Abstract: Because the existing algorithms failed to cluster the power data, the recall rate decreases. Therefore, a refined verification algorithm for power multilevel redundant data in variable load mode is proposed. In the variable load mode, through the sparsity of power signal, the transformation coefficient is linearly projected to the low-dimensional observation vector to solve the sparsity optimization with high probability and complete the data acquisition. The genetic clustering optimization algorithm is used to cluster the collected power data. According to the clustering results, the analytic hierarchy process is introduced to obtain the correlation between different data, and the refined verification criterion of power multilevel redundant data is constructed, and the data verification is completed through the verification criterion. Experimental results show that the proposed algorithm can effectively reduce the verification time and extra storage overhead, and increase the recall ratio and the accuracy of verification results.

Key words: variable load mode')">

variable load mode, power multi-level redundant data, refinement, verification, clustering