PMU Placement Methods in Power Systems Based on Evolutionary Algorithms and GPS Receiver

In this paper, optimal placement of phasor measurement unit (pmu) using global positioning system (gps) is discussed. ant colony optimization (aco), simulated annealing (sa), particle swarm optimization (pso) and genetic algorithm (ga) are used for this problem. pheromone evaporation coefficient and the probability of moving from state x to state y by ants are introduced into the aco. the modified algorithm overcomes the aco in obtaining global optimal solution and convergence speed, when applied to optimize the pmu placement problem. we also compare this simulation with sa, pso and ga to examine the capability of aco in the search of optimal solution. the fitness function includes observability, redundancy and the number of pmu. logarithmic least square method (llsm) is used to calculate the weights of fitness function. the suggested optimization method is applied in 30-bus ieee system and the simulation results show that modified aco results are better than pso and sa, but it has nearly the same results as ga.