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Multi-criteria fuzzy algorithm for energy management of a domestic photovoltaic panel

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  • Ben Salah, Chokri
  • Chaabene, Maher
  • Ben Ammar, Mohsen

Abstract

This paper presents a fuzzy algorithm which makes decision so as to connect domestic apparatus on either the electrical grid or a photovoltaic panel (PVP). The decision is made in real time with respect to multi-energy save criteria and upon the PVP maximum available power and apparatus states. The algorithm is validated on a 1kW peak (kWp) PVP and domicile apparatus of different powers installed at the Energy and Thermal Research Centre (CRTEn) in the north of Tunisia. Criteria are verified on the system behaviour during days covering the different seasons of the year. The power audit, established using measures, confirms that the energy save during daylight reaches 90% of the PVP available energy.

Suggested Citation

  • Ben Salah, Chokri & Chaabene, Maher & Ben Ammar, Mohsen, 2008. "Multi-criteria fuzzy algorithm for energy management of a domestic photovoltaic panel," Renewable Energy, Elsevier, vol. 33(5), pages 993-1001.
    • Handle: RePEc:eee:renene:v:33:y:2008:i:5:p:993-1001
    DOI: 10.1016/j.renene.2007.05.036
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    References listed on IDEAS

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    Cited by:

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    2. Ammar, Mohsen Ben & Chaabene, Maher & Elhajjaji, Ahmed, 2010. "Daily energy planning of a household photovoltaic panel," Applied Energy, Elsevier, vol. 87(7), pages 2340-2351, July.
    3. Datta, Manoj & Senjyu, Tomonobu & Yona, Atsushi & Funabashi, Toshihisa, 2011. "A fuzzy based method for leveling output power fluctuations of photovoltaic-diesel hybrid power system," Renewable Energy, Elsevier, vol. 36(6), pages 1693-1703.
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    5. Sallem, Souhir & Chaabene, Maher & Kamoun, M.B.A., 2009. "Energy management algorithm for an optimum control of a photovoltaic water pumping system," Applied Energy, Elsevier, vol. 86(12), pages 2671-2680, December.
    6. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    7. Comodi, Gabriele & Giantomassi, Andrea & Severini, Marco & Squartini, Stefano & Ferracuti, Francesco & Fonti, Alessandro & Nardi Cesarini, Davide & Morodo, Matteo & Polonara, Fabio, 2015. "Multi-apartment residential microgrid with electrical and thermal storage devices: Experimental analysis and simulation of energy management strategies," Applied Energy, Elsevier, vol. 137(C), pages 854-866.
    8. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    9. Moran, J.C. & Miguez, J.L. & Porteiro, J. & Patiño, D. & Granada, E. & Collazo, J., 2009. "Study of the feasibility of mixing Refuse Derived Fuels with wood pellets through the grey and Fuzzy theory," Renewable Energy, Elsevier, vol. 34(12), pages 2607-2612.

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