Prediction system, aggregation system, method and program

Abstract

To realize a prediction system for providing information capable of improving merits for a user by cooperating with a request of a demand response.SOLUTION: A prediction system predicts a power demand of each of one or more facilities which produce products. The prediction system comprises: a calculation unit which calculates a power use scheduled amount in a target time zone on the basis of past record data of power consumption and a production plan of the product for each of the one or more facilities; and a determination unit which determines a power purchase scheduled amount from a power system in the target time zone on the basis of the power use scheduled amount and a power transaction price of the target time zone for each of the one or more facilities.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a forecasting system, a method, and a program for forecasting power demand, and an aggregation system for adjusting the balance between power supply and demand. [Background technology]

[0002] In recent years, the importance of demand response (DR) to ensure a stable supply of electricity has been increasing. Demand response is a system in which consumers save and store electricity in response to requests, and receive rewards when they achieve their goals.

[0003] Japanese Patent Application Laid-Open No. 2016-81074 (Patent Document 1) discloses a technique for periodically updating a demand response capability list based on a facility usage plan based on a production plan. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-81074 Summary of the Invention [Problem to be solved by the invention]

[0005] According to the technology disclosed in Patent Document 1, the demand response capability list is updated based only on the production plan, so that consumers who own the equipment may cooperate with the DR request even though the benefits to them are low.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and aims to provide a prediction system, method, and program that provide information that can improve the benefits to consumers of cooperating with DR requests. Another aim of the present disclosure is to provide an aggregation system that can adjust the balance of supply and demand of electricity in consideration of the benefits to consumers of cooperating with DR requests. [Means for solving the problem]

[0007] According to one example of the present disclosure, a prediction system predicts the power demand of each of one or more facilities that produce a product. The prediction system includes: a calculation unit that calculates a planned power consumption amount for a target time period for each of the one or more facilities based on actual power consumption data and a production plan for the product; and a determination unit that determines a planned amount of power to be purchased from a power grid for each of the one or more facilities based on the planned power consumption amount and the power trading price for the target time period.

[0008] According to this disclosure, the planned amount of electricity purchased from the power grid is determined based on the electricity trading price. Therefore, the planned amount of electricity purchased is determined taking into consideration the benefit (typically, compensation) to consumers of cooperating with a DR request. In this way, the prediction system can provide information that can increase the benefit to consumers of cooperating with a DR request.

[0009] In the above disclosure, the determination unit further determines, based on the planned power usage amount and the power trading price, a portion of the planned power usage amount to be supplied by each of one or more power supply sources separate from the power grid. The one or more power supply sources include at least one of a private power generation device and a power storage device. According to this disclosure, the breakdown of the power supply is automatically determined.

[0010] In the above disclosure, the one or more power supply sources include a solar power generation device, and the determination unit determines a planned amount of power purchase and a quantity of each of the one or more power supply sources based on weather forecast information, a planned amount of power usage, and an electricity trading price.

[0011] According to this disclosure, the determination unit can accurately determine the amount corresponding to the photovoltaic power generation device based on weather forecast information.

[0012] In the above disclosure, the determination unit sets a priority for each of a plurality of time slots included in a target period based on the electricity trading price. The determination unit sequentially selects a target time slot from the plurality of time slots according to the priority. The determination unit determines the planned power purchase amount and the amount of each of the one or more power supply sources for the target time slot so as not to affect the planned power purchase amount and the amount of each of the one or more power supply sources determined for a time slot among the plurality of time slots with a higher priority than the target time slot.

[0013] According to this disclosure, the breakdown of power supply for each time period is determined according to the priority determined based on the power trading price. As a result, the determination unit can determine the breakdown of power supply for a time period when the power trading price is favorable for the consumer, for example, so that the consumer can receive a higher reward for cooperating with a DR request.

[0014] In the above disclosure, the prediction system further includes a notification unit that notifies the aggregator of notification data indicating information related to the planned amount of power purchase.

[0015] According to this disclosure, an aggregator can more easily adjust the balance between power supply and demand based on the notification data.

[0016] In the above disclosure, the determination unit further determines a third adjustable amount of the planned power purchase amount based on at least one of the first adjustable amount of the production plan and the second adjustable amount of power supplied from the one or more power supply sources. The prediction system further includes a notification unit that notifies the aggregator of notification data indicating information on the planned power purchase amount and the third adjustable amount.

[0017] According to this disclosure, it becomes easier for an aggregator to adjust the balance between power supply and demand based on the notification data.

[0018] In the above disclosure, the notification unit determines whether to notify the aggregator of the notification data based on the electricity trading price.

[0019] According to this disclosure, the prediction system does not notify the aggregator of notification data for time periods when the consumer is less benefited, so that the consumer can avoid cooperating with a DR request when the consumer is less benefited.

[0020] In the above disclosure, the prediction system further includes an output unit that outputs the power cost corresponding to the third adjustable amount.

[0021] According to this disclosure, consumers can understand the magnitude of the benefits they will receive from cooperating with a DR request by checking their electricity costs.

[0022] In the above disclosure, the determination unit periodically updates the planned amount of power purchases based on the planned amount of power usage calculated based on the latest production plan, the latest power trading price, and the latest status of one or more power supply sources.

[0023] According to this disclosure, the determination unit can update the planned amount of electricity purchase to an appropriate amount for consumers even in the intraday market.

[0024] In the above disclosure, the forecasting system further includes an adjustment unit that adjusts the planned amount of power usage to satisfy a demand response request from an aggregator when the demand response request is satisfied. According to this disclosure, consumers are more likely to cooperate with the DR request.

[0025] In the above disclosure, the one or more facilities include a plurality of facilities, and the forecasting system further includes an adjusting unit that adjusts production plans for the plurality of facilities in response to an electricity trading price.

[0026] According to this disclosure, for example, the adjustment unit can reduce the planned production volume of facilities in areas where the electricity trading price is relatively high, which makes it easier for facilities in areas where the electricity trading price is relatively high to receive higher rewards by cooperating with DR requests.

[0027] According to another example of the present disclosure, an aggregation system in communication with the above-mentioned prediction system includes a determination unit that determines whether to request a demand response for each of one or more facilities based on the notification data and the planned amount of power supply from the power grid.

[0028] According to this disclosure, the aggregation system can adjust the balance between supply and demand of electricity, taking into consideration the benefits to consumers of cooperating with DR requests.

[0029] According to yet another example of the present disclosure, a method for predicting electricity demand for a facility that produces a product includes: a processor calculating, for the facility, a planned amount of electricity usage during a target time period based on actual power consumption data and a production plan for the product; and a processor determining, for the facility, a planned amount of electricity to be purchased from an electric power grid during the target time period based on the planned amount of electricity usage and an electricity trading price for the target time period.

[0030] According to yet another example of the present disclosure, a program causes a computer to execute the above method.

[0031] By disclosing these, the method or program can also provide information that can improve the benefits to consumers of cooperating with a DR request. [Effects of the Invention]

[0032] According to the present disclosure, the prediction system, method, or program can provide information that can improve the benefits to consumers of cooperating with a DR request. According to the present disclosure, the aggregation system can adjust the balance of supply and demand of electricity taking into account the benefits to consumers of cooperating with a DR request. [Brief explanation of the drawings]

[0033] [Figure 1] FIG. 1 is a diagram illustrating an example of a power network including a prediction system according to an embodiment. [Figure 2] FIG. 2 is a schematic diagram illustrating an example of a hardware configuration of a prediction system. [Figure 3] FIG. 2 is a diagram illustrating an example of a functional configuration of a prediction system. [Figure 4] FIG. 1 is a diagram illustrating an example of a functional configuration of an aggregation system. [Figure 5] 1 is a flowchart illustrating an example of a process flow in an electricity network for spot market electricity trading. [Figure 6] FIG. 10 is a diagram showing a transition of the actual value of the amount of power consumption on a certain day. [Figure 7] FIG. 10 is a diagram illustrating an example of performance data. [Figure 8] 10 is a flowchart showing the flow of processing in a subroutine of step S1. [Figure 9] FIG. 10 is a diagram illustrating the process of step S12. [Figure 10] FIG. 2 is a diagram illustrating an example of production plan data. [Figure 11] FIG. 10 is a diagram showing parameters used in step S2. [Figure 12] 10 is a flowchart showing the flow of processing in a subroutine of step S2. [Figure 13] 13 is a flowchart showing the process flow of a subroutine of step S26 shown in FIG. 12. [Figure 14] 10 is a flowchart showing the flow of processing in a subroutine of step S3. [Figure 15] FIG. 10 is a diagram illustrating the processing in step S3. [Figure 16] 1 is a flowchart illustrating an example of a processing flow in an electricity network for electricity trading in an intraday market. DETAILED DESCRIPTION OF THE INVENTION

[0034] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail with reference to the accompanying drawings, in which the same or corresponding parts in the drawings are designated by the same reference numerals and the description thereof will not be repeated.

[0035] §1 Application Examples 1 is a diagram illustrating an example of an electric power network including a prediction system according to an embodiment. As shown in FIG. 1, the electric power network 1 includes an electric power retailer 2, one or more facilities 3, an aggregator 4, an energy trading market 5, and an electric power grid 6.

[0036] The retail electricity supplier 2 is an organization that supplies electricity to consumers from the power grid 6. Each of the one or more facilities 3 is operated by a consumer and produces products using the electricity supplied by the retail electricity supplier 2.

[0037] The aggregator 4 is an intermediary business that aggregates energy resources owned by consumers and acts as an intermediary between consumers and power companies to adjust the balance between supply and demand for electricity. The aggregator 4 has an aggregation system 60 that manages DR requests. The aggregation system 60 is composed of one or more computers.

[0038] The electricity trading market 5 is an organization that trades electricity. For example, the Japan Electric Power eXchange (JEPX) is known as an electricity trading market 5 in Japan. The JEPX determines spot market prices and intraday market prices. The spot market prices and intraday market prices are examples of the "electricity trading price" in this disclosure and fluctuate depending on the time of day. The spot market is a market that handles electricity transactions for the next day and is also called the "day-ahead market." The spot market price is determined for each of 48 30-minute time slots on the next day. Each time slot is also called a "time slot." The intraday market is a market that addresses mismatches between electricity supply and demand that occur between the end of the spot market and one hour before actual supply and demand, and is also called the "hour-ahead market." The intraday market price is determined for each 30-minute time slot on the day.

[0039] The facility 3 includes a prediction system 10, a private power generation system 20, an energy management device 30, one or more pieces of equipment 40, and one or more power meters 50.

[0040] The private power generation system 20 generates solar power. The private power generation system 20 includes a PV (Photovoltaic) panel 21 and a storage battery 22. The PV panel 21 is a photovoltaic power generation device that converts solar energy into electrical energy. The PV panel 21 is an example of a "private power generation device" in the present disclosure. The power generated by the PV panel 21 may be output directly from the private power generation system 20 or may be temporarily stored in the storage battery 22. The output destination of the power generated by the PV panel 21 (one or more facilities 40 or the storage battery 22) is controlled by the prediction system 10. The storage battery 22 charges and discharges according to the control of the prediction system 10. The storage battery 22 is an example of a "power storage device" in the present disclosure.

[0041] The energy management device 30 manages the power consumed in the facility 3. The power consumed in the facility 3 includes power purchased from the retail electricity supplier 2 (power supplied from the power grid 6) and power supplied from the private power generation system 20. The power supplied from the private power generation system 20 includes power generated by the PV panel 21 and power discharged from the storage battery 22.

[0042] The one or more pieces of equipment 40 operate using the supplied power. The one or more pieces of equipment 40 include production equipment that is directly involved in the production of products, and equipment that is not directly involved in the production of products (for example, lighting or air conditioners).

[0043] The one or more power meters 50 measure the amount of power consumed by one or more pieces of equipment 40 for each time period. Each power meter 50 measures the amount of power consumed by the corresponding one or more pieces of equipment 40. The total amount of power consumed measured by the one or more power meters 50 represents the amount of power consumed by the facility 3.

[0044] The prediction system 10 predicts the power demand of a facility 3. The prediction system 10 is configured with one or more computers. The prediction system 10 stores production plan data 11 and performance data 12, and includes a calculation unit 13 and a determination unit 14.

[0045] The production plan data 11 indicates a production plan for a product in the facility 3. The production plan data 11 is generated by, for example, a manager of the facility 3, and stored in the prediction system 10.

[0046] The performance data 12 indicates the performance of the power consumption of the facility 3. The performance data 12 is generated based on past measurement results from one or more power meters 50.

[0047] The calculation unit 13 calculates the planned amount of power consumption for a target time period based on the actual power consumption data 12 and the production plan for the product indicated by the production plan data 11. For example, the calculation unit 13 sequentially selects a target time period for which the planned amount of power consumption is to be calculated from among 48 time periods for the next day, and calculates the planned amount of power consumption for the target time period.

[0048] The determination unit 14 determines the planned amount of power to be purchased from the power grid 6 during the target time period, based on the planned amount of power usage during the target time period and the power trading price during the target time period. The determination unit 14 uses, for example, the spot market price and the intraday market price provided by the power trading market 5 as the power trading price.

[0049] The amount of planned power usage excluding the planned amount of purchased power is supplied by the private power generation system 20. The prediction system 10 controls the output destination of the power generated by the PV panel 21 and the charging and discharging of the storage battery 22 so that the amount is supplied to one or more facilities 40 during the target time period.

[0050] According to the above configuration, the planned amount of power purchased from the power grid 6 is determined based on the power trading price. Therefore, the planned amount of power purchased is determined taking into consideration the benefit (typically, compensation) that consumers will receive from cooperating with a DR request. In this way, the prediction system 10 can provide information that can improve the benefit that consumers will receive from cooperating with a DR request.

[0051] Data on the determined planned power purchase amount is notified to, for example, the aggregator 4. The planned power purchase amount is determined according to the planned power usage amount that is accurately calculated based on the production plan. This allows the aggregator 4 to appropriately adjust the supply and demand of power.

[0052] §2 Specific examples <Hardware configuration of prediction system and aggregation system> Fig. 2 is a schematic diagram showing an example of the hardware configuration of a prediction system. Fig. 2 shows the hardware configuration of a prediction system configured by one computer. As shown in Fig. 2, the prediction system 10 includes a CPU (Central Processing Unit) 101, which is an example of a hardware processor, a memory 102 configured as a volatile storage device such as a DRAM (Dynamic Random Access Memory), a storage 103 configured as a non-volatile storage device, an input interface 104, a display controller 105, a communication interface 106, and a data reader / writer 107. These components are connected to each other via a bus 108 so as to be able to communicate data with each other.

[0053] The CPU 101 reads the program 131 stored in the storage 103 and loads it into the memory 102. The CPU 101 executes the loaded program 131.

[0054] The storage 103 includes, for example, a hard disk drive (HDD), a solid state drive (SSD), a flash memory, etc. The storage 103 stores various data used for executing the program 131 in addition to the program 131.

[0055] The input interface 104 mediates data transmission between the CPU 101 and an input device 120 such as a keyboard, mouse, or touch panel. That is, the input interface 104 receives data indicating various user inputs from the input device 120 and transmits the received data to the CPU 101. The display controller 105 is connected to a display 122 and displays the results of processing by the CPU 101 on the display 122. The communication interface 106 communicates with external devices. The data reader / writer 107 mediates data transmission between the CPU 101 and an external storage medium 124. The storage medium 124 includes a volatile storage medium, a non-volatile storage medium, a general-purpose semiconductor storage device such as a CF (Compact Flash) or an SD (Secure Digital), a magnetic storage medium such as a flexible disk, or an optical storage medium such as a CD-ROM (Compact Disk Read Only Memory).

[0056] The program 131 may be provided not as a standalone program but as part of an arbitrary program. In this case, the program 131 cooperates with the arbitrary program to realize the processing according to this embodiment. In addition, some or all of the functions provided by the program 131 may be realized by a dedicated hardware circuit (for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array)).

[0057] The aggregation system 60 also has the hardware configuration shown in Fig. 2. Hereinafter, the CPU 101 included in the prediction system 10 will be referred to as "CPU101_1", and the CPU 101 included in the aggregation system 60 will be referred to as "CPU101_2". The program 131 included in the prediction system 10 will be referred to as "program 131_1", and the program 131 included in the aggregation system 60 will be referred to as "program 131_2".

[0058] <Functional configuration of the prediction system> 3 is a diagram illustrating an example of the functional configuration of a prediction system 10. As illustrated in FIG. 3, the prediction system 10 includes a calculation unit 13, a determination unit 14, a storage unit 15, an acquisition unit 16, a notification unit 17, an output unit 18, an adjustment unit 19, and a control unit 25.

[0059] The calculation unit 13 and the determination unit 14 are realized by the CPU 101_1 shown in FIG. 2 executing a program 131_1. The notification unit 17, the adjustment unit 19, and the control unit 25 are realized by the CPU 101_1 executing the program 131_1 and the communication interface 106. The acquisition unit 16 is realized by the CPU 101_1 executing the program 131_1 and the input interface 104. The output unit 18 is realized by the CPU 101_1 executing the program 131_1 and the display controller 105.

[0060] The storage unit 15 is realized by the memory 102 or the storage 103 (see FIG. 2) included in the prediction system 10. The storage unit 15 stores the production plan data 11 and the performance data 12.

[0061] As described above, the calculation unit 13 calculates the planned amount of power usage for a target time period based on the performance data 12 and the production plan data 11. For example, the calculation unit 13 sequentially selects a target time period from among 48 time periods on the following day, and calculates the planned amount of power usage for each of the 48 time periods. Alternatively, the calculation unit 13 sequentially selects a target time period from one or more time periods up to midnight on the current day, and calculates the planned amount of power usage for each of the one or more time periods.

[0062] As described above, the determination unit 14 determines the planned amount of power to be purchased from the power grid 6 during the target time period, based on the planned amount of power usage during the target time period and the power trading price during the target time period. Furthermore, the determination unit 14 further determines, based on the planned amount of power usage and the power trading price, the amount of power to be supplied by each of one or more power supply sources other than the power grid 6. In the present embodiment, the one or more power supply sources other than the power grid 6 include the PV panel 21 and the storage battery 22. That is, the determination unit 14 determines, of the planned amount of power usage, the amount to be supplied from the PV panel 21 and the amount to be supplied from the storage battery 22. In this way, the determination unit 14 determines the amounts (breakdown) to be supplied from the power grid 6, the PV panel 21, and the storage battery 22 for the planned amount of power usage calculated by the calculation unit 13.

[0063] The amount of power generated by the PV panel 21 depends on weather conditions. Therefore, the determination unit 14 determines the amount (breakdown) of the planned amount of power to be supplied from the power grid 6, the PV panel 21, and the storage battery 22 based on weather forecast information, the planned amount of power usage, and the power trading price. The weather forecast information is acquired from a weather forecast service (not shown) via a communication network.

[0064] The electricity trading price varies for each time period. Therefore, the determination unit 14 sets a priority for each of one or more time periods in 30-minute increments during a target period (for example, a period until midnight on the following day or the current day) based on the electricity trading price. The determination unit 14 then selects a target time period from the one or more time periods in order according to the priority. The determination unit 14 determines the planned amount of power to be purchased and the amount to be supplied by each of the PV panel 21 and the storage battery 22 for the target time period so as not to affect the planned amount of power to be purchased and the amount to be supplied by each of the PV panel 21 and the storage battery 22 determined for a time period with a higher priority than the target time period among the one or more time periods.

[0065] The determination unit 14 outputs to the control unit 25 the amounts of power that can be supplied by the PV panel 21 and the storage battery 22, which have been determined for each time period.

[0066] By knowing the fluctuation range of the planned power purchase amount of each consumer, the aggregator 4 can more easily adjust the balance between power supply and demand. For this reason, the determination unit 14 may further determine an adjustable amount of the planned power purchase amount. Specifically, the determination unit 14 determines an adjustable amount of the planned power purchase amount (hereinafter referred to as a "third adjustable amount") based on at least one of an adjustable amount of the production plan (hereinafter referred to as a "first adjustable amount") and an adjustable amount of power supplied from the private power generation system 20 (hereinafter referred to as a "second adjustable amount"). The second adjustable amount includes an adjustable amount of power supplied from the PV panel 21 (hereinafter referred to as a "fourth adjustable amount") and an adjustable amount of power supplied from the storage battery 22 (hereinafter referred to as a "fifth adjustable amount").

[0067] The acquisition unit 16 acquires the first adjustable amount, the fourth adjustable amount, and the fifth adjustable amount. For example, the planned production volume of a product indicated by the production plan may have a fluctuation range depending on the order volume, inventory volume, etc. Therefore, the acquisition unit 16 acquires the fluctuation range of the planned production volume input to the input device 120 as the first adjustable amount.

[0068] It is considered that a specified percentage of the amount of power generated by the PV panel 21 is set to be used for charging the storage battery 22. In this case, by changing the specified percentage, the amount of power that can be supplied from the PV panel 21 to one or more pieces of equipment 40 can be adjusted. Therefore, the acquisition unit 16 acquires the fourth adjustable amount based on the adjustment range of the specified percentage input to the input device 120.

[0069] The storage battery 22 is usually controlled so that the remaining amount of stored power does not fall below a predetermined lower limit. By changing the lower limit, the amount of power that can be supplied from the storage battery 22 to one or more pieces of equipment 40 can be adjusted. Therefore, the acquisition unit 16 acquires the fifth adjustable amount based on the adjustment range of the lower limit input to the input device 120.

[0070] The determination unit 14 determines the third adjustable amount based on the first adjustable amount, the fourth adjustable amount, and the fifth adjustable amount acquired by the acquisition unit 16.

[0071] The notification unit 17 notifies the aggregator 4 of notification data indicating information regarding the planned power purchase amount determined by the determination unit 14 for the time period included in the period in which a DR request can be accepted. This makes it easier for the aggregator 4 to adjust the balance between power supply and demand based on the notification data. The information regarding the planned power purchase amount includes, for example, at least one of the planned power purchase amount, the ratio of the planned power purchase amount to the contracted power, the difference between the contracted power and the planned power purchase amount, and the ratio of the difference to the contracted power. The contracted power is the largest value of the maximum power demand for each month in the past year including the current month. The maximum power demand is the largest value of the average power for every 30 minutes within the month.

[0072] The notification unit 17 may determine whether or not to notify the aggregator 4 of the notification data for each time period based on the electricity trading price.

[0073] Demand response (DR) includes up-driving DR and down-driving DR. Up-driving DR is activated to increase demand when the supply of electricity exceeds the demand. This allows excess output from renewable energy sources such as solar power generation to be effectively used to operate facilities or charge storage devices. Down-driving DR is activated to reduce demand when the supply of electricity is insufficient compared to the demand.

[0074] If a request for an upward DR is received when the electricity trading price is relatively high, the consumer will not benefit much. Therefore, the notification unit 17 determines not to notify the aggregator 4 of notification data for a time period when the electricity trading price is equal to or higher than a predetermined first threshold during a period when an upward DR is expected to be invoked. The period when an upward DR is expected to be invoked is determined based on, for example, the environment (weather, season, temperature, day of the week, etc.) during which a past upward DR was invoked.

[0075] If a request for a downward DR is received when the electricity trading price is relatively low, there is little benefit to the consumer. Furthermore, once a consumer cooperates with a downward DR, they will be unable to respond to a sudden increase in production. Alternatively, if cooperating with a downward DR requires adjustments such as a review of production plans, the consumer may have the disadvantage of having to make the adjustments. Therefore, the notification unit 17 determines not to notify the aggregator 4 of notification data for a time period when the electricity trading price is equal to or lower than a predetermined second threshold during a period when a downward DR is expected to be invoked. The period when a downward DR is expected to be invoked is determined, for example, based on the environment (weather, season, temperature, day of the week, etc.) during the period when a downward DR was invoked in the past.

[0076] The notification data may indicate the third adjustable amount in addition to the information about the planned power purchase amount, which makes it easier for the aggregator 4 to adjust the power supply and demand balance based on the third adjustable amount.

[0077] The output unit 18 outputs the electricity cost corresponding to the third adjustable amount. The electricity cost corresponding to the third adjustable amount is the remuneration amount received when responding to a DR request by the third adjustable amount. The calculation method of the remuneration amount depends on the contract between the aggregator 4 and the consumer. Therefore, the output unit 18 calculates the electricity cost according to a calculation method according to the contract details. For example, the output unit 18 calculates the electricity cost as the product of the third adjustable amount and the electricity trading price. The output unit 18 displays the calculated electricity cost on the display 122. This allows the consumer to confirm the remuneration amount received when responding to a DR request by the third adjustable amount.

[0078] When responding to a DR request from the aggregator 4, the adjustment unit 19 adjusts the planned amount of power usage so as to satisfy the DR request. The adjustment unit 19 may determine whether to respond to the DR request from the aggregator 4 in accordance with a user input. Alternatively, the adjustment unit 19 may automatically determine to respond to the DR request when a DR request is received for a time period for which the notification data has been notified to the aggregator 4.

[0079] The adjustment unit 19 determines whether or not adjustment of the planned amount of power usage is necessary based on the content of the DR request. For example, when the adjustment unit 19 receives a request for downward DR (a request for power saving) from the aggregator 4, it determines whether or not the relationship between the requested amount of power saving, the planned amount of power purchase, and the contracted power satisfies the following formula. Contracted power ≥ Planned power purchase amount + Requested power saving amount + Constant The constant is determined in advance, taking a margin into consideration. If the above formula is satisfied, the adjustment unit 19 determines that adjustment of the planned power usage is unnecessary. In other words, if the above formula is not satisfied, the adjustment unit 19 determines that adjustment of the planned power usage is necessary. For example, the aggregator 4 may make a DR request to change the demand amount including the third adjustable amount. Specifically, the aggregator 4 may request an amount of power saving that is greater than the difference between the planned power purchase amount indicated by the notification data and the contracted power. In this case, the adjustment unit 19 determines that adjustment of the planned power usage is necessary, and adjusts the planned power usage by correcting the planned production amount within the range of the first adjustable amount.

[0080] Alternatively, the adjusting unit 19 may reduce the amount of power purchased from the power grid 6 by adjusting the amount of power supplied from the PV panels 21 to the one or more facilities 40 within the range of the fourth adjustable amount. That is, the adjusting unit 19 may adjust the amount of planned power usage that is covered by the PV panels 21, instead of the planned power usage. Similarly, the adjusting unit 19 may reduce the amount of power purchased from the power grid 6 by adjusting the amount of power supplied from the storage battery 22 to the one or more facilities 40, within the range of the fifth adjustable amount. That is, the adjusting unit 19 may adjust the amount of planned power usage that is covered by the storage battery 22, instead of the planned power usage.

[0081] When the adjusting unit 19 adjusts the amount of power supplied by the PV panel 21 and the storage battery 22 for each time period, the adjusting unit 19 outputs the adjusted amount to the control unit 25.

[0082] For each time period, the control unit 25 receives from the determination unit 14 the amount of planned power usage that is to be supplied by the PV panels 21 and the storage battery 22. Furthermore, when the amount is adjusted by the adjustment unit 19, the control unit 25 receives the adjusted amount from the adjustment unit 19. The control unit 25 controls the output destination of the power generated by the PV panels 21 and the charging and discharging of the storage battery 22 so that the corresponding amount is supplied to one or more pieces of equipment 40 for each time period.

[0083] <Functional configuration of the aggregation system> Fig. 4 is a diagram illustrating an example of a functional configuration of an aggregation system 60. As illustrated in Fig. 4, the aggregation system 60 includes a determination unit 61 and a notification unit 62. The determination unit 61 and the notification unit 62 are realized by the CPU 101_2 that executes the program 131_2 illustrated in Fig. 2 and the communication interface 106.

[0084] The determination unit 61 determines whether to notify each facility 3 of a DR request based on the notification data received from each facility 3 and the planned amount of power supply from the power grid 6. The planned amount of power supply is notified to the aggregator 4 by the electricity retailer 2.

[0085] Specifically, the determination unit 61 determines whether to request DR depending on whether the planned power supply amount is in excess or shortage with respect to the maximum demand amount. The maximum demand amount is determined based on the total amount of contracted power for each consumer.

[0086] The determination unit 61 determines that a downward DR request is necessary when the planned power supply amount is insufficient relative to the maximum demand amount. The determination unit 61 determines whether a downward DR request is possible for each facility 3 based on the notification data received from the facility 3. For example, the determination unit 61 determines that a downward DR request is possible when the difference between the contracted power and the planned power purchase amount exceeds a predetermined third threshold. The determination unit 61 determines the amount of power saving to be requested for each facility 3 for which it has determined that a downward DR request is possible, based on the shortfall in the planned power supply amount relative to the maximum demand amount. The amount of power saving to be requested is determined so that it is equal to or less than the difference between the contracted power and the planned power purchase amount. Alternatively, when the notification data indicates a third adjustable amount, the determination unit 61 may adjust the planned power purchase amount by the third adjustable amount and determine the amount of power saving to be requested so that it is equal to or less than the difference between the contracted power and the adjusted planned power purchase amount.

[0087] The determination unit 61 determines that a request for an upward DR is necessary when the planned power supply amount is in excess of the maximum demand amount. The determination unit 61 determines whether or not an upward DR can be requested for each facility 3 based on notification data received from the facility 3. Specifically, the determination unit 61 determines whether or not an upward DR can be requested based on the third adjustable amount indicated by the notification data. The determination unit 61 determines the amount of demand increase to be requested for each facility 3 for which it has been determined that an upward DR can be requested, based on the excess of the planned power supply amount relative to the maximum demand amount. The amount of demand increase to be requested is determined so as to be equal to or less than the purchase-available amount, which will be described later, of the third adjustable amount.

[0088] The notification unit 62 notifies the prediction system 10 of the facility 3 for which it is determined that a DR request is possible of the DR request.

[0089] <Power network processing for spot market energy trading> FIG. 5 is a flowchart showing an example of a processing flow in an electricity network for electricity trading in the spot market.

[0090] First, in step S1, the CPU 101_1 of the prediction system 10 calculates the planned amount of power consumption for each time slot in 30-minute increments for the next day based on the actual power consumption data 12 of the facility 3 and the production plan of the product.

[0091] In the next step S2, the CPU 101_1 determines, for each time slot, the planned amount of power to be purchased from the power grid 6 based on the planned amount of power usage and the power trading price (spot market price).

[0092] In the next step S3, the CPU 101_1 calculates, for each time slot, a third adjustable amount of the planned amount of power purchase based on the first adjustable amount of the production plan and the second adjustable amount (fourth adjustable amount and fifth adjustable amount) of power supplied from the private power generation system 20. In step S3, the CPU 101_1 may calculate an electricity cost corresponding to the third adjustable amount based on the electricity trading price (spot market price) and display the electricity cost on the display 122.

[0093] In the next step S4, the CPU 101_1 determines whether or not there is a time slot during which notification to the aggregator 4 is necessary, based on the power trading price.

[0094] If there is a time period for which it is determined that notification to the aggregator 4 is necessary (YES in step S4), in step S5, the CPU 101_1 generates notification data indicating information regarding the planned amount of electricity to be purchased and the third adjustable amount for the time period, and notifies the aggregator 4 of the notification data.

[0095] If there is no time period in which it is determined that notification to the aggregator 4 is necessary (NO in step S4), the process ends.

[0096] In step S6 after step S5, the CPU 101_2 of the aggregation system 60 determines whether or not there is a time slot in which a DR request is necessary, based on the excess or shortage of the planned amount of power supply from the power grid 6 relative to the maximum demand.

[0097] If there is a time period in which a DR request is necessary (YES in step S6), in step S7, the CPU 101_2 notifies the prediction system 10 that has transmitted the notification data for the time period of the DR request. In the case of a downward DR, the CPU 101_2 notifies the amount of power saving to be requested. In the case of an upward DR, the CPU 101_2 notifies the amount of demand increase to be requested. If there is no time period in which a DR request is necessary (NO in step S6), the process ends.

[0098] In step S8 after step S7, the CPU 101_1 of the prediction system 10 that has received the DR request adjusts the planned amount of power usage so as to satisfy the contents of the DR request. Alternatively, the CPU 101_1 may adjust the amount of planned power usage that is covered by the PV panel 21 and the storage battery 22 so as to satisfy the contents of the DR request. After step S8, the process ends.

[0099] <Details of Step S1> Details of step S1 will be described with reference to Figures 6 to 10. Figure 6 is a diagram showing the transition of actual values ​​of power consumption on a certain day. Figure 6 shows a breakdown of power consumption by production equipment, power consumption by air conditioners, and power consumption by other equipment (such as lighting) for each one-hour time period. The production period is from 9:00 to 17:30.

[0100] As shown in Figure 6, the amount of power consumed by the production equipment increases during the manufacturing period. Also, during the manufacturing period, the amount of heat generated by the production equipment increases, so the amount of power consumed by the air conditioner also increases.

[0101] Outside of the manufacturing period, the power consumption of production equipment is not zero. This is because the production equipment consumes standby power even outside of the manufacturing period. Also, just before the start of the manufacturing period, the production equipment consumes a large amount of power to start up. Also, the power consumption of air conditioners and other equipment is not zero.

[0102] Fig. 7 is a diagram showing an example of performance data. Fig. 7 shows performance data 12 indicating the performance of power consumption on a certain day. As shown in Fig. 7, the performance data 12 includes performance data 12a for the manufacturing period when the product is being manufactured and performance data 12b for periods outside the manufacturing period.

[0103] The performance data 12a indicates, for each product lot, the item name, production volume, scheduled production start time, scheduled production end time, power consumption during the manufacturing period, process name, and equipment usage pattern. As shown in the figure, the equipment usage pattern may differ depending on the item. Therefore, the power consumption may vary depending on the item. Furthermore, the power consumption may also vary depending on the production volume.

[0104] The performance data 12b indicates the amount of power consumption and environmental information for each time period. The environmental information indicates, for example, weather, temperature, humidity, etc. Outside the production period, a fixed amount of power is consumed that does not directly contribute to the production of products. However, the amount of power consumption outside the production period may vary depending on the environment.

[0105] In this way, the total amount of power consumption of the facility 3 includes a variable portion that varies depending on the production conditions of the products and a fixed portion that does not vary depending on the production conditions of the products. Therefore, the CPU 101_1 of the prediction system 10 calculates the estimated amount of power consumption for each time period by using the performance data 12 and the production plan of the products, taking into account the variable portion and the fixed portion.

[0106] 8 is a flowchart showing the flow of the subroutine processing of step S1. First, in step S11, the CPU 101_1 of the prediction system 10 reads out the performance data 12. As described above, the performance data 12 includes performance data 12a for the manufacturing period and performance data 12b for periods other than the manufacturing period.

[0107] In the next step S12, the CPU 101_1 calculates a coefficient of variation a and a fixed portion b for each item of the product by using the performance data 12a.

[0108] 9 is a diagram illustrating the processing of step S12. For each product item, CPU 101_1 extracts data on the production lot of the item from performance data 12a. CPU 101_1 identifies a linear function that indicates the relationship between the production volume (X) and the power consumption (Y) indicated by the extracted data. CPU 101_1 determines the slope of the linear function as the "coefficient of variation a" and the Y intercept of the linear function as the "fixed portion b."

[0109] Returning to FIG. 8, in the next step S13, the CPU 101_1 reads out the production plan data 11 indicating the production plan for the next day.

[0110] Fig. 10 is a diagram showing an example of production plan data. As shown in Fig. 10, the production plan data 11 indicates a production schedule for product lots, and indicates, for each product lot, the item name, the planned production amount, the planned production start time, and the planned production end time.

[0111] Returning to FIG. 8, in the next step S14, the CPU 101_1 calculates the planned amount of power usage (α) for each time period in 30-minute increments during the period when the product is produced (manufacturing period) using the production plan data 11 and the coefficient of variation a and fixed portion b for each item.

[0112] Specifically, CPU 101_1 calculates, for each product lot, the planned power consumption (Y1=a×X1+b) for the period from the scheduled production start time to the scheduled production end time based on the coefficient of variation a and fixed portion b corresponding to the item in the product lot and the planned production volume (X1) of the product lot. CPU 101_1 calculates the planned power consumption (α) for each 30-minute time slot in the manufacturing period by integrating or dividing the planned power consumption (Y1) for each product lot. For example, CPU 101_1 divides the planned power consumption (Y1) for the period from the scheduled production start time of 9:00 to the scheduled production end time of 10:00 into the planned power consumption (α) for the time slot from 9:00 to 9:30 and the planned power consumption (α) for the time slot from 9:30 to 10:00. CPU 101_1 may divide the planned power consumption using a known interpolation method.

[0113] In the next step S15, the CPU 101_1 uses the performance data 12b to generate correlation information that defines the correlation between the environmental information and the fixed portion b outside the manufacturing period. The correlation information is typically a table or a trained model. For example, the CPU 101_1 may perform machine learning using pairs of environmental information and power consumption amounts for each time period indicated by the performance data 12b as training data, thereby generating a trained model that receives input of environmental information and outputs power consumption amounts.

[0114] In the next step S16, CPU 101_1 uses the correlation information to calculate the planned amount of power usage for each time period outside the manufacturing period of the next day. For example, CPU 101_1 acquires weather forecast information for each time period from a weather forecast center and inputs the weather forecast information into the correlation information as environmental information expected for that time period, thereby calculating the planned amount of power usage for that time period. After step S16, step S1 ends.

[0115] Note that the coefficient of variation a and the fixed portion b for each item do not fluctuate from day to day. Therefore, steps S11 and S12 may be performed only periodically (for example, seasonally). Similarly, the correlation information defining the correlation between the environmental information and the fixed portion b outside the manufacturing period also does not fluctuate from day to day. Therefore, step S15 may be performed only periodically (for example, seasonally).

[0116] <Details of Step S2> Details of step S2 will be described with reference to Fig. 11 to Fig. 13. Fig. 11 is a diagram showing parameters used in step S2. As shown in Fig. 11, the CPU 101_1 uses, for step S2, the planned amount of power usage (α), the predicted amount of power generation (β) of the PV panel 21, the remaining amount of the storage battery 22 (hereinafter referred to as "remaining amount of stored power (γ)"), and the power trading price (P). Furthermore, for step S2, the CPU 101_1 uses a predetermined reference price.

[0117] The CPU 101_1 may use any one of the following values ​​(a) to (f) as the reference price. Value (a) is the median of the electricity trading price for 48 time slots on the previous day. Value (b) is the average value of the electricity trading price in a specific time zone on the previous day. The specific time zone is determined based on past trends in electricity trading prices and includes multiple consecutive time periods in which fluctuations in electricity trading prices are small. The value (c) is a moving average value (weekly, monthly, quarterly or annually) obtained from past electricity trading prices. The value (d) is the average value (weekly, monthly, quarterly or annually) obtained from past electricity trading prices. The value (e) is a value input by the user. The user can input a value appropriate for the consumer based on the trends in the electricity trading price.

[0118] 12 is a flowchart showing the flow of the subroutine processing of step S2. First, in step S21, the CPU 101_1 of the prediction system 10 acquires, from the power trading market 5, the power trading price (P) (spot market price) for each time slot of the next day.

[0119] In the next step S22, the CPU 101_1 acquires weather forecast information for each time zone of the next day from a weather forecast service, and calculates the predicted power generation amount (β) of the PV panel 21 for each time zone based on the weather forecast information.

[0120] In the next step S23, the CPU 101_1 calculates an initial value of the remaining amount of stored power (γ) for each time slot of the next day. Specifically, the CPU 101_1 calculates the initial value of the remaining amount of stored power (γ) for each time slot based on the following hypothetical conditions: (Tentative terms) The remaining battery power (γ) for the first time period (0:00~0:30) is set to the same as the remaining battery power (γ) for the last time period (23:30~24:00) of the previous day. · The planned amount of electricity consumption (α) is covered entirely by the amount of electricity purchased from power grid 6. The predicted power generation amount (β) of the PV panel 21 is used to charge the storage battery 22.

[0121] In the next step S24, the CPU 101_1 sets a priority for each time slot based on the power trading price (P). Specifically, the CPU 101_1 sets a priority so that the higher the power trading price (P), the higher the priority.

[0122] In the next step S25, the CPU 101_1 selects the time slot with the highest priority.

[0123] In the next step S26, the CPU 101_1 adjusts the breakdown of the power supply sources (the power grid 6, the PV panel 21, and the storage battery 22) that cover the planned amount of power usage for the selected time period.

[0124] In the next step S27, CPU 101_1 determines whether or not there is an unselected time slot. If there is an unselected time slot (YES in step S27), CPU 101_1 selects a time slot with the next highest priority in step S28. After step S28, the process returns to step S26. If there is no unselected time slot (NO in step S27), step S2 ends.

[0125] FIG. 13 is a flowchart showing the flow of the subroutine processing of step S26 shown in FIG.

[0126] First, in step S31, the CPU 101_1 determines whether or not the selected time period is a time period during which power generation is possible for the PV panel 21. Specifically, the CPU 101_1 may determine whether or not the predicted power generation amount (β) of the PV panel 21 for the selected time period exceeds 0.

[0127] If YES in step S31, in step S32, the CPU 101_1 determines whether or not the electricity trading price (P) in the selected time slot is equal to or lower than a predetermined reference price.

[0128] If YES in step S32, in step S33, the CPU 101_1 determines whether or not the predicted power generation amount (β) of the PV panel 21 in the selected time period is equal to or greater than the planned power usage amount (α) in the selected time period.

[0129] If YES in step S33, in step S34, the CPU 101_1 selects the PV panel 21 as a candidate for all supply sources of the estimated amount of power usage (α) in the selected time period.

[0130] If NO in step S33, in step S35, the CPU 101_1 determines whether or not the remaining amount of stored electricity (γ) in the selected time period is equal to or greater than a predetermined lower limit (L).

[0131] If the result is NO in step S35, in step S36, the CPU 101_1 selects the PV panel 21 and the power grid 6 as candidates for the supply source of the planned power usage amount (α) for the selected time period. The CPU 101_1 sets a candidate for the amount of planned power usage amount (α) that will be covered by the PV panel 21 as the predicted power generation amount (β), and sets a candidate for the amount of planned power usage amount (α) that will be covered by the power grid 6 as (α-β).

[0132] If YES in the step S35, the CPU 101_1 determines in a step S37 whether or not (γ-L)≧(α-β) is satisfied.

[0133] If the determination is YES in step S37, in step S38, the CPU 101_1 selects the PV panel 21 and the storage battery 22 as candidates for the supply source of the planned power usage amount (α) for the selected time period. The CPU 101_1 sets a candidate for the amount of planned power usage amount (α) that will be covered by the PV panel 21 as the predicted power generation amount (β), and sets a candidate for the amount of planned power usage amount (α) that will be covered by the storage battery 22 as (α-β).

[0134] If the result is NO in step S37, in step S39, the CPU 101_1 selects the PV panel 21, the storage battery 22, and the power grid 6 as candidates for the supply source of the planned power usage amount (α) for the selected time period. The CPU 101_1 sets a candidate for the amount of planned power usage amount (α) that will be covered by the PV panel 21 as the predicted power generation amount (β), sets a candidate for the amount of planned power usage amount (α) that will be covered by the storage battery 22 as (γ-L), and sets a candidate for the amount of planned power usage amount (α) that will be covered by the power grid 6 as (α-β-(γ-L)).

[0135] If NO at step S31 or step S32, at step S40, the CPU 101_1 determines whether or not the remaining amount of stored electricity (γ) in the selected time period is equal to or greater than a predetermined lower limit (L).

[0136] If YES in step S40, the CPU 101_1 determines in step S41 whether or not (γ-L)≧α is satisfied.

[0137] If YES in step S41, in step S42, the CPU 101_1 selects the storage battery 22 as a candidate for all supply sources of the estimated amount of power usage (α) in the selected time period.

[0138] If the result is NO in step S41, in step S43, the CPU 101_1 selects the storage battery 22 and the power grid 6 as candidates for the supply source of the planned power usage amount (α) for the selected time period. The CPU 101_1 sets the candidate for the amount of planned power usage amount (α) that is covered by the storage battery 22 as (γ-L), and sets the candidate for the amount of planned power usage amount (α) that is covered by the power grid 6 as (α-(γ-L)).

[0139] If NO in step S40, in step S44, the CPU 101_1 selects the electric power system 6 as a candidate for all supply sources of the planned amount of electric power usage (α) in the selected time slot.

[0140] In step S45 after steps S34, S36, S38, S39, and S42 to S44, CPU 101_1 determines whether or not the breakdown of power supply sources determined for a time slot higher in priority than the selected time slot is affected when the selected candidate is reflected. CPU 101_1 determines that there is an impact when the breakdown of power supply sources determined for a time slot higher in priority than the selected time slot cannot be realized.

[0141] When a candidate including the storage battery 22 is reflected as a power supply source, the remaining amount of stored power (γ) decreases in a time period after the selected time period. Therefore, even though the storage battery 22 is determined as a supply source for the planned power usage amount (α) in a time period after the selected time period and having a higher priority than the selected time period, a situation may arise in which the planned power usage amount (α) cannot be covered by the power supplied from the storage battery 22. In such a case, the CPU 101_1 determines that there is an impact on the breakdown of power supply sources determined for the time period having a higher priority than the selected time period.

[0142] If YES in step S45, in step S46, the CPU 101_1 rejects the candidates selected in steps S34, S36, S38, S39, and S42 to S44. That is, the CPU 101_1 does not adjust the breakdown of the power supply source for the selected time period.

[0143] If NO in step S45, in step S47, CPU 101_1 reflects the candidates selected in steps S34, S36, S38, S39, S42 to S44. That is, CPU 101_1 adjusts the breakdown of the power supply source for the selected time period so that it matches the selected candidate. Furthermore, CPU 101 adjusts the remaining amount of stored power (γ) for the time period after the selected time period in accordance with the adjustment of the selected time period.

[0144] <Details of Step S3> Details of step S3 will be described with reference to Figures 14 and 15. Figure 14 is a flowchart showing the flow of the subroutine processing of step S3. Figure 15 is a diagram explaining the processing of step S3. Steps S51 to S54 in Figure 15 are executed for each time period.

[0145] First, in step S51, the CPU 101_1 of the prediction system 10 acquires a first adjustable amount of the production plan. The first adjustable amount includes an increaseable amount and a decreaseable amount of the production amount.

[0146] In the next step S52, the CPU 101_1 acquires a fourth adjustable amount (B) of the power A2 supplied from the PV panel 21. The fourth adjustable amount (B) includes an increaseable amount (B1) and a reductionable amount (B2).

[0147] In the next step S53, the CPU 101_1 acquires a fifth adjustable amount (C) of power supplied from the storage battery 22. The fifth adjustable amount (C) includes an increaseable amount (C1) and a reductionable amount (C2).

[0148] In the next step S54, the CPU 101_1 calculates a third adjustable amount (D) of the planned amount of power purchase based on the first adjustable amount, the fourth adjustable amount (B), and the fifth adjustable amount (C). The third adjustable amount (D) includes a purchase-increase-possible amount (D1) and a reduction-possible amount (D2). The purchase-increase-possible amount (D1) is used for raising the DR. The reduction-possible amount (D2) is used for lowering the DR.

[0149] Specifically, the CPU 101_1 calculates a sixth adjustable amount (A) of the scheduled power usage amount by multiplying the first adjustable amount by the above-mentioned coefficient of variation α. ​​The sixth adjustable amount (A) includes a possible increase amount (A1) and a possible reduction amount (A2). The CPU 101_1 calculates the sum (A1+B2+C2) of the possible increase amount (A1), the possible reduction amount (B2), and the possible reduction amount (C2) as the possible additional purchase amount (D1). The CPU 101_1 calculates the sum (A2+B1+C1) of the possible reduction amount (A2), the possible increase amount (B1), and the possible increase amount (C1) as the possible reduction amount (D2).

[0150] <Power network processing for intraday energy trading> FIG. 16 is a flowchart showing an example of a processing flow in an electricity network for electricity trading in an intraday market.

[0151] First, in step S61, the CPU 101_1 of the prediction system 10 reflects the latest actual result of the power consumption amount in the actual result data 12. Furthermore, the CPU 101_1 acquires the production plan data 11 indicating the latest production plan.

[0152] Next, the CPU 101_1 executes steps S1a to S3a in order. Step S1a differs from step S1 above only in that step S1a targets each 30-minute time slot from the current time to midnight on the current day. Step S2a differs from step S2 above only in that i) step S2a targets each 30-minute time slot from the current time to midnight on the current day, ii) the current market price is used as the electricity trading price instead of the spot market price, and iii) the current amount of charge of the storage battery 22 is used as the initial value of the remaining amount of stored power (γ). The current market price corresponds to the "latest electricity trading price" in the present disclosure. Step S3a differs from step S3 above only in that i) step S1a targets each 30-minute time slot from the current time to midnight on the current day, and ii) the current market price is used as the electricity trading price instead of the spot market price. Therefore, detailed description of steps S1a to S3a will be omitted.

[0153] In the next step S62, the CPU 101_1 compares, for each time period, the planned amount of electricity to be purchased calculated in step S2a with the planned amount of electricity to be purchased determined for the spot market (the planned amount of electricity to be purchased determined in step S2 of the flow shown in Figure 5), and calculates the difference between the two.

[0154] In the next step S63, the CPU 101_1 determines whether or not there is a time period in which the difference exceeds a predetermined fourth threshold value.

[0155] If there is no time period in which the difference exceeds the predetermined fourth threshold (NO in step S53), the process returns to step S61.

[0156] If there is a time period in which the difference exceeds a predetermined fourth threshold (YES in step S53), CPU 101_1 determines that time period as a time period in which notification to aggregator 4 is required, and executes step S5a. Step S5a is the same as step S5 described above. Therefore, detailed description of step S5a will be omitted. After step S5a, steps S6a to S8a are executed in order. Steps S6a to S8a are the same as steps S6 to S8 described above. Therefore, detailed description of steps S6a to S8a will be omitted.

[0157] As shown in FIG. 16, the CPU 101_1 operating as the determination unit 14 periodically updates the planned amount of electricity to be purchased based on the planned amount of electricity usage calculated based on the latest production plan, the latest electricity trading price, and the latest status of one or more electricity supply sources.

[0158] <Modification> In the above description, the prediction system 10 is assumed to be installed in the facility 3 (consumer). However, all or part of the prediction system 10 does not have to be installed in the facility 3. For example, the determination unit 14 may be installed outside the facility 3.

[0159] Furthermore, the prediction system 10 may be shared by a plurality of facilities 3. In this case, the prediction system 10 calculates the planned amount of power usage in each time period for each of the plurality of facilities 3, and determines the planned amount of power purchase in each time period.

[0160] Electricity trading prices may differ from region to region. Therefore, the adjustment unit 19 of the forecasting system 10 shared by multiple facilities 3 may adjust the production plans of the multiple facilities 3 according to the electricity trading prices in the regions to which the multiple facilities 3 belong. For example, the adjustment unit 19 reduces the planned production volume of the facilities 3 that belong to regions where the electricity trading prices are relatively high. This allows the facilities 3 that belong to regions where the electricity trading prices are relatively high to easily receive higher rewards by cooperating with the request for downward DR.

[0161] CPU 101_1 may omit some of the processes in the subroutine of step S26 shown in Fig. 13. For example, if NO in step S33, CPU 101_1 may omit steps S35 to S39 and shift the process to step S40. If YES in step S40, CPU 101_1 may omit steps S41 and S43 and shift the process to step S42.

[0162] The private power generation system 20 may have only the PV panel 21 and may not have the storage battery 22. In this case, the determination unit 14 determines the amount of the planned power usage that will be covered by the power grid 6 (planned amount of power purchase) and the amount that will be covered by the PV panel 21.

[0163] Alternatively, the facility 3 may be provided with only the storage battery 22 instead of the private power generation system 20. In this case, the determination unit 14 determines the amount of the planned power usage that will be covered by the power grid 6 (planned amount of power purchase) and the amount that will be covered by the storage battery 22.

[0164] The CPU 101_1 operating as the determination unit 14 may use the incentive price provided by the aggregator 4 as the electricity trading price. That is, the incentive price is an example of the "electricity trading price" of the present disclosure. The incentive price is determined for each time period in accordance with the contract between the consumer and the aggregator 4.

[0165] §3 Supplementary Note As described above, the present embodiment includes the following disclosure.

[0166] (Configuration 1) A forecasting system (10) for forecasting the power demand of each of one or more facilities (3) that produce a product, comprising: a calculation unit (13, 101_1) that calculates a planned amount of power consumption for a target time period based on actual power consumption data (12) and a production plan for the product for each of the one or more facilities (3); A prediction system (10) comprising: a determination unit (14, 101_1) that determines, for each of the one or more facilities (3), a planned amount of electricity to be purchased from the power grid during the target time period based on the planned amount of electricity usage and the electricity trading price during the target time period.

[0167] (Configuration 2) The prediction system (10) according to configuration 1, wherein the determination unit (14, 101_1) further determines, based on the planned amount of power usage and the power trading price, an amount of the planned amount of power usage that will be supplied by each of one or more power supply sources (21, 22) separate from the power grid, and the one or more power supply sources (21, 22) include at least one of a private power generation device (21) and a power storage device (22).

[0168] (Configuration 3) The one or more power supply sources include a solar power generation device (21); The prediction system (10) according to configuration 2, wherein the determination unit (14, 101_1) determines the planned amount of power purchase and the amount of each of the one or more power supply sources (21, 22) based on weather forecast information, the planned amount of power usage, and the power trading price.

[0169] (Configuration 4) The determination unit (14, 101_1) setting a priority for each of a plurality of time periods included in a target period based on the electricity trading price; selecting the target time period from the plurality of time periods in order according to the priority; The prediction system (10) according to configuration 2 or 3, wherein the planned amount of power to be purchased and the amount of each of the one or more power supply sources are determined for the target time period so as not to affect the planned amount of power to be purchased and the amount of each of the one or more power supply sources determined for a time period among the plurality of time periods that has a higher priority than the target time period.

[0170] (Configuration 5) 5. The prediction system (10) according to any one of configurations 1 to 4, further comprising a notification unit (17, 101_1, 106) that notifies the aggregator (4) of notification data indicating information related to the planned amount of power purchase.

[0171] (Configuration 6) the determination unit (14, 101_1) further determines a third adjustable amount of the planned amount of power purchase based on at least one of a first adjustable amount of the production plan and a second adjustable amount of power supplied from the one or more power supply sources; The prediction system (10) The prediction system (10) according to any one of configurations 2 to 4, further comprising a notification unit (17, 101_1, 106) that notifies the aggregator (4) of notification data indicating information regarding the planned amount of electricity purchased and the third adjustable amount.

[0172] (Configuration 7) 7. The prediction system (10) according to configuration 5 or 6, wherein the notification unit (17, 101_1, 106) determines whether to notify the aggregator (4) of the notification data based on the electricity trading price.

[0173] (Configuration 8) The prediction system (10) according to configuration 6, further comprising an output unit (18, 101_1, 105) that outputs the power cost corresponding to the third adjustable amount.

[0174] (Configuration 9) The prediction system (10) according to any one of configurations 2 to 4, wherein the determination unit (14, 101_1) periodically updates the planned amount of electricity purchase based on the planned amount of electricity usage calculated based on a latest production plan, the latest electricity trading price, and the latest status of the one or more electricity supply sources.

[0175] (Configuration 10) The prediction system (10) according to any one of configurations 1 to 9, further comprising an adjustment unit (19, 101_1) that adjusts the planned amount of power usage so as to satisfy a demand response request from an aggregator (4) when the request is met.

[0176] (Configuration 11) The one or more facilities (3) include a plurality of facilities, 10. The forecasting system (10) according to any one of configurations 1 to 9, further comprising an adjusting unit (19, 101_1) that adjusts the production plans of the plurality of facilities in accordance with the electricity trading price.

[0177] (Configuration 12) An aggregation system (60) in communication with the prediction system (10) according to any one of configurations 5 to 7, An aggregation system (60) comprising a determination unit (61, 101_2) that determines whether or not to request a demand response for each of the one or more facilities (3) based on the notification data and the planned amount of power supply from the power grid.

[0178] (Configuration 13) A method for forecasting the electricity demand of a facility (3) that produces a product, comprising: A processor (101_1) calculates (S1) a planned amount of power consumption for the facility (3) in a target time period based on actual power consumption data and a production plan for the product; The method comprises the processor (101_1) determining (S2) a planned amount of electricity to be purchased from the power grid for the facility (3) during the target time period based on the planned amount of electricity usage and the electricity trading price for the target time period.

[0179] (Configuration 14) A program (131_1) for causing a computer to execute a method for predicting power demand of a facility (3) that produces a product, the method comprising: Calculating (S1) a planned amount of power consumption for the facility (3) during a target time period based on actual power consumption data and a production plan for the product; A program (131_1) comprising determining (S2) a planned amount of electricity to be purchased from the power grid during the target time period for the facility (3) based on the planned amount of electricity usage and the electricity trading price during the target time period.

[0180] Although the embodiments of the present invention have been described, the embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present invention is defined by the claims, and it is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0181] 1 Power network, 2 Electricity retailer, 3 Facility, 4 Aggregator, 5 Energy trading market, 6 Power system, 10 Forecasting system, 11 Production plan data, 12, 12a, 12b Actual data, 13 Calculation unit, 14 Decision unit, 15 Memory unit, 16 Acquisition unit, 17, 62 Notification unit, 18 Output unit, 19 Adjustment unit, 20 Self-power generation system, 21 PV panel, 22 Storage battery, 25 Control unit, 30 Energy management device, 40 Equipment, 50 Power meter, 60 Aggregation system, 61 Judgment unit, 101, 101_1, 101_2 CPU, 102 Memory, 103 Storage, 104 Input interface, 105 Display controller, 106 Communication interface, 107 Data reader / writer, 108 Bus, 120 Input device, 122 Display, 124 Storage media, 131,131_1,131_2 programs.

Claims

1. 1. A forecasting system for forecasting an electrical power demand for each of one or more facilities that produce a product, comprising: a calculation unit that calculates a planned amount of power usage during a target time period for each of the one or more facilities based on actual power consumption data and a production plan for the product; a determination unit that determines a planned amount of electricity to be purchased from the power grid during the target time period for each of the one or more facilities based on the planned amount of electricity usage and an electricity trading price for the target time period.

2. 2. The prediction system of claim 1, wherein the determination unit further determines, based on the planned amount of power usage and the power trading price, an amount of the planned amount of power usage that will be covered by each of one or more power supply sources separate from the power grid, and the one or more power supply sources include at least one of a private power generation device and a power storage device.

3. the one or more power sources include a solar power generation device; The prediction system according to claim 2 , wherein the determination unit determines the planned amount of power purchase and the amount of each of the one or more power supply sources based on weather forecast information, the planned amount of power usage, and the power trading price.

4. The determination unit is setting a priority for each of a plurality of time periods included in a target period based on the electricity trading price; Selecting the target time slots from the plurality of time slots in order according to the priority; The prediction system according to claim 2 or 3, wherein the planned amount of electricity to be purchased and the amount of each of the one or more power supply sources are determined for the target time period so as not to affect the planned amount of electricity to be purchased and the amount of each of the one or more power supply sources determined for a time period among the plurality of time periods that has a higher priority than the target time period.

5. The prediction system according to claim 1 , further comprising a notification unit that notifies an aggregator of notification data indicating information related to the planned amount of power purchase.

6. The determination unit further determines a third adjustable amount of the planned power purchase amount based on at least one of a first adjustable amount of the production plan and a second adjustable amount of power supplied from the one or more power supply sources; The prediction system comprises: The prediction system according to claim 2 , further comprising a notification unit configured to notify an aggregator of notification data indicating information related to the planned amount of power purchase and the third adjustable amount.

7. The prediction system according to claim 5 , wherein the notification unit determines whether or not to notify the aggregator of the notification data based on the power trading price.

8. The prediction system of claim 6 , further comprising an output unit that outputs a power cost corresponding to the third adjustable amount.

9. 3. The prediction system according to claim 2, wherein the determination unit periodically updates the planned amount of electricity purchased based on the planned amount of electricity usage calculated based on a latest production plan, the latest electricity trading price, and the latest status of the one or more electricity supply sources.

10. The prediction system according to claim 1 , further comprising an adjustment unit that adjusts the planned amount of power usage so as to satisfy a demand response request from an aggregator when the request is responded to.

11. The one or more facilities may include a plurality of facilities; The prediction system according to claim 1 , further comprising an adjustment unit that adjusts the production plans of the plurality of facilities in response to the electricity trading price.

12. An aggregation system in communication with the prediction system of claim 5 or 6, comprising: an aggregation system comprising a determination unit that determines whether or not to request a demand response for each of the one or more facilities based on the notification data and a planned amount of power supply from the power grid.

13. 1. A method for forecasting electrical power demand at a facility that produces a product, comprising: A processor calculates a planned amount of power usage for the facility during a target time period based on actual power consumption data and a production plan for the product; The method comprises the processor determining, for the facility, a planned amount of electricity to be purchased from a power grid during the target time period based on the planned amount of electricity usage and an electricity trading price for the target time period.

14. A program for causing a computer to execute a method for predicting power demand at a facility that produces a product, the method comprising: Calculating a planned amount of power usage for the facility during a target time period based on actual power consumption data and a production plan for the product; determining, for the facility, a planned amount of electricity to be purchased from the power grid during the target time period based on the planned amount of electricity usage and an electricity trading price for the target time period.

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