混合量测下序贯抗差状态估计算法研究  

Study for Sequential Robust State Estimation under Hybrid Measurements

作　　者：李波[1] 何星[1] 方兴其[1] 

机构地区：[1]上海交通大学自动化系系统控制与信息处理教育部重点实验室,上海200240

出　　处：《控制工程》2013年第6期1084-1087,1093,共5页Control Engineering of China

基　　金：国家自然科学基金(61004088);航空科学基金(20100157001)

摘　　要：混合量测下电力系统动态状态估计算法,目前主要假设量测信息在同一时间获得,且很少考虑量测异常值对状态估计的影响。针对以上不足,充分利用混合量测的特性,在分析监控及数据采集系统(SCADA)数据取用时间窗口的基础上,提出了混合量测下序贯抗差状态估计算法。该算法首先序贯入同一时间断面上的同步相量测量单元(PMU)量测值,然后依次序贯入陆续到来的SCADA量测值。初步融合完成后计算融合代价函数,如果超过设定阀值,则增广量测矩阵形成混合量测集,通过扩展卡尔曼滤波(EKF)进行抗差状态估计。该算法能够提高估计中心的利用率以及状态估计的实时性和精度,降低量测异常值对状态估计的影响。最后在IEEE14节点系统上进行了仿真,验证了该算法的有效性和优越性。Most power system dynamic state estimation algorithms under hybrid measurements assume that the information can be avail able at the same time and rarely consider the impact of bad data on state estimation. Aiming at the problems above and taking full ad vantage of hybrid measurements, a sequential robust dynamic state estimation is proposed based on the analysis of the SCADA estimation time window of the mixed measure system. Firstly, the algorithm fusions the phasor measurement unit （ PMU ） measurements sam piing at the same time and then the supervisory control and data acquisition （SCADA） measurements are taken into estimation in se quential of arrival time. Then the cost function is calculated. A set of SCADA/PMU measurements is formed and used for state estima tion via extended Kalman filter （EKF） if the cost funetion exceeds a threshold The algorithm can make good use of utilization of the es timation center, reduce the impact of measurement outliers on the state estimation and improve state estimation real time and accura cy. Finally, simulations on an IEEE 14 bus test system demonstrate the effectiveness and superiority of the proposed algorithm.

关 键 词：混合量测 量测时延 序贯抗差状态估计 

分 类 号：TP27[自动化与计算机技术—检测技术与自动化装置]