High Order Contingency Selection Using Particle Swarm Optimization and Tabu Search

There is a growing interest in investigating the high order contingency events that may result in large blackouts, which have been a great concern for power grid secure operation. The actual number of high order contingency is too large for operators and planner to apply a brute-force enumerative analysis. This paper presents a method, which combines the unique features of particle swarm optimization (PSO) and tabu search, to select severe high order contingencies. The original PSO algorithm gives an intelligent strategy to search the feasible solution space, but tends to find the best solution only. The proposed method combines the original PSO with tabu search such that a number of top candidates will be identified. This fits the need of high order contingency screening, which can be eventually the input to many other more complicate security analyses.