Data Mining Technology Application In Load Characteristics Analysis

In recent years, the power demand has been driven by fast increasing of Jiangsu's economic. The high record of social electricity consumption and its risen rate has been updated for several times. It's a big challenge for power supply in order. The conflict between supplying and demanding side centralizes in lacking-power through whole year, specially in summer while only partly or seasonal lacking-power in 2002. In order to help administrators make decisions analyzing the local load characteristics then taking new and efficient measures is required as soon as possible. Many types of power data is needed such as load weather economic and so on. How to handle these large sort of data fast and quickly is a problem which is becoming more and more emergent. In some fields more and more matured data mining technology has emerged its advantages. To promote the efficient and reliability of power system data mining technology will be used more widely.This paper introduces the development of local economy and power supply firstly. Then it analyses the local load characteristics, mainly on load-rate of years and typical daily load data or curves so that we can find the main specialty of the local load.After that, the relativity analysis on temperature including economic factors and load characteristics carries on based on Apriori arithmetic which belongs to data mining technology.Finally the paper used Fuzzy Clusters Method analyzing consumer's load curves. Then reshape the curve of the whole society according the clusters. Compared the reshaped curve with the true curve and make a conclusion.