The HVAC systems in subway stations are energy consuming giants, each of which may consume over 10, 000 Kilowatts per day for cooling and ventilation. To save energy for the HVAC systems, it is critically important to firstly know the "load signatures" of the HVAC system, i.e., the quantity of heat imported from the outdoor environments and by the passengers respectively in different periods of a day, which will significantly benefit the design of control policies. In this paper, we present a novel sensing and learning approach to identify the load signature of the HVAC system in the subway stations. In particular, sensors and smart meters were deployed to monitor the indoor, outdoor temperatures, and the energy consumptions of the HVAC system in real-time. The number of passengers was counted by the ticket checking system. At the same time, the cooling supply provided by the HVAC system was inferred via the energy consumption logs of the HVAC system. Since the indoor temperature variations are driven by the difference of the loads and the cooling supply, linear regression model was proposed for the load signature, whose coefficients are derived via a proposed algorithm . We collected real sensing data and energy log data from HaiDianHuangZhuang Subway station, which is in line 4 of Beijing from the duration of July 2012 to Sept. 2012. The data was used to evaluate the coefficients of the regression model. The experiment results show typical variation signatures of the loads from the passengers and from the outdoor environments respectively, which provide important contexts for smart control policies.
Another related work reported the factors affecting the range of heat transfer in subways @cite_13 . They show by numerical analysis that how the heat is transferred in tunnels and stations. Reference @cite_11 studied the environmental characters in the subway metro stations in Cairo, Egypt, which showed the different environment characters in the tunnel and on the surface. The most related work is @cite_7 , which surveyed the energy consumption of Beijing subway lines in 2008. Different from these existing work, we deployed sensors and presented models to study the the load signatures and distinct features of energy consumptionof subway HVAC systems.
@cite_13 @cite_7 @cite_11
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In order to examine the factors which affect the range of heat transfer in earth surrounding subways, FLAC3D was adopted in this study to analyze these factors, under different conditions, in a systematic manner. When we compare these numerical tests, the results show that the main factors, affecting the heat transfer range are the thermal properties of the surrounding earth, the initial ground temperature and the temperature in the tunnel. The heat transfer coefficient between air and linings has little effect on the temperature distribution around the tunnel. The current results can provide a reference for improving the thermal environment in subways and optimizing the design of subway ventilation and air conditioning. Because of large numbers of passengers,Beijing subway has a great demand for huge power consumption.It is necessary to search possibilities of reducing the power consumption of Beijing Subway.This paper analyzed the actual power consumption of each subway line,the electric power used for powering the trains and all secondary consumption of electric power for operating the train stations of Beijing subway in detail.Additionally,the water consumption of each subway line of Beijing subway was also analyzed.The results provide a scientific basis for the design and operation of energy-saving subways. In subway systems, the energy put into accelerating trains can be reconverted into electric energy by using the motors as generators during the braking phase. In general, except for a small part that is used for onboard purposes, most of the recovery energy is transmitted backward along the conversion chain and fed back into the overhead contact line. To improve the utilization of recovery energy, this paper proposes a cooperative scheduling approach to optimize the timetable so that the recovery energy that is generated by the braking train can directly be used by the accelerating train. The recovery that is generated by the braking train is less than the required energy for the accelerating train; therefore, only the synchronization between successive trains is considered. First, we propose the cooperative scheduling rules and define the overlapping time between the accelerating and braking trains for a peak-hours scenario and an off-peak-hours scenario, respectively. Second, we formulate an integer programming model to maximize the overlapping time with the headway time and dwell time control. Furthermore, we design a genetic algorithm with binary encoding to solve the optimal timetable. Last, we present six numerical examples based on the operation data from the Beijing Yizhuang subway line in China. The results illustrate that the proposed model can significantly improve the overlapping time by 22.06 at peak hours and 15.19 at off-peak hours. Metro construction in China enjoyed and will continue to enjoy unprecedented development in the tenth 5 Year Plan period and the upcoming eleventh 5 Year Plan period. In China, cities are densely populated, and as a modernized urban rail transit means, metros have been undertaking increasingly important tasks of large passenger flow transportation, under which circumstance the injury and casualty will be enormous if an accident occurs. China's work safe laws and regulations have stipulated that safety evaluation must be carried out during planning, design, construction and operation of metros. As a part of the metro safety evaluation, occupant safe evacuation is a critical aspect to be assessed. This paper will first introduce the occupants evacuation design in the construction of metros in China based on Code for design of metro (CFDOM) (GB 50157-2003), including evacuation passage design, evacuation time and evacuation safe area as well as fire-engineering-based occupants evacuation design philosophy and calculation method. Finally, a computer simulation of the process of evacuation of occupants from deep buried metro station (DBMS) by using occupants evacuation dynamic model will be conducted on the example of DBMS of Guangzhou Metro Line 6, so as to study whether the occupants can be safely evacuated from DBMS in case of fire.