  • Sukamongkol, Y.
  • Chungpaibulpatana, S.
  • Ongsakul, W.

Abstract

This paper describes the development of a simulation model for predicting the performance of a solar photovoltaic (PV) system under specified load requirements and prevailing meteorological conditions at the site location. This study is aimed at situations where the loads are provided by alternating current (AC) electrical devices. The model consists of several submodels for each of the main components of the PV system; namely, PV array, battery, controller, inverter and various loads. Mathematical equations developed for modeling the performance of each component are explained along with the methodology to determine the performance coefficients. In order to validate the developed simulation model, an experimental system has been set up and tested under a variety of climatic conditions. Simulated results from the model under the same operating and environmental conditions are compared with those observed from the experimental tests. Good agreement is found in the comparison. Slight discrepancies appearing in the results are described and recommendations are given for further improvement. The simulation model developed can be used not only for analyzing the PV system performance, but also for sizing the PV system which is most suitable to the load requirements at any specified location provided that the local meteorological data is available.

Suggested Citation

  • Sukamongkol, Y. & Chungpaibulpatana, S. & Ongsakul, W., 2002. "A simulation model for predicting the performance of a solar photovoltaic system with alternating current loads," Renewable Energy, Elsevier, vol. 27(2), pages 237-258.
    • Handle: RePEc:eee:renene:v:27:y:2002:i:2:p:237-258
    DOI: 10.1016/S0960-1481(02)00002-2
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    References listed on IDEAS

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    1. Chaurey, A. & Deambi, S., 1992. "Battery storage for PV power systems: An overview," Renewable Energy, Elsevier, vol. 2(3), pages 227-235.
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    1. Mellit, A. & Kalogirou, S.A. & Hontoria, L. & Shaari, S., 2009. "Artificial intelligence techniques for sizing photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(2), pages 406-419, February.
    2. Eltawil, Mohamed A. & Zhao, Zhengming, 2010. "Grid-connected photovoltaic power systems: Technical and potential problems--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 112-129, January.
    3. Cheick Tidjane Kone & Jean-Denis Mathias & Gil De Sousa, 2017. "Adaptive management of energy consumption, reliability and delay of wireless sensor node: Application to IEEE 802.15.4 wireless sensor node," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-28, February.
    4. Daud, Abdel-Karim & Ismail, Mahmoud S., 2012. "Design of isolated hybrid systems minimizing costs and pollutant emissions," Renewable Energy, Elsevier, vol. 44(C), pages 215-224.
    5. Mellit, A. & Benghanem, M. & Kalogirou, S.A., 2007. "Modeling and simulation of a stand-alone photovoltaic system using an adaptive artificial neural network: Proposition for a new sizing procedure," Renewable Energy, Elsevier, vol. 32(2), pages 285-313.
    6. Syafaruddin, & Karatepe, Engin & Hiyama, Takashi, 2009. "Polar coordinated fuzzy controller based real-time maximum-power point control of photovoltaic system," Renewable Energy, Elsevier, vol. 34(12), pages 2597-2606.
    7. Uzunoglu, M. & Onar, O.C. & Alam, M.S., 2009. "Modeling, control and simulation of a PV/FC/UC based hybrid power generation system for stand-alone applications," Renewable Energy, Elsevier, vol. 34(3), pages 509-520.
    8. El Halabi, N. & García-Gracia, M. & Comech, M.P. & Oyarbide, E., 2012. "Distributed generation network design considering ground capacitive couplings," Renewable Energy, Elsevier, vol. 45(C), pages 119-127.
    9. Zakaria Belboul & Belgacem Toual & Abdellah Kouzou & Lakhdar Mokrani & Abderrahman Bensalem & Ralph Kennel & Mohamed Abdelrahem, 2022. "Multiobjective Optimization of a Hybrid PV/Wind/Battery/Diesel Generator System Integrated in Microgrid: A Case Study in Djelfa, Algeria," Energies, MDPI, vol. 15(10), pages 1-30, May.
    10. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "Solar photovoltaic system modeling and performance prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 304-315.
    11. García-Gracia, M. & El Halabi, N. & Khodr, H.M. & Sanz, Jose Fco, 2010. "Improvement of large scale solar installation model for ground current analysis," Applied Energy, Elsevier, vol. 87(11), pages 3467-3474, November.
    12. Zhang, Xiaoling & Shen, Liyin & Chan, Sum Yee, 2012. "The diffusion of solar energy use in HK: What are the barriers?," Energy Policy, Elsevier, vol. 41(C), pages 241-249.
    13. Kaplani, E. & Kaplanis, S., 2012. "A stochastic simulation model for reliable PV system sizing providing for solar radiation fluctuations," Applied Energy, Elsevier, vol. 97(C), pages 970-981.
    14. Ali M. Jasim & Basil H. Jasim & Florin-Constantin Baiceanu & Bogdan-Constantin Neagu, 2023. "Optimized Sizing of Energy Management System for Off-Grid Hybrid Solar/Wind/Battery/Biogasifier/Diesel Microgrid System," Mathematics, MDPI, vol. 11(5), pages 1-34, March.

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