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Intelligent control strategy for a grid connected PV/SOFC/BESS energy generation system

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  • Chettibi, N.
  • Mellit, A.

Abstract

In this paper, an intelligent control strategy for a grid connected hybrid energy generation system consisting of Photovoltaic (PV) panels, Fuel Cell (FC) stack and Battery Energy Storage System (BESS) is proposed. Firstly, the dynamic modeling of the electrical energy resources is carried out. Then, the local controllers of DC-DC power converters are designed to regulate the operating points of the energy generation units. An online-trained Elman Neural Network (ENN) based controller is developed to perform the tracking of the optimal operating point of the PV source. Moreover, a Takagi-Sugeno-Kang based fuzzy gain tuner is adopted for the adjustment of the PI parameters of the FC and BESS controllers. Besides, the Virtual Flux Oriented Control (VFOC) scheme based on neuro-fuzzy gain tuners is adopted to control the power flow between the hybrid system, the local loads and the utility grid. Furthermore, a centralized power supervisor is established to determine the levels of the power references for the local controllers according to the supply and demand conditions. The simulation results obtained in the Matlab/Simulink environment demonstrate the efficiency of the proposed control scheme.

Suggested Citation

  • Chettibi, N. & Mellit, A., 2018. "Intelligent control strategy for a grid connected PV/SOFC/BESS energy generation system," Energy, Elsevier, vol. 147(C), pages 239-262.
    • Handle: RePEc:eee:energy:v:147:y:2018:i:c:p:239-262
    DOI: 10.1016/j.energy.2018.01.030
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    Cited by:

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    5. Dong, Weijie & He, Guoqing & Cui, Quansheng & Sun, Wenwen & Hu, Zhenlong & Ahli raad, Erfan, 2022. "Self-scheduling of a novel hybrid GTSOFC unit in day-ahead energy and spinning reserve markets within ancillary services using a novel energy storage," Energy, Elsevier, vol. 239(PE).
    6. Calise, F. & Cappiello, F.L. & Cimmino, L. & Vicidomini, M., 2022. "Dynamic simulation modelling of reversible solid oxide fuel cells for energy storage purpose," Energy, Elsevier, vol. 260(C).
    7. Ghenai, Chaouki & Bettayeb, Maamar, 2019. "Modelling and performance analysis of a stand-alone hybrid solar PV/Fuel Cell/Diesel Generator power system for university building," Energy, Elsevier, vol. 171(C), pages 180-189.
    8. Rahaf S. Ghanem & Laura Nousch & Maria Richter, 2022. "Modeling of a Grid-Independent Set-Up of a PV/SOFC Micro-CHP System Combined with a Seasonal Energy Storage for Residential Applications," Energies, MDPI, vol. 15(4), pages 1-20, February.
    9. Ceran, Bartosz, 2019. "The concept of use of PV/WT/FC hybrid power generation system for smoothing the energy profile of the consumer," Energy, Elsevier, vol. 167(C), pages 853-865.
    10. Uday K. Chakraborty, 2018. "Reversible and Irreversible Potentials and an Inaccuracy in Popular Models in the Fuel Cell Literature," Energies, MDPI, vol. 11(7), pages 1-11, July.
    11. Jin, Yuhui & Wu, Xiao & Shen, Jiong, 2022. "Power-heat coordinated control of multiple energy system for off-grid energy supply using multi-timescale distributed predictive control," Energy, Elsevier, vol. 254(PB).
    12. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Samer H. Atawneh & Madihah Md. Rasid & Nayyar Hussain Mirjat & Muhammad Akram Bhayo & Ilyas Khan, 2020. "Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids," Energies, MDPI, vol. 13(16), pages 1-22, August.
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