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Adaptive Wide-Area Damping Control Scheme for Smart Grids with Consideration of Signal Time Delay

Author

Listed:
  • Guowei Cai

    (School of Electrical Engineering, Northeast Dianli University, Jilin 132012, China)

  • Deyou Yang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Cheng Liu

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

Abstract

As an important part of the smart grid, a wide-area measurement system (WAMS) provides the key technical support for power system monitoring, protection and control. But 20 uncertainties in system parameters and signal transmission time delay could worsen the damping effect and deteriorate the system stability. In the presented study, the subspace system identification technique (SIT) is used to firstly derive a low-order linear model of a power system from the measurements. Then, a novel adaptive wide-area damping control scheme for online tuning of the wide-area damping controller (WADC) parameters using the residue method is proposed. In order to eliminate the effects of the time delay to the signal transmission, a simple and practical time delay compensation algorithm is proposed to compensate the time delay in each wide-area control signal. Detailed examples, inspired by the IEEE test system under various disturbance scenarios, have been used to verify the effectiveness of the proposed adaptive wide-area damping control scheme.

Suggested Citation

  • Guowei Cai & Deyou Yang & Cheng Liu, 2013. "Adaptive Wide-Area Damping Control Scheme for Smart Grids with Consideration of Signal Time Delay," Energies, MDPI, vol. 6(9), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:9:p:4841-4858:d:28809
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    Citations

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    Cited by:

    1. Tao Zhou & Zhong Chen & Siqi Bu & Haoran Tang & Yi Liu, 2018. "Eigen-Analysis Considering Time-Delay and Data-Loss of WAMS and ITS Application to WADC Design Based on Damping Torque Analysis," Energies, MDPI, vol. 11(11), pages 1-15, November.
    2. Kwan-Shik Shim & Seon-Ju Ahn & Sang-Yun Yun & Joon-Ho Choi, 2017. "Analysis of Low Frequency Oscillation Using the Multi-Interval Parameter Estimation Method on a Rolling Blackout in the KEPCO System," Energies, MDPI, vol. 10(4), pages 1-18, April.
    3. Francesco Bonavolontà & Luigi Pio Di Noia & Davide Lauria & Annalisa Liccardo & Salvatore Tessitore, 2019. "An Optimized HT-Based Method for the Analysis of Inter-Area Oscillations on Electrical Systems," Energies, MDPI, vol. 12(15), pages 1-22, July.
    4. Ziquan Liu & Wei Yao & Jinyu Wen, 2017. "Enhancement of Power System Stability Using a Novel Power System Stabilizer with Large Critical Gain," Energies, MDPI, vol. 10(4), pages 1-15, April.
    5. Kwan-Shik Shim & Seon-Ju Ahn & Joon-Ho Choi, 2017. "Synchronization of Low-Frequency Oscillation in Power Systems," Energies, MDPI, vol. 10(4), pages 1-11, April.

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