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Research On Load Calculation Of Subway Environmental Control System Based On Estimation Of Passenger Dwell Time In Station

Posted on:2019-02-25Degree:MasterType:Thesis
Country:ChinaCandidate:J H FanFull Text:PDF
GTID:2322330542474978Subject:Transportation planning and management
Abstract/Summary:PDF Full Text Request
The high energy consumption of the urban rail transit system has become one of the most important factors to restrict its sustainable development.The energy consumption of the environmental control system accounts for a large proportion of the energy consumption of the subway station,and the potential for energy conservation is relatively large and should be accurately calculated.Passenger flow parameters as an important variable in the load calculation of the subway environmental control system,there are still a lot of problems such as the value is extensive,leave the difference and dynamics of passenger dwell time in station out of consideration,which resulting in the accuracy of calculation is low.Aiming at the problem of inaccurate passenger flow parameters in the existing load calculation method,a method to estimate the passenger dwell time in station based on AFC data and probability distribution is proposed.Based on this,a refined load calculation method of subway environmental system based on dynamic passenger dwell time in station is proposed,and verified the feasibility and effectiveness of the method through the actual example of Beijing subway station.The research content and main achievements of this paper include the following four parts:(1)Analyzed the constituent of environmental control system load.The structural model analysis method was used to qualitatively analyze the load of subway environmental control system and its influencing factors.The results show that the main factors are passenger flow,train arrival frequency and outdoor weather parameters,and emphatically analyzed the importance of passenger flow factors.(2)A method to estimate the passenger dwell time in station based on AFC data and probability distribution is proposed.Ppassenger dwell time in station is divided into two parts,paid area and unpaid area,using the AFC data and passenger walking time probability distribution respectively to calculate.Compared with the value of passenger flow parameters in the existing load calculation method,this method can provide a more accurate and refined passenger flow parameters for load calculation of environmental control system.(3)A method for calculating the load of subway environmental control systme based on dymanic passenger dwell time in station was established.The passenger flow parameters in the existing load calculation method is changed from the number of passengers in peak hour and the same dwell time to the accumulation result of the passenger dwell time in the statistical period which is proposed in this paper.The method can be used to calculate the load under different time granularities and can improve the refinement of load calculation effectively.(4)In order to validate the validity of the above two methods proposed in this paper,an example application analysis is carried out using Beijing Anhuaqiao subway station.It is found by comparison that,in the same time period,the power consumption corresponding to the load calculation result using the refined calculation method is reduced by 5.8%and 7.4%,respectively the result using existing load calculation method and the measured load data.The effectiveness and practical significance of the refined load calculation method is presented.Finally,the gray relational degree method is used to quantitatively analyze the load of subway environmental control system and its influencing factors,and the conclusion is drawn that the dynamic changes of passenger flow are the main influencing factors of the time-varying load of subway environmental control system.
Keywords/Search Tags:Urban rail transit, Time-space expanded network, Load calculation of subway environmental control system, Extraction of passenger flow parameters, Automatic fare collection(AFC)data, Energy-saving
PDF Full Text Request
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