Abstract: To facilitate the efficient integration of photovoltaic (PV) power into the grid, this paper reviews recent advances in PV power forecasting, summarizes physical, statistical, machine learning, and hybrid forecasting models, highlights progress in model optimization, deep learning, and multi-source data fusion, while identifying model adaptability, data quality, and computational efficiency as key future research directions.