Recent meta-heuristic grasshopper optimization algorithm for optimal reconfiguration of partially shaded PV array

• Published in: Solar energy Vol. 171; pp. 638 - 651
• Main Author: Fathy, Ahmed
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.09.2018; Pergamon Press Inc
• Subjects: Algorithms; Arrays; Efficiency; Genetic algorithms; Global maximum power; Grasshopper optimization algorithm; Heuristic; Heuristic methods; Maximum power; Methods; Modules; Objective function; Optimization; Partially shaded PV array; Radiation; Reconfiguration; Reliability analysis; Shading; Solar energy; Solar radiation; Global maximum power; Grasshopper optimization algorithm; Partially shaded PV array
• ISSN: 0038-092X; 1471-1257
• DOI: 10.1016/j.solener.2018.07.014

•Grasshopper optimization algorithm (GOA) is applied to reconfigure the partially shaded PV array optimally.•Proposed objective function representing the sum of raw powers is presented.•Four different shadow patterns are studied and comparison with TCT, Su Do Ku and GA configuration are done.•The obtained results confirm the superiority of the proposed GOA. When solar radiation striking the PV modules inserted in PV array is non-homogeneous; then the partial shading operation is taken place. This phenomenon has negative effects on the efficiency of the PV array as the generated power is reduced, hot spots are generated; one solution to get rid of these negatives is the reconfiguration of modules such that distributing the solar radiation in regular form as much as possible. Therefore, this paper proposed a new methodology based on recent meta-heuristic optimization algorithm named grasshopper to be applicable in solving the reconfiguration process of the partially shaded PV array optimally. The main purpose of such action is to maximize the power extracted from the array via proposed objective function presented in this work. The PV array arrangement obtained via the proposed approach incorporated recent meta-heuristic grasshopper optimization algorithm (GOA) is compared with those obtained via total cross tied connection (TCT), Su Do Ku connection and genetic algorithm (GA) configuration. Additionally, different shadow patterns during a day are studied and reconfiguration arrangement is obtained at each hour. The obtained results confirm the reliability and the efficiency of the proposed GOA in evaluating the global maximum power point (GMPP) extracted from the partially shaded PV array.