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: Zhong, Xianjing, Sun, Xianbo, Wu, Yuhan
Format: Article in Journal/Newspaper
Language:unknown
Published: Frontiers Media SA 2024
Subjects:
Economics and Econometrics
Energy Engineering and Power Technology
Fuel Technology
Renewable Energy, Sustainability and the Environment
Elia
Beluga
Beluga whale
Beluga*
Online Access:http://dx.doi.org/10.3389/fenrg.2024.1336205
https://www.frontiersin.org/articles/10.3389/fenrg.2024.1336205/full
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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