Control plan generation system, control plan generation method, and control plan generation program

Abstract

To create adjustment capacity according to power supply and demand by generating a control plan that takes into account factors that affect quality.SOLUTION: There is provided a control plan generation system that has a processor and a memory unit. The memory unit holds constraint conditions relevant to control of one or more production facilities that use electricity in a factory, a first control plan for controlling the one or more production facilities for production in the factory, and demand response information indicating predicted results of implementing a demand response to adjust the power demand in the factory. The constraint conditions include at least conditions that affect the quality of products produced in the factory. The processor generates one or more second control plans based on the constraint conditions and the demand response information, evaluates the one or more second control plans by comparing costs required for production between the first control plan and the one or more second control plans, and outputs at least one of the one or more second control plans and the evaluation result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a control plan generation technique for realizing a control plan according to demand response in a factory. [Background technology]

[0002] With the increasing adoption of variable renewable energy sources such as solar and wind power, issues related to adjusting power supply and demand have become apparent, and the Ministry of Economy, Trade and Industry has been promoting calls and initiatives for adjusting power supply and demand. One of the countermeasures is demand response (hereinafter referred to as DR), in which power consumers respond to requests to adjust their power usage based on the power supply and demand balance. There are two types of demand response: downward DR, which suppresses sudden increases in power demand, and upward DR, which actively utilizes surplus renewable energy. Currently, DR in factories is limited to cooperation with large power consumers in specific businesses whose power demand can be easily predicted in advance during specific time periods when power shortages are expected.

[0003] The following prior art is known as background art in this technical field: Patent Document 1 (WO 2014 / 207851) describes a supply and demand planning device including: an electricity demand forecasting unit that forecasts electricity demand; a profit expectation value forecasting unit that calculates an expected profit per unit amount of reduced electricity based on the probability of a demand response occurring and a rebate value obtained through the demand response; and an optimal operation plan creation unit that uses an evaluation function obtained by adding together a first cost required for purchasing electricity, a second cost required for generating electricity by an electricity supply facility, and a product of the expected profit value and a reserve capacity, which is the amount of electricity that can be further generated by the electricity supply facility after generating a supply amount that satisfies the electricity demand, and determines an operation plan for the reserve capacity and the electricity supply facility such that, when the electricity demand is satisfied by the amount of electricity purchased and the amount of electricity generated by the electricity supply facility and the reserve capacity is generated, the constraints of the electricity supply facility are satisfied and the evaluation function is minimized. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2014 / 207851 Summary of the Invention [Problem to be solved by the invention]

[0005] In demand response, it is desirable to create greater adjustment capabilities and stabilize power supply and demand by involving factories in a wide range of fields, rather than just large consumers in specific businesses. However, when expanding application to factories in a wide range of fields, it is necessary to optimize the operation of production equipment by taking into account power supply and demand. However, conventional control plan generation systems do not include information on the characteristics of factory equipment or factors affecting quality, making it difficult to adjust control plans to match power supply and demand. Furthermore, power storage equipment such as storage batteries is expensive, making it difficult for factories to own them. These have been barriers to participation in demand response.

[0006] The present invention aims to provide a control plan generation system that generates a control plan that takes into account quality-affecting factors in a factory, thereby creating adjustment capabilities according to power supply and demand, and enabling participation in demand response by operating existing equipment. [Means for solving the problem]

[0007] A representative example of the invention disclosed in the present application is as follows: A control plan generation system having a processor and a storage unit, wherein the storage unit stores constraints related to the control of one or more pieces of production equipment that use electricity in a factory, a first control plan for controlling the one or more pieces of production equipment for production in the factory, and demand response information indicating a predicted result of implementing a demand response for adjusting the electricity demand in the factory, the constraints including at least a condition affecting the quality of products produced in the factory, the processor generates one or more second control plans based on the constraints and the demand response information, evaluates the one or more second control plans by comparing the production costs between the first control plan and the one or more second control plans, and outputs at least one of the one or more second control plans and the evaluation result. [Effects of the Invention]

[0008] According to one aspect of the present invention, by generating a control plan for existing equipment in a factory, quality can be guaranteed, and adjustment capabilities can be created to enable DR support. Problems, configurations, and effects other than those described above will be made clear through the following description of the embodiment. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing a configuration of a control plan generation system according to an embodiment of the present invention; [Figure 2] 1 is a block diagram showing a physical configuration of a control plan generation system according to an embodiment of the present invention. [Figure 3] 10 is a flowchart illustrating a process executed by a prediction unit according to an embodiment of the present invention. [Figure 4] 10 is a flowchart illustrating a process executed by a plan generating unit according to an embodiment of the present invention. [Figure 5] 10 is a flowchart illustrating a process executed by an evaluation unit according to the embodiment of the present invention. [Figure 6A] 10 is an example of a control plan output in an embodiment of the present invention. [Figure 6B] 10 is an example of a control plan output in an embodiment of the present invention. [Figure 6C] 10 is an example of a control plan output in an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0010] FIG. 1 is a block diagram showing the configuration of a control plan generation system according to an embodiment of the present invention.

[0011] The control plan generation system 1 of this embodiment includes a receiving unit 10, a predicting unit 20, a plan generating unit 30, an evaluating unit 40, and an output unit 50, and generates a control plan for a target factory.

[0012] The receiving unit 10 connects to a network 110 and acquires external information 100. The predicting unit 20 predicts the probability that a demand response will be implemented and the power demand, and calculates the maximum DR response amount, which is the maximum value of negawatts created by the demand response. Details of the processing executed by the predicting unit 20 will be described later with reference to FIG. 3.

[0013] The plan generating unit 30 generates a first control plan based on the constraint conditions. The constraint conditions are stored as a power utilization facility constraint condition table 103, the details of which will be described later. The first control plan does not assume the implementation of demand response. Furthermore, the plan generating unit 30 generates one or more second control plans based on the demand response information predicted by the prediction unit 20 and the constraint conditions. The details of the processing executed by the plan generating unit 30 will be described later using FIG. 4.

[0014] The evaluation unit 40 evaluates one or more second control plans based on the difference in production costs between the one or more second control plans and the first control plan, and the difference in power consumption between the one or more second control plans and the first control plan. Details of the processing executed by the evaluation unit 40 will be described later with reference to FIG. 5.

[0015] The output unit 50 outputs the second control plan, the evaluation result of the second control plan, and the evaluation result regarding quality (risk judgment).

[0016] The control plan generation system 1 also includes, as data used by each functional unit for processing, external information 100, a DR performance table 101, a production performance table 102, and a power utilization facility constraint condition table 103. These data may be stored in an auxiliary storage device, a memory, or an external storage device.

[0017] The external information 100 includes information on the probability of DR occurring calculated externally, and is acquired from an electric power company or an aggregator. Specifically, the external information 100 may include, for example, the value of the probability of DR occurring itself calculated by an electric power company or the like, or may include information that can be used to calculate the probability of DR occurring. The latter information may include, for example, weather forecast information, calendar information, trend information, etc. The weather forecast information may include, for example, the presence or absence of sunshine, the presence or absence of rain, the temperature, etc. The calendar information may include, for example, information on the day of the week, holidays, etc. The trend information may include, for example, information on increased production, shutdowns, etc. in a specific industry.

[0018] The DR record table 101 includes the response record to demand response in the factory. This includes record data on the conditions under which demand response was implemented (weather, amount of renewable energy generated, amount of self-supplied power, power demand status, power price, demand response price, equipment operation status, etc.).

[0019] The production performance table 102 indicates the operation status of equipment in a factory, and includes data on the number of operating equipment units and the amount of power consumption according to the operation status, etc. The production performance table 102 stores past operation data, but may also include forecast data calculated based on the stored data.

[0020] The power usage facility constraint table 103 indicates constraints related to facilities that use power in a factory, and may include, for example, the following items:

[0021] [1] Equipment constraints -Maximum number of simultaneous operations (e.g. 3) Setup process time (for example, 20 minutes after the previous process ends) · Process duration (e.g., 30 minutes) Continuous operation time (for example, within 10 hours) Waiting time limit (for example, 1 hour) Output control range (e.g., 100kW) Maintenance conditions (e.g., once a week)

[0022] [2] Human constraints Required personnel (e.g., 2 people per unit) Working hours (e.g., 10 hours / day) Shift change deadline (for example, up to one week in advance)

[0023] [3] Quality constraints - Heating rate (for example, 10K / min or less) Temperature retention time (for example, up to 1 hour) Processing speed (for example, 5 mm / sec or less)

[0024] [4] Production constraints -Production delivery time (for example, one week later) Production demand (e.g., 10 tons / week) - Availability (e.g., 80% or more)

[0025] Here, the power utilization facility constraint condition table 103 is not limited to constraints on a single facility, but may also include constraints arising from cooperation between multiple facilities or multiple processes.

[0026] FIG. 2 is a block diagram showing the physical configuration of the control plan generation system 1 according to the embodiment of the present invention.

[0027] The control plan generation system 1 of this embodiment is configured by a computer having a processor (CPU) 201 , a memory 202 , an auxiliary storage device 203 , a communication interface 204 , an input interface 205 and an output interface 208 .

[0028] The processor 201 is an arithmetic device that executes programs stored in the memory 202, and the processor 201 executes various programs to realize various functions of the control plan generation system 1. Note that part of the processing performed by the processor 201 by executing the programs may be executed by another arithmetic device.

[0029] The memory 202 includes a ROM, which is a non-volatile storage element, and a RAM, which is a volatile storage element. The ROM stores unchanging programs, etc. The RAM is a high-speed, volatile storage element such as a DRAM, and temporarily stores programs executed by the processor 201 and data used when the programs are executed.

[0030] The auxiliary storage device 203 is a large-capacity, non-volatile storage device such as a magnetic storage device (HDD) or a flash memory (SSD). The auxiliary storage device 203 also stores data used by the processor 201 when executing a program (e.g., external information 100, DR record table 101, production record table 102, power usage facility constraint condition table 103, etc.), and programs executed by the processor 201 (e.g., prediction program, plan generation program, calculation program, output program, evaluation program, etc.). That is, the programs are read from the auxiliary storage device 203, loaded into the memory 202, and executed by the processor 201 to realize each function of the control plan generation system 1.

[0031] The communication interface 204 is a network interface device that controls communication with other devices according to a predetermined protocol.

[0032] The input interface 205 is an interface to which input devices such as a keyboard 206 and a mouse 207 are connected and which receives input from an operator. The output interface 208 is an interface to which an output device such as a display device 209 is connected and which outputs the execution results of the program in a visually recognizable format. Note that a terminal (not shown) connected to the control plan generation system 1 via the network 110 may provide the input device and the output device.

[0033] The program executed by the processor 201 is provided to the control plan generation system 1 from a removable medium (such as a CD-ROM or flash memory) or via a network, and is stored in a non-volatile auxiliary storage device 203, which is a non-transitory storage medium. For this reason, the control plan generation system 1 may have an interface for reading data from removable media.

[0034] The control plan generation system 1 is a computer system configured on one physical computer, or on multiple logically or physically configured computers, and may operate on a virtual computer constructed on multiple physical computer resources.

[0035] Next, the processing executed by each unit of the control plan generation system 1 will be described.

[0036] The receiving unit 10 has a function of acquiring external information 100. Data reception in the receiving unit 10 is repeatedly executed at a predetermined timing.

[0037] FIG. 3 is a flowchart showing the process executed by the prediction unit 20 according to the embodiment of the present invention.

[0038] The processor 201 starts the prediction unit 20 by a prediction program and executes the prediction process. This prediction process is executed repeatedly at predetermined timings.

[0039] First, the prediction unit 20 collates the external information 100 and the DR record table 101 (S501) and determines a similar DR record pattern 101' (S502). If the DR record table 101 is patterned, it is sufficient to select a similar record pattern, and if the DR record table 101 is in a log format, similar record data is selected and determined as the record pattern.

[0040] For example, the prediction unit 20 may compare the forecast value of the weather after a predetermined time, calendar information, event information, etc. contained in the external information 100 with the weather, calendar information, event information, etc. when demand response was implemented in the past stored in the DR performance table 101, and determine one or more DR performance patterns 101' that are similar to the information after the predetermined time.

[0041] Next, the prediction unit 20 predicts the occurrence of a demand response based on the external information 100 and the DR record table 101 (S503) and predicts the DR demand amount (S504). Specifically, the prediction unit 20 selects similar situations after a predetermined time from the DR record table 101 and calculates the proportion (occurrence rate) of cases in which a demand response is requested among the selected data. At this time, the occurrence rate of a demand response may be calculated taking into account characteristic changes in electricity demand due to calendar factors (day of the week, holidays, Obon, New Year's) or trends (news of increased production in a specific industry, shutdown of operations, etc.). Alternatively, the occurrence probability of a demand response may be directly obtained externally. Then, the prediction unit 20 calculates a statistical value (e.g., an average value) of the demand response request amount among the selected data and sets it as a predicted value of the DR request amount.

[0042] Thereafter, the prediction unit 20 predicts the power demand of the factory and calculates the maximum demand response value (S505). For example, the prediction unit 20 predicts the power demand at the start of the demand response using the selected external information 100, the DR record table 101, and the production record table 102. The prediction result of the demand response by the prediction unit 20 is stored in, for example, the auxiliary storage device 203.

[0043] As described above, instead of the prediction unit 20 predicting the occurrence of a demand response based on the external information 100 or the like, the prediction unit 20 may acquire prediction information of the occurrence of a demand response included in the external information 100. In this case, the acquired prediction information is stored in the auxiliary storage device 203.

[0044] FIG. 4 is a flowchart showing the process executed by the plan generating unit 30 according to the embodiment of the present invention.

[0045] When the prediction unit 20 predicts the DR request amount (S504), the processor 201 starts the plan generation unit 30 by the reception program, and starts the plan generation process.

[0046] First, the plan generating unit 30 estimates the DR unit price using the predicted value of the DR request amount and the DR performance table 101 (S506). For example, the plan generating unit 30 selects data for which a demand response has been implemented from the data selected in the DR request amount predicted in step S504, calculates a statistical value (for example, an average value) of the unit price of the demand response, estimates the DR unit price, and selects data with similar conditions from the DR price forecast data.

[0047] Next, the plan generating unit 30 generates a control plan using the production record table 102 and the power utilization facility constraint condition table 103 (S507).

[0048] The generated control plan will now be explained. In order to generate a large amount of negawatts through demand response, it is preferable to target facilities with large amounts of power consumption as control targets. Furthermore, targeting multiple facilities can be expected to generate a larger amount of negawatts. Therefore, the plan generation unit 30 generates a control plan for reducing power demand by combining the following individual control methods.

[0049] [1] Transition one or more facilities to an operating mode with low output power [2] Shut down some of the equipment and continue operation with the remaining equipment.

[0050] Any of the control plans created here is feasible in the factory in accordance with the power utilization facility constraint condition table 103.

[0051] FIG. 5 is a flowchart showing the process executed by the evaluation unit 40 according to the embodiment of the present invention.

[0052] When the plan generating unit 30 generates the control plan (S507), the processor 201 starts the evaluation unit 40 and executes the evaluation process.

[0053] First, the evaluation unit 40 determines the DR response amount using the production record table 102, the power utilization facility constraint condition table 103, and the DR unit price prediction result, and calculates the incurred cost. Here, the incurred cost is calculated based on, for example, the amount of energy required for facility operation, labor costs, and the incentive for the DR response. In other words, the more energy required, the higher the incurred cost, and the higher the labor costs, the higher the incurred cost. When a demand response is responded to, the incurred cost is deducted by the set incentive amount.

[0054] Next, the evaluation unit 40 evaluates one or more second control plans based on the difference in production cost between the one or more generated second control plans and the first control plan, and the difference in power consumption between the one or more second control plans and the first control plan (S510). For example, the evaluation function is as follows:

[0055] Evaluation function = {(amount of energy consumed in the second control plan) - (amount of energy consumed in the first control plan)} x (energy unit price) + (cost incurred due to personnel changes caused by control plan changes) - (incentive difference due to DR response) x (DR occurrence expected value)

[0056] If the evaluation function is positive, it means that executing the newly created second control plan will increase costs compared to the first control plan. Therefore, the plan generation unit 30 regenerates the control plan (S511), and the evaluation unit 40 evaluates it in the same manner as described above. However, for example, there may be cases where DR is desired as external PR even if costs increase. Therefore, regeneration of the control plan is not necessarily required, and the determination threshold for regeneration is arbitrary. On the other hand, if the evaluation function is negative, it means that executing the newly created second control plan will decrease costs compared to the first control plan. In this case, the generated second control plan may be used as a final plan, or may be retained as a provisional plan, and the plan generation unit 30 may regenerate the control plan.

[0057] Next, the evaluation unit 40 performs a quality evaluation of the generated second control plan using the power utilization facility constraint condition table 103 (S512). If there is an item that conflicts with any constraint condition included in the power utilization facility constraint condition table 103, the plan generation unit 30 generates a control plan again (S511).

[0058] Finally, the evaluation results of the generated control plan are created and stored together with the control plan (S513).

[0059] The output unit 50 outputs the stored control plan and its evaluation result. Furthermore, if there is an item that conflicts with any constraint condition included in the power utilization facility constraint condition table 103, the output unit 50 also outputs the content of that item.

[0060] Here, an example of the generation of the first control plan, the generation of the second control plan (S507), and the regeneration of the second control plan (S511) performed by the plan generating unit 30 will be described.

[0061] For example, the plan generating unit 30 generates a first control plan so that the constraint conditions are satisfied (in other words, so that deviation from the constraint conditions is minimized). At this time, the predicted DR request amount is not taken into consideration. As a technique for generating a control plan using the constraint conditions as input, any method such as general mathematical optimization can be adopted, and therefore a detailed description thereof will be omitted.

[0062] Furthermore, the plan generating unit 30 generates a second control plan so that the power consumption is a value according to the predicted DR request amount and the constraint conditions are satisfied (S507). This may be performed by generating a control plan by adding the power consumption according to the DR request to the input constraint conditions.

[0063] If a second control plan is generated that does not increase costs compared to the first control plan and satisfies all of the constraints, the second control plan can be adopted. On the other hand, if the costs based on the second control plan are higher than the costs based on the first control plan, or if a second control plan that satisfies all of the constraints cannot be generated (i.e., the generated second control plan does not satisfy at least one of the constraints), the plan generating unit 30 generates a new second control plan (S511).

[0064] At this time, the plan generating unit 30 may change the weights of the constraint conditions when generating the control plan. For example, when constraint condition items such as the above-mentioned [1] facility constraint conditions to [4] production-related constraint conditions are set, a weight may be assigned to each item in advance, and the second control plan may be generated based on the weights. Specifically, the second control plan may be generated so that the greater the weight of an item, the smaller the deviation from the constraint conditions (preferably, the more the constraint conditions are satisfied).

[0065] Then, when generating a new second control plan in step S511, the plan generating unit 30 may change the weight values. Specifically, the weight values may be changed so that the item with the highest weight before and after the change is different. This increases the possibility of generating a second control plan that is acceptable to the producer.

[0066] Alternatively, the plan generating unit 30 may generate the second control plan so as to control the power of not only one piece of equipment in a factory but also multiple pieces of equipment. In this case, the plan generating unit 30 may generate the second control plan so as to control the power of each of the multiple pieces of equipment in different time periods. Examples of such second control plans will be described later with reference to FIGS. 6A to 6C. This increases the likelihood that a control plan that has little impact on production volume and quality even when responding to demand response will be generated.

[0067] Furthermore, the plan generation unit 30 may calculate the production volume based on each of the first control plan and the second control plan, and if the production volume based on the second control plan is smaller than the production volume based on the first control plan, generate a third control plan to compensate for the difference. Specifically, for example, the third control plan may be generated for a period other than the period covered by the second control plan, so that the constraints for that period are satisfied and a production volume equivalent to the difference is added. This makes it possible to generate a control plan that does not reduce the overall production volume, including other periods, even if the production volume decreases during the period responding to demand response.

[0068] 6A to 6C are examples of control plans output in an embodiment of the present invention.

[0069] When a downward DR occurs, (i) in Figure 6A is a plan based on the first control plan that does not support DR, with the output power at that time set to 100. (ii) in Figure 6B is a plan that supports DR by controlling equipment A alone. While this is easy to implement due to individual control, it conflicts with quality constraints due to the long-term output control of one piece of equipment. (iii) in Figure 6C is an example of control being performed on three pieces of equipment. DR is supported by staggering the short-term output adjustments of each piece of equipment. This method makes it possible to generate negawatts even when long-term output control is not possible due to quality constraints. In other words, it is possible to reduce power demand by implementing demand response while minimizing the impact on production volume and product quality.

[0070] In this way, by evaluating the cost calculated from the difference between a control plan that does not support DR and a control plan that supports DR, and by taking into consideration quality constraints, it is possible to realize a control plan that saves energy and guarantees quality. Because power reduction is achieved through a control plan that makes use of equipment characteristics, the introduction of large storage batteries, etc. is not necessary, and it is expected that more factories will participate in demand response.

[0071] Furthermore, the system according to the embodiment of the present invention may be configured as follows.

[0072] (1) A control plan generation system (e.g., control plan generation system 1) having a processor (e.g., processor 201) and a storage unit (e.g., memory 202 and auxiliary storage device 203), wherein the storage unit holds constraint conditions (e.g., power consumption equipment constraint condition table 103) related to control of one or more production facilities that use electricity in a factory, a first control plan for controlling the one or more production facilities for production in the factory, and demand response information indicating a predicted result of implementing a demand response for adjusting the electricity demand of the factory, and the processor generates one or more second control plans based on the constraint conditions and the demand response information (e.g., step S507), evaluates the one or more second control plans by comparing the production costs between the first control plan and the one or more second control plans (e.g., step S510), and outputs at least one of the one or more second control plans and the evaluation result thereof (e.g., step S513).

[0073] This makes it possible to generate a control plan that takes into account quality-affecting factors and create adjustment capacity according to power supply and demand.

[0074] (2) In the control plan generation system described in (1) above, the processor generates the one or more second control plans to adjust the power demand of the factory based on the predicted demand response and satisfy the constraints, and outputs the results of evaluating the quality of the product under the one or more second control plans (e.g., steps S512 and S513).

[0075] This allows the generation of a control plan with little impact on quality.

[0076] (3) In the control plan generation system described in (2) above, the constraint conditions include at least one item of the characteristics of the production equipment, the time required for the production process, the personnel required for the production process, conditions related to the control of the production equipment that affect the quality of the product, and the delivery date of the product (for example, at least one item of the above [1] Equipment constraint conditions to [4] Production-related constraint conditions).

[0077] (4) In the control plan generation system described in (3) above, the processor generates a new second control plan when the constraint condition is not satisfied (for example, step S511).

[0078] This allows the generation of a control plan with little impact on quality.

[0079] (5) In the control plan generation system described in (4) above, the processor generates, as the second control plan, a plan for controlling the power of a plurality of the production facilities (for example, the multiple control plan shown in FIG. 6C).

[0080] This makes it possible to link control plans for multiple production facilities and generate a control plan that has little impact on quality.

[0081] (6) In the control plan generation system described in (5) above, the processor generates, as the second control plan, a plan for controlling the power of multiple pieces of production equipment at different time periods (for example, the multiple control plan shown in Figure 6C).

[0082] This makes it possible to link control plans for multiple production facilities and generate a control plan that has little impact on quality.

[0083] (7) In the control plan generation system described in (4) above, a weight is set for each item included in the constraint condition, and the processor generates the second control plan based on the weight so that the items of the constraint condition are satisfied, and if the constraint condition is not satisfied, changes the value of the weight and generates the new second control plan (e.g., step S511).

[0084] This allows the generation of a control plan with little impact on quality.

[0085] (8) In the control plan generation system described in (4) above, when the amount of the product in the second control plan is less than the amount of the product in the first control plan, the processor generates a third control plan for a period other than the period covered by the second control plan to compensate for the difference between the amount of the product in the first control plan and the amount of the product in the second control plan.

[0086] This makes it possible to generate a control plan that does not reduce the overall production volume.

[0087] (9) In the control plan generation system described in (1) above, the processor compares the costs required for production based on the power consumption and labor costs based on the first control plan with the power consumption, labor costs, and incentives for responding to the demand response based on the second control plan (e.g., steps S508 to S510).

[0088] This allows control plans to be evaluated based on costs, including incentives for demand response.

[0089] (10) In the control plan generation system described in (1) above, the processor generates a new second control plan when the cost based on the second control plan is greater than the cost based on the first control plan (e.g., step S511).

[0090] This makes it possible to generate a control plan that reduces production costs when responding to demand response.

[0091] (11) In the control plan generation system described in (10) above, the constraint conditions include at least one item of the characteristics of the production equipment, the time required for the production process, the personnel required for the production process, conditions related to the control of the production equipment that affect the quality of the product, and the delivery date of the product (for example, at least one item of the above-mentioned [1] equipment constraint conditions to [4] production-related constraint conditions), and a weight is set for each item included in the constraint conditions.The processor generates the second control plan based on the weight so as to reduce deviation from the items of the constraint conditions, and if the cost based on the second control plan is greater than the cost based on the first control plan, changes the value of the weight and generates the new second control plan (for example, step S511).

[0092] This makes it possible to generate a control plan that reduces production costs when responding to demand response.

[0093] (12) In the control plan generation system described in (1) above, the processor predicts the implementation of the demand response based on information acquired from outside the control plan generation system and stores the result in the memory unit (e.g., steps S501 to S504).

[0094] This makes it possible to predict the implementation of demand response and generate a second control plan based on the prediction results.

[0095] It should be noted that the present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to facilitate a better understanding of the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0096] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The above-described configurations, functions, etc. may also be implemented in software, with a processor interpreting and executing a program that implements each function. Information such as the programs, tables, and files that implement each function can be stored in storage devices such as nonvolatile semiconductor memory, hard disk drives, and solid-state drives (SSDs), or in computer-readable, non-transitory data storage media such as IC cards, SD cards, and DVDs.

[0097] Furthermore, the control lines and information lines shown are those considered necessary for the explanation, and do not necessarily show all the control lines and information lines necessary for implementation. In reality, it can be considered that almost all components are interconnected. [Explanation of symbols]

[0098] 1. Control plan generation system 10 Receiving unit 20 Prediction Department 30 Plan Generation Unit 40 Evaluation Department 50 Output section 100 External Information 101 DR performance table 102 Production Results Table 103 Power usage facility constraints table

Claims

1. A control plan generation system having a processor and a storage unit, the storage unit holds constraints related to control of one or more pieces of production equipment that use electricity in a factory, a first control plan for controlling the one or more pieces of production equipment for production in the factory, and demand response information indicating a predicted result of implementation of a demand response for adjusting electricity demand in the factory; the constraints include at least conditions that affect the quality of products produced in the factory; The processor: generating one or more second control plans based on the constraints and the demand response information; evaluating the one or more second control plans by comparing production costs between the first control plan and the one or more second control plans; A control plan generation system that outputs at least one of the one or more second control plans and an evaluation result thereof.

2. 2. The control plan generation system according to claim 1, The processor: generating the one or more second control plans to adjust the power demand of the plant based on the predicted demand response and to satisfy the constraints; a control plan generation system that outputs a result of evaluating the quality of the product under the one or more second control plans;

3. 3. The control plan generation system according to claim 2, The constraint conditions include at least one item of the characteristics of the production equipment, the time required for the production process, the personnel required for the production process, conditions related to the control of the production equipment that affect the quality of the product, and the delivery date of the product.

4. 4. The control plan generation system according to claim 3, The control plan generation system is characterized in that the processor generates a new second control plan when the constraint condition is not satisfied.

5. 5. The control plan generation system according to claim 4, The control plan generation system is characterized in that the processor generates, as the second control plan, a plan for controlling the power of a plurality of the production facilities.

6. 6. The control plan generation system according to claim 5, The control plan generation system is characterized in that the processor generates, as the second control plan, a plan for controlling the power of each of the plurality of production facilities at different time periods.

7. 5. The control plan generation system according to claim 4, A weight is set for each item included in the constraint condition, the processor generates the second control plan based on the weights so that the constraints are satisfied; A control plan generation system, characterized in that, when the constraint conditions are not satisfied, the weight values are changed and the new second control plan is generated.

8. 5. The control plan generation system according to claim 4, a control plan generation system characterized in that, when the amount of product in the second control plan is smaller than the amount of product in the first control plan, the processor generates a third control plan for a period other than the period covered by the second control plan to compensate for the difference between the amount of product in the first control plan and the amount of product in the second control plan.

9. 2. The control plan generation system according to claim 1, The processor compares the costs required for production based on the amount of power consumption and labor costs based on the first control plan and the amount of power consumption, labor costs, and incentives for responding to the demand response based on the second control plan.

10. 2. The control plan generation system according to claim 1, a processor that generates a new second control plan when the cost based on the second control plan is greater than the cost based on the first control plan;

11. The control plan generation system according to claim 10, the constraint conditions include at least one item of characteristics of the production equipment, time required for the production process, personnel required for the production process, conditions related to control of the production equipment that affect the quality of the product, and delivery date of the product; A weight is set for each item included in the constraint condition, the processor generates the second control plan based on the weights so that the constraints are satisfied; a control plan generation system that, when the cost based on the second control plan is greater than the cost based on the first control plan, changes the weight value and generates the new second control plan.

12. 2. The control plan generation system according to claim 1, a processor for predicting implementation of the demand response based on information obtained from outside the control plan generation system, and storing the result in the storage unit;

13. A control plan generation method executed by a computer system having a processor and a storage unit, comprising: the storage unit holds constraints related to control of one or more pieces of production equipment that use electricity in a factory, a first control plan for controlling the one or more pieces of production equipment for production in the factory, and demand response information indicating a predicted result of implementation of a demand response for adjusting electricity demand in the factory; the constraints include at least conditions that affect the quality of products produced in the factory; The control plan generation method includes: generating one or more second control plans based on the constraints and the demand response information; the processor evaluating the one or more second control plans by comparing production costs between the first control plan and the one or more second control plans; and a step of the processor outputting at least one of the one or more second control plans and an evaluation result thereof.

14. A control plan generation program to be executed by a computer system having a processor and a storage unit, the storage unit holds constraints related to control of one or more pieces of production equipment that use electricity in a factory, a first control plan for controlling the one or more pieces of production equipment for production in the factory, and demand response information indicating a predicted result of implementation of a demand response for adjusting electricity demand in the factory; the constraints include at least conditions that affect the quality of products produced in the factory; The control plan generation program generating one or more second control plans based on the constraints and the demand response information; evaluating the one or more second control plans by comparing production costs between the first control plan and the one or more second control plans; and a step of outputting at least one of the one or more second control plans and an evaluation result thereof.

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