Maximum Power Point Tracking (MPPT) Techniques for Hybrid Solar PV-Wind Turbine Energy Systems

The integration of hybrid solar photovoltaic (PV) and wind turbine systems has garnered significant attention in addressing the global demand for sustainable and reliable energy sources. These hybrid systems offer operational advantages, especially in off-grid and remote areas where extending centralized power infrastructure is impractical. A crucial aspect of such hybrid systems is the optimization of power extraction, which is achieved through Maximum Power Point Tracking (MPPT) techniques. This paper presents a review of the key MPPT methods used in hybrid PV-wind systems, including Perturb and Observe (P&O), Incremental Conductance (INC), Fuzzy Logic Control (FLC), and Artificial Neural Networks (ANN). The paper compares their operational characteristics, highlighting their advantages, limitations, and suitability under different environmental conditions. Moreover, the paper explores two MPPT architectures for hybrid systems: independent MPPT units for each energy source and a unified MPPT controller that integrates advanced algorithms. The study aims to provide insights into the optimal selection of MPPT techniques to enhance the efficiency and reliability of hybrid renewable energy systems. Keywords: Hybrid energy system, MPPT, solar PV, wind turbine, FLC, ANN, adaptive control