Resilient Event-Triggered MPC for Load Frequency Regulation With Wind Turbines Under False Data Injection Attacks

风力发电 钥匙(锁) 背景(考古学) 模型预测控制 计算机科学 事件(粒子物理) 电力系统 控制器(灌溉) 电力系统仿真 可靠性工程 经济调度 工程类 实时计算 控制(管理) 功率(物理) 控制工程 计算机安全 人工智能 电气工程 农学 古生物学 物理 生物 量子力学
作者
Zhijian Hu,Rong Su,Keck Voon Ling,Yao Guo,Renjie Ma
出处
期刊:IEEE Transactions on Automation Science and Engineering [Institute of Electrical and Electronics Engineers]
卷期号:: 1-11 被引量:10
标识
DOI:10.1109/tase.2023.3337006
摘要

To further the penetration level of renewable energy sources (RESs) in power systems, the paper integrates wind turbines into conventional load frequency control (LFC). A resilient model predictive control (MPC) framework is constructed in the context of potential false data injection (FDI) attacks on vulnerable communication networks of multi-area power systems. To reduce the power generation cost, an economic cost function for MPC is firstly formulated. Then, a decentralized-model-based $\chi^{2}$ detection unit is presented to distinguish the attacked measurements sent from neighbors. Moreover, to reduce the computation burden of executing the distributed MPC strategy, an intensified event-triggered scheme that can handle incomplete and inaccurate modeling issues is proposed. Validation results illustrate the efficacy of the detection unit and the intensified event-triggered scheme, and conclude the relationships between alarming thresholds and key performance indicators. Note to Practitioners —This paper explores the applicability of LFC with the integration of wind turbines under economic MPC framework. Motivated by the underlying FDI attacks on vulnerable communication networks among different control areas, an intrusion detection unit is proposed to install at each controller side to realize resiliency enhancement. Different from the existing works, this paper meticulously investigates the relationships between alarming thresholds and key performance indicators (KPIs), aiming at providing some valuable references for power operators and managers. Besides, this paper proposes an intensified event-triggered scheme to relieve the computation burden of MPC algorithm. This intensified event-triggered scheme has two advantages. One is that it considers the historic released signals in event-triggered conditions, which makes sure the critical signals at crests or troughs of frequency dynamic curves can be triggered. The other advantage is that the supplementary event-trigged condition can well tolerant the incomplete and inaccurate modeling problems existing in conventional event-triggered conditions. Simulations verify the efficacy and feasibility of the resilient event-triggered MPC strategy for frequency regulation under FDI attacks.
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