An intelligent decentralized energy management strategy for the optimal electric vehicles' charging in low‐voltage islanded microgrids.
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| Title: | An intelligent decentralized energy management strategy for the optimal electric vehicles' charging in low‐voltage islanded microgrids. |
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| Authors: | Boglou, Vasileios1 (AUTHOR) vboglou@ee.duth.gr, Karavas, Christos‐Spyridon2,3 (AUTHOR), Karlis, Athanasios1 (AUTHOR), Arvanitis, Konstantinos2 (AUTHOR) |
| Source: | International Journal of Energy Research. Mar2022, Vol. 46 Issue 3, p2988-3016. 29p. |
| Subjects: | Microgrids, Electric power system reliability, Energy management, Hybrid electric vehicles, Electric vehicles, Electric power consumption, Clean energy, Cognitive maps (Psychology) |
| Abstract: | Summary: The expected significant growth in global electricity demand, followed by the adoption of green energy sources, led to the modernization of the energy distribution grids, such as the development of microgrids that can improve the reliability of the electric power system. Meanwhile, the increased integration of electric vehicles is expected to have a negative impact on power quality, normal operation, and investment costs of the microgrid. In this paper, a microgrid topology was studied for the islanded operation of a low‐voltage distribution network. The deployment of such energy management systems is essential to guarantee the safe and reliable operation of isolated microgrids. Hence, a decentralized energy management system, based on multi‐agent systems, was developed for the efficient charging of electric vehicles, by expanding a state‐of‐the‐art fuzzy logic controller‐based energy management strategy, in combination with a charging power controller, based on fuzzy cognitive maps. According to the authors' best knowledge, this is the first time that fuzzy cognitive maps theory is introduced in EVs' charging management problems. The performance of the proposed multi‐agent decentralized energy management system presented significant reduction in the investment costs of the microgrid, as compared with the use of a sole fuzzy logic controller‐based energy management strategy. The total cost of the microgrid for a 20‐year investment period is decreased by approximately 8.8%. Furthermore, the incorporation of the fuzzy cognitive maps‐based charging power controller leads to a significant amount of chargeable EVs. The mean chargeable EVs increased by 31%. Finally, the proposed energy management system reduces the peak load and load variances approximately 17% and 29%, respectively, without shifting and delaying the charging of the EVs. Hence, the proposed novel charging management system offers an intelligence approach for islanding distribution grids including the high penetration of electric vehicles by presenting operational and financial benefits. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Energy Research is the property of Wiley-Blackwell 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 |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 155325005 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: An intelligent decentralized energy management strategy for the optimal electric vehicles' charging in low‐voltage islanded microgrids. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Boglou%2C+Vasileios%22">Boglou, Vasileios</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> vboglou@ee.duth.gr</i><br /><searchLink fieldCode="AR" term="%22Karavas%2C+Christos‐Spyridon%22">Karavas, Christos‐Spyridon</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Karlis%2C+Athanasios%22">Karlis, Athanasios</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Arvanitis%2C+Konstantinos%22">Arvanitis, Konstantinos</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Energy+Research%22">International Journal of Energy Research</searchLink>. Mar2022, Vol. 46 Issue 3, p2988-3016. 29p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Microgrids%22">Microgrids</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+power+system+reliability%22">Electric power system reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+management%22">Energy management</searchLink><br /><searchLink fieldCode="DE" term="%22Hybrid+electric+vehicles%22">Hybrid electric vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+vehicles%22">Electric vehicles</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+power+consumption%22">Electric power consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Clean+energy%22">Clean energy</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+maps+%28Psychology%29%22">Cognitive maps (Psychology)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Summary: The expected significant growth in global electricity demand, followed by the adoption of green energy sources, led to the modernization of the energy distribution grids, such as the development of microgrids that can improve the reliability of the electric power system. Meanwhile, the increased integration of electric vehicles is expected to have a negative impact on power quality, normal operation, and investment costs of the microgrid. In this paper, a microgrid topology was studied for the islanded operation of a low‐voltage distribution network. The deployment of such energy management systems is essential to guarantee the safe and reliable operation of isolated microgrids. Hence, a decentralized energy management system, based on multi‐agent systems, was developed for the efficient charging of electric vehicles, by expanding a state‐of‐the‐art fuzzy logic controller‐based energy management strategy, in combination with a charging power controller, based on fuzzy cognitive maps. According to the authors' best knowledge, this is the first time that fuzzy cognitive maps theory is introduced in EVs' charging management problems. The performance of the proposed multi‐agent decentralized energy management system presented significant reduction in the investment costs of the microgrid, as compared with the use of a sole fuzzy logic controller‐based energy management strategy. The total cost of the microgrid for a 20‐year investment period is decreased by approximately 8.8%. Furthermore, the incorporation of the fuzzy cognitive maps‐based charging power controller leads to a significant amount of chargeable EVs. The mean chargeable EVs increased by 31%. Finally, the proposed energy management system reduces the peak load and load variances approximately 17% and 29%, respectively, without shifting and delaying the charging of the EVs. Hence, the proposed novel charging management system offers an intelligence approach for islanding distribution grids including the high penetration of electric vehicles by presenting operational and financial benefits. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Energy Research is the property of Wiley-Blackwell 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: 10.1002/er.7358 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 29 StartPage: 2988 Subjects: – SubjectFull: Microgrids Type: general – SubjectFull: Electric power system reliability Type: general – SubjectFull: Energy management Type: general – SubjectFull: Hybrid electric vehicles Type: general – SubjectFull: Electric vehicles Type: general – SubjectFull: Electric power consumption Type: general – SubjectFull: Clean energy Type: general – SubjectFull: Cognitive maps (Psychology) Type: general Titles: – TitleFull: An intelligent decentralized energy management strategy for the optimal electric vehicles' charging in low‐voltage islanded microgrids. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Boglou, Vasileios – PersonEntity: Name: NameFull: Karavas, Christos‐Spyridon – PersonEntity: Name: NameFull: Karlis, Athanasios – PersonEntity: Name: NameFull: Arvanitis, Konstantinos IsPartOfRelationships: – BibEntity: Dates: – D: 10 M: 03 Text: Mar2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 0363907X Numbering: – Type: volume Value: 46 – Type: issue Value: 3 Titles: – TitleFull: International Journal of Energy Research Type: main |
| ResultId | 1 |
