State estimation (SE) serves as the heart of the energy management systems in providing online database by processing slow‐sampled supervisory control and data acquisition (SCADA) measurements. The recent development of fast sampled phasor measurement units (PMUs) provides real‐time measurements that enable tracking of the system state; however, the associated high initial cost does not allow to completely replace the existing SCADA measurements by PMUs. This article thus attempts to employ both the SCADA and PMU measurements, and suggests a new SE scheme comprising of a static SE module (SSEM) that estimates system state at defined time interval in the order of minutes using both the SCADA and PMU measurements, and a fast state reconstructing module for tracking the system state using PMU measurements and the calculated pseudo measurements in place of SCADA measurements. The proposed scheme employs Broyden's approach that avoids repeated formation and factorization of the Jacobian and gain matrices, respectively while iteratively solving the nonlinear simultaneous equations. It exhibits superior computational efficiency of the suggested scheme by presenting simulation results of four standard test systems.
State estimation (SE) processes the real-time measurements and provides database to energy control centre for safety control of energy systems. Traditionally Weighted Least Square (WLS) and Weighted Least Absolute Value (WLAV) based algorithms have been suggested for SE but the development of very fast computers and parallel processing enable the system engineers to think of employing the computationally inefficient evolutionary algorithms, which are known to be robust and stable, in solving SE problems. This paper suggests a most valuable player algorithm based SE involving WLS and WLAV objectives one at a time, and presents results on four IEEE test systems for illustrating its superiority.
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