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For sustainability and energy saving, the problem to optimize the control ofheating, ventilating, and air-conditioning (HVAC) systems has attracted greatattentions, but analyzing the signatures of thermal environments and HVACsystems and the evaluation of the optimization policies has encounteredinefficiency and inconvenient problems due to the lack of public dataset. Inthis paper, we present the Subway station Energy and Environment Dataset(SEED), which was collected from a line of Beijing subway stations, providingminute-resolution data regarding the environment dynamics (temperature,humidity, CO2, etc.) working states and energy consumptions of the HVAC systems(ventilators, refrigerators, pumps), and hour-resolution data of passengerflows. We describe the sensor deployments and the HVAC systems for datacollection and for environment control, and also present initial investigationfor the energy disaggregation of HVAC system, the signatures of the thermalload, cooling supply, and the passenger flow using the dataset.

SEED: Public Energy and Environment Dataset for Optimizing HVAC Operation in Subway Stations