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Low carbon electricity development in China--An IRSP perspective based on Super Smart Grid

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  • Yuan, Jiahai
  • Hu, Zhaoguang

Abstract

Low carbon electricity is essential for China's low carbon development. In the paper low carbon electricity is defined as an economy body manages to realize its potential economic growth fueled by less electricity consumption, which can be characterized by indexes of GDP electricity intensity and CO2 emissions per unit electricity generation. IRSP is proposed by Hu [11] to implement power planning on state level in deregulated power sector and is used in the paper to study China's power planning into 2030. A business-as-usual scenario is projected as baseline for comparison while low carbon electricity development based on IRSP is studied. Results show that, with IRSP, China could save energy by 1.5 billion toes and reduce CO2 emission by 5.7 billion tons, during 2010-2030. Super Smart Grid (SSG) must be constructed as the physical foundation of IRSP. The main components of developing SSG in China are discussed.

Suggested Citation

  • Yuan, Jiahai & Hu, Zhaoguang, 2011. "Low carbon electricity development in China--An IRSP perspective based on Super Smart Grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2707-2713, August.
    • Handle: RePEc:eee:rensus:v:15:y:2011:i:6:p:2707-2713
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    References listed on IDEAS

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    1. Hu, Zhaoguang & Tan, Xiandong & Yang, Fan & Yang, Ming & Wen, Quan & Shan, Baoguo & Han, Xinyang, 2010. "Integrated resource strategic planning: Case study of energy efficiency in the Chinese power sector," Energy Policy, Elsevier, vol. 38(11), pages 6391-6397, November.
    2. Hu, Zhaoguang & Wen, Quan & Wang, Jianhui & Tan, Xiandong & Nezhad, Hameed & Shan, Baoguo & Han, Xinyang, 2010. "Integrated resource strategic planning in China," Energy Policy, Elsevier, vol. 38(8), pages 4635-4642, August.
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    5. Yuan, Jiahai & Hou, Yong & Xu, Ming, 2012. "China's 2020 carbon intensity target: Consistency, implementations, and policy implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4970-4981.
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    8. Ran, Fengming & Gao, Dian-ce & Zhang, Xu & Chen, Shuyue, 2020. "A virtual sensor based self-adjusting control for HVAC fast demand response in commercial buildings towards smart grid applications," Applied Energy, Elsevier, vol. 269(C).
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    10. Blarke, Morten B. & Jenkins, Bryan M., 2013. "SuperGrid or SmartGrid: Competing strategies for large-scale integration of intermittent renewables?," Energy Policy, Elsevier, vol. 58(C), pages 381-390.
    11. He Huang & DaPeng Liang & Liang Liang & Zhen Tong, 2019. "Research on China’s Power Sustainable Transition Under Progressively Levelized Power Generation Cost Based on a Dynamic Integrated Generation–Transmission Planning Model," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
    12. Ming, Zeng & Junjie, Feng & Song, Xue & Zhijie, Wang & Xiaoli, Zhu & Yuejin, Wang, 2013. "Development of China's pumped storage plant and related policy analysis," Energy Policy, Elsevier, vol. 61(C), pages 104-113.
    13. Yuan, Jiahai & Xu, Yan & Hu, Zhen & Yu, Zhongfu & Liu, Jiangyan & Hu, Zhaoguang & Xu, Ming, 2012. "Managing electric power system transition in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5660-5677.
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    16. Zheng, Yanan & Hu, Zhaoguang & Wang, Jianhui & Wen, Quan, 2014. "IRSP (integrated resource strategic planning) with interconnected smart grids in integrating renewable energy and implementing DSM (demand side management) in China," Energy, Elsevier, vol. 76(C), pages 863-874.
    17. Chou, Jui-Sheng & Ngo, Ngoc-Tri, 2016. "Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns," Applied Energy, Elsevier, vol. 177(C), pages 751-770.
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