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Bi-level Integrated Electricity and Natural Gas System retrofit planning model considering Carbon Capture, Utilization and Storage

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APPLIED ENERGY 2025年 385卷

作者： Xuan, Ang Shen, Xinwei Luo, Yangfan Tsinghua Univ Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China

Integrated Electricity and Natural Gas System (IEGS) considers the interactions between electricity and natural gas systems with broad prospects in carbon emission mitigation to achieve the global low-carbon transition, which is an approachable pathway to tap the potential of different energy systems. Concurrently, advancements in technologies such as Carbon Capture, Utilization and Storage (CCUS), Gas-fired Power Generation (GPG), and Power to Gas (PtG) enable the integration of these two large systems, allowing for bi-directional energy flows. This paper proposes an original IEGS retrofit planning model, in which the traditional power plant/gas source (PP/GS) is retrofitted into the carbon capture power plant/carbon capture gas source (CCPP/CCGS) with CCUS and PtG/GPG, as well as the gas pipelines and electricity transmission lines, are considered. Additionally, the IEGS retrofit model employs a bi-level planning strategy to distinguish conflicts of interest between investors and investees. Furthermore, the reformulation and decomposition (R&D) algorithm is developed to tackle the complexities of the bi-level mixed-integer programming problem. Numerical results demonstrate the effectiveness and superiority of the proposed model, showcasing its potential for practical application. Finally, the study analyzes the efficient boundaries associated with carbon price/tax and carbon capture/storage cost, providing valuable insights for policymakers and stakeholders.

关键词： Integrated Electricity and Natural Gas System Bi-level mixed integer optimization reformulation and decomposition algorithm Sensitivity analysis Carbon Capture, Utilization and Storage

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Stackelberg-game-based modeling and optimization for supply chain design and operations: A mixed integer bilevel programming framework

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COMPUTERS & CHEMICAL ENGINEERING 2017年 102卷 81-95页

作者： Yue, Dajun You, Fengqi Northwestern Univ Dept Chem & Biol Engn Evanston IL 60208 USA Cornell Univ Robert Frederick Smith Sch Chem & Biomol Engn Ithaca NY 14853 USA

While Stackelberg leader-follower games and bilevel programming have become increasingly prevalent in game-theoretic modeling and optimization of decentralized supply chains, existing models can only handle linear programming or quadratic programming followers' problems. When discrete decisions are involved in the follower's problem, the resulting lower-level mixed-integer program prohibits direct transformation of the bilevel program into a single-level mathematical program using the MKT conditions. To address this challenge, we propose a mixed-integer bilevel programming (MIBP) modeling framework and solution algorithm for optimal supply chain design and operations, where the follower is allowed to have discrete decisions, e.g. facility location, technology selection, and opening/shutting-down of production lines. A reformulation-and-decomposition algorithm is developed for global optimization of the MIBP problems. A case study on an integrated forestry and biofuel supply chain is presented to demonstrate the application, along with comparisons to conventional centralized modeling and optimization methods. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Supply chain optimization Game theory Mixed-integer bilevel programming reformulation and decomposition algorithm Biofuel

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