Maximum power point tracking of photovoltaic power generation based on improved fuzzy control and conductance increment method

Abstract

Abstract The National Development and Reform Commission of China announced in 2022 that it would promote the development of carbon peaking and carbon-neutrality. Therefore, gradual improvement in photovoltaic (PV) development technology would gradually show its advantages. Additionally, the development of the PV power generation industry is promoted significantly by the year-on-year increase in PV power generation. This study combines the traditional fuzzy control and incremental conductance methods by comparing the current maximum power point (MPP) intelligence with the traditional control algorithm. Furthermore, it proposes an optimization algorithm to improve the tracking speed of the MPP by using the partition variable step size. An incomplete partial differential equation is added to the judgment condition of the small step size to solve the problem of oscillation near the MPP caused by the ideal differential equation. A simulation model is established in MATLAB®/Simulink® and the method is simulated under specific conditions. The time to reach the first maximum output point is shortened by 0.21 and 0.14 s by analysing the oscillation process data of three simulation cycles of the incremental conductance, fuzzy control and fuzzy conductance methods, respectively. Additionally, the vibration loss caused by environmental mutation is reduced by 6.5% and 3.1%, respectively. The improved incremental conductance method utilizes the simulation results to optimize the problem of steady-state oscillation and improve the efficiency of the PV power generation. The feasibility and effectiveness of the improved incremental conductance method are verified by comparing the traditional control algorithm with the improved incremental conductance method.