Eigenvalue-based optimal placement of PMUs in large power systems

This paper presents an eigenvalue-based approach for optimal placement of phasor measurement units (PMUs) in large power systems. Eigenvalues of system parameters are used to determine the critical points of the system. The identification of the critical points of a system for PMU installation could be crucial in the detection of potential outages and preventing them from occurring. This method ensures that a minimal number of PMU locations are identified and that the loss of a PMU does not affect the reliability of the monitoring system. Therefore, it is cost-effective. The number of measurements obtainable using this approach is fewer than the 2n−1 required for conventional state estimation to function. (n is the number of buses in the system.) The proposed approach is a holistic approach to the monitoring of the entire system, in that the placement of PMUs for monitoring critical points of the system does not happen at the expense of monitoring the rest of the system. To show that the identified critical PMU measurements are capable of accurately estimating all system variables, an artificial neural network is utilized to map the estimation function between the critical variables and the rest of the system variables. The performance of the proposed techniques is demonstrated on the IEEE 118-bus system.