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A framework of service-oriented operation model of China׳s power system

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  • Zhou, Kaile
  • Yang, Shanlin

Abstract

Based on the rapid development of smart grid and emerging information technologies in China, a new cloud-based power system operational model called Cloud Grid (CG) is presented in this study. CG is a service-oriented operation model of China׳s power system, which integrates the concepts and techniques of cloud computing, big data analytics, internet of things (IoTs), high performance computing, smart grid and other advanced information and communication technologies (ICTs). The power production resources, power production capacities and power resources are virtualized in CG. Moreover, it makes the power system services provided readily available, on-demand, flexible, efficient, safety and reliable for both power producers and electricity consumers. First, the concept and service model of CG are defined, and its system architecture is established. Then, the key techniques of CG are discussed. Finally, we present a brief analysis of the future developments of CG.

Suggested Citation

  • Zhou, Kaile & Yang, Shanlin, 2015. "A framework of service-oriented operation model of China׳s power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 719-725.
    • Handle: RePEc:eee:rensus:v:50:y:2015:i:c:p:719-725
    DOI: 10.1016/j.rser.2015.05.041
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    Cited by:

    1. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    2. Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
    3. Zhou, Kaile & Yang, Shanlin, 2016. "Understanding household energy consumption behavior: The contribution of energy big data analytics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 810-819.
    4. Lubing Xie & Xiaoming Rui & Shuai Li & Xiaozhao Fan & Ruijing Shi & Guohua Li, 2018. "A Critical Analysis on Influential Factors on Power Energy Resources in China," Modern Applied Science, Canadian Center of Science and Education, vol. 12(2), pages 1-1, February.
    5. Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2016. "Energy Internet: The business perspective," Applied Energy, Elsevier, vol. 178(C), pages 212-222.

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