智能监测系统下的线性电网状态估计研究  

Research on state estimation of linear grid based on intelligent monitoring system

作　　者：张晓兰 谷永刚 张少强 李庚 杨传凯 王帅 Zhang Xiaolan;Gu Yonggang;Zhang Shaoqiang;Li Geng;Yang Chuankai;Wang Shuai(State Grid Shaanxi Electric Power Research Institute,Xi’an 710199,China;State Grid Shaanxi Electric Power Company,Xi’an 710199,China;State Grid Shanxi Electric Power Company Electric Power Research Institute,Taiyuan 030001,China)

机构地区：[1]国网陕西省电力公司电力科学研究院,西安710199 [2]国网陕西省电力公司,西安710199 [3]国网山西省电力公司电力科学研究院,太原030001

出　　处：《电测与仪表》2021年第10期112-117,共6页Electrical Measurement & Instrumentation

基　　金：国家电网有限公司科技研发项目(520530180015)。

摘　　要：针对传统电力监测系统状态估计(SE)的非线性导致的测量数据错误、不确定性和准确率低等问题。提出了一种改进的RTU线性状态估计模型。该模型在智能监测系统下的状态估计器内并入PMU和RTU测量,对其进行了算法改进,使整个SE问题呈线性,提升了电力监测系统状态估计准确性。实验中将传统的RTU和改进的RTU线性状态估计模型依次分配给系统总线4,对噪声变量和估计误差进行了概率状态估计。结果表明,改进的RTU线性状态估计模型整体性能优于传统的非线性模型,计算速度快、节约内存,提升了整个SE的准确性。该模型为未来大型电力智能检测系统进行电网状态估计提供有力的理论与技术支持。Measurement data errors,certaintes,low accuracy asnd other real-world moblems causeil by non and other real-world problems caused by nonlinearity of traditional power monitoring system state estimation(SE)an improved RTU.In this paper,an improved RTU linear state estimation model is proposed.The model incorporates PMU and RTU measurements in the state estimator under the intelligent monitoring system,which makes the whole SE problem linear and improves its estimation accuracy.In the experiment,the traditional RTU and the improved RTU linear state estimation model are sequentially assigned to the system bus 4,and the probability state estimation of the noise variable and the estimation error is performed.The results show that the improved RTU linear state estimation model has better overall performance than the traditional nonlinear model,and the calculation speed is fast,the memory is saved,and the accuracy of the whole SE is improved.This model provides powerful theoretical and technical support for future large-scale power intelligent detection systems for grid state estimation.

关 键 词：电力监测系统 状态估计 PMU 线性RTU 概率状态估计 

分 类 号：TM732[电气工程—电力系统及自动化]