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IntelliSense technology in the new power systems

Author

Listed:
  • Xie, Haonan
  • Jiang, Meihui
  • Zhang, Dongdong
  • Goh, Hui Hwang
  • Ahmad, Tanveer
  • Liu, Hui
  • Liu, Tianhao
  • Wang, Shuyao
  • Wu, Thomas

Abstract

The energy and climate crises have accelerated the decarbonization of electric power systems. An important part of this decarbonization process, along with the incorporation of renewable and alternative energies, is the emergence of Carbon-neutral, intelligent systems technologies, coupled with digital transformation. These have brought new dynamics to the electric power systems transformation. Significant amounts of renewable energy, massive power electronics, changes in market planning, policy influence, demand response, and emerging technologies all become the essential components of new power systems, bringing remarkable changes to this new power systems' enabling technologies: IntelliSense. A novel IntelliSense framework driven by new power system requirements is proposed. The development status, classification characteristics, the application of intelligent sensors, intelligent sensor flexible charging, and multisource plus multidimensional big data processing are all discussed in detail. They are interspersed with discussions of critical features of new power systems, the uncertainties inherent in big data about power, wireless power transfer technologies, edge-fog-cloud collaborative computing, intelligent algorithms, and other core elements of IntelliSense. Finally, ten core IntelliSense technology challenges and five major future opportunities are summarized and are expected to serve as a reference and spark new ideas for low-carbon power system development.

Suggested Citation

  • Xie, Haonan & Jiang, Meihui & Zhang, Dongdong & Goh, Hui Hwang & Ahmad, Tanveer & Liu, Hui & Liu, Tianhao & Wang, Shuyao & Wu, Thomas, 2023. "IntelliSense technology in the new power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:rensus:v:177:y:2023:i:c:s1364032123000850
    DOI: 10.1016/j.rser.2023.113229
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    Cited by:

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    2. Lei, Xiang & Yu, Hang & Shao, Ziyun & Jian, Linni, 2023. "Optimal bidding and coordinating strategy for maximal marginal revenue due to V2G operation: Distribution system operator as a key player in China's uncertain electricity markets," Energy, Elsevier, vol. 283(C).
    3. Liu, Tianhao & Tian, Jun & Zhu, Hongyu & Goh, Hui Hwang & Liu, Hui & Wu, Thomas & Zhang, Dongdong, 2023. "Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation," Energy, Elsevier, vol. 277(C).
    4. Xie, Haonan & Goh, Hui Hwang & Zhang, Dongdong & Sun, Hui & Dai, Wei & Kurniawan, Tonni Agustiono & Dennis Wong, M.L. & Teo, Kenneth Tze Kin & Goh, Kai Chen, 2024. "Eco-Energetical analysis of circular economy and community-based virtual power plants (CE-cVPP): A systems engineering-engaged life cycle assessment (SE-LCA) method for sustainable renewable energy de," Applied Energy, Elsevier, vol. 365(C).

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