Zhenzi Song, Xiuli Wang, Tianyang Zhao, Mohammad Reza Hesamzadeh, Tao Qian, Jing Huang, Xin Li
{"title":"Low-carbon power system operation with disperse carbon capture-transportation-utilization chain","authors":"Zhenzi Song, Xiuli Wang, Tianyang Zhao, Mohammad Reza Hesamzadeh, Tao Qian, Jing Huang, Xin Li","doi":"10.1049/gtd2.13184","DOIUrl":null,"url":null,"abstract":"<p>The carbon capture-transportation-utilization (C-CTU) chain strengthens the coupling between terminal energy consumption and renewable energy resources (RES), achieving carbon emission reduction in power generation sectors. However, the dynamic operation of the C-CTU chain and the uncertainties induced by RES output pose new challenges for the low-carbon operation. To address above challenges, the nonlinear dynamic operation model of C-CTU chain is first proposed in this study. It is further incorporated into the day-ahead operation scheme of the electricity-carbon integrated system considering the stochastic nature of wind power. This scheme is treated as a two-stage stochastic integer programming (TS-SIP) problem with a mixed-integer nonlinear recourse. By means of the polyhedral envelope-based linearization method, this recourse is reformulated into its linear counterpart. To further improve the computational performance of classical decomposition algorithms, a novel Benders decomposition framework with hybrid cutting plane strategies is proposed to obtain better feasible solutions within a limited time. Simulations are conducted on two power system test cases with the C-CTU chain. Numerical results indicate that the engagement of C-CTU chain promotes the low-carbon economic operation of the power system. Also, the proposed decomposition algorithm shows a superior solution capability to handle large-scale TS-SIP than state-of-the-art commercial solvers.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13184","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/gtd2.13184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
The carbon capture-transportation-utilization (C-CTU) chain strengthens the coupling between terminal energy consumption and renewable energy resources (RES), achieving carbon emission reduction in power generation sectors. However, the dynamic operation of the C-CTU chain and the uncertainties induced by RES output pose new challenges for the low-carbon operation. To address above challenges, the nonlinear dynamic operation model of C-CTU chain is first proposed in this study. It is further incorporated into the day-ahead operation scheme of the electricity-carbon integrated system considering the stochastic nature of wind power. This scheme is treated as a two-stage stochastic integer programming (TS-SIP) problem with a mixed-integer nonlinear recourse. By means of the polyhedral envelope-based linearization method, this recourse is reformulated into its linear counterpart. To further improve the computational performance of classical decomposition algorithms, a novel Benders decomposition framework with hybrid cutting plane strategies is proposed to obtain better feasible solutions within a limited time. Simulations are conducted on two power system test cases with the C-CTU chain. Numerical results indicate that the engagement of C-CTU chain promotes the low-carbon economic operation of the power system. Also, the proposed decomposition algorithm shows a superior solution capability to handle large-scale TS-SIP than state-of-the-art commercial solvers.