 One-segment linearization modeling of electricity-gas system optimizationShiyuan Bao, Zhifang Yang, Lin Guo, Juan Yu and Wei Dai Energy, 2020, vol. 197, issue C Abstract: Linear models of energy systems are preferable in industries because linear optimization problems bring benefits in convergence, efficiency, and convenience for pricing. The nonlinear model of the natural-gas system is a major bottleneck for the fully-linear modeling of electricity-gas systems. In this paper, a one-segment linear gas flow model without the need of integer variables is presented. To facilitate the linear formulation of the gas flow model, a deep learning method is applied to predict the interval of the gas pressure. A special setting of the linearization interval is proposed, which avoids the influence of the range of the linearization interval on the optimal energy flow (OEF) solution. Based on the one-segment linear gas flow model, a fully-linear OEF model of the electricity-gas system is formulated. The efficiency of the proposed method is much improved compared with the traditional mixed integer linear programming approach. Keywords: Linear gas flow model; Deep learning; Cyclic and tree gas network; Optimal energy flow (OEF); Electricity-gas system (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:197:y:2020:i:c:s0360544220303376 DOI: 10.1016/j.energy.2020.117230 Access Statistics for this article Energy is currently edited by Henrik Lund and Mark J. Kaiser More articles in Energy from Elsevier |
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