Anomaly detection method and system for monitoring data flow of power grid equipment

The invention relates to the technical field of multivariate data monitoring and diagnosis in the power grid power industry, and provides a power grid equipment monitoring data flow anomaly detection method and system, and the method comprises the steps: 1, collecting power grid equipment monitoring data, and forming to-be-processed data; 2, processing the to-be-processed data by adopting a sliding window algorithm, and solving a linear predicted value; step 3, obtaining confidence intervals of all the predicted values in the linear predicted values, comparing whether the actual values of the data to be processed corresponding to the predicted values are within the confidence intervals, if so, continuing to judge the actual values of other data to be processed, and if not, continuing to judge the actual values of other data to be processed; if not, judging that the actual value of the to-be-processed data is abnormal data, and storing a predicted value corresponding to the abnormal data in a predicted value d