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Energy supply efficiency evaluation of integrated energy systems using novel SBM-DEA integrating Monte Carlo

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  • Cong, Di
  • Liang, Lingling
  • Jing, Shaoxing
  • Han, Yongming
  • Geng, Zhiqiang
  • Chu, Chong

Abstract

With the economic development, the clean and low-carbon integrated energy system is of great significance to the social sustainable development in the world. Therefore, this paper proposes a novel energy supply efficiency evaluation model of integrated energy systems based on slacks-based measure data envelopment analysis (SBM-DEA) integrating Monte Carlo for energy saving and optimization. The extended energy supply data of integrated energy systems based on the Monte Carlo is verified in terms of F test. Then cooling load, heating load, electric load and internal combustion engine load are taken as inputs. And cooling income, heating income and electricity sales are set as desired outputs and the carbon tax is set as the undesired output to build the energy supply efficiency evaluation model of integrated energy systems using the SBM-DEA for energy optimization and carbon tax reduction. The results show that the proposed method has a high degree of discrimination to obtain better effective decision-making units (DMUs). Moreover, energy optimization and carbon tax reduction of integrated energy systems are achieved.

Suggested Citation

  • Cong, Di & Liang, Lingling & Jing, Shaoxing & Han, Yongming & Geng, Zhiqiang & Chu, Chong, 2021. "Energy supply efficiency evaluation of integrated energy systems using novel SBM-DEA integrating Monte Carlo," Energy, Elsevier, vol. 231(C).
    • Handle: RePEc:eee:energy:v:231:y:2021:i:c:s0360544221010823
    DOI: 10.1016/j.energy.2021.120834
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    1. Iftikhar, Yaser & Wang, Zhaohua & Zhang, Bin & Wang, Bo, 2018. "Energy and CO2 emissions efficiency of major economies: A network DEA approach," Energy, Elsevier, vol. 147(C), pages 197-207.
    2. Han, Yongming & Liu, Shuang & Geng, Zhiqiang & Gu, Hengchang & Qu, Yixin, 2021. "Energy analysis and resources optimization of complex chemical processes: Evidence based on novel DEA cross-model," Energy, Elsevier, vol. 218(C).
    3. Xu, Xiandong & Jin, Xiaolong & Jia, Hongjie & Yu, Xiaodan & Li, Kang, 2015. "Hierarchical management for integrated community energy systems," Applied Energy, Elsevier, vol. 160(C), pages 231-243.
    4. Orehounig, Kristina & Evins, Ralph & Dorer, Viktor, 2015. "Integration of decentralized energy systems in neighbourhoods using the energy hub approach," Applied Energy, Elsevier, vol. 154(C), pages 277-289.
    5. Arnold, Uwe & Yildiz, Özgür, 2015. "Economic risk analysis of decentralized renewable energy infrastructures – A Monte Carlo Simulation approach," Renewable Energy, Elsevier, vol. 77(C), pages 227-239.
    6. Han, Yongming & Wu, Hao & Geng, Zhiqiang & Zhu, Qunxiong & Gu, Xiangbai & Yu, Bin, 2020. "Review: Energy efficiency evaluation of complex petrochemical industries," Energy, Elsevier, vol. 203(C).
    7. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
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