Dynamic event‐triggered‐based adaptive frequency control of microgrids under cyber‐attacks via adaptive dynamic programming

Zemeng Mi; Hanguang Su; Qiuye Sun; Zhongyang Ming

doi:10.1049/rpg2.13187

journal article Open Access Jan 01, 2025

Dynamic event‐triggered‐based adaptive frequency control of microgrids under cyber‐attacks via adaptive dynamic programming

Zemeng Mi Hanguang Su

Qiuye Sun

Zhongyang Ming

IET Renewable Power Generation Vol. 19 No. 1 · Institution of Engineering and Technology (IET)

View at Publisher Save 10.1049/rpg2.13187

Abstract

Abstract
The increasing penetration of renewable energy sources (RES) and the development of the cyber‐physical microgrids (CPMs) make greater demands for frequency control of microgrids. The common approach for frequency control is controlling the micro‐turbine to compensate for frequency deviations, with energy storage systems serving as an auxiliary approach. This article proposes an online adaptive frequency control method to control the governor and energy storage to realize the frequency recovery of microgrid, subject to the external unknown disturbances caused by wind turbine, power load and false data injection (FDI) attacks. First, the non‐zero sum (NZS) games of the considered system are modeled in this work, where the unknown disturbances are also taken into account. For the sake of estimating the unknown disturbances, a disturbance observer (DOB) for the microgrid system is introduced. Then, on the basis of the estimated results of the applied DOB, the disturbance compensation input is derived to offset the interference of the unknown disturbance. Meanwhile, the adaptive dynamic programming (ADP) approach is employed to derive the adaptive optimal control input for the NZS games of microgrid system. Besides, the dynamic event‐triggered (DET) control is introduced, reducing the occupation of computing resources. By utilizing the Lyapunov's method, the stability of the closed‐loop system, the convergence of the estimation weight, the estimation disturbances and the system state are guaranteed. The effectiveness of the proposed method is ultimately verified by the simulation results.

Topics

No keywords indexed for this article. Browse by subject →

References

43

[1]

10.1109/tii.2024.3393569

[2]

10.1109/jiot.2024.3450725

[3]

10.1109/tii.2024.3390595

[4]

10.1109/tii.2023.3241682

[5]

10.1109/tii.2024.3397400

[6]

10.1016/j.apenergy.2024.124780

[7]

10.1109/icde53745.2022.00225

[8]

10.14778/3384345.3384353

[9]

10.14778/3450980.3450987

[10]

10.1016/j.energy.2024.131809

[11]

10.1109/tce.2023.3241684

[12]

10.1109/tsg.2019.2942770

[13]

10.1016/s0927-0248(02)00196-4

[14]

Cooperative Optimal Control of Battery Energy Storage System Under Wind Uncertainties in a Microgrid

Tianqiao Zhao, Zhengtao Ding

IEEE Transactions on Power Systems 10.1109/tpwrs.2017.2741672

[15]

10.1109/tste.2017.2754522

[16]

10.1016/j.isatra.2019.01.036

[17]

10.1080/15599612.2020.1828516

[18]

10.1016/j.automatica.2007.10.011

[19]

10.1109/tnnls.2019.2959005

[20]

10.1109/tcyb.2022.3232599

[21]

Liu F. "Dynamic self‐triggered adaptive control for voltage regulation of DC microgrids" IEEE Trans. Circuits Syst. II Exp. Briefs (2024)

[22]

Su H. "ADP‐based self‐triggered optimal control of active loads in DC microgrid" IEEE Trans. Circuits Syst. II Exp. Briefs (2024)

[23]

10.1109/tnnls.2021.3057438

[24]

10.1109/tcsii.2022.3162239

[25]

10.1109/tii.2021.3108876

[26]

10.1016/j.jfranklin.2018.01.005

[27]

10.1109/tfuzz.2023.3245294

[28]

10.1109/tste.2018.2878470

[29]

10.1109/tpwrs.2016.2537984

[30]

10.1109/tii.2018.2862436

[31]

Dynamic Triggering Mechanisms for Event-Triggered Control

Antoine Girard

IEEE Transactions on Automatic Control 10.1109/tac.2014.2366855

[32]

10.1109/tsg.2020.3005179

[33]

10.1109/tec.2010.2089688

[34]

10.1109/tie.2020.2975494

[35]

10.1016/j.neucom.2020.01.082

[36]

10.1109/41.857974

[37]

Disturbance-Observer-Based Control and Related Methods—An Overview

Wen-Hua Chen, Jun Yang, Lei Guo et al.

IEEE Transactions on Industrial Electronics 10.1109/tie.2015.2478397

[38]

10.1109/tcyb.2022.3175650

[39]

10.1109/tcyb.2016.2611613

[40]

10.1109/tcyb.2015.2488680

[41]

Online actor–critic algorithm to solve the continuous-time infinite horizon optimal control problem

Kyriakos G. Vamvoudakis, Frank L. Lewis

Automatica 10.1016/j.automatica.2010.02.018

[42]

10.1016/j.neucom.2019.07.029

[43]

10.1109/tcyb.2020.2972748

Cited By

6

Scaling and integrating digital twin applications for battery energy storage systems from building to city

Hyuna Kang, Dahyun Jung · 2026

Renewable and Sustainable Energy Re...

Metrics

6

Citations

43

References

Details

Published: Jan 01, 2025
Vol/Issue: 19(1)
License: View

Authors

Z

Zemeng Mi

School of Information Science and Engineering Northeastern University Shenyang Liaoning China

H

Hanguang Su

School of Information Science and Engineering Northeastern University Shenyang Liaoning China

Q

Qiuye Sun

School of Information Science and Engineering Northeastern University Shenyang Liaoning China

Z

Zhongyang Ming

School of Information Science and Engineering Northeastern University Shenyang Liaoning China

Funding

National Natural Science Foundation of China Award: 62373091

Fundamental Research Funds for the Central Universities Award: N2104016

China Postdoctoral Science Foundation Award: GZC20240227

National Key Research and Development Program of China Award: 2018YFA0702200

Natural Science Foundation of Liaoning Province Award: 2023‐MSBA‐082

Natural Science Foundation of Shandong Province Award: ZR2024QF276

Cite This Article

Zemeng Mi, Hanguang Su, Qiuye Sun, et al. (2025). Dynamic event‐triggered‐based adaptive frequency control of microgrids under cyber‐attacks via adaptive dynamic programming. IET Renewable Power Generation, 19(1). https://doi.org/10.1049/rpg2.13187

Dynamic event‐triggered‐based adaptive frequency control of microgrids under cyber‐attacks via adaptive dynamic programming

You May Also Like