Title :
Characteristics Analysis and Risk Modeling of Ice Flashover Fault in Power Grids
Author :
Sun, Yu ; Wang, Xiuli ; Bie, Zhaohong ; Wang, Xifan
Author_Institution :
State Key Lab. of Electr. Insulation & Power Equip., Xi´´an Jiaotong Univ., Xi´´an, China
fDate :
7/1/2012 12:00:00 AM
Abstract :
Ice flashover faults (IFFs) that occur in groups can be a key factor in grid collapse. This study analyzed IFF characteristics and developed a basic risk assessment model. The aim is to reveal the IFF inherent law, and provides a direction for the future ice storms. Moreover, IFF risk model is the basis of risk assessment of power grid during ice storms. The critical values of ice bridging and shedding from insulators were identified. A state division principle categorized the IFF modes. A risk rating method then developed, based on these IFF modes. In view of the limited experience data with small sample size and many important inputs, the least squares support vector machines risk modeling method was adopted and its model parameters optimized by Bayesian inference. In reduction to practice, some vulnerability indices are suggested to analyze the risk of grid IFFs for future ice storms.
Keywords :
belief networks; flashover; insulators; least squares approximations; load shedding; power engineering computing; power grids; power system faults; support vector machines; Bayesian inference; IFF characteristics; IFF inherent law; IFF risk model; ice bridging; ice flashover fault; ice shedding; insulators; least squares support vector machines risk modeling method; power grids; risk assessment; risk rating method; Ice thickness; Insulators; Monitoring; Power grids; Storms; Temperature sensors; Characteristics analysis; extreme ice disaster event; ice flashover faults; reliability modeling; risk identification; small sample method; vulnerability indices;
Journal_Title :
Power Delivery, IEEE Transactions on
DOI :
10.1109/TPWRD.2012.2193903