Control Methods and AI Application for Grid-Connected PV Inverter: A Review
Feng Wang, Ayiguzhali Tuluhong, B. L., Ailitabaier Abudureyimu
Abstract
Grid-connected PV inverters (GCPI) are key components that enable photovoltaic (PV) power generation to interface with the grid. Their control performance directly influences system stability and grid connection quality. However, as PV penetration increases, conventional controllers encounter difficulties in managing nonlinear dynamics and weak-grid conditions. This paper reviews both conventional and artificial intelligence (AI)-based control methods for GCPI. It compares their performance characteristics, application scenarios, and limitations and summarizes current research progress and remaining challenges. The potential and issues of applying AI to enhance system intelligence are also highlighted. Finally, future development trends are discussed, emphasizing high efficiency, strong adaptability, and intelligent integration in GCPI technologies.