Energy Data Collection and Scheduling of AMI Based on Consistent Hash and Greedy Optimization

Abstract

Efficient access to smart meter data is of great significance to the stable operation of AMI. However, the traditional power grid system still has problems such as unbalanced distributed storage load and low efficiency. Aiming at the problem of system performance deterioration caused by the rapid increase in the amount of energy data, this paper proposes a scheduling method based on consistent hash and greedy algorithms to optimize the storage, query and analysis process of smart meter data. First, different hash algorithms are researched. Then the SHA-1 algorithm with better effect is selected and put into use. After that, consistent hash is used to optimize the performance of distributed storage. Finally, the node selection strategy can be adjusted based on the greedy algorithm, and the appropriate greedy threshold parameter is statistically summarized. The experimental results show that our method is effective.