Prediction of regional power generation based on BP neural network

Presently, with the rapid increase of China´s electricity demand, fluctuation of power load as well as the continuous rise in coal prices, the electricity market generation side of some part region of China is facing risk. By the introduction of BP (Back Propagation) neural network theory, this paper established the regional power generation forecasting model, coal supply, policy implications, weather conditions, resources as well as competitive environment are quantified, then it was used as the network input as well as historical data of the regional power generation to forecast regional power generation as network output, calculate and analysis using by the established model. The outcome shows that this prediction was of full consideration of various factors and adjustment of the relationship between impact factors, it has the merits of minor error and high precision, and it is an effective method of regional power generation prediction.