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<p>Winter air conditioning loads have strong demand response potential as one of the peak load components.In the study, a two-tier scheduling strategy is offered to address the demand response potential of air-conditioning loads during the peak hours of the grid in winter. First, a virtual energy storage model for air conditioning, considering the time-varying characteristics of the outdoor temperature, was developed to analyze the adjustable amount of air conditioning clusters. Second, the heating capacity of air-conditioning loads is combined with thermal energy storage devices to participate in CCHP microgrid scheduling. To minimize CCHP operating costs, upper-level scheduling uses an improved red-billed blue magpie optimization algorithm to determine the air conditioning regulation. Lower-level scheduling aims to reduce the deviation between the regulated quantity and the actual demand and precisely control the amount of air conditioning temperature regulation. The simulation results show that compared with the original method, the method increases the user compensation cost. Still, the heating cost is reduced by 13.2%, the grid interaction cost is reduced by 64.6%, and the total cost of the system is reduced by 9.3%, which provides a new method to improve the economy and sustainability of the power grid.</p>

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Two-Tier Optimal Scheduling of Air-Conditioning Virtual Energy Storage Combined Cooling, Heating, and Power Microgrids Considering Demand Response

  • 期刊论文

  • 发表日期：

    2025年8月26日

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  • Mengran Zhou,
  • Xiangnan Sun,
  • Feng Hu,
  • Ziwei Zhu,
  • Kun Wang,
  • Chunchen Shi,
  • Mengcheng Zhou,
  • Yu Zhang,
  • Yuewen Zhang,
  • Lehan Zhang

摘要

Winter air conditioning loads have strong demand response potential as one of the peak load components.In the study, a two-tier scheduling strategy is offered to address the demand response potential of air-conditioning loads during the peak hours of the grid in winter. First, a virtual energy storage model for air conditioning, considering the time-varying characteristics of the outdoor temperature, was developed to analyze the adjustable amount of air conditioning clusters. Second, the heating capacity of air-conditioning loads is combined with thermal energy storage devices to participate in CCHP microgrid scheduling. To minimize CCHP operating costs, upper-level scheduling uses an improved red-billed blue magpie optimization algorithm to determine the air conditioning regulation. Lower-level scheduling aims to reduce the deviation between the regulated quantity and the actual demand and precisely control the amount of air conditioning temperature regulation. The simulation results show that compared with the original method, the method increases the user compensation cost. Still, the heating cost is reduced by 13.2%, the grid interaction cost is reduced by 64.6%, and the total cost of the system is reduced by 9.3%, which provides a new method to improve the economy and sustainability of the power grid.