A Linear-Prediction Maximum Power Point Tracking Algorithm for Photovoltaic Power Generation

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Conference Proceeding
IEEE Industrial Electronics Society Annual Meeting (IECON), 2012, pp. 3316 - 3321
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In this paper, a linear-prediction maximum power point tracking (MPPT) algorithm for photovoltaic (PV) power generation is presented. This allows rapid tracking without step-size reference. The new methodology has two parts: linear prediction and error correction. The first part estimates the maximum power point (MPP); this improves the MPPT response speed. The second part calibrates the error after the linear prediction; this enhances the calculation accuracy which leads to a faster MPP convergence. Theoretical analysis and simulations are put forward to validate the feasibility of the linear prediction method. Convergence, error correction, and steady and dynamic state evaluations are made. The results show that the algorithm can work effectively and have the advantages of fast response and high efficiency when compared to the Perturbation and Observe (P&O) algorithm.
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