电压降
试验台
微电网
控制理论(社会学)
自动频率控制
控制器(灌溉)
控制工程
带宽(计算)
计算机科学
智能控制
工程类
控制(管理)
电压
人工智能
电压调节器
计算机网络
电信
生物
电气工程
农学
作者
Mohammad Sadegh Orfi Yeganeh,Arman Oshnoei,Nenad Mijatović,Tomislav Dragičević,Frede Blaabjerg
出处
期刊:IEEE Transactions on Industrial Electronics
[Institute of Electrical and Electronics Engineers]
日期:2023-07-01
卷期号:70 (7): 6711-6723
被引量:10
标识
DOI:10.1109/tie.2022.3203677
摘要
This article proposes a distributed intelligent secondary control approach based on brain emotional learning-based intelligent controller (BELBIC) for power electronic-based ac microgrid (MG). The BELBIC controller is able to learn quick-auto and handle model complexity, nonlinearity, and uncertainty of the MG. The proposed controller is fully model-free, indicating that the voltage amplitude and frequency deviations are regulated without previous knowledge of the system model and parameters. This approach ensures low steady-state variations with higher bandwidth and maintains accurate power-sharing of the droop mechanism. Furthermore, primary control is realized with a robust finite control set-model predictive control in the inner level to increase the system frequency bandwidth and a droop control in the outer level to regulate the power-sharing among the distributed generations. Finally, experimental tests obtained from a hardware-in-the-loop testbed validate the proposed control strategy for different cases.
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