JP6708574B2 - Program and operation pattern determination device - Google Patents

Description

The present invention calls each train of the train schedule "train streak", the part that separates each train streak between stop stations is called "partial streak", and determines the operation pattern of each partial streak that separates each train streak Thus, the present invention relates to an operation pattern determination device or the like that determines the operation patterns of all the partial stripes on the train schedule.

In recent years, there is an increasing need for reduction of energy consumption in railways, and research on so-called energy-saving driving, in which energy consumption is reduced by devising driving operations, is being advanced. For example, in Patent Document 1, the energy consumption is reduced by modifying the operation curve created so that the running time becomes the shortest within the range of the train capability while keeping the speed limit set for the track. Techniques are disclosed.

JP, 2016-573, A

The method of Patent Document 1 described above focuses on one train and creates an operation curve that reduces the energy consumption of the train, and the running time between stations may change. However, in actual train operation, since it was created in consideration of passenger convenience and satisfying the constraint conditions such as track facilities, vehicle operation, crew operation, etc., the operation curve that strictly adheres to the train schedule Is desirable.

Further, in order to study the minimization of the energy consumption of the entire train operation with respect to the entire train schedule such as a train schedule for one day, it is necessary to consider the interaction of a plurality of running trains. When a train is regenerating and there is a train running nearby, the regenerative electric power is consumed as energy when the train is running. On the other hand, when there are no power trains nearby, regenerative revocation will occur and energy will be lost. That is, it is necessary to consider the timing at which one train regenerates and the timing at which another train powers.

Furthermore, in order to effectively utilize the regenerated electric power, research and development for providing an electric power storage device in the feeder circuit have been made, and are being put to practical use. Therefore, there is also a desire to consider minimizing the energy consumption of the entire train operation when an electric power storage device is provided. More specifically, it is necessary to consider not only whether or not the power storage device is provided, but also the efficiency associated with the loss that occurs during power storage and power feeding of a device including a power converter mounted in the power storage device.

The present invention has been made in view of the above circumstances, and an object thereof is to operate each partial streak of each train streak capable of reducing the total power consumption of the entire train operation according to the train schedule. It is to provide a technique for determining a pattern.

The first invention for solving the above problems is
For a given train by causing a computer to determine, for each sub-strip that separates each train streak at a stop station, a driving pattern when a given operation vehicle assigned to the sub-strip travels the sub-strip A program for determining the driving pattern of all the partial streaks of the diamond,
For each of the partial stripes, a driving pattern candidate setting means for setting a plurality of driving pattern candidates that the operation vehicle assigned to the partial stripe can travel while keeping the running time of the partial stripe,
For each of the driving pattern candidates, the assigned operation vehicle, the corresponding partial streak, the predicted power for setting a predicted power amount including at least power running or regenerative power amount for each time when traveling according to the driving pattern candidate Quantity setting means,
It is a combination in which each of the partial lines of the train schedule is selected from a plurality of operation pattern candidates set in the partial schedule, and the corresponding predicted power amount is applied to the traveling time on the train schedule. A calculation means for calculating the combination of the total amount of power consumption of the estimated electric energy of the running train in each time section through the train schedule that satisfies a predetermined minimum condition,
And a program for operating the computer.

According to the first aspect of the present invention, it is possible to determine an operation pattern of each partial streak such that the total power consumption of the entire train operation according to the train schedule satisfies a predetermined minimum condition. Specifically, while considering the balance between the power running power and regenerative power of each running train for each time section, the operation pattern for each partial stripe so that the total power consumption of the entire train operation satisfies the minimum condition. Determine the combination of. Here, the minimum condition may be "minimum" or "equal to or less than a predetermined power amount that can be regarded as minimum". Accordingly, it is possible to determine the operation pattern of each partial streak such that the total power consumption of the entire train operation satisfies the minimum condition while keeping the running time determined by the train schedule. The train schedule to be processed may be a one-day schedule for the entire predetermined line section, or may be a schedule for some time zones of some sections.

A second invention is the program of the first invention,
The predicted power amount setting means sets the predicted power amount for each of the driving pattern candidates by further adding a given passenger amount for each partial stripe.
Is a program for operating the computer.

According to the second aspect of the present invention, the predicted power amount for each driving pattern can be set in consideration of the passenger amount for each partial streak. That is, if the passenger amount is different, the load of the operating vehicle is changed, and the electric power amount related to the running of the train, such as the power running electric power amount and the regenerable electric power amount is changed. If the data of the actual number of passengers, for example, between the stations and for each time zone is used as the passenger amount, it is possible to determine a more actual driving pattern for the train schedule.

A third invention is the program according to the first or second invention,
The predicted power amount setting means sets the predicted power amount for each of the operation pattern candidates by further considering the given auxiliary power of the assigned operation vehicle.
Is a program for operating the computer.

According to the third aspect of the present invention, it is possible to set the predicted power amount for each driving pattern candidate in consideration of the auxiliary power of the operating vehicle. Auxiliary power varies depending on the operating vehicle. In other words, when the operation vehicle is different, the auxiliary machine power is different, and as a result, the electric power related to traveling such as the power running electric energy and the regenerative electric energy is different. By adding the auxiliary electric power according to the operating vehicle, it is possible to determine a more realistic driving pattern for the train schedule.

A fourth invention is the program according to any one of the first to third inventions,
For the combination satisfying the minimum condition, at least the balance in each time section, the power running power amount, the regenerable power amount, the regenerative power amount actually used in the time section of the regenerable power amount, and, Evaluation value calculation means for calculating total power consumption in the entire train schedule by subtotaling for each regenerative power consumption,
Is a program for further functioning the computer.

According to the fourth aspect of the present invention, when the vehicle travels according to the combination of operation patterns calculated assuming that the total power consumption amount satisfies the minimum condition, the power consumption amount, the regenerable power amount, the actually used regenerative power amount, and the regenerative invalid power. It is possible to determine the change over time in the amount of electric power related to the running of the train, such as the amount.

A fifth invention is the program according to any one of the first to fourth inventions,
The calculation means, assuming a given power storage device, the surplus power amount when the regenerable power amount exceeds the power running power amount in the time section is stored in the power storage apparatus, the power running power in the time section. Of the amount of power shortage when the amount exceeds the regenerable power amount, the amount of power that is equal to or less than the stored power amount of the power storage device at the time of the time section is to be fed from the power storage apparatus, in each time section. Calculate the balance,
Is a program for operating the computer.

According to the fifth aspect of the present invention, it is possible to determine an operation pattern that minimizes the total power consumption of the entire train operation while keeping the train schedule in consideration of the electric power storage device that stores electric power.

A sixth invention is a program according to the fifth invention,
For a combination satisfying the minimum condition, a power storage device evaluation value calculation means for calculating the total stored power amount of the power storage device,
Is a program for further functioning the computer.

According to the sixth aspect of the present invention, when the vehicle travels according to the combination of the operation patterns calculated assuming that the total power consumption amount satisfies the minimum condition, the power storage device-related power amount such as the total stored power amount or the peak stored power amount is calculated. You can Thereby, for example, it can be used as a material for studying the required capacity when the power storage device is installed, and can be useful for the design of the power storage device.

7th invention is the program of 5th or 6th invention, Comprising:
Power absorption rate setting means for setting the power absorption rate of the power storage device,
To further function the computer as
The calculating means calculates the amount of electric power during storage in the electric power storage device based on the electric power absorption rate,
Is a program for operating the computer.

According to the seventh aspect, by setting the power absorption rate of the power storage device to be variable, the amount of power stored in the power storage device is changed. Therefore, the combination of operation patterns for minimizing the total power consumption of the entire train operation may change depending on the power storage device with which the power absorption rate is installed, depending on the design of the power storage device. It is possible to determine an appropriate combination of driving patterns.

The eighth invention is
For each partial stripe that separates each train stripe at the stop station, by determining the operation pattern when a given operation vehicle assigned to the partial stripe travels the partial stripe, all of the given train schedule An operation pattern determination device for determining the operation pattern of the partial streaks of
For each of the partial streaks, a driving pattern candidate setting means for setting a plurality of driving pattern candidates in which the operation vehicle assigned to the partial streak can travel while keeping a running time of the partial streak,
For each of the driving pattern candidates, the assigned operation vehicle, the corresponding partial streak, the predicted power for setting a predicted power amount including at least power running or regenerative power amount for each time when traveling according to the driving pattern candidate Quantity setting means,
It is a combination in which each of the partial lines of the train schedule is selected from a plurality of operation pattern candidates set in the partial schedule, and the corresponding predicted power amount is applied to the traveling time on the train schedule. And a calculation means for calculating a combination of the total amount of power consumption of the predicted electric energy of the running train in each time section through the train schedule, which satisfies a predetermined minimum condition,
It is an operation pattern determination device provided with.

According to the eighth invention, it is possible to realize a driving pattern determination device having the same effect as that of the first invention.

An example of the target train operation system. An example of setting a driving pattern candidate. An example of setting of estimated electric energy. An example of the balance of calculation of the predicted power amount for each time zone. An example of the balance of the predicted electric energy by time zone. The functional block diagram of a driving pattern determination apparatus. An example of driving pattern candidate/predicted electric energy data. An example of operation pattern combination data. An example of electric energy evaluation value data. An example of electric power storage apparatus evaluation value data. The flowchart of a driving pattern determination process. An example of a train schedule. Calculation example of a combination of driving patterns. Calculation example of a combination of driving patterns. An example of calculating the amount of electric power for traveling. An example of calculation of the amount of electric power concerning an electric power storage device.

[Overview]
In this embodiment, the operation pattern of each train is determined such that the total amount of power consumption during train operation according to a given train schedule satisfies the minimum condition. The given train schedule may be a one-day schedule for the entire predetermined line section, or may be a schedule for a part of the line section and for some time zones, but in the present embodiment, It is explained as a day's timetable for the entire line area.

(1) Train Operation System FIG. 1 is a schematic diagram of a train operation system which is a target of the present embodiment. As shown in FIG. 1, in the present embodiment, a line section of a multiple line including an up line and a down line in which a plurality of stations (A station to Z station) is provided is targeted. Of course, this is an example, and it is also applicable to a single-line segment and a multiple-line segment. In addition, a feeder circuit is built along the railway line, which includes a substation that supplies electric power to the overhead line and an electric power storage device that stores regenerative power from the overhead line and supplies (powers) the stored power to the overhead line. And

Each train line on the train schedule is adjusted so that the total power consumption, which is the sum of the power consumption when traveling while observing the running time of the train schedule given for such a train operation system, satisfies the minimum condition. For each partial streak delimited by the stop station, a driving pattern when the operation vehicle assigned to the partial streak travels on the partial streak is determined. Further, in the present embodiment, the minimum condition is described as being “minimum” for the sake of simplicity of description, but the minimum condition can be regarded as a condition that can be regarded as the minimum. This is because the minimum calculation result is not always obtained in the convergence calculation by the computer, and the calculation result may be calculated as the minimum calculation result when the convergence calculation is completed when a certain condition (minimum condition) is satisfied.

(2) Driving Pattern Candidates First, as shown in FIG. 2, a plurality of driving pattern candidates are set for each partial stripe that separates each train stripe on the train schedule at the stop station. In FIG. 2, "1 train" and "2 trains" correspond to train lines, respectively. The driving pattern is a driving and manipulating method including notch handling of the operation vehicle to which the running of the partial streak is assigned, and is expressed as a curve showing the running speed at each running position. The driving pattern candidate is set to run at the running time determined by the train schedule between the stations corresponding to the partial streak. In addition, it is desirable to set a driving pattern that can be actually traveled as the driving pattern candidate. For example, a plurality of driving pattern candidates can be set by making different notches to be used among the notches that can be used in the operation vehicle.

(3) Predicted power amount Next, for each partial stripe that separates each train stripe of the train schedule at the stop station, the operation vehicle assigned to the partial stripe is determined according to each of the plurality of operation pattern candidates set for the partial stripe. The amount of electric power predicted when traveling (predicted amount of electric power) is set. FIG. 3 is a diagram illustrating an example of setting the predicted power amount. In FIG. 3, of the train streaks of “1 train”, the predicted power when the assigned operation vehicle travels according to the “driving pattern candidate A1” set in the partial streak corresponding to “between A station and B station” The example which sets a quantity is shown. The predicted power amount is a power running power amount or a power amount that can be regenerated (regenerative power amount), and is set in time series at predetermined time intervals. The power running electric energy is the electric energy when the operation vehicle travels while consuming electric power, and is mainly the electric energy consumed by the power running operation. The regenerable electric energy is the electric energy that can be returned to the overhead wire when the operation vehicle travels while returning the electric power to the overhead wire, and is mainly the regenerative electric energy generated by braking. In addition, the amount of power that can be regenerated is the value when it is assumed that regenerative revocation will not occur without considering other trains in the train.

In addition, the power running power amount and the regenerable power amount include the power consumption amount by the auxiliary machine (auxiliary machine power). During regenerative traveling, the amount of power consumed by the auxiliary machine is deducted to set the regenerable power amount. Further, during coasting, the amount of power consumed by the auxiliary machine is required, so it is set as the amount of power running. In the bar graph of the “predicted power amount” in FIG. 3, the slight power running power amount at the center of the time axis indicates the power consumption amount of the auxiliary machine during coasting. Auxiliary electric power is electric power used for lighting, cooling and heating of the operating vehicle, and is always necessary if the operating vehicle is in contact with the feeding circuit. The auxiliary electric power differs depending on the operating vehicle, and the amount of electric power due to the use of cooling and heating, which accounts for a large proportion of the auxiliary electric power, differs depending on the outside temperature. The auxiliary electric power can be obtained from the data that defines the relationship between the outside air temperature and the actual measured value of the auxiliary electric power including the power consumption by cooling and heating for each operating vehicle. When the operating vehicle and the outside air temperature are different, the auxiliary machine electric power is different, and as a result, the electric power related to traveling such as the power running electric energy and the regenerative electric energy is different.

Although the electric power amount such as the power running electric power amount and the regenerable electric power amount is a continuous value, in the present embodiment, the determination of the operation pattern for each station is realized by formulating and solving it as a mathematical optimization problem. Set as a discrete value. Specifically, the running power amount or the regenerable power amount is calculated and set as the predicted power amount for each time zone in which the running time between stations is divided into short predetermined time intervals (for example, about 1 to 5 seconds). To do.

Further, the calculation of the power running electric energy and the regenerative electric energy is performed based on the vehicle performance of the operation vehicle assigned to the partial streak and the number of passengers (the number of passengers) between the stations corresponding to the partial streak. The vehicle performance is a pulling force characteristic, a power running power characteristic, a regenerative power characteristic, a regenerative narrowing characteristic, a braking force, a running resistance type, a formation mass, and the like. Even when traveling between the same stations according to the same driving pattern, if the vehicle performance of the operating vehicle is different, the electric power for traveling such as the power running electric energy and the regenerative electric energy is different. The number of passengers can be obtained from a combination of a departure station (appearing station) and a destination station, and OD (Origin Destination) data defining a large number of passengers whose appearance times are determined. Even when the same operation vehicle travels between the same stations according to the same driving pattern, the different weights of the entire train will differ if the number of passengers is different, and thus the electric power for traveling such as the power running power amount and the regenerable power amount will be different.

(4) Determining the combination of operation patterns Then, based on the predicted power consumption, the total power consumption of the entire train operation according to the train schedule is minimized (to satisfy the minimum condition), and each partial stripe is For, regarding one of the plurality of driving pattern candidates set for the partial streak, a combination in which one is selected is determined.

Specifically, the balance of the predicted power consumption of each running train is calculated for each time section on the train schedule, and the total power consumption is calculated so that the total balance of the balance of each time section over the entire train schedule is minimized. , Determine the combination of driving patterns. The time section can be a time zone in which the predicted power amount is set. This is the sum of actual power consumption calculated by subtracting the sum of regenerative electric energy from the sum of power running energy for each time section, which minimizes the total power consumption of the entire train operation on the train schedule. This is because the balance between the power running and the regeneration, in which the regenerable electric power is consumed by the power running, is important to achieve, and it is desirable that more regenerative energy is consumed as the power running energy.

The balance of the predicted power amount in each time zone can be obtained as shown in FIG. First, as shown in FIG. 4, a train stripe running on a train timetable in a target time zone is extracted. In Figure 4, at a certain time period _{t a,} "1 Train", "2 train", "11 train", "12 Train", the five train lines of "13 train" train is traveling. Then, for each of the extracted train line, by selected portions streak corresponding to the time slot t _a, selects one operating pattern candidates of the plurality of operation patterns candidate set for each portion streaks, the the predicted power amount in the selected operating pattern candidate time slot t _a set corresponding to, and the predicted power of the time zone t _a of the train line. Selecting a driving pattern candidate means assuming that the partial streak runs according to the selected driving pattern candidate.

FIG. 5 shows an example of the predicted electric energy for each time period thus obtained. 5A and 5B show predicted power amounts for the same time zone t, the driving pattern candidates assumed for each running train (also referred to as a partial streak corresponding to the time zone t) are shown. It is an example of a different combination. When the assumed driving pattern candidates are different, the driving states such as power running, coasting, and braking are different, and as a result, the predicted power amount is also different. Based on the hypothesized driving pattern candidates, the running train is powered by the power consumption group that is consuming electric power by the power running operation and the coasting operation (that is, the predicted power amount is the power running energy amount) and the brake is applied to the train. By grouping the power generation groups that can be regenerated (that is, the predicted amount of power is the regenerable power amount) and comparing the total of the predicted amount of energy for each group, It is possible to obtain the power consumption amount, the regenerative power amount, and the regenerated invalid power amount.

In FIG. 5A, "1 train" and "12 trains" out of 5 trains ("1 train", "2 trains", "11 trains", "12 trains", "13 trains") "Train" and "13 trains" are power consumption groups, and the total power consumption of these is 260 [kWh]. In addition, "2 trains" and "11 trains" are power generation groups, and the total amount of regenerable power of these is 130 [kWh]. Therefore, the total amount of power consumption (260 [kWh]) is larger than the total amount of regenerative power (130 [kWh]), all of the regenerative power is consumed as power running power during the time period t, and regenerative revocation is not possible. Does not happen. That is, the actual regenerative power amount (hereinafter, appropriately referred to as “utilized regenerative power amount”) is 130 [kWh], and the power consumption amount is 130 [kWh] (=260 [kWh]−130 [kWh]).

Further, in FIG. 5B, “1 train” and “13 trains” are power consumption groups, and the total power consumption of these is 80 [kWh]. In addition, there are “2 trains”, “11 trains”, and “12 trains” in the power generation group, and the total amount of regenerable power of these is 230 [kWh]. Therefore, since the total power consumption (80 [kWh]) is smaller than the total regenerative power (230 [kWh]), in this case, only a part of the regenerative power is available as the power running power in the time zone t. It is consumed and regenerative revocation occurs. That is, the amount of regenerated electric power used and the amount of electric power consumed are equal to 80 [kWh], and the amount of regenerated invalid electric power that is not consumed as power running electric power is 150 [kWh] (=230 [kWh]-150 [kWh] of the regenerable electric power. ]).

(5) Electric Power Storage Device Furthermore, in the present embodiment, it is considered that the electric power storage device is used to effectively utilize the regenerated invalid power. That is, in a certain period of time, when the total amount of regenerable power exceeds the total amount of power consumption and regenerative revocation occurs, surplus power that is not consumed among the regenerable power is stored in the power storage device. Conversely, when the regenerable power amount is less than the total power running power amount, the power stored in the power storage device is preferentially supplied instead of the power supply from the overhead wire.

In the present embodiment, the capacity of the power storage device is set to infinity in calculation, and the surplus power is stored in the power storage device at the power absorption rate “w (0≦w≦1)”. That is, the energy loss rate when storing the surplus power is "1-w". Further, it is assumed that no loss occurs when discharging (power feeding) from the power storage device. The power absorption rate w=1 corresponds to the case where there is no loss during power storage, and the power absorption rate w=0 means that all of the surplus power is lost, that is, the power storage. This corresponds to the case where no device is provided.

(6) Formulation as an optimization problem From these, a mathematical optimization problem that finds a combination of operation patterns that minimizes the total power consumption is formulated as follows.

とし、列車ｉが停車駅間ｓ（ｉ，ｔ）を運転パターンｑで走行しているときの時刻ｔにおける回生可能電力量を、

とする。また、電力貯蔵装置の電力吸収率を“ｗ（０≦ｗ≦１）”とする。 First, the notation is defined. That is, a set of trains i (corresponding to train streaks) on the train schedule is "I", a set of time t (corresponding to the above-described time zone) is "T", and a train station stop s (partial streak). (Corresponding to the above) is referred to as “S ⁱ ”, and the set of operation patterns at the stop s(i,t) between the trains i is referred to as “Q ^i,s(i,t) ”. In addition, as the predicted power amount, the power running power amount at time t when the train i travels between the stopped stations s(i, t) in the driving pattern q,

And the regenerable electric energy at time t when the train i travels between the stopped stations s(i,t) in the operation pattern q,

And Further, the power absorption rate of the power storage device is “w (0≦w≦1)”.

Then, the optimization problem of determining the combination of operation pattern candidates that minimizes the total power consumption of the present embodiment is described as shown in the following equation.

Expression (3) is a decision variable and represents an operation pattern when the train i travels between the stop stations s(i,t).

また、式（４）において、“Ｕ^ｉ（ｔ）”は、列車ｉの時刻ｔにおける回生可能電力量であり、次式（７）で表される。

Equation (4) is an objective function. In Expression (4), “P ⁱ (t)” is the power running electric energy of the train i at time t, and is represented by the following Expression (6).

Further, in the equation (4), “U ⁱ (t)” is the regenerative electric power amount of the train i at the time t and is represented by the following equation (7).

Further, in Expression (4), “R ⁱ (t)” is the utilized regenerative electric energy of the train i (actual regenerative electric energy). However, the amount of regenerated electric power used is not calculated for each train. It is calculated as the sum of the regenerative electric energy used by all running trains at time t. The total of the regenerative electric energy used by all running trains at time t is determined by the total of the power running electric energy and the total of the reproducible electric energy, and is represented by the following equation (8).

That is, the formula (4) is the value obtained by subtracting the “total regenerative electric energy of all running trains” from the “total power running electric energy of all running trains” at a certain time t. In addition to "electric energy", when "regenerative electric energy of all running trains" exceeds "total power running electric energy of all running trains", the surplus electric energy that exceeds that It is assumed that electricity is stored in the power storage device at the absorption rate w, and is subtracted from the "power consumption". This indicates that the power consumption amount when summing this over all times is minimized. Here, it is characteristic that the "power consumption" is not the result of focusing on a certain train alone but the result of canceling the power running and the regeneration related to all running trains.

Expression (5) is a constraint condition and represents that the train i selects only one operation pattern q in the stop stations s(i,t).

従って、式（８）を次式（１０）のように置き換えることができるとともに、変数ａ（ｔ），ｂ（ｔ），ｃ（ｔ）に関する制約条件を追加することができる。なお、式（１０）では、変数ｃ（ｔ）を最小化しているため、変数ｃ（ｔ）の値は、変数ａ（ｔ）、ｂ（ｔ）のうちの小さい方の値と一致する。

ゆえに、次式（１１）の変形が成立する。

In solving the optimization problem formulated in this way, since the expression representing the used regenerative electric energy (actual regenerative electric energy) R ⁱ (t) includes the min operator, the following equation is used to facilitate the solution. Transform and add constraints. That is, using the variables a(t), b(t), and c(t), the following equation (9) is set.

Therefore, the equation (8) can be replaced by the following equation (10), and a constraint condition regarding the variables a(t), b(t), and c(t) can be added. Since the variable c(t) is minimized in Expression (10), the value of the variable c(t) matches the smaller value of the variables a(t) and b(t).

Therefore, the modification of the following expression (11) is established.

Then, the optimization problem in which the variable c(t) representing the total amount of regenerated electric power used at the time t is added as a decision variable and formulated as shown in Expressions (3) to (5) is as follows. ) Can be transformed. In the first expression, which is the objective function of Expression (12), the power absorption rate w is in the range of 0≦w≦1, so that the coefficient “−(1-w)” of the variable c(t). Will take a value of "-1 or more and 0 or less", and the variable c(t) tries to take a value as large as possible while minimizing the objective function of the first expression of the expression (12). The conversion condition described in Expression (10) is satisfied. A well-known method can be adopted as a method for solving the formulated optimization problem.

[Function configuration]
FIG. 6 is a block diagram showing a functional configuration of the operation pattern determination device 1. As shown in FIG. 6, the driving pattern determination device 1 is a kind of computer configured to include an input unit 102, a display unit 104, a communication unit 106, a processing unit 200, and a storage unit 300.

The input unit 102 is an input device including, for example, a keyboard, a mouse, a touch panel, various switches, and the like, and outputs an operation signal according to a user's operation input to the processing unit 200. The display unit 104 is a display device including, for example, a liquid crystal display (LCD) or an organic EL display, and performs various displays based on the display signal from the processing unit 200. The communication unit 106 is a communication device including, for example, a wireless communication module, a router, a modem, a jack of a wired communication cable, a control circuit, and the like, and performs data communication with an external device.

The processing unit 200 includes an arithmetic device or an arithmetic circuit such as a CPU (Central Processing Unit) or an FPGA (Field Programmable Gate Array), and the programs and data stored in the storage unit 300, the input data from the input unit 102, and the like. Based on the above, various calculation processes are performed, and at the same time, instructions and data transfer are performed to each unit constituting the operation pattern determination device 1. In the present embodiment, the processing unit 200 includes a driving pattern candidate setting unit 202, a predicted power amount setting unit 204, a power absorption rate setting unit 206, a combination calculation unit 208, a power amount evaluation value calculation unit 210, and a power consumption. The storage device evaluation value calculation unit 212 is included in the storage device evaluation value calculation unit 212, and performs the operation pattern determination process (see FIG. 11) according to the operation pattern determination program 302.

The train schedule data to be processed is train schedule data 306, and the allocation of operation vehicles to each partial stripe of each train stripe of the train schedule is vehicle operation data 308. Specifications such as performance and weight of each operation vehicle. Is stored as the vehicle performance data 310, and the target line section is stored as the track data 304.

The operation pattern candidate setting unit 202 has a plurality of operation patterns for each partial stripe that divides each train stripe of the train schedule at the stop station and that the operation vehicle assigned to the partial stripe can travel while keeping the running time of the partial stripe. Set.

The driving pattern candidates are created by a predetermined creation process with reference to the linearity (slope, curve, etc.) of the running line section (more specifically, between the stations of the corresponding partial streak), speed limit, performance of the operating vehicle, etc. -Can be set. Of course, the data of the driving pattern candidates may be set by the user inputting via the input unit 102.

The set driving pattern candidate is stored as the driving pattern candidate/predicted power amount data 316 in association with the predicted power amount set by the predicted power amount setting unit 204.

The predicted power amount setting unit 204 is, for each driving pattern candidate, every time when the assigned operation vehicle runs a corresponding partial streak according to the driving pattern candidate (each of the above-mentioned time zones and every time t. ) The predicted power amount including at least the power running or regenerative power amount is calculated and set. Further, the predicted power amount for each operation pattern candidate can be calculated and set by further considering the auxiliary device power and the given passenger amount set in the corresponding partial stripe.

That is, for each partial streak that separates each train streak of the train schedule at the stop station, for each time when the operation vehicle assigned to the partial streak runs according to each of the plurality of operation pattern candidates set for the partial streak The power running power amount or the regenerable power amount is set as the predicted power amount. The predicted electric energy is set in consideration of the performance of the operating vehicle, the auxiliary electric power, and the number of passengers between the stations. The performance of the operating vehicle is acquired by referring to the vehicle performance data 310. The auxiliary electric power is acquired by referring to the auxiliary electric power data 311 included in the vehicle performance data 311 corresponding to the operation vehicle. Auxiliary electric power differs depending on the operating vehicle and also on the outside temperature. Since the outside temperature is roughly determined depending on the season, the auxiliary electric power data 311 can be data corresponding to auxiliary electric power when the corresponding operating vehicle travels for each season divided by the date. By referring to the auxiliary machine power data 311, it is possible to acquire the auxiliary machine power corresponding to the assumed date and season. The auxiliary machine power data 311 may be data in which the seasons are further detailed and the auxiliary machine power is associated with each month such as January and February. Further, the auxiliary machine power data 311 may be data in which the outside machine temperature in a predetermined temperature range such as every 5 degrees is associated with the auxiliary machine power, not the season or the month. Further, the number of passengers is obtained as the number of passengers in the corresponding traveling time zone between the corresponding stations by referring to the OD data 312.

Such setting of the predicted electric energy is set by a predetermined calculation process referring to the performance of the operating vehicle, the auxiliary electric power, and the number of passengers between stations in the traveling time zone. It may be set by inputting via.

The set predicted power amount is stored as the driving pattern candidate/predicted power amount data 316 in association with the corresponding driving pattern candidate. FIG. 7 is an example of the driving pattern candidate/predicted power amount data 316. As shown in FIG. 7, the driving pattern candidate/predicted power amount data 316 includes the set driving pattern candidate and predicted power amount for each stop station of each train (train streak) corresponding to a partial streak on the train schedule. Are stored in association with each other.

The power absorption rate setting unit 206 sets the power absorption rate w of the power storage device. The power absorption rate w is set as a value in the range of 0≦w≦1. The setting of the power absorption rate can be performed according to the input via the input unit 102. The set power absorption rate w is stored as the power absorption rate data 314.

The combination calculation unit 208 is a combination in which each partial streak of the train schedule is selected from a plurality of operation pattern candidates set in the partial streak, and the corresponding predicted power amount is traveled on the train schedule. A combination is calculated in which the total amount of power consumption obtained by adding up the balance of the estimated amount of power of the running train in each time section applied to the time through the train schedule satisfies a predetermined minimum condition. The balance in each time section assumes a given power storage device, and 1) at that time in the time section, the "sum of regenerative electric energy of all running trains" is "of all running trains". The surplus power when the total power running is exceeded is stored in the power storage device, and 2) in the time section, the "total power running of all running trains" is "running". Calculated by supplying from the power storage device the power that is equal to or less than the stored power amount of the power storage device at the time of the relevant time section among the power shortages when the total regenerative power of all trains is exceeded. To do. In addition, the amount of power stored in the power storage device is calculated based on the set power absorption rate w.

That is, based on the predicted electric energy for each time corresponding to each of the plurality of operation pattern candidates set for each station for each train corresponding to the partial streak, the formula (3) to (5) or the formula (12) is used. By solving the optimization problem formulated as shown and obtaining the value of the decision variable shown in Expression (3), a combination of operation pattern candidates to be applied between the train stations is calculated for each train.

In addition, the combination calculation unit 208 obtains a combination of operation patterns that minimizes the total power consumption for each power absorption rate w set for the power storage device. As will be described later, when the power absorption rate w is different, the combination of operation patterns that minimizes the total power consumption is different.

The calculated combination of driving pattern candidates is stored as driving pattern combination data 320. FIG. 8 is an example of the operation pattern combination data 320. According to FIG. 8, the operation pattern combination data 320 is a plurality of data for each power absorption rate of the power storage device, and each data is the candidate number of the operation pattern applied between the stations of each train corresponding to the partial streak. Are stored in association with each other.

The power amount evaluation value calculation unit 210 calculates, as an evaluation value, the power amount related to the running of each train in accordance with the combination of the operation patterns calculated by the combination calculation unit 208 as the minimum total power consumption amount.

Specifically, using the predicted power amount corresponding to the operation pattern applied between each station of each train, among trains running at each time, of each train that consumes power by powering operation or coasting operation The sum of the power running electric energy which is the predicted electric energy and the total of the regenerative electric energy which is the predicted electric energy of each train that is in the brake and is in the regenerative state is calculated. Next, the total amount of power running electric power and the total amount of regenerative electric power are compared to obtain the regenerated electric power used, which is consumed as the power running electric power, and the surplus electric power amount thereof, among the regenerative electric power amounts. Then, assuming that the surplus power amount is charged at the power absorption rate w, the power amount charged in the power storage device is obtained. When the power storage device is not provided, all of this surplus power amount becomes the regenerative invalid power amount. Furthermore, the total power running energy, which is the sum of the total power running energy at each time, and the total regenerative power, which is the total sum of the regenerative power usage at each time, are obtained, and the total power regeneration is calculated from the total power running power. The amount of power obtained by subtracting the amount of power is calculated as the total amount of power consumption of the entire train operation according to the train schedule.

The combination of operation patterns that minimizes the total power consumption calculated by the combination calculation unit 208 is calculated for each power absorption rate w of the power storage device. Therefore, the power amount evaluation value calculation unit 210 calculates the power amount related to the running of the train for each combination of operation patterns corresponding to each power absorption rate w.

The calculated electric energy related to the running of the train is stored as electric energy evaluation value data 322. FIG. 9 is an example of the power amount evaluation value data 322. According to FIG. 9, the power amount evaluation value data 322 is a plurality of data for each power absorption rate of the power storage device, and each data includes, for each time, the total power running power amount by the running train and the regenerative power. The total possible power amount, the total regenerative power amount used, and the power amount charged to the power storage device are stored in association with each other.

The electric power storage device evaluation value calculation unit 212 calculates the electric power related to the electric power storage device when each train runs in accordance with the combination of operation patterns calculated by the combination calculation unit 208 as having the minimum total power consumption. Specifically, at each time, the total power running electric energy of all running trains and the total regenerative electric energy are compared, and the surplus electric power of the regenerative electric energy is charged or the It is determined whether or not the stored power is supplied to the overhead line, and the amount of power (charging power amount or power supply amount) is obtained. The charging power amount is a value obtained by multiplying the surplus power amount by the power absorption rate w. Then, the stored power amount of the power storage device after being charged or fed is calculated.

The combination of operation patterns that minimizes the total power consumption calculated by the combination calculation unit 208 is calculated for each power absorption rate w of the power storage device. Therefore, the power storage device evaluation value calculation unit 212 calculates the amount of power related to the power storage device for each combination of operation patterns corresponding to each power absorption rate w.

The calculated power amount of the power storage device is stored as power storage device evaluation value data 324. FIG. 10 is an example of the power storage device evaluation value data 324. According to FIG. 10, the power storage device evaluation value data is a plurality of data for each power absorption rate of the power storage device, and each data includes, for each time, the charging power amount, the power feeding power amount, and the stored power amount. And are stored in association with each other.

Returning to FIG. 6, the storage unit 300 stores, in the storage unit 300, a system program for realizing various functions for the processing unit 200 to integrally control the operation pattern determination device 1, programs and data for realizing the present embodiment, and the like. And is used as a work area of the processing unit 200 and temporarily stores calculation results executed by the processing unit 200 according to various programs, input data from the input unit 102, and the like. In the present embodiment, in the storage unit 300, a driving pattern determination program 302, track data 304, train schedule data 306, vehicle operation data 308, vehicle performance data 310 including auxiliary equipment power data 311 and OD data. 312, power absorption rate data 314, operation pattern candidate/predicted power amount data 316, operation pattern combination data 320, power amount evaluation value data 322, and power storage device evaluation value data 324 are stored.

[Process flow]
FIG. 11 is a flowchart illustrating the flow of a driving pattern process executed by the driving pattern determination device 1. This processing is realized by the processing unit 200 executing the operation pattern determination program 302. It is assumed that data such as the train schedule data 306, the track data 304, the vehicle operation data 308, the vehicle performance data 310, and the OD data 312 are set and stored prior to the execution of the processing.

First, the driving pattern candidate setting unit 202 sets a plurality of driving pattern candidates for traveling at the running time determined by the train schedule for each partial stripe that separates each train stripe of the train schedule at the stop station ( Step S1). In addition, the assumed date and season are set (step S2). Next, the predicted power amount setting unit 204 sets, for each driving pattern candidate, the predicted power amount for each time when the vehicle travels according to each driving pattern candidate. At this time, the predicted power amount for each time is set using the auxiliary machine power obtained by calculating the auxiliary machine power according to the date and season set in step S2 (step S3). Subsequently, the power absorption rate setting unit 206 sets the power absorption rate w of the power storage device (step S5).

Then, the combination calculating unit 208 determines that the surplus power at each time is charged in the power storage device at the set power absorption rate w based on the set operation pattern candidate and the predicted power amount corresponding to the set driving pattern candidate, and that each train stripe is A combination is selected in which one is selected from the plurality of set operation pattern candidates, and the combination that minimizes the total power consumption of the entire train schedule is calculated (step S7).

Next, the power amount evaluation value calculation unit 210 calculates the power amount related to the running when each train runs in accordance with the combination of the calculated driving pattern candidates (step S9). This is the power amount evaluation value. Further, the power storage device evaluation value calculation unit 212 calculates the amount of power related to the power storage device when each train runs in accordance with the combination of the calculated operation pattern candidates (step S11). This is the power storage device evaluation value.

After that, it is determined whether or not this processing is to be ended, and if not ended (step S13: NO), the process returns to step S5, and similarly, the power absorption rate w of the power storage device is reset, and the combination of operation pattern candidates is set. Recalculate. That is, when the power absorption rate w of the power storage device is changed and recalculation is performed, the process returns to step S5. On the other hand, if this process ends (step S13: YES), the combination of operation patterns applied to each train streak calculated for each set power absorption rate w and the running of the train corresponding to this combination of operation patterns The result display such as displaying the amount of power and the amount of power related to the power storage device on the display unit 104 is performed (step S15). When the above processing is performed, the operation pattern determination processing ends.

[Calculation example]
A calculation example of a combination of operation patterns that minimizes the total power consumption according to the present embodiment will be described. The target train timetables were two types of pattern timetables in which each train stopped at each station and each train departed and arrived at each station at predetermined intervals. FIG. 12 shows two types of train schedules targeted. FIG. 12A shows a train schedule α with a train interval of 5 minutes, and FIG. 12B shows a train schedule α that is twice as long as the train schedule α of FIG. This is the train schedule β. In addition, the target line section, operation vehicle, date and time zone are the same.

Then, the power absorption rate w of the power storage device is set to “w=0.0 (corresponding to no power storage device)”, “w=0.8”, “w=1.0 (ideal power storage device). For each of the three types, the combination of operation patterns that minimizes the total power consumption is calculated. Since the train schedule is a pattern schedule as shown in FIG. 12, three types of operation pattern candidates, in which the brake notch has three patterns of “B5N”, “B4N”, and “B3N”, are common to all partial stripes. Set.

13 and 14 are diagrams showing combinations of calculated operation patterns. In FIG. 13 and FIG. 14, in the target train diagram, each partial streak corresponding to the stop station of each train is shown in a display form (thick solid line, thin solid line, and thick dotted line) according to the applied driving pattern. ing. FIG. 13 is a calculation result for the train schedule α in FIG. 12A, and FIG. 14 is a calculation result for the train schedule β in FIG. 12B. 13A shows the calculation result when the power absorption rate w=0.0, and FIG. 13B shows the calculation result when the power absorption rate w=0.8. FIG. 13C shows the calculation result when the power absorption rate w=1.0. FIG. 14A shows a calculation result when the power absorption rate w=0.0, and FIG. 14B shows a calculation result when the power absorption rate w=0.8. FIG. 14C shows the calculation result when the power absorption rate w=1.0.

As described above, even with the same train schedule, it can be seen that when the power absorption rates w of the power storage devices to be set differ, the combinations of operation patterns that minimize the total power consumption differ. This is because a loss occurs when the power storage device is charged with surplus electric energy in which the regenerable electric energy exceeds a power running electric energy at a certain time, and the surplus electric energy is increased at a certain time depending on the degree of this loss. This is because the combination of operation patterns that minimizes the total power consumption, such as whether it is better or smaller, is different. This is because, for example, at a certain time, the surplus power amount changes depending on whether it is better to perform power running, regenerative running (brake), coasting, or a combination of running states of each train.

FIG. 15 is an example of the amount of electric power for traveling when traveling according to a combination of operation patterns that minimizes the total amount of power consumption calculated for each power absorption rate w of the power storage device for each of the two types of train schedules. All are electric power amounts related to the entire train operation. In FIG. 15, for each of the two types of train schedules, the total power consumption by power absorption rate w, the average power consumption per train obtained by dividing this total power consumption by the number of trains, and the regenerative power consumption , And the average regenerative power consumption per train obtained by dividing the regenerative power consumption by the number of trains. The “regenerative invalid power amount” is a loss that occurs when the power storage device is charged with surplus power when the regenerable power amount exceeds the power running power amount. It will be the multiplied value. From FIG. 15, it can be seen that the larger the power absorption rate w, the smaller the total power consumption.

FIG. 16 is an example of the amount of power related to the power storage device when traveling according to a combination of operation patterns that minimizes the total power consumption calculated for each power absorption rate w of the power storage device for each of the two types of train schedules. is there. All are electric power amounts related to the entire train operation. In FIG. 16, for each of the two types of train schedules, the total amount of electric power stored in the electric power storage device and the average amount of electric power stored per train, which is obtained by dividing the total amount of stored electric power by the number of trains, for each electric power absorption rate w. And the maximum charging power amount are shown. The maximum charging power amount is the maximum value of the charging power amount at each time. The operation pattern determination device 1 of the present embodiment can calculate the electric energy (also referred to as an evaluation value) as shown in FIGS. 15 and 16.

[Effect]
As described above, according to the present embodiment, it is possible to determine the operation pattern of each train so as to minimize the total power consumption of the entire train operation while complying with the travel time determined by the train schedule. .. Further, the operation pattern can be determined in consideration of the energy loss of the power storage device that stores the regenerated power. Specifically, for each station, a plurality of driving pattern candidates are set so that the train travels at the running time determined by the train schedule, and one of the plurality of driving pattern candidates set between the stations for each train is set. A combination to which the total power consumption amount obtained by summing the balance of the power running power amount and the regenerative power amount by each running train at each time point through the train schedule satisfies the minimum condition is calculated.

Note that the applicable embodiments of the present invention are not limited to the above-described embodiments, and it goes without saying that appropriate modifications can be made without departing from the spirit of the present invention.

1 Operation Pattern Determining Device 102 Input Unit, 104 Display Unit, 106 Communication Unit 200 Processing Unit 202 Operation Pattern Candidate Setting Unit, 204 Predicted Power Amount Setting Unit 206 Power Absorption Rate Setting Unit, 208 Combination Calculation Unit 210 Electric Energy Evaluation Value Calculation Unit , 212 power storage device evaluation value calculation unit 300 storage unit 302 operation pattern determination program 304 track data, 306 train schedule data, 308 vehicle operation data 310 vehicle performance data, 311, auxiliary equipment power data, 312 OD data 314 power absorption rate data 316 Operation pattern candidate/predicted electric energy data 320 Operation pattern combination data 322 Electric energy evaluation value data 324 Electric power storage device evaluation value data

Claims (6)

The computer, each part streak separated each train line, by determining the operation pattern during a given operational vehicle assigned travels, to determine the operation pattern of each portion streak of a given train schedule Is a program for
Driving pattern candidate setting means for setting a plurality of driving pattern candidates in which the assigned operation vehicle travels for each of the partial stripes,
For each of the operation pattern candidate, operational vehicle assigned, corresponding parts streak, sets the predicted amount of electric power including at least a running power amount and regenerative electric force per time in the case of running in accordance with the operating pattern candidate prediction Electric energy setting means,
Power absorption rate setting means for setting a plurality of power absorption rates of the power storage device provided in the feeder circuit,
It is a combination in which each of the partial lines of the train schedule is selected from a plurality of operation pattern candidates set in the partial schedule, and the corresponding predicted power amount is applied to the traveling time on the train schedule. The power absorption rate set by the power absorption rate setting means is a combination in which the total power consumption of the estimated power consumption of the running train in each time section meets the predetermined minimum condition through the train schedule. Calculation means to calculate separately ,
It makes the computer function as,
The calculating means stores the surplus power amount in the time section in the power storage device based on the power absorption rate when the total regenerable power amount exceeds the total power running power amount, and the power running is performed in the time section. Of the amount of power shortage when the total amount of power exceeds the total amount of regenerable power, the amount of power that is equal to or less than the amount of power stored in the power storage device at the time of the time section is to be supplied from the power storage device. By calculating the balance in each time section, a combination of total power consumption satisfying the minimum condition is calculated for each power absorption rate set by the power absorption rate setting means.
program. The predicted power amount setting means sets the predicted power amount for each of the driving pattern candidates by further adding a given passenger amount for each partial stripe.
The program according to claim 1, which causes the computer to function. The predicted power amount setting means sets the predicted power amount for each of the operation pattern candidates by further considering the given auxiliary power of the assigned operation vehicle.
The program according to claim 1 or 2 for causing the computer to function. For the combination satisfying the minimum condition, at least the balance in each time section, the power running power amount, the regenerable power amount, the regenerative power amount actually used in the time section of the regenerable power amount, and, Evaluation value calculation means for calculating total power consumption in the entire train schedule by subtotaling for each regenerative power consumption,
The program according to any one of claims 1 to 3, which further functions as the computer. For each combination satisfying the minimum condition calculated by the power absorption rate set by the power absorption rate setting means, a power storage device evaluation value calculation means for calculating the total stored power amount of the power storage device,
The program according to any one of claims 1 to 4, which further functions as the computer. Each portion streak separated each train line, that given operational vehicle assigned to determine the operation pattern when traveling, determining operation pattern which determines the operation pattern of each portion streak of a given train schedule A device,
For each of the partial stripes, a driving pattern candidate setting means for setting a plurality of driving pattern candidates in which the assigned operation vehicle travels ,
For each of the operation pattern candidate, operational vehicle assigned, corresponding parts streak, sets the predicted amount of electric power including at least a running power amount and regenerative electric force per time in the case of running in accordance with the operating pattern candidate prediction Electric energy setting means,
Power absorption rate setting means for setting a plurality of power absorption rates of the power storage device provided in the feeder circuit,
It is a combination in which each of the partial lines of the train schedule is selected from a plurality of operation pattern candidates set in the partial schedule, and the corresponding predicted power amount is applied to the traveling time on the train schedule. The power absorption rate set by the power absorption rate setting means is a combination in which the total power consumption of the estimated power consumption of the running train in each time section meets the predetermined minimum condition through the train schedule. Calculation means for calculating separately ,
Equipped with
The calculating means stores the surplus power amount in the time section in the power storage device based on the power absorption rate when the total regenerable power amount exceeds the total power running power amount, and the power running is performed in the time section. Of the amount of power shortage when the total amount of power exceeds the total amount of regenerable power, the amount of power that is equal to or less than the amount of power stored in the power storage device at the time of the time section is to be supplied from the power storage device. By calculating the balance in each time section, a combination of total power consumption satisfying the minimum condition is calculated for each power absorption rate set by the power absorption rate setting means.
Driving pattern determination device.

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