用Apriori关联规则挖掘算法发现湖北电网雷击灾害的时空分布规律

doi:10.3969/j.issn.0255-8297.2017.01.004

Journal of Applied Sciences ›› 2017, Vol. 35 ›› Issue (1): 31-41.doi: 10.3969/j.issn.0255-8297.2017.01.004

• Special Column of Smart Grid • Previous Articles Next Articles

Spatiotemporal Distribution of Lightning Disasters of Power Lines in Hubei Province Using Data Mining Based on Apriori Association Rules

HUANG Jun-jie^1,2, TAN Bo³, CHEN Xiao-ming^1,2, CHEN Jiang-ping³, RUAN Ling^1,2, FENG Wan-shu³, XIONG Yu^1,2

1. State Grid Hubei Electric Power Research Institute, Wuhan 430077, China;
2. Key Laboratory of High-voltage Field-Test Technique of State Grid, Wuhan 430077, China;
3. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

Received:2015-10-29 Revised:2016-03-04 Online:2017-01-30 Published:2017-01-30

Abstract

Abstract:

By using the data of lightning failure and monitoring of the past years provided by Hubei Grid, this paper studies the characteristics of daily and monthly distributions of lightning activity, as well as the elevation distribution and spatiotemporal distribution.The results show that lightning in Hubei Province mainly occurs in July and August, and between 15:00 and 18:00 during the day.The active regions include the east parts of Huangshi and Xianning, central Wuhan, central and eastern Yichang, and southern and part of northern Xiangfan.The multi-source lightning data are fused with an algorithm based on Apriori association rules.The research shows that lightning shield of the power lines may fail when daily average relative humidity is higher than 80%, daily average air pressure is higher than 1×10⁵Pa, or daily average water vapor pressure is between 3×10³ Pa and 4×10³ Pa.In these cases, therefore, measures should be taken to strengthen lightning prevention.Analyzing big data of lightning around power lines using the association rules can provide guidance to decision makers of power lines for disaster prevention.

Key words: power grid, association rule mining, temporal and spatial regularity, lightning

CLC Number:

P237

HUANG Jun-jie, TAN Bo, CHEN Xiao-ming, CHEN Jiang-ping, RUAN Ling, FENG Wan-shu, XIONG Yu. Spatiotemporal Distribution of Lightning Disasters of Power Lines in Hubei Province Using Data Mining Based on Apriori Association Rules[J]. Journal of Applied Sciences, 2017, 35(1): 31-41.

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Spatiotemporal Distribution of Lightning Disasters of Power Lines in Hubei Province Using Data Mining Based on Apriori Association Rules

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