An adaptive hybrid dynamic state estimation method of the medium-voltage DC integrated power system with pulse load

When a great change periodically takes place in power of the periodic pulse load in the medium-voltage DC integrated power system in a short time, it will lead the system to stay in a periodic electromagnetic (EM) transient state. Its time constant is far less than that of the traditional land power system which is in an electromechanical transient state, so the convergence of the filter and accuracy of the estimation will be affected. This problem is similar to the estimation of a maneuvering target in tracking, but the methods used for estimating the maneuvering target cannot be directly applied to estimate the EM transient of the system. For this reason this paper proposes an adaptive estimation method. Based on the high accuracy of unscented Kalman filter and reliability of Hybrid extended Kalman filter under EM transient conditions, the method can ensure the accuracy of estimation and reliability of the algorithm by adaptively adjusting the estimation method according to changes in the system operating conditions. The method is proved to be better than the existing method in terms of estimative effect through experiment and also proved to be reliable by the consistency test on the filter.

Automated summary

An adaptive estimation method is proposed in this paper to ensure the accuracy of estimation and reliability of the algorithm by adaptively adjusting the estimation method according to changes in the system operating conditions, providing a solution to the electromagnetic transient issue caused by the periodic pulse load power changes in the medium-voltage DC integrated power system. The method is proven to be superior to existing methods in terms of estimative effect through experiments and is also validated for its reliability through consistency tests on the filter.