CN-117465513-B - Urban rail train schedule and bidirectional converter operation characteristic optimization method

CN117465513BCN 117465513 BCN117465513 BCN 117465513BCN-117465513-B

Abstract

The invention discloses a city rail train schedule and a bidirectional converter operation characteristic optimization method, which comprises the following steps of obtaining train data and line data, generating all-day feasible departure strategies with fixed departure quantity and corresponding schedule sets, calculating a train speed curve, calculating train power and operation positions of each moment when a train operates in all intervals of the whole line, obtaining minimum cost under different schedules and corresponding bidirectional converter operation parameter comprehensive schemes through a particle swarm algorithm, and outputting the schedule with the minimum cost and a bidirectional converter no-load voltage, limiting voltage and sagging slope scheme. The invention comprehensively considers the transmission, utilization and feedback of the train schedule and the operation parameter characteristics of the bidirectional converter to the regenerative braking energy of the direct current reversible traction power supply system, and simultaneously meets the requirements of reducing the economic cost and the voltage fluctuation rate of the traction network, thereby improving the train operation benefit and the operation safety.

Inventors

SUN PENGFEI
HUANG ZILU
FENG XIAOYUN
WANG QINGYUAN
YANG SHUNFENG

Assignees

西南交通大学

Dates

Publication Date: 20260508
Application Date: 20231103

Claims (7)

1. A city rail train schedule and bidirectional converter operation characteristic optimization method is characterized by comprising the following steps: s1, acquiring train data and line data; s2, searching adjacent train number departure intervals through a violence search algorithm to generate all feasible departure strategies with fixed departure quantity and corresponding schedule sets; S3, calculating the speed of the train at each moment when the train runs in all intervals of the whole line under the set interval running time according to the maximum principle, and obtaining a speed curve; s4, calculating the power and the running position of the train at each moment when the train runs in all intervals of the whole train according to the speed curve; S5, obtaining minimum cost under different schedules and a corresponding comprehensive scheme of the operation parameters of the bidirectional converter through a particle swarm algorithm based on the power and the operation position of the train at each moment in operation; S6, the schedule with the minimum output cost and the scheme of no-load voltage, limit voltage and sagging slope of the bidirectional converter finish the optimization of urban rail train schedule and bidirectional converter operation characteristics; the specific method of step S5 comprises the following sub-steps: s5-1, inputting a power curve when the train runs in all the intervals of the whole train, and setting the basic unit price of the bidirectional converter Cost per unit volume c, annual number of full life cycle L, unit price of electricity rate a, annual discount rate r, annual payment period p, and three-dimensional particle And linear weighting of cost functions And ; S5-2, calculating timetable Power-position-time data of all running trains within the lower total time window T; S5-3, initializing particle swarm velocity And position Wherein 、 And Respectively represent no-load voltage Limiting voltage And sagging slope ; 、 And Respectively represent no-load voltage Limiting voltage And sagging slope Is a search speed of (a); S5-4, obtaining a voltage matrix of all traction substations at time t in a total time window through tide calculation And current matrix ; S5-5 based on voltage matrix And current matrix Calculating total output energy consumption of reversible substation in single day total time window Average voltage fluctuation ratio of all-line substation By no-load voltage Limiting voltage And sagging slope Calculating the rated power of a bi-directional converter inverter ; S5-6, according to the rated power of the bidirectional converter inverter Calculating installation cost of bidirectional converter in full life cycle And the cost of electricity charge And according to the installation cost of the bidirectional converter in the whole life cycle Cost of electricity charge And average voltage fluctuation ratio of all-line substation Calculating a cost function C; s5-7, judging whether iteration is finished, if so, obtaining minimum cost under different schedules and a corresponding comprehensive scheme of the bidirectional converter operation parameters, otherwise, calculating a fitness value according to a cost function C, updating the global optimal position of the particle swarm, the local optimal position of the particle swarm, the particle speed and the particle position according to the fitness value, and returning to the step S5-5; the specific method of the step S5-6 is as follows: according to the formula: obtaining the installation cost of the bidirectional converter in the whole life cycle Cost of electricity charge Cost function C and power rating of a bi-directional converter inverter Wherein N is the number of traction substations included in the line data; c is the unit capacity cost; the method is characterized in that the method is electricity fee unit price, r is annual electricity fee discount rate, p is annual electricity fee payment period number, and L is full life cycle time.
2. The method for optimizing urban rail train schedule and bidirectional converter operation characteristics according to claim 1, wherein in the step S1, train data comprises train quality M, and the line data comprises a number N of traction substations, a number Q of sections, running time R of an up-down train in each section of a whole line, stop time D of each station, a daily total time window T, a daily single train departure number S, a departure interval K of an up-down first class train and a maximum value of departure intervals of two adjacent trains Minimum value Discrete step size No-load voltage range of traction substation Limiting voltage range And sagging slope range 。
3. The urban rail train schedule and bidirectional converter operating characteristic optimization method according to claim 2, wherein the specific method of step S2 is as follows: Searching an all-day departure strategy and a corresponding schedule set which meet the following constraint conditions through a violence search algorithm: Wherein the method comprises the steps of Stop time of the ascending train at the nth station; The running time of the ascending train in the q-th interval; the departure interval between the s-th and the (s+1) -th train numbers of the upper train is set; stop time of the nth station for the downlink train; the running time of the descending train in the q-th interval; The departure interval between the s-th and the s+1th train is the next train.
4. The urban rail train schedule and bidirectional converter operating characteristic optimization method according to claim 1, wherein the specific method of step S4 is as follows: according to the formula: acquiring train power at the d time of the mth operation interval And an operating position Wherein The mth operation interval is the running speed at the time d; the net force conversion efficiency is achieved; train traction force at the d moment of the mth operation interval; a train braking force at the d time of the mth operation interval; Is the mass of the train; The mth operation interval is The running speed at the moment; The mth operation interval is The running speed at the moment.
5. The urban rail train schedule and bi-directional converter operating characteristic optimizing method according to claim 1, wherein the specific method of step S5-4 comprises the sub-steps of: S5-4-1, inputting train power time data, setting the initial time to 0, the initial iteration number to 0 and a voltage matrix And current matrix Setting the maximum iteration number Iterative accuracy ; S5-4-2, and constructing node admittance matrix at t moment ; S5-4-3, according to the formula: calculating a voltage matrix at t time in the next iteration process Wherein A current matrix at the time t in the current iteration process is represented; s5-4-4, judging whether the difference value of the voltage matrixes corresponding to two adjacent iterations at the same time t is smaller than the iteration precision Or whether the current iteration number w is greater than the maximum iteration number If yes, outputting the voltage matrix at the current moment And current matrix And entering step S5-4-5, otherwise adding 1 to the iteration times and returning to step S5-4-3; s5-4-5, switching working conditions of the reversible substation, updating the current moment and resetting the current iteration times to 0; S5-4-6, judging whether the current time is smaller than a single day total time window, if yes, returning to the step S5-4-2, and if not, ending.
6. The urban rail train schedule and bidirectional converter operating characteristic optimization method according to claim 1, wherein the specific method of step S5-5 is as follows: according to the formula: obtaining total output energy consumption of reversible substation in single day total time window Average voltage fluctuation ratio of all-line substation Wherein T is a single day total time window, N is the number of traction substations included in the line data; representing a voltage matrix of an nth traction substation at a time t; the current matrix of the nth traction substation at the time t is represented; , The average value of the voltage values of the inner network side of the nth traction substation in a single day total time window is obtained; and the standard deviation of the voltage value of the inner network side of the nth transformer substation in a single day total time window is obtained.
7. The method for optimizing urban rail train schedule and bidirectional converter operating characteristics according to claim 1, wherein the specific method for determining whether to end the iteration in step S5-7 is to determine whether the maximum number of iterations is reached.

Description

Urban rail train schedule and bidirectional converter operation characteristic optimization method Technical Field The invention relates to the field of comprehensive optimization of train operation and power supply parameters, in particular to an urban rail train schedule and bidirectional converter operation characteristic optimization method. Background Most of the existing researches are based on the optimization research of the operation characteristics of the bidirectional converter device under the fixed mode of the train departure strategy, the influence of the train group operation strategy on the energy transmission, utilization and feedback processes of the reversible traction power supply system is ignored, and the optimization result has a space for further optimization. In the prior art (Chen. Bidirectional converter-based urban rail traction substation voltage optimization control strategy [ D ]. Beijing: beijing traffic university, 2022), an offline optimization method for the urban rail traction substation operation characteristics based on the bidirectional converter on the premise of fixed train operation departure interval time is researched, and optimization targets for minimizing energy consumption cost and extremely poor voltage fluctuation are realized by changing parameters such as no-load voltage, sagging slope and the like of the bidirectional converter. However, this technique has the following disadvantages: 1) The value of train operation cost under the full life cycle of the bidirectional converter is not considered. 2) The optimization problem of the cooperative optimization of the train schedule and the bidirectional converter operation characteristics under the constraint of fixed train number of single-day time window departure is not comprehensively considered. 3) The problem of coordination and optimization between the energy consumption cost, the installation cost of the bidirectional converter and the fluctuation degree of the voltage value is not comprehensively considered. Disclosure of Invention Aiming at the defects in the prior art, the optimization method for the urban rail train schedule and the bidirectional converter operation characteristics solves the problem that the economic cost and the traction network voltage stability are not considered in the prior art. In order to achieve the aim of the invention, the invention adopts the following technical scheme: The utility model provides a city rail train schedule and bi-directional converter operating characteristic optimizing method, which comprises the following steps: s1, acquiring train data and line data; s2, searching adjacent train number departure intervals through a violence search algorithm to generate all feasible departure strategies with fixed departure quantity and corresponding schedule sets; S3, calculating the speed of the train at each moment when the train runs in all intervals of the whole line under the set interval running time according to the maximum principle, and obtaining a speed curve; s4, calculating the power and the running position of the train at each moment when the train runs in all intervals of the whole train according to the speed curve; S5, obtaining minimum cost under different schedules and a corresponding comprehensive scheme of the operation parameters of the bidirectional converter through a particle swarm algorithm based on the power and the operation position of the train at each moment in operation; And S6, the schedule with the minimum output cost and the scheme of no-load voltage, limit voltage and sagging slope of the bidirectional converter finish the optimization of the urban rail train schedule and the operation characteristics of the bidirectional converter. Further, in the step S1, the train data comprise train quality M, the line data comprise the number N of traction substations, the number Q of sections, the running time R of the up-down trains in each section of the whole line, the stop time D of each station, the single-day total time window T, the single-day single-row departure times S, the departure interval K of the up-down first class, the maximum value H max, the minimum value H min, the discrete step delta H and the no-load voltage range of the traction substations of the adjacent two trainsLimiting voltage rangeAnd a droop slope range [ k min,kmax ]. Further, the specific method of step S2 is as follows: Searching an all-day departure strategy and a corresponding schedule set which meet the following constraint conditions through a violence search algorithm: Wherein the method comprises the steps of Stop time of the ascending train at the nth station; The running time of the ascending train in the q-th interval; the departure interval between the s-th and the (s+1) -th train numbers of the upper train is set; stop time of the nth station for the downlink train; the running time of the descending train in the q-th interval; The departure int