Research and application progress of data mining technology in electric power system

Abstract

With the rapid development of computer technology and the improvement of intelligent technologies in electric power engineering, the volume of data has increased exponentially. Data mining technology can be utilized to search information hidden in the huge amounts of data, and then the data can be transformed into useful knowledge to promote the development of electric power technology. In order to be acquainted with the research and application progress of data mining technology in electric power engineering, several major data mining algorithms are introduced in this paper, including ANN (Artificial Neural Network) algorithm, SVM (Support Vector Machine) algorithm, decision tree algorithm, K-means algorithm, NBC (Naive Bayesian Classification) algorithm and Apriori algorithm. And then, the methods of data mining technology in prediction, classification, clustering and association rules analysis are explained in detail in this engineering, which are combined with the electricity price prediction, power load forecasting, fault type identification, system state classification, power generation side association rules, power grid operation data association analysis. At last, this technology in electric power engineering is summarized and an expectation for the future development is provided.