MPPT Control of PV Power Generation with an Improved Sparrow Search Algorithm
摘要
This paper proposes an MPPT control strategy that combines Perturb and Observe (P&O) with an Improved Sparrow Search Algorithm (ISSA) to address the local optimum problem under partial shading. The P&O-based initialization guides ISSA toward high-power regions, while the improved update mechanism enhances the balance between global exploration and local refinement. Simulation results under partial shading and irradiance variations show that the proposed P&O-ISSA method achieves faster GMPP convergence and lower steady-state power oscillation compared with conventional P&O and standard SSA algorithms.