Iterative Learning Control for Virtual Inertia: Improving Frequency Stability in Renewable Energy Microgrids

Nguyen Van Tan (), Thi Bich Thanh Truong, Quang Vu Truong, Hong Viet Phuong Nguyen and Minh Quan Duong
Additional contact information
Nguyen Van Tan: Faculty of Electrical Engineering, The University of Danang—University of Science and Technology, Danang 50006, Vietnam
Thi Bich Thanh Truong: Faculty of Electrical Engineering, The University of Danang—University of Science and Technology, Danang 50006, Vietnam
Quang Vu Truong: Faculty of Electrical Engineering, The University of Danang—University of Science and Technology, Danang 50006, Vietnam
Hong Viet Phuong Nguyen: Faculty of Electrical Engineering, The University of Danang—University of Science and Technology, Danang 50006, Vietnam
Minh Quan Duong: Faculty of Electrical Engineering, The University of Danang—University of Science and Technology, Danang 50006, Vietnam

Sustainability, 2025, vol. 17, issue 15, 1-21

Abstract: The integration of renewable energy sources (RESs) into power systems, particularly in microgrids, is becoming a prominent trend aimed at reducing dependence on traditional energy sources. Replacing conventional synchronous generators with grid-connected RESs through power electronic converters has significantly reduced the inertia of microgrids. This reduction negatively impacts the dynamics and operational performance of microgrids when confronted with uncertainties, posing challenges to frequency and voltage stability, especially in a standalone operating mode. To address this issue, this research proposes enhancing microgrid stability through frequency control based on virtual inertia (VI). Additionally, the Iterative Learning Control (ILC) method is employed, leveraging iterative learning strategies to improve the quality of output response control. Accordingly, the ILC-VI control method is introduced, integrating the iterative learning mechanism into the virtual inertia controller to simultaneously enhance the system’s inertia and damping coefficient, thereby improving frequency stability under varying operating conditions. The effectiveness of the ILC-VI method is evaluated in comparison with the conventional VI (C-VI) control method through simulations conducted on the MATLAB/Simulink platform. Simulation results demonstrate that the ILC-VI method significantly reduces the frequency nadir, the rate of change of frequency (RoCoF), and steady-state error across iterations, while also enhancing the system’s robustness against substantial variations from renewable energy sources. Furthermore, this study analyzes the effects of varying virtual inertia values, shedding light on their role in influencing response quality and convergence speed. This research underscores the potential of the ILC-VI control method in providing effective support for low-inertia microgrids.

Keywords: frequency regulation; microgrid; virtual inertia control; iterative learning control (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/15/6727/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/15/6727/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:15:p:6727-:d:1708898

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().