Dynamic-state-estimation scheme including nonlinear measurement function considerations

Abstract

An algorithm that includes nonlinear measurement-function considerations is proposed. To enhance the robustness of the method, the exponential weight function was embedded and the nonlinear measurement function was integrated with the state-estimation model. In this way, the method can be employed in different scenarios while the estimation performance can be maintained effectively. This approach has been tested on different power systems under various operating conditions, where normal operation, bad measurement, sudden load change and topology error are all investigated. The performance indices under different test cases were also evaluated. Test results support the feasibility of the proposed method for dynamic-state-estimation applications.