Dynamic State Estimation of Medium-voltage DC Integrated Power System with Pulse Load

Abstract

The dynamic characteristic evaluation is an important prerequisite for safe and reliable operation of the mediumvoltage DC integrated power system (MIPS), and the dynamic state estimation is an essential technical approach to the evaluation. Unlike the electromechanical transient process in a traditional power system, periodic change in pulse load of the MIPS is an electromagnetic transient process. As the system state suddenly changes in the range of a smaller time constant, it is difficult to estimate the dynamic state due to periodic disturbance. This paper presents a dynamic mathematical model of the MIPS according to the network structure and control strategy, thereby overcoming the restrictions of algebraic variables on the estimation and developing a dynamic state estimation method based on the extended Kalman filter. Using the method of adding fictitious process noise, it is possible to solve the problem that the linearized algorithm of the MIPS model is less reliable when an abrupt change occurs in the pulse load. Therefore, the accuracy of the dynamic state estimation and the stability of the filter can be improved under the periodic disturbance of pulse load. The simulation and experimental results confirm that the proposed model and method are feasible and effective.

Time-domain Dynamic State Estimation for Unbalanced Three-phase Power Systems

“…2) At t 1 = 1, t 2 = 2, and t 3 = 3, we consider load transients in which the active and reactive power of the three-phase loads at buses 14,17, and 26, respectively, increase by the factor 2.…”

“…An unknown-input extended Kalman filter (EKF) is used in [16] for a robust estimation of the generator states. Other component-based DSE approaches based on an EKF have been proposed in [17]- [19]. Reference [20] presents a DSE which estimates the dynamic states of converter-interfaced generation units in microgrids.…”

Dynamic state estimation of power systems considering maximum correlation entropy and quadratic function

“…Traditional supervisory control and data acquisition system cannot obtain fast sampled synchronous measurements, while the phasor measurement units (PMU) based on the global positioning system technology, can provide real-time and synchronized measurements [11,12]. In order to estimate the dynamic states of power system, many approaches including the extended Kalman filter (EKF) [13][14][15], unscented Kalman filter (UKF) [16][17][18][19] and cubature Kalman filter (CKF) [10,[20][21][22]. In addition, the particle filter is also applied for DSE [23][24][25].…”

“…A DSE method using the maximum posterior criteria and EKF is proposed to identify and discard the abnormal values in the measured data [15]. However, the EKF is only suitable for slightly nonlinear systems since it is easy to lose accuracy for highly nonlinear systems [14]. Therefore, a series of UKF based algorithms are proposed to eliminate the errors caused by linearization of nonlinear systems.…”

An energy dispatch optimization for hybrid power ship system based on improved genetic algorithm

“…3 In addition, due to the limitation of ship model caused by the diesel generator system, the traditional optimization strategy can not solve the energy management problem. 4 Therefore, it is crucial to develop an appropriate optimal scheduling strategy for the HESPS under the cost and emission constraints.…”