Neural Network Predictive Controller for Grid-Connected Virtual Synchronous Generator

Saadatmand, Sepehr; Nia, Mohamad Sanjari; Shamsi, Pourya; Ferdowsi, Mehdi; Wunsch, Donald C.

doi:10.1109/naps46351.2019.9000386

Neural Network Predictive Controller for Grid-Connected Virtual Synchronous Generator

Conference · 01 October 2019 · 2019 North American Power Symposium (NAPS)

DOI:https://doi.org/10.1109/naps46351.2019.9000386· OSTI ID:1992479

Saadatmand, Sepehr; Nia, Mohamad Sanjari; Shamsi, Pourya; Ferdowsi, Mehdi; Wunsch, Donald C.

In this paper, a neural network predictive controller is proposed to regulate the active and the reactive power delivered to the grid generated by a three-phase virtual inertia-based inverter. The concept of the conventional virtual synchronous generator (VSG) is discussed, and it is shown that when the inverter is connected to non-inductive grids, the conventional PI-based VSGs are unable to perform acceptable tracking. The concept of the neural network predictive controller is also discussed to replace the traditional VSGs. This replacement enables inverters to perform in both inductive and non-inductive grids. The simulation results confirm that a well-trained neural network predictive controller illustrates can adapt to any grid impedance angle, compared to the traditional PI-based virtual inertia controllers.

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Research Organization:: Missouri University of Science and Technology

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Vehicle Technologies Office (VTO)

DOE Contract Number:: EE0008449

OSTI ID:: 1992479

Journal Information:: 2019 North American Power Symposium (NAPS), Conference: 2019 North American Power Symposium (NAPS)

Country of Publication:: United States

Language:: English

References (10)

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24 POWER TRANSMISSION AND DISTRIBUTION
Grid connected inverters
neural network predictive controller
optimal control
virtual synchronous generator

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