A Robust Decentralized Peer-to-Peer Energy Trading in Community of Flexible Microgrids
This article proposes a novel platform for microgrid (MG) prosumers that can actively trade energy with the power grid and each other directly. This platform provides Peer-to-Peer (P2P) energy trading among MG prosumers to achieve a win-win outcome in the presence of emerging energy resources, such...
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Veröffentlicht in: | IEEE systems journal 2023-03, Vol.17 (1), p.640-651 |
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description | This article proposes a novel platform for microgrid (MG) prosumers that can actively trade energy with the power grid and each other directly. This platform provides Peer-to-Peer (P2P) energy trading among MG prosumers to achieve a win-win outcome in the presence of emerging energy resources, such as electric vehicles (EVs), energy storage systems (ESSs), and demand response programs (DRPs). P2P energy trading, from the power system perspective, can facilitate energy balance locally and self-sufficiency. Despite the conventional noncooperative game that players act individually, prosumers can cooperate in exchanging energy and reaping economic benefits in the proposed model. To this end, a bargaining cooperative game is adopted due to MGs autonomy and self-interest. Besides, to avoid prosumers' private data launching, the fast-alternating direction method of multipliers is introduced to solve MGs' energy management problem in a decentralized manner. A robust optimization method is also applied to manage electricity market uncertainty, allowing MGs operators to decide how much risk they want to consider by adjusting the uncertainty budget parameter. The numerical results show that MGs can actively trade with each other and achieve economic benefits. Moreover, many of the utilized technologies such as ESS, DRP, and EVs assist MGs in sharing more energy with each other. |
doi_str_mv | 10.1109/JSYST.2022.3197412 |
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This platform provides Peer-to-Peer (P2P) energy trading among MG prosumers to achieve a win-win outcome in the presence of emerging energy resources, such as electric vehicles (EVs), energy storage systems (ESSs), and demand response programs (DRPs). P2P energy trading, from the power system perspective, can facilitate energy balance locally and self-sufficiency. Despite the conventional noncooperative game that players act individually, prosumers can cooperate in exchanging energy and reaping economic benefits in the proposed model. To this end, a bargaining cooperative game is adopted due to MGs autonomy and self-interest. Besides, to avoid prosumers' private data launching, the fast-alternating direction method of multipliers is introduced to solve MGs' energy management problem in a decentralized manner. A robust optimization method is also applied to manage electricity market uncertainty, allowing MGs operators to decide how much risk they want to consider by adjusting the uncertainty budget parameter. The numerical results show that MGs can actively trade with each other and achieve economic benefits. Moreover, many of the utilized technologies such as ESS, DRP, and EVs assist MGs in sharing more energy with each other.</description><identifier>ISSN: 1932-8184</identifier><identifier>EISSN: 1937-9234</identifier><identifier>DOI: 10.1109/JSYST.2022.3197412</identifier><identifier>CODEN: ISJEB2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Bargaining cooperative game ; Costs ; decentralized energy trading ; Distributed generation ; Economic models ; Electric power systems ; Electric vehicles ; Electricity distribution ; Energy ; Energy management ; Energy sources ; Energy storage ; Game theory ; Games ; Mathematical models ; Microgrids ; Optimization ; Parameter uncertainty ; Peer-to-peer computing ; peer-to-peer energy trading ; Power systems ; robust optimization ; Robustness (mathematics) ; Storage systems ; transactive energy ; Uncertainty</subject><ispartof>IEEE systems journal, 2023-03, Vol.17 (1), p.640-651</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c295t-cce322c196fc1e22a445b7dc05995a605e22419980ecb381b8e37518b748f0a93</citedby><cites>FETCH-LOGICAL-c295t-cce322c196fc1e22a445b7dc05995a605e22419980ecb381b8e37518b748f0a93</cites><orcidid>0000-0002-7230-7648 ; 0000-0002-0255-8353 ; 0000-0002-8793-7642</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9880548$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,793,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9880548$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Saatloo, Amin Mansour</creatorcontrib><creatorcontrib>Mirzaei, Mohammad Amin</creatorcontrib><creatorcontrib>Mohammadi-Ivatloo, Behnam</creatorcontrib><title>A Robust Decentralized Peer-to-Peer Energy Trading in Community of Flexible Microgrids</title><title>IEEE systems journal</title><addtitle>JSYST</addtitle><description>This article proposes a novel platform for microgrid (MG) prosumers that can actively trade energy with the power grid and each other directly. This platform provides Peer-to-Peer (P2P) energy trading among MG prosumers to achieve a win-win outcome in the presence of emerging energy resources, such as electric vehicles (EVs), energy storage systems (ESSs), and demand response programs (DRPs). P2P energy trading, from the power system perspective, can facilitate energy balance locally and self-sufficiency. Despite the conventional noncooperative game that players act individually, prosumers can cooperate in exchanging energy and reaping economic benefits in the proposed model. To this end, a bargaining cooperative game is adopted due to MGs autonomy and self-interest. Besides, to avoid prosumers' private data launching, the fast-alternating direction method of multipliers is introduced to solve MGs' energy management problem in a decentralized manner. A robust optimization method is also applied to manage electricity market uncertainty, allowing MGs operators to decide how much risk they want to consider by adjusting the uncertainty budget parameter. The numerical results show that MGs can actively trade with each other and achieve economic benefits. Moreover, many of the utilized technologies such as ESS, DRP, and EVs assist MGs in sharing more energy with each other.</description><subject>Bargaining cooperative game</subject><subject>Costs</subject><subject>decentralized energy trading</subject><subject>Distributed generation</subject><subject>Economic models</subject><subject>Electric power systems</subject><subject>Electric vehicles</subject><subject>Electricity distribution</subject><subject>Energy</subject><subject>Energy management</subject><subject>Energy sources</subject><subject>Energy storage</subject><subject>Game theory</subject><subject>Games</subject><subject>Mathematical models</subject><subject>Microgrids</subject><subject>Optimization</subject><subject>Parameter uncertainty</subject><subject>Peer-to-peer computing</subject><subject>peer-to-peer energy trading</subject><subject>Power systems</subject><subject>robust optimization</subject><subject>Robustness (mathematics)</subject><subject>Storage systems</subject><subject>transactive energy</subject><subject>Uncertainty</subject><issn>1932-8184</issn><issn>1937-9234</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kFtLAzEQhYMoWKt_QF8CPm_NtUkeS229UFFsFXwKu9nZkrLdrckuWH-92ws-nWE4Z-bwIXRNyYBSYu6e51_zxYARxgacGiUoO0E9arhKDOPidD-zRFMtztFFjCtCpJbK9NDnCL_XWRsbfA8Oqiakpf-FHL8BhKSpk53iSQVhucWLkOa-WmJf4XG9XreVb7a4LvC0hB-flYBfvAv1Mvg8XqKzIi0jXB21jz6mk8X4MZm9PjyNR7PEMSObxDngjDlqhoWjwFgqhMxU7og0RqZDIrudoMZoAi7jmmYauJJUZ0rogqSG99Ht4e4m1N8txMau6jZU3UvLlDJDpbjRnYsdXF29GAMUdhP8Og1bS4nd8bN7fnbHzx75daGbQ8gDwH_AaE2k0PwPT2priw</recordid><startdate>202303</startdate><enddate>202303</enddate><creator>Saatloo, Amin Mansour</creator><creator>Mirzaei, Mohammad Amin</creator><creator>Mohammadi-Ivatloo, Behnam</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><orcidid>https://orcid.org/0000-0002-7230-7648</orcidid><orcidid>https://orcid.org/0000-0002-0255-8353</orcidid><orcidid>https://orcid.org/0000-0002-8793-7642</orcidid></search><sort><creationdate>202303</creationdate><title>A Robust Decentralized Peer-to-Peer Energy Trading in Community of Flexible Microgrids</title><author>Saatloo, Amin Mansour ; Mirzaei, Mohammad Amin ; Mohammadi-Ivatloo, Behnam</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c295t-cce322c196fc1e22a445b7dc05995a605e22419980ecb381b8e37518b748f0a93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Bargaining cooperative game</topic><topic>Costs</topic><topic>decentralized energy trading</topic><topic>Distributed generation</topic><topic>Economic models</topic><topic>Electric power systems</topic><topic>Electric vehicles</topic><topic>Electricity distribution</topic><topic>Energy</topic><topic>Energy management</topic><topic>Energy sources</topic><topic>Energy storage</topic><topic>Game theory</topic><topic>Games</topic><topic>Mathematical models</topic><topic>Microgrids</topic><topic>Optimization</topic><topic>Parameter uncertainty</topic><topic>Peer-to-peer computing</topic><topic>peer-to-peer energy trading</topic><topic>Power systems</topic><topic>robust optimization</topic><topic>Robustness (mathematics)</topic><topic>Storage systems</topic><topic>transactive energy</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Saatloo, Amin Mansour</creatorcontrib><creatorcontrib>Mirzaei, Mohammad Amin</creatorcontrib><creatorcontrib>Mohammadi-Ivatloo, Behnam</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library</collection><collection>CrossRef</collection><jtitle>IEEE systems journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Saatloo, Amin Mansour</au><au>Mirzaei, Mohammad Amin</au><au>Mohammadi-Ivatloo, Behnam</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Robust Decentralized Peer-to-Peer Energy Trading in Community of Flexible Microgrids</atitle><jtitle>IEEE systems journal</jtitle><stitle>JSYST</stitle><date>2023-03</date><risdate>2023</risdate><volume>17</volume><issue>1</issue><spage>640</spage><epage>651</epage><pages>640-651</pages><issn>1932-8184</issn><eissn>1937-9234</eissn><coden>ISJEB2</coden><abstract>This article proposes a novel platform for microgrid (MG) prosumers that can actively trade energy with the power grid and each other directly. 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A robust optimization method is also applied to manage electricity market uncertainty, allowing MGs operators to decide how much risk they want to consider by adjusting the uncertainty budget parameter. The numerical results show that MGs can actively trade with each other and achieve economic benefits. Moreover, many of the utilized technologies such as ESS, DRP, and EVs assist MGs in sharing more energy with each other.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSYST.2022.3197412</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-7230-7648</orcidid><orcidid>https://orcid.org/0000-0002-0255-8353</orcidid><orcidid>https://orcid.org/0000-0002-8793-7642</orcidid></addata></record> |
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subjects | Bargaining cooperative game Costs decentralized energy trading Distributed generation Economic models Electric power systems Electric vehicles Electricity distribution Energy Energy management Energy sources Energy storage Game theory Games Mathematical models Microgrids Optimization Parameter uncertainty Peer-to-peer computing peer-to-peer energy trading Power systems robust optimization Robustness (mathematics) Storage systems transactive energy Uncertainty |
title | A Robust Decentralized Peer-to-Peer Energy Trading in Community of Flexible Microgrids |
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