Enhanced state estimator incorporating adaptive underfrequency load shedding under contingencies via the alternating optimization method

Abstract An enhanced state estimator (SE) is proposed to incorporate the real-time underfrequency load shedding (UFLS) information in this paper. During contingencies, the historical SCADA measurements are not accurate enough while the PMU measurements may be inadequate for the SE. Considering that load shedding strategy is a common practice to prevent the system from collapse during contingencies, we can use the shedding information as a viable option to update/correct the SCADA measurements by employing proper techniques. The auxiliary binary variables and scheduled load shedding amount are introduced in the traditional weighted least square formulation so that a more accurate SE can be obtained. The alternating optimization method is utilized to solve the SE problem. Case studies are conducted on the IEEE 30- and 118-Bus system to illustrate the proposed methodology and demonstrate the evident improvements on the reconstructed states.