Nonlinear Multiple Models Adaptive Secondary Voltage Control of Microgrids

Ma, Zixiao; Wang, Zhaoyu; Guo, Yifei; Yuan, Yuxuan; Chen, Hao

doi:10.1109/tsg.2020.3023307

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Nonlinear Multiple Models Adaptive Secondary Voltage Control of Microgrids

Ma, Zixiao·Wang, Zhaoyu·Guo, Yifei·Yuan, Yuxuan·Chen, Hao

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Abstract

This article proposes a model-free secondary voltage control (SVC) for microgrids (MG) using nonlinear multiple models adaptive control. Firstly, a linear robust adaptive controller is designed to guarantee the voltage stability in the bounded-input- bounded-output (BIBO) manner so as to meet the operation requirements of MGs. Secondly, a nonlinear adaptive controller is developed to improve the voltage tracking performance with the help of artificial neural networks (ANNs). A switching mechanism for coordinating such two controllers is designed to guarantee the closed-loop stability while achieving accurate voltage tracking. Here, by an online identification based on the input and output data of MGs, the proposed method does not resort to any apriori information of system model and primary control, thus exhibiting good robustness, ease of deployment and disturbance rejection.

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17 WIND ENERGY Artificial neural network (ANN)adaptive control microgrid (MG)multiple models secondary voltage control (SVC)

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BibTeX RIS

Ma, Zixiao, Wang, Zhaoyu, Guo, Yifei, Yuan, Yuxuan, Chen, Hao. 2021-09-10. Nonlinear Multiple Models Adaptive Secondary Voltage Control of Microgrids. https://doi.org/10.1109/tsg.2020.3023307

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