Multi-objective optimal distributed generation placement using simulated annealing

In this paper, the simulated annealing (SA) is applied to solve the multi-objective optimal placement of distributed generation (DG). The result on the IEEE 30 bus test system shows that the SA can find the optimal location and size with the less computing time than genetic algorithm (GA) and tabu search (TS) as well as the result of multi-objective problem can conclude that the DGs placing in the optimal location are indeed capable of obtaining higher quality solution efficiently comparing with single objective. With the optimal placement of DGs, the system can reduced power loss about 22%, emission about 27.5% and system contingency about 43% comparing with the system without DG.