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• W4386814240 abstract "The research focuses on the air-conditioning system in a public area of a subway station. To address this, an optimization model based on the grid time segmentation method was constructed, specifically a GM (1,1) model. We explored the influence of the hourly passenger flow fluctuation on the load of the subway air-conditioning system, obtained the dynamic change law of the air conditioning system load in the subway station, and then dynamically adjusted the air conditioning system according to the dynamic change law to reduce the operation energy consumption of the system. Through the analysis of the simulation results, the model predicted that compared with the actual passenger flow data, the average maximum relative error was 14.97%. On this basis, the change law of the dynamic load of the subway air-conditioning system which caused by the change in passenger flow from time to time could be calculated and analyzed. Compared with the calculated load of the air conditioning system, the working day load was decreased by 1469.77 kW, or 22.00%. The findings indicate that in response to the dynamic load of fluctuations, timely adjustment of the air supply parameter of the air-conditioning system offers a significant reference point for optimizing energy efficiency in subway stations." @default.
• W4386814240 created "2023-09-18" @default.
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• W4386814240 date "2023-09-15" @default.
• W4386814240 modified "2023-09-26" @default.
• W4386814240 title "Study on Dynamic Load of Air-Conditioning System in Subway Station Based on Hourly Passenger Flow" @default.
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• W4386814240 doi "https://doi.org/10.3390/buildings13092349" @default.
• W4386814240 hasPublicationYear "2023" @default.
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