Optimised Maximum Power Point Tracking for Non-uniform PV Array

Felix K. Okpoti, Joseph Cudjoe Attachie, Patrick Adjei, Christian K. Amuzuvi

Abstract


Installed photovoltaic (PV) array works in difficult conditions or harsh environments, therefore, non-uniform aging will occur and affect unfavourably the performance of a PV system, particularly at the centre during their life span. Because of the high cost of supplanting matured PV modules by new modules, it is important to enhance the energy efficiency of matured PV system. For this reason, this project displays a PV module reconfiguration methodology to accomplish the maximum power generation from non-consistently matured PV system without critical investment. At a point when PV systems are influenced by aging, a Global Maximum Power Point Tracking (GMPPT) algorithm is needed to build the energy reaping capacity of the system. A new GMPPT algorithm is proposed using a Perturb and Observe (P&O) algorithm, which is incorporated into a Genetic Algorithm (GA) function to create a single algorithm. By embedding a simple P&O into a GA algorithm, the population size and the number of iterations are decreased, thus finding the Maximum Power Point (MPP) in a shorter time. The algorithm parameters (population size, number of genes, and number of iterations) are Optimised and the final solution is provided. The control part and the GMPPT algorithm were tested and analysed in MATLAB for a small-scale photovoltaic system. A description of this algorithm and its performance is detailed and verified through simulation.

Keywords: Global Maximum Power Point Tracking, Photovoltaic, Genetic Algorithm


Keywords


Global Maximum Power Point Tracking, Photovoltaic, Genetic Algorithm

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References


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