Anomaly detection method of power dispatching data based on cloud computing platform

The traditional power dispatching data anomaly detection method USES the principle of template matching, which not only has large calculation amount and long processing time, but also the accuracy of the detection method is greatly affected by the template. Aiming at the above problems, the anomaly detection method of power dispatching data based on cloud computing platform is studied. The power demand of residents in the grid is analyzed to determine the load response of residential electricity. To process the detected power dispatching data, the cloud computing platform is used to cluster the processed data and the electricity demand response data to complete the detection of abnormal data. Through the comparison experiment with the traditional power dispatching data anomaly detection method, it is verified that the detection method based on the cloud platform saves about 1.3 times of the detection time, and the detection accuracy of abnormal data is higher.