Research on photovoltaic power generation based on multi-dimensional indicators and models

Introduction Photovoltaic (PV) power generation is vital for sustainable energy and carbon reduction, yet existing studies often focus on single aspects, lacking integrated planning support. Methods This study develops a framework combining power forecasting, optimization, and carbon assessment using a multidimensional indicator system, PCA, t-SNE, and PSO. Results A 1% increase in PV generation could reduce China’s power sector carbon emissions by 2.05% by 2035; the model achieved an R 2 =0.9975. Discussion The framework supports regional energy planning, though future models should incorporate policy shifts and market dynamics.