Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator

Aiming at large system operation fluctuations caused by the technical control of virtual synchronous generators, this article studies the introduction of interface converter control power, builds a virtual synchronous generator (VSG)-based hybrid microgrid model and adaptive control strategy. Finall...

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Published in:Advanced Control for Applications: Engineering and Industrial Systems
Main Author: Wang J.; Ramli N.; Aziz N.H.A.
Format: Article
Language:English
Published: John Wiley and Sons Inc 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162857275&doi=10.1002%2fadc2.155&partnerID=40&md5=877853285df7285458f395466d0eb125
id 2-s2.0-85162857275
spelling 2-s2.0-85162857275
Wang J.; Ramli N.; Aziz N.H.A.
Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator
2024
Advanced Control for Applications: Engineering and Industrial Systems
6
2
10.1002/adc2.155
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162857275&doi=10.1002%2fadc2.155&partnerID=40&md5=877853285df7285458f395466d0eb125
Aiming at large system operation fluctuations caused by the technical control of virtual synchronous generators, this article studies the introduction of interface converter control power, builds a virtual synchronous generator (VSG)-based hybrid microgrid model and adaptive control strategy. Finally it optimizes it with fuzzy logic to obtain an fuzzy logic controller (FLC) based adaptive VSG control strategy. The experimental results show that under the FLC-based adaptive VSG control strategy, in the reverse current mode, the system regression time is 0.37 s, and the DC bus voltage is 6.5 V; In the rectification mode, the system regression time is 0.49 s, and the DC bus voltage is 2.1 V. The results obtained are faster than the traditional VSG control strategy, and the DC bus voltage is 42.48%–68.66% lower. In summary, the suggested control approach is effective and reliable under the two operation modes, which can make the system operate safely and stably. © 2023 John Wiley & Sons Ltd.
John Wiley and Sons Inc
25780727
English
Article

author Wang J.; Ramli N.; Aziz N.H.A.
spellingShingle Wang J.; Ramli N.; Aziz N.H.A.
Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator
author_facet Wang J.; Ramli N.; Aziz N.H.A.
author_sort Wang J.; Ramli N.; Aziz N.H.A.
title Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator
title_short Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator
title_full Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator
title_fullStr Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator
title_full_unstemmed Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator
title_sort Modeling and adaptive control strategy of hybrid microgrid based on virtual synchronous generator
publishDate 2024
container_title Advanced Control for Applications: Engineering and Industrial Systems
container_volume 6
container_issue 2
doi_str_mv 10.1002/adc2.155
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162857275&doi=10.1002%2fadc2.155&partnerID=40&md5=877853285df7285458f395466d0eb125
description Aiming at large system operation fluctuations caused by the technical control of virtual synchronous generators, this article studies the introduction of interface converter control power, builds a virtual synchronous generator (VSG)-based hybrid microgrid model and adaptive control strategy. Finally it optimizes it with fuzzy logic to obtain an fuzzy logic controller (FLC) based adaptive VSG control strategy. The experimental results show that under the FLC-based adaptive VSG control strategy, in the reverse current mode, the system regression time is 0.37 s, and the DC bus voltage is 6.5 V; In the rectification mode, the system regression time is 0.49 s, and the DC bus voltage is 2.1 V. The results obtained are faster than the traditional VSG control strategy, and the DC bus voltage is 42.48%–68.66% lower. In summary, the suggested control approach is effective and reliable under the two operation modes, which can make the system operate safely and stably. © 2023 John Wiley & Sons Ltd.
publisher John Wiley and Sons Inc
issn 25780727
language English
format Article
accesstype
record_format scopus
collection Scopus
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