Improve and analyze the performance of photovoltaic systems controlled by an advanced fuzzy logic method for fast and stable MPPT

Abstract

The main problem that often arises in photovoltaic systems is to achieving the maximum output power and maintaining the DC-DC connection voltage at a stable value since the power generated by photovoltaic panels is very powerless in uncertain climatic conditions. Moreover, the sunshine and temperature constantly change during the day. The aim of this work is to adapt and optimize an intelligent control algorithm for photovoltaic systems based on a fuzzy logic method to track the maximum power point (MPPT) at a stable value with a fast settling time and to optimize the efficiency under different influences of weather conditions (lighting and temperature). The system consists of a photovoltaic solar module connected to a DC-DC boost converter and a load. The effectiveness of the proposed system was validated by computer simulations using MATLAB/Simulink software. The results of this work show that the efficiency of the photovoltaic system can be improved up to 99.1% by using the advanced fuzzy logic controller.

Optimizing photovoltaic systems performance under partial shading using an advanced cuckoo search algorithm

“…In this context, researchers have put out several optimization methods in recent years to address the problems with GMPP in partially shaded solar panels. These techniques  ISSN: 2088-8694 encompass genetic algorithms [4], fuzzy logic controller (FLC) [5], grey wolf optimization (GWO) [6], and model predictive control (MPC) [7]. However, these methods have limitations in computational efficiency, speed response, and accuracy.…”