加权最小二乘状态估计量测权值计算的实用方法

GONG Chengming

您当前的位置：

首页 >

文章列表页 >

加权最小二乘状态估计量测权值计算的实用方法

更新时间：2025-08-13

- 加权最小二乘状态估计量测权值计算的实用方法
- Automation of Electric Power Systems Vol. 40, Issue 11, Pages: 143-147(2016)
- 作者机构：
  
  国电南瑞科技股份有限公司,江苏省,南京市,211106
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016
- 稿件说明：
移动端阅览
GONG Chengming. [J]. Automation of electric power systems, 2016, 40(11): 143-147.
DOI：

GONG Chengming. [J]. Automation of electric power systems, 2016, 40(11): 143-147. DOI：

摘要

分析了实际系统中直接影响加权最小二乘状态估计量测权值的因素

基于量测精度等级及满量程提出了设置量测权值的实用化方法

展示了实际系统中典型量测权值的标幺化数值

可以看出不同电压等级功率量测权值的差别以及电压幅值量测和功率量测权值之间的关系。使用文中方法计算得到的量测权值能更准确地反映量测精度

从而能够提高状态估计结果的准确性

模拟算例和实际工程应用验证了所述方法的有效性。文中还分析说明了计算两种派生量测权值的方法以及选取零注入量测权值的原则。

Abstract

This paper analyzes the affecting factors of measurement weight and addresses a practical way to calculate the default weights based on the information of measurement precision grade and full scale. Typical per-unit weight values from actual systems are illustrated to show the great difference between power measurement at different voltage levels and the relationship between power measurement and voltage measurement. As the proposed method is based on available information that can well represent the precision of measurement

more appropriate weights can be generated and hence higher state estimation precision. The effectiveness of the proposed method is verified by simulated case studies. Furthermore

the method for calculating the weights of two kinds of combined measurement and the principles of setting proper weights for zero-injection measurement are briefly treated.

关键词

Keywords

references

Views

3373

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Distribution Network Restoration Decision Considering Risk of State Estimation Error in Restoration Process

Time-varying Virtual Inertia and State Estimation of Grid-following Converter Based on Maximum Correntropy Criterion and Polynomial Chaos Kalman Filter

Forecasting-aided State Estimation for Distribution Networks Based on Event-triggering Encryption

Related Author

ZHU Kaiyu

LIN Jikeng

HAO Lili

KAN Yizhou

XUE Yusheng

XUE Feng

WANG Yuhong

WANG Xueke

Related Institution

College of Electronics and Information Engineering, Tongji University

College of Electrical Engineering & Control Science, Nanjing Tech University

State Grid Electric Power Research Institute (NARI Group Corporation)

School of Electrical Engineering, Sichuan University

State Grid Urumqi Power Supply Company

⁰