Shanghai Electricity Consumption Prediction Based on Long-Range Energy Alternatives Planning Model

Electricity consumption prediction plays a crucial role in energy planning and policy formulation, especially in rapidly growing urban centers like Shanghai. This paper presents a methodology for forecasting electricity consumption in Shanghai using the long-range energy alternatives planning (LEAP) model. By integrating various influencing factors such as population growth, economic development, industrial activity, technological advancements, and policy interventions, the LEAP model facilitates scenario analysis and parameterization to generate predictions of electricity consumption under diverse plausible scenarios. First, this paper outlines the steps involved in developing the LEAP forecast model, discusses key assumptions and input data. Next, the accuracy of the proposed model over classical machine learning based methods is tested and validated. Finally, the model is employed to predict Shanghai electricity consumption till 2050.