Analytical Investigation of Maximum Power Point Tracking (MPPT) for Optimization of energy performance of PV generation for Sonipat

Abstract

This comprehensive study employs MATLAB Simulink for the analysis and optimization of solar cells, offering valuable insights into their behaviour under varying environmental conditions. The research delves into the creation of a Simulink model, encompassing mathematical representations of solar cell electrical characteristics and incorporating real-world factors like irradiance and temperature. Various Maximum Power Point Tracking (MPPT) techniques, including Perturb & Observe, Incremental Conductance, Fractional Voc, Fractional Isc, Fuzzy Logic Control, and Neural Network, are explored, considering convergence speed, complexity, and tuning requirements. The chosen MPPT technique is then applied to optimize parameters, demonstrating the iterative adjustment process. The study emphasizes the systematic research methodology, reliability of conclusions, and the role of MATLAB Simulink in designing efficient solar energy systems. The future scope suggests integrating the Perturb & Observe algorithm with machine learning, exploring multi-objective optimization, and conducting real-world field trials for practical applications. Overall, the research contributes significantly to advancing renewable energy and addressing climate change challenges.