Modeling and Performance of Grid Connected Inverter Based Photovoltaic Systems

Abstract

Electricity is one of the prime factors of the growth. It determines the value of the different societies. A reliable, continuous supply of electrical energy is very essential for the functioning of today's modern complex and advanced society. The renewable energy sources are considered the savior of the electricity generation as there is a great depletion of the conventional energy resources. The photovoltaic energy is one form of the solar energy resource that considered one of the greatest sources of energy in the world. The solar energy is green, renewable and available all the years especially in Egypt. As the characteristics of the photovoltaic cells are not linear, therefore the maximum power may not be utilized as this depends on the operating conditions such as the irradiance and temperature. A maximum power point tracking algorithm should be applied to operate the photovoltaic arrays with its maximum output power. One of the major problems in this type of systems is the shading conditions that the photovoltaic arrays may be subjected to. Hence, modified algorithms should be considered to overcome this problem. Some of these algorithms depend on artificial intelligence tools. This thesis introduces one of these methods which is the Flower Pollination Optimization Algorithm. A system modeling and simulation are performed using MATLAB/SIMULINK package to verify the applicability of using the proposed algorithm to solve the problem of maximum power point tracking under different shading conditions.