近期，实验室博士生胡志坚作为第一作者，导师吴立刚教授作为通讯作者的论文“Intrusion-Detector-Dependent Distributed Economic Model Predictive Control for Load Frequency Regulation With PEVs Under Cyber Attacks”已被控制领域权威期刊IEEE Transactions on Circuits and Systems I: Regular Papers录用。

该论文针对大量插电式电动汽车参与电力系统负载频率调节问题，提出了一种分布式经济模型预测控制策略。考虑到负载频率调节对错误信息注入攻击的脆弱性，论文设计了基于模型的入侵检测单元。这种基于模型的入侵检测单元不仅可以监测外部错误信息注入攻击，还能为分布式经济模型预测控制器生成基于模型的状态预测。此外，论文设计了一种新型事件触发机制，以减少邻域控制器的计算与通信负担。仿真结果验证了所提出入侵检测单元与事件触发条件对分布式经济模型预测控制的有效性。

Abstract

With the participation of a significant number of plug-in electric vehicles (PEVs), it is really challenging to achieve economic-effective in load frequency control (LFC) while sustaining satisfactory system performance. To tackle this challenge, a new distributed economic model predictive control (DEMPC) strategy is proposed for the LFC with the large-scale PEV participation. In the light of the vulnerability of LFC to false data injection (FDI) attacks, a model-based intrusion detection unit is integrated with the proposed DEMPC. This model-based intrusion detection unit can not only monitor the FDI attacks, but also generate a model-based state prediction for the DEMPC once the data is identified as compromised. Then, an event triggering mechanism is presented to reduce the computation and communication burdens of each area controller. Simulation studies of a four-area power system are conducted and the results validate the effectiveness of the proposed intrusion detection unit and event-triggering conditions for the DEMPC.