期刊
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
卷 69, 期 8, 页码 8066-8079出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIE.2021.3109515
关键词
Convergence; Costs; Heuristic algorithms; Prediction algorithms; Optimization; Maximum power point trackers; Hardware; DC-DC power conversion; solar energy; tracking
PV arrays with partial shading conditions exhibit multiple local maximum power points. Traditional global MPP tracking algorithms may have slow convergence and fail to track the global MPP. This article proposes a new algorithm that uses a single current sensor and parabolic equations to accurately calculate the global MPP during partial shading conditions. Simulation and experimental results show fast tracking and high tracking efficiency.
Photovoltaic (PV) arrays exhibit multiple local maximum power points (MPPs) in their I-V and P-V characteristic curves when different modules are subjected to different radiations at the same time, known as a partial shading condition (PSC). Hence, tracking the global MPP is crucial to increase the PV system efficiency. Conventional global MPP tracking (GMPPT) algorithms suffer from slow convergence, while some can fail to track the global MPP during PSCs. This article proposes a totally new approach to finding the global MPP during PSC using a single current sensor: the parabolic assumption GMPPT algorithm uses a fixed number of current scans (steps) equal to the number of solar modules connected in series to directly and immediately calculate the global MPP. The proposed algorithm uses simple parabolic equations to calculate the global MPP near-exactly during PSCs. The performance of the proposed algorithm is first evaluated by simulation in MATLAB/Simulink, and then by experimental verification. The results show very fast global MPP tracking and negligible tracking energy loss with an experimental tracking efficiency over 99.6% for the four PSC patterns tested.
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