The successful completion of electric power operation and maintenance guarantee is related to the safety of regional electricity. This paper analyzes the functional needs of electric power operation and maintenance, and designs the intelligent electric power operation and maintenance guarantee platform through multi-dimensional comprehensive consideration to realize the intelligence of electric power operation and maintenance. On the basis of linear division of load data, transformer load factor-winding temperature rise causal pair is constructed, and its correlation rules are mined. Combined with the short-term load combination prediction method containing predictioncorrection, it predicts and corrects transformer loads at all levels of the substation to reduce the risk of transformer damage and O&M costs. Using actual load data, the effectiveness of the association analysis method and shortterm load combination prediction method is verified, and the technical advantages of the intelligent operation and maintenance guarantee platform are judged. The results show that the transformer intelligent maintenance model based on correlation analysis achieves an overall recognition rate of 0.9 for transformer fault conditions, and is able to realize effective early warning. In the test of short-term load prediction combination method containing predictioncorrection, it can effectively predict three outliers in the load data for two consecutive days, and the fluctuation of load data remains stable after correction.
