A parallel evaluation method of health degree based on MapReduce for smart grid dispatching and control system

In order to grasp the running status of the smart grid dispatching and control system in time, a parallel evaluation method of health degree based on MapReduce is proposed in this paper for the system's business complexity, complexity of evaluation indicators, large amount of evaluation calculation and requirement of evaluation time. Firstly, the health degree evaluation system which reflects the relationship between service level and priority is sorted out on the basis of D5000 system hierarchy analysis. Secondly, the health score of the system is calculated by modular MapReduce framework. In the first level MapReduce, Map task reads data and splits task. Reduce task calculates second-level indicators by hierarchical of D5000 system. In the second level MapReduce, it summaries score of second-level indicators in order to get the score of system and give the system status. Meanwhile, the adaptive task scheduling method ensure the system load balancing. Finally, the experiment platform of health evaluation of D5000 system is established, and the health evaluation experiment is carried out by the data of D5000 system. The result shows that the proposed method improves the efficiency of health calculation.