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Assessing the low-carbon effects of inter-regional energy delivery in China's electricity sector

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  • Chen, Qixin
  • Kang, Chongqing
  • Ming, Hao
  • Wang, Zeyu
  • Xia, Qing
  • Xu, Guoxin

Abstract

In China, the electricity sector consumes approximately 50% of the coal and emits 40% of the CO2 from fossil fuel combustion. The unbalanced spatial distribution between energy resources and demands and the remarkable differences in power-generation capabilities among regions are important factors that impede decarbonization of China's electricity sector. Utilization of the abundant low-carbon energy resources in the central and western regions is restricted by limited local demand. Energy demand in these regions accounts for approximately 26% of the entire nation's demand. By comparison, the regions have more than 45% of the energy resources. However, long-distance energy delivery incurs considerable losses. At present, approximately 80% of inter-regional energy delivery uses primary coal transport and 20% travels by secondary electricity transmission. The Chinese government is planning to build an ambitious inter-regional transmission grid for energy delivery. We demonstrate that this plan would significantly change the current delivery patterns and improve delivery efficiency. Approximately 40% of inter-regional energy delivery would travel by secondary electricity transmission and a 25% improvement in the delivery efficiency of the entire system is expected. Therefore, utilization of low-carbon energy resources would be promoted and overall carbon emission would be reduced. Using a fine-grained electricity dispatch model to simulate and optimize the operation of the power system, the carbon emission mitigation potential is quantitatively assessed based on real planning data. The results indicate a significant 10% reduction in CO2 emissions in 2030, amounting to 0.49Gt. This reduction should be included as an important component for the sector's low-carbon budget. Finally, we assess the potential for further reductions in carbon emissions by making modifications to the planned transmission grid.

Suggested Citation

  • Chen, Qixin & Kang, Chongqing & Ming, Hao & Wang, Zeyu & Xia, Qing & Xu, Guoxin, 2014. "Assessing the low-carbon effects of inter-regional energy delivery in China's electricity sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 671-683.
  • Handle: RePEc:eee:rensus:v:32:y:2014:i:c:p:671-683
    DOI: 10.1016/j.rser.2013.12.050
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    References listed on IDEAS

    as
    1. Chen, Qixin & Kang, Chongqing & Xia, Qing & Guan, Dabo, 2011. "Preliminary exploration on low-carbon technology roadmap of China’s power sector," Energy, Elsevier, vol. 36(3), pages 1500-1512.
    2. Pekala, Lukasz M. & Tan, Raymond R. & Foo, Dominic C.Y. & Jezowski, Jacek M., 2010. "Optimal energy planning models with carbon footprint constraints," Applied Energy, Elsevier, vol. 87(6), pages 1903-1910, June.
    3. Grubb,Michael & Jamasb,Tooraj & Pollitt,Michael G. (ed.), 2008. "Delivering a Low Carbon Electricity System," Cambridge Books, Cambridge University Press, number 9780521888844, September.
    4. Atkins, Martin J. & Morrison, Andrew S. & Walmsley, Michael R.W., 2010. "Carbon Emissions Pinch Analysis (CEPA) for emissions reduction in the New Zealand electricity sector," Applied Energy, Elsevier, vol. 87(3), pages 982-987, March.
    5. Kannan, R., 2009. "Uncertainties in key low carbon power generation technologies - Implication for UK decarbonisation targets," Applied Energy, Elsevier, vol. 86(10), pages 1873-1886, October.
    6. Zhang, Chi & Shukla, P.R. & Victor, David G. & Heller, Thomas C. & Biswas, Debashish & Nag, Tirthankar, 2006. "Baselines for carbon emissions in the Indian and Chinese power sectors: Implications for international carbon trading," Energy Policy, Elsevier, vol. 34(14), pages 1900-1917, September.
    7. Wang, Qiang & Chen, Yong, 2010. "Status and outlook of China's free-carbon electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1014-1025, April.
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