多采样周期混合量测环境下的主动配电网状态估计方法

WANG Shaofang

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多采样周期混合量测环境下的主动配电网状态估计方法

更新时间：2025-08-13

- 多采样周期混合量测环境下的主动配电网状态估计方法
- Automation of Electric Power Systems Vol. 40, Issue 19, Pages: 30-36(2016)
- 作者机构：
  
  中国电力科学研究院,北京市,100192
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016
- 稿件说明：
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WANG Shaofang. [J]. Automation of electric power systems, 2016, 40(19): 30-36.
DOI：

WANG Shaofang. [J]. Automation of electric power systems, 2016, 40(19): 30-36. DOI：

摘要

针对主动配电网中远程终端单元(RTU)、相量测量单元(PMU)与高级量测体系(AMI)多采样周期量测数据长期共存的实际情况

提出了一种基于RTU

PMU

AMI混合量测的主动配电网状态估计混合算法。该混合算法由非线性静态状态估计、线性静态状态估计与线性动态状态估计3种算法组成。线性动态状态估计与线性静态状态估计利用PMU量测与RTU量测

实时跟踪系统注入节点有功功率与无功功率的变化

在非AMI量测的采集时刻

为非线性静态状态估计提供高精度的虚拟量测。所提算法缩短了非线性静态状态估计的计算周期

提高了非线性静态状态估计的精度

提升了对主动配电网运行状态的预测能力。通过算例仿真

验证了所提算法的有效性。

Abstract

According to the fact of long-term coexistence of the remote terminal unit(RTU)

the phasor measurement unit(PMU)and the advanced metering infrastructure(AMI)in active distribution networks

this paper presents a hybrid algorithm of state estimation based on hybrid measurements of RTU

PMU and AMI

which consists of nonlinear static state estimation

linear static state estimation and linear dynamic state estimation. Linear dynamic state estimation and linear static state estimation track the changes in node injected active and reactive power by utilizing PMU and RTU measurements

which can provide highly accurate virtual measurements for nonlinear static state estimation in the absence of AMI measurements. The proposed algorithm can shorten the calculation cycle and improve the accuracy of nonlinear static state estimation

while enhancing the ability of state forecasting for active distribution networks. The effectiveness of the proposed algorithm is verified by a numerical simulation. This work is supported by National High Technology Research and Development Program of China(863 Program)(No. 2014AA051901)

National Natural Science Foundation of China(No. 51261130472)and State Grid Corporation of China.

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