Abstract
Maximum power point tracking (MPPT) algorithms are necessary to achieve the higher effectiveness of photovoltaic systems (PVs). PV arrays have a nonlinear power-voltage characteristic; hence, the curve has a specific point called the “MPP”. In literature, most of the conventional MPPT processes are set to track the MPP under uniform atmospheric conditions. Otherwise, it may trap at local MPP under partial shading conditions (PSCs). In this paper, we propose an MPPT based on Whale Optimization Algorithm (WOA) under PSC. The proposed MPPT has been tested with both the uniform patterns and non-uniform patterns. A comparison between the proposed MPPT, a Conventional P&O and a PSO with Constriction Coefficient MPPT algorithms has been made in order to validate the proposed strategy. The simulation results using Matlab/Simulink show the superiority of the proposed MPPT in term of tracking efficiency and settling time to the global MPP (GMPP), under both uniform and non-uniform shading patterns.
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Zabia, D.E., Afghoul, H., Kraa, O. (2022). Maximum Power Point Tracking of a Photovoltaic System Under Partial Shading Condition Using Whale Optimization Algorithm. In: Hatti, M. (eds) Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities. IC-AIRES 2021. Lecture Notes in Networks and Systems, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-030-92038-8_12
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DOI: https://doi.org/10.1007/978-3-030-92038-8_12
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