Researching And Application Of Kaiping Power System Load Forecasting Method

Load forecasting refers to the estimation and predication of electric power needs according to the variation of electric power load and the influential rules of such factors as economic through the analysis of historic data as well as the study of inherent relationship between things and variation rules. As an important part of the running of power supply enterprises, Load Forecasting is not only the base of electric system construction and maintenance, but also the prerequisite for electric system security.Load Forecasting takes power load or power consumption of an entire area as the subject of predication, whose result determines future power demand and capacity of power network. The amount of power load and power consumption, as the foundation of electric system planning, is determined by the scale and developing speed of electric system, while the result of load forecasting serves as direct reference for the determination of power source location. The improvement of Load Forecasting accuracy will be of great significance for analyzing power market needs and marketing and maintaining client relationship as well as guaranteeing enough electricity for producing and living. The accuracy of Load Forecasting has a direct bearing on the interests of all aspects, including power suppliers, electric power transmission, distribution, and power consumers. Methods of predicating, also called mathematical models, are the core of Load Forecasting. This thesis introduces in detail the concepts, features, and catalogues as well as common methods of Power Load Forecasting. Through analyzing the historic data of Kaiping City's power load, the author selected a predicating mathematical model that was suitable to local load developing rules. Based on this, the best forecasting results would come from a scientific combination of results from different mathematical models. Then the author forecasted Kaiping City's power consumption in five years in order to offer scientific reference to electricity distribution and management of electricity consumption needs.