Yasser E. Abu Eldahab
Ain-shams University, Egypt
Title: Design and implementation of a novel search technique to the global maximum power point under partial shading conditions
Biography
Biography: Yasser E. Abu Eldahab
Abstract
The partial shading issue is one of the most critical problems facing the maximum power point tracking (MPPT) algorithms. This paper presents the design and implementation of a novel search technique for global maximum power point (GMPP) under partial shading conditions (PSC). It utilizes a two-stage algorithm to overcome the partial shading issue. In the first stage, it uses the genetic neural algorithm (GA) to determine the nearest point to the GMPP. In the second stage, it starts from the optimum point obtained in stage one and applies a new and smart MPPT algorithm to increase the searching speed. In order to determine the performance parameters and evaluate the validity and efficiency of the new method, a complete experimental prototype is implemented. The experimental results prove that, under all possible partial shading conditions, the new technique reaches directly the GMPP with very limited steady state oscillation. Moreover, it tracks the maximum power point (MPP) much faster than the traditional methods. Consequently, the new technique has a significant improvement in energy extraction efficiency from the photovoltaic array to the load.