State Estimation of Power Systems Using Broyden s Method and Metaheuristic Algorithms

Abstract

Motivation and Problem Statement: State estimation (SE) is the centre of the EMSs by developing SCADA (slow-sampled) measurements yielding online database. The contemporary evolution of fast sampled PMUs provides measurements in real-time that track the state of the system; but, the high cost does not encourage in the replacement of SCADA with PMUs. The classical WLS-based static SE (SSE) methods were devised to process only the SCADA measurements (slow-sampled), and may not exploit the fast-sampled PMU measurements in reconstructing the system state in between the two subsequent SSE processes. The repeated Jacobian matrix formation, multiplication of several matrices to form the gain matrix, and the gain matrix inversion during the iterations make the WLS scheme an inefficient one. This drawback necessitates the development of improved WLS having the ability to process the fast-sampled PMUMs in reconstructing the system state in a real-time environmen newline