Moth-Flame Optimization-Based Maximum Power Point Tracking for Photovoltaic Systems Under Partial Shading Conditions

This paper presents a moth-flame optimization (MFO)-based maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The MFO algorithm is a new optimization method that exhibits satisfactory performance in terms of exploration, exploitation, local optima avoidance, and convergence. Therefore, the MFO algorithm is quite suitable for solving multiple peaks of PV systems under partial shading conditions (PSCs). The proposed MFO-MPPT is compared with four MPPT algorithms, namely the perturb and observe (P&O)-MPPT, incremental conductance (INC)-MPPT, particle swarm optimization (PSO)-MPPT and whale optimization algorithm (WOA)-MPPT. Simulation and experiment results demonstrate that the proposed algorithm can extract the global maximum power point (MPP) with greater tracking speed and accuracy under various conditions.

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Cite this article

[IEEE Style]

J. Shi, D. Zhang, F. Xue, Y. Li, W. Qiao, W. Yang, Y. Xu, T. Yang, "Moth-Flame Optimization-Based Maximum Power Point Tracking for Photovoltaic Systems Under Partial Shading Conditions," Journal of Power Electronics, vol. 19, no. 5, pp. 1248-1258, 2019. DOI: https://doi.org/10.6113/JPE.2019.19.5.1248.

[ACM Style]

Ji-Ying Shi, Deng-Yu Zhang, Fei Xue, Ya-Jing Li, Wen Qiao, Wen-Jing Yang, Yi-Ming Xu, and Ting Yang. 2019. Moth-Flame Optimization-Based Maximum Power Point Tracking for Photovoltaic Systems Under Partial Shading Conditions. Journal of Power Electronics, 19, 5, (2019), 1248-1258. DOI: https://doi.org/10.6113/JPE.2019.19.5.1248.