Dynamic lightning protection method of electric power systems based on the large data characteristics

Abstract

In this paper, a new active dynamic lightning protection method is proposed based on the large data characteristics of electric power. This method mainly includes two parts: Part one, Neo4j framework model which is used to analyze large data of power system and dynamic regulation of power system, and Python software which is used to compare and analyze different framework models; Part two, the comparison between dynamic lightning and conventional protection methods. The results show that Neo4j traversal speed is 87.5% and 89.1% faster than Hadoop and Spark respectively, clustering effect is 12.5% and 17.8% higher than Hadoop and Spark respectively. As a result, Neo4j framework model is more suitable for the characteristics of large data in power system. After the lightning accident, the power-off time of dynamic lightning protection system is reduced by about 53.1%, and the recovery time of the system also decreased by about 42.8%. In the dynamic regulation of power system, the output of power supply is reduced by 35.1 MW and the load is cut out by 15.8 MW, which greatly reduce the impact of lightning strike on power supply and important load.