Research on Long-Term Electricity Demand Forecasting Based on WOA-BP

Power supply and demand balance is a vital prerequisite for boosting economic development and raising people’s living standards, and precise forecasting of power demand is the cornerstone for guaranteeing power supply and demand balance. Reasonable and accurate power demand forecast plays an important role in guiding the planning and development of power industry. Therefore, this paper takes the power consumption of the whole society as the representative of the power demands as the research objective, selects the influential factors that may affect the power consumption from multiple angles, and uses the grey correlation degree to analyze the influence degree, and the factors with greater influence in the whole region as the predictive dependent variable. Then, the back propagation neural network optimized by the whale algorithm is used to train the model through the screened data and predict the future electricity consumption of the whole society. Then, an empirical model analysis is carried out with the whole society electricity consumption of a province in East China as the research object, which proves that the prediction effect of the model is good, and the prediction results provide a basis for the future power planning and development of the province.