基于WAMS的电力系统机电暂态过程动态状态估计  

Dynamic State Estimator Based on WAMS During Power System Transient Process

作　　者：秦晓辉[1] 毕天姝[1] 杨奇逊[1] 

机构地区：[1]电力系统保护与动态安全监控教育部重点实验室(华北电力大学),北京市昌平区102206

出　　处：《中国电机工程学报》2008年第7期19-25,共7页Proceedings of the CSEE

基　　金：国家自然科学基金项目(50607005);教育部科学技术研究重点项目(106052);新世纪优秀人才支持计划(NCET-05-0216);长江学者和创新团队发展计划(IRT0515)~~

摘　　要：广域同步测量系统(wide area measurement system,WAMS)作为一种量测手段,不可避免地会存在量测误差和坏数据。如果对WAMS量测数据不进行估计而直接应用,将有可能导致采取错误的控制策略,甚至恶化系统状态,造成严重后果。针对该问题,根据WAMS实测数据,提出了一种电力系统动态过程中发电机状态变量估计的新方法。该方法将发电机转子运动方程与外部网络解耦,进而给出对WAMS实测功角轨迹进行估计的模型,提出了相应的坏数据检测和剔除方法以及整体算法流程。仿真结果表明该方法可以实时提供估计后的发电机状态信息,有效减小WAMS量测数据误差及坏数据的影响,为基于WAMS的各种动态应用与实时控制打下了基础。As a measurement tool, wide area measurement system （WAMS） has the measurement error and bad data unavoidably. If the raw data is applied directly, the unpredictable consequence will be resulted in. Aiming at this problem, a novel dynamic state estimator for generator state variables is proposed. The mathematical model and the flowchart of the algorithm are described. Bad data detection and elimination approach is given as well. The simulation results show that the proposed method can provide the estimated trajectories of the generators in real-time, which eliminates the impact of measurement error and bad data and gives the backbone for WAMS based dynamic applications and real-time control.

关 键 词：电力系统 发电机状态变量 动态状态估计 卡尔曼滤波 广域同步测量系统 

分 类 号：TM76[电气工程—电力系统及自动化]