An Integrated Optimization Method for Multiuser Energy Storage Configuration and Leasing in Campus Energy Systems.
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| Title: | An Integrated Optimization Method for Multiuser Energy Storage Configuration and Leasing in Campus Energy Systems. |
|---|---|
| Authors: | Qiao, Yunchi1 (AUTHOR), Zhang, Quanming1,2 (AUTHOR) 13980069315@139.com, Xu, Weiting1 (AUTHOR), Pan, Xuejiao1,2 (AUTHOR), Liu, Fang1 (AUTHOR), Shi, Jia1 (AUTHOR), Zeng, Youxin2 (AUTHOR) youxinzeng@stu.scu.edu.cn, Zhang, Jiyuan2 (AUTHOR) |
| Source: | Energies (19961073). Dec2025, Vol. 18 Issue 23, p6244. 20p. |
| Subjects: | Energy storage, Multiuser computer systems, Evaluation methodology, Resource allocation, Feasibility studies, Optimization algorithms |
| Abstract: | With respect to the current campus energy systems, the research on energy storage deployment has focused mostly on single users or a single metric, making it difficult to accommodate diverse multiuser needs while efficiently utilizing the available resources. This results in narrow evaluation dimensions and underutilized storage assets. To address this issue, an integrated method for multiuser energy storage, optimal sizing and leasing is proposed in this paper; the method is aimed at improving the economics and utilization of storage. First, we construct a campus energy system architecture that includes an energy storage service provider and develop a storage sizing model that minimizes the average daily total cost, yielding the optimal power ratings and capacities for different users. Second, we construct a comprehensive evaluation framework from both economic and technical perspectives and apply quantitative methods to select the best configuration scheme. On this basis, we propose a multicriteria optimization-based storage leasing mechanism that enables resource sharing among users and maximizes the revenue received by the service provider. Simulation results reveal that across five typical user scenarios, the proposed method outperforms the traditional single-configuration models: the overall storage utilization rate increases by 3.84%, the cost-reduction rates for some users exceed 16%, and the investment payback period decreases by approximately one year. Compared with configuration-only approaches, the proposed integrated configuration–leasing framework simultaneously enhances user-side economics and the profitability of the service provider. The integrated sizing and leasing method not only demonstrates solid economic and technical feasibility but is also applicable to multiuser campuses, shared storage cases, and cloud storage scenarios, providing a reference path for future multidimensional value extraction processes and commercial operations. [ABSTRACT FROM AUTHOR] |
| Copyright of Energies (19961073) 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. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 190517971 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: An Integrated Optimization Method for Multiuser Energy Storage Configuration and Leasing in Campus Energy Systems. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Qiao%2C+Yunchi%22">Qiao, Yunchi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Quanming%22">Zhang, Quanming</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> 13980069315@139.com</i><br /><searchLink fieldCode="AR" term="%22Xu%2C+Weiting%22">Xu, Weiting</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pan%2C+Xuejiao%22">Pan, Xuejiao</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Fang%22">Liu, Fang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shi%2C+Jia%22">Shi, Jia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zeng%2C+Youxin%22">Zeng, Youxin</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> youxinzeng@stu.scu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Jiyuan%22">Zhang, Jiyuan</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Dec2025, Vol. 18 Issue 23, p6244. 20p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Energy+storage%22">Energy storage</searchLink><br /><searchLink fieldCode="DE" term="%22Multiuser+computer+systems%22">Multiuser computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+methodology%22">Evaluation methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Feasibility+studies%22">Feasibility studies</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: With respect to the current campus energy systems, the research on energy storage deployment has focused mostly on single users or a single metric, making it difficult to accommodate diverse multiuser needs while efficiently utilizing the available resources. This results in narrow evaluation dimensions and underutilized storage assets. To address this issue, an integrated method for multiuser energy storage, optimal sizing and leasing is proposed in this paper; the method is aimed at improving the economics and utilization of storage. First, we construct a campus energy system architecture that includes an energy storage service provider and develop a storage sizing model that minimizes the average daily total cost, yielding the optimal power ratings and capacities for different users. Second, we construct a comprehensive evaluation framework from both economic and technical perspectives and apply quantitative methods to select the best configuration scheme. On this basis, we propose a multicriteria optimization-based storage leasing mechanism that enables resource sharing among users and maximizes the revenue received by the service provider. Simulation results reveal that across five typical user scenarios, the proposed method outperforms the traditional single-configuration models: the overall storage utilization rate increases by 3.84%, the cost-reduction rates for some users exceed 16%, and the investment payback period decreases by approximately one year. Compared with configuration-only approaches, the proposed integrated configuration–leasing framework simultaneously enhances user-side economics and the profitability of the service provider. The integrated sizing and leasing method not only demonstrates solid economic and technical feasibility but is also applicable to multiuser campuses, shared storage cases, and cloud storage scenarios, providing a reference path for future multidimensional value extraction processes and commercial operations. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Energies (19961073) 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/en18236244 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 6244 Subjects: – SubjectFull: Energy storage Type: general – SubjectFull: Multiuser computer systems Type: general – SubjectFull: Evaluation methodology Type: general – SubjectFull: Resource allocation Type: general – SubjectFull: Feasibility studies Type: general – SubjectFull: Optimization algorithms Type: general Titles: – TitleFull: An Integrated Optimization Method for Multiuser Energy Storage Configuration and Leasing in Campus Energy Systems. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Qiao, Yunchi – PersonEntity: Name: NameFull: Zhang, Quanming – PersonEntity: Name: NameFull: Xu, Weiting – PersonEntity: Name: NameFull: Pan, Xuejiao – PersonEntity: Name: NameFull: Liu, Fang – PersonEntity: Name: NameFull: Shi, Jia – PersonEntity: Name: NameFull: Zeng, Youxin – PersonEntity: Name: NameFull: Zhang, Jiyuan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 18 – Type: issue Value: 23 Titles: – TitleFull: Energies (19961073) Type: main |
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