Resilient Topology Design for EV Charging Network Based on Percolation-Fractal Analytics
This letter proposes a complex network theory based analytical model for resilient topology design of electric vehicle charging network (EVCN). In particular, percolation-fractal (PF) analytics is adopted in the process of network feature extraction, through which multiple tailor-made indices are co...
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| Veröffentlicht in: | IEEE transactions on smart grid 2024-05, Vol.15 (3), p.3341-3344 |
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| creator | Dong, Qianyu Zhou, Guanyu Xu, Zhao Jia, Youwei |
| description | This letter proposes a complex network theory based analytical model for resilient topology design of electric vehicle charging network (EVCN). In particular, percolation-fractal (PF) analytics is adopted in the process of network feature extraction, through which multiple tailor-made indices are constructed to reflect the topological properties of EVCN. In evaluating the topological resilience, a novel metric is proposed by jointly considering the correlation between load loss and topology properties. On top of this, an EVCN planning model is developed by optimally locating charging stations from network perspective. According to preliminary case studies, this gives rise to an average 22.8% resilience increase at the sacrifice of 3.7% loss in system service ability. |
| doi_str_mv | 10.1109/TSG.2024.3373260 |
| format | Article |
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In particular, percolation-fractal (PF) analytics is adopted in the process of network feature extraction, through which multiple tailor-made indices are constructed to reflect the topological properties of EVCN. In evaluating the topological resilience, a novel metric is proposed by jointly considering the correlation between load loss and topology properties. On top of this, an EVCN planning model is developed by optimally locating charging stations from network perspective. 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According to preliminary case studies, this gives rise to an average 22.8% resilience increase at the sacrifice of 3.7% loss in system service ability.</description><subject>charging station locating</subject><subject>Charging stations</subject><subject>Complex networks</subject><subject>Costs</subject><subject>Electric vehicle charging</subject><subject>electric vehicles</subject><subject>Feature extraction</subject><subject>Fractal analysis</subject><subject>Interconnected power-transportation network</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Percolation</subject><subject>Planning</subject><subject>Power system dynamics</subject><subject>Resilience</subject><subject>resilience analysis</subject><subject>Topology</subject><issn>1949-3053</issn><issn>1949-3061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkEtLAzEUhYMoWGr3LlwEXE_NazLJslZbhaKiVdyFTCYZp46TmkyR_ntTWsS7uC_OuVw-AM4xGmOM5NXyZT4miLAxpQUlHB2BAZZMZhRxfPzX5_QUjGJcoRSUUk7kALw_29i0je16uPRr3_p6C2_Squ6g8wHevsHphw5109XwwfY_PnzCax1tBX0Hn2wwvtV947tsFrTpdQsnnW63fWPiGThxuo12dKhD8Dq7XU7vssXj_H46WWSGsLzPJMkFqwrMS4dKgVyVas6lE0xQJ0hhywKVu8wJE8ZQiTnBtkijq4zTFR2Cy_3ddfDfGxt7tfKbkL6IiiLGklqKIqnQXmWCjzFYp9ah-dJhqzBSO4QqIVQ7hOqAMFku9pbGWvtPznJJKKa_IeVsSw</recordid><startdate>20240501</startdate><enddate>20240501</enddate><creator>Dong, Qianyu</creator><creator>Zhou, Guanyu</creator><creator>Xu, Zhao</creator><creator>Jia, Youwei</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-3071-5552</orcidid><orcidid>https://orcid.org/0000-0003-4480-7394</orcidid></search><sort><creationdate>20240501</creationdate><title>Resilient Topology Design for EV Charging Network Based on Percolation-Fractal Analytics</title><author>Dong, Qianyu ; Zhou, Guanyu ; Xu, Zhao ; Jia, Youwei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c245t-92584d716bf0b80fdbf0569f8483f827eb70b7eb76248cc391621e7762fdcfad3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>charging station locating</topic><topic>Charging stations</topic><topic>Complex networks</topic><topic>Costs</topic><topic>Electric vehicle charging</topic><topic>electric vehicles</topic><topic>Feature extraction</topic><topic>Fractal analysis</topic><topic>Interconnected power-transportation network</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Percolation</topic><topic>Planning</topic><topic>Power system dynamics</topic><topic>Resilience</topic><topic>resilience analysis</topic><topic>Topology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dong, Qianyu</creatorcontrib><creatorcontrib>Zhou, Guanyu</creatorcontrib><creatorcontrib>Xu, Zhao</creatorcontrib><creatorcontrib>Jia, Youwei</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on smart grid</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dong, Qianyu</au><au>Zhou, Guanyu</au><au>Xu, Zhao</au><au>Jia, Youwei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Resilient Topology Design for EV Charging Network Based on Percolation-Fractal Analytics</atitle><jtitle>IEEE transactions on smart grid</jtitle><stitle>TSG</stitle><date>2024-05-01</date><risdate>2024</risdate><volume>15</volume><issue>3</issue><spage>3341</spage><epage>3344</epage><pages>3341-3344</pages><issn>1949-3053</issn><eissn>1949-3061</eissn><coden>ITSGBQ</coden><abstract>This letter proposes a complex network theory based analytical model for resilient topology design of electric vehicle charging network (EVCN). 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| subjects | charging station locating Charging stations Complex networks Costs Electric vehicle charging electric vehicles Feature extraction Fractal analysis Interconnected power-transportation network Mathematical analysis Mathematical models Percolation Planning Power system dynamics Resilience resilience analysis Topology |
| title | Resilient Topology Design for EV Charging Network Based on Percolation-Fractal Analytics |
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