Faced with the power system operation data set which has the characteristics of massive amounts of data and multiple numerical types

how to achieve a rapid and accurate network loss evaluation in power system will become an important issue. In accord with the data mining and typical scenario simulation method

a novel network loss evaluation method based on hybrid clustering analysis is proposed. The clustering attributes associated with network loss are determined from the power system operation data set first. Based on the division of different numerical types of clustering attributes

the original clustering problem is divided into two clustering sub-problems. In consideration of the characteristic of power data

the partitioning clustering method and hierarchical clustering method are adopted respectively to deal with the two clustering sub-problems. The clustering ensemble technique is further employed to achieve a mixed clustering result

which is finally utilized to generate a typical power system operation data set for the evaluation of network loss. The numerical result shows the proposed network loss evaluation method has good evaluation precision and computational efficiency

which can be effectively applied to engineering practice. This work is supported by National Natural Science Foundation of China (No. 51277141).