TY  - EJOU
AU  - Jiang, Ziwei 
AU  - Li, Shuaibing 
AU  - Ma, Xiping 
AU  - Li, Xingmin 
AU  - Kang, Yongqiang 
AU  - Li, Hongwei 
AU  - Dong, Haiying 

TI  - State Estimation of Regional Power Systems with Source-Load Two-Terminal Uncertainties
T2  - Computer Modeling in Engineering \& Sciences

PY  - 2022
VL  - 132
IS  - 1
SN  - 1526-1506

AB  - <p>The development and utilization of large-scale distributed power generation and the increase of impact loads represented by electric locomotives and new energy electric vehicles have brought great challenges to the stable operation of the regional power grid. To improve the prediction accuracy of power systems with source-load two-terminal uncertainties, an adaptive cubature Kalman filter algorithm based on improved initial noise covariance matrix <i>Q</i>0 is proposed in this paper. In the algorithm, the <i>Q</i>0 is used to offset the modeling error, and solves the problem of large voltage amplitude and phase fluctuation of the source-load two-terminal uncertain systems. Verification of the proposed method is implemented on the IEEE 30 node system through simulation. The results show that, compared with the traditional methods, the improved adaptive cubature Kalman filter has higher prediction accuracy, which verifies the effectiveness and accuracy of the proposed method in state estimation of the new energy power system with source-load two-terminal uncertainties.</p>

KW  - New energy source; impact load; new energy power system; state estimation; uncertain system

DO  - 10.32604/cmes.2022.019996