JP7176338B2 - Operation plan optimization device - Google Patents

Description

The present invention relates to an operation plan optimization device.

Patent Literature 1 listed below discloses an energy management system capable of achieving more efficient energy management in the entire factory. This energy management system is equipped with a factory energy management system (FEMS) that manages energy for the factory, a production management system that formulates the production plan of the factory, a storage battery system that can supply power to the factory, and a solar power generation system. FEMS predicts the energy load of the factory in cooperation with the production plan of the production management system, predicts the power that can be supplied from the storage battery system and the solar power generation system, and predicts the power that can be supplied based on the information in the production plan. Adjust including peak cut or peak shift to achieve more efficient energy management by leveling the forecasted factory load, including the amount of supply from Output to the production control system.

In this energy management system, as described in paragraphs 0068 to 0070 of Patent Document 1 and FIG. By adjusting the time zone of work (manufacturing work) on the production line, peak cutting and peak shifting of the energy load are realized.

Japanese Patent No. 6114532

By the way, the energy load (power consumption) during operation of the production line (power load equipment) is not necessarily a constant value, and often fluctuates over time. Therefore, the above energy management system is difficult to apply to a factory (facility) including production equipment whose power consumption fluctuates. In particular, when it is applied to a facility having equipment with a relatively large fluctuation range of power consumption, there is a great concern about its effectiveness.

SUMMARY OF THE INVENTION The present invention has been made in view of the circumstances described above, and it is an object of the present invention to realize peak shift of power consumption in a facility having a plurality of facilities whose power consumption fluctuates in time series.

In order to achieve the above object, in the present invention, as a first solution related to the operation plan optimizing device, the power consumption peak of a facility equipped with a plurality of power load facilities and one or a plurality of power storage facilities is minimized. An operation plan optimizing device, comprising an optimization unit that obtains an operation schedule of the power load facility and a charge/discharge schedule of the power storage facility based on predicted power consumption data of the power load facility. do.

In the present invention, as a second solution related to the operation plan optimizing device, in the first solution, the optimization unit obtains both or one of the operation schedule and the charge/discharge schedule, and obtains the obtained A means of repeatedly determining the operation schedule and the discharge schedule by fixing one schedule and determining the other schedule is adopted.

In the present invention, as a third solution to the operation plan optimizing device, in the first or second solution, the optimization unit charges and discharges the power storage equipment so that the number of times of charging and discharging is minimized. Adopt a means of asking for a schedule.

In the present invention, as a fourth solution means related to the operation plan optimization device, in any one of the first to third solution means, when a plurality of the power storage equipment are provided, the number of times of charging and discharging each of the power storage equipment Employs a means of obtaining a charge/discharge schedule so that is equalized.

In the present invention, as a fifth solving means related to the operation plan optimizing device, in any one of the first to fourth solving means, the facility further comprises a distributed power source.

In the present invention, as a sixth solution means related to the operation plan optimization device, in any one of the first to fifth solution means, the facility supplies grid power to the power load equipment and the power storage equipment, adopt the means.

In the present invention, as a seventh solution means related to the operation plan optimizing device, in any one of the first to sixth solution means, the power load equipment is a heat treatment furnace that heats a predetermined object. adopt the means of

ADVANTAGE OF THE INVENTION According to this invention, it is possible to implement|achieve the peak shift of the power consumption of the facility provided with the multiple equipment whose power consumption fluctuates in time series.

BRIEF DESCRIPTION OF THE DRAWINGS It is a schematic diagram which shows the electric power system of the heat processing factory (facility) in 1st Embodiment of this invention. BRIEF DESCRIPTION OF THE DRAWINGS It is a schematic diagram which shows the outline|summary of the electric power load equipment in 1st Embodiment of this invention. 4 is a graph showing changes in power consumption and in-furnace temperature of the heat treatment furnace in the first embodiment of the present invention. 1 is a block diagram showing the functional configuration of a heat treatment factory optimization device according to a first embodiment of the present invention; FIG. 4 is a first flow chart showing the operation of the heat treatment factory optimization device according to the first embodiment of the present invention; 4 is a second flow chart showing the operation of the heat treatment factory optimization device according to the first embodiment of the present invention; FIG. 4 is a characteristic diagram showing predicted values of total power consumption in a heat treatment plant according to the first embodiment of the present invention; FIG. 4 is a characteristic diagram showing predicted values of charge/discharge power and remaining charge of the power storage equipment in the first embodiment of the present invention; It is a Gantt chart which shows the charging/discharging plan of the electrical storage equipment in 1st Embodiment of this invention. FIG. 6 is a schematic diagram showing a power system of a heat treatment factory (facility) according to a second embodiment of the present invention; It is a flowchart which shows operation|movement of the heat processing factory optimization apparatus which concerns on 2nd Embodiment of this invention. It is a Gantt chart which shows the discharge plan of the 1st electrical storage equipment and 2nd electrical storage equipment in 2nd Embodiment of this invention. FIG. 10 is a characteristic diagram showing predicted values of charge/discharge power and remaining charge of the first power storage device in the second embodiment of the present invention; FIG. 10 is a characteristic diagram showing predicted values of charge/discharge power and remaining charge of a second power storage device according to the second embodiment of the present invention;

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[First embodiment]
First, the first embodiment will be described. As shown in FIG. 1, the heat treatment factory optimization apparatus according to the first embodiment is optimized for a heat treatment factory A equipped with a plurality (eight units) of heat treatment furnaces R1 to R8 and one or a plurality of power storage facilities J. there is This heat treatment plant A corresponds to the facilities in the present invention, and the plurality of heat treatment furnaces R1 to R8 correspond to power load facilities in the present invention.

The power storage equipment J constitutes a power supply facility together with the system power supply D, and charges and discharges part of the system power received by the heat treatment plant A from the external system power supply D. This power storage equipment J is, for example, a secondary battery or a flywheel battery. Such power storage equipment J is supplied from the system power source D to the heat treatment plant A by switching the operation mode to the charge mode, the discharge mode, or the stop mode based on the charge/discharge plan created by the heat treatment plant optimization device. or supply the charged power stored by itself to a plurality of heat treatment furnaces R1 to R8.

As shown in FIG. 2, the heat treatment plant A is equipped with a plurality of upstream lines U, a parts storage S, and a plurality of downstream lines L, in addition to the power storage facility J and a plurality of heat treatment furnaces R1 to R8. A plurality of parts X (objects) are concurrently subjected to heat treatment (jobs) using heat treatment furnaces R1 to R8. That is, the heat treatment factory A is interconnected with the system power supply D, and by operating the plurality of heat treatment furnaces R1 to R8 based on the power supplied from the system power supply D through the system interconnection, a plurality of heat treatments ( Job) is a facility for parallel processing.

In such a heat treatment factory A, each upstream line U is a production line that performs predetermined pretreatment (cleaning treatment, etc.) on parts X before heat treatment. It is a part holding facility that temporarily holds the part X that has been placed.

Each of the heat treatment furnaces R1 to R8 is a power load facility operated by power supplied from the system power supply D and/or the power storage facility J, and performs heat treatment on a plurality of parts X. It is a heating and cooling furnace that sequentially receives a predetermined number of parts X from a parts storage S and performs heat treatment under predetermined processing conditions.

In these heat treatment furnaces R1 to R8, for example, as indicated by the dashed line in FIG. 3, the temperature inside the furnace rises from room temperature to the target temperature over a predetermined time (temperature rise time), and then the target temperature rises for a predetermined time (equalization time). heating time), and further decreases to normal temperature over a predetermined time (cooling time). The temperature rise time, soaking time, cooling time, and target temperature are processing conditions for a job (heat treatment) and are set for each component X.

The power consumption of such heat treatment furnaces R1 to R8 changes as indicated by the solid line in FIG. That is, the power consumption of each of the heat treatment furnaces R1 to R8 reaches a maximum value from zero during the temperature rise time, then decreases to maintain a constant value, and further drops to zero during the cooling time. Each of the heat treatment furnaces R1 to R8 repeats the heat treatment in which the furnace temperature and power consumption change in this way for a predetermined number of parts X sequentially received from the parts storage S. Each downstream line L is a production line for subjecting heat-treated parts X received from heat treatment furnaces R1 to R8 to predetermined post-treatments (sorting treatment, etc.).

Each of the heat treatment furnaces R1 to R8 in the heat treatment plant A is a treatment facility that consumes much higher power than the other upstream line U, parts storage S and downstream line L. That is, the plurality of heat treatment furnaces R1 to R8 are treatment facilities that control power consumption in the heat treatment factory.

The heat treatment plant optimizing device can determine the operation schedule of the heat treatment furnaces R1 to R8 that minimizes the peak (maximum value) of the power consumption of the heat treatment plant A, that is, the optimum heat treatment plan, and can minimize the number of charge/discharge cycles. It is a device for obtaining an operation schedule (charging/discharging schedule), that is, an optimum charging/discharging plan, for the power storage equipment J. Such a heat treatment plant optimization device corresponds to the operation plan optimization device according to the present invention, and performs information processing based on a predetermined heat treatment support program (software) to perform a heat treatment plan and a charge/discharge plan. Ask for

More specifically, as shown in FIG. 4, this heat treatment factory optimization apparatus is a kind of computer having a storage unit 1, an operation unit 2, a communication unit 3, a calculation unit 4, and a display unit 5 as functional components. be. Note that, among the functional components of such a support device, the storage unit 1 and the calculation unit 4 constitute an optimization unit in the present invention.

The storage unit 1 comprises an internal storage device such as a ROM (Read Only Memory) and a RAM (Random Access Memory) and an external storage device such as a hard disk and/or a memory card, and includes at least a heat treatment furnace database 1a and a program storage unit 1b. ing.

The heat treatment furnace database 1a is a data table in which a plurality of operating histories of the heat treatment furnaces R1 to R8 are registered. This operation history includes at least power consumption data in past heat treatments performed in the heat treatment furnaces R1 to R8. This power consumption data, as shown in FIG. 3, indicates the temporal change in power consumption required for heat treatment.

The program storage unit 1b is a storage area in which the support program, that is, the program executed by the calculation unit 4 is stored. The program storage unit 1b stores at least a power consumption prediction program and a mathematical programming program as the support programs.

The power consumption prediction program is a support program for generating predicted power consumption data indicating changes in power consumption of heat treatments (jobs) to be executed next in the heat treatment furnaces R1 to R8 based on the heat treatment furnace database 1a. The mathematical programming program solves the power optimization problem using a predetermined algorithm, thereby minimizing the power consumption peak of the heat treatment factory A. It is a support program that asks for a charge and discharge plan for the battery.

The operation unit 2 is an input device that receives operation instructions from an operator who operates the heat treatment factory optimization apparatus, and more specifically, is a pointing device such as a keyboard and a mouse. The operation unit 2 outputs an operation signal corresponding to the operator's operation instruction to the calculation unit 4 . The communication unit 3 is a communication device that transmits and receives data to and from an external device via a predetermined communication line, and communicates with the external device using a communication protocol conforming to LAN (Local Area Network) or the Internet, for example.

The arithmetic unit 4 is an arithmetic unit that obtains the individual predicted power consumption data and the heat treatment plan based on the above-mentioned dedicated program, the heat treatment furnace database 1a, the operation signal, etc. Hardware such as an interface circuit and a CPU (Central Processing Unit) consists of The interface circuit is an electronic circuit that exchanges various signals with the storage unit 1, the operation unit 2, the communication unit 3, and the display unit 5. The CPU is a central processing unit that executes the support program described above.

Moreover, the calculation unit 4 includes at least a prediction unit 4a and an optimization unit 4b as functional components. Based on the heat treatment furnace database 1a and the power consumption prediction program, the prediction unit 4a generates individual predicted power consumption data of the predicted power consumption of each heat treatment (job) in each of the heat treatment furnaces R1 to R8. The optimization unit 4b obtains a heat treatment plan and a charge/discharge plan based on the individual predicted power consumption data and the mathematical programming program stored in the program storage unit 1b.

The calculation unit 4 outputs the heat treatment plan and the charge/discharge plan obtained by itself to the display unit 5 , and the display unit 5 displays the heat treatment plan and the charge/discharge plan input from the calculation unit 4 . This display unit 5 is, for example, a liquid crystal display.

Next, the operation of the heat treatment factory optimization apparatus according to the first embodiment will be described in detail with reference to FIGS. 5 to 8 as well.

First, when obtaining a heat treatment plan for each of the heat treatment furnaces R1 to R8 and a charge/discharge plan for the electrical storage facility J in a predetermined planning period (for example, one week) using this heat treatment factory optimization device, each heat treatment during the above planning period It is necessary to input the contents of the heat treatment for a plurality of parts X performed by the furnaces R1 to R8 as a job (execution unit of heat treatment) to the heat treatment factory optimization device. That is, the heat treatment factory optimizing device receives jobs related to a plurality of parts X to be heat treated in the heat treatment factory A during the planned period as necessary information.

Further, in order to obtain a heat treatment plan and a charge/discharge plan using this heat treatment plant optimization device, in addition to the plurality of jobs described above, the necessary conditions for the execution of each job are constraints for solving the power optimization problem. It is necessary to input to the heat treatment factory optimization device as a condition. These constraints include, for example, the earliest executable time of each job, the delivery date of the part X after heat treatment to the customer, the execution priority of each job, the work schedule of the workers, the maintenance of the heat treatment furnaces R1 to R8 and the storage facility J.・Schedule, the number of heat treatment furnaces R1 to R8 that can be started per unit time, etc.

The operator inputs the above-described plurality of jobs and constraint conditions from the operation unit 2 by operating the operation unit 2 (step S1). When an operation signal relating to each job and constraint is input from the operation unit 2, the calculation unit 4 stores each heat treatment (job) and constraint in the storage unit 1, and then executes the power consumption prediction program. By doing so, individual predicted power consumption data for each heat treatment (job) is generated, and a heat treatment plan and a charge/discharge plan are searched for by solving a power optimization problem including the individual predicted power consumption data and the constraint conditions (step S2 ).

That is, the prediction unit 4a generates individual predicted power consumption data for each heat treatment (job) by searching the heat treatment furnace database 1a for power consumption data similar to each heat treatment (job). In addition, the optimization unit 4b, based on the individual predicted power consumption data and the mathematical programming program, creates a heat treatment plan for each heat treatment furnace R1 to R8, that is, each heat treatment furnace R1 capable of minimizing the total power consumption peak of each heat treatment furnace R1 to R8. ∼R8 operation schedule and charging/discharging schedule of the electrical storage equipment J, that is, a charging/discharging plan capable of minimizing the number of charging/discharging times. And the calculating part 4 outputs and displays the heat processing plan and charging/discharging plan which were acquired in this way to the display part 5 (step S3).

Here, the power optimization problem of the first embodiment will be described in detail. The operation schedule and charge/discharge schedule are updated by solving the power optimization problem after the above-described multiple jobs and constraints are input. However, the update cycle of the charge/discharge plan can be shortened compared to the update cycle of the heat treatment plan, in which the required time for one job is several hours or more. Under such circumstances, the operation plan optimization problem and the charge/discharge plan optimization problem are formulated separately.

Even if the formulas are formulated separately as described above, in the search for the heat treatment plan and the charge/discharge plan (step S2), one schedule is fixed, and the fixed power consumption value or charge/discharge power value is considered. By repeating the determination of the other schedule, the operation schedule and the discharge schedule can be determined repeatedly. That is, the optimization unit 4b first stores, for example, the storage unit J as a stop mode in the storage unit 1, and after considering a fixed charge/discharge power value (0 in this case), solves the operation plan optimization problem. to obtain the heat treatment plan, then store the obtained heat treatment plan in the storage unit 1, consider the fixed power consumption value, and solve the charge/discharge plan optimization problem to obtain the charge/discharge plan. (See FIG. 6).

Details of the formulation and solution of the operation plan optimization problem are described in Japanese Patent Application No. 2017-141248. This Japanese Patent Application No. 2017-141248 is a prior application of the present applicant, and describes a specific formulation and solution of a power optimization problem that can minimize the total power consumption peak for multiple heat treatment furnaces. Therefore, in this specification, detailed description of the formulation and solution of the operation plan optimization problem among the above will be omitted. Note that the heat treatment plan and the charge/discharge plan may be formulated as the same power optimization problem without distinction.

First, the symbols shown in Tables 1 to 5 are used in this charge/discharge plan optimization problem. The symbols in Table 1 are symbols related to the scale of the charge/discharge plan optimization problem, the symbols in Table 2 are symbols related to the grid connection points, the symbols in Table 3 are symbols related to the power storage equipment J, and the symbols in Table 4 are The symbols are for the heat treatment furnaces R1 to R8, and the symbols in Table 5 are for the charge/discharge schedule optimization problem.

By using such symbols, the grid connection point model is represented by the following formula (1), the grid connection point power peak value is represented by the following formula (2), and the model of the power storage equipment J (power storage equipment model) is represented by the following equations (3) to (5).

Using the above symbols, the charge/discharge plan optimization problem is represented by the objective function shown in the following equation (6) and the constraint functions shown in equations (7) to (12).

Here, in this charge/discharge plan optimization problem, when a plurality of power storage facilities J are provided, a charge/discharge schedule is obtained so that the number of charge/discharge times of each power storage facility J is equalized. That is, the charge/discharge plan optimization problem of the first embodiment is formulated including the following conditional expression (13). Note that the symbol “N” in this formula (13) is the number of power storage facilities J, and “n” is the facility number of the power storage facility J.

Further, the objective function f is a target function (first objective function) related to peak power consumption given by the following equation (14) and an objective function (second objective function) relating to the charge/discharge power change rate given by the following equation (15). is the weighted sum of , and is represented by the following equation (16).

Here, in the calculation of the objective function f shown in Equation (16), since Equation (2) includes the max function, which is a non-linear function, there is a non-differentiable point. Under these circumstances, in the power optimization problem, the constraint condition of equation (11) using the auxiliary variable y ^peak is introduced, and the objective function f shown in equation (16) is defined as in equation (17) below. fix.

The optimization unit 4b of the calculation unit 4 solves such a charging/discharging plan optimization problem according to a well-known algorithm such as the interior point method, the sequential quadratic programming method, or the active constraint method, thereby obtaining a charging/discharging schedule for the power storage facility J. A charge/discharge plan is obtained.

FIG. 7 shows predicted values (one example) of the total power consumption of the heat treatment furnaces R1 to R8 (power load equipment) based on the heat treatment plan. The peak power consumption of this total power consumption is 466 kW, which is significantly reduced from the peak power consumption (735 kW) before optimization. Further, FIG. 8 shows predicted values (an example) of charge/discharge power (kW) and charge remaining amount (%) of the power storage equipment J based on the charge/discharge plan. The charge/discharge power and the remaining amount of charge are values that satisfy the upper limit value and the lower limit value indicating the recommended operating range of the power storage equipment J. FIG.

Also, FIG. 9 is a Gantt chart showing a charge/discharge plan when, for example, there are five power storage facilities J (equipment numbers No. 1 to No. 5) and a power optimization problem is solved. This FIG. 9 shows the facility number No. 1 to No. 5 shows that the electrical storage equipment J of 5 repeats charging and discharging evenly.

According to the first embodiment as described above, peak shift of the power consumption of the heat treatment plant A, which is equipped with the power storage equipment J and the plurality of heat treatment furnaces R1 to R8 (power load equipment) whose power consumption fluctuates in time series, is realized. It is possible to obtain a heat treatment plan that can be used, and it is possible to obtain a charge/discharge plan that can minimize the number of charge/discharge cycles of the power storage equipment J.

[Second embodiment]
Next, a second embodiment of the invention will be described with reference to FIGS. 10 to 14. FIG. As shown in FIG. 10, the heat treatment factory optimization apparatus according to the second embodiment is optimized for the heat treatment factory B in which the power storage facility J in the first embodiment is replaced with a first power storage facility J1 and a second power storage facility J2. and Among the first power storage facility J1 and the second power storage facility J2, the first power storage facility J1 is a facility whose cycle life should be taken into consideration when obtaining a charge/discharge plan, and the second power storage facility J2 requires consideration of a cycle life. No facilities.

The heat treatment plant optimization device according to the second embodiment has the same functional configuration as the heat treatment plant optimization device according to the first embodiment, and is shown in FIG. It works according to the flow chart. In addition, in the operation of the heat treatment plant optimization device according to the second embodiment, the biggest difference from the operation of the heat treatment plant optimization device according to the first embodiment is step S2a.

That is, when obtaining a heat treatment plan and a charge/discharge plan with the heat treatment factory optimization apparatus according to the second embodiment, the operator sets a plurality of jobs and constraint conditions (step S1a), and furthermore, the charge/discharge plan A first power storage facility J1 and a second power storage facility J2 are designated from among power storage facilities, ie, a plurality of power storage facilities (step S2a). The calculation unit 4 searches for the heat treatment plan and the charge/discharge plan based on each job, the constraint conditions, and the setting information of the first power storage equipment J1 (step S3a), and displays the heat treatment plan and the charge/discharge plan, which are the search results, on the display unit. 5 (step S4a).

Here, in step S2a, the following three conditions are considered in setting the first power storage equipment J1.
(1) Accumulated value of charge/discharge times < Threshold for charge/discharge times (2) Capacity decrease rate for initial capacity < Capacity decrease rate threshold (3) Output decrease rate for initial output < Output decrease rate threshold Above charging The threshold for the number of times of discharge, the threshold for capacity decrease rate, and the threshold for output decrease rate are appropriately set by the operator, and are, for example, 80%.

For example, the operation data of each power storage equipment, that is, the number of times of charge/discharge, the capacity and the output of the first power storage equipment J1 and the second power storage equipment J2 are taken into the heat treatment factory optimization device and sequentially stored, and the charge/discharge frequency threshold , the capacity decrease rate threshold value and the output decrease rate threshold value are stored in advance in the heat treatment plant optimizing device, so that step S2a can be automated.

The calculation unit 4 compares the charge/discharge frequency, capacity and output of the first power storage equipment J1 and the second power storage equipment J2 with the charge/discharge frequency threshold, the capacity decrease rate threshold and the output decrease rate threshold, respectively. , the power storage equipment that satisfies the above conditions is determined. Then, the calculation unit 4 causes the display unit 5 to display power storage equipment that satisfies the above conditions.

In such a second embodiment, as in the first embodiment, even if the operation plan optimization problem and the charge/discharge plan optimization problem are formulated separately, one schedule is fixed and the other By repeating the determination of the schedule, the operation schedule and the discharge schedule can be repeatedly determined. Then, the charge/discharge plan optimization problem is formulated as follows. The symbols used in the charging/discharging plan optimization problem of the second embodiment are the symbols shown in Table 6 below in addition to the symbols in Tables 1 to 5 used in the first embodiment.

Then, by using the above symbols, the grid connection point model of the second embodiment is described as in the following equation (18), and the power storage equipment model is described by the above equations (3) to (5) in addition to the equation ( 19) and (20).

In addition, the charge-discharge plan optimization problem of the second embodiment is the objective function shown by equation (21), equations (22) to (25) and equations (11) and (12) of the first embodiment Constraint functions consisting of is represented as follows. Note that the function f in the above equation (21) is the same as the equation (16) of the first embodiment.

In step S2a, for example, the equipment number No. 1 to No. 5 of the five power storage facilities, the facility number No. 1 to No. 3 is set as the first power storage facility J1, and the facility number No. 3 is set as the first power storage facility J1. 4, No. 5 power storage facility is set as the second power storage facility J2, the power optimization problem is solved. are obtained.

FIG. 12 shows that the second power storage facility J2 discharges more frequently than the first power storage facility J1. Further, comparing FIG. 13 and FIG. 14, the fluctuations in the charge/discharge power and the remaining amount of charge of the second power storage facility J2 are smaller than those of the second power storage facility J2, that is, fluctuate in a shorter period of time. That is, the first power storage facility J1, whose cycle life should be taken into account, has a relatively small number of charge/discharge cycles, whereas the second power storage facility J2, which is a facility and does not require consideration of its cycle life, has a relatively small number of charge/discharge cycles. Relatively many.

According to the second embodiment, heat treatment capable of realizing peak shift of power consumption of the heat treatment plant B comprising the first power storage equipment J1, the second power storage equipment J2, and the heat treatment furnaces R1 to R8 (power load equipment) It is possible to obtain a plan and a charge/discharge plan that can minimize the number of times of charging/discharging the first power storage facility J1.

Further, according to the second embodiment, since the deterioration degrees of the first power storage equipment J1 and the second power storage equipment J2 are different, that is, the deterioration degrees of the power storage equipment are grouped into two, maintenance planning of the power storage equipment There is an advantage that it is easy to rattle.

It should be noted that the present invention is not limited to the above-described embodiments, and for example, the following modifications are conceivable.
(1) In the above embodiment, the case where the plurality of heat treatment furnaces R1 to R8 are used as power load equipment has been described, but the present invention is not limited to this. That is, the present invention can be applied to various power load facilities other than the plurality of heat treatment furnaces R1 to R8, and can be applied to various facilities other than the heat treatment factories A and B.

For example, a machining center for machining parts can be considered as power load equipment. This machining center is a power load facility whose power consumption fluctuates greatly during operation. In a manufacturing plant (facilities) equipped with a plurality of such machining centers (equipment), the effect of suppressing maximum power consumption is large, as in a heat treatment plant.

(2) In the above-described embodiment, the power supply equipment is composed of the system power source D and the power storage device J or the system power source D and the first and second power storage devices J1 and J2, but the present invention is not limited to this. For example, the heat treatment plants A and B are provided with generators and/or distributed power sources, and the power supply equipment is provided by the system power source D, the power storage device J and the generator or/and the distributed power sources, or the system power source D and the first and second power storage devices. It may consist of J1, J2 and generators and/or distributed power sources.

(3) In the above embodiment, the system is connected to the system power source D, but the present invention is not limited to this. The electric power load equipment may be operated by the electric power of the power generators and/or distributed power sources provided in the heat treatment plants A and B without being connected to the grid.

(4) In the above embodiment, the power optimization problem was formulated by equations (6) to (12) or equations (11), (12), (20) to (24). The conversion is not limited to these formulas. In particular, the constraints may be modified in various ways as required.

(5) In the above embodiment, the predicted power consumption data is generated based on the heat treatment furnace database 1a, but the present invention is not limited to this. For example, a physical model of the heat treatment furnace R may be stored in the storage unit 1, and predicted power consumption data may be generated using the physical model. Also, the predicted power consumption data may be generated using both the physical model and the heat treatment furnace database 1a.

A, B Heat treatment factory (facility)
D System power supply J Power storage facility J1 First power storage facility J2 Second power storage facility R1 to R8 Heat treatment furnace (power load facility)
U Upstream line S Parts storage L Downstream line X Parts (objects)
REFERENCE SIGNS LIST 1 storage unit 1a heat treatment furnace database 1b program storage unit 2 operation unit 3 communication unit 4 calculation unit 4a prediction unit 4b optimization unit 5 display unit

Claims (6)

An operation plan optimization device for minimizing peak power consumption of a facility having a plurality of power load equipment and one or more power storage equipment,
an optimization unit that obtains an operation schedule of the power load equipment and a charge/discharge schedule of the power storage equipment based on predicted power consumption data of the power load equipment ;
The optimization unit obtains both or one of the operation schedule and the charge/discharge schedule, fixes one of the obtained schedules, and repeats obtaining the other schedule, thereby obtaining the operation schedule and the charge/discharge schedule. An operation plan optimization device characterized in that iteratively obtains and . An operation plan optimization device for minimizing peak power consumption of a facility having a plurality of power load equipment and one or more power storage equipment,
an optimization unit that obtains an operation schedule of the power load equipment and a charge/discharge schedule of the power storage equipment based on predicted power consumption data of the power load equipment;
The operation plan optimizing device, wherein the optimizing unit obtains a charging/discharging schedule such that the number of charging/discharging times of the power storage equipment is minimized. An operation plan optimization device for minimizing peak power consumption of a facility having a plurality of power load equipment and one or more power storage equipment,
an optimization unit that obtains an operation schedule of the power load equipment and a charge/discharge schedule of the power storage equipment based on predicted power consumption data of the power load equipment;
An operation plan optimizing apparatus, wherein when a plurality of power storage facilities are provided, a charging/discharging schedule is obtained so that the number of charging/discharging times of each of the power storage facilities is equalized. The operation plan optimizing device according to any one of claims 1 to 3 , wherein the facility further comprises a distributed power source . The operation plan optimizing device according to any one of claims 1 to 4 , wherein the facility supplies grid power to the power load equipment and the power storage equipment . The operation plan optimizing apparatus according to any one of claims 1 to 5 , wherein the power load facility is a heat treatment furnace for heat-treating a predetermined object .

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