Design and Simulation of Improved Particle Swarm Optimization based Maximum Power Point Tracking System for Solar Photovoltaic System Under Variable Irradiance Condition
The Indian government has set an ambitious goal that by 2030, 40% of the energy comes from renewable energy, the purpose is to meet the country ’s rapidly growing demand, which is currently mainly met by coal and oil. New Delhi is working hard to use renewable energy to generate 175 GW (GW) by 2022, with solar energy predominant, with a target of 100GW, followed by wind power. India has 450,000 KW of hydropower, has an installed wind power capacity of 230,000 KW, but has almost no great level for renewable power. Solar energy represents a large proportion of the government's expansion strategy. Photovoltaic energy must be converted from DC to AC to supply the grid or AC load. When using an IGBT inverter, the applied DC voltage on the DC link is converted to a single-phase AC voltage.. In this research, a diode based circuit model of solar photovoltaic system has been developed under MATLAB. Intelligent model for duty cycle optimization has been developed using particle swarm optimization. The optimization model of particle swarm optimization has been improved using optimization of acceleration coefficient as well as velocity factors. It provides efficient tracking of global peak power point swiftly and avoids early convergence. Comprehensive study on grid-connected solar system is developed and forecasting model for analytical analysis of the system is done. The result have shown least transient response and stable steady state response of proposed system as compared to contemporary soft computing techniques and conventional methods of power point tracking.