Optimal Placement of PMU and RTU by Hybrid Genetic Algorithm and Simulated Annealing for Multiarea Power System State Estimation

Abstract

This paper proposes a hybrid genetic algorithm and simulated annealing (HGS) for solving optimal placement of PMU and RTU for multiarea power system state estimation. Each power system control area includes one PMU and several RTUs. Voltage magnitude, voltage angle, and real and reactive current are measured by PMU while the injection and flow of real and reactive power are measured and monitored through RTU. The power injection and flow measurement pairs are placed to observe the raw data of boundary bus and tie line for data exchange in wide-area state estimator. The critical measurement identification is used to consider the critical measurement free in each area. To reduce the number of measurements and RTUs, a PMU is placed at the bus with the highest number of connected branches. The power injection and flow measurement pairs and RTUs are optimally placed to minimize the installation cost of RTUs and power injection and flow measurement pairs. The results of 10-bus single area, IEEE 14 with 2 areas and 118-bus with 9 areas systems are the optimal measurement placement with critical measurement free. Comparison with simulated annealing (SA) is also made.