IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v292y2024ics0360544224002287.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224002287
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.130457?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, 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).
    Full references (including those not matched with items on IDEAS)

    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. Amirteimoori, Alireza & Kazemi Matin, Reza & Yadollahi, Amir Hossein, 2024. "Stochastic resource reallocation in two-stage production processes with undesirable outputs: An empirical study on the power industry," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    2. Fang, Lei, 2022. "Measuring and decomposing group performance under centralized management," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1006-1013.
    3. Ang, Sheng & Liu, Pei & Yang, Feng, 2020. "Intra-Organizational and inter-organizational resource allocation in two-stage network systems," Omega, Elsevier, vol. 91(C).
    4. Zhao, Weigang & Cao, Yunfei & Miao, Bo & Wang, Ke & Wei, Yi-Ming, 2018. "Impacts of shifting China's final energy consumption to electricity on CO2 emission reduction," Energy Economics, Elsevier, vol. 71(C), pages 359-369.
    5. Akram Dehnokhalaji & Mojtaba Ghiyasi & Pekka Korhonen, 2017. "Resource allocation based on cost efficiency," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1279-1289, October.
    6. Yu, Xiang, 2023. "An assessment of the green development efficiency of industrial parks in China: Based on non-desired output and non-radial DEA model," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 81-88.
    7. Mehdi Toloo & Mona Barat & Atefeh Masoumzadeh, 2015. "Selective measures in data envelopment analysis," Annals of Operations Research, Springer, vol. 226(1), pages 623-642, March.
    8. Sulaima, Mohamad Fani & Dahlan, Nofri Yenita & Yasin, Zuhaila Mat & Rosli, Marlinda Mohd & Omar, Zulkiflee & Hassan, Mohammad Yusri, 2019. "A review of electricity pricing in peninsular Malaysia: Empirical investigation about the appropriateness of Enhanced Time of Use (ETOU) electricity tariff," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 348-367.
    9. Wang, Derek D., 2019. "Performance-based resource allocation for higher education institutions in China," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 66-75.
    10. Zhang, Ganggang & Wu, Jie & Zhu, Qingyuan, 2020. "Performance evaluation and enrollment quota allocation for higher education institutions in China," Evaluation and Program Planning, Elsevier, vol. 81(C).
    11. Antonio Peyrache & Maria C. A. Silva, 2022. "Efficiency and Productivity Analysis from a System Perspective: Historical Overview," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 173-230, Springer.
    12. M. Mozaffari & J. Gerami & J. Jablonsky, 2014. "Relationship between DEA models without explicit inputs and DEA-R models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 22(1), pages 1-12, March.
    13. Liesiö, Juuso & Andelmin, Juho & Salo, Ahti, 2020. "Efficient allocation of resources to a portfolio of decision making units," European Journal of Operational Research, Elsevier, vol. 286(2), pages 619-636.
    14. Lin, Ruiyue & Liu, Yue, 2019. "Super-efficiency based on the directional distance function in the presence of negative data," Omega, Elsevier, vol. 85(C), pages 26-34.
    15. Zhang, Chonghui & Li, Xiangwen & Sun, Yunfei & Chen, Ji & Streimikiene, Dalia, 2023. "Policy modeling consistency analysis during energy crises: Evidence from China's coal power policy," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    16. Wang, Weijiao & Xu, Fei & Chu, Junfei & Dong, Yanhua & Yuan, Zhe, 2025. "Determining the equilibrium efficient frontier by proportional frontier shifting for data envelopment analysis with fixed-sum outputs," Omega, Elsevier, vol. 130(C).
    17. A Z Milioni & J V G de Avellar & T N Rabello & G M de Freitas, 2011. "Hyperbolic frontier model: a parametric DEA approach for the distribution of a total fixed output," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1029-1037, June.
    18. OA Carboni & P. Russu, 2014. "Measuring Environmental and Economic Efficiency in Italy: an Application of the Malmquist-DEA and Grey Forecasting Model," Working Paper CRENoS 201401, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    19. Despotis, Dimitris K. & Stamati, Lamprini V. & Smirlis, Yiannis G., 2010. "Data envelopment analysis with nonlinear virtual inputs and outputs," European Journal of Operational Research, Elsevier, vol. 202(2), pages 604-613, April.
    20. Cherchye, Laurens & Rock, Bram De & Walheer, Barnabé, 2015. "Multi-output efficiency with good and bad outputs," European Journal of Operational Research, Elsevier, vol. 240(3), pages 872-881.

    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:292:y:2024:i:c:s0360544224002287. 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.