using the nonlinear Kalman filter to reduce the effect of lack of measurements on distribution grid state

In smart distribution grids, different parameters are sent to a control center via a communication network. Each distribution grid state estimator uses these measurements. The state estimation error would be increased if there are no measurements because of the communication platform is damaged or some of meters are failed. In this paper, astate estimation method based on unscented Kalman filter(UKF)has been proposed. The proposed method is resistant to the lack of measurements for a long time.

Keywords:

distribution grid , state estimation , unscented Kalman filter , dynamic model