摘要
针对机电暂态过程中发电机动态状态难以精确估计问题,提出一种基于连续-离散容积信息滤波的动态状态估计方法。首先建立能准确刻画发电机实际运行动态的连续-离散状态估计模型,然后利用1.5阶泰勒展开将随机微分方程转换为随机差分方程并根据三阶球半径容积规则对状态预测值进行精确计算,最后利用测量值对预测状态进行修正得到精确状态估计值。四机两区发电机系统的仿真结果表明,相较于传统发电机状态估计方法,文中方法不仅具有更高的估计精度、更强的鲁棒性和可接受的计算开销,而且具有易扩展于分布式电力系统状态估计的灵活性。
Aiming at the problem that it is difficult to accurately estimate the dynamic state of the generator in the electromechanical transient process,a dynamic state estimation method based on continuous-discrete cubature information filtering is proposed in this paper.First,a continuous-discrete state estimation model that can accurately describe the actual operating dynamics of the generator is established,then the stochastic differential equation(SDE)is converted into a stochastic difference equation by using 1.5th-order Taylor expansion,and the state prediction value is accurately calculated according to the third-order spherical radius cubature rule,and finally the predicted state is corrected by the measurements to obtain an accurate state estimate.The simulation results of the four-machine twozone generator system show that,compared with the traditional generator state estimation methods,the proposed method in this paper not only has higher estimation accuracy,stronger robustness and acceptable computational overhead,but also has the flexibility to be easily extended to distributed power system state estimation.
作者
王京景
张文奇
王艳辉
谢大为
彭伟
Wang Jingjing;Zhang Wenqi;Wang Yanhui;Xie Dawei;Peng Wei(State Grid Anhui Electric Power Company Ltd.,Hefei 230061,China;School of Electrical Engineering and Automation,Hefei University of Technology,Hefei 230009,China)
出处
《电子测量技术》
北大核心
2023年第14期109-116,共8页
Electronic Measurement Technology
基金
国网安徽省电力有限公司科技项目(5212002000AU)
国家自然科学基金(62103123)项目资助
关键词
发电机
状态估计
连续-离散系统
随机微分方程
容积信息滤波
generator
state estimation
continuous-discrete system
stochastic differential equation
cubature information filtering