A robust global MPPT to mitigate partial shading of triple-junction solar cell-based system using manta ray foraging optimization algorithm

被引:68
作者
Fathy, Ahmed [1 ,2 ]
Rezk, Hegazy [3 ,4 ]
Yousri, Dalia [5 ]
机构
[1] Jouf Univ, Fac Engn, Elect Engn Dept, Sakakah, Saudi Arabia
[2] Zagazig Univ, Fac Engn, Elect Power & Machine Dept, Zagazig, Egypt
[3] Prince Sattam Bin Abdulaziz Univ, Coll Engn Wadi Addawaser, Al Kharj, Saudi Arabia
[4] Menia Univ, Fac Engn, Elect Engn Dept, Al Minya, Egypt
[5] Fayoum Univ, Fac Engn, Elect Engn Dept, Al Fayyum, Egypt
关键词
Energy efficiency; Triple-junction solar cell; Shading; Manta ray foraging optimization; POWER POINT TRACKING; PV SYSTEMS; PERFORMANCE;
D O I
10.1016/j.solener.2020.06.108
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The high efficiency triple-junction solar cells (TJSC) have received considerable attention in the concentrated PV systems nonetheless the harvested electrical energy generated by TJSC-based system has been reduced under the partial shading conditions. Tracking the global maximum power point in the TJSC-based system characteristics is a main challenge faced the traditional trackers like perturb and observe (P&O). Therefore, this paper proposes a new global maximum power point tracker (MPPT) based on recent metaheuristic approach of Manta ray foraging optimization (MRFO). The proposed MRFO based MPPT is employed to extract the global maximum power point (GMPP) from the Triple-Junction solar based array operated under shadow conditions. Seven shadow patterns are studied on seven topologies of triple junction solar based arrays. The obtained results are compared with differential evolution (DE) and crow search algorithm (CSA). The obtained results confirmed the superiority of the proposed MPPT based MRFO in extracting the GMPP under different partial shadow patterns followed by CSA and DE optimizers.
引用
收藏
页码:305 / 316
页数:12
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