IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v302y2021ics0306261921009557.html
   My bibliography  Save this article

Unlocking emerging impacts of carbon tax on integrated energy systems through supply and demand co-optimization

Author

Listed:
  • Wang, Meng
  • Yu, Hang
  • Yang, Yikun
  • Lin, Xiaoyu
  • Guo, Haijin
  • Li, Chaoen
  • Zhou, Yue
  • Jing, Rui

Abstract

Integrated energy systems (IES) can help achieve greater energy efficiency, and then ultimately promote a climate-neutral economy by utilizing local renewable resources. Demand-side energy-saving measures can reduce operational costs associated with energy usage. Most existing IES models, however, focus on supply-side optimization, while the demand-side energy-saving potential and its impacts on whole-system performance are still not clear. The increasing carbon tax makes it even more important to understand the interactions between supply and demand sides to achieve a sustainable system with a minimal carbon charge. Hence, this study proposes a co-optimization model to simultaneously optimize the supply and demand sides of an IES considering the impact of the carbon tax. A selection tree is developed to describe various demand-side envelope upgrading technologies, and a binary tree is established by generating a set of supply-side scenarios with corresponding probabilities. Based on these results, an improved two-stage stochastic programming model is proposed. The robustness of the modeling results was further validated by a simulation–optimization-based uncertainty analysis addressing price uncertainties. A case study in Shanghai indicates that the proposed co-optimization model achieves more cost-efficient solutions than supply-side-only optimization considering carbon tax. Introducing carbon tax can reduce the installed capacity of fuel-based energy technologies by up to 24% and greatly accelerate the penetration of renewables. The increasing carbon tax also promotes the adoption of more advanced energy-saving technologies. Uncertainty analysis reveals acceptable robustness of the optimal demand-side scheme and supply-side configuration with a deviation of less than 5% and a coefficient of variation of 7%. Overall, the observations of the proposed model and case study provide valuable insights for IES design considering an emerging charge of carbon tax.

Suggested Citation

  • Wang, Meng & Yu, Hang & Yang, Yikun & Lin, Xiaoyu & Guo, Haijin & Li, Chaoen & Zhou, Yue & Jing, Rui, 2021. "Unlocking emerging impacts of carbon tax on integrated energy systems through supply and demand co-optimization," Applied Energy, Elsevier, vol. 302(C).
    • Handle: RePEc:eee:appene:v:302:y:2021:i:c:s0306261921009557
    DOI: 10.1016/j.apenergy.2021.117579
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921009557
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.117579?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. Perera, A.T.D. & Javanroodi, Kavan & Nik, Vahid M., 2021. "Climate resilient interconnected infrastructure: Co-optimization of energy systems and urban morphology," Applied Energy, Elsevier, vol. 285(C).
    2. Wang, Yongli & Ma, Yuze & Song, Fuhao & Ma, Yang & Qi, Chengyuan & Huang, Feifei & Xing, Juntai & Zhang, Fuwei, 2020. "Economic and efficient multi-objective operation optimization of integrated energy system considering electro-thermal demand response," Energy, Elsevier, vol. 205(C).
    3. Chen, Yongbao & Xu, Peng & Chen, Zhe & Wang, Hongxin & Sha, Huajing & Ji, Ying & Zhang, Yongming & Dou, Qiang & Wang, Sheng, 2020. "Experimental investigation of demand response potential of buildings: Combined passive thermal mass and active storage," Applied Energy, Elsevier, vol. 280(C).
    4. Siddaiah, Rajanna & Saini, R.P., 2016. "A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 376-396.
    5. Martelli, Emanuele & Freschini, Marco & Zatti, Matteo, 2020. "Optimization of renewable energy subsidy and carbon tax for multi energy systems using bilevel programming," Applied Energy, Elsevier, vol. 267(C).
    6. Wu, Di & Han, Zhonghe & Liu, Zhijian & Li, Peng & Ma, Fanfan & Zhang, Han & Yin, Yunxing & Yang, Xinyan, 2021. "Comparative study of optimization method and optimal operation strategy for multi-scenario integrated energy system," Energy, Elsevier, vol. 217(C).
    7. Zhang, Zhihui & Jing, Rui & Lin, Jian & Wang, Xiaonan & van Dam, Koen H. & Wang, Meng & Meng, Chao & Xie, Shan & Zhao, Yingru, 2020. "Combining agent-based residential demand modeling with design optimization for integrated energy systems planning and operation," Applied Energy, Elsevier, vol. 263(C).
    8. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    9. Jing, Rui & Wang, Meng & Liang, Hao & Wang, Xiaonan & Li, Ning & Shah, Nilay & Zhao, Yingru, 2018. "Multi-objective optimization of a neighborhood-level urban energy network: Considering Game-theory inspired multi-benefit allocation constraints," Applied Energy, Elsevier, vol. 231(C), pages 534-548.
    10. Wolfinger, David & Salazar-González, Juan-José, 2021. "The Pickup and Delivery Problem with Split Loads and Transshipments: A Branch-and-Cut Solution Approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 470-484.
    11. Schütz, Thomas & Schiffer, Lutz & Harb, Hassan & Fuchs, Marcus & Müller, Dirk, 2017. "Optimal design of energy conversion units and envelopes for residential building retrofits using a comprehensive MILP model," Applied Energy, Elsevier, vol. 185(P1), pages 1-15.
    12. Patel, Alpesh M. & Singal, Sunil Kumar, 2019. "Optimal component selection of integrated renewable energy system for power generation in stand-alone applications," Energy, Elsevier, vol. 175(C), pages 481-504.
    13. Mu, Chenlu & Ding, Tao & Qu, Ming & Zhou, Quan & Li, Fangxing & Shahidehpour, Mohammad, 2020. "Decentralized optimization operation for the multiple integrated energy systems with energy cascade utilization," Applied Energy, Elsevier, vol. 280(C).
    14. Jing, Rui & Wang, Meng & Zhang, Zhihui & Wang, Xiaonan & Li, Ning & Shah, Nilay & Zhao, Yingru, 2019. "Distributed or centralized? Designing district-level urban energy systems by a hierarchical approach considering demand uncertainties," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    15. Jing, Rui & Kuriyan, Kamal & Lin, Jian & Shah, Nilay & Zhao, Yingru, 2020. "Quantifying the contribution of individual technologies in integrated urban energy systems – A system value approach," Applied Energy, Elsevier, vol. 266(C).
    16. Bahlawan, Hilal & Morini, Mirko & Pinelli, Michele & Poganietz, Witold-Roger & Spina, Pier Ruggero & Venturini, Mauro, 2019. "Optimization of a hybrid energy plant by integrating the cumulative energy demand," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    17. Kang, Ligai & Yang, Junhong & An, Qingsong & Deng, Shuai & Zhao, Jun & Wang, Hui & Li, Zelin, 2017. "Effects of load following operational strategy on CCHP system with an auxiliary ground source heat pump considering carbon tax and electricity feed in tariff," Applied Energy, Elsevier, vol. 194(C), pages 454-466.
    18. Ferrara, Maria & Rolfo, Andrea & Prunotto, Federico & Fabrizio, Enrico, 2019. "EDeSSOpt – Energy Demand and Supply Simultaneous Optimization for cost-optimized design: Application to a multi-family building," Applied Energy, Elsevier, vol. 236(C), pages 1231-1248.
    19. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 222(C), pages 932-950.
    20. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    21. Mayer, Martin János & Szilágyi, Artúr & Gróf, Gyula, 2020. "Environmental and economic multi-objective optimization of a household level hybrid renewable energy system by genetic algorithm," Applied Energy, Elsevier, vol. 269(C).
    22. Zheng, Xuyue & Qiu, Yuwei & Zhan, Xiangyan & Zhu, Xingyi & Keirstead, James & Shah, Nilay & Zhao, Yingru, 2017. "Optimization based planning of urban energy systems: Retrofitting a Chinese industrial park as a case-study," Energy, Elsevier, vol. 139(C), pages 31-41.
    23. Diakaki, Christina & Grigoroudis, Evangelos & Kolokotsa, Dionyssia, 2013. "Performance study of a multi-objective mathematical programming modelling approach for energy decision-making in buildings," Energy, Elsevier, vol. 59(C), pages 534-542.
    24. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.
    25. Wang, Meng & Yu, Hang & Lin, Xiaoyu & Jing, Rui & He, Fangjun & Li, Chaoen, 2020. "Comparing stochastic programming with posteriori approach for multi-objective optimization of distributed energy systems under uncertainty," Energy, Elsevier, vol. 210(C).
    26. Jing, Rui & Li, Yubing & Wang, Meng & Chachuat, Benoit & Lin, Jianyi & Guo, Miao, 2021. "Coupling biogeochemical simulation and mathematical optimisation towards eco-industrial energy systems design," Applied Energy, Elsevier, vol. 290(C).
    27. Thalfeldt, Martin & Pikas, Ergo & Kurnitski, Jarek & Voll, Hendrik, 2017. "Window model and 5 year price data sensitivity to cost-effective façade solutions for office buildings in Estonia," Energy, Elsevier, vol. 135(C), pages 685-697.
    28. Sungwoo Lee & Hyoungtae Kim & Tae Hyun Kim & Hansol Shin & Wook Kim, 2019. "Fault Current Constraint Transmission Expansion Planning Based on the Inverse Matrix Modification Lemma and a Valid Inequality," Energies, MDPI, vol. 12(24), pages 1-17, December.
    29. Liu, Zhiyuan & Yu, Hang & Liu, Rui, 2019. "A novel energy supply and demand matching model in park integrated energy system," Energy, Elsevier, vol. 176(C), pages 1007-1019.
    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. Wang, Meng & Yu, Hang & Liu, Yupeng & Lin, Jianyi & Zhong, Xianzhun & Tang, Yin & Guo, Haijin & Jing, Rui, 2024. "Unlock city-scale energy saving and peak load shaving potential of green roofs by GIS-informed urban building energy modelling," Applied Energy, Elsevier, vol. 366(C).
    2. Jing, Rui & Hua, Weiqi & Lin, Jian & Lin, Jianyi & Zhao, Yingru & Zhou, Yue & Wu, Jianzhong, 2022. "Cost-efficient decarbonization of local energy systems by whole-system based design optimization," Applied Energy, Elsevier, vol. 326(C).
    3. Wu, Zhiyue & Shi, Xin & Fang, Fang & Wen, Gangcheng & Mi, Yunjie, 2023. "Co-optimization of building energy systems with renewable generations combining active and passive energy-saving," Applied Energy, Elsevier, vol. 351(C).
    4. Lyu, Xiangmei & Liu, Tianqi & Liu, Xuan & He, Chuan & Nan, Lu & Zeng, Hong, 2023. "Low-carbon robust economic dispatch of park-level integrated energy system considering price-based demand response and vehicle-to-grid," Energy, Elsevier, vol. 263(PB).
    5. Xiang, Xiwang & Ma, Minda & Ma, Xin & Chen, Liming & Cai, Weiguang & Feng, Wei & Ma, Zhili, 2022. "Historical decarbonization of global commercial building operations in the 21st century," Applied Energy, Elsevier, vol. 322(C).
    6. Jia, Zhijie & Lin, Boqiang & Liu, Xiying, 2023. "Rethinking the equity and efficiency of carbon tax: A novel perspective," Applied Energy, Elsevier, vol. 346(C).
    7. Wang, P.P. & Huang, G.H. & Li, Y.P. & Liu, Y.Y. & Li, Y.F., 2024. "An ecological input-output CGE model for unveiling CO2 emission metabolism under China's dual carbon goals," Applied Energy, Elsevier, vol. 365(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. Wu, Zhiyue & Shi, Xin & Fang, Fang & Wen, Gangcheng & Mi, Yunjie, 2023. "Co-optimization of building energy systems with renewable generations combining active and passive energy-saving," Applied Energy, Elsevier, vol. 351(C).
    2. Jing, Rui & Kuriyan, Kamal & Lin, Jian & Shah, Nilay & Zhao, Yingru, 2020. "Quantifying the contribution of individual technologies in integrated urban energy systems – A system value approach," Applied Energy, Elsevier, vol. 266(C).
    3. Wang, Meng & Yu, Hang & Lin, Xiaoyu & Jing, Rui & He, Fangjun & Li, Chaoen, 2020. "Comparing stochastic programming with posteriori approach for multi-objective optimization of distributed energy systems under uncertainty," Energy, Elsevier, vol. 210(C).
    4. Jing, Rui & Li, Yubing & Wang, Meng & Chachuat, Benoit & Lin, Jianyi & Guo, Miao, 2021. "Coupling biogeochemical simulation and mathematical optimisation towards eco-industrial energy systems design," Applied Energy, Elsevier, vol. 290(C).
    5. Lin, Jian & Zhong, Xiaoyi & Wang, Jing & Huang, Yuan & Bai, Xuetao & Wang, Xiaonan & Shah, Nilay & Xie, Shan & Zhao, Yingru, 2021. "Relative optimization potential: A novel perspective to address trade-off challenges in urban energy system planning," Applied Energy, Elsevier, vol. 304(C).
    6. Ghaemi, Zahra & Tran, Thomas T.D. & Smith, Amanda D., 2022. "Comparing classical and metaheuristic methods to optimize multi-objective operation planning of district energy systems considering uncertainties," Applied Energy, Elsevier, vol. 321(C).
    7. Kachirayil, Febin & Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2022. "Reviewing local and integrated energy system models: insights into flexibility and robustness challenges," Applied Energy, Elsevier, vol. 324(C).
    8. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2021. "Multi-objective optimization and evaluation of hybrid CCHP systems for different building types," Energy, Elsevier, vol. 215(PA).
    9. Liu, Liuchen & Cui, Guomin & Chen, Jiaxing & Huang, Xiaohuang & Li, Di, 2022. "Two-stage superstructure model for optimization of distributed energy systems (DES) part I: Model development and verification," Energy, Elsevier, vol. 245(C).
    10. Leprince, Julien & Schledorn, Amos & Guericke, Daniela & Dominkovic, Dominik Franjo & Madsen, Henrik & Zeiler, Wim, 2023. "Can occupant behaviors affect urban energy planning? Distributed stochastic optimization for energy communities," Applied Energy, Elsevier, vol. 348(C).
    11. Bartolini, Andrea & Mazzoni, Stefano & Comodi, Gabriele & Romagnoli, Alessandro, 2021. "Impact of carbon pricing on distributed energy systems planning," Applied Energy, Elsevier, vol. 301(C).
    12. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    13. Ren, Xiaoxiao & Han, Zijun & Ma, Jinpeng & Xue, Kai & Chong, Daotong & Wang, Jinshi & Yan, Junjie, 2024. "Life-cycle-based multi-objective optimal design and analysis of distributed multi-energy systems for data centers," Energy, Elsevier, vol. 288(C).
    14. Li, Ke & Yang, Fan & Wang, Lupan & Yan, Yi & Wang, Haiyang & Zhang, Chenghui, 2022. "A scenario-based two-stage stochastic optimization approach for multi-energy microgrids," Applied Energy, Elsevier, vol. 322(C).
    15. Afzali, Sayyed Faridoddin & Cotton, James S. & Mahalec, Vladimir, 2020. "Urban community energy systems design under uncertainty for specified levels of carbon dioxide emissions," Applied Energy, Elsevier, vol. 259(C).
    16. Zhang, Zhihui & Jing, Rui & Lin, Jian & Wang, Xiaonan & van Dam, Koen H. & Wang, Meng & Meng, Chao & Xie, Shan & Zhao, Yingru, 2020. "Combining agent-based residential demand modeling with design optimization for integrated energy systems planning and operation," Applied Energy, Elsevier, vol. 263(C).
    17. Kiani-Moghaddam, Mohammad & Soltani, Mohsen N. & Kalogirou, Soteris A. & Mahian, Omid & Arabkoohsar, Ahmad, 2023. "A review of neighborhood level multi-carrier energy hubs—uncertainty and problem-solving process," Energy, Elsevier, vol. 281(C).
    18. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2022. "A review on the integration and optimization of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    19. Li, Lanyu & Yao, Zhiyi & You, Siming & Wang, Chi-Hwa & Chong, Clive & Wang, Xiaonan, 2019. "Optimal design of negative emission hybrid renewable energy systems with biochar production," Applied Energy, Elsevier, vol. 243(C), pages 233-249.
    20. Brodnicke, Linda & Gabrielli, Paolo & Sansavini, Giovanni, 2023. "Impact of policies on residential multi-energy systems for consumers and prosumers," Applied Energy, Elsevier, vol. 344(C).

    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:302:y:2021:i:c:s0306261921009557. 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.