Mid- to Long-Term Distribution System Planning Using Investment-Based Modeling.
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| Title: | Mid- to Long-Term Distribution System Planning Using Investment-Based Modeling. |
|---|---|
| Authors: | Ryu, Hosung1 (AUTHOR), Chae, Wookyu1 (AUTHOR), Kim, Hongjoo1 (AUTHOR), Cho, Jintae1 (AUTHOR) jintae.cho@kepco.co.kr |
| Source: | Energies (19961073). Jul2025, Vol. 18 Issue 14, p3702. 17p. |
| Subjects: | Distribution planning, Linear programming, Constraints (Physics), Strategic planning, Statistical decision making, Scalability, Risk assessment, Cost analysis |
| Abstract: | This study presents a practical and scalable framework for the mid- to long-term distribution network planning that reflects real-world infrastructure constraints and investment requirements. While traditional methods often rely on simplified network models or reactive reinforcement strategies, the proposed approach introduces an investment-oriented planning model that explicitly incorporates physical elements such as duct capacity, pole availability, and installation feasibility. A linear programming (LP) formulation is adopted to determine the optimal routing and sizing of new facilities under technical constraints including voltage regulation, power balance, and substation capacity limits. To validate the model's effectiveness, actual infrastructure and load data were used. The results show that the model can derive cost-efficient expansion strategies over a five-year horizon by prioritizing existing infrastructure use and flexibly adapting to spatial limitations. The proposed approach enables utility planners to make realistic, data-driven decisions and supports diverse scenario analyses through a modular structure. By embedding investment logic directly into the network model, this framework bridges the gap between high-level planning strategies and the engineering realities of distribution system expansion. [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: 186930449 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Mid- to Long-Term Distribution System Planning Using Investment-Based Modeling. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ryu%2C+Hosung%22">Ryu, Hosung</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chae%2C+Wookyu%22">Chae, Wookyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kim%2C+Hongjoo%22">Kim, Hongjoo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cho%2C+Jintae%22">Cho, Jintae</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jintae.cho@kepco.co.kr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Jul2025, Vol. 18 Issue 14, p3702. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Distribution+planning%22">Distribution planning</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+programming%22">Linear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Constraints+%28Physics%29%22">Constraints (Physics)</searchLink><br /><searchLink fieldCode="DE" term="%22Strategic+planning%22">Strategic planning</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+decision+making%22">Statistical decision making</searchLink><br /><searchLink fieldCode="DE" term="%22Scalability%22">Scalability</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Cost+analysis%22">Cost analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study presents a practical and scalable framework for the mid- to long-term distribution network planning that reflects real-world infrastructure constraints and investment requirements. While traditional methods often rely on simplified network models or reactive reinforcement strategies, the proposed approach introduces an investment-oriented planning model that explicitly incorporates physical elements such as duct capacity, pole availability, and installation feasibility. A linear programming (LP) formulation is adopted to determine the optimal routing and sizing of new facilities under technical constraints including voltage regulation, power balance, and substation capacity limits. To validate the model's effectiveness, actual infrastructure and load data were used. The results show that the model can derive cost-efficient expansion strategies over a five-year horizon by prioritizing existing infrastructure use and flexibly adapting to spatial limitations. The proposed approach enables utility planners to make realistic, data-driven decisions and supports diverse scenario analyses through a modular structure. By embedding investment logic directly into the network model, this framework bridges the gap between high-level planning strategies and the engineering realities of distribution system expansion. [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/en18143702 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 3702 Subjects: – SubjectFull: Distribution planning Type: general – SubjectFull: Linear programming Type: general – SubjectFull: Constraints (Physics) Type: general – SubjectFull: Strategic planning Type: general – SubjectFull: Statistical decision making Type: general – SubjectFull: Scalability Type: general – SubjectFull: Risk assessment Type: general – SubjectFull: Cost analysis Type: general Titles: – TitleFull: Mid- to Long-Term Distribution System Planning Using Investment-Based Modeling. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ryu, Hosung – PersonEntity: Name: NameFull: Chae, Wookyu – PersonEntity: Name: NameFull: Kim, Hongjoo – PersonEntity: Name: NameFull: Cho, Jintae IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 07 Text: Jul2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 18 – Type: issue Value: 14 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |
