The rapid depletion of non-renewable energy resources and the growing impact of environmental pollution have intensified the global shift toward renewable energy technologies. Among available renewable sources, solar and wind energy have gained significant attention due to their abundance, technological maturity, and environmental sustainability. However, the inherent intermittency and variability of these resources pose major challenges in achieving reliable and efficient power generation. Maximum Power Point Tracking (MPPT) techniques play a crucial role in optimizing energy extraction from solar photovoltaic (PV) systems and wind energy conversion systems under varying environmental conditions such as irradiance fluctuations, temperature changes, and partial shading. This paper presents a comprehensive study of renewable energy sources with a focus on solar and wind energy systems. Detailed modeling of PV cells, modules, and arrays using the single-diode model is discussed, along with an analysis of electrical characteristics under different irradiance levels. The paper further reviews conventional MPPT techniques and highlights their limitations under dynamic operating conditions. To overcome these drawbacks, a hybrid MPPT framework integrating intelligent control strategies is proposed. MATLAB/Simulink-based simulation results demonstrate improved tracking performance, reduced power fluctuations, and enhanced energy conversion efficiency under varying irradiance and wind speed conditions. The results confirm that hybrid MPPT techniques offer superior adaptability and reliability, making them suitable for modern grid-connected and distributed renewable energy systems.
Ratan et al. (Sat,) studied this question.