张叶贵,刘敏,石倩,罗永平,孙江山.基于自适应容积卡尔曼滤波的主动配电网状态估计[J].电测与仪表,2020,57(19):27-32. ZHANG Yegui,LIU Min,SHI Qian,LUO Yongping,SUN JiangShan.State Estimation of Active Distribution Network Based on ACKF[J].Electrical Measurement & Instrumentation,2020,57(19):27-32.
基于自适应容积卡尔曼滤波的主动配电网状态估计
State Estimation of Active Distribution Network Based on ACKF
An effective state estimation algorithm which provides a precondition for ensuring a safe, stable, and economic operation of the power system. Aiming at the shortcomings of the traditional unscented Kalman filter (UKF), such as the difficult question of choosing parameter, less flexibility and filter degradation of high order system. The cubature Kalman filter (CKF) with better numerical stability is introduced into distribution network dynamic state estimation. Compared with the improved adaptive unscented Kalman filter (AUKF) the simulation which show that CKF algorithm has higher filtering accuracy and better numerical stability than the AUKF algorithm. However, When the system load is abrupt, the filtering accuracy decreases. Therefore, in order to improve the estimation performance, an adaptive cubature Kalman filter (ACKF) algorithm is proposed. The simulation analysis is carried out in three-phase unbalanced distribution network which show that the AUKF algorithm has higher filtering accuracy and better numerical stability than the CKF algorithm.
