The Research And Application On Decision Support Technology In Power Quality Monitoring

With the extensive application of electric power in various national economy departments and the rapid increase of electric power load, problems of electric power quality have increasingly become more important. Accurate dynamic monitoring and timely predicting alarm in grid are the precondition of ensuring normal order of power supply to users and strengthening the management and monitoring of electric power quality. Based on problems of electric power quality and requirements of fieldwork, this thesis focuses on the research of decision support technology and its application in monitoring, to construct on-line monitoring system in which the functions of data analysis, problem-classifying and predicting, real-time data displaying are analyzed and designed. Meanwhile, This thesis carries out the online analysis of real-time monitoring data in a certain electric power department, analyses the problems of electric power quality and achieves the functions of classifying, predicting alarm and the real-time displaying of each data index through the methods of wavelet analysis and bayes classification.