Application Of Improved PSO In MPPT Control Of Photovoltaic Generation System

Over-development and over-utilization of fossil energy has resulted in serious environmental pollution and energy crisis. New energy, renewable energy, and energy saving technology have been paid to more and more great attention by the world. Due to pollution-free, enormous reserves, and lower-cost, solar energy grows into the main component of energy future. Photovoltaic power technology is of great significance to improve energy structure and reduce the pollution of the environment.During the power generation process, photovoltaic panels are inadvertently shaded by buildings, fallen leaves, dust, clouds, and so on. Then the power-voltage characteristic curve of photovoltaic array has multiple power peaks, conventional maximum power point tracking(MPPT) control methods and improved algorithms will fail to work.This paper has analyzed research background and significance of photovoltaic power, constructed and debated the photovoltaic cell model and output characteristic curve which are structured by dual-diode equivalent circuit. Several classic MPPT control algorithms, algorithm flow, and failure cause are introduced in this article with examples, as well as particle swarm optimization. Then the dormant particle swarm optimization(DPSO) is acquired by optimizing and improving the structure, flow, and preferences of algorithm. DPSO owns a faster convergence speed and higher efficiency. By combining DPSO with incremental conductance, dual-algorithm model can be achieved to find the optimal work point under complex shaded conditions.MPPT model is established and simulated in MATLAB/Simulink under three kinds of continuous shaded conditions and gradual change conditions to validate its validity, practicability, convergence ability, and optimization ability. In addition, hardware experiment platform is constructed and experimental results show that dual-algorithm model has an advantage.