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An Improved Stability Criterion for Load Frequency Control of Power Systems with Time-Varying Delays

Author

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  • Bi-Ying Chen

    (School of Automation, China University of Geosciences, Wuhan 430074, China
    The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China)

  • Xing-Chen Shangguan

    (School of Automation, China University of Geosciences, Wuhan 430074, China
    The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China)

  • Li Jin

    (School of Automation, China University of Geosciences, Wuhan 430074, China
    The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China)

  • Dan-Yun Li

    (School of Automation, China University of Geosciences, Wuhan 430074, China
    The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China)

Abstract

This paper aims at developing a novel stability criterion to access the influence of the time-varying delay on the stability of power systems equipped with a proportional-integral (PI)-based load frequency control (LFC). The model of the LFC scheme considering time-varying communication delays is established at first. Then, an improved stability condition related to the information of delay bounds is deduced by constructing an augmented Lyapunov–Krasovski functional and using a matrix inequality, and it is expressed as linear matrix inequalities (LMIs) for easily checking. Finally, case studies for one-area and two-area LFC systems are carried out to show the relationship between delay margins ensuring the stability and the PI gains of the LFC, and also verify the superiority of proposed stability criterion compared with the previous ones.

Suggested Citation

  • Bi-Ying Chen & Xing-Chen Shangguan & Li Jin & Dan-Yun Li, 2020. "An Improved Stability Criterion for Load Frequency Control of Power Systems with Time-Varying Delays," Energies, MDPI, vol. 13(8), pages 1-14, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:2101-:d:349338
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    References listed on IDEAS

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    1. Hassan Haes Alhelou & Mohamad-Esmail Hamedani-Golshan & Reza Zamani & Ehsan Heydarian-Forushani & Pierluigi Siano, 2018. "Challenges and Opportunities of Load Frequency Control in Conventional, Modern and Future Smart Power Systems: A Comprehensive Review," Energies, MDPI, vol. 11(10), pages 1-35, September.
    2. Ashraf Khalil & Ang Swee Peng, 2018. "An Accurate Method for Delay Margin Computation for Power System Stability," Energies, MDPI, vol. 11(12), pages 1-22, December.
    3. Ashraf Khalil & Ang Swee Peng, 2018. "A New Method for Computing the Delay Margin for the Stability of Load Frequency Control Systems," Energies, MDPI, vol. 11(12), pages 1-18, December.
    4. Shang-Guan, Xingchen & He, Yong & Zhang, Chuanke & Jiang, Lin & Spencer, Joseph William & Wu, Min, 2020. "Sampled-data based discrete and fast load frequency control for power systems with wind power," Applied Energy, Elsevier, vol. 259(C).
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    Citations

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    Cited by:

    1. Pranta Das & Shuvra Prokash Biswas & Sudipto Mondal & Md Rabiul Islam, 2023. "Frequency Fluctuation Mitigation in a Single-Area Power System Using LQR-Based Proportional Damping Compensator," Energies, MDPI, vol. 16(12), pages 1-18, June.
    2. Sadeq D. Al-Majidi & Mohammed Kh. AL-Nussairi & Ali Jasim Mohammed & Adel Manaa Dakhil & Maysam F. Abbod & Hamed S. Al-Raweshidy, 2022. "Design of a Load Frequency Controller Based on an Optimal Neural Network," Energies, MDPI, vol. 15(17), pages 1-28, August.
    3. Wenxi Feng & Yanshan Xie & Fei Luo & Xianyong Zhang & Wenyong Duan, 2021. "Enhanced Stability Criteria of Network-Based Load Frequency Control of Power Systems with Time-Varying Delays," Energies, MDPI, vol. 14(18), pages 1-22, September.
    4. Sadeq D. Al-Majidi & Hisham Dawood Salman Altai & Mohammed H. Lazim & Mohammed Kh. Al-Nussairi & Maysam F. Abbod & Hamed S. Al-Raweshidy, 2023. "Bacterial Foraging Algorithm for a Neural Network Learning Improvement in an Automatic Generation Controller," Energies, MDPI, vol. 16(6), pages 1-19, March.
    5. Phuong Nam Dao & Hong Quang Nguyen & Minh-Duc Ngo & Seon-Ju Ahn, 2020. "On Stability of Perturbed Nonlinear Switched Systems with Adaptive Reinforcement Learning," Energies, MDPI, vol. 13(19), pages 1-19, September.
    6. Ashraf Khalil & Dina Shona Laila, 2022. "An Accurate Method for Computing the Delay Margin in Load Frequency Control System with Gain and Phase Margins," Energies, MDPI, vol. 15(9), pages 1-21, May.
    7. Debanjan, Mukherjee & Karuna, Kalita, 2022. "An Overview of Renewable Energy Scenario in India and its Impact on Grid Inertia and Frequency Response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).

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