In the electricity information acquisition network

how to scientifically and accurately identify the abnormal power consumption is crucially important to improve the management of power system. A novel analysis algorithm for abnormal power consumption based on density-based spatial clustering of applications with noise(DBSCAN)in power system is presented. Firstly

the abnormal power range is given by DBSCAN and local outlier factor(LOF). Secondly

the association analysis is used to get association rules and support degree. Then

the score of abnormal power consumption can be gained with combining the before analysis and current power consumption. The identification of abnormal information about power consumption can be realized quickly and reliably by using the percentage of abnormal scores. The simulation results demonstrate that the abnormal analysis algorithm can detect abnormal power consumption effectively

improving the accuracy of the abnormal power consumption analysis.