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A Fast Solution for the Lagrange Multiplier-Based Electric Power Network Parameter Error Identification Model

Author

Listed:
  • Ye Guo

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Wenchuan Wu

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Boming Zhang

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Hongbin Sun

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

Abstract

The Lagrange multiplier-based method is an effective network parameter error identification method. However, two full matrices with high-dimensions are involved in the calculation procedure; these create huge computational burdens for large-scale power systems. To solve this problem, a fast solution is proposed in this paper, where special treatment techniques for full matrices are used to dramatically improve the calculation efficiency. A practical parameter error identification program has been developed and used in many electric power control centers. In this paper, the results for test systems and on-site applications are given, which show that the proposed approach is very efficient.

Suggested Citation

  • Ye Guo & Wenchuan Wu & Boming Zhang & Hongbin Sun, 2014. "A Fast Solution for the Lagrange Multiplier-Based Electric Power Network Parameter Error Identification Model," Energies, MDPI, vol. 7(3), pages 1-12, March.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:3:p:1288-1299:d:33667
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    Cited by:

    1. Yu Shi & Yueting Hou & Yue Yu & Zhaoyang Jin & Mohamed A. Mohamed, 2023. "Robust Power System State Estimation Method Based on Generalized M-Estimation of Optimized Parameters Based on Sampling," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    2. Tao Jin & Fuliang Chu & Cong Ling & Daniel Legrand Mon Nzongo, 2015. "A Robust WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology," Energies, MDPI, vol. 8(4), pages 1-19, April.
    3. Wei-Tzer Huang & Kai-Chao Yao & Chun-Ching Wu & Yung-Ruei Chang & Yih-Der Lee & Yuan-Hsiang Ho, 2016. "A Three-Stage Optimal Approach for Power System Economic Dispatch Considering Microgrids," Energies, MDPI, vol. 9(11), pages 1-18, November.
    4. Tao Jin & Xueyu Shen, 2018. "A Mixed WLS Power System State Estimation Method Integrating a Wide-Area Measurement System and SCADA Technology," Energies, MDPI, vol. 11(2), pages 1-22, February.

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