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IoT-Enabled Optimal Incentive Strategy for Flexible Loads in Intelligent Demand Response Frameworks

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    College of Architecture and Urban Planning, Tongji University, Shanghai, China

    • Fund Project: This study was supported by the Natural Science Foundation of Shanghai province, China (Grant No. 25ZR1401349), the Fundamental Research Funds for the Central Universities, the Basic Scientific Research Fund Project of Shanghai, and the Shanghai Professional Technical Service Platform of Smart and Low-Carbon Controlled Built Environment (Grant No. 23DZ2290100).
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  • Corresponding author: luomaohui@tongji.edu.cn
  • Received Date:  March 15, 2026
    Accepted Date:  June 09, 2026
    Published Online:  June 25, 2026
Energy Use  2(2),  https://doi.org/10.59717/ipj.energy-use.2026.100048  |  Cite this article
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  • Cite this article:

    Li X., Gao Y., Zhou X., et al. (2026). IoT-Enabled Optimal Incentive Strategy for Flexible Loads in Intelligent Demand Response Frameworks. Energy Use 2:100048. https://doi.org/10.59717/ipj.energy-use.2026.100048
    Li X., Gao Y., Zhou X., et al. (2026). IoT-Enabled Optimal Incentive Strategy for Flexible Loads in Intelligent Demand Response Frameworks. Energy Use 2:100048. https://doi.org/10.59717/ipj.energy-use.2026.100048

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