  For sustainability and energy saving, the problem to optimize the control of
heating, ventilating, and air-conditioning (HVAC) systems has attracted great
attentions, but analyzing the signatures of thermal environments and HVAC
systems and the evaluation of the optimization policies has encountered
inefficiency and inconvenient problems due to the lack of public dataset. In
this paper, we present the Subway station Energy and Environment Dataset
(SEED), which was collected from a line of Beijing subway stations, providing
minute-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 passenger
flows. We describe the sensor deployments and the HVAC systems for data
collection and for environment control, and also present initial investigation
for the energy disaggregation of HVAC system, the signatures of the thermal
load, cooling supply, and the passenger flow using the dataset.

Systems and Control