The Method And Application On Load Forecasting Base On Data Mining Of The Longyan Electric Energy Data Acquisition System

With the increasing development of power system in our country, people pay more and more attention to the development of load forecasting, load forecasting has become one of the important symbols of modernization management level. Selecting the appropriate load forecasting model is the key to improve the load forecasting accuracy. Load forecasting Accurate can make operation personnel in power system timely grasp the rules of the load variation.This paper first briefly introduces the power load forecasting of the purpose, significance and the domestic and foreign research trends and information acquisition system. At the same time, this paper introduces the relevant theory, first introduced the classification of power load forecasting, load forecasting method and the effects of main factors such as load forecasting;Secondly, the paper introduce the structure, the function and the application of the electric energy data acquisition systemThis paper through to the Longyan regional power load characteristics of in-depth study, and analysis of the impact of power load characteristics and related factors of influence of specific relations, provides the basis for load forecasting.In combination with the electric energy data acquisition system of original data and the analysis of load characteristic in Longyan area, this paper adopts the method of regression analysis, the grey model analysis method, time series prediction method of three kinds of load forecasting model, and predicts Longyan area power load development condition. The results show that, using this three kinds to forecast a method, can achieve satisfactory forecast results.The paper constructs the mathematic model at the basis of analyzing the speciality of the real load an applying the knowledge of maths and computer to real course, finally obtains accurate forecasting results. Before analyzing the speciality of the real and constructing the mathematic model, it’s necessary to processing the data to wipe off the bad-data which does not accord with the fact.Finally, the paper points out some problems in the process of the load forecasting Including data preprocessing, sample selection and standardization of treatment, ect.