Analysing the performance of optimized intelligent machine learning based MPPT technique for energy management in hybrid RES system

Abstract

Renewable energy sources (RES) has a significant impact in solving newlineglobal issues of energy sustainability and global warming. As the world shifts newlineaway from fossil fuels, RES such as solar and wind energy offer cleaner newlinealternatives that substantially decrease greenhouse gas emissions and reliance newlineon limited resources. Photovoltaic (PV) systems convert sunlight directly into newlineelectricity, making solar power one of the most accessible and widely adopted newlineforms of renewable energy. Similarly, wind energy harnesses the natural newlinemovement of air to generate electricity, providing a reliable and efficient newlinesource of power. Both PV and wind systems not only contribute to a more newlinesustainable energy landscape but also enhance energy security and resilience, newlinemaking them essential components in the transition to a greener future. newlineHowever, the intermittency of the RES create challenges for grid stability and newlinerequires additional infrastructure to manage supply and demand effectively. In newlinethis research work, a hybrid system that involves wind energy conversion newlinesystem (WECS), PV and Battery energy storage with advance converter and newlineintelligent control techniques are proposed for better energy management. newline