Dynamic state estimation for integrated electricity-gas systems based on Kalman filter

Yanbo Chen; Yuan Yao; Yuzhang Lin; Xiaonan Yang

doi:10.17775/CSEEJPES.2020.02050

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Dynamic state estimation for integrated electricity-gas systems based on Kalman filter

Special Section Papers | 更新时间：2026-10-15

- Dynamic state estimation for integrated electricity-gas systems based on Kalman filter
- Dynamic state estimation for integrated electricity-gas systems based on Kalman filter
- 中国电机工程学会电力与能源系统学报(英文) 2022年8卷第1期页码：293-303
- 作者机构：
  
  1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University,Beijing,China
  2. School of Engineering, Xining University,Xining,China
  3. School of Electrical and Electronic Engineering, North China Electric Power University,Beijing,China
  4. Department of Electrical and Computer Engineering, University of Massachusetts, Lowell,MA,USA
  5. China Electric Power Research Institute,Beijing,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2020.02050
  中图分类号：
- 纸质出版：2022-01-01
- 稿件说明：
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Yanbo Chen, Yuan Yao, Yuzhang Lin, 等. Dynamic state estimation for integrated electricity-gas systems based on Kalman filter[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(1):293-303.

Yanbo Chen, Yuan Yao, Yuzhang Lin, et al. Dynamic state estimation for integrated electricity-gas systems based on Kalman filter[J]. CSEE Journal of Power and Energy Systems, 2022, 8(1): 293-303.
Yanbo Chen, Yuan Yao, Yuzhang Lin, 等. Dynamic state estimation for integrated electricity-gas systems based on Kalman filter[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(1):293-303. DOI： 10.17775/CSEEJPES.2020.02050.

Yanbo Chen, Yuan Yao, Yuzhang Lin, et al. Dynamic state estimation for integrated electricity-gas systems based on Kalman filter[J]. CSEE Journal of Power and Energy Systems, 2022, 8(1): 293-303. DOI： 10.17775/CSEEJPES.2020.02050.

摘要

Abstract

In recent years

integrated electricity-gas systems (IEGSs) have attracted widespread attention. The unified scheduling and control of the IEGS depends on high-precision operating data. To this end

it is necessary to establish an appropriate state estimation (SE) model for IEGS to filter the raw measured data. Considering that power systems and natural gas systems have different time scales and sampling periods

this paper proposes a dynamic state estimation (DSE) method based on a Kalman filter that can consider the dynamic characteristics of natural gas pipelines. First

the standardized state transition equations for the gas system are developed by applying the finite difference method to the partial differential equations (PDEs) of the gas system; then the DSE model for IEGS is formulated based on a Kalman filter; also

the measurements from the electricity system and the gas system with different sampling periods are fused to ensure the observability of DSE by using the interpolation method. The IEEE 39-bus electricity system and the 18-nodes Belgium gas system are integrated as the test systems. Simulation results verify the proposed method's accuracy and calculation efficiency.

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