Fuzzy Logic–Based Decentralized Voltage–Frequency Control and Inertia Control of a VSG-Based Isolated Microgrid System

Baheej Alghamdi ()
Additional contact information
Baheej Alghamdi: Smart Grids Research Group, Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Energies, 2022, vol. 15, issue 22, 1-29

Abstract: This work proposes the use of fuzzy-logic-based voltage frequency control (VFC) and adaptive inertia to improve the frequency response of a virtual synchronous generator (VSG)-based isolated microgrid system. The joint VFC and inertial control scheme is proposed to limit frequency deviations in these isolated microgrid systems, mainly caused by the increasing penetration of intermittent distributed energy resources, which lack rotational inertia. The proposed controller uses artificial neural networks (ANN) to estimate the exponent of voltage-dependent loads and modulate the system frequency by adjusting the output voltage of the VSGs, which increases the system’s active power reserves while providing inertial control by adjusting the inertia of VSGs to minimize frequency and VSG DC-link voltage excursions. A genetic algorithm (GA)-based optimization strategy is developed to optimally adjust the parameters of the fuzzy logic controller to diminish the impact of disturbances on the system. In addition, the proposed technique is illustrated through simulations within the framework of a test system based on the CIGRE medium-voltage benchmark under various circumstances. The results of these simulations demonstrate that the proposed control strategy outperforms existing methods.

Keywords: artificial neural network; decentralized control; frequency control; genetic algorithm; isolated microgrids; virtual inertia; virtual synchronous generators; voltage control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/22/8401/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/22/8401/ (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:jeners:v:15:y:2022:i:22:p:8401-:d:968718

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

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