并网VSC系统神经网络控制器的状态空间建模与稳定性分析

P. Bana, M. Amin
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引用次数: 0

摘要

近年来,基于人工神经网络(ANN)的控制器在并网VSC系统中得到了广泛的研究。尽管人工神经网络控制器具有一些优势,但其黑盒建模使其在工业上缺乏吸引力。本文通过小信号建模方法揭示了人工神经网络电流控制器的工作机理及其与VSC系统的交互作用。在部署用于测试之前,人工神经网络控制器使用标准pi控制器数据进行训练。然后,推导了VSC系统和人工神经网络控制器的状态空间方程,建立了小信号模型。通过对MATLAB/Simulink非线性模型的时域仿真结果进行验证。然后利用小信号模型来研究系统的稳定性。通过对小信号模型进行参与因子和参数灵敏度分析,研究了系统和人工神经网络控制器的行为。
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State-space Modelling and Stability Analysis of ANN controller for Grid-connected VSC System
Recently, Artificial Neural Network (ANN)-based controllers have been extensively investigated for grid-connected VSC systems. Despite having several advantageous features, the black-box modelling of the ANN controller makes it less industry attractive. This paper reveals the working mechanism of the ANN current controller and its interaction with the VSC system through the small-signal modelling approach. The ANN controller is trained with the standard PI-controller data before deploying for testing. Afterward, state-space equations of the VSC system and ANN controller are derived to develop the small-signal model. The derived model is verified against the time-domain simulation results obtained from the non-linear MATLAB/Simulink model. The small-signal model is then utilised to study the stability of the system. The system and ANN controller behaviour are also studied by performing the participation factor and parametric sensitivity analysis to the small-signal model.
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