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Tracking Maximum Power Point For Photovoltaic System Using A Novel Differential Particle Swarm Optimization

Author

Listed:
  • Van Huong Dong

    (Ho Chi Minh City University of Transport, Ho Chi Minh city, VietnamAuthor-Name: Khai Hoan Nhu
    Ho Chi Minh City University of Transport, Ho Chi Minh city, Vietnam)

  • Thi Thom Hoang

    (Nha Trang University, Khanh Hoa, Vietnam)

  • Thanh Cong Pham

    (Ho Chi Minh City University of Food Industry, Ho Chi Minh city, Vietnam)

Abstract
In this paper, a new differential particle swarm optimization (DPSO) method is investigated for tracking the maximum power point (MPP) for the photovoltaic (PV) system in order to enhance the operating efficiency of the PV system. The DPSO-based MPPT method is not only able to tract the MPP using few iterations, but also avoids the steady-state oscillation phenomenon. Moreover, the proposed method is capable for extracting the optimization power under varyingtemperature condition as well as large fluctuations of irradiation. To demonstrate the effectiveness of the proposed, the obtained results are compared to those obtained using the conventional perturb and observation (P&O), incremental conductance (IncCond), and classical particle swarm optimization (PSO). Furthermore, a boost converter supplied by a solar array simulator is done to check the stability of the circuit. Meanwhile, the DPSO-MPPT algorithm is embedded in the PV system simulated by using Simulink software and MATLAB Toolbox. The simulating results show the superiority of the proposed approach in improving the efficiency of the photovoltaic system.

Suggested Citation

  • Van Huong Dong & Thi Thom Hoang & Thanh Cong Pham, 2018. "Tracking Maximum Power Point For Photovoltaic System Using A Novel Differential Particle Swarm Optimization," Journal of Mechanical Engineering Research & Developments (JMERD), Zibeline International Publishing, vol. 41(4), pages 116-121, November.
    • Handle: RePEc:zib:zjmerd:v:41:y:2018:i:4:p:116-121
    DOI: 10.26480/jmerd.04.2018.116.121
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    References listed on IDEAS

    as
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