Predicting urban electricity consumption is essential to electricity deployment of the electrical sector. An econometric model is established by using real monthly data from 2004 to 2012 to estimate the impact of weather on electricity consumption. Based on the model estimates, an online operation system of electricity consumption prediction has been initiated and tested for real application. The results show that: (1) There exists a robust and Ushaped relationship between temperature and electricity consumption. (2) The total electricity consumption peaks in winter, and the industrial electricity consumption decreases while the residential increases significantly due to the Spring Festival in February. (3) The simulated values fit quite well with the historical records and the predicted error is less than 5% demonstrating the capability of midlong term prediction. (4) The operation system, incorporated with weather forecasting data, help calculate continuous possible electricity demand of the next 12 months, which provides useful implications for electricity allocation and management.