Scenario reduction framework to support efficient and accurate power system reliability analysis

Reliability analysis is an important part of power system planning and operation. Considering all events and scenarios which can have a significant impact on the reliability of supply to customers can lead to a large computational burden. Scenario reduction techniques can alleviate some of these challenges. A framework for reducing a set of original operating states into a set of representative operating states using clustering techniques is presented in this paper. A case study is performed where different scenario reduction approaches are tested using the proposed framework. It is shown that scenario reduction can decrease the time spent on the associated reliability analysis by several orders of magnitude, with a limited accuracy impact.