Performance analysis of novel intelligent optimization algorithms based maximum power point tracking of solar PV systems using hybrid DC DC converter

Abstract

Renewable energy is promising future energy. Among the different newlinerenewable energy sources, solar photovoltaics is one to replace conventional newlineenergy sources. Solar power output is dependent on irradiation and newlinetemperature. Irradiation varies daily and seasonal; therefore, solar power also newlinechanges. Even though there is good sunshine, solar energy varies due to the newlineshadow of adjacent trees, buildings and passing clouds. Solar panels produce newlinemultiple peak power points when shaded. The variation should be tracked newlinecontinuously to tap the highest available power. Maximum Power Point newlinetracking algorithms constantly check the variation of current and voltage of newlinesolar panels and, thereby, power. There are innumerable techniques available newlineto track the maximum power. These techniques are evaluated based on their newlinetracking time and efficiency. newlineThe Solar Photovoltaic system is modeled for both uniform and newlinepartial shading conditions. PV current versus voltage and power versus newlinevoltage characteristics are drawn to validate the working of the PV systems. newlineDue to shading, the photovoltaic system exhibits multiple peak power; among newlinethese, one is called global maximum power, and the other powers are called newlinelocal maximum power. The proposed research is to track the global maximum newlinepower and discard the local maximum powers. A hybrid converter, combining newlinea single-ended primary inductor converter and the boost converter, is newlineproposed to reduce the steady-state oscillations and to avoid inrush current. newlineThe performance of the proposed hybrid converter is compared with the boost newlineand the buck-boost converters to validate the importance of it. newline newline