1090 / 2019-05-20 16:43:50

Monthly Electricity Forecast Based on the Electricity Consumption Characteristics Analysis and Several Effect Factors

electricity forecast,Elman nerual network,electricity consumption characteristics,temperature

The accurate prediction of users' monthly electricity is the basis for electric power department to allocate power resources and for electric power company to make reasonable sales plans. Based on the in-depth mining of historical electricity data and comprehensively electricity consumption characteristics analysis, a monthly electricity forecast method considering temperature and holidays is proposed. Firstly, the Elman neural network prediction model is built based on historical electricity data and temperature data. Then, the monthly electricity data affected by holidays is modified to obtain a more accurate monthly electricity prediction model. The monthly electricity data of province A is used to do the verification. By comparing the forecast error of Elman neural network without considering effect of temperature and holidays and the forecast error of proposed algorithm, the accuracy of the proposed algorithm is verified to be improved.It verifies the effectiveness of the prediction algorithm．