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Design and implementation of optimized virtual oscillatory controllers for grid-forming inverters.
- Source :
-
ISA transactions [ISA Trans] 2023 Aug; Vol. 139, pp. 685-712. Date of Electronic Publication: 2023 Apr 21. - Publication Year :
- 2023
-
Abstract
- The percentage of renewable power in conventional power generation is gradually growing due to developments in power electronic converters (PECs). Renewable energy sources (RESs) can be integrated into the main grid through PECs, which are the most prevalent method to accomplish this. Virtual oscillator control (VOC) is a well-known time-domain method to regulate grid-forming inverters. VOC objective is to model the nonlinear dynamics of deadzone oscillator in a system of voltage source inverters to give a steady AC microgrid (MG). VOC is a self-synchronizing control method that just involves the current feedback signal. In contrast, classical droop and virtual synchronous machine (VSM) controllers both require the use of low pass filters to calculate real and reactive powers. The selection of control parameters in deadzone VOC is difficult and time-consuming. The VOC parameters are designed using different optimization techniques such as Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), modified Sine Cosine Algorithm (mSCA), African Vulture Optimization Algorithm (AVOA), and Artificial Jellyfish Search Optimization (AJSO). MATLAB and a real-time digital simulator (Opal RT-OP5142) were used to examine the system's performance with aforesaid controllers (droop, VSM, conventional VOC, VOC-PSO, VOC-SCA, VOC-mSCA, VOC-AVOA, and VOC-AJSO). In comparison to all control methods, the proposed VOC-AJSO provides faster synchronization. The effectiveness of the suggested VOC-AJSO control approach is proved by the hardware results.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2023 ISA. Published by Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1879-2022
- Volume :
- 139
- Database :
- MEDLINE
- Journal :
- ISA transactions
- Publication Type :
- Academic Journal
- Accession number :
- 37130764
- Full Text :
- https://doi.org/10.1016/j.isatra.2023.04.015