Expansion Planning of Soft Open Points Based Distribution System Considering EV Traffic Flow
Regarding distribution systems coupled with transportation networks, this study proposes an expansion planning approach to minimize various costs with respect to soft open point (SOP) based distribution system and electric vehicle (EV) navigation. An energy consumption model of EV that considers tra...
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Veröffentlicht in: | IEEE transactions on industry applications 2024-01, Vol.60 (1), p.1-11 |
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description | Regarding distribution systems coupled with transportation networks, this study proposes an expansion planning approach to minimize various costs with respect to soft open point (SOP) based distribution system and electric vehicle (EV) navigation. An energy consumption model of EV that considers traffic flow is developed to analyze charging behaviors of EVs. Subsequently, the EV average speed and related energy consumption is estimated to generate optimal charging routes. The proposed model of the EV energy consumption can help to minimize the cost of navigating EVs along the transportation network according to the traffic flow. Referring to the distribution system, the total cost associated with the investment and maintenance of network assets as well as subsequent operations is optimized. Hereafter, an expansion planning model of distribution system considering EV navigation is established. A relaxation approach is employed through which the prescribed nonconvex mixed-integer nonlinear planning model is converted into the form of mixed-integer second order cone programming that can be efficiently solved by commonly used solvers. A 54-bus distribution system coupled with a 35-node transportation network is employed in the case study section to verify the effectiveness of the proposed method. The rationality of considering SOP deployment and EV navigation is validated. |
doi_str_mv | 10.1109/TIA.2023.3293496 |
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An energy consumption model of EV that considers traffic flow is developed to analyze charging behaviors of EVs. Subsequently, the EV average speed and related energy consumption is estimated to generate optimal charging routes. The proposed model of the EV energy consumption can help to minimize the cost of navigating EVs along the transportation network according to the traffic flow. Referring to the distribution system, the total cost associated with the investment and maintenance of network assets as well as subsequent operations is optimized. Hereafter, an expansion planning model of distribution system considering EV navigation is established. A relaxation approach is employed through which the prescribed nonconvex mixed-integer nonlinear planning model is converted into the form of mixed-integer second order cone programming that can be efficiently solved by commonly used solvers. A 54-bus distribution system coupled with a 35-node transportation network is employed in the case study section to verify the effectiveness of the proposed method. The rationality of considering SOP deployment and EV navigation is validated.</description><identifier>ISSN: 0093-9994</identifier><identifier>EISSN: 1939-9367</identifier><identifier>DOI: 10.1109/TIA.2023.3293496</identifier><identifier>CODEN: ITIACR</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Charging ; Costs ; Distribution system planning ; Electric vehicles ; Energy consumption ; Estimation ; EV navigation ; Mixed integer ; Navigation ; Planning ; soft open points ; Substations ; Traffic flow ; Transportation ; transportation network ; Transportation networks</subject><ispartof>IEEE transactions on industry applications, 2024-01, Vol.60 (1), p.1-11</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c245t-7c2884971e3b3910a8b44597c865d35b1b449333ffb710ef4efe7be616a15c233</cites><orcidid>0000-0003-2786-0601 ; 0000-0001-9116-7487 ; 0000-0003-3580-1564</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10177257$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10177257$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Shen, Yichen</creatorcontrib><creatorcontrib>Zhang, Shenxi</creatorcontrib><creatorcontrib>Ding, Maosheng</creatorcontrib><creatorcontrib>Cheng, Haozhong</creatorcontrib><creatorcontrib>Li, Canbing</creatorcontrib><creatorcontrib>Liu, Dundun</creatorcontrib><title>Expansion Planning of Soft Open Points Based Distribution System Considering EV Traffic Flow</title><title>IEEE transactions on industry applications</title><addtitle>TIA</addtitle><description>Regarding distribution systems coupled with transportation networks, this study proposes an expansion planning approach to minimize various costs with respect to soft open point (SOP) based distribution system and electric vehicle (EV) navigation. An energy consumption model of EV that considers traffic flow is developed to analyze charging behaviors of EVs. Subsequently, the EV average speed and related energy consumption is estimated to generate optimal charging routes. The proposed model of the EV energy consumption can help to minimize the cost of navigating EVs along the transportation network according to the traffic flow. Referring to the distribution system, the total cost associated with the investment and maintenance of network assets as well as subsequent operations is optimized. Hereafter, an expansion planning model of distribution system considering EV navigation is established. A relaxation approach is employed through which the prescribed nonconvex mixed-integer nonlinear planning model is converted into the form of mixed-integer second order cone programming that can be efficiently solved by commonly used solvers. A 54-bus distribution system coupled with a 35-node transportation network is employed in the case study section to verify the effectiveness of the proposed method. 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subjects | Charging Costs Distribution system planning Electric vehicles Energy consumption Estimation EV navigation Mixed integer Navigation Planning soft open points Substations Traffic flow Transportation transportation network Transportation networks |
title | Expansion Planning of Soft Open Points Based Distribution System Considering EV Traffic Flow |
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