A maximum power harvesting for photovoltaic system under partial shading conditions using artificial intelligence techniques

Abstract

In recent years, renewable energy sources experiencing high demand for power generation due to the degradation of conventional resources. Moreover, conventional resources are having drawbacks such as high prices and greenhouse emissions. Among all the renewable energy resources, PVbased energy plays a vibrant role because they are economical, easily available, and atmospheric friendly. PV systems can be employed as newlineindependent systems and as grid-connected systems. So many research works are focusing on PV systems. On the other side of the coin, solar systems have the main issue of intermittent nature power generation like all other renewable energy resources, and PV systems have the problems of low conversion efficiency and climate dependency. PV systems incur higher installation costs. Hence, there is a need for operating the PV cells at their maximum power point. A single operating point produces maximum efficiency on the nonlinear current voltage curve of the PV cell called the maximum PowerPoint. This Maximum power point tracking is necessary for not only producing maximum power generation but also for the long lifetime of PV cells. Moreover, single optimal point calculation is more difficult as the nonlinear characteristics of current voltage and under the Partial Shading condition (PSc). PSc happens by the passing clouds, the shadow of buildings, birds, and other nearby objects on the PV module fully or partially. This partial shading on PV modules affects the cell temperature, and irradiance decreases the energy retrieved from the PV module. Hence, in this thesis, maximum power point tracking techniques are proposed, and also to minimize the power loss efficient PV array configuration is proposed. newline newline