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Sampled-data based discrete and fast load frequency control for power systems with wind power

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  • Shang-Guan, Xingchen
  • He, Yong
  • Zhang, Chuanke
  • Jiang, Lin
  • Spencer, Joseph William
  • Wu, Min

Abstract

Load frequency control employs communication networks to transmit measurements and control signals. The controller is usually designed in continuous-mode and discretized in implementation with a large sampling period, which may result in a degraded dynamic performance or even cause system instability. On the other hand, high penetration of wind power reduces the inertia of the power system, leading to a faster frequency response and larger frequency deviation after a contingency, and desires a fast load frequency control. Therefore, this paper presents a discrete-mode load frequency control scheme considering a large sampling period of control/measurement signals via sampled-data control, and introduces an exponential decay rate as a new performance index to guide a design of load frequency control scheme with desired faster frequency response. The proposed scheme is evaluated on a one-area power system, a traditional two-area power system with wind power and a deregulated three-area power system with wind power. Using the proposed scheme and the state-of-the-art schemes, the frequency response performance and the tolerance to sampling period of power systems are analyzed. The results demonstrate that the proposed control scheme can ensure the stable operation of the system under a larger sampling period so as to reduce the communication network burden. Also, the results show that the controller designed by a large exponential decay rate can provide a fast frequency response to alleviate the impact of the system’s frequency response due to the high penetration of wind power.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s0306261919318896
    DOI: 10.1016/j.apenergy.2019.114202
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    References listed on IDEAS

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    Cited by:

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    7. 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.
    8. Liu, Xingyue & Shi, Kaibo & Cheng, Jun & Wen, Shiping & Liu, Yajuan, 2023. "Adaptive memory-based event-triggering resilient LFC for power system under DoS attack," Applied Mathematics and Computation, Elsevier, vol. 451(C).
    9. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    10. Mishra, Dillip Kumar & Ray, Prakash Kumar & Li, Li & Zhang, Jiangfeng & Hossain, M.J. & Mohanty, Asit, 2022. "Resilient control based frequency regulation scheme of isolated microgrids considering cyber attack and parameter uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    11. Hisham M. Soliman & Farag A. El-Sheikhi & Ehab H. E. Bayoumi & Michele De Santis, 2022. "Ellipsoidal Design of Robust Stabilization for Markov Jump Power Systems under Normal and Contingency Conditions," Energies, MDPI, vol. 15(19), pages 1-16, October.
    12. Xu, Luo & Guo, Qinglai & He, Guannan & Jia, Shuyu & Sun, Hongbin, 2022. "Novel properties of heterogeneous delay in inverter-based cyber–physical microgrids under fully distributed control," Applied Energy, Elsevier, vol. 306(PB).
    13. Chen, Chunyu & Cui, Mingjian & Fang, Xin & Ren, Bixing & Chen, Yang, 2020. "Load altering attack-tolerant defense strategy for load frequency control system," Applied Energy, Elsevier, vol. 280(C).
    14. Abdul Latif & S. M. Suhail Hussain & Dulal Chandra Das & Taha Selim Ustun, 2021. "Design and Implementation of Maiden Dual-Level Controller for Ameliorating Frequency Control in a Hybrid Microgrid," Energies, MDPI, vol. 14(9), pages 1-15, April.
    15. Oshnoei, Soroush & Aghamohammadi, Mohammad Reza & Oshnoei, Siavash & Sahoo, Subham & Fathollahi, Arman & Khooban, Mohammad Hasan, 2023. "A novel virtual inertia control strategy for frequency regulation of islanded microgrid using two-layer multiple model predictive control," Applied Energy, Elsevier, vol. 343(C).
    16. Huo, Zhihong & Wang, Bing, 2023. "Distributed resilient multi-event cooperative triggered mechanism based discrete sliding-mode control for wind-integrated power systems under denial of service attacks," Applied Energy, Elsevier, vol. 333(C).
    17. Shangguan, Xing-Chen & He, Yong & Zhang, Chuan-Ke & Jiang, Lin & Wu, Min, 2022. "Load frequency control of time-delayed power system based on event-triggered communication scheme," Applied Energy, Elsevier, vol. 308(C).
    18. Yang, Jin & Zhong, Qishui & Ghias, Amer M.Y.M. & Dong, Zhao Yang & Shi, Kaibo & Yu, Yongbin, 2023. "Distributed fault-tolerant PI load frequency control for power system under stochastic event-triggered scheme," Applied Energy, Elsevier, vol. 351(C).
    19. Xu, Luo & Guo, Qinglai & He, Guannan & Sun, Hongbin, 2021. "The impact of synchronous distributed control period on inverter-based cyber–physical microgrids stability with time delay," Applied Energy, Elsevier, vol. 301(C).
    20. Han, Ji & Miao, Shihong & Chen, Zhe & Liu, Zhou & Li, Yaowang & Yang, Weichen & Liu, Ziwen, 2021. "Multi-View clustering and discrete consensus based tri-level coordinated control of wind farm and adiabatic compressed air energy storage for providing frequency regulation service," Applied Energy, Elsevier, vol. 304(C).

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