1.School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China;2.School of Computer Science and Technology, Beihua University, Jilin 132021, China;3.Tonghua Power Supply Company, State Grid Jilin Electric Power Supply Company, Tonghua 134001, China;4.Changchun Power Supply Company, State Grid Jilin Electric Power Supply Company, Changchun 130021, China

Aiming at the problem of how to realize the efficient transformation of rural electric power grid through precise investment, a lean transformation method for rural electric power grid is put forward based on cascaded combination scoring. Firstly, the main problems existing in the current rural electric power grid are sorted out, and the corresponding evaluation indices are defined. The calculation formulas for matching each evaluation index are given. The severity of each problem is graded, and the cascaded evaluation criteria for each evaluation index is set up. An evaluation index system is constructed, which can fully reflect the weak links of rural electric power grid and its severity. Secondly, according to the index value, the equipment that needs to be transformed is determined and taken as the evaluation object. According to the evaluation index evaluation criteria, the evaluation object is scored. The weight of each evaluation index is determined by criteria importance through intercriteria correlation (CRITIC) method, the comprehensive score of evaluation object is calculated and the cascaded combination score of the evaluation objects is then completed. Finally, the evaluation objects are arranged in the descending order according to the size of the comprehensive score and the top ranking equipment should be given priority to be reformed first. The example analysis proves the correctness and effectiveness of the method.

This work is supported by National Key R&D Program of China (No. 2017YFB0902200), Industrial Innovation Foundation of Jilin Province (No. 2019C058-7) and Science and Technology Project of Education Department of Jilin Province (No. JJKH20180442KJ).