IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v331y2023ics030626192201683x.html
   My bibliography  Save this article

Two-stage distributionally robust optimization model of integrated energy system group considering energy sharing and carbon transfer

Author

Listed:
  • Fan, Wei
  • Ju, Liwei
  • Tan, Zhongfu
  • Li, Xiangguang
  • Zhang, Amin
  • Li, Xudong
  • Wang, Yueping

Abstract

Due to the small scale and few functions of the single integrated energy system, the absorption capacity of wind turbine and photovoltaic is limited, the ability to cope with uncertainties is weak, and the space for optimal allocation of resources is limited. To solve the coordination problem of robustness, economy, environmental protection and efficiency, this paper forms an integrated energy system group (IESG) by means of energy sharing and carbon transfer, and innovatively proposes a two-stage distributionally robust optimization model (TSDRO) based on kernel density estimation (KDE) and Wasserstein metric. Firstly, the structure of IESG with carbon capture, utilization, and storage-power-to-gas (CCUS-P2G) system is introduced. Then, the nonparametric KDE method is applied to fit the probability density functions of the forecast power error of wind turbine and photovoltaic. Wasserstein metric is used to characterize the fuzzy uncertainty set of distributions. The cumulative distribution function of KDE is taken as the center, and the obtained distance is taken as the radius to form the Wasserstein ball of probability distribution. Based on affinely adjustable policy, a correlation model of real-time variables with respect to day-ahead variables is established. Finally, according to the dual theory and convex optimization theory, the TSDRO model is reformulated into a solvable model. The simulation results show that: (1) energy sharing and carbon transfer can improve the ability of IESG to cope with uncertainty and expand the boundary of resource optimal allocation, and the minimum expected operating cost under the worst distribution is $ 40,259.94. (2) CCUS-P2G system strengthens the synergistic relationship between electricity and carbon and reduces the carbon emission of the system by 128.2 t. (3) After testing, the results obtained by nonparametric KDE are closer to the true distribution and more objective. (4) The TSDRO model is data-driven and has the advantages of high solving efficiency and low decision-making conservatism. The solution time of the TSDRO model is 73.03 % less than that of the stochastic optimization model, and the operation cost is 1.69 % less than that of the robust optimization model, which achieves the balance of economy, robustness and environmental protection of IESG.

Suggested Citation

  • Fan, Wei & Ju, Liwei & Tan, Zhongfu & Li, Xiangguang & Zhang, Amin & Li, Xudong & Wang, Yueping, 2023. "Two-stage distributionally robust optimization model of integrated energy system group considering energy sharing and carbon transfer," Applied Energy, Elsevier, vol. 331(C).
    • Handle: RePEc:eee:appene:v:331:y:2023:i:c:s030626192201683x
    DOI: 10.1016/j.apenergy.2022.120426
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192201683X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.120426?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Rutian & Wen, Xiangyun & Wang, Xiuyun & Fu, Yanbo & Zhang, Yu, 2022. "Low carbon optimal operation of integrated energy system based on carbon capture technology, LCA carbon emissions and ladder-type carbon trading," Applied Energy, Elsevier, vol. 311(C).
    2. Wang, Yuwei & Yang, Yuanjuan & Fei, Haoran & Song, Minghao & Jia, Mengyao, 2022. "Wasserstein and multivariate linear affine based distributionally robust optimization for CCHP-P2G scheduling considering multiple uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    3. Janzen, Ryan & Davis, Matthew & Kumar, Amit, 2020. "Evaluating long-term greenhouse gas mitigation opportunities through carbon capture, utilization, and storage in the oil sands," Energy, Elsevier, vol. 209(C).
    4. Edmonds, James & Nichols, Christopher & Adamantiades, Misha & Bistline, John & Huster, Jonathan & Iyer, Gokul & Johnson, Nils & Patel, Pralit & Showalter, Sharon & Victor, Nadja & Waldhoff, Stephanie , 2020. "Could congressionally mandated incentives lead to deployment of large-scale CO2 capture, facilities for enhanced oil recovery CO2 markets and geologic CO2 storage?," Energy Policy, Elsevier, vol. 146(C).
    5. Fan, Wei & Tan, Zhongfu & Li, Fanqi & Zhang, Amin & Ju, Liwei & Wang, Yuwei & De, Gejirifu, 2023. "A two-stage optimal scheduling model of integrated energy system based on CVaR theory implementing integrated demand response," Energy, Elsevier, vol. 263(PC).
    6. Wu, Min & Xu, Jiazhu & Zeng, Linjun & Li, Chang & Liu, Yuxing & Yi, Yuqin & Wen, Ming & Jiang, Zhuohan, 2022. "Two-stage robust optimization model for park integrated energy system based on dynamic programming," Applied Energy, Elsevier, vol. 308(C).
    7. Zakaria, A. & Ismail, Firas B. & Lipu, M.S. Hossain & Hannan, M.A., 2020. "Uncertainty models for stochastic optimization in renewable energy applications," Renewable Energy, Elsevier, vol. 145(C), pages 1543-1571.
    8. Wang, Nan & Akimoto, Keigo & Nemet, Gregory F., 2021. "What went wrong? Learning from three decades of carbon capture, utilization and sequestration (CCUS) pilot and demonstration projects," Energy Policy, Elsevier, vol. 158(C).
    9. Niu, Dongxiao & Sun, Lijie & Yu, Min & Wang, Keke, 2022. "Point and interval forecasting of ultra-short-term wind power based on a data-driven method and hybrid deep learning model," Energy, Elsevier, vol. 254(PA).
    10. Yang, Ting & Zhao, Liyuan & Li, Wei & Zomaya, Albert Y., 2021. "Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning," Energy, Elsevier, vol. 235(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhao, Naixin & Gu, Wenbo & Zheng, Zipeng & Ma, Tao, 2023. "Multi-objective bi-level planning of the integrated energy system considering uncertain user loads and carbon emission during the equipment manufacturing process," Renewable Energy, Elsevier, vol. 216(C).
    2. Fan, Wei & Fan, Ying & Yao, Xing & Yi, Bowen & Jiang, Dalin & Wu, Lin, 2024. "Distributed transaction optimization model of multi-integrated energy systems based on nash negotiation," Renewable Energy, Elsevier, vol. 225(C).
    3. Xu, Jing & Wang, Xiaoying & Gu, Yujiong & Ma, Suxia, 2023. "A data-based day-ahead scheduling optimization approach for regional integrated energy systems with varying operating conditions," Energy, Elsevier, vol. 283(C).
    4. Ju, Liwei & Bai, Xiping & Li, Gen & Gan, Wei & Qi, Xin & Ye, Fan, 2024. "Two-stage robust transaction optimization model and benefit allocation strategy for new energy power stations with shared energy storage considering green certificate and virtual energy storage mode," Applied Energy, Elsevier, vol. 362(C).
    5. Guan, Zhimin & Lu, Chunyan & Li, Yiming & Wang, Jiangjiang, 2023. "Chance-constrained optimization of hybrid solar combined cooling, heating and power system considering energetic, economic, environmental, and flexible performances," Renewable Energy, Elsevier, vol. 212(C), pages 908-920.
    6. Xiong, Houbo & Zhou, Yue & Guo, Chuangxin & Ding, Yi & Luo, Fengji, 2023. "Multi-stage risk-based assessment for wind energy accommodation capability: A robust and non-anticipative method," Applied Energy, Elsevier, vol. 350(C).
    7. Jiyong Li & Zeyi Hua & Lin Tian & Peiwen Chen & Hao Dong, 2024. "Optimal Capacity Allocation for Life Cycle Multiobjective Integrated Energy Systems Considering Capacity Tariffs and Eco-Indicator 99," Sustainability, MDPI, vol. 16(20), pages 1-22, October.
    8. Li, Weiwei & Qian, Tong & Zhao, Wei & Huang, Wenwei & Zhang, Yin & Xie, Xuehua & Tang, Wenhu, 2023. "Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss," Applied Energy, Elsevier, vol. 350(C).
    9. Yang, Lihua & Wu, Xiao, 2024. "Net-zero carbon configuration approach for direct air carbon capture based integrated energy system considering dynamic characteristics of CO2 adsorption and desorption," Applied Energy, Elsevier, vol. 358(C).
    10. Du, Yida & Li, Xiangguang & Liang, Yan & Tan, Zhongfu, 2024. "Two-stage multi-objective distributionally robust optimization of the electricity-hydrogen coupling system under multiple markets," Energy, Elsevier, vol. 303(C).
    11. Liu, Dewen & Luo, Zhao & Qin, Jinghui & Wang, Hua & Wang, Gang & Li, Zhao & Zhao, Weijie & Shen, Xin, 2023. "Low-carbon dispatch of multi-district integrated energy systems considering carbon emission trading and green certificate trading," Renewable Energy, Elsevier, vol. 218(C).
    12. Zhang, Liu & Zhang, Kaitian & Zheng, Zhong & Chai, Yi & Lian, Xiaoyuan & Zhang, Kai & Xu, Zhaojun & Chen, Sujun, 2023. "Two-stage distributionally robust integrated scheduling of oxygen distribution and steelmaking-continuous casting in steel enterprises," Applied Energy, Elsevier, vol. 351(C).
    13. Xiaoling Yuan & Can Cui & Guanxin Zhu & Hanqing Ma & Hao Cao, 2023. "Research on the Optimization of Energy–Carbon Co-Sharing Operation in Multiple Multi-Energy Microgrids Based on Nash Negotiation," Energies, MDPI, vol. 16(15), pages 1-20, July.
    14. Li, Yuxuan & Zhang, Junli & Wu, Xiao & Shen, Jiong & Maréchal, François, 2023. "Stochastic-robust planning optimization method based on tracking-economy extreme scenario tradeoff for CCHP multi-energy system," Energy, Elsevier, vol. 283(C).
    15. Lin, Xiaojie & Mao, Yihui & Chen, Jiaying & Zhong, Wei, 2023. "Dynamic modeling and uncertainty quantification of district heating systems considering renewable energy access," Applied Energy, Elsevier, vol. 349(C).
    16. Zhu, Mengshu & Ai, Xiaomeng & Fang, Jiakun & Cui, Shichang & Wu, Kejing & Zheng, Lufan & Wen, Jinyu, 2024. "Optimal scheduling of hydrogen energy hub for stable demand with uncertain photovoltaic and biomass," Applied Energy, Elsevier, vol. 360(C).
    17. Fan, Guozhu & Peng, Chunhua & Wang, Xuekui & Wu, Peng & Yang, Yifan & Sun, Huijuan, 2024. "Optimal scheduling of integrated energy system considering renewable energy uncertainties based on distributionally robust adaptive MPC," Renewable Energy, Elsevier, vol. 226(C).
    18. Wang, Yuwei & Song, Minghao & Jia, Mengyao & Shi, Lin & Li, Bingkang, 2023. "TimeGAN based distributionally robust optimization for biomass-photovoltaic-hydrogen scheduling under source-load-market uncertainties," Energy, Elsevier, vol. 284(C).
    19. Seyed Mohammad Shojaei & Reihaneh Aghamolaei & Mohammad Reza Ghaani, 2024. "Recent Advancements in Applying Machine Learning in Power-to-X Processes: A Literature Review," Sustainability, MDPI, vol. 16(21), pages 1-41, November.
    20. Zhang, Tao & Li, Guojun & Wei, Linyang & Ji, Wenchao & Qiu, Yong & Zhang, Qinrui, 2024. "A novel dynamic simulation strategy for regional integrated energy system considering coupling components failure," Energy, Elsevier, vol. 295(C).
    21. Tang, Bao-Jun & Cao, Xi-Lin & Li, Ru & Xiang, Zhi-Bo & Zhang, Sen, 2024. "Economic and low-carbon planning for interconnected integrated energy systems considering emerging technologies and future development trends," Energy, Elsevier, vol. 302(C).
    22. Pan, Yushu & Ju, Liwei & Yang, Shenbo & Guo, Xinyu & Tan, Zhongfu, 2024. "A multi-objective robust optimal dispatch and cost allocation model for microgrids-shared hybrid energy storage system considering flexible ramping capacity," Applied Energy, Elsevier, vol. 369(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Jinliang & Liu, Ziyi, 2024. "Low carbon economic scheduling model for a park integrated energy system considering integrated demand response, ladder-type carbon trading and fine utilization of hydrogen," Energy, Elsevier, vol. 290(C).
    2. Fan, Guozhu & Peng, Chunhua & Wang, Xuekui & Wu, Peng & Yang, Yifan & Sun, Huijuan, 2024. "Optimal scheduling of integrated energy system considering renewable energy uncertainties based on distributionally robust adaptive MPC," Renewable Energy, Elsevier, vol. 226(C).
    3. Zhang, Zhonglian & Yang, Xiaohui & Li, Moxuan & Deng, Fuwei & Xiao, Riying & Mei, Linghao & Hu, Zecheng, 2023. "Optimal configuration of improved dynamic carbon neutral energy systems based on hybrid energy storage and market incentives," Energy, Elsevier, vol. 284(C).
    4. Ju, Liwei & Bai, Xiping & Li, Gen & Gan, Wei & Qi, Xin & Ye, Fan, 2024. "Two-stage robust transaction optimization model and benefit allocation strategy for new energy power stations with shared energy storage considering green certificate and virtual energy storage mode," Applied Energy, Elsevier, vol. 362(C).
    5. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Yan, Zhiyu, 2022. "A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems," Renewable Energy, Elsevier, vol. 196(C), pages 204-219.
    6. Wang, Xuan & Wang, Shouxiang & Zhao, Qianyu & Lin, Zhuoran, 2023. "Low-carbon coordinated operation of electric-heat-gas-hydrogen interconnected system and benchmark design considering multi-energy spatial and dynamic coupling," Energy, Elsevier, vol. 279(C).
    7. Zhang, Bin & Wu, Xuewei & Ghias, Amer M.Y.M. & Chen, Zhe, 2023. "Coordinated carbon capture systems and power-to-gas dynamic economic energy dispatch strategy for electricity–gas coupled systems considering system uncertainty: An improved soft actor–critic approach," Energy, Elsevier, vol. 271(C).
    8. Jie Zhu & Buxiang Zhou & Yiwei Qiu & Tianlei Zang & Yi Zhou & Shi Chen & Ningyi Dai & Huan Luo, 2023. "Survey on Modeling of Temporally and Spatially Interdependent Uncertainties in Renewable Power Systems," Energies, MDPI, vol. 16(16), pages 1-19, August.
    9. Gao, Jianwei & Meng, Qichen & Liu, Jiangtao & Wang, Ziying, 2024. "Thermoelectric optimization of integrated energy system considering wind-photovoltaic uncertainty, two-stage power-to-gas and ladder-type carbon trading," Renewable Energy, Elsevier, vol. 221(C).
    10. Xiao, Ting & Chen, Ting & Ma, Zhiwei & Tian, Hailong & Meguerdijian, Saro & Chen, Bailian & Pawar, Rajesh & Huang, Lianjie & Xu, Tianfu & Cather, Martha & McPherson, Brian, 2024. "A review of risk and uncertainty assessment for geologic carbon storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    11. Wu, Qunli & Li, Chunxiang, 2023. "Modeling and operation optimization of hydrogen-based integrated energy system with refined power-to-gas and carbon-capture-storage technologies under carbon trading," Energy, Elsevier, vol. 270(C).
    12. Wang, Yuwei & Song, Minghao & Jia, Mengyao & Li, Bingkang & Fei, Haoran & Zhang, Yiyue & Wang, Xuejie, 2023. "Multi-objective distributionally robust optimization for hydrogen-involved total renewable energy CCHP planning under source-load uncertainties," Applied Energy, Elsevier, vol. 342(C).
    13. Li, Yang & Bu, Fanjin & Li, Yuanzheng & Long, Chao, 2023. "Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach," Applied Energy, Elsevier, vol. 333(C).
    14. Fan, Wei & Fan, Ying & Yao, Xing & Yi, Bowen & Jiang, Dalin & Wu, Lin, 2024. "Distributed transaction optimization model of multi-integrated energy systems based on nash negotiation," Renewable Energy, Elsevier, vol. 225(C).
    15. Yanbin Li & Yanting Sun & Yulin Kang & Feng Zhang & Junjie Zhang, 2023. "An Optimal Site Selection Framework for Near-Zero Carbon Emission Power Plants Based on Multiple Stakeholders," Energies, MDPI, vol. 16(2), pages 1-26, January.
    16. Fan, Wei & Tan, Zhongfu & Li, Fanqi & Zhang, Amin & Ju, Liwei & Wang, Yuwei & De, Gejirifu, 2023. "A two-stage optimal scheduling model of integrated energy system based on CVaR theory implementing integrated demand response," Energy, Elsevier, vol. 263(PC).
    17. Yi Zhang & Tian Lan & Wei Hu, 2023. "A Two-Stage Robust Optimization Microgrid Model Considering Carbon Trading and Demand Response," Sustainability, MDPI, vol. 15(19), pages 1-22, October.
    18. Saif Jamal & Jagadeesh Pasupuleti & Nur Azzammudin Rahmat & Nadia M. L. Tan, 2022. "Energy Management System for Grid-Connected Nanogrid during COVID-19," Energies, MDPI, vol. 15(20), pages 1-20, October.
    19. Zhang, Yagang & Wang, Hui & Wang, Jingchao & Cheng, Xiaodan & Wang, Tong & Zhao, Zheng, 2024. "Ensemble optimization approach based on hybrid mode decomposition and intelligent technology for wind power prediction system," Energy, Elsevier, vol. 292(C).
    20. Jiaqi Wu & Qian Zhang & Yangdong Lu & Tianxi Qin & Jianyong Bai, 2023. "Source-Load Coordinated Low-Carbon Economic Dispatch of Microgrid including Electric Vehicles," Sustainability, MDPI, vol. 15(21), pages 1-21, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:331:y:2023:i:c:s030626192201683x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.