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A Fuzzy-Based PI Controller for Power Management of a Grid-Connected PV-SOFC Hybrid System

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  • Shivashankar Sukumar

    (Institute of Power Engineering (IPE), Universit Tenaga Nasional, Selangor 43000, Malaysia)

  • Marayati Marsadek

    (Institute of Power Engineering (IPE), Universit Tenaga Nasional, Selangor 43000, Malaysia)

  • Agileswari Ramasamy

    (Department of Electronics and Communication Engineering, Universiti Tenaga Nasional, Selangor 43000, Malaysia)

  • Hazlie Mokhlis

    (Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia)

  • Saad Mekhilef

    (Power Electronics and Renewable Energy Research Laboratory (PEARL), University of Malaya, Kuala Lumpur 50603, Malaysia)

Abstract

Solar power generation is intermittent in nature. It is nearly impossible for a photovoltaic (PV) system to supply power continuously and consistently to a varying load. Operating a controllable source like a fuel cell in parallel with PV can be a solution to supply power to variable loads. In order to coordinate the power supply from fuel cells and PVs, a power management system needs to be designed for the microgrid system. This paper presents a power management system for a grid-connected PV and solid oxide fuel cell (SOFC), considering variation in the load and solar radiation. The objective of the proposed system is to minimize the power drawn from the grid and operate the SOFC within a specific power range. Since the PV is operated at the maximum power point, the power management involves the control of SOFC active power where a proportional and integral (PI) controller is used. The control parameters of the PI controller K p (proportional constant) and T i (integral time constant) are determined by the genetic algorithm (GA) and simplex method. In addition, a fuzzy logic controller is also developed to generate appropriate control parameters for the PI controller. The performance of the controllers is evaluated by minimizing the integral of time multiplied by absolute error (ITAE) criterion. Simulation results showed that the fuzzy-based PI controller outperforms the PI controller tuned by the GA and simplex method in managing the power from the hybrid source effectively under variations of load and solar radiation.

Suggested Citation

  • Shivashankar Sukumar & Marayati Marsadek & Agileswari Ramasamy & Hazlie Mokhlis & Saad Mekhilef, 2017. "A Fuzzy-Based PI Controller for Power Management of a Grid-Connected PV-SOFC Hybrid System," Energies, MDPI, vol. 10(11), pages 1-17, October.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:11:p:1720-:d:116674
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    References listed on IDEAS

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    1. Lau, K.Y. & Yousof, M.F.M. & Arshad, S.N.M. & Anwari, M. & Yatim, A.H.M., 2010. "Performance analysis of hybrid photovoltaic/diesel energy system under Malaysian conditions," Energy, Elsevier, vol. 35(8), pages 3245-3255.
    2. Luk, P.C.K. & Low, K.C. & Sayiah, A., 1999. "GA-based fuzzy logic control of a solar power plant using distributed collector fields," Renewable Energy, Elsevier, vol. 16(1), pages 765-768.
    3. Eltawil, Mohamed A. & Zhao, Zhengming, 2013. "MPPT techniques for photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 793-813.
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    Cited by:

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    2. Qixiang Yan & Ibrahim Adamu Tasiu & Hong Chen & Yuting Zhang & Siqi Wu & Zhigang Liu, 2019. "Design and Hardware-in-the-Loop Implementation of Fuzzy-Based Proportional-Integral Control for the Traction Line-Side Converter of a High-Speed Train," Energies, MDPI, vol. 12(21), pages 1-24, October.
    3. Jing Huang & John Boland, 2018. "Performance Analysis for One-Step-Ahead Forecasting of Hybrid Solar and Wind Energy on Short Time Scales," Energies, MDPI, vol. 11(5), pages 1-12, May.
    4. Nicu Bizon & Mircea Raceanu & Emmanouel Koudoumas & Adriana Marinoiu & Emmanuel Karapidakis & Elena Carcadea, 2020. "Renewable/Fuel Cell Hybrid Power System Operation Using Two Search Controllers of the Optimal Power Needed on the DC Bus," Energies, MDPI, vol. 13(22), pages 1-26, November.
    5. Khlid Ben Hamad & Doudou N. Luta & Atanda K. Raji, 2021. "A Grid-Tied Fuel Cell Multilevel Inverter with Low Harmonic Distortions," Energies, MDPI, vol. 14(3), pages 1-24, January.
    6. Muhammad Awais & Laiq Khan & Saghir Ahmad & Mohsin Jamil, 2021. "Feedback-Linearization-Based Fuel-Cell Adaptive-Control Paradigm in a Microgrid Using a Wavelet-Entrenched NeuroFuzzy Framework," Energies, MDPI, vol. 14(7), pages 1-17, March.
    7. Nebiyu Kedir & Phuong H. D. Nguyen & Citlaly Pérez & Pedro Ponce & Aminah Robinson Fayek, 2023. "Systematic Literature Review on Fuzzy Hybrid Methods in Photovoltaic Solar Energy: Opportunities, Challenges, and Guidance for Implementation," Energies, MDPI, vol. 16(9), pages 1-38, April.

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