IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v237y2021ics0360544221017825.html
   My bibliography  Save this article

Environmental and economic multi-objective optimization of comprehensive energy industry: A case study

Author

Listed:
  • Kong, Hui
  • Li, Zheng
  • Yu, Zhufeng
  • Zhang, Jun
  • Wang, Hongsheng
  • Wang, Jian
  • Gao, Dan

Abstract

Coal will continue to dominate the energy structure for a long time, however, the severe environmental issues require that coal should be cleanly and efficiently utilized. This work proposes to carry out integrated research on the optimization model of the coal and new energy-based industrial structure at the enterprise level. To meet the low-carbon requirements, a multi-objective superstructure optimization model of the coal and new energy-based energy structure under a variety of constraints is constructed, while the carbon emissions and total profits are selected as the objectives simultaneously. Then a case study is conducted with the industrial structure of a representative energy company as the study object. Via self-developed mixed programming to achieve the optimal solution of Pareto-frontier, this study analyzed the energy industry adjustment and layout optimization under three different scenarios. The turning point with the emission reduction rate of 2 % is recommended as the optimal choice under the baseline scenario, and new energy power generation has become a new growth point of the group's profits after adjusting the investment structure. Comparisons between the coal and new energy power generation prices will seriously affect the optimization and prediction results of the low-carbon scenario. The annual profit in 2020 will decrease significantly under the epidemic situation, but the change rules of emissions and profits are basically consistent with the baseline scenario. The research methods and quantitative results could be generalized for relevant comprehensive energy companies to adjust their strategic layout and make plans.

Suggested Citation

  • Kong, Hui & Li, Zheng & Yu, Zhufeng & Zhang, Jun & Wang, Hongsheng & Wang, Jian & Gao, Dan, 2021. "Environmental and economic multi-objective optimization of comprehensive energy industry: A case study," Energy, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:energy:v:237:y:2021:i:c:s0360544221017825
    DOI: 10.1016/j.energy.2021.121534
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221017825
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.121534?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. Kong, Hui & Kong, Xianghui & Wang, Jian & Zhang, Jun, 2019. "Thermodynamic analysis of a solar thermochemical cycle-based direct coal liquefaction system for oil production," Energy, Elsevier, vol. 179(C), pages 1279-1287.
    2. Cui, Yunfei & Geng, Zhiqiang & Zhu, Qunxiong & Han, Yongming, 2017. "Review: Multi-objective optimization methods and application in energy saving," Energy, Elsevier, vol. 125(C), pages 681-704.
    3. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    4. Laha, Priyanka & Chakraborty, Basab, 2021. "Low carbon electricity system for India in 2030 based on multi-objective multi-criteria assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    5. Kong, Hui & Hao, Yong & Jin, Hongguang, 2018. "Isothermal versus two-temperature solar thermochemical fuel synthesis: A comparative study," Applied Energy, Elsevier, vol. 228(C), pages 301-308.
    6. Mu, Yaqian & Cai, Wenjia & Evans, Samuel & Wang, Can & Roland-Holst, David, 2018. "Employment impacts of renewable energy policies in China: A decomposition analysis based on a CGE modeling framework," Applied Energy, Elsevier, vol. 210(C), pages 256-267.
    7. Wu, Zhibin & Xu, Jiuping, 2013. "Predicting and optimization of energy consumption using system dynamics-fuzzy multiple objective programming in world heritage areas," Energy, Elsevier, vol. 49(C), pages 19-31.
    8. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    9. Suwal, Naresh & Huang, Xianfeng & Kuriqi, Alban & Chen, Yingqin & Pandey, Kamal Prasad & Bhattarai, Khem Prasad, 2020. "Optimisation of cascade reservoir operation considering environmental flows for different environmental management classes," Renewable Energy, Elsevier, vol. 158(C), pages 453-464.
    10. Khanali, Majid & Akram, Asadollah & Behzadi, Javad & Mostashari-Rad, Fatemeh & Saber, Zahra & Chau, Kwok-wing & Nabavi-Pelesaraei, Ashkan, 2021. "Multi-objective optimization of energy use and environmental emissions for walnut production using imperialist competitive algorithm," Applied Energy, Elsevier, vol. 284(C).
    11. Niknam, Taher & Narimani, Mohammad rasoul & Jabbari, Masoud & Malekpour, Ahmad Reza, 2011. "A modified shuffle frog leaping algorithm for multi-objective optimal power flow," Energy, Elsevier, vol. 36(11), pages 6420-6432.
    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. Pan Jiang & Hanwen Zhang & Mengyue Li & Yuhan Zhang & Xiujuan Gong & Dong He & Liang Liu, 2023. "Research on the Structural Optimization of the Clean Energy Industry in the Context of Dual Carbon Strategy—A Case Study of Sichuan Province, China," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    2. Kong, Hui & Wang, Jian & Zheng, Hongfei & Wang, Hongsheng & Zhang, Jun & Yu, Zhufeng & Bo, Zheng, 2022. "Techno-economic analysis of a solar thermochemical cycle-based direct coal liquefaction system for low-carbon oil production," Energy, Elsevier, vol. 239(PC).

    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. Yadav, Deepak & Banerjee, Rangan, 2022. "Thermodynamic and economic analysis of the solar carbothermal and hydrometallurgy routes for zinc production," Energy, Elsevier, vol. 247(C).
    2. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    3. Omu, Akomeno & Choudhary, Ruchi & Boies, Adam, 2013. "Distributed energy resource system optimisation using mixed integer linear programming," Energy Policy, Elsevier, vol. 61(C), pages 249-266.
    4. Mena, Rodrigo & Hennebel, Martin & Li, Yan-Fu & Zio, Enrico, 2014. "Self-adaptable hierarchical clustering analysis and differential evolution for optimal integration of renewable distributed generation," Applied Energy, Elsevier, vol. 133(C), pages 388-402.
    5. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    6. Kong, Hui & Wang, Jian & Zheng, Hongfei & Wang, Hongsheng & Zhang, Jun & Yu, Zhufeng & Bo, Zheng, 2022. "Techno-economic analysis of a solar thermochemical cycle-based direct coal liquefaction system for low-carbon oil production," Energy, Elsevier, vol. 239(PC).
    7. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "Optimal design of distributed energy resource systems coupled with energy distribution networks," Energy, Elsevier, vol. 85(C), pages 433-448.
    8. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    9. Hu, Xiao & Zhang, Heng & Chen, Dongwen & Li, Yong & Wang, Li & Zhang, Feng & Cheng, Haozhong, 2020. "Multi-objective planning for integrated energy systems considering both exergy efficiency and economy," Energy, Elsevier, vol. 197(C).
    10. Rey, Anthony & Zmeureanu, Radu, 2018. "Multi-objective optimization framework for the selection of configuration and equipment sizing of solar thermal combisystems," Energy, Elsevier, vol. 145(C), pages 182-194.
    11. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    12. Yu, Nan & Kang, Jin-Su & Chang, Chung-Chuan & Lee, Tai-Yong & Lee, Dong-Yup, 2016. "Robust economic optimization and environmental policy analysis for microgrid planning: An application to Taichung Industrial Park, Taiwan," Energy, Elsevier, vol. 113(C), pages 671-682.
    13. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "An MILP (mixed integer linear programming) model for optimal design of district-scale distributed energy resource systems," Energy, Elsevier, vol. 90(P2), pages 1901-1915.
    14. Madjid Tavana & Akram Shaabani & Francisco Javier Santos-Arteaga & Iman Raeesi Vanani, 2020. "A Review of Uncertain Decision-Making Methods in Energy Management Using Text Mining and Data Analytics," Energies, MDPI, vol. 13(15), pages 1-23, August.
    15. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    16. Chen, Jing & Kong, Hui & Wang, Hongsheng, 2023. "A novel high-efficiency solar thermochemical cycle for fuel production based on chemical-looping cycle oxygen removal," Applied Energy, Elsevier, vol. 343(C).
    17. Keirstead, James & Jennings, Mark & Sivakumar, Aruna, 2012. "A review of urban energy system models: Approaches, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3847-3866.
    18. Horasan, Muhammed Bilal & Kilic, Huseyin Selcuk, 2022. "A multi-objective decision-making model for renewable energy planning: The case of Turkey," Renewable Energy, Elsevier, vol. 193(C), pages 484-504.
    19. Bohlmann, H.R. & Horridge, J.M. & Inglesi-Lotz, R. & Roos, E.L. & Stander, L., 2019. "Regional employment and economic growth effects of South Africa’s transition to low-carbon energy supply mix," Energy Policy, Elsevier, vol. 128(C), pages 830-837.
    20. Yin, Sihua & Yang, Haidong & Xu, Kangkang & Zhu, Chengjiu & Zhang, Shaqing & Liu, Guosheng, 2022. "Dynamic real–time abnormal energy consumption detection and energy efficiency optimization analysis considering uncertainty," Applied Energy, Elsevier, vol. 307(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:energy:v:237:y:2021:i:c:s0360544221017825. 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.journals.elsevier.com/energy .

    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.