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Distributed Nash Equilibrium Seeking of Residential Energy Grids over Unreliable Communication Networks Using Predictive Control | ||
| AUT Journal of Modeling and Simulation | ||
| دوره 55، شماره 1، شهریور 2023، صفحه 139-154 اصل مقاله (1.38 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/miscj.2023.22098.5313 | ||
| نویسندگان | ||
| Hamid Reza Babaei Ghazvini؛ Mahsa Ghavami؛ Mohammad Haeri* | ||
| Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran | ||
| چکیده | ||
| In this article, we manage the energy consumption of numerous intelligent homes and charging stations including several electric vehicles in real-time using a computationally efficient predictive controller. The studied scenario is made up of a couple of primary layers. At the low level of the hierarchical framework, users are clustered into different groups based on their vehicles’ departure times. Meanwhile, the energy consumption of subordinate users is controlled by multiple aggregators, interaction among which is modeled as an aggregative game. The high-level interactive and distributed control problem can be solved by a predictive controller, wherein the terminal constraints related to the reference energy of each cluster’s storage capacity are transferred to the end of the prediction horizon. Additionally, each aggregator can only exchange local data with some neighboring aggregators through an untrustable communication network. As a result of denial of service attacks on the aggregators' network, the strong connectivity of the communication graph may be directly destroyed, leading to performance degradation. To address such an issue, each aggregator reconstructs the attacked information of its neighbors using a linear combination of received data in the last two iterations. Furthermore, a time-of-use pricing tariff whose value is small for faithful households is investigated so that convergence time remains unaltered. Practical examples are simulated to assess the usefulness of the proposed iterative algorithm. | ||
| کلیدواژه‌ها | ||
| Distributed Nash equilibrium seeking algorithm؛ noncooperative games؛ residential households؛ denial of service attacks؛ model predictive control | ||
| مراجع | ||
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[1] Zhao, J Guo, X. Luo, C.S. Lai, P. Yang, L.L. Lai, P. Li, J.M. Guerrero, and M. Shahidehpour, “Distributed robust model predictive control-based energy management strategy for islanded multi-micro-grids considering uncertainty,” IEEE Transactions on Smart Grid, vol. 13, pp. 2107-2120, May 2022.
[2] H. Farzaneh, M. Shokri, H. Kebriaei, and F. Aminifar, “Robust energy management of residential nano-grids via decentralized mean field control,” IEEE Transactions on Sustainable Energy, vol. 11, no. 3, pp. 1995-2002, 2020.
[3] M.A. Tajeddini and H. Kebriaei, “A mean-field game method for decentralized charging coordination of a large population of plug-in electric vehicle,” IEEE Systems Journal, vol. 13, no. 1, pp. 854-863, 2019.
[4] H. Kebriaei, S.J. Sadati-Savadkoohi, M. Shokri, and S. Grammatico, “Multi-population aggregative games: equilibrium seeking via mean-field control and consensus,” IEEE Transactions on Automatic Control, vol. 66, no. 12, pp. 6011-6016, Dec. 2021.
[5] Z.A. Pan, T. Yu, L.P. Chen, B. Yang, B. Wang, and W.X. Guo, “Real-time stochastic optimal scheduling of large-scale electric vehicle: A multidimensional approximate dynamic programming approach,” International Journal of Electrical Power and Energy Systems, vol. 116, 105542, 2020.
[6] M. Bianchi, G. Belgioioso, and S. Grammatico, “Fast generalized Nash equilibrium seeking under partial-decision information,” Automatica, vol. 136, 110080, Feb. 2022.
[7] G. Belgioioso and S. Grammatico, “Semi-decentralized generalized Nash equilibrium seeking in monotone aggregative games,” IEEE Transactions on Automatic Control, vol. 68, no. 1, pp. 140-155, Dec. 2021.
[8] G. Wu, C. Yi, H. Xiao, Q. Wu, L. Zeng, Q. Yan, and M. Zhang, “Multi-objective optimization of integrated energy systems considering renewable energy uncertainty and electric vehicles,” IEEE Transactions on Smart Grid, March 2023, doi: 10.1109/TSG.2023.3250722.
[9] A. Zhou, M. Yang, T. Wu, and L. Yang, “Distributionally robust energy management for islanded micro-grids with variable moment information: an MISOCP approach,” IEEE Transactions on Smart Grid, Jan. 2023, doi: 10.1109/TSG.2023.3236019.
[10] H.R. Babaei Ghazvini and M. Haeri, "Byzantine agents’ detection in distributed Nash equilibrium seeking algorithms using an adaptive event-triggered scheme," IEEE Systems Journal, May 2023, doi: 10.1109/JSYST.2023.3267160.
[11] A. Parisio, E. Rikos, and L. Glielmo, “A model predictive control approach to micro-grid operation optimization,” IEEE Transactions on Control Systems Technology, vol. 22, no. 5, pp. 1813- 1827, Sep. 2014.
[12] A. Parisio, C. Wiezorek, T. Kyntäjä, J. Elo, K. Strunz, and K.H. Johansson, “Cooperative MPC-based energy management for networked micro-grids,” IEEE Transactions on Smart Grid, vol. 8, no. 6, pp. 3066-3074, Nov. 2017.
[13] V. Casagrande, I. Prodan, S.K. Spurgeon, and F. Boem, “Resilient distributed MPC algorithm for micro-grid energy management under uncertainties,” in 2022 European Control Conference (ECC), July 2022.
[14] A. Joshi, H. Kebriaei, V. Marini, and L. Glielmo, “Decentralized control of residential energy storage system for community peak shaving: A constrained aggregative game,” IEEE Madrid PowerTech Conference, Madrid, Spain, July 2021.
[15] A. Karimi and M. Haeri, “Game theory meets distributed model predictive control in vehicle-to-grid systems,” 2019 11th International Conference on Electrical and Electronics Engineering (ELECO), pp. 764-768, 2019.
[16] S. Tan, J.M. Guerrero, P. Xie, R. Han, and J.C. Vasquez, “Brief survey on attack detection methods for cyber-physical systems,” IEEE Systems Journal, vol. 14, no. 4, pp. 5329-5339, May 2020.
[17] R.V. Yohanandhan, R.M. Elavarasan, R. Pugazhendhi, M. Premkumar, L. Mihet-Popa, and V. Terzija, “A holistic review on Cyber-Physical Power System (CPPS) testbeds for secure and sustainable electric power grid – Part – I: Background on CPPS and necessity of CPPS testbeds,” International Journal of Electrical Power & Energy Systems, vol. 136, 107718, March 2022.
[18] Q. Meng, X. Nian, Y. Chen, and Z. Chen “Attack-resilient distributed Nash equilibrium seeking of uncertain multiagent systems over unreliable communication networks,” IEEE Transactions on Neural Networks and Learning Systems, pp. 1-15, Oct. 2022.
[19] J. Xiao, L. Wang, Z. Qin, and S P. Bauer, “A resilience enhanced secondary control for ac micro-grids,” IEEE Transactions on Smart Grid, April 2023, doi: 10.1109/TSG.2023.3268245.
[20] P. Chen, S. Liu, B. Chen, and L. Yu, “Multi-agent reinforcement learning for decentralized resilient secondary control of energy storage systems against DoS attacks,” IEEE Transactions on Smart Grid, vol. 13, no. 3, May 2022.
[21] P. Ge, B. Chen, and F. Teng, “Cyber-resilient self-triggered distributed control of networked micro-grids against multi-layer DoS attacks,” IEEE Transactions on Smart Grid, Dec. 2022, doi: 10.1109/TSG.2022.3229486.
[22] B.M. Kaas, “Model Predictive Control Architecture Comparison for a Power Scheduling Electric Vehicle Aggregator,” Delft Center for Systems and Control, Delft University of Technology, Jun. 2017.
[23] F. Facchinei and J. S. Pang, “Nash equilibria: The variational approach,” D. P. Palomar and Y. C. Eldar, Eds. Cambridge University Press, 2009.
[24] P. Palma-Behnke, C. Benavides, F. Lanas, B. Severino, L. Reyes, J. Llanos, and D. Saez, “A micro-grid energy management system based on the rolling horizon strategy,” IEEE Transactions on Smart Grid, vol. 4, pp. 996-1006,2013. | ||
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آمار تعداد مشاهده مقاله: 355 تعداد دریافت فایل اصل مقاله: 264 |
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