Association Rules Mining Of Transmission Line Fault In Extreme Climate Research

In the 21st century, with the development of production and people’s living, the demand for electricity is also increasing. However, the frequent accidents of power system have become a serious impediment to social development. There are many causes of the power system fault, extreme climate is one of the most influential causes and some laws hide in the incident properties, if we can dig out the potential link in the accident data, then the relevant departments would take action according to the science analysis.This paper first of all researched on the power system accident in extreme climate, summarized the approach stage accident analysis of the power system at home and abroad. By analyzing we knew that the power system accident demonstrated the complexity and diversity, this mean, data processing tools, data anglicizing ways and means in the traditional sense had been slowly not meet the requirements of the time. So we used association rules of data mining to dig out knowledge from the mass of unknown data and elaborated the basic knowledge of association rules; second used the association rules in the real power system accident cases to find the valuable information and dig out the hiding rules in accident factors. Used the data of above 110KV transmission line fault in a province from 2008 to 2012 as analysis model and described the properties of the power system accident, built the model of the power system accident properties; last according to the data analysis, researched and improved the Apriori algorithm and finally used it in the case, mined the influence factors of the power system accident. If weaken or disappear the associated factors by artificial regulation, we can prevent and reduce accidents to a certain extent.From the experiment result, it turn out application of association rule in the power system accident was feasible and valuable.