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Distributed cooperative automatic generation control and multi-event triggered mechanisms co-design for networked wind-integrated power systems

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  • Huo, Zhihong
  • Xu, Chang

Abstract

The participation of wind energy brings new challenges to the networked power systems. Now, more network nodes compete for limited communication resources. Considering the utilization efficiency of network transmission resources, a novel multi-event triggered mechanisms based distributed cooperative automatic generation control scheme is investigated for networked wind-integrated power systems (NWIPSs). The multi-event triggered mechanisms based distributed wind-integrated power systems modeling method is proposed. By utilizing the Lyapunov-Krasovskii functional method, the sufficient conditions for system asymptotical stability are obtained. Concerning the previous event-triggered method the proposed multi-event triggered method widespread considered the coupling relationship between interconnected subsystems and make full use of each subsystem state information. The numerical example shows that the proposed scheme is feasible and the design of multi-event triggered mechanisms based distributed cooperative automatic generation controller provides less conservatism and stronger robustness.

Suggested Citation

  • Huo, Zhihong & Xu, Chang, 2022. "Distributed cooperative automatic generation control and multi-event triggered mechanisms co-design for networked wind-integrated power systems," Renewable Energy, Elsevier, vol. 193(C), pages 41-56.
    • Handle: RePEc:eee:renene:v:193:y:2022:i:c:p:41-56
    DOI: 10.1016/j.renene.2022.05.011
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    References listed on IDEAS

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    1. Ayman Alhejji & Alban Kuriqi & Jakub Jurasz & Farag K. Abo-Elyousr, 2021. "Energy Harvesting and Water Saving in Arid Regions via Solar PV Accommodation in Irrigation Canals," Energies, MDPI, vol. 14(9), pages 1-24, May.
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    Cited by:

    1. Hu, Wenyu & E, Jiaqiang & Zhang, Feng & Chen, Jingwei & Ma, Yinjie & Leng, Erwei, 2022. "Investigation on cooperative mechanism between convective wind energy harvesting and dust collection during vehicle driving on the highway," Energy, Elsevier, vol. 260(C).
    2. Zhao, Lulin & Yin, Linfei, 2024. "Knowledge-shareable adaptive deep dynamic programming for hierarchical generation control of distributed high-percentage renewable energy systems," Renewable Energy, Elsevier, vol. 228(C).

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