Comparative Analysis of MPPT Techniques for PV Systems in Microgrids

With the rapid development of renewable energy, photovoltaic systems are increasingly being applied in microgrids. However, their output power is significantly affected by environmental conditions (such as irradiance and temperature), exhibiting nonlinear characteristics. To improve energy conversion efficiency, maximum power point tracking (MPPT) technology has become crucial. This paper conducts theoretical analysis and simulation experiments to compare the performance of various MPPT methods. The research results show that the constant voltage/constant current single-loop PI control structure is simple but has poor environmental adaptability, while the double-loop control enhances dynamic performance by coordinating voltage and current regulation. The incremental conductance method (INC) and the perturb and observe method (P&O) demonstrate stronger tracking capabilities in dynamic environments, but traditional algorithms have issues such as slow response or steady-state oscillation; the improved INC achieves a balance between speed and accuracy through dynamic step size adjustment. Additionally, the constant voltage method has weak adaptability to temperature changes, while INC and P&O have greater advantages in dynamic tracking. The research provides a theoretical basis for the selection of MPPT algorithms for photovoltaic systems in microgrids, and indicates that intelligent algorithms can further optimize the global optimization ability in complex environments in the future.