A train operation diagram scale configuration method and system for reducing traction energy consumption

Abstract

The present invention provides a method and system for configuring a train operation diagram scale that reduces traction energy consumption. The method includes: setting passenger flow OD data, and determining the stop time range of each platform in combination with operational requirements; determining the vehicle bottom turnover time based on the coupling relationship between departure interval, vehicle bottom utilization number, and vehicle bottom turnover time; setting line physical conditions, section passenger capacity, and train traction characteristic curve data, and calculating the traction energy consumption corresponding to different passenger capacities and different operating times in each section; taking the minimum train turnover traction energy consumption and the minimum deviation from the operational specified stop time as the objective function, constructing a train operation diagram scale optimization model, and using the Gurobi solver to solve the train operation diagram scale optimization model to obtain the optimized train stop scale and section operation scale. The present invention starts from the operation perspective of the urban rail transit system, and optimizes the setting of the train operation diagram scale by taking into account the dual goals of transportation capacity and energy saving.

Description

Technical Field

[0001] The present invention relates to the technical field of urban rail transit control, and in particular to a train operation diagram scale configuration method and system for reducing traction energy consumption. Background Art

[0002] With the continuous expansion of urban scale and the stable growth of social economy, the role and status of urban rail in urban public transportation system have become increasingly prominent. In recent years, it has made great progress with the strong support of national and local governments. The energy consumption problem brought about by this cannot be ignored. According to the statistical report of the China Urban Rail Transit Association, the total power consumption of urban rail transit in China in 2023 will be 24.977 billion kW·h, of which traction energy consumption will be 12.934 billion kW·h, an increase of 14.31% year-on-year, accounting for 51.79% of the total power consumption, of which total power consumption and traction energy consumption have reached historical highs. Therefore, energy conservation and emission reduction, cost reduction and efficiency improvement are the outstanding problems facing the current rail transit system.

[0003] The operation diagram scale is the core technical parameter for compiling the train operation diagram, which stipulates the time standard for various operations during the train operation, such as the stop scale, the interval operation diagram scale, the entry and exit scale, and the return scale, etc. Reasonable setting of the operation diagram scale is of great significance to ensuring transportation capacity, optimizing the train operation process, and reducing traction energy consumption. At present, most urban rail transit systems in my country use a set of scales throughout the day, and are generally set based on the goal of maximizing capacity supply, resulting in excessive actual train traction energy consumption. And considering that the urban rail transit passenger flow has uneven temporal and spatial distribution, the use of a set of scales throughout the day will lead to a mismatch between the supply and demand of transportation capacity in some time periods, resulting in energy waste.

[0004] A train operation diagram scale configuration scheme in the prior art proves that the train running time is the determining factor of the train traction energy consumption. Generally speaking, the longer the running time of the interval, the smaller the corresponding traction energy consumption; there is also a scheme to fit the inverse proportional characteristic curve of time energy consumption in different intervals; calculate the redundant time of each interval, and discretize the redundant time to obtain multiple time units. Then, the time unit is pre-allocated to all intervals, and the time unit is allocated to the interval with the largest energy consumption change by comparison until all the redundant time is allocated; there is also a scheme to establish a single-train multi-station operation time optimization model, under the condition of ensuring the total train operation time, the energy consumption and operation time of each train in the interval are redistributed, so that the train's idling distance is increased, thereby reducing the traction energy consumption of the interval operation to achieve energy saving effect; there is also a scheme that introduces in detail the train operation level pre-stored in the ATS system in actual operation, and different levels correspond to different station-to-station operation time and operation curves; there is also a scheme that takes the compression value of the stop time as a variable, and takes the energy saving index and punctuality index as the optimization target to establish a multi-train optimization model during non-peak hours; there is also a scheme to establish a timetable optimization model considering train energy-saving operation, by optimizing the train interval operation time and stop time, find a set of Pareto optimal solutions for energy consumption and time balance, so that the train net energy consumption and passenger time on the train reach the dual goal of optimal. There is also a scheme that analyzes the characteristics of high and flat peak passenger flow and optimizes the operation diagram scale by time period, but does not consider the impact of train load on traction energy consumption.

[0005] The disadvantages of the train operation diagram scale configuration scheme in the above prior art include:

[0006] (1) The current research on energy-saving operation diagrams by scholars at home and abroad mainly focuses on the utilization of train regenerative braking energy. The constructed models are relatively complex and difficult to solve accurately, and the optimization effect is not robust. In reality, if an unexpected event deviates from the scheduled time by a few seconds, the optimization effect will be greatly reduced.

[0007] (2) Existing optimizations for the operation chart scale only consider a single time period or generally divide it into peak and off-peak periods, without carefully considering the passenger flow characteristics of different time periods and the impact of train load on traction energy consumption, resulting in limited optimization effects. Summary of the invention

[0008] The embodiments of the present invention provide a train operation diagram scale configuration method and system for reducing traction energy consumption, so as to effectively improve the energy-saving effect of the train.

[0009] In order to achieve the above object, the present invention adopts the following technical scheme.

[0010] A train operation diagram scale configuration method and system for reducing traction energy consumption, comprising:

[0011] Set the OD data from the passenger flow starting point to the end point, and determine the stop time range of each platform based on the operation requirements;

[0012] Determine the vehicle base turnover time based on the coupling relationship among the departure interval, the number of vehicle bases used and the vehicle base turnover time;

[0013] Set the line physical conditions, section passenger capacity and train traction characteristic curve data, and calculate the traction energy consumption corresponding to different passenger capacities and different running times in each section;

[0014] Taking the stop time range and vehicle turnover time of each platform as constraints, based on the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section, taking the minimum traction energy consumption of train turnover and the minimum deviation of the operation-specified stop time as the objective function, a train operation diagram scale optimization model is constructed, and the Gurobi solver is used to solve the train operation diagram scale optimization model to obtain the optimized train stop scale and section operation scale.

[0015] Preferably, the setting of the OD data from the passenger flow starting point to the end point and determining the stop time range of each station in combination with the operation requirements include:

[0016] Step 1.1: Sort out the operations performed during the train stop process, combine the passenger boarding and alighting process, and construct a formula for calculating the train stop time;

[0017] Step 1.2: Set the OD passenger flow data of the line in the same historical period and calculate the number of passengers getting on and off at each platform;

[0018] Step 1.3: Input the calculated number of passengers getting on and off at each platform into the train stop time calculation formula, and determine the stop time range for each station based on operational requirements.

[0019] Preferably, the operations performed during the train stop in step 1.1 include opening of doors and platform screen doors, boarding and alighting of passengers, closing of doors and platform screen doors, driver confirmation of train safety and waiting for signal opening; wherein opening of doors and platform screen doors, closing of doors and platform screen doors, driver confirmation of train safety and waiting for signal opening are all static operations with fixed operation time; boarding and alighting of passengers are dynamic operations with operation time depending on the number of passengers getting on and off the train, including the process of getting off and the process of getting on;

[0020] The calculation formula for the train stop time is:

[0021] t j =r a ·a j +r b b j +τ

[0022] Where, t jrepresents the train's stop time at platform j; r a Indicates the speed at which passengers get off the bus, in seconds per person; r b Indicates the passenger boarding speed; a j Indicates the number of passengers getting off at platform j of the current train; b j represents the number of people boarding the current train at platform j; τ represents the sum of static operation time, including the opening of doors and platform screen doors, the closing of doors and platform screen doors, the driver confirming the safety of the train, and waiting for the signal to open.

[0023] Preferably, the historical OD passenger flow data of the line in the same period in step 1.2 is the OD passenger flow of the line in the same period on weekdays within the three-month history of the current line. The total number of passengers getting on and off at each platform within 1 hour is calculated, and the number of passengers getting off is calculated as follows:

[0024]

[0025] The number of passengers on board is calculated as follows:

[0026]

[0027] Where D represents the date set, d represents the date index, d∈D={1,2,…,d,…M}, J represents the line platform set, i,j represents the platform index, i,j∈J={1,2,…,i,…,j,…2N}, where N represents the number of stations, 2N represents the number of platforms, 1 to N are up platforms, N+1 to 2N are down platforms, represents the total number of people getting off at platform j during the planning period on day d, represents the total number of people boarding at platform j during the planning period on day d, represents the number of passengers going from platform i to platform j during the planning period of day d, and the two must satisfy the relationship 1≤i<j≤N or N+1≤i<j≤2N;

[0028] Since the departure intervals of trains in the same time period are consistent, and it is assumed that trains arrive evenly in the same time period, the average number of passengers getting on and off each train at each station is calculated:

[0029]

[0030]

[0031] In the formula represents the average number of passengers getting off at platform j per train during the planning period of day d, represents the average number of passengers boarding each train at platform j during the planning period on day d, w d represents the number of service vehicles during the planning period of day d;

[0032] According to the above formula, for any platform j, the number of passengers boarding the bus during the same period on weekdays in the past three months is calculated. and the number of passengers getting off A j and B j The sampling samples of the number of passengers getting on and off at each station during the planning period are formed. The number of passengers getting on and off at each platform during the same operating period is determined to be in accordance with the normal distribution. The mean and variance of the overall distribution are estimated by using the maximum likelihood method through sample estimation. The upper α quantile z of the probability density function of the number of passengers getting on and off is estimated using the calculated value. α :

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039] In the formula, They represent the maximum likelihood estimates of the mean probability density functions of the number of passengers getting off and getting on at platform j during the planning period, represents the maximum likelihood estimate of the variance of the probability density function of the overall standard deviation of the number of people getting off and getting on at platform j during the planning period; are the α quantiles of the probability density function for estimating the number of people getting off and getting on the bus; α is the set probability parameter. The number of passengers and passengers is used as the lower limit for calculating the stop time at each station. The stop time satisfies the passenger flow status of the station with a probability of α.

[0040] Preferably, in step 1.3, the calculated number of passengers getting on and off each platform is input into the train stop time calculation formula, and the stop time range of each station is determined in combination with the operation requirements as follows:

[0041]

[0042]

[0043] In the formula represents the upper limit of the train's stop time at platform j; represents the lower limit of the train's stop time at platform j; t p It indicates the maximum stop time of the train at platform j as stipulated by the operation regulations.

[0044] Preferably, the method of determining the vehicle bottom turnover time based on the coupling relationship among the departure interval, the number of vehicle bottom applications and the vehicle bottom turnover time comprises:

[0045] The coupling relationship among the departure interval, the number of vehicle bottoms used, and the vehicle bottom turnover time is:

[0046] T z =(C+1)·h

[0047] Where, T z It represents the vehicle bottom turnover time in seconds; C represents the number of vehicle bottoms used, and h represents the departure interval.

[0048] Preferably, the setting of line physical conditions, section passenger capacity and train traction characteristic curve data to calculate the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section includes:

[0049] The line physical conditions include section line length, speed limit, ramp and curve information; the train traction characteristic curve data include train traction and braking characteristic curves under different load conditions; the section volume data is the average passenger flow statistics of each section during the planned working day period in the past three months; based on the line physical conditions, section passenger capacity and train traction characteristic curve data, a train traction calculation simulation method is called to calculate the traction energy consumption of the train corresponding to different passenger capacities and different operating times in each section.

[0050] Preferably, the train operation diagram scale optimization model is constructed based on the stop time range and vehicle bottom turnover time of each platform as constraint conditions, and the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section, with the minimum train turnover traction energy consumption and the minimum deviation from the operation specified stop time as the objective function, including:

[0051] Based on the traction energy consumption corresponding to different passenger capacities and different running times in each section, the objective function is to minimize the traction energy consumption of train turnover and minimize the deviation of the stop time specified by the operation. The calculation formula of this objective function is:

[0052]

[0053]

[0054] In the formula Indicates whether the train adopts the operation level r in the section (j, j+1), 1 if it adopts it, and 0 if it does not; It represents the traction energy consumption of the train in the section (j, j+1) with a load of m and operating level r;

[0055] The train must and can only choose one operating level in all sections. The specific calculation formula is:

[0056]

[0057] The train stop time is limited to comply with the stop time range constraints of each platform. The specific calculation formula is:

[0058]

[0059] The vehicle bottom turnover time is limited to meet the constraints of the vehicle bottom turnover time. The specific calculation formula is:

[0060]

[0061] The train is restricted to meet the specified technical speed requirements during operation. The specific calculation formula is:

[0062]

[0063] Where V c To specify the technical speed; L z It is the total running mileage of the train in a single turnover process.

[0064] It can be seen from the technical solutions provided by the above embodiments of the present invention that the present invention optimizes the setting of the train operation diagram scale from the perspective of the operation of the urban rail transit system, taking into account the dual goals of transportation capacity and energy saving. The present invention considers the traction and braking characteristics of trains under different loads in a refined manner, and through reasonable scale configuration, it can reduce the traction energy consumption during train operation while ensuring the transportation capacity.

[0065] Additional aspects and advantages of the present invention will be given in part in the following description, which will become obvious from the following description, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0067] Figure 1 A processing flow chart of a train operation diagram scale configuration method for reducing traction energy consumption provided by an embodiment of the present invention;

[0068] Figure 2 A schematic diagram of a calculation process of a train stop time provided by an embodiment of the present invention;

[0069] Figure 3 and Figure 4A schematic diagram of the corresponding relationship between the passenger flow and probability density of a train provided by an embodiment of the present invention;

[0070] Figure 5 A schematic diagram of the corresponding relationship between the interval running time and energy consumption of a train provided in an embodiment of the present invention;

[0071] Figure 6 A structural diagram of a train operation diagram scale configuration system for reducing traction energy consumption provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0072] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0073] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or coupling. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items.

[0074] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as those generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless defined as herein.

[0075] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings, and each embodiment does not constitute a limitation on the embodiments of the present invention.

[0076] The present invention fully considers the passenger flow characteristics of different time periods and proposes a method for fine-tuning the time-segment train operation diagram scale for energy saving. At the same time, the present invention encapsulates the stop time calculation module, turnaround time calculation module, train traction calculation module, and operation diagram scale optimization module in the optimization process into a system, which can realize the operation diagram scale configuration from scratch.

[0077] The processing flow of a train operation diagram scale configuration method for reducing traction energy consumption provided by an embodiment of the present invention is as follows: Figure 1 As shown, the following steps are included:

[0078] Step S1: Set the passenger flow OD (Origin to Destination) data and determine the stop time range of each platform in combination with the operation requirements.

[0079] The specific process is as follows:

[0080] Step 1.1: Sort out the operations performed during the train stop process, combine the passenger boarding and alighting process, and construct a formula for calculating the train stop time;

[0081] Step 1.2: Set the OD passenger flow data of the line in the same historical period and calculate the number of passengers getting on and off at each platform;

[0082] Step 1.3: Input the calculated number of passengers and passengers into the stop time calculation formula, and determine the stop time range of each station in combination with the operation requirements;

[0083] Step 2: Determine the vehicle base turnover time based on the coupling relationship among the departure interval, the number of vehicle bases used, and the vehicle base turnover time;

[0084] Step 3: Set the line physical conditions, section passenger capacity and train traction characteristic curve data, and calculate the traction energy consumption corresponding to different passenger capacities and different running times in each section.

[0085] Step 4: Taking the stop time range and vehicle bottom turnover time of each platform as constraints, and based on the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section, taking the lowest train turnover traction energy consumption and the smallest deviation from the operation-specified stop time as the objective function, a train operation diagram scale optimization model is constructed, and the Gurobi solver is used to solve the train operation diagram scale optimization model. The train operation diagram scale is optimized by comprehensively considering the passenger service quality and energy-saving requirements, and the optimized train stop scale and section operation scale are obtained.

[0086] The details are as follows:

[0087] Step 4.1: Construct a train operation diagram scale optimization model;

[0088] Step 4.2: Use the Gurobi solver to solve the train operation diagram scale optimization model to obtain the optimized train operation diagram scale.

[0089] Figure 2 A schematic diagram of the calculation process of a train stop time provided by an embodiment of the present invention. The train stop operation described in step 1.1 includes the opening of doors and platform screen doors, passengers boarding and disembarking, the closing of doors and platform screen doors, the driver confirming the safety of the train and waiting for the signal to be opened; among which, the opening of doors and platform screen doors, the closing of doors and platform screen doors, the driver confirming the safety of the train and waiting for the signal to be opened are all static operation contents with fixed operation time; the boarding and disembarking of passengers are dynamic operation contents, and the operation time depends on the number of passengers getting on and off the train. The specific process can be described as two stages: the disembarking process and the boarding process; based on this, the train stop time calculation formula is constructed:

[0090] t j =r a ·a j +r b b j +τ

[0091] In the formula, t j represents the train's stop time at platform j; r a Indicates the speed at which passengers get off the bus, in seconds per person; r b Indicates the passenger boarding speed, in seconds per person; a j Indicates the number of passengers getting off at platform j of the current train; b j represents the number of people boarding the current train at platform j; τ represents the sum of static operation time, including the opening of doors and platform screen doors, the closing of doors and platform screen doors, the driver confirming the safety of the train, and waiting for the signal to open.

[0092] Furthermore, the historical OD passenger flow data of the same period of this line in step 1.2 is the OD passenger flow of this line in the same period of time (1 hour) on weekdays within the three-month history of the current line. The total number of passengers getting on and off at each platform within 1 hour is calculated, and the number of passengers getting off is calculated as follows:

[0093]

[0094] The number of passengers on board is calculated as follows:

[0095]

[0096] In the formula, D represents the date set, d represents the date index, J represents the line station set, i,j represents the station index, Where N is the number of stations, 2N is the number of platforms, 1 to N are up platforms, and N+1 to 2N are down platforms. represents the total number of people getting off at platform j during the planning period on day d, represents the total number of people boarding at platform j during the planning period on day d, It represents the number of passengers going from platform i to platform j during the planning period of day d, and the two must satisfy the relationship 1≤i<j≤N or N+1≤i<j≤2N.

[0097] Since the departure intervals of trains in the same period are consistent and it is assumed that trains arrive evenly in the same period, we can further calculate the average number of passengers getting on and off each train at each station:

[0098]

[0099]

[0100] In the formula represents the average number of passengers getting off at platform j per train during the planning period of day d, represents the average number of passengers boarding each train at platform j during the planning period on day d, w d It represents the number of service vehicles in the planning period of day d.

[0101] According to the above formula, for any platform j, the number of passengers boarding the bus during the same period on weekdays in the past three months can be calculated: and the number of passengers getting off A j and B j A sampling of the number of passengers getting off and getting on at each station during the planning period. Figure 3 and Figure 4 A schematic diagram of the corresponding relationship between the passenger flow and probability density of a train provided by an embodiment of the present invention, combined with Figure 3 , Figure 4 , it is determined that the number of passengers boarding and alighting at each platform during the same operating period conforms to the normal distribution, the mean and variance of the overall distribution are estimated by sample estimation using the maximum likelihood method, and the upper α quantile z of the probability density function of the number of boarding and alighting is estimated using the calculated value α :

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108] In the formula, They represent the maximum likelihood estimates of the mean probability density functions of the number of passengers getting off and getting on at platform j during the planning period, represents the maximum likelihood estimate of the variance of the probability density function of the overall standard deviation of the number of people getting off and getting on at platform j during the planning period; are the α quantiles on the probability density function of the estimated number of people getting off and getting on the bus; α is the set probability parameter.

[0109] Will The number of passengers and passengers is used as the lower limit of the stop time at each station to ensure that the calculated stop time meets the passenger flow status of the station with a probability of α.

[0110] Furthermore, the calculated number of passengers and passengers as described in step 1.3 is input into the stop time calculation formula, and the stop time range of each station is determined in combination with the operation requirements:

[0111]

[0112]

[0113] In the formula represents the upper limit of the train's stop time at platform j; represents the lower limit of the train's stop time at platform j; t p It indicates the maximum stop time of the train at platform j as stipulated by the operation regulations.

[0114] Furthermore, the coupling relationship among the departure interval, the number of vehicle bottom applications and the vehicle bottom turnover time described in step S2 is:

[0115] T z =(C+1)·h

[0116] Where, T z It represents the vehicle bottom turnover time in seconds; C represents the number of vehicle bottoms used, and h represents the departure interval.

[0117] Furthermore, the line physical conditions described in step S3 include section line length, speed limit, ramp and curve information; the train traction characteristic curve data include train traction and braking characteristic curves under different load conditions; the section volume data is the average of the passenger flow statistics of each section during the three-month working day planning period; and the existing mature train traction calculation simulation method is called to calculate the traction energy consumption of the train corresponding to different passenger capacities and different operating times in each section. Figure 5 A schematic diagram of the corresponding relationship between the interval running time and energy consumption of a train provided in an embodiment of the present invention.

[0118] Furthermore, the construction of the train operation diagram scale optimization model described in step 4.1 is as follows:

[0119] (1) The objective function is to minimize the train turnover traction energy consumption and minimize the deviation from the stop time specified by the operation, which can be expressed as:

[0120]

[0121]

[0122] In the formula Indicates whether the train adopts the operation level r in the section (j, j+1), 1 if it adopts it, and 0 if it does not; It represents the traction energy consumption of the train in the section (j, j+1) with a load of m and operating level r;

[0123] (2) Selection uniqueness constraint: The train must and can only choose one operating level in all sections, which is specifically manifested as:

[0124]

[0125] (3) Stop time constraint: The train stop time is limited to the result calculated in step 1.3, which is specifically expressed as follows:

[0126]

[0127] (4) Turnaround time constraint: The vehicle bottom turnover time is limited to the result calculated in step 2, which is specifically expressed as follows:

[0128]

[0129] (5) Technical speed constraints: trains must meet specified technical speed requirements during operation to ensure passenger service quality and capacity requirements. The specific performance is as follows:

[0130]

[0131] Where V c To specify the technical speed; L z It is the total running mileage of the train in a single turnover process.

[0132] Furthermore, the train operation diagram scale optimization model is solved using the Gurobi solver as described in step 4.2 to obtain an optimized train stop time scale and section operation diagram scale.

[0133] The structure of a train operation diagram scale configuration system for reducing traction energy consumption provided by an embodiment of the present invention is as follows: Figure 6 As shown, it includes the following modules:

[0134] The stop time range determination module 10 is used to set the OD data from the passenger flow starting point to the end point, and determine the stop time range of each platform in combination with the operation requirements;

[0135] The vehicle bottom turnover time determination module 20 is used to determine the vehicle bottom turnover time based on the coupling relationship between the departure interval, the number of vehicle bottom applications and the vehicle bottom turnover time;

[0136] The traction energy consumption calculation module 30 is used to set the line physical conditions, the passenger capacity of the section and the train traction characteristic curve data, and calculate the traction energy consumption corresponding to the different passenger capacities and different running times of the train in each section;

[0137] The train operation diagram scale acquisition module 40 is used to construct a train operation diagram scale optimization model based on the stop time range and vehicle bottom turnover time of each platform as constraint conditions, based on the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section, with the minimum traction energy consumption of train turnover and the minimum deviation from the operation specified stop time as the objective function, and use the Gurobi solver to solve the train operation diagram scale optimization model to obtain the optimized train stop scale and section operation scale.

[0138] The specific process of configuring the train operation diagram scale to reduce traction energy consumption using the system of the embodiment of the present invention is similar to the aforementioned method embodiment and will not be repeated here.

[0139] In summary, the present invention optimizes the setting of train operation diagram scales from the perspective of the operation of the urban rail transit system, taking into account the dual goals of transportation capacity and energy saving; the present invention considers the traction and braking characteristics of trains under different loads in a refined manner, and proposes a method and system for finely setting the operation diagram scales in different time periods for energy saving;

[0140] The system included in the present invention comprises a stop time calculation module, a turnaround time calculation module, a train traction calculation module, and an operation diagram scale optimization module, and can realize the operation diagram scale configuration from scratch.

[0141] (1) Based on the temporal and spatial distribution characteristics of the line passenger flow, this aspect carefully considers the impact of platform passenger flow and section passenger flow on the stop scale and operating energy consumption, takes into account the dual needs of passenger service and energy conservation, and constructs an energy-saving operation diagram scale optimization model to reduce the traction energy consumption of train turnover.

[0142] (2) The effectiveness of the proposed method was verified by simulation using actual data from a domestic subway line. The results show that the traction energy consumption can be reduced by up to 12.71% during off-peak hours and by up to 6.69% during peak hours. The proposed method can effectively adapt to the passenger flow characteristics of different operating periods and finely set the operation diagram scale.

[0143] Those skilled in the art can understand that the accompanying drawings are only schematic diagrams of an embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement the present invention.

[0144] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present invention can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention or certain parts of the embodiments.

[0145] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0146] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A train operation diagram scale configuration method for reducing traction energy consumption, characterized in that: include: Set the OD data from the passenger flow starting point to the end point, and determine the stop time range of each platform based on the operation requirements; Determine the vehicle base turnover time based on the coupling relationship among the departure interval, the number of vehicle bases used and the vehicle base turnover time; Set the line physical conditions, section passenger capacity and train traction characteristic curve data, and calculate the traction energy consumption corresponding to different passenger capacities and different running times in each section; Taking the stop time range and vehicle bottom turnover time of each platform as constraint conditions, based on the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section, taking the minimum traction energy consumption of train turnover and the minimum deviation of the stop time specified by the operation as the objective function, a train operation diagram scale optimization model is constructed, and the train operation diagram scale optimization model is solved by using the Gurobi solver to obtain the optimized train stop scale and section operation scale; The above-mentioned setting of passenger flow starting point to end point OD data and determining the stop time range of each platform in combination with operation requirements include: Step 1.1: Sort out the operations performed during the train stop process, combine the passenger boarding and alighting process, and construct a formula for calculating the train stop time; Step 1.2: Set the OD passenger flow data of the line in the same historical period and calculate the number of passengers getting on and off at each platform; Step 1.3: Input the calculated number of passengers getting on and off each platform into the train stop time calculation formula, and determine the stop time range of each station in combination with the operation requirements; The operations performed during the train stop in step 1.1 include opening of doors and platform screen doors, boarding and alighting of passengers, closing of doors and platform screen doors, driver confirmation of train safety and waiting for signal opening; among which, opening of doors and platform screen doors, closing of doors and platform screen doors, driver confirmation of train safety and waiting for signal opening are all static operations with fixed operation time; boarding and alighting of passengers are dynamic operations with operation time depending on the number of passengers getting on and off the train, including the process of getting off and getting on the train; The calculation formula for the train stop time is: t j =r a ·a j +r b ·b j +τ Where, t j represents the train's stop time at platform j; r a Indicates the speed at which passengers get off the bus, in seconds per person; r b Indicates the passenger boarding speed; a j Indicates the number of passengers getting off at platform j of the current train; b j represents the number of people boarding the current train at platform j; τ represents the sum of static operation time, including the opening of doors and platform screen doors, the closing of doors and platform screen doors, the driver confirming the safety of the train, and waiting for the signal to open.

2. The method according to claim 1, characterized in that The historical OD passenger flow data of the same period of this line in step 1.2 is the OD passenger flow of this line in the same period of workdays within the three-month history of the current line. The total number of passengers getting on and off each platform within 1 hour is calculated. The number of passengers getting off is calculated as follows: The number of passengers on board is calculated as follows: Where D represents the date set, d represents the date index, d∈D={1,2,…,d,…M}, J represents the line platform set, i,j represents the platform index, i,j∈J={1,2,…,i,…,j,…2N}, where N represents the number of stations, 2N represents the number of platforms, 1 to N are up platforms, N+1 to 2N are down platforms, represents the total number of people getting off at platform j during the planning period on day d, represents the total number of people boarding at platform j during the planning period on day d, represents the number of passengers going from platform i to platform j during the planning period of day d, and the two must satisfy the relationship 1≤i<j≤N or N+1≤i<j≤2N; Since the departure intervals of trains in the same time period are consistent, and it is assumed that trains arrive evenly in the same time period, the average number of passengers getting on and off each train at each station is calculated: In the formula represents the average number of passengers getting off at platform j per train during the planning period of day d, represents the average number of passengers boarding each train at platform j during the planning period on day d, w d represents the number of service vehicles during the planning period of day d; According to the above formula, for any platform j, the number of passengers boarding the bus during the same period on weekdays in the past three months is calculated. and the number of passengers getting off A j and B j The sampling samples of the number of passengers getting on and off at each station during the planning period are formed. The number of passengers getting on and off at each platform during the same operating period is determined to be in accordance with the normal distribution. The mean and variance of the overall distribution are estimated by using the maximum likelihood method through sample estimation. The upper α quantile z of the probability density function of the number of passengers getting on and off is estimated using the calculated value. α : In the formula, They represent the maximum likelihood estimates of the mean probability density functions of the number of passengers getting off and getting on at platform j during the planning period, represents the maximum likelihood estimate of the variance of the probability density function of the overall standard deviation of the number of people getting off and getting on at platform j during the planning period; are the α quantiles of the probability density function for estimating the number of people getting off and getting on the bus; α is the set probability parameter. The number of passengers and passengers is used as the lower limit for calculating the stop time at each station. The stop time satisfies the passenger flow status of the station with a probability of α.

3. The method according to claim 2, characterized in that In step 1.3, the calculated number of passengers getting on and off each platform is input into the train stop time calculation formula, and the stop time range of each station is determined in combination with the operation requirements as follows: In the formula represents the upper limit of the train's stop time at platform j; represents the lower limit of the train's stop time at platform j; t j,p It indicates the maximum stop time of the train at platform j as stipulated by the operation regulations.

4. The method according to claim 3, characterized in that The method of determining the vehicle bottom turnover time based on the coupling relationship among the departure interval, the number of vehicle bottom applications and the vehicle bottom turnover time includes: The coupling relationship among the departure interval, the number of vehicle bottoms used, and the vehicle bottom turnover time is: T z =(C+1)·h Where, T z It represents the vehicle bottom turnover time in seconds; C represents the number of vehicle bottoms used, and h represents the departure interval.

5. The method according to claim 1, characterized in that: The setting of line physical conditions, section passenger capacity and train traction characteristic curve data, and calculation of the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section, include: The line physical conditions include section line length, speed limit, ramp and curve information; the train traction characteristic curve data include train traction and braking characteristic curves under different load conditions; the section volume data is the average passenger flow statistics of each section during the planned working day period in the past three months; based on the line physical conditions, section passenger capacity and train traction characteristic curve data, a train traction calculation simulation method is called to calculate the traction energy consumption of the train corresponding to different passenger capacities and different operating times in each section.

6. The method according to claim 3, characterized in that The train operation diagram scale optimization model is constructed based on the stop time range and vehicle bottom turnover time of each platform as constraint conditions, the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section, and the minimum train turnover traction energy consumption and the minimum deviation of the operation specified stop time as the objective function, including: Based on the traction energy consumption corresponding to different passenger capacities and different running times in each section, the objective function is to minimize the traction energy consumption of train turnover and minimize the deviation of the stop time specified by the operation. The calculation formula of this objective function is: In the formula Indicates whether the train adopts the operation level r in the section (j, j+1), 1 if it adopts it, and 0 if it does not; It represents the traction energy consumption of the train in the section (j, j+1) with a load of m and operating level r; The train must and can only choose one operating level in all sections. The specific calculation formula is: The train stop time is limited to comply with the stop time range constraints of each platform. The specific calculation formula is: The vehicle bottom turnover time is limited to meet the constraints of the vehicle bottom turnover time. The specific calculation formula is: The train is restricted to meet the specified technical speed requirements during operation. The specific calculation formula is: Where V c To specify the technical speed; L z It is the total running mileage of the train in a single turnover process.

7. A train operation diagram scale configuration system for reducing traction energy consumption, characterized in that: include: The stop time range determination module is used to set the OD data from the starting point to the end point of the passenger flow, and determine the stop time range of each platform in combination with the operation requirements; including: step 1.1: sorting out the operation content performed during the train stop process, and building a train stop time calculation formula in combination with the passenger boarding and alighting process; step 1.2: setting the OD passenger flow data of the line in the same historical period, and calculating the number of passengers boarding and alighting at each platform; step 1.3: inputting the calculated number of passengers boarding and alighting at each platform into the train stop time calculation formula, and determining the stop time range of each station in combination with the operation requirements; the operation content performed during the train stop process in step 1.1 includes opening of doors and platform screen doors, boarding and alighting of passengers, closing of doors and platform screen doors, driver confirmation of train safety and waiting for signal opening; wherein the opening of doors and platform screen doors, closing of doors and platform screen doors, driver confirmation of train safety and waiting for signal opening are all static operation contents with fixed operation time; passenger boarding and alighting are dynamic operation contents, and the operation time depends on the number of passengers getting on and off the train, including the getting off process and the getting on process; The calculation formula for the train stop time is: t j =r a ·a j +r b ·b j +τ Where, t j represents the train's stop time at platform j; r a Indicates the speed at which passengers get off the bus, in seconds per person; r b Indicates the passenger boarding speed; a j Indicates the number of passengers getting off at platform j of the current train; b j represents the number of people boarding the current train at platform j; τ represents the sum of static operation time, including the opening of doors and platform screen doors, the closing of doors and platform screen doors, the driver confirming the safety of the train, and waiting for the signal to open; The vehicle bottom turnover time determination module is used to determine the vehicle bottom turnover time based on the coupling relationship between the departure interval, the number of vehicle bottom applications and the vehicle bottom turnover time; The traction energy consumption calculation module is used to set the line physical conditions, section passenger capacity and train traction characteristic curve data, and calculate the traction energy consumption corresponding to different passenger capacities and different running times in each section; The train operation diagram scale acquisition module is used to construct a train operation diagram scale optimization model based on the stop time range and vehicle bottom turnover time of each platform as constraint conditions, based on the traction energy consumption corresponding to different passenger capacities and different running times of the train in each section, with the minimum train turnover traction energy consumption and the minimum deviation from the operation specified stop time as the objective function, and use the Gurobi solver to solve the train operation diagram scale optimization model to obtain the optimized train stop scale and section operation scale.

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