Probabilistic multi-objective state estimationbased PMU placement in the presence of bad data and missing measurements

Abstract

This study proposes a multi-objective probabilistic coordinated method for state estimation (SE) in a power system by optimal placement of phasor measurement units (PMUs) in the presence of bad data and missing measurements. For this purpose, using a three-stage SE approach and a linear estimator, the conventional and PMU measurements are used simultaneously for SE and then, the obtained estimates are integrated through estimation fusion theory. Subsequently, the proposed optimal PMU placement (OPP) method finds out the minimum number and the optimal location of PMUs required to achieve the desired accuracy of the power system SE. Furthermore, a 2m+1 point estimated method is used to model the uncertainty of measurements to increase the adaptation with realistic operation condition. A modified Jaya algorithm is formulated to minimises four objective functions in an effective multi-objective method where the network constraints are satisfied. The standard IEEE 30-and 57-bus systems are used to evaluate the efficiency of the proposed method. To investigate different aspects of the proposed formulation, different cases are proposed and the results obtained are compared. The obtained results show that the determined OPP by the proposed method can eliminate the effect of conventional bad measuring data and missing measurement devices.