Energy consumption of subway stations in China: Data and influencing factors

Guan, Bowen; Liu, Xiaohua; Zhang, Tao; Xia, Jianjun

doi:10.1016/j.scs.2018.09.018

Cited by 45 publications

(21 citation statements)

References 17 publications

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“…Floor Area of Different Zones Station. Previous studies (e.g., [11,12]) have shown that the scale of a metro station could have significant impact on ECMS. In general, a metro station can broadly be divided into four zones: concourse, platform, plant room and staff accommodation room.…”

Section: Interior Design Scheme Of Metro Stationmentioning

confidence: 99%

“…In this subsection, the hold-out validation method is also implemented in the process of hyper-parameters optimizing to verify the superiority of the validation scheme applied in this paper, (12)…”

Section: Comparison Of Validation Schemesmentioning

confidence: 99%

“…Wang et al [11] proposed a linear calculating model to forecast the trend of energy consumption of a given metro network, based on the indicator of monthly energy consumption. Guan et al [12] applied a multivariate linear regression (MLR) model to analyse the contribution of different factors such as floor area of station and passenger volume to the ECMS. Ahn et al [13] built a linear regression model to assess existing subway stations performance and predict energy consumption levels for future expansion.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Estimation Model on Electricity Consumption of New Metro Stations

Zhao

Bai

et al. 2020

Journal of Advanced Transportation

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Electricity consumption of metro stations increases sharply with expansion of a metro network and this has been a growing cause for concern. Based on relevant historical data from existing metro stations, this paper proposes a support vector regression (SVR) model to estimate daily electricity consumption of a newly constructed metro station. The model considers some major factors influencing the electricity consumption of metro station in terms of both the interior design scheme of a station (e.g., layout of the station and allocation of facilities) and external factors (e.g., passenger volume, air temperature and relative humidity). A genetic algorithm with five-fold cross-validation is used to optimize the hyper-parameters of the SVR model in order to improve its accuracy in estimating the electricity consumption of a metro station (ECMS). With the optimized hyper-parameters, results from case studies on the Beijing Subway showed that the estimating accuracy of the proposed SVR model could reach up to 95% and the correlation coefficient was 0.89. It was demonstrated that the proposed model could outperform the traditional methods which use a back-propagation neural network or multivariate linear regression. The method presented in this paper can be an adequate tool for estimating the ECMS and should further assist in the delivery of new, energy-efficient metro stations.

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Section: Interior Design Scheme Of Metro Stationmentioning

confidence: 99%

Section: Comparison Of Validation Schemesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Estimation Model on Electricity Consumption of New Metro Stations

Zhao

Bai

et al. 2020

Journal of Advanced Transportation

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“…Fully enclosed platforms can separate the platform and the tunnel. This can isolate the heat dissipated by trains from the platform and improve the air quality inside the subway platform [ 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. In this study, a total of eight indoor air pollutants were measured for six consecutive days and analyzed to evaluate the integrated indoor air quality level on a subway platform with fully enclosed platform screen doors.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of Air Quality in a Subway Station with Fully Enclosed Platform Screen Doors

Pang

Yang

Cao

et al. 2020

IJERPH

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In this study, the indoor air quality (IAQ) was investigated in a subway station with fully enclosed platform screen doors in Beijing, China. Eight indoor air pollutants, including PM2.5, PM10, SO2 (sulfur dioxide), NO2 (nitrogen dioxide), NH3 (ammonia), CO (carbon monoxide), CH2O (formaldehyde) and TVOC (total volatile organic compound), were measured for six consecutive days in October 2019. The results indicated that the IAQ in the subway station was basically stable at good levels for most times during the whole measurement period. All eight indoor air pollutants were far below their corresponding maximum allowable concentrations, except for the PM2.5 concentrations, which occasionally exceeded the concentration limits. The concentrations of indoor air pollutants in the subway station were basically within the corresponding standards. The correlation analyses showed that outdoor air pollutants have important influences on indoor air pollutants. The concentrations of PM10, PM2.5, SO2, NO2 and CO in the subway station were positively correlated with their corresponding outdoor concentrations. PM10 was statistically significantly correlated with the passenger flow and train frequency, but the other air pollutants were less impacted by the passenger flow and train frequency.

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“…Compared with 2017, the growth ratio is about 23% (Yang et al, 2019;Zhang et al, 2019a). The annual energy consumption of non-transfer subway station ranges from 1.8 to 2.3 million kW h, while the energy consumption of the ventilation and air conditioning (VAC) system accounts for at least 50% (Ampofo et al, 2003;Guan et al, 2018;Philip and Eric, 2013). The energy consumption is becoming increasingly severe.…”

Section: Introductionmentioning

confidence: 99%

Field investigation on operation parameters and performance of air conditioning system in a subway station

Zhang

Wang

et al. 2019

Energy Exploration & Exploitation

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Ventilation and air conditioning system in subway stations accounts for about 50% of the total energy consumption of the subway stations. The energy consumption ratio of public area to equipment room is about 6.5:3.5. In order to understand the energy saving potential of public areas and equipment rooms, a field measurement for a typical subway station in central China was conducted from 19 to 29 September 2018. The field testing parameters include weather conditions, indoor air temperature and humidity, supply and return air flow rate, chilled water temperature, and flow rate. Meanwhile, some parameters recorded by the system control panel, such as pump frequency, chiller power demand, and energy consumption, were also collected. The paper studied the operating characteristics of the ventilation and air conditioning system and the cooling load pattern of the subway station, focusing on the following three aspects: cooling capacity and power demand of the chiller under different conditions, dynamic cooling capacity of the air handling units, and cooling load characteristics of the equipment rooms. Different operation conditions influence the operation of chiller. It was found that the real power demands under two operation conditions, i.e. minimum and all fresh air modes, are 121 and 77 kW, and the corresponding coefficient of performances are 4.33 and 4.77, respectively. The actual cooling capacity at night is about 80% that of the daytime, and is about 40% of the design value, which indicates that the air handling units operate under partial load. During the testing period, the actual cooling load is about 10–50% of the design load, of which 50–95% is sensible cooling load. These data can help readers understand the overall situation of a typical subway station adequately and provide numerical basis for energy saving optimization of the ventilation and air conditioning system.

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Energy consumption of subway stations in China: Data and influencing factors

Cited by 45 publications

References 17 publications

An Estimation Model on Electricity Consumption of New Metro Stations

An Estimation Model on Electricity Consumption of New Metro Stations

Experimental Investigation of Air Quality in a Subway Station with Fully Enclosed Platform Screen Doors

Field investigation on operation parameters and performance of air conditioning system in a subway station

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