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The centralised data envelopment analysis model integrated with cost information and utility theory for power price setting under carbon peak strategy at the firm-level

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  • Zhang, Chonghui
  • Bai, Chen
  • Su, Weihua
  • Balezentis, Tomas

Abstract

The post-pandemic economic rebound has accelerated power demand. However, in a power generation system dominated thermal power plants, implementing the carbon peak strategy induces a contradiction between power supply and demand. This gives rise to the issues of the rational power allocation. To address this issue, based on enterprise micro-data, this study develops a model that allows power allocation across industrial enterprises to maximise their output. The ladder price is used for power redistribution seeking to ensure efficiency and fairness of the power allocation. Then, the utility theory is used to explore the effects of changes in the power use under different ladder prices. The paper relies on the unique dataset for Chinese enterprises. The results show that the proposed model renders power re-allocation among the enterprises (31 % of enterprises should reduce their power use, 32 % whereas should increase their power use by more than 50 %). By including the power cost in the model, significant differences were discovered between the optimal power use of three ladder price levels. This study provides recommendations for power allocation and the use of the ladder prices.

Suggested Citation

  • Zhang, Chonghui & Bai, Chen & Su, Weihua & Balezentis, Tomas, 2024. "The centralised data envelopment analysis model integrated with cost information and utility theory for power price setting under carbon peak strategy at the firm-level," Energy, Elsevier, vol. 292(C).
    • Handle: RePEc:eee:energy:v:292:y:2024:i:c:s0360544224002287
    DOI: 10.1016/j.energy.2024.130457
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    as
    1. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2016. "Potential gains from carbon emissions trading in China: A DEA based estimation on abatement cost savings," Omega, Elsevier, vol. 63(C), pages 48-59.
    2. Nepal, Rabindra & Paija, Nirash, 2019. "Energy security, electricity, population and economic growth: The case of a developing South Asian resource-rich economy," Energy Policy, Elsevier, vol. 132(C), pages 771-781.
    3. Jianyun Zhang & Xinxin Li & Lingying Pan, 2022. "Policy Effect on Clean Coal-Fired Power Development in China," Energies, MDPI, vol. 15(3), pages 1-18, January.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Echenique, Federico & Miralles, Antonio & Zhang, Jun, 2021. "Fairness and efficiency for allocations with participation constraints," Journal of Economic Theory, Elsevier, vol. 195(C).
    6. Wang, Chen & Zhou, Kaile & Yang, Shanlin, 2017. "A review of residential tiered electricity pricing in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 533-543.
    7. Edward J. Balistreri & Christoph Böhringer & Thomas F. Rutherford, 2018. "Carbon policy and the structure of global trade," The World Economy, Wiley Blackwell, vol. 41(1), pages 194-221, January.
    8. Guang, Fengtao & He, Yongxiu & Wen, Le, 2019. "Impacts of hybrid time-varying tariffs on residential electricity demand: The case of Zhejiang Province," Utilities Policy, Elsevier, vol. 61(C).
    9. Sebastián Lozano & Gabriel Villa, 2004. "Centralized Resource Allocation Using Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 22(1), pages 143-161, July.
    10. Yang, Changhui & Meng, Chen & Zhou, Kaile, 2018. "Residential electricity pricing in China: The context of price-based demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2870-2878.
    11. Danielsson, Erna & Nyhlén, Jon & Olausson, Pär M., 2020. "Strategic planning for power shortages," Energy Policy, Elsevier, vol. 137(C).
    12. Xu, Weiwei & Zhou, Dan & Huang, Xiaoming & Lou, Boliang & Liu, Dong, 2020. "Optimal allocation of power supply systems in industrial parks considering multi-energy complementarity and demand response," Applied Energy, Elsevier, vol. 275(C).
    13. Wu, Ya & Zhang, Li, 2017. "Evaluation of energy saving effects of tiered electricity pricing and investigation of the energy saving willingness of residents," Energy Policy, Elsevier, vol. 109(C), pages 208-217.
    14. Steenhof, Paul A., 2006. "Decomposition of electricity demand in China's industrial sector," Energy Economics, Elsevier, vol. 28(3), pages 370-384, May.
    15. Li, Der-Chiang & Chang, Che-Jung & Chen, Chien-Chih & Chen, Wen-Chih, 2012. "Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case," Omega, Elsevier, vol. 40(6), pages 767-773.
    16. Jacquet-Lagreze, E. & Siskos, J., 1982. "Assessing a set of additive utility functions for multicriteria decision-making, the UTA method," European Journal of Operational Research, Elsevier, vol. 10(2), pages 151-164, June.
    17. Bo Wang & Limao Wang & Shuai Zhong & Ning Xiang & Qiushi Qu, 2022. "Low-Carbon Transformation of Electric System against Power Shortage in China: Policy Optimization," Energies, MDPI, vol. 15(4), pages 1-18, February.
    18. Langlois-Bertrand, Simon & Pineau, Pierre-Olivier, 2018. "Pricing the transition: Empirical evidence on the evolution of electricity rate structures in North America," Energy Policy, Elsevier, vol. 117(C), pages 184-197.
    19. Ma, Haoran, 2022. "Prediction of industrial power consumption in Jiangsu Province by regression model of time variable," Energy, Elsevier, vol. 239(PB).
    20. Hankinson, G. A. & Rhys, J. M. W., 1983. "Electricity consumption, electricity intensity and industrial structure," Energy Economics, Elsevier, vol. 5(3), pages 146-152, July.
    21. Xiong, Xi & Yang, Guo-liang & Zhou, De-qun & Wang, Zi-long, 2022. "How to allocate multi-period research resources? Centralized resource allocation for public universities in China using a parallel DEA-based approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    22. Feng Wang & Yijie Jiang & Wulin Zhang & Fang Yang, 2019. "Elasticity of factor substitution and driving factors of energy intensity in China’s industry," Energy & Environment, , vol. 30(3), pages 385-407, May.
    23. Xu, Jie & Lv, Tao & Hou, Xiaoran & Deng, Xu & Liu, Feng, 2021. "Provincial allocation of renewable portfolio standard in China based on efficiency and fairness principles," Renewable Energy, Elsevier, vol. 179(C), pages 1233-1245.
    24. Ahammed, Md. Tanvir & Khan, Imran, 2022. "Ensuring power quality and demand-side management through IoT-based smart meters in a developing country," Energy, Elsevier, vol. 250(C).
    25. Zhu Liu & Dabo Guan & Scott Moore & Henry Lee & Jun Su & Qiang Zhang, 2015. "Climate policy: Steps to China's carbon peak," Nature, Nature, vol. 522(7556), pages 279-281, June.
    26. Zhu, Qingyuan & Xu, Shuqi & Sun, Jiasen & Li, Xingchen & Zhou, Dequn, 2022. "Energy efficiency evaluation of power supply system: A data-driven approach based on shared resources," Applied Energy, Elsevier, vol. 312(C).
    27. Lozano, Sebastián, 2023. "Bargaining approach for efficiency assessment and target setting with fixed-sum variables," Omega, Elsevier, vol. 114(C).
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