Contingency Probability Estimation Using Weather and Geographical Data for On-Line Security Assessment

Contingency probabilities are essential in applying probabilistic methods to operations-based security assessment and related decision-making. There are two basic issues that need particular attention. One is lack of data. The other is dependence on environmental conditions. This paper describes design and implementation of a contingency probability estimator. Statistical methods employed in the estimator include maximum likelihood and linear regression. The work makes use of a limited amount of historical data together with corresponding weather and locational data, to provide contingency probabilities that appropriately reflect conditions and location of each circuit. The approach is illustrated using four years of outage data