Analysis of Multi Index Association of Power Grid Work Order based on Data Mining

Abstract

Distribution network work order is one of the important indicators to reflect the operation and management level of distribution network, which has important information value for providing auxiliary production decision-making of distribution network. In the face of massive distribution network work order data, need to solve the problem of how to transform the data into auxiliary decision-making information. In this paper, through machine learning, big data and other artificial intelligence technology and data mining technology, the distribution network operation index correlation analysis and intelligent prediction, found the inherent law between the operation index, realized accurate operation and maintenance and scientific decision-making. Firstly, the distribution network work order data was preprocessed to clean the error and abnormal data, and the fuzzy algorithm was used to match the corresponding station area according to the lack of station area. Secondly, the type and characteristics of each type of work order were analyzed, and the distribution network work order index mining was carried out through PrefixSpan algorithm. Finally, the effectiveness of the proposed algorithm was verified through the actual data, and the operation and maintenance of the distribution network were analyzed The paper put forward the preventive measures for the weak links in the service.