A novel approach for optimal allocation of fault current limiter in distribution system via combination of particle swarm optimization algorithm and genetic algorithm (PSOGA)

Nowadays, power systems expansions are undeniable due to increase in power demands. This fact has caused the increase in short circuit level of power networks. So that, The occurrence of short circuit in such networks results in a large short circuit current throughout the system, which may exceed the rating of existing circuit breakers and damage power system equipments. There are some approaches to reduce and suppress this fault current such as power network reinforcement, equipment rating update, utilization of fault current limiter (FCLs) in power system and etc. Because of difficulty and non economic justification in some cases of power network reinforcement, the utilization of FCLs is effective way to limit and suppress fault currents. FCLs utilization have many benefits, such as power network reliability improvement, voltage stability and short circuit current limitation. But this effectiveness depends on rating, number and installation location of FCLs. In this paper, the authors providing a heuristic optimization algorithm that combined particle swarm optimization algorithm (PSO) and genetic algorithm (GA) so that has more effectiveness rather than both of PSO and GA to determine the optimal rating, number and location of FCLs to improve the power network reliability and fault current reduction. IEEE 30 bus system and IEEE 34 node system are considered to evaluate the effectiveness and feasibility of the proposed method. The objective functions considered for the optimal allocation are reliability of power system, economical impact and short circuit current reduction.