Multi-objective reactive power optimization by Modified Artificial Fish Swarm Algorithm in IEEE 57-bus power system

Modified Artificial Fish Swarm Algorithm (MAFSA) was proposed to optimize the reactive power optimization, which is evaluated on an IEEE 57-bus power system. MAFSA based on the global search characteristic of Artificial Fish Swarm Algorithm (AFSA) and combined with the local search of chaos optimization algorithm(COA) can avoid trapping into local minimal value and decrease the iteration numbers, which was a swarm intelligence optimization algorithm applied to continuous space. The models of multi-objective reactive power optimization were established taking the minimum active power losses, the best voltage level and the biggest static voltage stability margin as the objects, using fuzzy set theory to transform multi-objective optimization problems into a single objective optimization problem. The simulation results and the comparison results with AFSA proved that the MAFSA was able to heighten power system voltage stability during the economical operation and the algorithm can make effectively use in multi-objective reactive power optimization.