A method and related device for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity

Abstract

The present invention provides a method and related devices for optimizing an energy-saving operation diagram of fast and slow trains based on passenger capacity, and relates to the technical field of rail transit. The method calculates the positions of fast trains and slow trains at any time according to the running ratio of fast trains and slow trains and the train departure timetable; determines the number of passengers of the train at each station, and calculates the weight of the fast train and slow train at each station according to the number of passengers; calculates the traction energy consumption and regeneration energy required for the running line during the entire operating time; takes minimizing the total energy consumption of all service trains during the entire operating time as the goal, and establishes an energy-saving operation diagram optimization model of fast and slow trains based on passenger capacity according to the required traction energy consumption and regeneration energy; solves the energy-saving operation diagram optimization model of fast and slow trains to obtain an energy-saving operation time table of fast and slow trains. The present invention optimizes the train operation diagram by adjusting the train departure interval, station stay time, and total turnover time, thereby reducing energy consumption and improving the utilization rate of renewable energy.

Description

Technical Field

[0001] The present invention relates to the field of rail transit technology, and in particular to a method for optimizing an energy-saving operation diagram of fast and slow trains based on passenger capacity and a related device. Background Art

[0002] As the scale of subway networks in various cities in my country grows, the resource carrying capacity of cities is facing increasing pressure due to the huge power consumption of subway systems. Research on subway energy conservation is of great significance for reducing operating costs and ensuring sustainable development. Traction energy is the main component of subway energy consumption, accounting for about 40%-48% of total energy consumption. In recent years, with the good application of regenerative braking technology in subway systems, the effective use of regenerative braking energy to reduce subway operation energy consumption has become a new direction for environmental protection and energy conservation in subway systems. In actual operation, whether it is the use of energy storage devices or the use of grid coordinated control to convert and store electrical energy, the effect is not ideal. Summary of the invention

[0003] The purpose of the present invention is to provide a method and a related device for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0004] In a first aspect, the present application provides a method for optimizing an energy-saving operation diagram of fast and slow vehicles based on passenger capacity, comprising:

[0005] Obtain the operation ratio of express trains and slow trains and the train departure timetable, and calculate the positions of express trains and slow trains at any time based on the operation ratio of express trains and slow trains and the train departure timetable;

[0006] Use facial recognition technology to determine the number of passengers on the train at each station, and calculate the weight of express and slow trains at each station based on the number of passengers;

[0007] Based on the weight and position of express trains and slow trains at each station, the traction energy consumption calculation models of express trains and slow trains are constructed to calculate the traction energy consumption required for the running line during the entire operating time.

[0008] Based on the actual running speed curves and positions of express trains and slow trains, the regenerative energy generation models of express trains and slow trains are constructed respectively to calculate the regenerative energy of the running line during the entire operating time.

[0009] With the goal of minimizing the total energy consumption of all service trains during the entire operating time, an optimization model for the energy-saving operation diagram of fast and slow trains based on passenger capacity is established according to the required traction energy consumption and regenerative energy.

[0010] Solve the fast and slow train energy-saving operation diagram optimization model to obtain the fast and slow train energy-saving operation timetable.

[0011] In a second aspect, the present application also provides a device for optimizing a fast and slow vehicle energy-saving operation diagram based on passenger capacity, comprising:

[0012] Acquisition module: obtain the operation ratio of express trains and slow trains and the train departure schedule, and calculate the positions of express trains and slow trains at any time according to the operation ratio of express trains and slow trains and the train departure schedule;

[0013] Weight calculation module: Use facial recognition technology to determine the number of passengers on the train at each station, and calculate the weight of express and slow trains at each station based on the number of passengers;

[0014] Energy consumption calculation module: Based on the weight and position of express trains and slow trains at each station, the traction energy consumption calculation models of express trains and slow trains are constructed to calculate the traction energy consumption required for the running line during the entire operating time;

[0015] Energy calculation module: Based on the actual running speed curves and positions of express trains and slow trains, the regenerative energy generation models of express trains and slow trains are constructed respectively to calculate the regenerative energy of the running line during the entire operating time;

[0016] Model building module: with the goal of minimizing the total energy consumption of all service trains during the entire operating time, an energy-saving operation diagram optimization model for fast and slow trains based on passenger capacity is established according to the required traction energy consumption and regenerative energy;

[0017] Solving module: Solving the fast and slow train energy-saving operation diagram optimization model to obtain the fast and slow train energy-saving operation timetable.

[0018] In a third aspect, the present application also provides a device for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity, including:

[0019] Memory for storing computer programs;

[0020] A processor is used to implement the steps of the method for optimizing the fast and slow train energy-saving operation diagram based on passenger capacity when executing the computer program.

[0021] In a fourth aspect, the present application further provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity are implemented.

[0022] The beneficial effects of the present invention are:

[0023] The present invention constructs an energy-saving operation diagram optimization model for fast and slow trains based on passenger capacity with the goal of minimizing the total net energy consumption of all trains on the entire line. On the basis of not changing the train running time in the section, the train operation diagram is optimized by adjusting the train departure interval, station stay time, and total turnover time, thereby reducing energy consumption and improving the utilization rate of renewable energy. The present invention is feasible and universal.

[0024] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 A train route diagram in an embodiment of the present invention;

[0027] Figure 2 It is a schematic flow chart of a method for optimizing a fast and slow train energy-saving operation diagram based on passenger capacity described in an embodiment of the present invention;

[0028] Figure 3 It is a schematic structural diagram of a fast and slow train energy-saving operation diagram optimization device based on passenger capacity described in an embodiment of the present invention;

[0029] Figure 4 It is a schematic diagram of the structure of the equipment for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity described in an embodiment of the present invention.

[0030] Markings in the figure:

[0031] 800. Equipment for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity; 801. Processor; 802. Memory; 803. Multimedia component; 804. I / O interface; 805. Communication component. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0033] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0034] Embodiment 1:

[0035] Urban rail transit line G=(N,N s ,E,E s )like Figure 1 As shown, N is the station set, N s is the express stop collection, E is the station collection, and E s The express train gathers between stations. After passing the first station, the vehicle travels in the downward direction to station N, then turns back and departs from station N+1 and travels in the upward direction to station 2N, then returns to the depot for recycling or restarts the next cycle. When the express train runs between stations (n, n′), it departs from station n, does not stop at station n+1, and stops at station n′.

[0036] In the same power supply section, by coordinating the traction and braking moments of different trains, the regenerative braking energy generated by the braking train can be used more for train traction energy supply. The regenerative energy generated by the train braking at stations n-1 and 2N-n+1 is fed back to the substation through the overhead line, thereby providing energy for the train traction acceleration at station n+k-1 and the train cruising operation between stations 2N-n-k+1 and 2N-n-k+2. By adjusting the time when the train arrives at stations n-1 and 2N-n+1 and the time when the train leaves stations n+k-1 and 2N-n-k+1, the overlapping time of train regenerative braking and train traction and cruising is increased, thereby improving the utilization of regenerative energy.

[0037] Based on this, this embodiment provides a method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity.

[0038] See also Figure 1 , the figure shows that the method comprises:

[0039] S1. Obtain the operation ratio of express trains and slow trains and the train departure schedule, and calculate the positions of express trains and slow trains at any time according to the operation ratio of express trains and slow trains and the train departure schedule;

[0040] Specifically, the step S1 includes:

[0041] S11. Obtain the departure interval of the slow train, the running time of the slow train between stations, and the stay time of the slow train at the station from the departure timetable;

[0042] S12. The time when the slow train leaves each station is calculated based on the ratio of express trains to slow trains 1:K, the departure interval, the running time of the slow train between stations, and the dwelling time of the slow train at the station; wherein, the ratio of express trains to slow trains 1:K means that one express train is run for every K slow trains;

[0043] 1) Calculate the departure time of the slow train in the downlink phase, that is, for all 1≤i≤I,i≠(1+K),2(1+K),…,I, the calculation formula for the time when the slow train i leaves station 1 is:

[0044]

[0045] Where i represents the vehicle index, i = 1, 2, ..., I, when i ≠ (1 + K), 2 (1 + K), ..., I, the i-th vehicle is a slow vehicle, and I represents the number of vehicles running throughout the day. represents the departure time of slow train i at station 1, h f,f+1 It indicates the interval between the f and f+1 slow trains. represents the stay time of slow train i at station 1.

[0046] For all 2≤n≤N-1, the formula for calculating the time when slow train i leaves station n is:

[0047]

[0048] In the formula, represents the departure time of slow train i at station n, represents the dwelling time of slow train i at station f, Indicates the running time of the slow train between stations f and f′.

[0049] 2) Calculate the departure time of the slow train in the return phase, that is, for all 1≤i≤I,i≠(1+K),2(1+K),…,I, the calculation formula for the time when the slow train i leaves the station N+1 is:

[0050]

[0051] Where: z i Indicates the time required for the entire return process of the slow train;

[0052] For all N+1≤n≤2N-1, the time when slow train i leaves station n is calculated as:

[0053]

[0054] S13. Obtain the running curve of the slow train between stations, and calculate the speed of the slow train between stations according to the time when the slow train leaves each station and the running curve:

[0055] For all 1≤i≤I,i≠(1+K),2(1+K),…,I,1≤n≤N-1 and N+1≤n≤2N-1, the speed calculation formula of slow train i at the station (n,n′) at time t is:

[0056]

[0057] Where: represents the speed of slow train i at the station (n,n′) at time t, represents the time when slow train i leaves station n, Represents the speed curve of the slow train between stations (n,n′).

[0058] S14. Obtain the distance between stations, and calculate the position of the slow train between stations at any time according to the distance between stations and the speed of the slow train between stations;

[0059] For all 1≤i≤I,i≠(1+K),2(1+K),…,I, the position calculation formula of slow car i at time t is:

[0060]

[0061] Where: represents the position of slow train i at the station (n,n′) at time t, S f,f+1 represents the distance between stations (f,f+1), S n,n+1 Represents the distance between stations (n,n+1).

[0062] Since the calculation principle of the express train position is the same as that of the slow train, the position of the express train between stations at any time can be obtained according to steps S11-S14:

[0063]

[0064] Where: Express train i′ is at the station (N s ,N s ′), Express train i′ is at the station (N s ,N s ′) speed, Express train i′ leaves station N s The time at which the express train stops is s, where s represents the index of the express train stop station, s=1,2,…,S,S+1,…,2S.

[0065] Based on the above embodiments, the method further includes:

[0066] S2. Use facial recognition technology to determine the number of passengers on the train at each station, and calculate the weight of express and slow trains at each station based on the number of passengers;

[0067] Specifically, step S2 includes:

[0068] S21. Use facial recognition technology to count the number of passengers getting on and off each train at each station. Specifically, the number of passengers getting on and off each train at each station can be obtained by comprehensive statistics of vehicle weighing and platform cameras;

[0069] S22. Calculate the number of passengers on slow trains at each station based on the number of passengers getting on and off the train:

[0070] For all 1≤i≤I,i≠(1+K),2(1+K),…,I, the formula for calculating the number of passengers on slow train i between stations (n,n′) is:

[0071]

[0072] Where: represents the number of passengers of slow train i between stations (n, n′), n′ is the station where the slow train stops next, represents the number of people boarding slow train i at station n, Represents the number of passengers getting off slow train i at station n.

[0073] S23. Obtain the weight of the slow train, and calculate the weight of the slow train at each station based on the weight of the slow train and the number of passengers:

[0074]

[0075] Where: represents the mass of slow train i between stations (n,n'), m0 represents the average weight of each passenger, and M represents the mass of the train.

[0076] According to steps S21-S23, the weight of the express train at each station can be calculated:

[0077]

[0078] Where: represents the quality of express train i' between stations (n,n').

[0079] Based on the above embodiments, the method further includes:

[0080] S3. Based on the weight and position of express trains and slow trains at each station, traction energy consumption calculation models of express trains and slow trains are constructed to calculate the traction energy consumption required for the running line during the entire operating time;

[0081] Specifically, step S3 includes:

[0082] S31. Obtain the traction time and cruising time of the slow train between stations;

[0083] According to the actual operating curve, the vehicle's operation process between stations can generally be divided into four operating conditions: traction, cruising, coasting and braking.

[0084] S32. According to the time when the slow train leaves each station and the traction time and cruising time of the slow train between stations, the traction period and cruising period of the slow train are calculated. Specifically, for all 1≤i≤I,i≠(1+K),2(1+K),…,I,1≤n≤N-1 and N+1≤n≤2N-1,

[0085]

[0086] Where: represents the transition time from traction to cruising of slow train i between stations (n,n′), The transition time from cruising to coasting of slow train i between stations (n,n′) is: The transition time from coasting to braking of slow train i at station (n,n′) is: represents the time when the slow train arrives at station n′, represents the traction time of the slow train between stations (n,n′), represents the cruising time of the slow train between stations (n,n′), represents the idling time of the slow train between stations (n,n′), The braking time of the slow train between stations (n,n′);

[0087] Therefore, in The slow train is in the traction period, and the traction force works to accelerate the train;

[0088] exist When a slow train is in the cruising stage, the traction force is used to keep the train moving at a constant speed, which requires energy. The rest of the time, the traction energy consumption is zero.

[0089] S33. According to the mass of the slow train, the speed of the slow train between stations and the position between stations, a slow train traction energy consumption calculation model is constructed to calculate the energy required for the slow train during the traction period and the cruising period;

[0090] The traction energy consumption calculation model of the slow train is:

[0091]

[0092] Where: represents the average resistance of the slow train running between stations (n,n′), β1 represents the traction efficiency from electrical energy to kinetic energy, Δt represents the time unit, represents the energy required by slow car i.

[0093] Similarly, the traction energy consumption calculation model of the express train is:

[0094]

[0095] In the formula, Indicates that express train i′ is between stations (N s ,N s ') The transition time from towing to cruising, Indicates that express train i′ is between stations (N s ,N s ') The transition time from cruising to coasting, represents the energy required by express train i′, Indicates that the express train is between stations (N s ,N s ′) Average resistance of operation.

[0096] Therefore, the traction energy consumption of the train between all stations is q for:

[0097]

[0098] From this, we can get the traction energy consumption E required for the running line during the entire operating time. q for:

[0099]

[0100] In the formula, r represents the rth time unit, R represents the time unit of full-day operation, T stands for full-day operation time.

[0101] Based on the above embodiments, the method further includes:

[0102] S4. Based on the actual running speed curves and positions of the express train and the slow train, the regenerative energy generation models of the express train and the slow train are respectively constructed to calculate the regenerative energy of the running line during the entire operating time;

[0103] Specifically, step S4 includes:

[0104] S41. Get the braking time of the slow train between stations;

[0105] S42. According to the time when the slow train leaves each station and the braking time of the slow train between stations, the braking period of the slow train is calculated. The braking period calculated by step S32 is

[0106] S43. According to the preset loss coefficient, the mass of the slow train, the speed of the slow train between stations and the position between stations, a regenerative energy generation model of the slow train is constructed to calculate the energy generated by the slow train during the braking period.

[0107]

[0108] Where: α represents the loss coefficient of renewable energy transmission, and β2 represents the conversion efficiency of kinetic energy to electrical energy.

[0109] Similarly, during the braking period of the express train The energy generated is:

[0110]

[0111] In the formula, It represents the energy generated by the express train during the braking period. Indicates that express train i′ is between stations (N s ,N s ′) The transition moment from coasting to braking, Express train i′ arrives at station N s ’ moment.

[0112] S44. Obtaining the train in the same time period as the slow train and in the traction period and the energy required by the train in the traction period;

[0113] S45. Compare the energy required by the train during the traction period with the energy generated by the slow train during the braking period, and use the smaller energy as the available regenerative energy;

[0114] The calculation formula for the direct utilization of regenerative energy within a time unit is:

[0115]

[0116] Where: er represents the regenerative energy in a time unit, γ(i′,t,p) represents that the express train I′ is located in the power supply section p at time t, and γ(i,t,p) represents that the slow train i is located in the power supply section p at time t, which is expressed as follows:

[0117]

[0118] Where: Indicates the starting position of the power supply interval P, Indicates the end position of the power supply section P, p represents the power supply section index, p = 1, 2, ..., P, and P represents the total number of line power supply sections.

[0119] Therefore, the regenerative energy of the running line during the entire operation time can be expressed as follows:

[0120]

[0121] Based on the above embodiments, the method further includes:

[0122] S5. With the goal of minimizing the total energy consumption of all service trains during the entire operating time, an optimization model for the energy-saving operation diagram of fast and slow trains based on passenger capacity is established according to the required traction energy consumption and regenerative energy;

[0123] Specifically, step S5 includes:

[0124] S51. Constructing operation time constraints, train stop time constraints, train departure interval and total return time constraints, and train minimum tracking interval constraints based on departure interval and station stay time;

[0125] (1) Operation time constraints

[0126] In order to ensure the operational efficiency of the actual operation process and the practical significance of the model, it is necessary to ensure that the operation time of the entire operation cycle is equal to the actual operation time, which is specifically expressed as follows:

[0127]

[0128] Where: T represents the full-day operating time, I represents the number of vehicles running throughout the day, represents the running time of the express train between stations n and n', represents the running time of the slow train between stations n and n', represents the stay time of the express train at station n, represents the dwelling time of the slow train at station n, z I represents the total return time, and I|(K+1) means that I is divisible by K+1.

[0129] (2) Train stop time constraints

[0130] The stop time of a train at a station where it needs to stop is determined by the passenger flow. It is necessary to ensure operational efficiency and sufficient time for passengers to get on and off the train. Therefore, the stop time of a slow train at a station and the stop time of an express train when it does not pass must not be less than the minimum stop time and greater than the maximum stop time, as shown below:

[0131]

[0132] Where: represents the minimum stopping time of the vehicle at station n, The maximum dwelling time of a vehicle at station n, represents the stay time of the express train at station n, represents the dwelling time of the slow train at station n.

[0133] (3) Constraints on train departure interval and total return time

[0134] In order to ensure the safety of train operation and the quality of operation services, the departure interval between two adjacent trains shall not be less than the minimum train departure time and greater than the maximum train departure time, and the total turnaround time of train i shall not be less than the minimum total turnaround time of train i and greater than the maximum total turnaround time of train i, as shown below:

[0135]

[0136] Where: Indicates the minimum departure interval of trains. Indicates the maximum departure interval of trains, h i,i+1 represents the departure interval between vehicles i and i+1, Z min Indicates the minimum total return time of the train, Z max Indicates the maximum total return time of the train.

[0137] (4) Minimum train tracking interval constraints

[0138] During train operation, in order to ensure driving safety, two adjacent trains need to maintain a certain safety distance, that is, they need to meet the minimum tracking interval constraint, which is expressed as follows:

[0139]

[0140] Where: T z Indicates the minimum tracking interval of the train. represents the time when the slow train i arrives at the station n′, represents the time when express train i' arrives at station n', represents the time when slow train i leaves station n, represents the time when express train i' leaves station n, represents the time when express train i′ arrives at station n.

[0141] S52. According to the energy and regenerative energy required by the running line during the entire operating time, the total energy consumption of all trains during the entire operating time is calculated:

[0142]

[0143] Where: E represents the total energy consumption, h i,i+1 represents the departure interval between vehicles i and ik+1, represents the dwelling time of the slow train at station n, Indicates that the slow train is at station N S The length of stay; represents the total return time of vehicle i.

[0144] S53. Under the conditions of satisfying the operating time constraints, train stop time constraints, train departure interval and total return time constraints, and train minimum tracking interval constraints, the total energy consumption of all trains during the entire operating time is minimized as the objective function, and an energy-saving operation diagram optimization model for fast and slow trains based on passenger capacity is established:

[0145]

[0146]

[0147] Based on the above embodiments, the method further includes:

[0148] S6. Solve the fast and slow train energy-saving operation diagram optimization model to obtain the fast and slow train energy-saving operation schedule;

[0149] Specifically, step S6 includes:

[0150] S61. Constructing an operation time gap, and converting the fast and slow train energy-saving operation diagram optimization model into an overall planning model based on the operation time gap;

[0151] Considering the actual operation of the train, appropriate assumptions are made for the model parameters to simplify the calculation, including: the variables and some parameters required for the model establishment process, such as train traction time, cruising time, inertia time, braking time, train stop time, train turnaround time, train departure interval, passenger mass and train running distance, are all assumed to be integers;

[0152] Under the condition of satisfying the constraints, construct an operation time gap ΔG so that the feasible solution's full-day operation time is smaller than the actual full-day operation time by ΔG:

[0153]

[0154] Where: I|(K+1) means that I is divisible by K+1, and K+1 means that the last car is an express car.

[0155] The overall planning model is:

[0156]

[0157] S62. Solve the overall planning model based on the grey wolf algorithm with improved convergence factor and differential evolution to obtain the optimal departure interval, stop time and total turnaround time of express trains and slow trains.

[0158] Specifically, step S62 includes:

[0159] S621. According to the gray wolf optimization algorithm rules, the position update formula and parameter calculation formula of the wolf population in the original gray wolf algorithm are constructed:

[0160] During the search process, the position update formula of the wolf population in the original gray wolf algorithm is expressed as follows:

[0161] D=|C·X p (t)-X(t)|; (28)

[0162] X(t+1)=X p (t)-A·D; (29)

[0163] Where: X p represents the current position of the prey, X represents the position of the gray wolf, τ represents the current number of iterations, and the calculation formulas of A and C parameters are as follows:

[0164] A=2·a·r1-a; (30)

[0165] C = 2·r2; (31)

[0166]

[0167] Where: r1 and r2 are random numbers between [0,1], T max is the maximum number of iterations, and the coefficient a decreases linearly from 2 to 0 as the number of iterations increases;

[0168] S622, calculate the positions of α wolf, β wolf and δ wolf: according to the positions of α wolf, β wolf and δ wolf, effectively adjust the position of the prey, and construct the calculation formula of the positions of α wolf, β wolf and δ wolf:

[0169] D α =|C1·X α -X|; (33)

[0170] D β =|C2·X β -X|; (34)

[0171] D δ =|C3·X δ -X|; (35)

[0172] X1=X α -A1·D α ; (36)

[0173] X2=X β -A2·D β ; (37)

[0174] X3=X δ -A3·D δ ; (38)

[0175]

[0176] Where: A1, A2, A3 represent the updated parameters of A, C1, C2, C3 represent the updated parameters of C, D α , D β , D δ represents the distance between the current wolf and α wolf, β wolf and δ wolf, X1, X2, X3 represent the random positions where α wolf, β wolf and δ wolf are generated;

[0177] S623. Calculate the improved convergence factor: Based on the nonlinear characteristics of the actual convergence process of the algorithm, a convergence factor calculation formula based on the cosine variation law is constructed:

[0178]

[0179] Where: a s ,a e represents the initial and final values ​​of the convergence factor, and λ is a decreasing exponent between (0,1].

[0180] The convergence factor a decreases slowly in the early stage of iteration, so that A maintains a large value for a longer time, enhancing the breadth search of the algorithm. The convergence factor a decreases quickly in the middle stage of iteration, so that A decreases quickly, accelerating the convergence speed of the algorithm. The convergence factor a slowly approaches 0 in the late stage of iteration, so that A maintains a small value for a longer time, enhancing the depth search of the algorithm. The breadth search, depth search and convergence speed of the algorithm are balanced.

[0181] S624. Calculate the positions of α wolf, β wolf and δ wolf based on the improved gray wolf algorithm: According to the rules of the gray wolf optimization algorithm, the idea of ​​differential evolution is integrated when updating the gray wolf position, and the position differences of α wolf, β wolf and δ wolf are determined respectively. After the dynamic scaling factor, the position update formula based on differential evolution is constructed:

[0182]

[0183]

[0184] Where: max and ω min The maximum and minimum values ​​of the scaling factor are used to adjust the position difference through the dynamic scaling factor, balance the breadth search and depth search of the algorithm, and improve the accuracy of the algorithm.

[0185] S625, solution steps of the grey wolf algorithm based on improved convergence factor and differential evolution:

[0186] S6251: Initialize parameter a s 、a e ,ω max ,ω min Etc., initialize the gray wolf population, and randomly generate the location of the corridor population.

[0187] S6252: Calculate the fitness of the gray wolf population, select the gray wolf with the smallest fitness as the α wolf, and the second and third smallest fitness as the β wolf and δ wolf.

[0188] S6253: Determine the number of iterations Update the values ​​of parameters a, A, and C according to the parameter calculation formula and the convergence factor calculation formula.

[0189] S6254: Determine whether |A|<1, and update the position of the current individual according to the position update formula after dynamic scaling factor and differential evolution.

[0190] S6255: If the algorithm reaches the maximum number of iterations T max , end the algorithm and output the optimal solution to obtain the optimal departure interval, stop time and total turnaround time for express and slow trains; otherwise, return to step S6252.

[0191] Embodiment 2:

[0192] like Figure 3 As shown, this embodiment provides a device for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity, and the device includes:

[0193] Acquisition module: obtain the operation ratio of express trains and slow trains and the train departure schedule, and calculate the positions of express trains and slow trains at any time according to the operation ratio of express trains and slow trains and the train departure schedule;

[0194] Weight calculation module: Use facial recognition technology to determine the number of passengers on the train at each station, and calculate the weight of express and slow trains at each station based on the number of passengers;

[0195] Energy consumption calculation module: Based on the weight and position of express trains and slow trains at each station, the traction energy consumption calculation models of express trains and slow trains are constructed to calculate the traction energy consumption required for the running line during the entire operating time;

[0196] Energy calculation module: Based on the actual running speed curves and positions of express trains and slow trains, the regenerative energy generation models of express trains and slow trains are constructed respectively to calculate the regenerative energy of the running line during the entire operating time;

[0197] Model building module: with the goal of minimizing the total energy consumption of all service trains during the entire operating time, an optimization model for the energy-saving operation diagram of fast and slow trains based on passenger capacity is established according to the required traction energy consumption and regenerative energy;

[0198] Solution module: solve the fast and slow train energy-saving operation diagram optimization model to obtain the fast and slow train energy-saving operation timetable.

[0199] Based on the above embodiment, the acquisition module includes:

[0200] The first acquisition unit: acquires the departure interval of the slow train, the running time of the slow train between stations and the stay time of the slow train at the station from the departure timetable;

[0201] Departure time calculation unit: calculates the departure time of slow trains from each station based on the operation ratio of express trains and slow trains, departure intervals, running time of slow trains between stations, and the stay time of slow trains at stations;

[0202] The second acquisition unit is used to acquire the running curve of the slow train between stations, and calculate the speed of the slow train between stations according to the time when the slow train leaves each station and the running curve;

[0203] Position calculation unit: obtains the distance between stations, and calculates the position of the slow train between stations at any time based on the distance between stations and the speed of the slow train between stations.

[0204] Based on the above embodiment, the weight calculation module includes:

[0205] Statistics unit: Use facial recognition technology to count the number of passengers getting on and off each train at each station;

[0206] Passenger number calculation unit: calculate the number of passengers of the slow train at each station according to the number of passengers getting on and off the train;

[0207] The third acquisition unit is used to acquire the weight of the slow train, and calculate the weight of the slow train at each station based on the weight of the slow train and the number of passengers.

[0208] Based on the above embodiment, the energy consumption calculation module includes:

[0209] The fourth acquisition unit is used to acquire the traction time and cruising time of the slow train between stations;

[0210] The first calculation unit calculates the traction period and cruising period of the slow train according to the time when the slow train leaves each station and the traction time and cruising time of the slow train between stations;

[0211] The second calculation unit: constructs a traction energy consumption calculation model of the slow train according to the mass of the slow train, the speed of the slow train between stations and the position between stations, and calculates the energy required by the slow train during the traction period and the cruising period.

[0212] Based on the above embodiment, the capability calculation module includes:

[0213] The fifth acquisition unit is used to acquire the braking time of the slow train between stations;

[0214] The third calculation unit is used to calculate the braking period of the slow train according to the time when the slow train leaves each station and the braking time of the slow train between stations;

[0215] The fourth calculation unit: constructs a regenerative energy generation model of the slow train according to a preset loss coefficient, the mass of the slow train, the speed of the slow train between stations, and the position of the slow train between stations, and calculates the energy generated by the slow train during the braking period;

[0216] A sixth acquisition unit is used for acquiring a train that is in the same time period as the slow train and is in the traction period, and the energy required by the train in the traction period;

[0217] Comparison unit: compares the energy required by the train during the traction period with the energy generated by the slow train during the braking period, and uses the smaller energy as usable regenerative energy.

[0218] Based on the above embodiment, the model building module includes:

[0219] Constraint construction unit: constructs operation time constraints, train stop time constraints, train departure interval and total return time constraints, and train minimum tracking interval constraints based on departure interval and station dwell time;

[0220] The fifth calculation unit: calculates the total energy consumption of all trains during the entire operation time according to the energy and regenerative energy required by the running line during the entire operation time;

[0221] Model building unit: Under the conditions of satisfying the operating time constraints, train stop time constraints, train departure interval time and total return time constraints and train minimum tracking interval constraints, the total energy consumption of all trains during the entire operating time is minimized as the objective function, and an energy-saving operation diagram optimization model for fast and slow trains based on passenger capacity is established.

[0222] Based on the above embodiment, the solution module includes:

[0223] Conversion unit: constructing operation time gaps, and converting the fast and slow train energy-saving operation diagram optimization model into an overall planning model based on the operation time gaps;

[0224] Solving unit: Solve the overall planning model based on the grey wolf algorithm with improved convergence factor and differential evolution to obtain the optimal departure interval, stop time and total turnaround time of express trains and slow trains.

[0225] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0226] Embodiment 3:

[0227] Corresponding to the above method embodiment, this embodiment also provides an energy-saving operation diagram optimization device for fast and slow vehicles based on passenger capacity. The energy-saving operation diagram optimization device for fast and slow vehicles based on passenger capacity described below and the energy-saving operation diagram optimization method for fast and slow vehicles based on passenger capacity described above can be referenced to each other.

[0228] Figure 4 FIG. 8 is a block diagram of a fast and slow train energy-saving operation diagram optimization device 800 based on passenger volume according to an exemplary embodiment. Figure 4 As shown, the fast and slow train energy-saving operation diagram optimization device 800 based on passenger capacity may include: a processor 801, a memory 802. The fast and slow train energy-saving operation diagram optimization device 800 based on passenger capacity may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0229] The processor 801 is used to control the overall operation of the fast and slow vehicle energy-saving operation diagram optimization device 800 based on passenger capacity, so as to complete all or part of the steps in the fast and slow vehicle energy-saving operation diagram optimization method based on passenger capacity. The memory 802 is used to store various types of data to support the operation of the fast and slow vehicle energy-saving operation diagram optimization device 800 based on passenger capacity, and these data may include, for example, instructions for any application or method operating on the fast and slow vehicle energy-saving operation diagram optimization device 800 based on passenger capacity, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 802 or sent via the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be keyboards, mice, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the fast and slow vehicle energy-saving operation diagram optimization device 800 based on passenger capacity and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 805 can include: Wi-Fi module, Bluetooth module, NFC module.

[0230] In an exemplary embodiment, the fast and slow vehicle energy-saving operation diagram optimization device 800 based on passenger capacity can be implemented by one or more application-specific integrated circuits (Application Specific Integrated Circuit, referred to as ASIC), digital signal processors (Digital Signal Processor, referred to as DSP), digital signal processing devices (Digital Signal Processing Device, referred to as DSPD), programmable logic devices (Programmable Logic Device, referred to as PLD), field programmable gate arrays (Field Programmable Gate Array, referred to as FPGA), controllers, microcontrollers, microprocessors or other electronic components, and are used to execute the above-mentioned fast and slow vehicle energy-saving operation diagram optimization method based on passenger capacity.

[0231] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity are implemented. For example, the computer-readable storage medium may be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions may be executed by the processor 801 of the fast and slow vehicle energy-saving operation diagram optimization device 800 based on passenger capacity to complete the above-mentioned method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity.

[0232] Embodiment 4:

[0233] Corresponding to the above method embodiment, a readable storage medium is also provided in this embodiment. The readable storage medium described below and the method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity described above can refer to each other.

[0234] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity in the above-mentioned method embodiment.

[0235] The readable storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or other readable storage medium that can store program codes.

[0236] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0237] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which 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 method for optimizing the energy-saving operation diagram of fast and slow trains based on passenger capacity, characterized in that: include: Get the operation ratio of express trains and slow trains and the train departure timetable, and calculate the positions of express trains and slow trains at any time according to the operation ratio of express trains and slow trains and the train departure timetable, including: Obtain the departure interval of slow trains, the running time of slow trains between stations and the staying time of slow trains at stations from the departure timetable; The time when the slow train leaves each station is calculated based on the ratio of express trains to slow trains, the departure interval, the running time of the slow train between stations, and the dwelling time of the slow train at the station; Obtain the running curve of the slow train between stations, and calculate the speed of the slow train between stations based on the time when the slow train leaves each station and the running curve; Get the distance between stations, and calculate the position of the slow train between stations at any time based on the distance between stations and the speed of the slow train between stations; Use facial recognition technology to determine the number of passengers on the train at each station, and calculate the weight of express and slow trains at each station based on the number of passengers; Based on the weight and position of express trains and slow trains at each station, the traction energy consumption calculation models of express trains and slow trains are constructed to calculate the traction energy consumption required for the running line during the entire operating time, including: Get the traction time and cruising time of slow trains between stations; The traction period and cruising period of the slow train are calculated according to the time when the slow train leaves each station, the traction time and cruising time of the slow train between stations; According to the mass of the slow train, the speed of the slow train between stations and the position between stations, a traction energy consumption calculation model of the slow train is constructed to calculate the energy required by the slow train during the traction period and the cruising period. Based on the actual running speed curves and positions of express trains and slow trains, the regenerative energy generation models of express trains and slow trains are constructed respectively to calculate the regenerative energy of the running line during the entire operating time. With the goal of minimizing the total energy consumption of all service trains during the entire operating time, an optimization model for the energy-saving operation diagram of fast and slow trains based on passenger capacity is established according to the required traction energy consumption and regenerative energy. Solve the fast and slow train energy-saving operation diagram optimization model to obtain the fast and slow train energy-saving operation timetable.

2. The method for optimizing the energy-saving operation diagram of fast and slow trains based on passenger capacity according to claim 1 is characterized in that ,Use facial recognition technology to determine the number of passengers on the train at each station, and calculate the weight of the slow train at each station based on the number of passengers, including: Use facial recognition technology to count the number of passengers getting on and off each train at each station; The number of passengers of the slow train at each station is calculated based on the number of passengers getting on and off the train; Get the weight of the slow train, and calculate the weight of the slow train at each station based on the weight of the slow train and the number of passengers.

3. The method for optimizing the energy-saving operation diagram of fast and slow trains based on passenger capacity according to claim 1 is characterized in that ,Based on the actual running speed curve and position of the slow train, a regenerative energy generation model of the slow train is constructed, including: Get the braking time of slow trains between stations; The braking period of the slow train is calculated based on the time when the slow train leaves each station and the braking time of the slow train between stations. A regenerative energy generation model of the slow train is constructed according to the preset loss coefficient, the mass of the slow train, the speed of the slow train between stations and the position of the slow train between stations, and the energy generated by the slow train during the braking period is calculated; Obtaining a train in the same time period as the slow train and in the traction period and the energy required by the train in the traction period; Compare the energy required by the train during the traction period with the energy generated by the slow train during the braking period, and use the smaller energy as usable regenerative energy.

4. The method for optimizing the energy-saving operation diagram of fast and slow trains based on passenger capacity according to claim 1 is characterized in that , with the goal of minimizing the total energy consumption of all service trains during the entire operating time, an energy-saving operation diagram optimization model for fast and slow trains based on passenger capacity is established according to the required traction energy consumption and regenerative energy, including: According to the departure interval and the time spent at the station, the operation time constraints, the train stop time constraints, the train departure interval and the total return time constraints, and the train minimum tracking interval constraints are constructed; Based on the energy required and regenerated energy of the running line during the entire operating time, the total energy consumption of all trains during the entire operating time is calculated; Under the conditions of satisfying the operating time constraints, train stop time constraints, train departure interval and total return time constraints as well as train minimum tracking interval constraints, an energy-saving operation diagram optimization model for fast and slow trains based on passenger capacity is established with the minimization of total energy consumption of all trains during the entire operating time as the objective function.

5. The method for optimizing the energy-saving operation diagram of fast and slow trains based on passenger capacity according to claim 1 is characterized in that ,Solving the energy-saving operation diagram optimization model of the fast and slow trains to obtain the energy-saving operation schedule of the fast and slow trains, including: Constructing an operation time gap, and converting the fast and slow train energy-saving operation diagram optimization model into an overall planning model based on the operation time gap; The overall planning model is solved by the Grey Wolf Algorithm based on improved convergence factor and differential evolution to obtain the optimal departure interval, stop time and total turnaround time of express and slow trains.

6. A device for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity, used in the method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity as claimed in any one of claims 1 to 5, characterized in that: include: Acquisition module: obtain the operation ratio of express trains and slow trains and the train departure schedule, and calculate the positions of express trains and slow trains at any time according to the operation ratio of express trains and slow trains and the train departure schedule; Weight calculation module: Use facial recognition technology to determine the number of passengers on the train at each station, and calculate the weight of express and slow trains at each station based on the number of passengers; Energy consumption calculation module: Based on the weight and position of express trains and slow trains at each station, the traction energy consumption calculation models of express trains and slow trains are constructed to calculate the traction energy consumption required for the running line during the entire operating time; Energy calculation module: Based on the actual running speed curves and positions of express trains and slow trains, the regenerative energy generation models of express trains and slow trains are constructed respectively to calculate the regenerative energy of the running line during the entire operating time; Model building module: with the goal of minimizing the total energy consumption of all service trains during the entire operating time, an energy-saving operation diagram optimization model for fast and slow trains based on passenger capacity is established according to the required traction energy consumption and regenerative energy; Solution module: solve the fast and slow train energy-saving operation diagram optimization model to obtain the fast and slow train energy-saving operation timetable.

7. A device for optimizing the energy-saving operation diagram of fast and slow trains based on passenger capacity, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity as described in any one of claims 1 to 5 when executing the computer program.

8. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for optimizing the energy-saving operation diagram of fast and slow vehicles based on passenger capacity as claimed in any one of claims 1 to 5 are implemented.

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