KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integration

As renewable energy penetration keeps growing, its intermittent nature poses huge challenges on the reliable and flexible operation of power systems. The uncertainty and reverse peak shaving characteristics of renewable energy further exacerbate issues of load shedding and renewable energy curtailme...

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Main Authors: Jing Liu, Zicheng Guo, Yalong Li
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Results in Engineering
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025028804
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author Jing Liu
Zicheng Guo
Yalong Li
author_facet Jing Liu
Zicheng Guo
Yalong Li
author_sort Jing Liu
collection DOAJ
description As renewable energy penetration keeps growing, its intermittent nature poses huge challenges on the reliable and flexible operation of power systems. The uncertainty and reverse peak shaving characteristics of renewable energy further exacerbate issues of load shedding and renewable energy curtailment. Additionally, both carbon trading and hydrogen energy which play important roles in reducing carbon emissions have attracted great attention. A novel bi-level optimal scheduling model of the electricity-carbon-hydrogen coupling system is proposed considering carbon trading, load flexibility and deep peak shaving. The model simultaneously minimizes load shedding, renewable energy curtailment and the operation cost. Moreover, the Kepler optimization (KO) algorithm is applied and benchmarked against flower pollination (FP) algorithm and particle swarm optimization (PSO) algorithm. Finally, comparative studies confirm that incorporating flexible resources (flexible load and deep peak shaving) significantly reduce renewable curtailment, eliminate load shedding, and lower operation cost. Furthermore, the newly introduced KO algorithm demonstrates superior performance over both FP and PSO algorithms across all evaluated metrics.
format Article
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institution Kabale University
issn 2590-1230
language English
publishDate 2025-09-01
publisher Elsevier
record_format Article
series Results in Engineering
spelling doaj-art-90470205f0a548a18dd3744d73c0c38c2025-08-23T04:49:02ZengElsevierResults in Engineering2590-12302025-09-012710681610.1016/j.rineng.2025.106816KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integrationJing Liu0Zicheng Guo1Yalong Li2School of Mechanical and Electrical Engineering, China University of Mining & Technology-Beijing, Beijing 100083, China; The Key Laboratory of Intelligent Mining and Robotics, Ministry of Emergency Management, Beijing 100083, China; Corresponding author.School of Mechanical and Electrical Engineering, China University of Mining & Technology-Beijing, Beijing 100083, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining & Technology-Beijing, Beijing 100083, ChinaAs renewable energy penetration keeps growing, its intermittent nature poses huge challenges on the reliable and flexible operation of power systems. The uncertainty and reverse peak shaving characteristics of renewable energy further exacerbate issues of load shedding and renewable energy curtailment. Additionally, both carbon trading and hydrogen energy which play important roles in reducing carbon emissions have attracted great attention. A novel bi-level optimal scheduling model of the electricity-carbon-hydrogen coupling system is proposed considering carbon trading, load flexibility and deep peak shaving. The model simultaneously minimizes load shedding, renewable energy curtailment and the operation cost. Moreover, the Kepler optimization (KO) algorithm is applied and benchmarked against flower pollination (FP) algorithm and particle swarm optimization (PSO) algorithm. Finally, comparative studies confirm that incorporating flexible resources (flexible load and deep peak shaving) significantly reduce renewable curtailment, eliminate load shedding, and lower operation cost. Furthermore, the newly introduced KO algorithm demonstrates superior performance over both FP and PSO algorithms across all evaluated metrics.http://www.sciencedirect.com/science/article/pii/S2590123025028804Electricity-carbon-hydrogen coupling systemshydrogen integrationRenewable energyDeep peak shavingKepler optimization algorithm
spellingShingle Jing Liu
Zicheng Guo
Yalong Li
KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integration
Results in Engineering
Electricity-carbon-hydrogen coupling systems
hydrogen integration
Renewable energy
Deep peak shaving
Kepler optimization algorithm
title KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integration
title_full KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integration
title_fullStr KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integration
title_full_unstemmed KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integration
title_short KO algorithm-based bi-level optimal scheduling of electricity-carbon-hydrogen coupling systems with flexible resources for renewable energy integration
title_sort ko algorithm based bi level optimal scheduling of electricity carbon hydrogen coupling systems with flexible resources for renewable energy integration
topic Electricity-carbon-hydrogen coupling systems
hydrogen integration
Renewable energy
Deep peak shaving
Kepler optimization algorithm
url http://www.sciencedirect.com/science/article/pii/S2590123025028804
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AT zichengguo koalgorithmbasedbileveloptimalschedulingofelectricitycarbonhydrogencouplingsystemswithflexibleresourcesforrenewableenergyintegration
AT yalongli koalgorithmbasedbileveloptimalschedulingofelectricitycarbonhydrogencouplingsystemswithflexibleresourcesforrenewableenergyintegration