Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/22834
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dc.contributor.authorLai, CS-
dc.contributor.authorYan, M-
dc.contributor.authorLi, X-
dc.contributor.authorLai, LL-
dc.contributor.authorXu, Y-
dc.date.accessioned2021-06-12T13:57:02Z-
dc.date.available2021-06-12T13:57:02Z-
dc.date.issued2021-05-28-
dc.identifier.citationLai, Chun S.; Yan, Mengxuan; Li, Xuecong; Lai, Loi L.; Xu, Yang. 2021. "Coordinated Operation of Electricity and Natural Gas Networks with Consideration of Congestion and Demand Response" Appl. Sci. 11, no. 11: 4987.en_US
dc.identifier.issn2076-3417-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/22834-
dc.description.abstract<jats:p>This work presents a new coordinated operation (CO) framework for electricity and natural gas networks, considering network congestions and demand response. Credit rank (CR) indicator of coupling units is introduced, and gas consumption constraints information of natural gas fired units (NGFUs) is given. Natural gas network operator (GNO) will deliver this information to an electricity network operator (ENO). A major advantage of this operation framework is that no frequent information interaction between GNO and ENO is needed. The entire framework contains two participants and three optimization problems, namely, GNO optimization sub-problem-A, GNO optimization sub-problem-B, and ENO optimization sub-problem. Decision sequence changed from traditional ENO-GNO-ENO to GNO-ENO-GNO in this novel framework. Second-order cone (SOC) relaxation is applied to ENO optimization sub-problem. The original problem is reformulated as a mixed-integer second-order cone programming (MISOCP) problem. For GNO optimization sub-problem, an improved sequential cone programming (SCP) method is applied based on SOC relaxation and the original sub-problem is converted to MISOCP problem. A benchmark 6-node natural gas system and 6-bus electricity system is used to illustrate the effectiveness of the proposed framework. Considering pipeline congestion, CO, with demand response, can reduce the total cost of an electricity network by 1.19%, as compared to −0.48% using traditional decentralized operation with demand response.</jats:p>en_US
dc.description.sponsorshipDepartment of Finance and Education of Guangdong Province 2016 [202]: Key Discipline Construction Program, China; and the Education Department of Guangdong Province: New and Integrated Energy System Theory and Technology Research Groupen_US
dc.format.extent4987 - 4987-
dc.languageen-
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectCoordinated operationen_US
dc.subjectNatural gas networken_US
dc.subjectElectrical networken_US
dc.subjectCredit rank indicatoren_US
dc.titleCoordinated Operation of Electricity and Natural Gas Networks with Consideration of Congestion and Demand Responseen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.3390/app11114987-
dc.relation.isPartOfApplied Sciences-
pubs.issue11-
pubs.publication-statusPublished online-
pubs.volume11-
dc.identifier.eissn2076-3417-
Appears in Collections:Dept of Electronic and Electrical Engineering Research Papers

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