Unmanned aerial vehicles versus smart grids

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
IET Smart Grid Pub Date : 2025-02-17 DOI:10.1049/stg2.70000
Alexis Pengfei Zhao, Shuangqi Li, Da Huo, Mohannad Alhazmi
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引用次数: 0

Abstract

The increasing threat of unmanned aerial vehicles (UAVs) to smart grid infrastructures poses critical challenges to energy systems security. This study examines smart grid vulnerabilities to UAV-based attacks and proposes a novel optimisation framework to enhance grid resilience. Employing a multi-objective optimisation approach using the Non-dominated Sorting Genetic Algorithm III (NSGA-III) and a game-theoretic Stackelberg model, the research captures the strategic interplay between UAV operators and grid defenders. Key contributions include the development of a multi-objective optimisation framework, integration of adversarial game theory, incorporation of dynamic environmental conditions, and generation of Pareto-optimal solutions for strategic defence planning. This research makes four pivotal contributions: (a) the design of a comprehensive multi-objective optimisation framework tailored for UAV strike optimisation, (b) the integration of game-theoretic principles to model adversarial behaviours, (c) the inclusion of dynamic environmental factors to improve solution robustness, and (d) the application of NSGA-III to generate trade-off solutions, equipping decision-makers with diverse strategies to enhance grid resilience. By addressing an urgent and timely challenge, this work offers practical guidance for fortifying smart grid infrastructures against emerging UAV threats in increasingly complex operational environments.

Abstract Image

无人驾驶飞行器vs智能电网
无人机对智能电网基础设施的威胁日益严重,对能源系统安全构成严峻挑战。本研究考察了智能电网对无人机攻击的脆弱性,并提出了一种新的优化框架来增强电网的弹性。采用非支配排序遗传算法III (NSGA-III)和博弈论Stackelberg模型的多目标优化方法,研究捕获了无人机操作员和网格防御者之间的战略相互作用。主要贡献包括多目标优化框架的发展,对抗性博弈论的整合,动态环境条件的结合,以及战略防御规划的帕累托最优解决方案的生成。本研究做出了四个关键贡献:(a)为无人机打击优化设计了一个全面的多目标优化框架,(b)整合博弈论原理来模拟对抗行为,(c)包含动态环境因素以提高解决方案的鲁棒性,以及(d)应用NSGA-III来生成权衡解决方案,为决策者提供多样化的策略以增强网格弹性。通过解决紧急和及时的挑战,这项工作为在日益复杂的作战环境中加强智能电网基础设施抵御新兴无人机威胁提供了实用指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
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