Distributed Finite-Time Cooperative Economic Dispatch Strategy for Smart Grid under DOS Attack

Author:

Song Zhenghang1,Wang Xiang1,Wei Baoze2,Shan Zhengyu3,Guan Peiyuan3ORCID

Affiliation:

1. Department of Information Science and Engineering, Northeastern University, Shenyang 110819, China

2. Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark

3. Department of Informatics, University of Oslo, 0373 Oslo, Norway

Abstract

This paper proposes an energy management strategy that can resist DOS attacks for solving the Economic Dispatch Problem (EDP) of the smart grid. We use the concept of energy agent, which acts as a hub for the smart grid, and each EA is an integrated energy unit that converts, stores, and utilizes its local energy resources. This approach takes into account the coupling relationship between energy agents (EA) and utilizes the Lyapunov function technique to achieve finite-time solutions for optimization problems. We incorporate strategies to resist DOS attacks when analyzing finite-time convergence using the Lyapunov technique. Based on this, a finite convergence time related to DOS attack time is derived. The integral sliding mode control strategy is adopted and the Lyapunov method is used to analyze it, so that the algorithm can resist DOS attacks and resist external disturbances. Through theoretical analysis, it is shown that the strategy is capable of converging to the global optimal solution in finite time even if it is attacked by DOS. We conducted case studies of six-EA and ten-EA systems to verify the effectiveness of this strategy. The proposed strategy has potential for deployment in distributed energy management systems that require resilience against DOS attacks.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Distributed Entire State Estimation and Consensus Control for Lipschitz Nonlinear Multi-Agent Systems;2024 3rd Conference on Fully Actuated System Theory and Applications (FASTA);2024-05-10

2. Model-Based Reinforcement Learning Method for Microgrid Optimization Scheduling;Sustainability;2023-06-07

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