Comparison of Control Method System by Using Perturbation and Observation Algorithms and Fuzzy Logic for the Maximum Power Point Control in Photovoltaic Systems

Abstract

Currently, photovoltaic energy conversion has developed tremendously in the global energy industry. The enormous capacity of solar power plants generates electricity all over the world. Hundreds of gigawatts of electrical energy are supplied to the networks of various countries around the globe. In addition, up to hundreds of gigawatts of installed capacity of solar power plants are commissioned every year in all countries of the world. And this has been the trend for the past few decades. The main problem of solar photovoltaic conversion is the instability of the solar radiation flux associated with the climatic conditions in the regions where photovoltaic plants are operated. This problem can be solved by using highly efficient methods to control the generation of solar power plants, in particular, such as the use of information control systems for a particular PV system to increase the final generation of electrical energy supplied to the consumer. The photovoltaic (PV) conversion of solar radiation flux is an important renewable energy source. Due to the varying intensity of the sun, the electricity generated by PV directly from the radiation flux is not constant. The photovoltaic system currently uses maximum power point (PMP) tracking in perturbation and observation (P&O) mode to increase the final output power of the photovoltaic panels. A step-down DC-DC converter allows PMP to change the PV operating voltage and determine the maximum power output of the PV panel. This study proposes a fuzzy logic implementation. The magnitude of the perturbed voltage is determined by the change in power dq and the change in power relative to the change in voltage dq/dv is fuzzy. The performance of fuzzy logic is investigated in this work in order to optimize MPM. Fuzzy logic can simplify maximum power tracking and reduce voltage instability. According to the simulation results, the MPM method based on fuzzy computation performs better than the traditional P&O method. By using the proposed methods, we can significantly improve electric power generation and increase the efficiency of photovoltaic conversion.