An Improved Power System State Estimation Using A Dynamically Adapted JAYA Algorithm

Abstract

State estimation is a central issue for power systems monitoring and control. Applying state estimation schemes ensures the accuracy of system real-time monitoring process. Due to the high nonlinearities and non-smoothness of the dynamic behavior of power systems, state estimation is getting more importance to lessen the error margins. In order to find the best estimate of the various variables of a power system, optimization-based and statistical techniques are applied. Classically, common metering devices are used to measure power system variables. Nevertheless, these devices are associated with errors, especially with the ongoing expansion of the power networks. These errors are linked to many issues related to operation and communication processes besides the errors caused by the metering device itself. The commonly applied technique to solve the power system state estimation problem is the Weighted Least-Squares (WLS) method. In this paper a dynamically adapted algorithm is introduced employing a WLS-based dynamic JAYA optimization technique. The algorithm was validated and applied on the well-known IEEE 14-bus network. The results proved the efficiency and advantages of the proposed algorithm when compared to other methods used for the state estimation problem.