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Application of QOCGWO-RFA for maximum power point tracking (MPPT) and power flow management of solar PV generation system

Arther Jain, A. ; Rabi, B. Justus ; Darly, S.S.

International journal of hydrogen energy, 2020-02, Vol.45 (7), p.4122-4136 [Periódico revisado por pares]

Elsevier Ltd

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  • Título:
    Application of QOCGWO-RFA for maximum power point tracking (MPPT) and power flow management of solar PV generation system
  • Autor: Arther Jain, A. ; Rabi, B. Justus ; Darly, S.S.
  • Assuntos: Hybrid energy system ; Instantaneous shading conditions ; Output power ; PV array ; Voltage parameters ; Wind turbine
  • É parte de: International journal of hydrogen energy, 2020-02, Vol.45 (7), p.4122-4136
  • Descrição: A hybrid technique for solar PV array (SPV) generating system for maximizing the power to load is proposed in this dissertation. The proposed hybrid technique is the joint execution of both the Quasi Oppositional Chaotic Grey Wolf Optimizer (QOCGWO) with Random Forest Algorithm (RFA) and hence it is named as QOCGWO-RFA technique. Here, QOCGWO optimizes the exact duty cycles required for the DC-DC converter of SPV based on the voltage and current parameters. RFA predicts the control signals of the voltage source inverter (VSI) based on the active and reactive power variations in the load side. With this control technique, the system parameter variations and external disturbances are reduced and the load demands are satisfied optimally. The proposed strategy is implemented in MATLAB/Simulink working platform with three different case studies and compared with existing techniques. With these case studies, the proposed technique generates the optimal PV power of 2.1 kW. •Hybrid technique for maximizing the PV power to load is presented.•The proposed hybrid technique is the QOCGWO-RFA technique.•QOCGWO optimizes the exact duty cycles required for converter.•RFA predicts the control signals of the voltage source inverter (VSI).•The proposed technique generates the optimal PV power of 2.1 kW.
  • Editor: Elsevier Ltd
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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