Electricity bill prediction system, electricity bill prediction method, and program

Abstract

To provide an electricity bill prediction system that predicts an electricity bill for equipment used by a user as an electricity forecast.SOLUTION: An electricity bill prediction system, which predicts an electricity bill for equipment used by a user, acquires an electricity usage amount of the user, acquires unit price data that changes every hour during a prediction period from market information, calculates, on the basis of the unit price data, the electricity usage amount, and the period, the electricity bill of the user for the period, and outputs the calculated electricity bill for the period.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technique that is effective for predicting electricity costs for facilities used by users. [Background technology]

[0002] BACKGROUND ART Conventionally, it is known that electric power companies and the like publish electricity rates in the electricity market on a daily basis (for example, see Non-Patent Document 1). [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] LOOOP Denki, "Electricity Forecast | LOOOP Denki Official Website", [online], [Retrieved December 11, 2023], Internet<URL:https: / / looop-denki.com / home / denkiforecast / > Summary of the Invention [Problem to be solved by the invention]

[0004] However, such electricity cost forecasts merely show fluctuations in electricity costs over time, as users at home, businesses, factories, etc. want to know how much electricity their equipment will cost on a monthly billing basis, which is something they are familiar with.

[0005] An object of the present invention is to provide an electricity bill prediction system, an electricity bill prediction method, and a program that are capable of predicting the electricity bill for equipment used by a user as an electricity forecast. [Means for solving the problem]

[0006] The present invention provides an electricity bill prediction system for predicting the electricity bill of equipment used by a user, a usage amount acquiring unit that acquires the amount of power usage of the user; a unit price acquisition unit that acquires unit price data that changes over time during a prediction period from market information; a calculation unit that calculates the electricity bill of the user for the period based on the unit price data, the amount of electricity used, and the period; an output unit that outputs the calculated electricity cost for the period; An electricity bill prediction system is provided.

[0007] According to the present invention, it is possible to predict the electricity charges for the equipment used by the user himself / herself as an electricity forecast.

[0008] Although the present invention is categorized as a system, the same effects and advantages can be obtained even when it is a method or a program. [Effects of the Invention]

[0009] According to the present invention, it is possible to predict the electricity charges for the equipment used by the user himself / herself as an electricity forecast. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an overview of an electricity bill prediction system 1. [Figure 2] FIG. 1 is a diagram illustrating a functional configuration of an electricity bill prediction system 1. [Figure 3] FIG. 10 is a flowchart showing a prediction result output process executed by the user terminal 10. [Figure 4] 10 is a flowchart showing an electricity forecast output process executed by the user terminal 10. FIG. [Figure 5] 10 is a flowchart showing a smart usage output process executed by the user terminal 10. FIG. [Figure 6] 1 is a diagram schematically illustrating an example of a UI output by the user terminal 10. FIG. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments of the present invention (hereinafter referred to as "embodiments") will be described in detail with reference to the accompanying drawings. In the following drawings, the same elements are designated by the same numbers or symbols throughout the description of the embodiments.

[0012] [Outline of Electricity Bill Prediction System 1] 1 is a schematic diagram for explaining an overview of an electricity bill prediction system 1. Components of the electricity bill prediction system 1 will be described based on FIG. The electricity bill prediction system 1 is a system that predicts the electricity bill of equipment used by a user, and is made up of at least a user terminal 10 used by the user. The user terminal 10 is a terminal device used by a user, and is, for example, a mobile terminal such as a mobile phone, a smartphone, or a tablet terminal, or a wearable terminal such as a smart watch, smart glasses, or an HMD (Head Mounted Display). In addition to the user terminal 10 described above, the electricity bill prediction system 1 may also include other terminals and devices such as a billing management system managed and operated by an electric power company, and a computer that manages an external database (hereinafter, the database may also be simply referred to as DB) in which market information summarizing the unit price (yen / kWh) of electricity by day and time period at each electric power company is registered, and the number, type and functions thereof are not particularly limited and can be designed as appropriate.

[0013] An outline of the processing steps performed by the electricity charge prediction system 1 when predicting the electricity charge for the equipment used by the user will be described.

[0014] The user terminal 10 acquires the amount of power used by the user (step S1). The user terminal 10 acquires the user's power usage from a billing management system managed and operated by an electric utility. The user terminal 10 may be configured to acquire power usage data stored in advance or power usage data input by the user. The billing management system also stores data other than power usage data, such as set electricity charges and government subsidies. Data on set charges, government subsidies, etc. is updated regularly.

[0015] The user terminal 10 acquires unit price data that changes with time during the prediction period from market information (step S2). The user terminal 10 acquires the unit price data from an external database in which market information is registered, via a billing management system. The user terminal 10 may be configured to acquire the unit price data from pre-stored market information or market information input by a user. The user terminal 10 may also be configured to acquire the unit price data directly, without going through a billing management system.

[0016] The user terminal 10 calculates the electricity bill for the user for this period based on the unit price data, the amount of electricity used, and the period (step S3). The user terminal 10 calculates the average power consumption based on the power consumption for the most recent two weeks, multiplies the calculated average by the number of days remaining in the period, and calculates the power consumption for the remaining days in the period. The user terminal 10 multiplies the power consumption for the remaining days in the period by the power supply fee and the area-specific fixed metered fee to calculate the electricity bill for the remaining days in the period. The user terminal 10 adds up the electricity charge for the remaining days of the calculated period, the electricity charge for the elapsed days of the calculated period, and a specified amount (renewable energy generation promotion levy, fuel cost adjustment amount, etc.), and calculates the user's electricity charge for this period.

[0017] The user terminal 10 outputs the calculated electricity bill for the period (step S4). The user terminal 10 displays the calculated electricity charge for the period on a predetermined UI via a predetermined application, and outputs the calculated electricity charge for the period.

[0018] The above is an overview of the electricity bill prediction system 1. According to the present electricity charge prediction system 1, it is possible to predict the electricity charge for the equipment used by the user himself / herself as an electricity forecast.

[0019] [Device configuration] 2 is a block diagram showing the configuration of the electricity bill prediction system 1. The device configuration of the electricity bill prediction system 1 will be described with reference to FIG. The electricity bill prediction system 1 is a system for predicting the electricity bill of the equipment used by the user, and is configured by at least a user terminal 10. The electricity bill prediction system 1 is a system in which a user terminal 10 is connected via a network such as a public line network so as to be able to communicate data with a billing management system (not shown) managed and operated by an electric utility, a computer (not shown) that manages an external database in which market information summarizing the unit prices (yen / kWh) of electricity by day and time period for each electric utility is registered, and the like. In addition to the user terminal 10, the electricity bill prediction system 1 may also include other terminals and devices such as a billing management system managed and operated by an electric utility, and a computer that manages an external database in which market information summarizing the unit prices (yen / kWh) of electricity by day and time period for each electric utility is registered, and the number, types and functions of the other terminals and devices can be designed as appropriate.

[0020] The user terminal 10 is a terminal device used by a user, and may be a mobile terminal or a wearable terminal as described above. The user terminal 10 has a terminal control unit including a CPU (Central Processing Unit), GPU (Graphics Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), etc., and a communication unit including a device that enables communication with other terminals and devices, a usage acquisition unit that acquires the user's electricity usage, and a unit price acquisition unit that acquires unit price data that changes over time during the predicted period from market information. The user terminal 10 includes a data storage unit such as a semiconductor memory or a recording medium as a memory unit. The user terminal 10 includes an input / output unit, which receives predetermined inputs, various devices for inputting and outputting various data, a calculation unit that calculates the user's electricity bill for a period based on unit price data, electricity usage, and the period, and an output unit that outputs the electricity bill for the calculated period.

[0021] In the user terminal 10, the control unit reads a predetermined program, and in cooperation with the communication unit, realizes a contract acquisition module, a usage amount acquisition module, and a unit price acquisition module. In addition, in the user terminal 10, the control unit reads a predetermined program, thereby realizing a storage module in cooperation with the storage unit. In addition, in the user terminal 10, the control unit reads a predetermined program, thereby realizing a calculation module, an output module, and a specific module in cooperation with the input / output unit.

[0022] Hereinafter, each process executed by the electricity cost prediction system 1 will be described together with the process executed by each of the modules described above. In this specification, each module may execute its processing content as its own function, or may execute its processing content via a predetermined application. In each process described below, the user terminal 10 may be in a state where it has previously received input from the user regarding the launch of a predetermined application for predicting the electricity bill for the equipment used by the user (such as tapping on a predetermined icon located on the home screen of the user terminal 10) and has already launched the corresponding application, or it may be in a state where it has received input from the user regarding the launch of a predetermined application for predicting the electricity bill for the equipment used by the user (such as tapping on a predetermined icon located on the home screen of the user terminal 10) and has already launched the corresponding application at a predetermined timing (such as when the user wishes to view the electricity bill).

[0023] [Prediction result output process executed by user terminal 10] The prediction result output process executed by the user terminal 10 will be described with reference to Fig. 3. This figure is a diagram showing a flowchart of the prediction result output process executed by the user terminal 10. This prediction result output process includes details of the usage amount acquisition process (step S1) that acquires the user's electricity usage amount described above, the unit price acquisition process (step S2) that acquires unit price data that changes with time during the prediction period from market information, the calculation process (step S3) that calculates the user's electricity bill for this period based on the unit price data, the electricity usage amount, and the period, and the output process (step S4) that outputs the calculated electricity bill for the period.

[0024] The contract acquisition module acquires the contract data of the user (step S10). Contract data is data related to the user's electricity contract information, such as business operator information (business operator name, address, etc.), supply point identification number, rate menu (rate plan (minimum rate, fixed rate by area, etc.)), options, contract conclusion date, supply start date, contract period, fuel cost adjustment amount, direct debit discount amount, and renewable energy generation promotion levy. The contract acquisition module accesses the billing management system managed and operated by the electric utility at a predetermined timing (when the processing of step S13 described below is executed, at a predetermined time or timing, etc.) and acquires the contract data of the relevant user from this billing management system. The user terminal 10 may be configured to store a DB in which contract data is registered in advance using a storage module, and to acquire the user's contract data from this stored DB using a contract acquisition module.The user terminal 10 may also be configured to accept input related to contract data from a user into a predetermined input form, drop-down list, etc. (such as direct input of text into an input form or selection input from options in a drop-down list), and to acquire the accepted input content as the user's contract data using the contract acquisition module.The user terminal 10 may also acquire the user's contract data using methods other than those mentioned above.

[0025] The usage amount obtaining module obtains the amount of power usage of the user (step S11). The amount of power usage is based on, for example, the actual power usage for the most recent period (the most recent two weeks, etc.). Note that this is not limited to the most recent two weeks and can be designed as appropriate, but in this embodiment, the most recent two weeks of power usage will be described as an example. The usage amount acquisition module accesses a billing management system managed and operated by an electric utility at a predetermined timing (when the processing of step S13 described later is executed, a preset time or timing, etc.), and acquires the relevant user's most recent power usage (for the user for the most recent two weeks) from this billing management system. The usage amount acquisition module acquires each power usage for each time period for the most recent two weeks, and also acquires the total power usage for the most recent two weeks. The user terminal 10 may be configured to store in advance a DB in which daily power usage amounts are registered using a storage module, and to acquire the power usage amounts from this stored DB using a usage amount acquisition module.The user terminal 10 may also be configured to accept input from the user regarding power usage amounts into a predetermined input form, drop-down list, etc. (such as input using text into an input form or selection input from an option in a drop-down list), and to acquire the accepted input content as the power usage amount using the usage amount acquisition module.The user terminal 10 may also acquire the user's power usage amounts using methods other than those mentioned above.

[0026] The unit price acquisition module acquires unit price data that changes with time during the prediction period from market information (step S12). The market information is a compilation of electricity unit prices (yen / kWh) by day and time period for each electric utility company, and is registered in an external database. The unit price data is data that indicates the unit price of this electricity. The prediction period is, for example, the current month. Note that this unit price data includes the fixed unit price (finishing unit price) of the electric utility company in addition to the unit price of the electricity (power source unit price). The unit price acquisition module acquires this unit price data via the billing management system from a computer (not shown) that manages an external database in which market information is registered, at a predetermined timing (such as when the processing of step S13 described below is executed, or at a predetermined time or timing). The billing management system accesses the computer that manages this external DB, acquires the unit price data of the relevant user, and transmits the acquired unit price data to the user terminal 10. The unit price acquisition module receives the unit price data sent by the billing management system, and acquires unit price data that changes over time during the prediction period from market information. The user terminal 10 may be configured to store market information in advance using a storage module, and acquire unit price data that changes over time during the prediction period from the stored market information using a unit price acquisition module. The user terminal 10 may also be configured to accept input from a user into a predetermined input form, drop-down list, or the like regarding unit price data that changes over time during the prediction period (such as input of text into an input form or selection input from an option in a drop-down list), and acquire the accepted input content as unit price data that changes over time during the prediction period using a unit price acquisition module. The user terminal 10 may also be configured to acquire this unit price data without going through a billing management system. The user terminal 10 may also acquire unit price data that changes over time during the prediction period from market information using a method other than those mentioned above.

[0027] The calculation module calculates the user's electricity bill for this period based on the unit price data, the amount of electricity used, and the period (step S13). The calculation module calculates the electricity bill for a period (the current month) based on actual electricity usage based on unit price data and electricity usage amounts for the most recent period (such as the most recent two weeks). The calculation module calculates the electricity bill for each time slot for the most recent two weeks based on the unit price data and electricity usage amounts for each time slot. The calculation module adds up the electricity bills for each time slot and calculates the electricity bill for the most recent two weeks. The calculation module may also calculate the electricity bill for a period (the current month) based on actual usage based on unit price data and electricity usage amounts up to the current day during a specified electricity usage period (bill calculation period). The calculation module may also calculate the electricity bill for a day rather than for each time slot. For example, the calculation module may calculate the average value of the unit price data and electricity usage amounts for each time slot in a day and use this calculated average value as the electricity bill for the day. The calculation module may calculate the electricity bill using not only the most recent unit price data but also the unit price data for the same month of the previous year, or may calculate the electricity bill using a weighted average of the most recent unit price data and the unit price data for the same month of the previous year using a weighting parameter set in advance. For example, when there is a large seasonal change (such as when there is a change from spring to summer), the calculation module may calculate the electricity bill using the unit price data for the same month of the previous year instead of the most recent unit price data. The calculation module calculates the usage period for the current month / next month (period subject to billing calculation), and calculates the amount of electricity used for the current month from the amount of electricity used for the most recent two weeks. The calculation module calculates the average amount of electricity used for the most recent two weeks. The calculation module calculates the average amount of electricity used for each time period based on the amount of electricity used for each time period for the most recent two weeks. The calculation module calculates the amount of electricity used for the remaining days of the current month based on this average amount. The calculation module multiplies the average amount of electricity used for each time period by the number of remaining days to calculate the amount of electricity used for each time period for the remaining days of the current month. The calculation module calculates the electricity bill for the current month based on the electricity usage for each time period for the remaining days of the month and the electricity bill for the number of days elapsed in the current month.The calculation module multiplies the electricity usage for each time period for the remaining days of the month by the power unit price for each time period and the area-specific fixed metered charge to calculate the electricity bill for each time period for the remaining days, and adds up the calculated electricity bills.The calculation module adds up the added-up electricity bill, the electricity bill for the number of days elapsed in the current month, the renewable energy power generation promotion levy, and the fuel cost adjustment amount to calculate the electricity bill for the current month. As a result, the calculation module calculates the user's electricity bill for this period based on the unit price data, the amount of electricity used, and the period.

[0028] The process of step S13 described above may be performed by a predetermined generation AI (Artificial Intelligence) instead of the user terminal 10, and the user terminal 10 may acquire the processing result by the generation AI. In addition, in the processing of step S13 described above, a billing management system linked to an API (Application Programming Interface) may perform the actual processing, and the user terminal 10 may acquire the user's electricity bill calculated as a processing result.

[0029] The output module outputs the electricity fee for the calculated period (step S14). The output module displays the calculated electricity bill for the period on a predetermined UI via a predetermined application (see FIG. 6). As a result, the output module outputs the electricity bill for the calculated period. Details of the UI and electricity bill output by the output module will be described later.

[0030] This completes the prediction result output process.

[0031] The user terminal 10 can also be configured to output a message according to the progress toward a preset electricity bill target amount. This target amount may be for each day, each month, or for a longer period. This case will be explained. The user terminal 10 identifies the progress of the user's electricity bill for the period (current month) calculated by the process of step S13 described above, indicating the extent to which the predetermined target amount has been achieved. The user terminal 10 generates a message according to the identified progress. This message is generated, for example, at predetermined rates (10%, 20%, ... 100%). The user terminal 10 outputs the generated message by outputting the message at a preset position or an arbitrary position on a predetermined UI, or by outputting the message by push notification, or the like. As a result, the user terminal 10 outputs a message according to the progress status toward the preset target amount for the electricity bill.

[0032] [Electricity forecast output process executed by user terminal 10] The electricity forecast output process executed by the user terminal 10 will be described with reference to Fig. 4. The figure shows a flowchart of the electricity forecast output process executed by the user terminal 10.

[0033] The identification module identifies the electricity bill situation according to the electricity bill for a predetermined period in the recent past (step S20). The electricity bill status is the price fluctuation status of the power source unit price in one day, and is the status based on the price fluctuation of the most recent unit price data (such as the past five days excluding the current day). Note that the most recent is not limited to the past five days excluding the current day, and can be designed as appropriate, but in this embodiment, the past five days excluding the current day will be described as an example. The identification module identifies time periods with low power unit prices and time periods with high power unit prices as electricity bill conditions. A low power unit price is a power unit price that is lower by a predetermined amount (e.g., 5 yen or more) than the average price data for the most recent period (past 5 days excluding the current day). A high power unit price is a power unit price that is higher by a predetermined amount (e.g., 5 yen or more) than the average price data for the most recent period (past 5 days excluding the current day). The identification module identifies a predetermined number (e.g., 10) of time periods in order from the cheapest time period among the identified time periods with the lowest power unit price. The identification module also associates each identified time period with an order. The identification module identifies a predetermined number (e.g., 10) of time periods among the identified time periods with high power unit prices, in order from the most expensive time period. The identification module also associates the identified time periods with an order. Furthermore, the identification module identifies, among the identified time periods with high power unit prices, time periods in which the average price data for the most recent period (the past five days excluding the current day) exceeds a predetermined amount (100 yen or more) as time periods in which prices are rising. The identification module identifies the fixed unit price of the electric utility in the same format as the power source unit price. The identification module may identify the electricity bill situation using different methods for weekdays and holidays (such as weekends and public holidays). For example, if the above example is for a weekday, the identification module may identify the electricity bill situation for a holiday by shortening the most recent period (such as three days excluding the current day), or may identify the electricity bill situation by lengthening the most recent period (such as seven days excluding the current day). Conversely, the identification module may identify the electricity bill situation for a weekday by shortening the most recent period (such as three days excluding the current day), or may identify the electricity bill situation by lengthening the most recent period (such as seven days excluding the current day). Furthermore, when identifying the electricity bill situation for a weekday, the identification module may use only the weekday portion of the unit price data. Furthermore, when identifying the electricity bill situation for a holiday, the identification module may use only the holiday portion of the unit price data. Furthermore, the identification module may identify the electricity bill situation by combining these methods.

[0034] The output module outputs an icon indicating the identified electricity bill situation (step S21). The output module generates a graph in a predetermined format (e.g., a line graph, a bar graph, a circle graph, etc.) based on the acquired power unit price and the fixed unit price of the electric utility company, and outputs the generated graph on the UI described above. This graph lists the power unit price and the fixed unit price for each time period of the day. The power unit price in this graph has different display styles for time periods with low power unit prices, high power unit prices, and other time periods based on the most recent electricity bill. For example, this display style may color time periods with high power unit prices red, time periods with low power unit prices dark green, and other time periods light green. The fixed unit prices in this graph may have the same display style as the power unit prices described above. Note that the display style is not limited to the above example and can be designed as appropriate. It is also possible to configure time periods with high power unit prices to have a darker color the higher the price, or to configure time periods with low power unit prices to have a darker color the lower the price. The output module may also display time periods when the power unit price is rising more emphatically than time periods when the power unit price is high (for example, by adding a symbol such as "!", text such as "warning", an illustration, or a mark to the display of time periods when the power unit price is high, or by flashing the display of time periods when the power unit price is high). The output module also outputs fixed unit prices in a similar format. The output module outputs the time period with the cheapest power unit price and that power unit price from the identified electricity bill situation, as well as the time period with the highest power unit price and that power unit price. The output module outputs these in a state where they are arranged near the output graph, etc. The output module also outputs fixed unit prices in a similar format. The output module outputs an icon indicating the time period when the power unit price is low from the identified electricity bill status. The output module outputs this icon by superimposing it on the output graph or by placing it nearby. The output module also outputs fixed unit prices in a similar format. The output module outputs an icon indicating a time period in which the power unit price is high from the identified electricity bill status as an icon indicating the electricity bill status. Furthermore, if the output module identifies a time period in which the power unit price is rising from the identified electricity bill status, it outputs an icon indicating this time period in which the power unit price is rising as an icon indicating the electricity bill status. The output module outputs these icons by superimposing them on the output graph or by placing them in the vicinity of the graph. By outputting these icons, the output module outputs an icon indicating the identified electricity bill status. Furthermore, by outputting an icon indicating a situation in which the power unit price is rising as an icon indicating the electricity bill status, the output module outputs a warning using an icon indicating a situation in which the power unit price is high. The output module also outputs fixed unit prices in a similar format. When outputting each icon, the output module outputs it in a different display mode. For example, an icon indicating a time period when the power unit price is low is displayed in the same display mode (dark green, etc.) as the time period when the power unit price is low in the graph described above, an icon indicating a time period when the power unit price is high is displayed in the same display mode (red, etc.) as the time period when the power unit price is high in the graph described above, and an icon indicating a time period when the power unit price is rising is displayed in a more emphasized mode than the time period when the power unit price is high (for example, by adding a symbol such as "!", text such as "warning," illustrations, marks, etc. to the display mode of the time period when the power unit price is high, or by flashing the display mode of the time period when the power unit price is high). The output module also outputs fixed unit prices in a similar format. The display mode when the output module outputs each icon is not limited to the above example, and can be designed as appropriate. The graphs and icons output by the output module will be described in detail below with reference to FIG.

[0035] The output module can be configured to output an icon on the UI according to the identified electricity bill situation, as well as to output a push notification. This case will be explained. The output module outputs, as a push notification, one or a combination of the following from the identified electricity bill status: time periods when the power unit price is low and the power unit price; time periods when the power unit price is high and the power unit price; and time periods when the power unit price is rising and the power unit price. The output module outputs, as a push notification, time periods when the power unit price is low and the power unit price itself, or a predetermined message notifying the time periods when the power unit price is low and the power unit price itself. The output module also outputs, as a push notification, time periods when the power unit price is high and the power unit price itself, or a predetermined message notifying the time periods when the power unit price is high and the power unit price itself. The output module also outputs, as a push notification, time periods when the power unit price is rising and the power unit price itself, or a predetermined message notifying the time periods when the power unit price is rising and the power unit price itself. The output module also outputs fixed unit prices in a similar format. The user can view this push notification and understand the status of their electricity bill. Furthermore, the user terminal 10 accepts input from the user in response to this push notification (such as a swipe), input such as launching an application, and executes the process of step S21 described above. As a result, the user is able to grasp the electricity bill situation.

[0036] This completes the electricity forecast output process.

[0037] [Smart usage output process executed by the user terminal 10] The smart usage output process executed by the user terminal 10 will be described with reference to Fig. 5. The figure shows a flowchart of the smart usage output process executed by the user terminal 10.

[0038] The calculation module calculates the sum of the power consumption in a predetermined time period in the most recent past and the power consumption that has been reduced compared to the average power consumption in the same power area in this predetermined time period (step S30). The calculation module subtracts the average power consumption in the same power area during the predetermined number of time periods with the lowest electricity rates identified by the processing in step S20 described above from the power consumption during these time periods, and calculates the power consumption that can be reduced from this average power consumption.The calculation module adds up the power consumption during the predetermined number of time periods with the lowest electricity rates identified by the processing in S20 and the calculated reduced power consumption, and calculates the sum of these values.

[0039] The process of step S30 described above may be performed by a predetermined generation AI (Artificial Intelligence) instead of the user terminal 10, and the user terminal 10 may acquire the processing result by the generation AI.

[0040] The output module outputs the calculated sum (step S31). The output module outputs the calculated sum on the UI. The output module outputs a predetermined icon linked to this sum on the UI. When the output module receives input (such as a tap) from the user on this icon, it outputs the sum linked to this icon superimposed on or placed near this icon. Alternatively, when the output module receives input (such as a tap) from the user on this icon, it switches this icon to the sum linked to this icon and outputs the calculated sum. Alternatively, when the output module receives input (such as a tap) from the user on this icon, it pops up the sum linked to this icon and outputs the calculated sum. The calculated sum value output by the output module will be described in detail below with reference to FIG.

[0041] The above is the smart usage output process.

[0042] The UIs output by the output module as a result of the above-described prediction result output process, electricity forecast output process, and smart usage output process will be described with reference to Fig. 6. This figure is a diagram schematically showing the UIs output by the output module. In this figure, UI 20 is shown. The UI 20 shows a prediction result area 30 and an electricity forecast area 40. The prediction result area 30 is an area that outputs the electricity bill for the calculated period as a result of the prediction result output process described above. The prediction result area 30 is also an area that outputs the calculated total value as a result of the smart usage output process described above. The electricity forecast area 40 is an area that outputs the graph generated as a result of the electricity forecast output process described above and an icon showing the electricity bill status. The output module outputs to the prediction result area 30 the electricity bill 31 for the calculated period, a smart usage icon 32 linked to the calculated total value, and a total usage icon 33 linked to the total amount of electricity usage for the period for which the electricity bill 31 was calculated. For the electricity bill 31, the electricity bill up to February 26th was 1,640 yen, and if the period of the current month is from February 5th to March 5th, the predicted value will be from February 27th to March 5th, and the sum of this 1,640 yen and this predicted value comes to 4,340 yen. The output module outputs this 4,340 yen as the electricity bill 31. When the output module receives input (such as a tap) from the user on the smart usage icon 32, it outputs the total value linked to this smart usage icon 32. As described above, the output module outputs this total value by superimposing it on, arranging it in the vicinity of, switching it around, popping it up, or the like. When the output module receives input (such as a tap) from the user on the total usage icon 33, it outputs the total amount of power usage linked to this total usage icon 33 in the same way as for the smart usage icon 32. This total usage may be the amount obtained by the processing in step S11 described above. The output module can also be configured to change the smart usage icon 32 according to changes in the calculated total value. In this case, when calculating the total value for the most recent two weeks in the process of step S30 described above, the calculation module also calculates the total value for the most recent week. The output module changes the smart usage icon 32 based on the total value for the most recent two weeks, depending on whether the total value for the most recent week has increased, decreased, or remained unchanged. For example, if there has been an increase, an up arrow icon is displayed; if there has been a decrease, a down arrow icon is displayed; and if there has been no change, a horizontal arrow icon is displayed. The output module can also be configured to change the total usage icon 33 according to fluctuations in the acquired total usage. In this case, when acquiring the total usage in the process of step S11 described above, the acquisition module acquires the total usage for the most recent two weeks and the total usage for the most recent week. The output module changes the total usage icon 33 according to whether the total usage for the most recent week has increased, decreased, or remained unchanged from the total usage for the most recent two weeks. For example, if there is an increase, an up arrow icon is displayed, if there is a decrease, a down arrow icon is displayed, and if there is no change, a horizontal arrow icon is displayed. The output module outputs a bar graph 41 generated by the processing of step S21 described above to the electricity forecast area 40, outputs specific time periods 42 as the time periods with the cheapest power unit price and the time periods with the highest power unit price within the day identified by the processing of step S20 described above, and outputs the electricity bill status 43 identified by the processing of step S20 described above. The bar graph 41 shows the power unit price and fixed unit price for one day, with two types of bar graphs, one for the power unit price and one for the fixed unit price, side by side. This bar graph 41 has different display styles for time periods when the power unit price is high, time periods when the power unit price is low, and other time periods. Furthermore, among the time periods when the power unit price is high, the time period with the highest power unit price has a different display style from other time periods when the power unit price is high. This bar graph 41 has a similar format for the fixed unit price. The specific time period 42 shows the time period with the highest power unit price and its unit price, and the time period with the cheapest power unit price and its unit price. The output module outputs a power unit price icon 44, which the user can use to switch between the power unit price and a fixed unit price, and a fixed unit price icon 45 to this specific time period 42. The power unit price icon 44 is linked to the time period with the highest power unit price and its unit price, and the time period with the cheapest power unit price and its unit price. Furthermore, the fixed unit price icon 45 is linked to the time period with the highest fixed unit price and its fixed price, and the time period with the cheapest fixed unit price and its fixed unit price. When the output module receives input (such as a tap) from the user to the power unit price icon 44, it outputs to the specific time period 42 the time period with the highest power unit price and its unit price, and the time period with the cheapest power unit price and its unit price, which are linked to this power unit price icon 44. When the output module receives input (tap, etc.) from the user to the fixed unit price icon 45, it outputs the time period with the highest fixed unit price and that fixed unit price linked to this fixed unit price icon 45, and the time period with the lowest fixed unit price and that fixed unit price, during the specific time period 42. When the output module receives input (tap, etc.) from the user to the fixed unit price icon 45 while outputting the power unit price, it switches to the fixed unit price linked to the fixed unit price icon 45 and outputs it, and when the output module receives input (tap, etc.) from the user to the power unit price icon 44 while outputting the fixed unit price, it switches to the power unit price linked to the power unit price icon 44 and outputs it. The electricity bill status 43 shows an icon indicating a time period when the unit price of power is low, an icon indicating a time period when the unit price of power is high, or an icon indicating a situation in which the unit price of power is rising, along with the unit price of power and the time period. The content output by the output module as the electricity bill status 43 may be in accordance with preset conditions (if there is a time period when the unit price of power is high, if there is a time period when the price is rising, a specific time period, etc.), or may be output in some other way. In the figure, the output module outputs an electricity forecast icon 46 indicating the time period when the unit price of power is cheap, the unit price of power, and the time period as electricity bill status 43. This electricity forecast icon 46 has the same display style (same color) as the one in the output bar graph 41 for the time period when the unit price of power is cheap. The output module can also be configured to output an icon indicating a time period when the power unit price is high, the power unit price, and the time period as the electricity bill status 43. In this case, the icon has the same display style (same color, etc.) as that of the time period when the power unit price is high in the output bar graph 41. The output module can also be configured to output an icon indicating a time period when the power unit price is rising, the power unit price, and the time period as the electricity bill status 43. In this case, the icon has the same display style (same color, more highlighted than that of the time period when the power unit price is high, etc.) as that of the time period when the power unit price is rising in the output bar graph 41. This concludes the explanation of UI20.

[0043] Although the above-described processes are described as separate processes, the user terminal 10 can be configured to execute a combination of some or all of the above-described processes. Also, the user terminal 10 can be configured to execute each process at a timing other than the timing described above. Furthermore, although the above-described processes are described as processes executed by the user terminal 10, a configuration is also possible in which some or all of the processes are executed by a computer connected to the user terminal 10 so as to enable data communication. In this case, for example, the computer executes each process (steps S11 to S13, S20, S30, etc.) executed by the user terminal 10 on the application, and outputs the processing results to the user terminal 10. The user terminal 10 receives the processing results, and the user terminal 10 displays the processing results on the UI.

[0044] The above-described means and functions are realized by a computer (including a CPU, an information processing device, and various terminals) reading and executing a predetermined program. The program may be provided, for example, from a computer via a network (Software as a Service (SaaS)) or as a cloud service. The program may also be provided in a form recorded on a computer-readable recording medium. In this case, the computer reads the program from the recording medium, transfers it to an internal or external recording device, records it, and executes it. The program may also be pre-recorded on a recording device (recording medium) and provided to the computer from the recording device via a communication line.

[0045] Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments. Furthermore, the effects described in the embodiments of the present invention are merely a list of the most preferable effects resulting from the present invention, and the effects of the present invention are not limited to those described in the embodiments of the present invention.

[0046] A first aspect disclosed in this embodiment is an electricity bill prediction system that predicts an electricity bill for equipment used by a user, a usage amount acquiring unit that acquires the amount of power usage of the user; a unit price acquisition unit that acquires unit price data that changes over time during a prediction period from market information; a calculation unit that calculates the electricity bill of the user for the period based on the unit price data, the amount of electricity used, and the period; an output unit that outputs the calculated electricity cost for the period; An electricity bill prediction system is provided.

[0047] In a second aspect disclosed in this embodiment, the output unit outputs an icon indicating the electricity bill status according to the electricity bill for a predetermined period in the most recent past. According to a first aspect, there is provided an electricity bill prediction system.

[0048] In a third aspect disclosed in this embodiment, the output unit outputs a warning using an icon indicating that the electricity bill is high, based on the electricity bill for a predetermined period in the most recent past. According to a first aspect, there is provided an electricity bill prediction system.

[0049] In a fourth aspect disclosed in this embodiment, the calculation unit calculates a sum of the amount of power consumption in a predetermined time period in the most recent past and the amount of power consumption that has been reduced compared to the average power consumption in the same power area in the predetermined time period; The output unit outputs the calculated sum. The electricity bill prediction system according to the first aspect. [Explanation of symbols]

[0050] 1. Electricity bill prediction system 10 User terminal 20 UI 30 Predicted Outcome Areas 31 Electricity bill 32 Smart Usage Icon 33 Total usage icon 40 Electricity forecast area 41 Bar Graph 42 Specific time period 43 Electricity bill status 44 Power unit price icon 45 Fixed Price Icon 46 Electricity forecast icon

Claims

1. An electricity bill prediction system that predicts the electricity bill of equipment used by a user, a usage amount acquiring unit that acquires the amount of power usage of the user; a unit price acquisition unit that acquires unit price data that changes over time during a prediction period from market information; a calculation unit that calculates the electricity bill of the user for the period based on the unit price data, the amount of electricity used, and the period; an output unit that outputs the calculated electricity cost for the period; An electricity bill prediction system equipped with

2. the output unit outputs an icon indicating the electricity bill status in accordance with the electricity bill for a predetermined period in the most recent past. The electricity bill prediction system according to claim 1 .

3. the output unit outputs a warning using an icon indicating that the electricity bill is high, based on the electricity bill for a predetermined period in the most recent past. The electricity bill prediction system according to claim 1 .

4. the calculation unit calculates a sum of the amount of power consumption in a predetermined time period in the most recent past and the amount of power consumption that has been reduced compared to the average power consumption in the same power area in the predetermined time period; The output unit outputs the calculated sum value. The electricity bill prediction system according to claim 1 .

5. An electricity bill prediction method executed by a computer for predicting an electricity bill for equipment used by a user, comprising: acquiring the amount of power usage of the user; A step of acquiring unit price data that changes over time during a prediction period from market information; calculating an electricity bill for the user for the period based on the unit price data, the amount of electricity used, and the period; outputting the calculated electricity bill for the period; An electricity bill prediction method comprising:

6. A computer that predicts the electricity costs of the equipment used by users acquiring the amount of power usage of the user; A step of obtaining unit price data that changes over time during a prediction period from market information; calculating an electricity bill for the user for the period based on the unit price data, the amount of electricity used, and the period; outputting the calculated electricity cost for the period; A computer-readable program for executing the program.

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