PMU-based recursive state estimation and its performance with neural network

Phasor measurement units (PMUs) are considered promising for future monitoring, protection and control of power systems. In this paper, an approach is proposed to achieve higher degrees of precision in state estimation using PMUs by recursive weighted least square method. Additionally, when neural network is used as a state estimator in conjunction with the PMUs, a method that uses less number of inputs is proposed for even higher precision of estimating the states as compared to conventional methods.