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Interval State Estimation of Electricity-Gas Systems Considering Measurement Correlations

Author

Listed:
  • Yan Huang

    (School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China)

  • Lin Feng

    (School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China
    School of Innovation and Entrepreneurship, Dalian University of Technology, Dalian 116024, China)

Abstract

The popularization of electricity-gas systems leads to increasing demand for state management of systems. However, the existence of neglected measurement correlations brings uncertainties to the electricity-gas systems state estimation. In this paper, an interval state estimation method that considers measurement correlations existing in the electricity-gas systems is presented. We derive the linear measurement model for the electricity-gas systems through Taylor series expansion and estimate the measurement variance-covariance matrix with measurement correlations. The system parameter matrix and the measurement variance-covariance matrix containing measurement correlations are combined into an interval, and the interval state matrix considering measurement correlations is constructed. Then, the linear equations for the state estimation interval considering measurement correlations are established based on the measurement containing correlations and interval state matrix; as a result, the electricity-gas system state estimation model containing measurement correlations is established. In addition, a method for determining the range of state estimation intervals is proposed. Numerical tests on an integrated electricity-gas system comprising a 10-node natural gas network and IEEE 30-bus system indicate that the proposed approach has more advantages over the UT+KO approach in computation accuracy and computation efficiency.

Suggested Citation

  • Yan Huang & Lin Feng, 2024. "Interval State Estimation of Electricity-Gas Systems Considering Measurement Correlations," Energies, MDPI, vol. 17(3), pages 1-22, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:3:p:755-:d:1333758
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    References listed on IDEAS

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    1. Jiang, Yunpeng & Ren, Zhouyang & Yang, Xin & Li, Qiuyan & Xu, Yan, 2022. "A steady-state energy flow analysis method for integrated natural gas and power systems based on topology decoupling," Applied Energy, Elsevier, vol. 306(PA).
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