电力系统及其自动化学报2013，Vol.25Issue(1)：102-106,5.
应用贝叶斯网络的连锁故障模式识别
Cascading Failures Recognition Based on Bayesian Networks
廖苑晰 1李华强 1韦平 2王伊渺 1林茂君 1戴旭1
作者信息
- 1. 四川大学电气信息学院智能电网四川省重点实验室,成都610065
- 2. 四川省地矿局华阳区域地质调查队,双流610213
- 折叠
摘要
Abstract
The evolution of power grid cascading failure is a random process and most of the line breaking faults can be described with breaker breaking. Bayesian network can describe the uncertain information flexibly, and conduct uncertainty reasoning. Build the real-time network topology using Bayesian network theory and calculate the probability of failure, the cascading failures are recognized by introducing the branch static energy function which reflects the power system state to build a risk index. IEEE-30 bus system was used for analysis. The simulation results can search out a set of serious cascading failures and reflect the severity of each mode, which shows the feasibility and validity of the proposed method. 关键词
连锁故障/贝叶斯网络/故障概率/风险指标/模式识别Key words
cascading failures/ Bayesian networks/ failure probability/ risk index/ pattern recognition分类
信息技术与安全科学引用本文复制引用
廖苑晰,李华强,韦平,王伊渺,林茂君,戴旭..应用贝叶斯网络的连锁故障模式识别[J].电力系统及其自动化学报,2013,25(1):102-106,5.
