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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Bibliographic Details
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:
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
Beluga
Beluga whale
Beluga*
Online Access:https://doi.org/10.3389/fenrg.2024.1336205
https://doaj.org/article/bf98bdcf83c3442e9eae9ccf960aeeb9
Description
Summary: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.

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