Charging Schedule Creation Device and Charging Schedule Creation Method

Abstract

To provide a charging schedule creating device and a charging schedule creating method for obtaining a charging plan that is optimal for a switcher-equipped charging facility according to a situation change.SOLUTION: A consumer facility is provided with a power reception facility for interconnection with a system, and performs charging / discharging by transmitting power required for charging, to at least one charging facility, and by respectively connecting electric cars to a plurality of charging ports of the charging facility. In the consumer facility, a charging schedule creating device 300 includes an acquisition unit 301 that acquires information about the charging facility, information about the plurality of electric cars, and information about an electricity rate, and an optimization unit 302 that creates a time-based charging plan of each of the electric cars by conducting, on the basis of the information acquired by the acquisition unit 301, an optimization calculation using linear programming from a constraint condition satisfying specifications of a switcher by using at least one of the electricity rate, a time required for charging, and a reception power peak as an objective function.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present application relates to a charging schedule creation device and a charging schedule creation method.

Background Art

[0002] In a charging facility equipped with a switcher that assigns charging targets to a plurality of charging ports, when there is a limit on the number of ports that can be charged simultaneously, a technique for changing the charging order in consideration of the charging length according to the remaining capacity of the battery is disclosed (see, for example, Patent Document 1).

[0003] Also, a charge-discharge control device is disclosed that solves an optimization problem based on constraint conditions such as the usage schedule of a vehicle to create a charge-discharge plan for the vehicle, and enables efficient charge-discharge control even when the number of charge-discharge devices is less than the number of vehicles (see, for example, Patent Document 2).

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, since the technology described in Patent Document 1 does not solve the optimization problem, it is impossible to minimize the electricity cost, etc., and in some cases, there is a problem that the electricity cost soars significantly. On the other hand, in the technology of Patent Document 2, an integer programming method that requires a huge amount of calculation time, such as GA (Genetic Algorithm), must be solved. Different from a simple switching device, when a switcher is provided, it is difficult to re-set the schedule corresponding to the change in the situation.

[0006] The present application discloses a technology for solving the above problems, and aims to obtain a charging schedule creation device that can obtain an optimal charging plan according to the change in the situation for a charging facility equipped with a switcher.

Means for Solving the Problems

[0007] The charging schedule creation device disclosed in the present application is a device that creates a charging schedule for a charging facility having a plurality of charging ports for charging a plurality of electric vehicles and a switcher for allocating the supply power to the plurality of charging ports, and includes an acquisition unit that acquires information on the charging facility, information on each of the plurality of electric vehicles, and information on the electricity cost, and based on the information acquired by the acquisition unit, performs an optimization calculation by linear programming from the constraint conditions that satisfy the specifications of the switcher with at least any one of the electricity cost, the time required for charging, and the received power peak as an objective function, and creates a charging plan along the time for each of the plurality of electric vehicles. Furthermore, based on the information acquired by the acquisition unit, the optimization unit creates a primary plan with a coarser time interval than the charging plan through optimization calculation without the constraint conditions, executes the optimization calculation based on the rule regarding the allocation and the primary plan, and creates the charging plan. It is characterized by this.

[0008] The charging schedule creation method disclosed in the present application is a method for creating a charging schedule for a charging facility having a plurality of charging ports for charging a plurality of electric vehicles and a switcher for allocating supply power to the plurality of charging ports. The method includes: an optimization step of performing an optimization calculation by linear programming using, as an objective function, at least one of the electricity charge, the time required for charging, and the peak power reception, based on information on the charging facility, information on each of the plurality of electric vehicles, and information on electricity charges, and creating a primary plan with a coarser time interval than the charging plan for each of the plurality of electric vehicles over time; and a re-optimization step of performing an optimization calculation by linear programming from constraint conditions that satisfy the specifications of the switcher using, as an objective function, at least one of the electricity charge, the time required for charging, and the peak power reception, based on the rules regarding the allocation and the primary plan, and creating the charging plan.

Advantages of the Invention

[0009] According to the charging schedule creation device or the charging schedule creation method disclosed in the present application, a plan can be created in a short calculation time, so that an optimal charging plan corresponding to a change in the situation can be obtained.

Brief Description of the Drawings

[0010]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

Figure 15

Figure 16

Embodiments for Carrying Out the Invention

[0011] Embodiment 1. Figures 1 to 13 are for explaining the configuration and operation of the charging schedule creation device and the charging schedule creation method according to Embodiment 1. Figure 1 is a block diagram showing the installation situation in a customer facility for explaining the configuration of the charging schedule creation device and the charging facility to be the object of creating the charging schedule. Figure 2 is a block diagram for explaining the software configuration of the charging schedule creation device. Figure 3 is a flowchart for explaining the operation of the charging schedule creation device, that is, the charging schedule creation method.

[0012] And, Figures 4, 5, and 6 are diagrams in tabular form showing data examples of EV information, charging facility information, and schedule information used for creating the charging plan, respectively. Figure 7 is a diagram in bar graph form showing a data example of the charge menu information used for creating the charging plan. And, Figure 8 is a diagram in tabular form showing a data example of the long-term charging plan. And Figure 9 is a diagram showing the charging time for each vehicle in the charging facility.

[0013] Figure 10 is a diagram in tabular form showing an assignment example of the short-term charging plan. Figure 11 is a diagram showing an example of the assignment rule used for creating the charging plan. Figure 12 is a diagram in tabular form showing an example of the short-term charging plan. Further, Figure 13 is a block diagram showing a configuration example of the hardware of the charging schedule creation device.

[0014] As shown in Figure 1, the charging schedule creation device 300 according to Embodiment 1 is a device that creates a charging schedule for a charging facility 200 having a switcher 201 that assigns charging targets to a plurality of charging ports 220. The charging schedule creation device 300 is connected to the charging facility 200 via a communication line 310. Note that, in this embodiment, the charging schedule creation device 300 is treated as a separate body from the charging facility 200, but the charging schedule creation device 300 may be provided as a part of the charging facility 200.

[0015] The consumer facility 100 where the charging device 200 is to be installed is provided with a power receiving device 103 for connecting to the power grid 400 via an electric wire 104, and transmits the power required for charging to at least one charging device 200. By connecting an electric vehicle (EV500) to each of the plurality of charging ports 220 of the charging device 200, charging and discharging can be performed.

[0016] Note that, for the sake of simplicity, the connection target of the charging port 220 is described as the EV500 as a pure electric vehicle (EV), but it is not limited to this. For example, it may be a vehicle equipped with a power generation facility such as a PHEV (Plug In Hybrid Electric Vehicle) or an FCEV (Fuel Cell Electric Vehicle), or other types of devices having a power storage capacity such as a stationary battery. Further, the consumer facility 100 is assumed to include a parking lot, a bus distribution center where EV buses come and go, a truck distribution center where EV trucks come and go, etc., but it is not limited thereto.

[0017] The charging device 200 has a plurality of charging ports 220, and the switcher 201 is used to allocate the ports to be charged. In this example, it is assumed that four charging ports 220 are provided, and each is distinguished as port 1, port 2, port 3, and port 4. When the ports are not distinguished, they are described as "charging ports 220", and in the data example (Fig. 6) described later, port 1 is simply indicated by the number "1", port 2 by "2", and so on. Needless to say, the number of ports is not limited to four.

[0018] As shown in FIG. 2, the charging schedule creation device 300 is provided with an acquisition unit 301 that acquires various types of information, and a database 305 (denoted as "DB" in the figure) that stores the information acquired by the acquisition unit 301. Further, based on the constraints of the switcher 201 described later and the acquired information, an optimization unit 302 that creates a long-term charging plan and a short-term charging plan, an allocation unit 303 that creates an allocation of modules in the short-term charging plan, and a command unit 304 that transmits a charging command to the charging facility 200 are provided.

[0019] The information to be acquired includes, for example, EV information D01, charging facility information D02, schedule information D03, fee menu information D04, allocation rule information D05, etc. For example, the current state of charge (SOC) of the EV500 can also be acquired via the charging facility 200. The exchange of information between the charging facility 200 and the EV500 can be performed, for example, via the CHAdeMO standard. The charging facility 200 can acquire the charging command value created by the charging schedule creation device 300 and perform charging of the EV500.

[0020] Based on the above-described configuration, the processing operations from acquiring various types of information to creating a charging plan and transmitting a charging command will be described with reference to the flowchart of FIG. 3.

[0021] In the description of the processing flow, as an example, the long-term charging plan is a plan with a 30-minute cycle and 48 frames 24 hours ahead, and the short-term charging plan is a plan with a 1-minute cycle and 30 frames 30 minutes ahead. However, the length and cycle of the plan are not limited to this.

[0022] In this example, due to the specifications of the switcher 201, it is assumed to have the following constraints (Constraints 1 to 4). For example, simultaneous charging of 50 kW each is possible for Port 1 and Port 3, but simultaneous charging of 50 kW each for Port 1 and Port 2 is not possible.

[0023] Constraint 1: Charging of up to 100 kW is possible at any one of Ports 1 to 4 Constraint 2: It is possible to charge up to 50 kW simultaneously to either one of Port 1 and Port 2, and to either one of Port 3 and Port 4 respectively. Constraint 3: Simultaneous charging of Port 1 and Port 2 is not allowed. Constraint 4: Simultaneous charging of Port 3 and Port 4 is not allowed.

[0024] The start of the processing flow is preferably triggered at the timing when the EV500 arrives, the timing when the EV500 departs, the timing when the schedule information D03 is added / modified / deleted, the timing of a 30-minute cycle, etc. However, without being limited to this, it may be triggered at any timing. In this embodiment, the case of starting at a timing with a 30-minute cycle (2021 / 10 / 01 / 00:00) will be assumed and described. Unless otherwise specified, the timing will hereinafter be expressed in the format of "yyyy / MM / dd / hh:mm".

[0025] When starting at 2021 / 10 / 01 / 00:00, the acquisition unit 301 acquires the EV information D01, the charging facility information D02, the schedule information D03, and the fee menu information D04 (step S1). After acquiring these information, the acquisition unit 301 stores them in the database 305.

[0026] The EV information D01 is, for example, as shown in FIG. 4, from the first column, the ID of the EV500, the maximum charging power [kW], the minimum charging power [kW], the rated capacity [kWh], the charge / discharge efficiency [%], and the current SOC [%]. Each data except the current SOC is input by the user to the charging schedule creation device 300 using an input device such as a keyboard and a mouse. Regarding the current SOC, if the target EV500 is at the customer facility 100, the SOC obtained via the charging facility 200 is input, and otherwise it is set to n / a.

[0027] The charging facility information D02 is, for example, as shown in Fig. 5, the ID of the charging facility 200, the maximum charging power [kW], the minimum charging power [kW], the charge-discharge efficiency [%], and the number of modules from the first column. Each piece of data is input by the user into the charging schedule creation device 300 using an input device such as a keyboard or mouse. In the case of this example, since there are two modules with a maximum charging power of 50 kW, the port to which one module is assigned can charge up to a maximum of 50 kW, and the port to which two modules are assigned can charge up to a maximum of 100 kW.

[0028] The schedule information D03 is, for example, as shown in Fig. 6, from the first column, the ID of the EV500, the arrival time, the departure time, the SOC [%] at arrival, the SOC [%] at departure, the assigned charging facility ID (the ID of the charging facility to be connected), and the assigned port number (the port number to be connected). Each piece of data is input by the user into the charging schedule creation device 300 using an input device such as a keyboard or mouse. Note that the SOC at arrival is the value estimated by the user, and the SOC at departure is the value desired by the user (the SOC required for the use of the EV).

[0029] The charge menu information D04 is, for example, as shown in Fig. 7, with the horizontal axis being the time (the notation here is mm:dd) and the vertical axis being the charge unit price [yen / kW], and is input into the charging schedule creation device 300 using an input device such as a keyboard or mouse. The horizontal axis is in 30-minute increments, and the vertical axis is the charge unit price corresponding to the power consumption during that 30-minute period.

[0030] When the acquisition of information is completed, the optimization unit 302 executes an optimization calculation using the linear programming method (step S2). In the optimization calculation process (step S2), a long-term charging plan (primary plan) in units of date and time is created and output for each EV500, and is stored in the database 305.

[0031] The long-term charging plan, as shown in Fig. 8 for example, consists of, from the first column, the EV ID, the planned time, the charging power [kW], the SOC [kWh], the assigned time for two modules [minutes], and the assigned time for one module [minutes]. Note that the charging power, the assigned time for two modules, and the assigned time for one module are the values for 30 minutes starting from the planned time. For example, if the planned time is 2021 / 10 / 01 / 00:00, the values from 2021 / 10 / 01 / 00:00 to 2021 / 10 / 01 / 00:30 will be used.

[0032] As a point to note, at this stage, the charging power does not yet meet the specifications of the switch 201. For example, as shown in Fig. 8, a plan may be output where all of EV1 to EV4 charge simultaneously at 2021 / 10 / 01 / 00:00. The charging plan that meets the specifications of the switch 201 will be carried out in the subsequent allocation calculation process (step S3).

[0033] The charging plan is calculated by solving an optimization problem consisting of the following objective function and constraint conditions. In the equations, t is the time index (t = 1, …, 48), i is the index for identifying the EV (i = 1, 2, 3, 4), and j is the index for identifying the charging facility 200 (in this embodiment, j = 1 only). In the text, the EV500 with index i is denoted as Evi, and the charging facility 200 with index j is denoted as charging facility j.

[0034] First, the objective function will be explained. If the objective function is a plan to perform high-speed charging that minimizes the electricity cost, for example, it can be expressed as in Equation (1).

[0035]

Equation

[0036] In formula (1), Buy(t) that constitutes the first term is the received power [kW] of the power receiving facility 103 at time t, and Rate(t) is the unit price of electricity [yen / kWh] at time t. Charge(t, i) that constitutes the second term is the charging power [kW] of the EVi at time t, and DisCharge(t, i) is the discharging power [kW] of the EVi at time t. The peak in the third term is the peak value of the received power [kW], and W1, W2, and W3 are the weights for each term.

[0037] The first term in formula (1) represents the electricity charge up to 24 hours ahead. The second term functions to create a plan to charge as early as possible when there is spare charging time. The third term functions to minimize the peak of the received power. Note that the weights W1, W2, and W3 may be appropriately changed depending on which of the first to third terms is emphasized.

[0038] Next, the constraint conditions will be described. First, the received power of the power receiving facility 103 is calculated by formula (2).

[0039]

Equation

[0040] Since peak in the objective function is the peak of the received power, it is necessary to satisfy the constraint shown in formula (3). Buy(t) ≦ peak (3)

[0041] Also, the constraint equations regarding the SOC of EV500 are expressed, for example, as in formulas (4) to (7).

[0042]

Equation

[0043] Here, SOC(t, i) is the SOC [kWh] at time t in EVi, ε(i) is the charge-discharge efficiency [%] of EVi, and η(j) is the charge-discharge efficiency [%] of charging facility j. Note that the connection relationship between EVi and charging facility j at time t is associated with the assigned charging facility ID in the schedule information D03, and the same applies hereinafter.

[0044] Also, in(i) and out(i) are the arrival time and departure time of EVi, respectively. When the arrival time or departure time is not in 30-minute intervals, corrections are made such as rounding down the departure time and rounding up the arrival time to make them in 30-minute intervals, but it is not limited to this. SOCMax(i) is the rated capacity [kWh] of EVi. SOCin(i) and SOCout(i) are the SOC at arrival and departure of EVi, respectively [%]. SOCnow(i) is the current SOC [%] of EVi. At the current time, when it is n / a, that is, when not arrived, SOCin(i) is used as a substitute, and in other cases where it has arrived, the corresponding value is used.

[0045] Also, the constraint expressions that satisfy the upper and lower limits of the charging power and the specifications of switch 201 are represented by, for example, equations (9) to (14).

[0046]

Equation

[0047] Here, EVMax(i) and ChargeMax(j) are the maximum charging powers [kW] of EVi and charging facility j, respectively. Similarly, EVMin(i) and ChargeMin(j) are the minimum charging powers [kW] of EVi and charging facility j, respectively. The maximum charging power and the minimum charging power are adjusted according to the bottleneck of both.

[0048] Also, SingleP(t, i) and SingleM(t, i) are the time [minutes] to allocate one 50kW module to EVi at time t, where the former is for charging and the latter is for discharging. Also, DoubleP(t, i) and DoubleM(t, i) are the time [minutes] to allocate two 50kW modules to EVi at time t, where the former is for charging and the latter is for discharging. Module(j) is the number of modules, which is 2 in this embodiment.

[0049] For example, if SingleP(1, 1)=20, DoubleP(1, 1)=10, DoubleP(1, 3)=10, and the rest are 0 as the solution, it means that at t = 1, EV1 is charged at a maximum of 100kW for 20 minutes, and for the remaining 10 minutes, EV1 and EV3 are each charged at a maximum of 50kW.

[0050] The last two constraint equations (Equations (13) and (14)) will be explained using the example in Figure 9. In Figure 9, the filled part is the time to allocate two modules, and the vertical and horizontal stripes are the times to allocate one module each. The sum of the filled part times represents the first term, and the sum of the vertical stripe times needs to be within the remaining time, and the same applies to the sum of the horizontal stripe times.

[0051] However, the sum of the vertical and horizontal stripes may overlap (the second term). In this case, from 00:16 to 00:18, EV1 and EV3 are charging simultaneously, from 00:18 to 00:23, EV2 and EV3 are charging simultaneously, and after that, EV2 and EV4 are charging simultaneously.

[0052] Next, the allocation calculation process (step S3) is performed by the allocation unit 303. The allocation calculation is repeated 30 times according to the number of frames per minute in the case of a 30-frame cycle at 1-minute intervals 30 minutes ahead, but the number of repetitions is changed according to the number of frames. In each repetition, based on the long-term charging plan's two-module allocation time, one-module allocation time, and the allocation rules, the allocation of the short-term charging plan is created and saved in the database 305.

[0053] First, an example of allocation in a short-term charging plan is shown in Fig. 10. The first column represents each time at a 1-minute interval for 30 frames 30 minutes ahead, and the second to fifth columns represent the number of modules to be allocated for each ID of EV500. Also, examples of allocation rules (Rule 1 to Rule 4) are shown in Fig. 11. Here, first, focusing on the first iteration (from 2021 / 10 / 01 / 00:00 to 2021 / 10 / 01 / 00:01), the allocation process will be explained.

[0054] From Rule 1, first, the allocation time (1 minute) for 2 modules of EV2 is allocated first, and then the allocation times for 1 module of EV1 to EV4 (13.12 minutes, 15 minutes, 9.82 minutes, and 18.52 minutes respectively) are allocated. Next, from Rule 2, the allocations of EV1 and EV3 are prioritized respectively. And since EV500 does not depart or arrive midway as in Rule 3 and Rule 4, as shown in Fig. 10, 1 is allocated as the number of modules to EV1 and EV3, and 0 is allocated to EV2 and EV4.

[0055] And each time an allocation is made, the allocation time is subtracted. In this case, the allocation time for 1 module of EV1 in the long-term charging plan (Fig. 8) becomes 12.12 minutes from 13.12 minutes, and the allocation time for 1 module of EV3 becomes 8.82 minutes from 9.82 minutes. This allocation result is the same until 2021 / 10 / 01 / 00:09. However, in the process at this time, the allocation time for 1 module of EV3 is less than 0. Therefore, from this point on, 1 module will be allocated to EV4 instead of EV3.

[0056] Similarly, at 2021 / 10 / 01 / 00:09, since the allocation time for 1 module of EV1 is less than 0, from this point on, 1 module will be allocated to EV2 instead of EV1. At 2021 / 10 / 01 / 00:29, since the allocation times for 1 module of EV1 to EV4 are less than 0, according to the first rule, the allocation time for 2 modules of EV1 will be allocated.

[0057] When the allocation calculation process (step S3) is completed, the optimization unit 302 performs an optimization recalculation process (step S4) using linear programming. In the optimization recalculation process (step S4), a short-term charging plan (final plan) in time units obtained by subdividing the long-term charging plan is output and stored in the database 305. The short-term charging plan is, for example, as shown in FIG. 12, from the first column, the ID of the EV500, the planned time, the charging power [kW], and the SOC [kWh].

[0058] The short-term charging plan is created by an optimization calculation using linear programming, similar to the long-term charging plan. However, the main difference is that the cycle of the planned time is 1 minute, and considering the allocation of the short-term charging plan, the charging plan at each planned time satisfies the specifications of the switch 201. Examples of the objective function and constraint conditions are described below. In the following formulas, t is the time index (t = 1,..., 30), and other characters are the same as in the optimization calculation process (step S2). First, the objective function is shown as, for example, formula (15).

[0059]

Number

[0060] And the constraint conditions are, for example, as shown in formulas (16) to (24).

[0061]

Number

[0062] Here, Alloc (formulas (22) and (23)) is the number of modules allocated at time t and EVi, and is obtained from the output in the allocation calculation process (step S3). Also, nextPlan (formula (24)) is the cycle in the next long-term charging plan visited up to 30 minutes later. For example, when the current time is 00:10, nextPlan is 00:30. The SOC in the long-term charging plan at that time is SOCPlan, and thus the short-term charging plan can be adjusted to the long-term charging plan.

[0063] When the charging plan is created in this way, the command unit 304 performs the plan output process (step S5). In the command unit 304, among the short-term charging plans, the charging plan values including the current time are output to the charging facility 200. For example, the command values from 2021 / 10 / 01 / 00:00 to 2021 / 10 / 01 / 00:01 are that EV1 is 50 kW, EV2 is 0 kW, EV3 is 50 kW, and EV4 is 0 kW.

[0064] By providing the charging schedule creation device 300 as described above, it is possible to perform optimal charging such as minimizing the electricity cost while satisfying the specifications of the switch 201. Generally, when creating an optimal charging plan, since the specifications of the switch 201 are modeled as discrete variables, it is necessary to solve the integer programming method using a GA (Genetic Algorithm) or the like. However, this requires a huge amount of computing resources, and it is difficult to create a plan with a one-minute cycle when the number of EV500s is large.

[0065] On the other hand, in the charging schedule creation device 300 of the present application, since the optimization unit 302 performs optimization calculations using the linear programming method, it does not require a huge amount of computing resources even when the specifications of the switch 201 are used as conditions. Therefore, even when there is a sudden change in the EV schedule or an unexpected deviation occurs, the calculation time is shorter than that of the integer programming method, so the plan can be corrected in a timely manner. Therefore, it is possible to recreate the charging plan so as to satisfy the specifications of the switch 201 by the allocation calculation in the allocation unit 303.

[0066] In addition, in the first embodiment and subsequent embodiments, the charging schedule creation device 300 can be realized by hardware such as a PC. That is, it may be configured by operating software on the hardware.

[0067] In that case, as shown in FIG. 13, it is also conceivable to configure with a single microcomputer 3000 including a processor 3001 and a storage device 3002. Although not shown, the storage device 3002 includes a volatile storage device such as a random access memory and a non-volatile auxiliary storage device such as a flash memory. Further, an auxiliary storage device of a hard disk may be provided instead of the flash memory. The processor 3001 executes a program input from the storage device 3002. In this case, the program is input from the auxiliary storage device to the processor 3001 via the volatile storage device. Further, the processor 3001 may output data such as calculation results to the volatile storage device of the storage device 3002, or may store the data in the auxiliary storage device via the volatile storage device.

[0068] Embodiment 2. In the above Embodiment 1, an example of creating a charging plan for a charging facility with a limitation on the combination of ports that can be charged simultaneously for four charging ports was described. In this Embodiment 2, an example of creating a charging plan for a charging facility in which the allocation of modules for each charging port can be changed will be described.

[0069] FIGS. 14 to 16 are for explaining the configuration and operation of the charging schedule creation device according to Embodiment 2. FIG. 14 is a block diagram for explaining the configuration of a charging facility that is the target of creating a charging plan, FIG. 15 is a table-form diagram showing an example of a long-term charging plan created by the schedule creation device as a charging plan, and FIG. 16 is a diagram showing an example of an allocation rule used for creating a charging plan. Note that the basic configuration and main operations of the charging schedule creation device are the same as those in Embodiment 1, and the description of the same parts is omitted, and FIGS. 1 to 3 used in Embodiment 1 are incorporated.

[0070] In Embodiment 1, as the charging facility 200, it was assumed that there were four ports, and there were restrictions such that either a maximum of 50 kW charging could be performed simultaneously on two ports or a maximum of 100 kW charging could be performed on one port.

[0071] On the other hand, among the charging facilities 200, as shown in FIG. 14, there may be a case where there are N (an arbitrary integer) modules 200m responsible for the maximum charging power (ChargeMax(j)) (described as modules 1 to module N similar to the port numbers). Furthermore, there are also those with M (an arbitrary integer) charging ports 220 (ports 1 to port M), and the assignment of the module 200m to each charging port can be arbitrarily changed.

[0072] In such a charging facility 200, each module 200m outputs within a range not exceeding ChargeMax(j) [kW], and charging is performed in a form where the outputs connected to the same port are totaled. For example, assuming ChargeMax(j) = 50, N = 3, and M = 2, and a situation where two modules 200m are connected to port 1 and one module 200m is connected to port 1, port 1 can output a maximum of 100 kW, and port 2 can output a maximum of 50 kW.

[0073] The charging schedule creation device 300 according to the second embodiment will be described with respect to the case of creating a charging plan for such a charging facility 200. Note that the description will be made for the case where the number of ports (M) in the charging facility 200 is 4 and the number of modules is 3 (N).

[0074] In the charging schedule creation device 300 according to the second embodiment, in the optimization calculation process (step S3) executed by the optimization unit 302, the expressions (11) and (12) described in the first embodiment are respectively replaced with expressions (25) and (26). Furthermore, expressions (13) and (14) are replaced with expression (27) to create a long-term charging plan. The other parts are the same as those in the first embodiment.

[0075]

Number

[0076] Here, x is a vector representing the assignment of module 200m to the charging port 220. The number of elements is the number of modules, and the value of each element points to the port number. However, when the value of an element is 0, it indicates that it is not assigned to any port. For example, when x = {1, 4, 0}, since the first element is 1, module 1 is assigned to port 1; since the second element is 4, module 2 is assigned to port 4; and since the third element is 0, module 3 is not assigned to any port.

[0077] X is a set consisting of all elements of possible patterns of x. When the number of modules is N and the number of ports is M, it will contain (M + 1) to the power of N elements. In the second embodiment, since it is (4 + 1) to the power of 3, it will contain 125 elements. Count(x, i) is a function that counts the number of i in x. For example, when x = {1, 4, 1} and i = 1, since there are 2 ones in x, Count(x, i) = 2.

[0078] TimeP(t, x) is a variable indicating the length of the charging time (in minutes) at time t with the assignment pattern x. For example, when x = {1, 4, 0} and TimeP(t, x) is 10, it means that at time t, module 1 is assigned to port 1, module 2 is assigned to port 4, and module 3 has no assignment simultaneously for 10 minutes. TimeM(t, x) represents a similar meaning for discharging.

[0079] The long-term charging plan to be created, as shown in FIG. 15 for example, manages the module assignment time for each number from the 5th column to the 7th column because the maximum number of modules is 3. The calculation of the module assignment time for each number is to sum up TimeP(t, x) for all patterns of x where Count(x, i) is the number of the module concerned with respect to the solution obtained from the optimization.

[0080] For example, when calculating the allocation time for two modules of EV1, all the patterns of x for which Count(x, 1) = 2 are {1, 1, 0}, {1, 1, 2}, {1, 1, 3}, {1, 1, 4}, {1, 0, 1}, {1, 2, 1}, {1, 3, 1}, {1, 4, 1}, {0, 1, 1}, {2, 1, 1}, {3, 1, 1}, {4, 1, 1}, a total of 12 patterns. Calculate TimeP(t, x) for each pattern of x and sum them up.

[0081] In the allocation calculation process (step S3) executed by the allocation unit 303, it is performed based on the example of the allocation rule shown in FIG. 16. Rule 1 is for preventing chattering caused by modeling errors or measurement errors. However, in the long-term plan shown in FIG. 15, since there is no module allocation time shorter than 1 minute, the process proceeds to Rule 2.

[0082] According to Rule 2, prioritize the module allocation time with a larger number of allocations. However, the modules with the most module allocation time are two for EV1 and EV2. In this case, according to Rule 4, the allocation of EV1 with a smaller EV number is prioritized first. Regarding Rule 3, since the two module allocations of EV2 are ignored because the maximum number of modules is 3, either one of the allocations of one module to EV3 and EV4 becomes a candidate. At this time, according to Rule 4, EV3 is prioritized.

[0083] Therefore, from 2021 / 10 / 01 / 00:00 to 2021 / 10 / 01 / 00:15, two modules of EV1 and one module of EV3 will be allocated. For the remaining 15 minutes from 2021 / 10 / 01 / 00:15 to 2021 / 10 / 01 / 00:30, two modules of EV2 and one module of EV4 will be allocated.

[0084] The subsequent processing is the same as that in Embodiment 1. As a result, in addition to the effects described in Embodiment 1, the number of modules and the number of ports of the charging facility 200 can be made variable, and cooperation with charging facilities 200 with a wider range of specifications can be achieved.

[0085] Note that although various exemplary embodiments and examples are described in this application, the various features, aspects, and functions described in one or more of the embodiments are not limited to the application of a specific embodiment, but are applicable to the embodiments alone or in various combinations. Therefore, countless variations not illustrated are envisioned within the scope of the technology disclosed in this application specification. For example, it includes cases where at least one component is modified, added, or omitted, and further, cases where at least one component is extracted and combined with components of other embodiments.

[0086] For example, for module 200m, it is not necessarily required to have a plurality, and one may also be sufficient. Further, although the long-term charging plan (primary plan) shows an example of creating a charging plan for one charging session, it may also be for multiple sessions, and it does not have to be restricted by the specifications of switch 201. It may be created at a coarser time interval than the final plan.

[0087] As described above, according to the charging schedule creation device 300 of this application, it is a device that creates a charging schedule for a charging facility 200 having a plurality of charging ports 220 for charging a plurality of electric vehicles (EV500) and a switch 201 that allocates supply power to the plurality of charging ports 220. The device includes an acquisition unit 301 that acquires information regarding the charging facility 200 (charging facility information D02), information regarding each of the plurality of electric vehicles (EV500) (EV information D01, schedule information D03), and information regarding electricity charges (tariff menu information D04). And based on the information acquired by the acquisition unit 301, an optimization calculation is performed by linear programming from the constraint conditions that satisfy the specifications of the switch 201 with at least any one of the electricity charge, the time required for charging, and the received power peak as the objective function, and an optimization unit 302 that creates a charging plan along with time for each of the plurality of electric vehicles (EV500). Thereby, even considering the constraint conditions of the switch 201, a plan can be created in a short calculation time, so that an optimal charging plan corresponding to a change in the situation can be obtained.

[0088] In particular, based on the information acquired by the acquisition unit 301, the optimization unit 302 creates a primary plan with a coarser time interval than the charging plan through optimization calculation without constraint conditions, and based on the rule regarding allocation (allocation rule information D05) and the primary plan, executes optimization calculation to create a charging plan. Therefore, the calculation time can be further shortened.

[0089] The charging plan creation target is a facility among the charging facilities 200 that has a plurality of modules 200m that output power, and the switcher 201 allocates one or more of the plurality of modules 200m to the charging port 220 to be charged among the plurality of charging ports 220 for allocation. It is equipped with an allocation unit 303 that performs allocation calculation for allocation by iterative calculation that subdivides the time in the primary plan based on the rule regarding allocation (allocation rule information D05). Since the optimization unit 302 executes optimization calculation based on the result of the allocation calculation and the primary plan, the calculation time can be further shortened.

[0090] If the optimization unit 302 creates a charging plan by prioritizing charging of electric vehicles (EV500) with earlier departure times among the plurality of electric vehicles, a charging plan closer to the actual situation can be created.

[0091] Also, according to the charging schedule creation method of the present application, it is a method for creating a charging schedule for a charging facility 200 having a plurality of charging ports 220 for charging a plurality of electric vehicles (EV500) and a switcher 201 for allocating supply power to the plurality of charging ports 220. Based on information regarding the charging facility 200 (charging facility information D02), information regarding each of the plurality of electric vehicles (EV500) (EV information D01, schedule information D03), and information regarding electricity charges (tariff menu information D04), an optimization calculation using linear programming is executed with at least one of the electricity charge, the time required for charging, and the power reception peak as an objective function, and an optimization step (step S2) of creating a primary plan with a coarser time interval than the charging plan along the time for each of the plurality of electric vehicles (EV500). Based on the rules regarding allocation (allocation rule information D05) and the primary plan, an optimization calculation using linear programming is executed from the constraint conditions that satisfy the specifications of the switcher 201 with at least one of the electricity charge, the time required for charging, and the power reception peak as an objective function, and a re-optimization step (step S4) of creating a charging plan is included. As a result, even considering the constraint conditions of the switcher 201, a plan can be created in a short calculation time, so that an optimal charging plan corresponding to a change in the situation can be obtained.

[0092] The charging plan creation target is a facility that has a plurality of modules 200m that output power among the charging facilities 200, and the switcher 201 allocates one or more of the plurality of modules 200m to the charging port 220 to be charged among the plurality of charging ports 220. Based on the rules regarding allocation (allocation rule information D05), an allocation step (step S3) of performing an allocation calculation for allocation by iterative calculation that subdivides the time in the primary plan is executed before the re-optimization step (step S4). Therefore, even if the configuration of the module 200m becomes complicated, a charging plan can be created in a short calculation time.

Explanation of Reference Numerals

[0093] 100: Home facility, 200: Charging equipment, 200m: Module, 201: Switcher, 220: Charging port, 300: Charging schedule creation device, 301: Acquisition unit, 302: Optimization unit, 303: Assignment unit, 304: Command unit, 500: EV.

Claims

1. An apparatus for creating a charging schedule for a charging facility having a plurality of charging ports for charging a plurality of electric vehicles and a switch for allocating supply power to the plurality of charging ports, comprising: an acquisition unit that acquires information about the charging facility, information about each of the plurality of electric vehicles, and information about electricity rates; and an optimization unit that, based on the information acquired by the acquisition unit, performs an optimization calculation by linear programming from constraint conditions that satisfy the specifications of the switch, using at least one of the electricity rate, the time required for charging, and the power reception peak as an objective function, and creates a charging plan for each of the plurality of electric vehicles over time, wherein the optimization unit creates a primary plan with a coarser time interval than the charging plan by performing an optimization calculation without the constraint conditions, based on the information acquired by the acquisition unit, and executes the optimization calculation based on the rules regarding the allocation and the primary plan to create the charging plan. A charging schedule creation apparatus characterized by this.

2. The charging plan creation target is a facility that has a plurality of modules for outputting power among the charging facilities, and the switch allocates one or more of the plurality of modules to a charging port to be charged among the plurality of charging ports to perform the allocation, comprising an allocation unit that performs an allocation calculation for the allocation by performing an iterative calculation that subdivides the time in the primary plan based on the rules regarding the allocation, wherein the optimization unit executes the optimization calculation based on the result of the allocation calculation and the primary plan. The charging schedule creation apparatus according to Claim 1, characterized by this.

3. The optimization unit creates the charging plan by prioritizing charging of an electric vehicle with an earlier departure time among the plurality of electric vehicles. The charging schedule creation apparatus according to Claim 1 or 2, characterized by this.

4. A method for creating a charging schedule for a charging facility having a plurality of charging ports for charging a plurality of electric vehicles and a switch for allocating supply power to the plurality of charging ports, comprising: Based on the information about the charging equipment, the information about each of the plurality of electric vehicles, and the information about the electricity rate, perform an optimization calculation by linear programming with at least one of the electricity rate, the time required for charging, and the peak power reception as the objective function, and create a primary plan with a coarser time interval than the charging plan for each of the plurality of electric vehicles over time. An optimization step, Based on the rule regarding the allocation and the primary plan, perform an optimization calculation by linear programming from the constraint conditions that satisfy the specifications of the switcher with at least one of the electricity rate, the time required for charging, and the peak power reception as the objective function, and create the charging plan. A re-optimization step, A charging schedule creation method characterized by including the above.

5. The object of creating the charging plan is among the charging equipment, has a plurality of modules that output power, and by the switcher, for the charging port to be charged among the plurality of charging ports, allocate one or more of the plurality of modules to perform the allocation. Equipment, The charging schedule creation method according to claim 4, further comprising an allocation step of performing an allocation calculation for the allocation by iterative calculation that subdivides the time in the primary plan before the re-optimization step based on the rule regarding the allocation.

Images