Hybrid Maximum Power Point Tracking Using Artificial Neural Network-Incremental Conduction With Short Circuit Current of Solar Panel

Abstract

Significant increase in energy and reduction in carbon emissions are the biggest challenges in world energy demand. One of the best solutions is to use renewable energy. Solar energy is the energy that has advantages in terms of availability, eco-friendly, and cost-effectiveness. But the solar panel has a low energy conversion efficiency, so often the solar energy obtained by the solar panel cannot be utilized as a whole. Maximum Power Point Tracking (MPPT) is a technique that can improve the efficiency of energy conversion from the solar panel. In this paper, the type of MPPT used is MPPT hybrid, which is a combination of Artificial Neural Network based MPPT and Incremental Conductance algorithm. The value of short circuit current from the solar panel is used as an ANN reference to reach of maximum power from the solar panel. Incremental conductance is used to keep the maximum power value of the solar panel and improve the tracking results from MPPT ANN. The result of the proposed Hybrid MPPT method can improve the tracking speed of the Incremental Conductance algorithm and can reach the maximum power of the solar panel.