在集成了混合可再生储能技术的多微网中结合网络攻击识别进行协调控制和能源管理

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
IET Smart Grid Pub Date : 2024-02-05 DOI:10.1049/stg2.12158
H. Faraji, Reza Hemmati
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引用次数: 0

摘要

为协调控制电压-频率-惯性和同时识别两个微电网(MGs)中的多重网络攻击开发了一个综合模型。微电网集成了太阳能装置、风力涡轮机(WT)、超级电容器-电池混合动力装置和燃料电池。MG 在孤岛和联网状态下运行时都要进行建模和控制。在建议的方法中,设计了一个数据中心,收集、评估和匹配与太阳能、风能、混合超级电容器电池和燃料电池(FC)相关的所有电气和控制信号。数据中心包括以下模块:电压-频率控制、风电机组的惯性控制,以及识别频率、功率、功率/频率和电压方面的虚假数据注入(FDI)网络攻击。本文中用于识别 FDI 攻击的技术基于实时方法和在时域中进行的逻辑比较。这种方法可提供迅速而精确的检测,从而及时采取预防措施和战略应对措施。FDI 攻击发生后,实施的控制系统可有效地管理和调节电压和频率,使其保持在所需的水平,并有效地区分正常运行、故障状态和潜在的网络攻击。出于安全考虑,不健康的 MG 可以将其负载转移到健康的 MG 上。然后,健康的 MG 与外部电网连接,并由建议的控制系统检查同步条件。在 MATLAB-Simulink 软件中进行的非线性仿真结果证实,所提议的模型可成功运行和控制所有资源(即太阳能/风能/电池/FC),在各种负载条件下调节电压/频率,并识别 FDI 网络攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coordinated control and energy management combined with cyberattack identification in multi‐microgrid integrated with hybrid renewable‐storage
A comprehensive model is developed for coordinated control of voltage‐frequency‐inertia and identifying multiple cyberattacks simultaneously in two microgrids (MGs). The MGs are integrated with solar units, Wind turbine (WT), hybrid supercapacitor‐battery, and fuelcell. The MGs are modelled and controlled for operation under both an island and connected states. In the proposed method, a data centre is designed in which all the electrical and control signals related to the solar, wind, hybrid supercapacitor‐battery, and Fuel cell (FC) are collected, evaluated, and matched. The data centre comprises the following blocks: voltage‐frequency control, inertia control of WT, and identification of false data injection (FDI) cyberattacks on frequency, power, power/frequency, and voltage. The technique used in this article to identify FDI attacks is based on the real‐time method coupled with logical comparisons conducted in the time domain. This methodology provides prompt and precise detection, allowing for timely preventive measures and strategic responses. After FDI attacks occur, the implemented control system effectively manages and regulates the voltage and frequency at the desired levels, efficiently differentiating between ordinary functioning, faulty states, and potential cyber‐attacks. The unhealthy MG can transfer its load to the healthy MG for safety reasons. The healthy MG is then connected to the external grid and the synchronisation conditions are checked by the proposed control system. The results of the non‐linear simulation performed in MATLAB‐Simulink software confirm that the proposed model successfully operates and controls all resources (i.e. solar/wind/battery/FC), regulates the voltage/frequency under various loading conditions, and identifies FDI cyberattacks.
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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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