Investigation of intelligent mppt controller for grid integrated solar pv system

Abstract

Solar photovoltaic (PV) power is widely used as a vital alternative energy source for fossil fuels due to its natural availability and no fuel cost. It was used for power generation as a standalone power plant earlier, but nowadays solar power plants are connected to utility grid via transformer. The efficiency of solar power plant mainly depends on solar radiation values, which is continually varied with respect to time. Maximum Power Point Tracking (MPPT) controller must be installed in a power plant to get the maximum output power at all possible times. The design of an efficient MPPT controller for a grid connected solar photovoltaic system is still a challenging task due to grid synchronization, grid load power demand and grid isolation under fault conditions. newlineThis research work mainly focuses on design of an efficient MPPT controller for grid interconnected solar PV system and tests the performance of the system under various controller implementations. In this work, incremental conductance technique and Incremental conductance with integral regulator-based controllers are modelled and implemented in the system. But the performances were not satisfactory under variable solar irradiation conditions. Artificial intelligence-based control techniques are more efficient than conventional controllers. Based on these facts, Fuzzy regulator, Fuzzy-PID regulator and Back Propagation Neural Network based MPPT controllers were implemented and simulated under various irradiation conditions of the system. Among these controllers, the Fuzzy-PID regulator exhibit good performances under various irradiation conditions. However, the performances of these controllers were not satisfactory on the grid side newline