Design of a transient stability scheme to prevent cascading blackouts

This paper presents a novel optimization technique of the settings for various emergency controls in an electrical power system. The goal of this technique is to prevent a cascading blackout and retrieve a new equilibrium operation point following a severe contingency. The main stabilizing actions are tripping generators together with load shedding. This problem is a complex mixed integer programming problem and it is very difficult to solve by ordinary optimization methods such as mathematical approaches. Genetic Algorithms are search algorithms based on the mechanics of natural selection and natural genetics, and are subject to survival of the fittest among string structures. Since the Genetic Algorithm approach is very successful at solving combinatorial optimization problems, it has been applied to solving the problem of cascading blackouts. A Genetic algorithm approach is used to find the optimal combination of generators and loads to be tripped in order to regain a new state of equilibrium in operation, and hence, to prevent the system from failing in this cascading manner. These solutions are evaluated by using the hybrid transient energy function, and the GA optimization technique is able to select the best solution. The two cases tested in order to assess the feasibility of this technique were the 14-bus IEEE network and the 20-machine, dynamically-reduced England Network. The results presented in this paper show that global or near-global optimum solutions can be ascertained within reasonable amounts of time by this new method.