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Research on Virtual Energy Storage Scheduling Strategy for Air Conditioning Based on Adaptive Thermal Comfort Model

Author

Listed:
  • Ran Lv

    (Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China)

  • Enqi Wu

    (Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China)

  • Li Lan

    (Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China)

  • Chen Fu

    (Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China)

  • Mingxing Guo

    (Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China)

  • Feier Chen

    (Economic and Technological Research Institute, State Grid Shanghai Electric Power Company, Shanghai 200233, China)

  • Min Wang

    (School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China)

  • Jie Zou

    (School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China)

Abstract

With the rapid development of a social economy, the yearly increase in air conditioning load in the winter and summer seasons may bring serious challenges to the safe and economic operation of the power grid during the peak period of electricity consumption. So, how we reasonably adjust the set temperature of air conditioning so as to cut down the load during peak periods is very important. In this paper, considering the thermal inertia of air-conditioned buildings and the adaptability of human thermal comfort to temperature changes, the air conditioning load is regarded as virtual energy storage, the air conditioning temperature adjustment range for different users is determined based on the adaptive thermal comfort model of different geographic locations and climatic conditions, and a compensation mechanism is set up based on air conditioning users’ level of participation. Then, an optimal scheduling strategy for a microgrid was constructed with the objectives of user satisfaction, carbon emissions, and microgrid operation benefits, as well as regulating the users’ electricity consumption behavior, and the strategy was solved by using a multi-objective JAYA algorithm. Finally, winter and summer are used as case studies to analyze the results, which demonstrate that regulating the virtual energy storage of air conditioning can effectively improve the economy and environmental friendliness of a microgrid operation and reduce the cost of electricity consumption for the users, taking into account the comfort of the users.

Suggested Citation

  • Ran Lv & Enqi Wu & Li Lan & Chen Fu & Mingxing Guo & Feier Chen & Min Wang & Jie Zou, 2024. "Research on Virtual Energy Storage Scheduling Strategy for Air Conditioning Based on Adaptive Thermal Comfort Model," Energies, MDPI, vol. 17(11), pages 1-19, May.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2670-:d:1405973
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    References listed on IDEAS

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    1. Yongzhen Wang & Congchuan Hu & Boyuan Wu & Jing Zhang & Zhenning Zi & Ligai Kang, 2020. "Matching Characteristic Research of Building Renewable Energy System Based on Virtual Energy Storage of Air Conditioning Load," Energies, MDPI, vol. 13(5), pages 1-15, March.
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