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Optimizing the provincial target allocation scheme of renewable portfolio standards in China

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  • Sun, J.
  • Wen, W.
  • Wang, M.
  • Zhou, P.

Abstract

Renewable portfolio standards (RPS) is widely regarded as a useful policy tool to steer energy transition. China government has recently released an RPS target allocation scheme to help promote its renewable electricity consumption. Formulating an efficient and equitable RPS target allocation scheme is a vital step to ensure the effectiveness of RPS. In this paper we argue that data envelopment analysis (DEA) can be used to optimize the provincial RPS targets in China from an efficiency perspective. We first evaluate the efficiency of the officially released RPS target allocation scheme and then apply a zero-sum gains DEA model to optimize the scheme. Further, we use the Gini coefficient to verify the merits of the optimized scheme over the official scheme in equity. The results indicate that the renewable electricity consumption responsibility allocated among provinces in the official scheme may suffer efficiency loss. Central, southern, eastern, and southwestern China can obtain more renewable electricity consumption responsibility, while northeastern, northern, and northwestern China should undertake less consumption responsibility. It provides the adjustment direction for RPS targets allocation among provinces which helps optimize the electricity consumption structure.

Suggested Citation

  • Sun, J. & Wen, W. & Wang, M. & Zhou, P., 2022. "Optimizing the provincial target allocation scheme of renewable portfolio standards in China," Energy, Elsevier, vol. 250(C).
  • Handle: RePEc:eee:energy:v:250:y:2022:i:c:s0360544222006028
    DOI: 10.1016/j.energy.2022.123699
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    as
    1. Wang, Delu & Wan, Kaidi & Song, Xuefeng & Liu, Yun, 2019. "Provincial allocation of coal de-capacity targets in China in terms of cost, efficiency, and fairness," Energy Economics, Elsevier, vol. 78(C), pages 109-128.
    2. Farooq, Muhammad Khalid & Kumar, S. & Shrestha, Ram M., 2013. "Energy, environmental and economic effects of Renewable Portfolio Standards (RPS) in a Developing Country," Energy Policy, Elsevier, vol. 62(C), pages 989-1001.
    3. Sarwar, Suleman & Chen, Wei & Waheed, Rida, 2017. "Electricity consumption, oil price and economic growth: Global perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 9-18.
    4. Berry, Trent & Jaccard, Mark, 2001. "The renewable portfolio standard:: design considerations and an implementation survey," Energy Policy, Elsevier, vol. 29(4), pages 263-277, March.
    5. Yannick Oswald & Anne Owen & Julia K. Steinberger, 2020. "Publisher Correction: Large inequality in international and intranational energy footprints between income groups and across consumption categories," Nature Energy, Nature, vol. 5(4), pages 349-349, April.
    6. 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.
    7. Jason Chilvers & Rob Bellamy & Helen Pallett & Tom Hargreaves, 2021. "A systemic approach to mapping participation with low-carbon energy transitions," Nature Energy, Nature, vol. 6(3), pages 250-259, March.
    8. E G Gomes & M P E Lins, 2008. "Modelling undesirable outputs with zero sum gains data envelopment analysis models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 616-623, May.
    9. Chen, Xiaotong & Yang, Fang & Zhang, Shining & Zakeri, Behnam & Chen, Xing & Liu, Changyi & Hou, Fangxin, 2021. "Regional emission pathways, energy transition paths and cost analysis under various effort-sharing approaches for meeting Paris Agreement goals," Energy, Elsevier, vol. 232(C).
    10. Lins, Marcos P. Estellita & Gomes, Eliane G. & Soares de Mello, Joao Carlos C. B. & Soares de Mello, Adelino Jose R., 2003. "Olympic ranking based on a zero sum gains DEA model," European Journal of Operational Research, Elsevier, vol. 148(2), pages 312-322, July.
    11. Yang, Mian & Hou, Yaru & Fang, Chao & Duan, Hongbo, 2020. "Constructing energy-consuming right trading system for China's manufacturing industry in 2025," Energy Policy, Elsevier, vol. 144(C).
    12. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    13. Zhou, P. & Sun, Z.R. & Zhou, D.Q., 2014. "Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis," Energy Economics, Elsevier, vol. 45(C), pages 99-110.
    14. Han, Rong & Li, Jianglong & Guo, Zhi, 2022. "Optimal quota in China's energy capping policy in 2030 with renewable targets and sectoral heterogeneity," Energy, Elsevier, vol. 239(PA).
    15. Yannick Oswald & Anne Owen & Julia K. Steinberger, 2020. "Large inequality in international and intranational energy footprints between income groups and across consumption categories," Nature Energy, Nature, vol. 5(3), pages 231-239, March.
    16. Pekka Korhonen & Mikko Syrjänen, 2004. "Resource Allocation Based on Efficiency Analysis," Management Science, INFORMS, vol. 50(8), pages 1134-1144, August.
    17. Inglesi-Lotz, Roula, 2016. "The impact of renewable energy consumption to economic growth: A panel data application," Energy Economics, Elsevier, vol. 53(C), pages 58-63.
    18. Shahbaz, Muhammad & Sarwar, Suleman & Chen, Wei & Malik, Muhammad Nasir, 2017. "Dynamics of electricity consumption, oil price and economic growth: Global perspective," Energy Policy, Elsevier, vol. 108(C), pages 256-270.
    19. Park, Sang Yong & Yun, Bo-Yeong & Yun, Chang Yeol & Lee, Duk Hee & Choi, Dong Gu, 2016. "An analysis of the optimum renewable energy portfolio using the bottom–up model: Focusing on the electricity generation sector in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 319-329.
    20. Buckman, Greg, 2011. "The effectiveness of Renewable Portfolio Standard banding and carve-outs in supporting high-cost types of renewable electricity," Energy Policy, Elsevier, vol. 39(7), pages 4105-4114, July.
    21. Yue-Jun Zhang & Jun-Fang Hao, 2017. "Carbon emission quota allocation among China’s industrial sectors based on the equity and efficiency principles," Annals of Operations Research, Springer, vol. 255(1), pages 117-140, August.
    22. Yang, Mian & Hou, Yaru & Ji, Qiang & Zhang, Dayong, 2020. "Assessment and optimization of provincial CO2 emission reduction scheme in China: An improved ZSG-DEA approach," Energy Economics, Elsevier, vol. 91(C).
    23. Wang, Ge & Zhang, Qi & Li, Yan & Mclellan, Benjamin C., 2019. "Efficient and equitable allocation of renewable portfolio standards targets among China's provinces," Energy Policy, Elsevier, vol. 125(C), pages 170-180.
    24. Zhou, P. & Zhang, L. & Zhou, D.Q. & Xia, W.J., 2013. "Modeling economic performance of interprovincial CO2 emission reduction quota trading in China," Applied Energy, Elsevier, vol. 112(C), pages 1518-1528.
    25. Sanya Carley & David M. Konisky, 2020. "The justice and equity implications of the clean energy transition," Nature Energy, Nature, vol. 5(8), pages 569-577, August.
    26. Li, Wei & Lu, Can & Zhang, Yan-Wu, 2019. "Prospective exploration of future renewable portfolio standard schemes in China via a multi-sector CGE model," Energy Policy, Elsevier, vol. 128(C), pages 45-56.
    27. Rouhani, Omid M. & Niemeier, Debbie & Gao, H. Oliver & Bel, Germà, 2016. "Cost-benefit analysis of various California renewable portfolio standard targets: Is a 33% RPS optimal?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1122-1132.
    28. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    29. Fang, Kai & Zhang, Qifeng & Long, Yin & Yoshida, Yoshikuni & Sun, Lu & Zhang, Haoran & Dou, Yi & Li, Shuai, 2019. "How can China achieve its Intended Nationally Determined Contributions by 2030? A multi-criteria allocation of China’s carbon emission allowance," Applied Energy, Elsevier, vol. 241(C), pages 380-389.
    30. Pang, Rui-zhi & Deng, Zhong-qi & Chiu, Yung-ho, 2015. "Pareto improvement through a reallocation of carbon emission quotas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 419-430.
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