用于抑制直流配电系统振荡的自适应补偿虚拟阻抗法

IF 7.2 1区 工程技术 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Industrial Electronics Pub Date : 2024-10-30 DOI:10.1109/TIE.2024.3476912
Xinyang Su;Minghao Wang;Bi an Zhao;Yue Wang;Zhao Xu;Tonglu Wang
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引用次数: 0

摘要

随着系统规模的扩大,直流配电系统的振荡问题日益突出。它主要是由系统阻抗失配引起的。传统上采用虚拟阻抗方法来重新配置阻抗,消除振荡。然而,传统的解决方案通常被批评为稳定性不理想,动态性能差,可扩展性低。为了克服这些缺点,本文提出了一种自适应补偿虚拟阻抗(ACVI)方法。该方法能够适应变输出功率,动态性能和稳定性得到显著提高。在此基础上,ACVI采用了一种在线源侧阻抗估计方法。它有助于优化控制参数,以适应不同的源阻抗。最后,在48v直流配电系统中实现了该方法。实验结果验证了该方法及其参数优化方法的有效性。
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An Adaptive Compensated Virtual Impedance Method for Oscillation Suppression in DC Distribution Power Systems
The oscillation problem in dc distribution power system is becoming increasingly prominent as the system scale expands. It is mainly caused by the system impedance mismatch. Traditionally, virtual impedance methods are employed to reconfigure the impedance and eliminate the oscillation. However, traditional solutions are generally criticized for unsatisfactory stability, poor dynamic performance, and low scalability. To overcome these drawbacks, an adaptive compensated virtual impedance (ACVI) method is proposed in this article. The proposed method can adapt to variable output power with significantly improved dynamic performance and stability. On top of this, an online source-side impedance estimation method is incorporated into the ACVI. It helps optimize the control parameters for adapting to different source impedances. Finally, the proposed method is implemented in a 48 V dc distribution power system. Experimental results demonstrate the effectiveness of the proposed ACVI method and its parameter optimization method.
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来源期刊
IEEE Transactions on Industrial Electronics
IEEE Transactions on Industrial Electronics 工程技术-工程:电子与电气
CiteScore
16.80
自引率
9.10%
发文量
1396
审稿时长
6.3 months
期刊介绍: Journal Name: IEEE Transactions on Industrial Electronics Publication Frequency: Monthly Scope: The scope of IEEE Transactions on Industrial Electronics encompasses the following areas: Applications of electronics, controls, and communications in industrial and manufacturing systems and processes. Power electronics and drive control techniques. System control and signal processing. Fault detection and diagnosis. Power systems. Instrumentation, measurement, and testing. Modeling and simulation. Motion control. Robotics. Sensors and actuators. Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems. Factory automation. Communication and computer networks.
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