PLSR Model-based Installed Capacity Forecasting of Renewable Energy in Northwest China

In recent years, significant progress has been made in renewable energy generation in China, especially in the northwest region. With the rapid development of renewable energy in this region, precise capacity forecasting is vital for energy planning and policymaking. Consequently, this paper utilizes the partial least squares regression (PLSR) method to develop a forecasting model for the renewable energy installed capacity in Northwest China. The model incorporates factors including natural resource endowment, electricity demand, power transmission capacity, and government policies, and provides forecasts across low, medium, and high development scenarios. The findings indicate that the PLSR method can effectively resolve multicollinearity issues among independent variables and offers reliable predictions across various scenarios.