An Optimal Regime of Energy Management for Smart Building Clusters With Electric Vehicles
Smart building clusters embedded with electric vehicles (EVs) have become a crucial system component in the process of the low-carbon and highly-efficient energy system transition. Effective utilization of the energy buffering capability of EVs is a promising solution to achieving a new optimal stat...
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Veröffentlicht in: | IEEE transactions on industrial informatics 2024-05, Vol.20 (5), p.7619-7629 |
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creator | Shi, Mengge Wang, Han Lyu, Cheng Dong, Qianyu Li, Xun Jia, Youwei |
description | Smart building clusters embedded with electric vehicles (EVs) have become a crucial system component in the process of the low-carbon and highly-efficient energy system transition. Effective utilization of the energy buffering capability of EVs is a promising solution to achieving a new optimal state in smart building energy management, which however casts a great challenge in tackling the intrinsic uncertainties of EVs. In this article, a novel optimal operating regime is proposed to facilitate the participation of SBC in the day-ahead energy and reserve ancillary service market. In considering that the unexpected departures of EV users can have a great impact on the energy scheduling of the charging stations, this article develops a segmented charging strategy for EVs in line with departure uncertainties. Moreover, a distributed peer-to-peer energy trading approach is designed, which is aimed at maximizing the benefits of smart buildings. To effectively solve the proposed operation problem, a fully distributed algorithm is proposed based on the alternating direction method of multipliers algorithm with a communication-less strategy. This algorithm enables multiple relevant parties to be effectively coordinated in the proposed regime. Extensive simulation results verify the effectiveness of the proposed operating regime and show the advantages of reducing the exchange power with the main grid and improving the convenience of EV users. |
doi_str_mv | 10.1109/TII.2024.3363059 |
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Effective utilization of the energy buffering capability of EVs is a promising solution to achieving a new optimal state in smart building energy management, which however casts a great challenge in tackling the intrinsic uncertainties of EVs. In this article, a novel optimal operating regime is proposed to facilitate the participation of SBC in the day-ahead energy and reserve ancillary service market. In considering that the unexpected departures of EV users can have a great impact on the energy scheduling of the charging stations, this article develops a segmented charging strategy for EVs in line with departure uncertainties. Moreover, a distributed peer-to-peer energy trading approach is designed, which is aimed at maximizing the benefits of smart buildings. To effectively solve the proposed operation problem, a fully distributed algorithm is proposed based on the alternating direction method of multipliers algorithm with a communication-less strategy. 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(IEEE) 2024</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c245t-f211cc777aa13005d8e5aae9d9d106c9799440dea9bbbd04223921fcd8b5dedb3</cites><orcidid>0000-0002-8200-9134 ; 0000-0001-6443-8034 ; 0000-0002-5520-1198 ; 0000-0001-5785-1373 ; 0000-0003-3071-5552</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10443251$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10443251$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Shi, Mengge</creatorcontrib><creatorcontrib>Wang, Han</creatorcontrib><creatorcontrib>Lyu, Cheng</creatorcontrib><creatorcontrib>Dong, Qianyu</creatorcontrib><creatorcontrib>Li, Xun</creatorcontrib><creatorcontrib>Jia, Youwei</creatorcontrib><title>An Optimal Regime of Energy Management for Smart Building Clusters With Electric Vehicles</title><title>IEEE transactions on industrial informatics</title><addtitle>TII</addtitle><description>Smart building clusters embedded with electric vehicles (EVs) have become a crucial system component in the process of the low-carbon and highly-efficient energy system transition. Effective utilization of the energy buffering capability of EVs is a promising solution to achieving a new optimal state in smart building energy management, which however casts a great challenge in tackling the intrinsic uncertainties of EVs. In this article, a novel optimal operating regime is proposed to facilitate the participation of SBC in the day-ahead energy and reserve ancillary service market. In considering that the unexpected departures of EV users can have a great impact on the energy scheduling of the charging stations, this article develops a segmented charging strategy for EVs in line with departure uncertainties. Moreover, a distributed peer-to-peer energy trading approach is designed, which is aimed at maximizing the benefits of smart buildings. To effectively solve the proposed operation problem, a fully distributed algorithm is proposed based on the alternating direction method of multipliers algorithm with a communication-less strategy. 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Extensive simulation results verify the effectiveness of the proposed operating regime and show the advantages of reducing the exchange power with the main grid and improving the convenience of EV users.</description><subject>Algorithms</subject><subject>Ancillary services</subject><subject>Clusters</subject><subject>Costs</subject><subject>Electric vehicle (EV)</subject><subject>Electric vehicle charging</subject><subject>Electric vehicles</subject><subject>Energy management</subject><subject>energy-reserve market</subject><subject>HVAC</subject><subject>Optimization</subject><subject>peer-to-peer (P2P)</subject><subject>Real-time systems</subject><subject>smart building</subject><subject>Smart buildings</subject><subject>Stochastic processes</subject><subject>Uncertainty</subject><issn>1551-3203</issn><issn>1941-0050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkD1PwzAQhi0EEqWwMzBYYk45fzX1WKoClYoqQQExRY59SVOlSbGTof8eV2Vguhue9z4eQm4ZjBgD_bBeLEYcuBwJMRag9BkZMC1ZAqDgPPZKsURwEJfkKoQtgEhB6AH5njZ0te-qnanpG5bVDmlb0HmDvjzQV9OYEnfYdLRoPX3fGd_Rx76qXdWUdFb3oUMf6FfVbei8Rtv5ytJP3FS2xnBNLgpTB7z5q0Py8TRfz16S5ep5MZsuE8ul6pKCM2ZtmqbGMBGPdRNUxqB22jEYW51qLSU4NDrPcweSc6E5K6yb5Mqhy8WQ3J_m7n3702Posm3b-yauzKIHzoEBm0QKTpT1bQgei2zv49P-kDHIjgKzKDA7Csz-BMbI3SlSIeI_XErBFRO_e9hsEw</recordid><startdate>20240501</startdate><enddate>20240501</enddate><creator>Shi, Mengge</creator><creator>Wang, Han</creator><creator>Lyu, Cheng</creator><creator>Dong, Qianyu</creator><creator>Li, Xun</creator><creator>Jia, Youwei</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | Algorithms Ancillary services Clusters Costs Electric vehicle (EV) Electric vehicle charging Electric vehicles Energy management energy-reserve market HVAC Optimization peer-to-peer (P2P) Real-time systems smart building Smart buildings Stochastic processes Uncertainty |
title | An Optimal Regime of Energy Management for Smart Building Clusters With Electric Vehicles |
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