CN105460048B - Comprehensive energy-saving control method and method integrating optimized manipulation and traffic scheduling for urban rail transit - Google Patents

Abstract

The invention discloses a comprehensive energy-saving control method and method for integrating optimized manipulation and traffic scheduling for urban rail transit. The method comprises the following steps of collecting train scheduling information, train operation parameters and train road condition information according to a train operation line; partitioning and dividing the train operation line into a plurality of segments, and obtaining an accelerating stage and a regenerated brake stage according to the train road condition information of each segment; establishing N traffic scheduling control sequences according to accelerating points and regenerated brake points in the segments, train departure intervals and train operation number, and constructing N traffic scheduling control models according to the N traffic scheduling control sequences; calculating the total energy consumption of each traffic scheduling control model so as to obtain the traffic scheduling control model corresponding to the lowest total energy consumption; and obtaining a traffic scheduling control timetable according to the traffic scheduling control model corresponding to the lowest total energy consumption. The timetable has the advantages of being capable of coordinating the balanced relation among the train number, the operation parameters and regenerated brake in a self-adapting manner, high in calculating efficiency, precise in computation and the like.

Description

Comprehensive energy-saving control method and device for optimizing control and driving scheduling of urban rail transit

Technical Field

The invention relates to the technical field of energy-saving control of urban rail transit vehicles, in particular to an energy-saving control method and device of urban rail transit vehicles, which integrates optimized operation and driving scheduling.

Background

The 2015 government work report indicates that the consciousness of energy conservation and environmental protection is further improved, the energy conservation and environmental protection are taken as a major technological attack in China, the energy conservation and environmental protection transformation of enterprises in China is accelerated, and the energy conservation and environmental protection technology is listed as the core competitiveness of enterprises in China. The railway transportation department as a vital transportation service provider in the economic development of China has a wide development prospect due to the advantages of large transportation capacity, economy, environmental friendliness and the like compared with other transportation tools. However, while providing the quick service, the railway department consumes a large amount of energy in the transportation process, so it is necessary to improve the energy utilization efficiency of the railway department to better exert the transportation service advantages of the railway department, and especially in recent years, with the rapid development of railway and urban rail transit construction and the continuous deepening of railway reform, the railway department as an important transportation service provider has the mission and responsibility of continuously reducing the cost, optimizing the industrial structure and striving for the maximum economic profit as other operation subjects in the market. Meanwhile, the annual increase of railway traffic volume and the large-area speed increase of railways in China continuously improve the running speed, the traction weight and the operation density of trains, and the energy consumption of the trains is rapidly increased. How to ensure the safe, comfortable and accurate operation of the train, and simultaneously reduce the energy consumption to the maximum extent and the operation cost, not only meets the actual requirements of the railway transportation development in China, but also responds to the inevitable requirements of constructing a resource-saving and environment-friendly society in China, thereby having important significance for energy-saving research on the train. Improvements in vehicle equipment and infrastructure technology require long periods of time and high capital investment, thus limiting train energy efficient operation. And the short-term or middle-term strategy for improving the train energy-saving optimized operation method to improve the energy utilization efficiency does not need high investment, so that under certain hardware environments of traction locomotives, vehicles, lines and the like and under the operation management conditions of established operation diagrams, train marshalling plans and the like, a train operation energy consumption calculation method is explored to find the optimal operation mode of the locomotives, and the method is an economic, effective and directly feasible energy-saving way.

At present, domestic and foreign railway researchers mainly concentrate on the field of train energy-saving control and regenerative braking aiming at the research of train energy-saving optimization operation methods, and the research of the energy-saving control method comprehensively considering train optimization operation and train dispatching is less. In 2014, an Indian scholars Nirmala establishes an optimization model of train scheduling by constructing OD matrixes of train number, route and transportation network, and solves by adopting a genetic algorithm to achieve the aim of energy conservation. Tomoyuki et al, Japan railway technology research institute 2014, further searched for an effective train energy-saving operation method by exploring energy-saving driving of train regenerative braking energy loss. In 2013, a French scholar Chevrier et al calculates and selects an optimal railway scheduling schedule by adopting a dual-target calculation method, so that the aim of energy-saving operation of a train is fulfilled. Spain scholars in 2012By designing a train running scheduling timetable, the train running scheduling timetable is further designedAnd determining the maximum overlapping time of the braking time of the rail vehicle and the acceleration time of the train in the same power supply interval, and improving the utilization rate of the regenerative energy of the train. The 2012 Spanish scholars Cucala establishes a fuzzy linear programming model for schedule optimization of train operation scheduling by taking uncertainty of train operation delay and quasi-point operation factors as fuzzy parameters based on a genetic algorithm. In China, the Beijing university of transportation in 2013 carries out integrated design by saving energy for one vehicle and utilizing regenerated energy cooperatively for multiple vehicles, and provides a schedule making method for reducing the total energy consumption of the system.

However, the train operation control energy-saving schedule of the prior art cannot establish an effective train energy-saving schedule for single-train energy saving and multi-train cooperative utilization of regenerative braking energy.

The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.

Disclosure of Invention

The invention aims to provide an urban rail transit optimizing operation and driving dispatching comprehensive energy-saving control method, so that the defect that an effective train driving control energy-saving schedule of single-train energy saving and multi-train cooperative utilization of regenerative braking energy cannot be established in train driving dispatching in the prior art is overcome.

In order to achieve the purpose, the invention provides a comprehensive energy-saving control method for urban rail transit optimized operation and driving scheduling, which comprises the following steps: train scheduling information, train operation parameters and train road condition information are acquired according to a train operation line, wherein the train scheduling information comprises: train operation quantity, train departure interval, punctual time and distance between stations, train operation parameter includes: the maximum allowable speed, the maximum allowable acceleration and the train weight, wherein the train road condition information comprises: gradient, distance between the ramp and the starting point, length of the ramp, length of the bend and distance between the bend and the starting point; dividing a train running line into a plurality of sections, wherein the speeds of junction points between every two adjacent sections are the same, and acquiring at least one acceleration stage and at least one regenerative braking stage according to the train road condition information of each section so as to correspondingly acquire at least one acceleration point and at least one regenerative braking point of each section; establishing N driving scheduling control sequences according to at least one accelerating point, at least one regenerative braking point, a train departure interval and the train running number in the plurality of sections, and establishing N driving scheduling control models according to the N driving scheduling control sequences; calculating the total energy consumption of each traffic scheduling control model to obtain the traffic scheduling control model corresponding to the lowest total energy consumption; and acquiring a traffic scheduling control moment table according to the traffic scheduling control model corresponding to the lowest total energy consumption.

Preferably, in the above technical solution, the driving schedule control model M is:

wherein, a_qnIs an acceleration, and a_qn≤a_max；v_bkFor the optimum uniform speed after acceleration, and v_bk≤v_bmax；v_wnIs the speed after a curve, and v_wm≤v_max；a_QnIs a second acceleration, and a_Qn≤a_max；v_BkIs the optimum uniform velocity after the second acceleration, and v_Bk≤v_bmax；v_dyIs the speed after regenerative braking, and v_dy≤v_max(ii) a n is the total number of the acceleration or the speed in the allowable range; t is_minSending the train for a minimum interval time; t is_maxThe maximum interval time for train departure; r is a minimum real number, is a decomposition coefficient of a train departure interval, and can be adjusted according to specific road conditions and calculation precision; a is_maxIs the maximum acceleration, v_bmaxAt maximum operating speed, v_maxIs the maximum post-deceleration speed.

Preferably, in the above technical solution, the obtaining of the driving schedule control schedule according to the driving schedule control model corresponding to the lowest total energy consumption specifically includes: establishing a regenerative braking energy model in cooperation with at least one regenerative braking stage of the plurality of sections according to the train operation number; acquiring the utilization rate of regenerative braking energy according to the regenerative braking energy model; and establishing a running scheduling control timetable meeting constraint conditions by combining the train running parameters and a running scheduling control model corresponding to the lowest total energy consumption according to the utilization rate of the regenerative braking energy.

Preferably, in the above technical solution, the regenerative braking energy J_zComprises the following steps:

in the formula, v_yFor limiting speed of curve, v_kFor air brake speed, r (v) ═ a + bv + cv²(a, b, c are train running resistance coefficients), Δ t_y+1＝t_y+1-t_y(y＝0,1,2,…),Δt_u+1＝t_u+1-t_u(u＝0,1,2,…)。

Preferably, in the above technical solution, the constraint condition includes: distance constraint conditions, quasi-point time constraint conditions and distance time constraint conditions;

the distance constraint conditions are as follows: s (t, a, v) ═ S

The quasi-point time constraint conditions are as follows: t (T, a, v) is less than or equal to T

The distance time constraint conditions are as follows:

wherein S and T are train punctual time and inter-station distance, respectively, and S (T, a, v) is when the train runs according to a certain train control sequenceDistance traveled, T (T, a, v) being the time of travel of a train when it is driven according to a train control sequence, T_min，T_maxRespectively representing the lower limit and the upper limit of the departure interval of the train; t is t_min，t_maxRespectively, the lower limit and the upper limit of the station stop time.

The invention also aims to provide an urban rail transit optimizing operation and driving dispatching comprehensive energy-saving control device, so as to overcome the defect that an effective train driving control energy-saving schedule with single-train energy saving and multi-train cooperative regenerative braking energy utilization cannot be established in train driving dispatching in the prior art.

In order to achieve the above object, the present invention provides an energy-saving control device for optimizing and controlling urban rail transit and scheduling, comprising: the data acquisition module is used for acquiring train scheduling information, train operation parameters and train road condition information according to a train operation line, wherein the train scheduling information comprises: train operation quantity, train departure interval, punctual time and distance between stations, train operation parameter includes: the maximum allowable speed, the maximum allowable acceleration and the train weight, wherein the train road condition information comprises: gradient, distance between the ramp and the starting point, length of the ramp, length of the bend and distance between the bend and the starting point; the parameter acquisition module is used for dividing the train running line into a plurality of sections, wherein the speeds of the junction points between every two adjacent sections are the same, and at least one acceleration stage and at least one regenerative braking stage are acquired according to the train road condition information of each section so as to correspondingly acquire at least one acceleration point and at least one regenerative braking point of each section; the model establishing module is used for establishing N driving scheduling control sequences according to at least one accelerating point, at least one regenerative braking point, train departure intervals and train running number in the plurality of sections and establishing N driving scheduling control models according to the N driving scheduling control sequences; the energy consumption calculation module is used for calculating the total energy consumption of each traffic scheduling control model so as to obtain the traffic scheduling control model corresponding to the lowest total energy consumption; and the schedule output module is used for acquiring the driving scheduling control schedule according to the driving scheduling control model corresponding to the lowest total energy consumption.

Preferably, in the above technical solution, the driving schedule control model M is:

wherein, a_qnIs an acceleration, and a_qn≤a_max；v_bkFor the optimum uniform speed after acceleration, and v_bk≤v_bmax；v_wnIs the speed after a curve, and v_wm≤v_max；a_QnIs a second acceleration, and a_Qn≤a_max；v_BkIs the optimum uniform velocity after the second acceleration, and v_Bk≤v_bmax；v_dyIs the speed after regenerative braking, and v_dy≤v_max(ii) a n is the total number of the acceleration or the speed in the allowable range; t is_minSending the train for a minimum interval time; t is_maxThe maximum interval time for train departure; r is a minimum real number, is a decomposition coefficient of a train departure interval, and can be adjusted according to specific road conditions and calculation precision; a is_maxIs the maximum acceleration, v_bmaxAt maximum operating speed, v_maxIs the maximum post-deceleration speed.

Preferably, in the above technical solution, the obtaining of the driving schedule control timetable according to the driving schedule control model corresponding to the lowest total energy consumption in the timetable output module specifically includes: establishing a regenerative braking energy model in cooperation with at least one regenerative braking stage of the plurality of sections according to the train operation number; acquiring the utilization rate of regenerative braking energy according to the regenerative braking energy model; and establishing a running scheduling control timetable meeting constraint conditions by combining the train running parameters and a running scheduling control model corresponding to the lowest total energy consumption according to the utilization rate of the regenerative braking energy.

Preferably, in the above technical solution, the regenerative braking energy J_zComprises the following steps:

in the formula, v_yFor limiting speed of curve, v_kFor air brake speed, r (v) ═ a + bv + cv²(a, b, c are train running resistance coefficients), Δ t_y+1＝t_y+1-t_y(y＝0,1,2,…),Δt_u+1＝t_u+1-t_u(u＝0,1,2,…)。

Preferably, in the above technical solution, the constraint condition includes: distance constraint conditions, quasi-point time constraint conditions and distance time constraint conditions;

the distance constraint conditions are as follows: s (t, a, v) ═ S

The quasi-point time constraint conditions are as follows: t (T, a, v) is less than or equal to T

The distance time constraint conditions are as follows:

compared with the prior art, the comprehensive energy-saving control method and device for urban rail transit optimization operation and traffic scheduling, disclosed by the invention, have the advantages that by utilizing the matrix and calculus control thought, the train running line partition is decomposed into a plurality of sections, fitted with the departure interval and coded; constructing a comprehensive matrix control model of train energy-saving optimized operation and train dispatching according to the combined control of different sections, departure intervals and train operation quantity; and finally, establishing an optimal energy-saving control timetable model of the train on the basis of the minimum total energy consumption of train operation and the energy regeneration of the single-train energy-saving optimized operation and the multi-train cooperative utilization. The method and the device comprehensively consider train control factors such as departure intervals, road conditions of ramps, curves and composite lines thereof, regenerative braking, driving scheduling and the like, can accurately calculate and design the most energy-saving control departure schedule of the trains, have the balance relationship among the self-adaptive coordination of the number of the trains, the operation parameters and the regenerative braking, and have the advantages of high calculation efficiency, accurate operation, wide application range and the like.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

FIG. 1 is a flow chart of an urban rail transit optimization operation and driving scheduling comprehensive energy-saving control method according to the invention.

Fig. 2 is a subway train regenerative braking energy utilization pattern according to the present invention.

Fig. 3 is a structural diagram of the comprehensive energy-saving control device for urban rail transit optimization operation and driving scheduling according to the invention.

Detailed Description

The following detailed description of the present invention is provided in conjunction with the accompanying drawings, but it should be understood that the scope of the present invention is not limited to the specific embodiments.

As shown in fig. 1, the method for comprehensive energy-saving control of urban rail transit optimization operation and driving scheduling according to the embodiment of the present invention includes the following steps:

step S100: and acquiring train scheduling information, train operation parameters and train road condition information according to the train operation line.

Specifically, train scheduling information, train operation parameters and train road condition information are acquired by using a vehicle-mounted sensor, and the train scheduling information, the train operation parameters and the train road condition information are transmitted based on a vehicle-mounted Ethernet. Based on the transmission mode of the vehicle-mounted Ethernet, the high efficiency and accuracy of data transmission are ensured; the acquired train scheduling information, train operation parameters and train road condition information are determined according to the specific operation line plan and the type of the subway train.

The train scheduling information includes: train operation quantity, train departure interval, punctual time and distance between stations, train operation parameter includes: the maximum allowable speed, the maximum allowable acceleration and the train weight, wherein the train road condition information comprises: slope, ramp distance from starting point, ramp length, curve length, and curve distance from starting point.

Step S101: the method comprises the steps of dividing a train running line into a plurality of sections, enabling speeds of connecting points between every two adjacent sections to be the same, and obtaining at least one acceleration stage and at least one regenerative braking stage according to train road condition information of each section so as to correspondingly obtain at least one acceleration point and at least one regenerative braking point of each section.

Based on the characteristics, in the embodiment of the invention, a calculus control method is adopted to carry out differential decomposition on train running lines, train departure intervals and train running quantity, wherein the differential decomposition of the train running lines refers to the decomposition of the train running lines into a plurality of sections, each section comprises at least one acceleration stage and at least one regenerative braking stage so as to correspondingly obtain at least one acceleration point and at least one regenerative braking point of each section, and when the train running lines are divided into a plurality of sections, the speeds of connecting points between every two adjacent sections are the same. Differential decomposition workshopThe interval means taking a minimum real number r, and taking a minimum departure interval T_minAnd the maximum departure interval T_maxThe time decomposition, the differential decomposition of the train running number refers to the decomposition of the train number, the acceleration, the regenerative braking and other operation methods into a plurality of modes.

Meanwhile, in order to improve the calculation efficiency and the calculation accuracy, the minimum acceleration at the initial acceleration or the end point of the regenerative braking deceleration stage is set as a connection point, and the train operation line is divided into sections. When a plurality of acceleration stages and a plurality of regenerative braking stages exist in the running process of the train, the permutation and combination established based on the running line of the train, the departure interval of the train, the running number of the train and the like can be minimum on the basis of the method, and the calculation efficiency is higher as the control sequence of the permutation and combination is less.

Step S102: and establishing N driving scheduling control sequences according to at least one accelerating point, at least one regenerative braking point, a train departure interval and the train running number in the plurality of sections, and establishing N driving scheduling control models according to the N driving scheduling control sequences.

Specifically, the matrix method is adopted for permutation and combination, where the matrix method is adopted for permutation and combination of a plurality of decomposed sections, train departure intervals, and train operation numbers by adopting a matrix method, so as to obtain control sequences (i.e., N train operation scheduling control sequences) with different train operations, as shown in fig. 2, an example of a permutation sequence of two trains is shown.

In this embodiment, the control sequence parameters of the driving scheduling control model include: acceleration, optimal uniform speed after acceleration, speed after regenerative braking and train departure interval; the driving scheduling control model M is expressed as:

wherein, a_qnIs an acceleration, and a_qn≤a_max；v_bkFor the optimum uniform speed after acceleration, and v_bk≤v_bmax；v_wnIs the speed after a curve, and v_wm≤v_max；a_QnIs a second acceleration, and a_Qn≤a_max；v_BkIs the optimum uniform velocity after the second acceleration, and v_Bk≤v_bmax；v_dyIs the speed after regenerative braking, and v_dy≤v_max(ii) a n is the total number of the acceleration or the speed in the allowable range; t is_minSending the train for a minimum interval time; t is_maxThe maximum interval time for train departure; r is a minimum real number, is a decomposition coefficient of a train departure interval, and can be adjusted according to specific road conditions and calculation precision; a is_maxIs the maximum acceleration, v_bmaxAt maximum operating speed, v_maxIs the maximum post-deceleration speed.

Step S103: and calculating the total energy consumption of each traffic scheduling control model to obtain the traffic scheduling control model corresponding to the lowest total energy consumption.

Step S104: and acquiring a traffic scheduling control moment table according to the traffic scheduling control model corresponding to the lowest total energy consumption.

More specifically, on the basis of single-train energy-saving optimized operation and multi-train cooperative utilization of regenerative braking energy, the minimum total energy consumption of train operation is taken as an objective function to establish a model of an optimal train operation scheduling control energy-saving schedule of the train, and the method specifically comprises the following steps:

establishing a single-train energy-saving optimized operation and multi-train cooperative utilization regenerative braking energy model according to the train operation number and at least one regenerative braking stage of a plurality of sections, wherein the model mainly comprises two modes of front train braking and rear train traction (as shown in fig. 2, regenerative braking energy generated by front train braking is used for rear train traction) or front train traction and rear train braking (as shown in fig. 2, regenerative braking energy generated by rear train braking is used for front train traction), and the key point of the regenerative braking energy recycling is that at least two trains are simultaneously braked and pulled in the same power supply section, and the pulled trains can absorb the regenerative energy generated by train braking;

the regenerative braking energy model is as follows:

in the formula, v_yFor limiting speed of curve, v_kFor air brake speed, r (v) ═ a + bv + cv²(a, b, c are train running resistance coefficients), Δ t_y+1＝t_y+1-t_y(y＝0,1,2,…),Δt_u+1＝t_u+1-t_u(u＝0,1,2,…)。

Acquiring the utilization rate of regenerative braking energy according to the regenerative braking energy model;

specifically, the utilization rate of the regenerative braking energy of the inter-station train is calculated through two modes, and is represented by the area of the overlapping part of a speed-time curve generated by two control methods of front train braking, rear train traction or front train traction and rear train braking, and the area of the overlapping part can be calculated by the time of the overlapping part.

And establishing an optimal driving dispatching control timetable meeting constraint conditions by combining the train operation parameters and the driving dispatching control model corresponding to the lowest total energy consumption according to the utilization rate of the regenerative braking energy.

The constraint conditions include: distance constraint conditions, quasi-point time constraint conditions and distance time constraint conditions;

the distance constraint conditions are as follows: s (t, a, v) ═ S

The quasi-point time constraint conditions are as follows: t (T, a, v) is less than or equal to T

The distance time constraint conditions are as follows:

wherein S and T are train punctual time and inter-station distance, respectively, and S (T, a, v) is that the train moves according to a certain train control sequenceDistance traveled while driving, T (T, a, v) being the time of travel of a train when it is driven according to a certain train control sequence, T_min，T_maxRespectively representing the lower limit and the upper limit of the departure interval of the train; t is t_min，t_maxRespectively representing the lower limit and the upper limit of the station stop time, min J_{General assembly}And t, a and v are train operation parameters for the lowest total energy consumption.

And finally, importing departure intervals, speed curves and acceleration curves established by the optimal train running scheduling control timetable into a station control center and a train vehicle-mounted control unit to control a plurality of traffic vehicles on the urban rail, wherein the optimal train running scheduling control timetable is the timetable corresponding to the time when the total energy consumption of all trains on a certain line is the lowest during running of the certain line.

The specific flow of the method is described in detail by an embodiment as follows:

example one

In the actual running process of the train, as the running lines of the ordinary train are all in complex road conditions such as uphill, downhill or curve, the subway train is started and braked more frequently in running, and the running condition is more complex. In the first embodiment, the regenerative braking energy utilization manner of a B2 train running in a certain section of a line in a certain city is specifically analyzed as an example, and is shown in fig. 2.

Let the stop time of the train at the s-th station be t^sThe regenerative braking energy utilization can be divided into two types, namely front vehicle braking, rear vehicle traction, traction and rear vehicle braking. The first type of regenerative braking utilization can be classified into modes of 1-3 regenerative braking utilization, and the second type of regenerative braking utilization can be classified into modes of 4-6 regenerative braking utilization, specifically, the regenerative energy utilization is 1 corresponding to the overlap time:

the overlap time corresponding to the regeneration energy utilization 2 is

The regenerative energy utilization 3 corresponds to an overlap time of

In the 1-3 mode for regenerative braking, s is the s-th station (s ═ 3,5,7, …)])，The time for the first acceleration of the train is,the time for accelerating the train after a curve is taken,the coasting time before the curve is the coasting time,the coasting time is the coasting time before the (s + 1) th station after the curve of the train,for the constant-speed operation time before the curve,the constant-speed running time of the train before the (s + 1) th station after the curve is obtained,the regenerative braking time before the curve is taken,the regenerative braking time before the (s + 1) th station after the curve of the train,is the air brake time, T is the departure interval of the train,the time for the train to travel on the curve is,the time of the train running on the ramp.

The second regenerative braking utilization type can be divided into 4-6 modes of regenerative braking utilization, and specifically, the corresponding overlapping time of the 4 regenerative energy utilization modes is as follows:

the regenerative energy utilization 5 corresponds to an overlap time of

The regenerative energy utilization 6 corresponds to an overlap time of

In the formula using 4-6 modes for regenerative braking, s ═ 2,4,6, …]，t^sThe stop time of the train at the s station is shown.

When the train running line does not have a ramp, a curve or a line formed by compounding the ramp, the curve or the curve, the regenerative braking energy utilization modes of the train are only 1 and 3, at the moment,

gauge for utilizing regenerative braking energyLaw, a set of train control time series can be obtainedEach group of train control time sequence corresponds to one group of train operation control sequenceWherein,is the first acceleration, a_maxThe maximum acceleration of the train is obtained,for the optimum operating speed after the first acceleration,for curve running speed, v_w-maxFor the maximum allowable operating speed of the curve,is the acceleration in the second phase of the acceleration,is the speed after the second acceleration,is the regenerative post-braking speed.

According to train control time sequenceEstablishing a train regenerative braking energy utilization function R, which specifically comprises the following steps:

the regeneration energy utilization in a certain section of the above analysis was:

the energy consumption of the train in the section is as follows:

the energy consumption of the entire operating line can thus be expressed as:

the calculation constraint conditions are as follows:

in the formula, T_min，T_maxRespectively representing the lower limit and the upper limit of the departure interval; t is t_min，t_maxRespectively, the lower limit and the upper limit of the station stop time.

Based on a matrix and calculus control idea, constructing a real matrix control model of a train control strategy and train departure intervals:

and r is a minimum real number and can be adjusted according to specific road conditions and calculation accuracy. If a certain line of the urban rail transit vehicle runs between N stations, the train running control strategy between each station of the line can be calculated and recorded asEach inter-station control strategy corresponds toA set of timesThen determining the overlapping time Ts, and then controlling the time groups corresponding to different row control sequencesSubstituting the energy consumption calculation function to solve to obtain min J meeting the constraint condition_{General assembly}Their corresponding control sequencesAnd the departure interval T is the comprehensive optimal control mode of the optimized operation and the running scheduling of the urban rail transit vehicle.

In the first embodiment, in order to increase the convergence rate and reduce the convergence time, the initial starting acceleration is set to be not less thanOptimum running speed is not less thanThe running speed of the curve is not less thanThe data obtained by the optimizing calculation of the computer shows that the total energy consumption for operation among the lines is 45.28kw · h, is less than the planned energy consumption value 50.01kw · h, saves the energy consumption by about 10% compared with the planned operation line, and the utilization rate of the regenerative braking energy is 0.2819, so that the method can meet the energy-saving optimized operation requirement of the train.

The flow of the comprehensive energy-saving control method based on the urban rail transit vehicle optimization operation and the driving scheduling is described in detail above, the method can also be realized by a device, and the structure and the function of the device are described in detail below.

The comprehensive energy-saving control device for optimizing operation and scheduling of urban rail transit, which is provided by the embodiment of the invention and is shown in fig. 3, comprises:

the data acquisition module 301 is configured to acquire train scheduling information, train operation parameters, and train road condition information according to a train operation route, where the train scheduling information includes: train operation quantity, train departure interval, punctual time and distance between stations, train operation parameter includes: maximum allowable speed, maximum allowable acceleration and train weight, and the train road condition information includes: gradient, distance between the ramp and the starting point, length of the ramp, length of the bend and distance between the bend and the starting point;

a parameter obtaining module 302, configured to decompose a train operation line partition into multiple segments, where speeds at junctions between adjacent segments are the same, and obtain at least one acceleration stage and at least one regenerative braking stage according to train road condition information of each segment, so as to correspondingly obtain at least one acceleration point and at least one regenerative braking point of each segment;

the model establishing module 303 is configured to establish N driving scheduling control sequences according to at least one acceleration point and at least one regenerative braking point in the plurality of sections and a train departure interval and the train running number, and establish N driving scheduling control models according to the N driving scheduling control sequences;

the energy consumption calculation module 304 is configured to calculate total energy consumption of each driving scheduling control model to obtain a driving scheduling control model corresponding to the lowest total energy consumption;

and the schedule output module 305 is configured to obtain the driving scheduling control schedule according to the driving scheduling control model corresponding to the lowest total energy consumption.

In this embodiment, the driving schedule control model M is:

wherein, a_qnIs an acceleration, and a_qn≤a_max；v_bkFor the optimum uniform speed after acceleration, and v_bk≤v_bmax；v_wnIs the speed after a curve, and v_wm≤v_max；a_QnIs a second acceleration, and a_Qn≤a_max；v_BkIs the optimum uniform velocity after the second acceleration, and v_Bk≤v_bmax；v_dyIs the speed after regenerative braking, and v_dy≤v_max(ii) a n is the total number of the acceleration or the speed in the allowable range; t is_minSending the train for a minimum interval time; t is_maxThe maximum interval time for train departure; r is a minimum real number, is a decomposition coefficient of a train departure interval, and can be adjusted according to specific road conditions and calculation precision; a is_maxIs the maximum acceleration, v_bmaxAt maximum operating speed, v_maxIs the maximum post-deceleration speed.

In this embodiment, the obtaining of the driving schedule control schedule according to the driving schedule control model corresponding to the lowest total energy consumption in the schedule output module 305 specifically includes:

establishing a regenerative braking energy model in cooperation with at least one regenerative braking stage of the plurality of sections according to the train operation number;

acquiring the utilization rate of regenerative braking energy according to the regenerative braking energy model;

and establishing an optimal running scheduling schedule meeting constraint conditions by combining the train running parameters and a running scheduling control model corresponding to the lowest total energy consumption according to the utilization rate of the regenerative braking energy.

In this embodiment, the regenerative braking energy J_zComprises the following steps:

in the formula, v_yFor limiting speed of curve, v_kFor air brake speed, r (v) ═ a + bv + cv²(a, b, c are train running resistance coefficients), Δ t_y+1＝t_y+1-t_y(y＝0,1,2,…),Δt_u+1＝t_u+1-t_u(u＝0,1,2,…)。

In this embodiment, the constraint condition includes: distance constraint conditions, quasi-point time constraint conditions and distance time constraint conditions;

the distance constraint conditions are as follows: s (t, a, v) ═ S

The quasi-point time constraint conditions are as follows: t (T, a, v) is less than or equal to T

The distance time constraint conditions are as follows:

wherein S and T are train punctuation time and inter-station distance, respectively, S (T, a, v) is the running distance of the train when running according to a certain train control sequence, T (T, a, v) is the running time of the train when running according to a certain train control sequence, T_min，T_maxRespectively representing the lower limit and the upper limit of the departure interval of the train; t is t_min，t_maxRespectively representing the lower limit and the upper limit of the station stop time, min J_{General assembly}And t, a and v are train operation parameters for the lowest total energy consumption.

In summary, the comprehensive energy-saving control method and device for urban rail transit optimization operation and traffic scheduling in the invention decomposes the train operation line partition into a plurality of sections by using matrix and calculus control thought, and fits and encodes with departure intervals; constructing a comprehensive matrix control model of train energy-saving optimized operation and train dispatching according to the combined control of different sections, departure intervals and train operation quantity; and finally, establishing an optimal energy-saving control timetable model of the train on the basis of the minimum total energy consumption of train operation and the energy regeneration of the single-train energy-saving optimized operation and the multi-train cooperative utilization. The method and the device comprehensively consider train control factors such as departure intervals, road conditions of ramps, curves and composite lines thereof, regenerative braking, driving scheduling and the like, can accurately calculate and design the most energy-saving control departure schedule of the trains, have the balance relationship among the self-adaptive coordination of the number of the trains, the operation parameters and the regenerative braking, and have the advantages of high calculation efficiency, accurate operation, wide application range and the like.

While the present invention is susceptible of embodiment in many different forms, there is shown in the drawings, and herein will be described in detail, specific embodiments with reference to the accompanying drawings, which are not intended to limit the invention to the specific forms set forth herein, but rather to limit the invention to the specific forms set forth herein.

Those of ordinary skill in the art will understand that: all or part of the steps of implementing the embodiments of the apparatus may be implemented by hardware related to program instructions, where the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the embodiments of the method; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. An urban rail transit optimization operation and driving scheduling comprehensive energy-saving control method is characterized by comprising the following steps:

train scheduling information, train operation parameters and train road condition information are acquired according to a train operation line, wherein the train scheduling information comprises: train operation quantity, train departure interval, punctual time and distance between stations, train operation parameter includes: the maximum allowable speed, the maximum allowable acceleration and the train weight, wherein the train road condition information comprises: gradient, distance between the ramp and the starting point, length of the ramp, length of the bend and distance between the bend and the starting point;

dividing a train running line into a plurality of sections, wherein the speeds of junction points between every two adjacent sections are the same, and acquiring at least one acceleration stage and at least one regenerative braking stage according to the train road condition information of each section so as to correspondingly acquire at least one acceleration point and at least one regenerative braking point of each section;

establishing N driving scheduling control sequences according to at least one accelerating point, at least one regenerative braking point, a train departure interval and the train running number in the plurality of sections, and establishing N driving scheduling control models according to the N driving scheduling control sequences;

calculating the total energy consumption of each traffic scheduling control model to obtain the traffic scheduling control model corresponding to the lowest total energy consumption;

acquiring a driving scheduling control time table according to a driving scheduling control model corresponding to the lowest total energy consumption, wherein the driving scheduling control model M is as follows:

$M=\left(\[a_{q1},a_{q2},\mathrm{...},a_{qn}\]\·\left[\begin{array}{c}{v}_{b1}\\ v_{b2}\\ \begin{array}{c}.\\ .\\ .\end{array}\\ v_{bk}\end{array}\right]\·\[v_{w1},v_{w2},\mathrm{...},v_{wm}\]+\[a_{Q1},a_{Q2},\mathrm{...},a_{Qn}\]\·\left[\begin{array}{c}{v}_{B1}\\ v_{B2}\\ \begin{array}{c}.\\ .\\ .\end{array}\\ v_{Bk}\end{array}\right]\·\[v_{d1},v_{d2},\mathrm{...},v_{dy}\]\right)\·\left[\begin{array}{c}{T}_{\min }\\ T_{\min }+r\\ T_{\min }+2r\\ \begin{array}{c}.\\ .\\ .\end{array}\\ T_{\min }+\left(x-1\right)r\\ T_{\max }\end{array}\right]$

wherein, a_qnIs an acceleration, and a_qn≤a_max；v_bkFor the optimum uniform speed after acceleration, and v_bk≤v_bmax；v_wnIs the speed after a curve, and v_wm≤v_max；a_QnIs a second acceleration, and a_Qn≤a_max；v_BkIs the optimum uniform velocity after the second acceleration, and v_Bk≤v_bmax；v_dyIs the speed after regenerative braking, and vd_y≤v_max(ii) a n is the total number of the acceleration or the speed in the allowable range; t is_minSending the train for a minimum interval time; t is_maxThe maximum interval time for train departure; r is a minimum real number, is a decomposition coefficient of a train departure interval, and can be adjusted according to specific road conditions and calculation precision; a is_maxIs the maximum acceleration, v_bmaxAt maximum operating speed, v_maxIs the maximum post-deceleration speed.

2. The urban rail transit optimization manipulation and driving scheduling comprehensive energy-saving control method according to claim 1, wherein the obtaining of the driving scheduling control schedule according to the driving scheduling control model corresponding to the lowest total energy consumption specifically comprises:

establishing a regenerative braking energy model in cooperation with at least one regenerative braking stage of the plurality of sections according to the train operation number;

acquiring the utilization rate of regenerative braking energy according to the regenerative braking energy model;

and establishing a running scheduling control timetable meeting constraint conditions by combining the train running parameters and a running scheduling control model corresponding to the lowest total energy consumption according to the utilization rate of the regenerative braking energy.

3. The urban rail transit optimized operation and driving dispatching comprehensive energy-saving control method according to claim 2, wherein the regenerative braking energy model is as follows:

$J_z=\frac{1}{2}M(v_b^2-v_w^2)-\underset{y=1}{\overset{n}{\mathrm{\Σ}}}Mr\left(v_y\right)v_y{\mathrm{\Δt}}_{y+1}+\frac{1}{2}M(v_b^2-v_k^2)-\underset{u=1}{\overset{n}{\mathrm{\Σ}}}Mr\left(v_u\right)v_u{\mathrm{\Δt}}_{u+1}$

in the formula, v_yFor limiting speed of curve, v_kFor air brake speed, r (v) ═ a + bv + cv²And a, b and c are train running resistance coefficients delta t_y+1＝t_y+1-t_y，y＝0,1,2,…,Δt_u+1＝t_u+1-t_u，u＝0,1,2,…。

4. The method for the comprehensive energy-saving control of urban rail transit optimization maneuvering and traffic scheduling as claimed in claim 2, characterized in that the constraint conditions comprise: distance constraint conditions, quasi-point time constraint conditions and distance time constraint conditions;

the distance constraint conditions are as follows: s (t, a, v) ═ S

The quasi-point time constraint conditions are as follows: t (T, a, v) is less than or equal to T

The distance time constraint conditions are as follows:

wherein S and T are train punctuation time and inter-station distance, respectively, S (T, a, v) is the running distance of the train when running according to a certain train control sequence, T (T, a, v) is the running time of the train when running according to a certain train control sequence, T_min，T_maxRespectively representing the lower limit and the upper limit of the departure interval of the train; t is t_min，t_maxRespectively representing the lower limit and the upper limit of the station stop time, min J_{General assembly}And t, a and v are train operation parameters for the lowest total energy consumption.

5. The utility model provides an urban rail traffic optimizes manipulation and traffic scheduling and synthesizes energy-conserving control device which characterized in that includes:

the data acquisition module is used for acquiring train scheduling information, train operation parameters and train road condition information according to a train operation line, wherein the train scheduling information comprises: train operation quantity, train departure interval, punctual time and distance between stations, train operation parameter includes: the maximum allowable speed, the maximum allowable acceleration and the train weight, wherein the train road condition information comprises: gradient, distance between the ramp and the starting point, length of the ramp, length of the bend and distance between the bend and the starting point;

the parameter acquisition module is used for dividing the train running line into a plurality of sections, wherein the speeds of the junction points between every two adjacent sections are the same, and at least one acceleration stage and at least one regenerative braking stage are acquired according to the train road condition information of each section so as to correspondingly acquire at least one acceleration point and at least one regenerative braking point of each section;

the model establishing module is used for establishing N driving scheduling control sequences according to at least one accelerating point, at least one regenerative braking point, train departure intervals and train running number in the plurality of sections and establishing N driving scheduling control models according to the N driving scheduling control sequences;

the energy consumption calculation module is used for calculating the total energy consumption of each traffic scheduling control model so as to obtain the traffic scheduling control model corresponding to the lowest total energy consumption;

the schedule output module is used for acquiring a traffic scheduling control schedule according to a traffic scheduling control model corresponding to the lowest total energy consumption, and the traffic scheduling control model M is as follows:

$M=\left(\[a_{q1},a_{q2},\mathrm{...},a_{qn}\]\·\left[\begin{array}{c}{v}_{b1}\\ v_{b2}\\ \begin{array}{c}.\\ .\\ .\end{array}\\ v_{bk}\end{array}\right]\·\[v_{w1},v_{w2},\mathrm{...},v_{wm}\]+\[a_{Q1},a_{Q2},\mathrm{...},a_{Qn}\]\·\left[\begin{array}{c}{v}_{B1}\\ v_{B2}\\ \begin{array}{c}.\\ .\\ .\end{array}\\ v_{Bk}\end{array}\right]\·\[v_{d1},v_{d2},\mathrm{...},v_{dy}\]\right)\·\left[\begin{array}{c}{T}_{\min }\\ T_{\min }+r\\ T_{\min }+2r\\ \begin{array}{c}.\\ .\\ .\end{array}\\ T_{\min }+\left(x-1\right)r\\ T_{\max }\end{array}\right]$

wherein, a_qnIs an acceleration, and a_qn≤a_max；v_bkFor the optimum uniform speed after acceleration, and v_bk≤v_bmax；v_wnIs the speed after a curve, and v_wm≤v_max；a_QnIs a second acceleration, and a_Qn≤a_max；v_BkIs the optimum uniform velocity after the second acceleration, and v_Bk≤v_bmax；v_dyIs the speed after regenerative braking, and v_dy≤v_max(ii) a n is the total number of the acceleration or the speed in the allowable range; t is_minSending the train for a minimum interval time; t is_maxThe maximum interval time for train departure; r is a minimum real number, is a decomposition coefficient of a train departure interval, and can be adjusted according to specific road conditions and calculation precision; a is_maxIs the maximum acceleration, v_bmaxAt maximum operating speed, v_maxIs the maximum post-deceleration speed.

6. The urban rail transit optimizing control and driving scheduling integrated energy-saving control device according to claim 5, wherein the obtaining of the driving scheduling control schedule according to the driving scheduling control model corresponding to the lowest total energy consumption in the schedule output module specifically comprises:

establishing a regenerative braking energy model in cooperation with at least one regenerative braking stage of the plurality of sections according to the train operation number;

acquiring the utilization rate of regenerative braking energy according to the regenerative braking energy model;

and establishing a running scheduling control timetable meeting constraint conditions by combining the train running parameters and a running scheduling control model corresponding to the lowest total energy consumption according to the utilization rate of the regenerative braking energy.

7. The urban rail transit optimized manipulation and driving scheduling comprehensive energy-saving control device according to claim 6,

the regenerative braking energy J_zComprises the following steps:

$J_z=\frac{1}{2}M(v_b^2-v_w^2)-\underset{y=1}{\overset{n}{\mathrm{\Σ}}}Mr\left(v_y\right)v_y{\mathrm{\Δt}}_{y+1}+\frac{1}{2}M(v_b^2-v_k^2)-\underset{u=1}{\overset{n}{\mathrm{\Σ}}}Mr\left(v_u\right)v_u{\mathrm{\Δt}}_{u+1}$

in the formula, v_yFor limiting speed of curve, v_kFor air brake speed, r (v) ═ a + bv + cv²And a, b and c are train running resistance coefficients delta t_y+1＝t_y+1-t_y，y＝0,1,2,…,Δt_u+1＝t_u+1-t_u，u＝0,1,2,…。

8. The urban rail transit optimized control and driving scheduling integrated energy-saving control device according to claim 6, wherein the constraint condition comprises: distance constraint conditions, quasi-point time constraint conditions and distance time constraint conditions;

the distance constraint conditions are as follows: s (t, a, v) ═ S

The quasi-point time constraint conditions are as follows: t (T, a, v) is less than or equal to T

The distance time constraint conditions are as follows:

wherein S and T are train punctuation time and inter-station distance, respectively, S (T, a, v) is the running distance of the train when running according to a certain train control sequence, T (T, a, v) is the running time of the train when running according to a certain train control sequence, T_min，T_maxRespectively representing the lower limit and the upper limit of the departure interval of the train; t is t_min，t_maxRespectively representing the lower limit and the upper limit of the station stop time, min J_{General assembly}And t, a and v are train operation parameters for the lowest total energy consumption.