Big Data Mining Analysis of Power Grid Based on Apriori Optimization

Abstract

To ensure the safe and stable operation of the power grid system and strengthen the refined management level of the State Grid Corporation of China, a grid operation big data association analysis model based on Apriori association algorithm is proposed. This paper discusses the logic framework of the power big data platform, and describes the specific implementation from the functional architecture, technical architecture and other aspects. Aiming at the problem of massive heterogeneous power data and low sharing degree, the transaction matrix is pruned and compressed by setting the minimum support degree and establishing the frequent set matrix, and the implementation process of the improved algorithm on the MapReduce programming model of Hadoop platform is provided. Based on the research of Spark programming model, the improved algorithm is implemented in parallel style. The experimental results show that the efficiency of the algorithm after parallel processing has been greatly improved, which can also effectively improve the calculation amount and efficiency of power big data.