Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/22834
Title: Coordinated Operation of Electricity and Natural Gas Networks with Consideration of Congestion and Demand Response
Authors: Lai, CS
Yan, M
Li, X
Lai, LL
Xu, Y
Keywords: Coordinated operation;Natural gas network;Electrical network;Credit rank indicator
Issue Date: 28-May-2021
Publisher: MDPI
Citation: Lai, 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.
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>
URI: http://bura.brunel.ac.uk/handle/2438/22834
DOI: http://dx.doi.org/10.3390/app11114987
ISSN: 2076-3417
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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