Evaluation of Maximum Power Point Tracking algorithm for off-grid photovoltaic pumping

The paper is concerned with the evaluation of some distributed Maximum Power Point Tracking techniques for an autonomous photovoltaic water pumping installation in a rural area in the Mediterranean. The efficiency of using Maximum Power Point Tracking algorithms for water pumping is proved. Then, some widely used Maximum Power Point Tracking algorithm performances (Look-up table, Neuro-Fuzzy, Incremental conductance and Perturb and Observe) are evaluated and compared using measured data from the target area. Despite the rapid change in the measured climatic parameters (solar radiation and ambient temperature), the Perturb and Observe algorithm shows a good dynamic performance. Hence, it is selected and successfully tested on a detailed model of the installation and then used to evaluate the relevance of the distributed Maximum Power Point Tracking for such installations.