期刊
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 6, 期 3, 页码 850-862出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2015.2413359
关键词
Differential evolution (DE) algorithm; maximum power point tracking (MPPT); partial shading; particle swarm optimization (PSO); photovoltaic (PV) system
资金
- Deakin University Research
- High Impact Research-Ministry of Higher Education (HIR-MOHE) [UM.C/HIR/MOHE/ENG/24]
In photovoltaic (PV) power generation, partial shading is an unavoidable complication that significantly reduces the efficiency of the overall system. Under this condition, the PV system produces a multiple-peak function in its output power characteristic. Thus, a reliable technique is required to track the global maximum power point (GMPP) within an appropriate time. This study aims to employ a hybrid evolutionary algorithm called the DEPSO technique, a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the maximum power point under partial shading conditions. The paper starts with a brief description about the behavior of PV systems under partial shading conditions. Then, the DEPSO technique along with its implementation in maximum power point tracking (MPPT) is explained in detail. Finally, Simulation and experimental results are presented to verify the performance of the proposed technique under different partial shading conditions. Results prove the advantages of the proposed method, such as its reliability, system-independence, and accuracy in tracking the GMPP under partial shading conditions.
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