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.
S. Saadatmand et al., "Neural Network Predictive Controller for Grid-Connected Virtual Synchronous Generator," Proceedings of the 2019 North American Power Symposium (2019, Wichita, KS), Institute of Electrical and Electronics Engineers (IEEE), Oct 2019.
The definitive version is available at https://doi.org/10.1109/NAPS46351.2019.9000386
2019 North American Power Symposium, NAPS (2019: Oct. 13-15, Wichita, KS)
Electrical and Computer Engineering
Center for Research in Energy and Environment (CREE)
Second Research Center/Lab
Center for High Performance Computing Research
Keywords and Phrases
Grid Connected Inverters; Neural Network Predictive Controller; Optimal Control; Virtual Synchronous Generator
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
15 Oct 2019