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A novel maximum power fuzzy logic controller for photovoltaic solar energy systems

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  • Altas, I.H.
  • Sharaf, A.M.

Abstract

The maximum power tracking problem and efficient energy utilization of a stand-alone photovoltaic array (PVA) feeding voltage controlled linear and nonlinear loads is studied. A novel and simple on-line fuzzy logic-based dynamic search, detection and tracking controller is developed to ensure maximum power point (MPP) operation under excursions in solar insolation, ambient temperature and electric load variations. A computer simulation model of the PVA renewable utilization scheme including the effects of temperature and solar irradiation changes was developed and fully simulated. The load voltage is controlled by a DC chopper and kept constant at the required rated voltage. A permanent magnet DC motor (PMDC) driving a fan-type load was connected in parallel to an RL passive load. A speed control scheme is also used for the PMDC motor drive so that the drive can be operated at specified speeds. Different controllers have been employed in the unified PVA scheme to control three separate loads at MPP tracking condition namely voltage at load bus and speed of the PMDC motor. The main objective of the paper is to present a novel enhanced, cost-effective MPP detector (MPPD) and dynamic MPP tracking (MPPT) controller for a hybrid mix of electric loads.

Suggested Citation

  • Altas, I.H. & Sharaf, A.M., 2008. "A novel maximum power fuzzy logic controller for photovoltaic solar energy systems," Renewable Energy, Elsevier, vol. 33(3), pages 388-399.
    • Handle: RePEc:eee:renene:v:33:y:2008:i:3:p:388-399
    DOI: 10.1016/j.renene.2007.03.002
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    References listed on IDEAS

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    1. Hua, C. & Lin, J., 2003. "An on-line MPPT algorithm for rapidly changing illuminations of solar arrays," Renewable Energy, Elsevier, vol. 28(7), pages 1129-1142.
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    1. Rajesh, R. & Mabel, M. Carolin, 2016. "Design and real time implementation of a novel rule compressed fuzzy logic method for the determination operating point in a photo voltaic system," Energy, Elsevier, vol. 116(P1), pages 140-153.
    2. Jordehi, A. Rezaee, 2016. "Maximum power point tracking in photovoltaic (PV) systems: A review of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1127-1138.
    3. Danandeh, M.A. & Mousavi G., S.M., 2018. "Comparative and comprehensive review of maximum power point tracking methods for PV cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2743-2767.
    4. Mellit, Adel & Kalogirou, Soteris A., 2014. "MPPT-based artificial intelligence techniques for photovoltaic systems and its implementation into field programmable gate array chips: Review of current status and future perspectives," Energy, Elsevier, vol. 70(C), pages 1-21.
    5. Tanaselan Ramalu & Mohd Amran Mohd Radzi & Muhammad Ammirrul Atiqi Mohd Zainuri & Noor Izzri Abdul Wahab & Ribhan Zafira Abdul Rahman, 2016. "A Photovoltaic-Based SEPIC Converter with Dual-Fuzzy Maximum Power Point Tracking for Optimal Buck and Boost Operations," Energies, MDPI, vol. 9(8), pages 1-17, July.
    6. AL-Rousan, Nadia & Isa, Nor Ashidi Mat & Desa, Mohd Khairunaz Mat, 2018. "Advances in solar photovoltaic tracking systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2548-2569.
    7. 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.
    8. Chun-Liang Liu & Jing-Hsiao Chen & Yi-Hua Liu & Zong-Zhen Yang, 2014. "An Asymmetrical Fuzzy-Logic-Control-Based MPPT Algorithm for Photovoltaic Systems," Energies, MDPI, vol. 7(4), pages 1-17, April.
    9. Song, Dongdong & Jiao, Hongtao & Fan, Chien Te, 2015. "Overview of the photovoltaic technology status and perspective in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 848-856.
    10. Dinçer, Furkan, 2011. "Overview of the photovoltaic technology status and perspective in Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3768-3779.
    11. Po-Chen Cheng & Bo-Rei Peng & Yi-Hua Liu & Yu-Shan Cheng & Jia-Wei Huang, 2015. "Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique," Energies, MDPI, vol. 8(6), pages 1-23, June.
    12. Jaw-Kuen Shiau & Yu-Chen Wei & Min-Yi Lee, 2015. "Fuzzy Controller for a Voltage-Regulated Solar-Powered MPPT System for Hybrid Power System Applications," Energies, MDPI, vol. 8(5), pages 1-21, April.
    13. Chen, Cheng-Chuan & Chang, Hong-Chan & Kuo, Cheng-Chien & Lin, Chien-Chin, 2013. "Programmable energy source emulator for photovoltaic panels considering partial shadow effect," Energy, Elsevier, vol. 54(C), pages 174-183.
    14. Chong, Lee Wai & Wong, Yee Wan & Rajkumar, Rajprasad Kumar & Rajkumar, Rajpartiban Kumar & Isa, Dino, 2016. "Hybrid energy storage systems and control strategies for stand-alone renewable energy power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 174-189.
    15. Chatterjee, Shantanu & Kumar, Prashant & Chatterjee, Saibal, 2018. "A techno-commercial review on grid connected photovoltaic system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2371-2397.
    16. Lalili, D. & Mellit, A. & Lourci, N. & Medjahed, B. & Berkouk, E.M., 2011. "Input output feedback linearization control and variable step size MPPT algorithm of a grid-connected photovoltaic inverter," Renewable Energy, Elsevier, vol. 36(12), pages 3282-3291.
    17. Mustayen, A.G.M.B. & Mekhilef, S. & Saidur, R., 2014. "Performance study of different solar dryers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 463-470.
    18. 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.
    19. Tingting Pei & Xiaohong Hao & Qun Gu, 2018. "A Novel Global Maximum Power Point Tracking Strategy Based on Modified Flower Pollination Algorithm for Photovoltaic Systems under Non-Uniform Irradiation and Temperature Conditions," Energies, MDPI, vol. 11(10), pages 1-16, October.
    20. Rajesh, R. & Carolin Mabel, M., 2015. "A comprehensive review of photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 231-248.

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