Academic Journal
A Novel Differentiated Control Strategy for an Energy Storage System That Minimizes Battery Aging Cost Based on Multiple Health Features.
| Title: | A Novel Differentiated Control Strategy for an Energy Storage System That Minimizes Battery Aging Cost Based on Multiple Health Features. |
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| Authors: | Xiao, Wei, Jia, Jun, Zhong, Weidong, Liu, Wenxue, Wu, Zhuoyan, Jiang, Cheng, Li, Binke |
| Source: | Batteries; Apr2024, Vol. 10 Issue 4, p143, 32p |
| Subject Terms: | Energy storage, Particle swarm optimization, Variable costs, Service life |
| Abstract: | In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to intricate coupled conditions, this distribution strategy inevitably results in increased inconsistency and hastened system aging. This paper presents a novel differentiated power distribution strategy comprising three control variables: the rotation status, and the operating boundaries for both depth of discharge (DOD) and C-rates (C) within a control period. The proposed strategy integrates an aging cost prediction model developed to express the mapping relationship between these control variables and aging costs. Additionally, it incorporates the multi-colony particle swarm optimization (Mc-PSO) algorithm into the optimization model to minimize aging costs. The aging cost prediction model consists of three functions: predicting health features (HFs) based on the cumulative charge/discharge throughput quantity and operating boundaries, characterizing HFs as comprehensive scores, and calculating aging costs using both comprehensive scores and residual equipment value. Further, we elaborated on the engineering application process for the proposed control strategy. In the simulation scenarios, this strategy prolonged the service life by 14.62%, reduced the overall aging cost by 6.61%, and improved module consistency by 21.98%, compared with the traditional equalized distribution strategy. In summary, the proposed strategy proves effective in elongating service life, reducing overall aging costs, and increasing the benefit of energy storage systems in particular application scenarios. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:edb&genre=article&issn=23130105&ISBN=&volume=10&issue=4&date=20240401&spage=143&pages=143-174&title=Batteries&atitle=A%20Novel%20Differentiated%20Control%20Strategy%20for%20an%20Energy%20Storage%20System%20That%20Minimizes%20Battery%20Aging%20Cost%20Based%20on%20Multiple%20Health%20Features.&aulast=Xiao%2C%20Wei&id=DOI:10.3390/batteries10040143 Name: Full Text Finder (for New FTF UI) (ns324271) Category: fullText Text: Full Text Finder MouseOverText: Full Text Finder |
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| Items | – Name: Title Label: Title Group: Ti Data: A Novel Differentiated Control Strategy for an Energy Storage System That Minimizes Battery Aging Cost Based on Multiple Health Features. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Xiao%2C+Wei%22">Xiao, Wei</searchLink><br /><searchLink fieldCode="AR" term="%22Jia%2C+Jun%22">Jia, Jun</searchLink><br /><searchLink fieldCode="AR" term="%22Zhong%2C+Weidong%22">Zhong, Weidong</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Wenxue%22">Liu, Wenxue</searchLink><br /><searchLink fieldCode="AR" term="%22Wu%2C+Zhuoyan%22">Wu, Zhuoyan</searchLink><br /><searchLink fieldCode="AR" term="%22Jiang%2C+Cheng%22">Jiang, Cheng</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Binke%22">Li, Binke</searchLink> – Name: TitleSource Label: Source Group: Src Data: Batteries; Apr2024, Vol. 10 Issue 4, p143, 32p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Energy+storage%22">Energy storage</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Variable+costs%22">Variable costs</searchLink><br /><searchLink fieldCode="DE" term="%22Service+life%22">Service life</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to intricate coupled conditions, this distribution strategy inevitably results in increased inconsistency and hastened system aging. This paper presents a novel differentiated power distribution strategy comprising three control variables: the rotation status, and the operating boundaries for both depth of discharge (DOD) and C-rates (C) within a control period. The proposed strategy integrates an aging cost prediction model developed to express the mapping relationship between these control variables and aging costs. Additionally, it incorporates the multi-colony particle swarm optimization (Mc-PSO) algorithm into the optimization model to minimize aging costs. The aging cost prediction model consists of three functions: predicting health features (HFs) based on the cumulative charge/discharge throughput quantity and operating boundaries, characterizing HFs as comprehensive scores, and calculating aging costs using both comprehensive scores and residual equipment value. Further, we elaborated on the engineering application process for the proposed control strategy. In the simulation scenarios, this strategy prolonged the service life by 14.62%, reduced the overall aging cost by 6.61%, and improved module consistency by 21.98%, compared with the traditional equalized distribution strategy. In summary, the proposed strategy proves effective in elongating service life, reducing overall aging costs, and increasing the benefit of energy storage systems in particular application scenarios. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Batteries is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/batteries10040143 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 32 StartPage: 143 Subjects: – SubjectFull: Energy storage Type: general – SubjectFull: Particle swarm optimization Type: general – SubjectFull: Variable costs Type: general – SubjectFull: Service life Type: general Titles: – TitleFull: A Novel Differentiated Control Strategy for an Energy Storage System That Minimizes Battery Aging Cost Based on Multiple Health Features. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Xiao, Wei – PersonEntity: Name: NameFull: Jia, Jun – PersonEntity: Name: NameFull: Zhong, Weidong – PersonEntity: Name: NameFull: Liu, Wenxue – PersonEntity: Name: NameFull: Wu, Zhuoyan – PersonEntity: Name: NameFull: Jiang, Cheng – PersonEntity: Name: NameFull: Li, Binke IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 23130105 Numbering: – Type: volume Value: 10 – Type: issue Value: 4 Titles: – TitleFull: Batteries Type: main |
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