A Prediction Model-Guided Jaya Algorithm for the PV System Maximum Power Point Tracking

This paper proposes a novel model-free solution algorithm, the natural cubic-spline-guided Jaya algorithm (S-Jaya), for efficiently solving the maximum power point tracking (MPPT) problem of PV systems under partial shading conditions. A photovoltaic (PV) system which controls the power generation with its operating voltage is considered. As the same as the generic Jaya algorithm, the S-Jaya is free of algorithm-specific parameters. A natural cubic-spline-based prediction model is incorporated into the iterative search process to guide the update of candidate solutions (operating voltage settings) in the S-Jaya and such extension is capable of improving the tracking performance. Simulation studies and experiments are conducted to validate the effectiveness of the proposed S-Jaya algorithm for better addressing PV MPPT problems considering a variety of partial-shading conditions. The performance of the proposed algorithm is benchmarked against the generic Jaya and the particle swarm optimization, which has been widely considered in themodel-free MPPT, to demonstrate its advantages. Results of simulation studies and experiments demonstrate that the S-Jaya algorithm converges faster and provides a higher overall tracking efficiency.