Optimal measurement placement for power system state estimation using hybrid genetic algorithm and simulated annealing

This paper proposes a hybrid genetic algorithm and simulated annealing (GA/SA) for solving optimal measurement placement for power system state estimation. Even though the global minimum measurement pair number is (N - 1), their positions are required to make the system observable. GA/SA algorithm is based on genetic algorithm (GA) process. The acceptance criterion of simulated annealing (SA) is used for chromosome selection. Single measurement pair loss contingency is also considered. The P theta observable concept is used to check the network observability. Test results of 10-bus, IEEE 14, 30, 57 and 118-bus systems indicate that GA/SA is superior to tabu search (TS), GA and SA in terms of higher frequency of the. best hit and faster computational time.