A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm

Endeavoring to enhance the penetration rate of renewable energy sources, concurrently ensuring economic and operational stability, this study proposes a novel bi-layer optimization method of the wind–solar-storage AC/DC microgrid (MG). First, by incorporating a superordinate electric and seasonal hy...

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Published in:Frontiers in Energy Research
Main Authors: Xianjing Zhong, Xianbo Sun, Yuhan Wu
Format: Article in Journal/Newspaper
Language:English
Published: Frontiers Media S.A. 2024
Subjects:
A
Online Access:https://doi.org/10.3389/fenrg.2024.1336205
https://doaj.org/article/bf98bdcf83c3442e9eae9ccf960aeeb9
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spelling ftdoajarticles:oai:doaj.org/article:bf98bdcf83c3442e9eae9ccf960aeeb9 2024-09-15T17:58:59+00:00 A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm Xianjing Zhong Xianbo Sun Yuhan Wu 2024-02-01T00:00:00Z https://doi.org/10.3389/fenrg.2024.1336205 https://doaj.org/article/bf98bdcf83c3442e9eae9ccf960aeeb9 EN eng Frontiers Media S.A. https://www.frontiersin.org/articles/10.3389/fenrg.2024.1336205/full https://doaj.org/toc/2296-598X 2296-598X doi:10.3389/fenrg.2024.1336205 https://doaj.org/article/bf98bdcf83c3442e9eae9ccf960aeeb9 Frontiers in Energy Research, Vol 12 (2024) wind–solar-storage AC/DC microgrid hybrid energy storage system optimal configuration bi-layer optimal model multi-strategy hybrid improvement of Beluga Whale Algorithm General Works A article 2024 ftdoajarticles https://doi.org/10.3389/fenrg.2024.1336205 2024-08-05T17:49:57Z Endeavoring to enhance the penetration rate of renewable energy sources, concurrently ensuring economic and operational stability, this study proposes a novel bi-layer optimization method of the wind–solar-storage AC/DC microgrid (MG). First, by incorporating a superordinate electric and seasonal hydrogen hybrid energy storage system (E&SHESS), the topology structure of the microgrid is established. Subsequently, to rectify the intrinsic limitations of the conventional beluga whale optimization (BWO) algorithm, this paper proposes a multi-strategy hybrid improvement to BWO (MHIBWO). This innovative improvement integrates an MTent strategy, a step size adjustment mechanism, and a crisscross strategy. Then, constructing a bi-layer iterative model based on the topology, annual net income and grid-connected friendliness are introduced as optimization objectives for the outer and inner layers, respectively, utilizing MHIBWO and CPLEX for resolution. Through a nested iteration of the two layers, the model outputs the capacity scheme with the best performance of economy and stability. Finally, the simulation unequivocally demonstrated the superiority of MHIBWO and the model proposed. In addition, based on the real data of the Elia power station, the validity of the method in operation is tested using the fuzzy C-means algorithm (FCMA) to extract and aggregate typical days, thereby presenting a sophisticated solution for the field of microgrids optimization configuration. Article in Journal/Newspaper Beluga Beluga whale Beluga* Directory of Open Access Journals: DOAJ Articles Frontiers in Energy Research 12
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic wind–solar-storage AC/DC microgrid
hybrid energy storage system
optimal configuration
bi-layer optimal model
multi-strategy hybrid improvement of Beluga Whale Algorithm
General Works
A
spellingShingle wind–solar-storage AC/DC microgrid
hybrid energy storage system
optimal configuration
bi-layer optimal model
multi-strategy hybrid improvement of Beluga Whale Algorithm
General Works
A
Xianjing Zhong
Xianbo Sun
Yuhan Wu
A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm
topic_facet wind–solar-storage AC/DC microgrid
hybrid energy storage system
optimal configuration
bi-layer optimal model
multi-strategy hybrid improvement of Beluga Whale Algorithm
General Works
A
description Endeavoring to enhance the penetration rate of renewable energy sources, concurrently ensuring economic and operational stability, this study proposes a novel bi-layer optimization method of the wind–solar-storage AC/DC microgrid (MG). First, by incorporating a superordinate electric and seasonal hydrogen hybrid energy storage system (E&SHESS), the topology structure of the microgrid is established. Subsequently, to rectify the intrinsic limitations of the conventional beluga whale optimization (BWO) algorithm, this paper proposes a multi-strategy hybrid improvement to BWO (MHIBWO). This innovative improvement integrates an MTent strategy, a step size adjustment mechanism, and a crisscross strategy. Then, constructing a bi-layer iterative model based on the topology, annual net income and grid-connected friendliness are introduced as optimization objectives for the outer and inner layers, respectively, utilizing MHIBWO and CPLEX for resolution. Through a nested iteration of the two layers, the model outputs the capacity scheme with the best performance of economy and stability. Finally, the simulation unequivocally demonstrated the superiority of MHIBWO and the model proposed. In addition, based on the real data of the Elia power station, the validity of the method in operation is tested using the fuzzy C-means algorithm (FCMA) to extract and aggregate typical days, thereby presenting a sophisticated solution for the field of microgrids optimization configuration.
format Article in Journal/Newspaper
author Xianjing Zhong
Xianbo Sun
Yuhan Wu
author_facet Xianjing Zhong
Xianbo Sun
Yuhan Wu
author_sort Xianjing Zhong
title A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm
title_short A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm
title_full A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm
title_fullStr A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm
title_full_unstemmed A bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm
title_sort bi-layer optimization method of the grid-connected microgrid based on the multi-strategy of the beluga whale algorithm
publisher Frontiers Media S.A.
publishDate 2024
url https://doi.org/10.3389/fenrg.2024.1336205
https://doaj.org/article/bf98bdcf83c3442e9eae9ccf960aeeb9
genre Beluga
Beluga whale
Beluga*
genre_facet Beluga
Beluga whale
Beluga*
op_source Frontiers in Energy Research, Vol 12 (2024)
op_relation https://www.frontiersin.org/articles/10.3389/fenrg.2024.1336205/full
https://doaj.org/toc/2296-598X
2296-598X
doi:10.3389/fenrg.2024.1336205
https://doaj.org/article/bf98bdcf83c3442e9eae9ccf960aeeb9
op_doi https://doi.org/10.3389/fenrg.2024.1336205
container_title Frontiers in Energy Research
container_volume 12
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