Certain investigations on performance improvement of standalone renewable energy systems

Abstract

In recent years, the attention towards the utilization of solar and newlinewind power systems are becoming more popular because of its non-polluted newlineand non-depleting nature. However, these power sources rely on newlineenvironmental conditions for power generation. So, it is essential to extract newlinethe maximum power available from the wind and solar systems. Apart from newlinehydro and wind power photovoltaic energy holds the most potential to meet newlineenergy demands. The wind energy is capable of generating large amount of newlinepower but its presence is highly unpredictable. Similarly, solar energy is newlinepresent throughout the day but the solar irradiation levels vary due to the newlineintensity of the sun. Partial shading is the important issue to be considered in newlinephotovoltaic (PV) power plants. Often the panels get partially shaded due to newlinesoiling, clouds and trees. newlineSolar photovoltaic (PV) systems under partial shading conditions newline(PSCs) have a nonmonotonic P-V characteristic with multiple local maximum newlinepower points, which makes the existing maximum power point tracking newline(MPPT) algorithms unsatisfactory. The common inherent drawback of wind newlineand photovoltaic systems are their intermittent natures that make them newlineunreliable. However, by combining these two intermittent sources and by newlineincorporating maximum power point tracking (MPPT) algorithms, the newlinesystem s power transfer efficiency and reliability can be improved. newlineThe MPPT will work well under steady state conditions. During the newlinenormal conditions, Hopfield Neural Network based Fuzzy Logic system is newlineemployed to extract the MPPT and to increase the power and efficiency of the newlinesolar system newline