WO2017090172A1 - Information collection unit, information processing method and program - Google Patents

Abstract

In the present invention, a HEMS controller uses a first life event plan (P1A) and history information (P1B) of life events that have occurred from the start time of a time period until a determination time and creates a second life event plan (P1C), and causes a tablet terminal to display a power consumption plan corresponding to the second life event plan (P1C). The second life event plan (P1C) is created by revising a portion from the determination time (11 o'clock) of the first life event plan (P1A) until the end time of the time period, using the history information (P1B). Preferably, the HEMS controller deletes an occurrence of a life event (EB) to create the second life event plan (P1C) if the life event (EB) is not scheduled to occur by the determination time (11 o'clock).

Description

Information collection unit, information processing method and program

The present invention relates to an information collection unit, an information processing method, and a program.

In recent years, attention has been focused on a smart grid system that combines a power system using a private generator using solar power generation or wind power generation and a power system for purchasing power from a power company. The smart grid system, for example, creates in advance an operation plan that defines a schedule of power consumption required for the load device and an operation plan that defines a schedule of output power from the private generator, and generates private power according to these operational plans. The output power from the machine is supplied to the load device, and the insufficient power is supplied by the purchased power.

An operation management apparatus that can be used for such a smart grid system and that can perform demand control according to fluctuations in the power load of a load device and a power supply device that have a large power load such as an air conditioning heat source machine, and the like No. 2012-080679 (Patent Document 1). In such a system, it is important to create a plan that accurately predicts the demand for power. In the operation management apparatus, the load data is corrected based on the difference between the actual load data subjected to operation control and the predicted data, and reflected in the next optimum operation plan creation.

JP2012-080679A (paragraph 0030)

In recent years, attention has been focused on an energy management system that introduces an electric power system using a private power generation device using solar power generation, a fuel cell, wind power generation, and the like, and an electric power system for purchasing electric power from an electric power company into a home. Some energy management systems include a storage battery as an adjustment buffer between the power generated by the private power generator and the power consumption at home.

Such an energy management system can save energy and operating costs by systematically executing charging / discharging of storage batteries and operation of household electrical devices based on prediction of photovoltaic power generation and household power consumption. preferable.

However, in the resident's daily life, there is a tendency for temporal deviation in household power consumption. If the household power consumption is unpredictable, it may not be possible to implement an optimal charging / discharging plan for the storage battery, and the power purchase may be increased. The correction of load data described in the above Japanese Patent Application Laid-Open No. 2012-080679 is intended for a specific load device having a large power load such as an air-conditioning heat source machine, and immediately consumes power consumed by electric appliances in the home. It cannot be applied to the prediction.

The present invention has been made in view of the above problems, and an object thereof is to provide an information collection unit, an information processing method, and a program capable of improving the accuracy of prediction of power consumption of an electric device.

The information collection unit according to the present invention is an information collection unit that collects information on electrical equipment and displays a power consumption plan corresponding to the event plan on the display unit. The event plan includes information about the time at which an event defined by at least one of an operation time zone, an operation time length, and the number of operations and an electric device to be used is scheduled to occur. The information collection unit includes a control unit and a display management unit. The control unit uses the first event plan and the history information of the events completed from the start time of the first event plan to the time of determination, to determine a portion from the time of determination of the first event plan to the end time. A modified second event plan and a power consumption plan corresponding to the second event plan are created. The display management unit transmits an instruction to switch the image indicating the power consumption plan from the first image corresponding to the first event plan to the second image corresponding to the second event plan to the display unit.

Since the present invention updates the event plan and the power consumption plan after the determination based on the history information of the event that has occurred, the accuracy of the power consumption plan after the determination can be improved. The power consumption plan with improved accuracy can be used, for example, for optimal control of the storage battery.

1 is a diagram illustrating an overall configuration of an energy management system 1 according to Embodiment 1. FIG. 2 is a functional block diagram of a HEMS controller 10. FIG. It is a figure for demonstrating the outline of the 1st example of a process of the prediction value correction | amendment part 12C. It is a figure for demonstrating the outline of the 2nd example of a process of the predicted value correction | amendment part 12C. It is a figure for demonstrating the outline of the 3rd example of a process of the prediction value correction | amendment part 12C. It is a table which shows the definition of a life event. It is the table which showed the power consumption estimated with respect to each life event. It is the figure which showed an example of the life event plan and the prediction power consumption corresponding to it. It is FIG. 1 for demonstrating the correction | amendment of the track record and the future plan at the time of determination (11 o'clock). It is FIG. 2 for demonstrating the correction | amendment of the track record at the time of determination (11:00), and a future plan. It is a flowchart for demonstrating the process which correct | amends a power consumption plan. It is a flowchart for demonstrating the process which updates the charging / discharging schedule of a storage battery using the correct | amended power consumption prediction information. It is a figure for demonstrating the control mode of the storage battery of each time slot | zone in a planning stage. It is the figure which showed transition of the battery residual amount in a planning stage. It is the figure which showed transition of the battery remaining amount when not correcting a charging / discharging plan. It is a figure which shows having corrected the prediction of power consumption. It is the figure which showed transition of the battery residual amount at the time of correcting a charging / discharging plan according to the performance of power consumption, and the correction | amendment of power consumption, and suppressing power purchase. 10 is a flowchart for explaining a process of correcting a power consumption plan in the second embodiment. It is the figure which showed the electric power consumption corrected to the absent plan in Embodiment 2. FIG. It is the figure which showed transition of the battery residual amount when correcting a charging / discharging plan according to the performance of power consumption in Embodiment 2, and the correction | amendment of power consumption, and suppressing power purchase. It is the figure which showed the whole structure of the energy management system 1A of the modification.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following drawings, the same or corresponding parts are denoted by the same reference numerals, and description thereof will not be repeated.

[Embodiment 1]
FIG. 1 is a diagram showing an overall configuration of an energy management system 1 according to the first embodiment.

Referring to FIG. 1, the energy management system 1 is a HEMS (Home Energy Management System) that displays the amount of power consumed by the electrical device 30 to the user. The energy management system 1 is based on the HEMS controller 10, the electric device 30 that operates using electric power as a power source, the electric power measurement unit 5 that measures electric power supplied to the electric device 30, and the electric power measured by the electric power measurement unit 5. The tablet terminal 8 which displays the calculated electric energy, the storage battery 20, and the solar power generation device 19 are included.

The HEMS controller 10 is connected to a network 6 such as the Internet by wire or wireless via a router (not shown). Connected to the network 6 are a cloud server 2 and a server 4 of a business operator that provides a weather forecast service.

The HEMS controller 10 is connected to each of the power measuring unit 5, the electric device 30, the storage battery 20, and the solar power generation device 19 by wire or wireless so that data can be transmitted / received to / from each other. Preferably, by adopting compatible devices for the gas meter 7 and the water meter 9, the HEMS controller 10 can receive data on the gas usage amount and the water usage amount from the gas meter 7 and the water meter 9, respectively.

The electric device 30 includes air conditioners 31A to 31D, lights 32A to 32C, and electric devices arranged in the kitchen. The electrical equipment disposed in the kitchen includes an IH cooking heater 33, a microwave oven 34, a refrigerator 35, and kitchen lighting 36.

Based on the weather forecast information obtained from the server 4 of the business operator that provides the weather forecast service and the information (specifications, installation location, power generation result data, etc.) of the solar power generation device 19 of each home, the cloud server 2 The generated power of the power generation device 19 is predicted. The generated power prediction information is transmitted to the HEMS controller 10 via the network 6.

The electric device 30 operates by receiving any one of power from a commercial power source (not shown), power generated by the solar power generation device 19, and power discharged from the storage battery 20. The storage battery 20 is charged by receiving power from either a commercial power source (not shown) or the solar power generator 19.

The HEMS controller 10 calculates the amount of power consumed per unit time based on the power information periodically acquired from the power measuring unit 5 and the operation information of the electrical device 30 according to the user operation of the tablet terminal 8. And displayed on the tablet terminal 8.

The HEMS controller 10 also has a certain period (for example, 1) based on a family action schedule input in advance by the user, average power consumption data extracted from power information acquired in the past from the power measuring unit 5, and the like. The daily power consumption of the electrical device 30 is predicted. Further, the HEMS controller 10 corrects the predicted transition of power consumption as needed based on the operation history of the electrical device 30, displays it on the tablet terminal 8, and creates an optimal usage schedule for the storage battery 20 and the electrical device 30.

Next, an outline of functions of the HEMS controller 10 will be described. FIG. 2 is a functional block diagram of the HEMS controller 10. The cloud server 2 in FIG. 1 operates as the PV power generation amount prediction unit in FIG. 2, and the server 4 in FIG. 1 operates as the weather forecast database in FIG. The cloud server 2 (PV power generation amount prediction unit) calculates the amount of solar radiation to the solar power generation device 19 based on the weather forecast obtained from the server 4 (weather forecast database), and predicts the power generation amount.

The HEMS controller 10 includes a storage unit 11, a calculation unit 12, a device interface unit 18, and an operation / display management unit 13.

The storage unit 11 includes a database 11A in which electric energy data is stored, a database 11B in which family action plans are stored, and a database 11C in which definitions of life events are stored. As the memory | storage part 11, memory, such as ROM, RAM, flash memory, a hard disk, etc. can be used, for example.

The calculation unit 12 includes a power consumption amount prediction unit 12A, a life event management unit 12B, a predicted value correction unit 12C, an energy management unit 12D, and a control execution unit 12E. For example, a processor (CPU: Central Processing Unit) can be used as the calculation unit 12.

The HEMS controller 10 is a computer that includes a processor, a main storage unit, an auxiliary storage unit, a communication unit, an input unit, a timing unit, and the like. By reading the program stored in the main storage unit into the computer, the computer is configured so that each of the power consumption prediction unit 12A, the life event management unit 12B, the predicted value correction unit 12C, the energy management unit 12D, and the control execution unit 12E. Works as.

The power consumption amount prediction unit 12A predicts the power consumption amount for a certain period (for example, one day) from the past power amount data obtained from the database 11A, the action schedule obtained from the database 11B, and the like. The power consumption prediction unit 12A predicts the power consumption by statistical processing for the electrical equipment 30 that is regularly and repeatedly used.

The life event management unit 12B determines, for example, whether or not the power consumption record is due to a life event in a cycle of 30 minutes or 1 hour based on the device condition defined in the life event definition. The life event will be described in detail later with reference to FIG. 4. For example, an event in the home such as preparation for breakfast, lunch, dinner, etc. with power consumption is referred to as a life event in this specification.

The predicted value correction unit 12C corrects and updates the predicted value of the power consumption predicted by the power consumption prediction unit 12A from the occurrence state of the life event.

The energy management unit 12D optimizes the charging / discharging schedule of the storage battery 20 based on the power generation amount predicted by the cloud server 2 (PV power generation amount prediction unit) and the power consumption amount prediction information updated by the predicted value correction unit 12C. Or optimizing the schedule of the electrical device 30.

The control execution unit 12E issues a control command to the electric device 30 or monitors the state of the electric device 30 based on the schedule created by the energy management unit 12D and the user's operation.

The operation / display management unit 13 displays 1) a charge / discharge schedule and a charge / discharge schedule change notification of the storage battery 20 on the tablet terminal 8 which is a user interface, and 2) displays an elapsed state of the life event, and the life by the user. Processes such as adding events and correcting judgments. Further, as will be described later, when the predicted value correction unit 12C corrects and updates the predicted value of the power consumption amount, the operation / display management unit 13 converts the image indicating the power consumption plan into the event plan before the update. A command to switch from the corresponding image to an image corresponding to the updated event plan is transmitted to the tablet terminal 8.

The equipment interface unit 18 is an interface for communicating with each of the electrical equipment 30, the solar power generation device 19, and the storage battery 20.

Next, an outline of processing of the predicted value correction unit 12C performed by the HEMS controller 10 will be described.

FIG. 3 is a diagram for explaining an outline of a first example of processing of the predicted value correction unit 12C. In the example shown in FIG. 3, the case where a life event occurs earlier than the power consumption prediction will be described. In this case, when the completion of the life event is detected, the future predicted value after the determination time is corrected by subtracting the predicted power consumption amount of the life event scheduled in the prediction stage from the predicted value.

Referring to FIG. 1 and FIG. 3, the HEMS controller 10 collects information on the electrical device 30 and generates a power consumption plan corresponding to a life event plan for a period (for example, 1 day) between the start time and the end time. It operates as an “information collecting unit” to be displayed on a “display unit” such as the tablet terminal 8.

An example of the definition of the life event will be described later with reference to FIG. 6, and is defined by at least one of the operation time zone, the operation time, and the number of operations, and the electric device 30 to be used. Examples of individual life events are, for example, “breakfast”, “lunch”, “dinner”, “cleaning”, and “laundry”.

The life event plan is a plan for determining a time zone in which a life event occurs in a certain period (for example, one day). The first life event plan P1A, which is an initial plan, is planned so that the life event EA occurs at 10:00 and the life events EA and EB occur at 11:00. On the other hand, the history information P1B indicating the actual value up to 11:00 at the time of determination records that the life events EA and EB occurred at 10:00. That is, it is shown that the life event EB, which was scheduled to occur at 11 o'clock, occurred one hour earlier.

In such a case, the HEMS controller 10 uses the history information P1B of the life event that has occurred from the start time of the period (for example, 1 o'clock) to the determination time (11 o'clock) and the first life event plan P1A. Then, the second life event plan P1C is created, and the power consumption plan corresponding to the second life event plan P1C is displayed on the tablet terminal 8.

The second life event plan P1C is created by correcting the part from the determination (11:00) to the end of the period (for example, 24:00) of the first life event plan P1A using the history information P1B.

Preferably, the HEMS controller 10 includes the occurrence of the life event EB in the history information P1B of the life event that has occurred from the start time (for example, 1 o'clock) to the determination time (11 o'clock) of the period, and the first If the occurrence of a life event EB is not planned between the start of the period (for example, 1 o'clock) and the determination time (11 o'clock) in the life event plan P1A of the first life event plan P1A (11 Time) to the end of the period (for example, 24:00), the generation of the life event EB is deleted, and a second life event plan P1C (11:00 life event plan) is created.

More specifically, an example will be described for the case where the life event is “Lunch Preparation”. From 11:00 to 12:00, the power consumption of IH cooking heater, microwave oven, kitchen lighting, etc. was predicted to be 1 kWh the previous day as lunch preparation. An 8 kW lunch preparation life event was detected. Therefore, 1 kW of lunch preparation predicted from 11:00 to 12:00 is subtracted from the predicted value assuming that it does not occur.

FIG. 4 is a diagram for explaining an outline of the second example of the process of the predicted value correction unit 12C. In this example, a case where the occurrence of a life event is delayed from the prediction will be described. In this case, at the time of determination when the predicted time has elapsed, the power consumption amount of the corresponding life event at the prediction stage is shifted as a predicted value with respect to the next time zone (added to the next time zone).

In FIG. 4, the first life event plan P2A, which is the initial plan, has a life event EA at 10:00, life events EA and EB at 11:00, and a life event EA at 12:00. Planned to occur. On the other hand, the history information P2B indicating the actual value up to 12:00 at the time of determination records that a life event EA occurred at 10:00 and a life event EA occurred at 11:00. That is, it is indicated that the life event EB that was scheduled to occur at 11:00 has not yet occurred.

In such a case, the HEMS controller 10 does not include the occurrence of the life event EB in the history information P2B of the life event that has occurred from the start of the period to the time of determination (12:00), and the first If the occurrence of the life event EB is planned from the start of the period of the life event plan P2A to the time of determination (12:00), the period of time from the time of determination (12:00) of the first life event plan P2A The occurrence of the life event EB is added to the portion up to the end point, and the second life event plan P2C (life event plan at 12 o'clock) is created.

FIG. 5 is a diagram for explaining the outline of the third example of the process of the predicted value correction unit 12C. FIG. 5 illustrates a case where a life event has not occurred. Each life event has a predetermined time zone. If the life event is not detected even after the time zone, the postponement is not performed and the assumed life event has not occurred. Do not make corrections. That is, the amount of power corresponding to an event that has not occurred is reduced from the predicted amount of power.

In FIG. 5, the first life event plan P3A, which is an initial plan, has a life event EA at 10:00, life events EA and EB at 11:00, and a life event EA at 12:00. It is planned that a life event EA will occur at around 13:00. On the other hand, in the history information P3B indicating the actual value up to 13:00 at the time of determination, a life event EA occurs at 10:00, a life event EA occurs at 11:00, and a life event EA occurs at 13:00. Has been recorded. That is, it is shown that the life event EB that was scheduled to occur at around 11:00 has not yet occurred even at 13:00.

In such a case, the HEMS controller 10 stops the shift to the subsequent time zone of the event EB and does not generate an event after a predetermined time (13:00) has passed.

Specifically, as shown in FIG. 4, the HEMS controller 10 does not include the occurrence of the life event EB in the history information P2B of the life event that has occurred from the start of the period to the time of determination (12:00). And the occurrence of the life event EB is planned from the start of the period of the first life event plan P2A to the time of determination (12:00), and the time of determination (12:00) is predetermined (13 If it was before the time), the life from the determination of the first life event plan P2A (12 o'clock) to the end of the period is divided into a first part (12 o'clock) The occurrence of the event EB is added, and the second life event plan P2C (life event plan at 12 o'clock) is created.

Further, as shown in FIG. 5, the HEMS controller 10 does not include the occurrence of the life event EB in the history information P3B of the life event that has occurred from the start of the period to the time of determination (13:00), and The occurrence of a life event EB is planned from the start of the period of the first life event plan P3A to the time of determination (13:00), and the time of determination (13:00) is predetermined (13:00). If it has been reached, the second life event plan P3C (life event plan at 13:00) is created without adding the occurrence of the life event EB to the first life event plan P3A.

Preferably, the life event includes at least one of a breakfast event, a lunch event, and a dinner event in which a plurality of electrical devices 30 (IHCH 33, microwave oven 34, refrigerator 35, and kitchen lighting 36) arranged in the kitchen are used. Including.

Preferably, as shown in FIG. 1, a solar power generation device 19 is connected to the HEMS controller 10. The power consumption plan is used to create a charge / discharge plan for the storage battery 20 together with the prediction data of the power generation amount of the solar power generation device 19.

Next, life events and life event plans will be described with more specific examples. FIG. 6 is a table showing definitions of life events. The table shown in FIG. 6 is stored in the database 11C related to the life event definition in FIG. Activities that occur daily and consume power are defined as “life events”. With reference to FIG. 6, the life event is defined by at least one of an operation time zone, an operation time, and the number of operations, and the device name of the electric device 30 to be used.

(Event number 0) If at least one of the lights A to C lights up once for a period of 5 minutes or more in the time zone from 5:00 to 7:00, the HEMS controller indicates that a life event “early morning activity” has occurred. 10 is judged.

(Event number 1) In the time zone from 7:00 to 9:00, if at least one of the lights A to C lights up once for a period of 5 minutes or more, the HEMS controller indicates that a life event “morning activity” has occurred. 10 is judged.

(Event number 2) In the time zone from 6:00 to 9:00, if any one of the following five conditions is satisfied, the HEMS controller 10 determines that a life event “breakfast” has occurred.
1) IHCH (IH cooking heater) for 1 minute or more, 1 operation 2) Microwave oven for 30 seconds or more, 1 operation 3) Refrigerator door opened and closed 2) Kitchen lighting for 5 minutes or more 5) The gas meter has detected that the gas has been used once (Event No. 3) If a power consumption of 0.6 to 1 kW is detected for more than 5 minutes in branch A of the distribution board, The HEMS controller 10 determines that a life event “” has occurred. Although not shown, the branch A is a branch wiring provided for a dedicated outlet of the washing machine, and a current transformer (CT) or the like is installed as the power measuring unit 5.

(Event number 4) If a power consumption of 0.6 to 1 kW is detected in branch B of the distribution board for 5 minutes or more, the HEMS controller 10 determines that a life event “cleaning” has occurred. Although not shown, the branch B is a branch wiring provided for an outlet mainly connected to the cleaner, and a current transformer (CT) or the like is installed as the power measuring unit 5.

(Event No. 5) If any one of the above conditions 1) to 5) used to determine “breakfast” is met in the time zone from 11:00 to 14:00, a life event “Lunch” has occurred and the HEMS The controller 10 determines.

(Event No. 6) If any one of the above conditions 1) to 5) used for the determination of “breakfast” is met in the time zone from 17:00 to 22:00, it is determined that a life event “dinner” has occurred. The controller 10 determines.

(Event No. 7) In the time zone from 17:00 to 23:00, if the bathroom lighting is operated once for a time of 5 minutes or more, the HEMS controller 10 determines that a life event “bathing A” has occurred. . In accordance with the number of family members, the first time may be defined as “bathing A”, the second time as “bathing B”, the third time as “bathing C”, and the like.

(Event No. 8) If at least one of air conditioner A and air conditioner B operates once for a period of 30 minutes or more in the time zone from 6:00 to 11:00, a life event “wake-up air conditioning” occurs. The HEMS controller 10 determines.

(Event number 9) When at least one of air conditioner C and air conditioner D operates once for a period of 30 minutes or more in the time period from 12:00 to 17:00, a life event “air-conditioning at home” has occurred. The HEMS controller 10 determines.

(Event No. 10) If at least one of air conditioner A and air conditioner B is operated once for a period of 30 minutes or more in the time zone from 17:00 to 24:00, it is said that a life event “night air conditioning” has occurred. The controller 10 determines.

(Event number 11) In the time zone from 17:00 to 24:00, if at least one of the lights A to C is lit once for a time of 5 minutes or more, a life event of event number 11 “night activity” occurs. The HEMS controller 10 determines that it has been performed.

In the case of breakfast, etc., the occurrence of a life event is detected when any one of a plurality of conditions is met, but the occurrence of a life event is detected when some of a plurality of conditions are met simultaneously. You may make it detect.

The above life event can be set by the user, but other than that, the daily life event may be extracted from the analysis of the past power consumption. The user can re-edit the definition of the life event for the result of the automatic extraction.

FIG. 7 is a table showing power consumption predicted for each life event. The table shown in FIG. 7 is stored in the database 11A related to the electric energy in FIG.

Predicted power consumption P0 to P11 is stored for event numbers 0 to 11, respectively. As the values of the power consumptions P0 to P11, values learned from past results may be adopted. Moreover, you may change with a day of the week or a season. The predicted power consumption P0 to P11 is used as power consumption corresponding to the life event plan (planned power consumption).

FIG. 8 is a diagram showing an example of a life event plan and predicted power consumption corresponding thereto. The life event plan is a plan for determining a time zone in which a life event occurs in a certain period (for example, one day).

FIG. 8 shows a time period in which the life events of event numbers 0 to 11 shown in FIG. 6 are predicted to occur during the period from 0 o'clock on the next day to 0 o'clock on the next day (from 0 o'clock to 25 hours). Is shown. In FIG. 8, the horizontal axis indicates time and the vertical axis indicates power. The electric power indicates a value obtained by accumulating planned power consumption corresponding to the life event.

Note that “a” indicates standby power, and “b” indicates operating power of a water heater for hot water supply. About these, it is the electric power which generate | occur | produces irrespective of a user's life event.

In FIG. 8, for example, at 7 o'clock, three life events, “0: early morning activity”, “8: air conditioning when waking up”, and “2: breakfast” are planned. The value obtained by accumulating the planned power consumption when it occurs is shown.

Such a life event plan is first created. The life event plan is created based on a life event occurrence schedule set for the user. However, the life event plan may be created based on a schedule automatically created by statistically processing the user's life event occurrence.

On the other hand, the actual value of power consumption and the history of occurrence of life events are detected at regular intervals (for example, every 30 minutes or one hour). Then, it is determined whether or not the life event plan after the determination needs to be corrected.

FIG. 9 is a first diagram for explaining actual results at the time of determination (11 o'clock) and correction of future plans. Referring to FIG. 9, from 0:00 to 9:00 (from 0:00 to 9:59), the occurrence of a life event is detected according to the life event plan shown in FIG. Values are shown. Since the actual power consumption value has a slight error from the value shown in FIG. 7, it does not necessarily match the power shown in the life event plan.

In FIG. 9, at the time of 11 o'clock, the occurrence of a 10 o'clock life event and the actual value of power consumption are detected. At 10 o'clock, it is detected that more power consumption than the plan of FIG. 8 has been detected, and that life event number 5 “lunch” has occurred.

Then, the HEMS controller 10 determines that the life event number 5 “lunch” has occurred earlier than planned, and determines the life event number 5 “lunch” planned at 11 o'clock from the life event plan after the determination time. In addition to the deletion, the power prediction graph is also corrected so as to reduce the corresponding power and displayed on the “display unit” of the tablet terminal 8 or the like.

FIG. 10 is a second diagram for explaining actual results at the time of determination (11 o'clock) and correction of future plans. In the example of FIG. 10, in the actual value, it is recognized that the power in the 10 o'clock range is higher than the planned value, but the life event of “lunch” of event number 5 is not detected, so event number 5 It is determined that “lunch” occurs as scheduled, and in the life event plan after the determination, “lunch” of event number 5 at 11 o'clock is maintained without being deleted.

In addition, when the life event of “Breakfast” is behind the time, it may be used for breakfast as early as lunch. For example, a “breakfast” life event is defined between 6:00 and 10:00, and a “lunch” life event is defined between 10:00 and 14:00, so that the “breakfast” life event does not occur by 10:00. If the “lunch” life event occurs at 10:30, the “breakfast” life event is deleted and the “lunch” life event remains. In such a case, the lifestyle may be learned from past data, and for example, it may be predicted that a “lunch” life event will occur on Sundays and holidays.

FIG. 11 is a flowchart for explaining processing for correcting the power consumption plan. The process of this flowchart is executed by the predicted value correction unit 12C in the HEMS controller 10 of FIG. The process of the flowchart of FIG. 11 is called from the main routine and executed at regular time intervals or whenever an execution condition is satisfied.

In the present embodiment, the information processing method executed by the HEMS controller 10 according to the flowchart of FIG. 11 displays a power consumption plan corresponding to a life event plan for a period (for example, one day) between the start time and the end time. Information processing method to be displayed on the unit (tablet terminal 8).

Referring to FIG. 11, first, in step S1, the HEMS controller 10 acquires the current time from a timer circuit or a network (not shown). Subsequently, in step S2, the HEMS controller 10 determines whether or not the current time matches a predetermined determination time. The determination time is determined to arrive every hour or 30 minutes, for example.

In step S2, if the current time does not coincide with the determination time (NO in S2), the process proceeds to step S3. In step S3, the HEMS controller 10 acquires each state (including operation history and power consumption) of the electrical device 30, stores the state of the electrical device 30, and returns the process to step S1 again.

On the other hand, if the current time coincides with the determination time in step S2 (YES in S2), the process proceeds to step S4. In this case, the HEMS controller 10 determines a corresponding life event from the operation history of the electrical device and the power consumption, and detects completion of the determined life event.

First, in step S4, the HEMS controller 10 totals the operation history of the electrical device 30 stored in step S3, and then totals the power consumption (actual value) in step S5.

Then, in steps S6 to S14, life event occurrence determination processing is executed for events 1 to N (N is a natural number greater than 1). First, in step S7, the HEMS controller 10 refers to the life event definition table shown in FIG. 6, and collates the operation history of the electric device with the list of electric devices in step S8.

If the natural number between 1 and N is i, the HEMS controller 10 collates the list of electrical devices defined in the i-th life event with the operation history tabulated in step S4 in step S8.

If the collation result between the operating device and the event target device indicates a match in step S9, it is determined in subsequent step S10 whether the time zones match, and in step S11 it is determined whether the operating time satisfies the condition. It is determined whether or not the number of operation times satisfies the condition.

If all the conditions in steps S10 to S12 are satisfied, the process proceeds to step S13, and the HEMS controller 10 updates the life event completion list, assuming that the life event i has been completed by the time of determination. If NO is determined in any of steps S9 to S12, the process of step S13 is not executed.

In step S14, the live event number i is incremented to i + 1, and if i + 1 is not the end value (N + 1), the processing of S7 to S13 is executed again.

In step S14, if all the life event numbers 1 to N have been determined, the process proceeds to step S15. In step S15, the HEMS controller 10 refers to the predicted power consumption data (predicted power consumption corresponding to the life event plan before correction), and in step S16, the predicted data is out of prediction with respect to the actual power consumption value. Determine if there was. For example, when no life event is detected and the power consumption is less than the prediction by the amount of power corresponding to the life event, the HEMS controller 10 determines that the prediction is unpredictable.

If it is not predicted in step S16, the power consumption prediction correction process in step S17 and the update process in step S18 are executed, and then the process returns to the main routine in step S19. On the other hand, if it is not out of prediction in step S16, the power consumption prediction correction process in step S17 is not executed, and the process returns to the main routine in step S19.

The power consumption prediction correction process executed in step S17 includes a process of deleting power consumption corresponding to an already executed event from the plan as shown in FIG. In the example illustrated in FIG. 3, in step S17, the HEMS controller 10 determines the history information P1B of life events that have occurred from the start time of the period (for example, 1 o'clock) to the determination time (11 o'clock), and the first life event. A second life event plan P1C is created using the plan P1A. In step S17, the corrected power consumption prediction is reflected in the update of the power consumption prediction information in step S18. In step S18, the HEMS controller 10 causes the tablet terminal 8 to display the power consumption plan corresponding to the second life event plan P1C.

The second life event plan P1C is created by correcting the part from the determination (11:00) to the end of the period (for example, 24:00) of the first life event plan P1A using the history information P1B.

In another case, the power consumption prediction correction process executed in step S17 includes a process of shifting power consumption corresponding to an unexecuted event and adding it to the plan as shown in FIG. In the example illustrated in FIG. 4, in step S17, the HEMS controller 10 does not include the occurrence of the life event EB in the history information P2B of the life event that has occurred from the start of the period to the time of determination (12:00). And, when the occurrence of the life event EB is planned from the start of the period of the first life event plan P2A to the time of determination (12:00), the time of determination of the first life event plan P2A (12 The generation of the life event EB is added to the part from the time until the end of the period, and the second life event plan P2C (life event plan at 12 o'clock) is created. In step S17, the corrected power consumption prediction is reflected in the update of the power consumption prediction information in step S18. In step S18, the HEMS controller 10 causes the tablet terminal 8 to display the power consumption plan corresponding to the second life event plan P2C.

11 can be said to be an information processing method for displaying a power consumption plan corresponding to an event plan in a period between a start time and an end time on the display unit.

As described with reference to FIG. 3, this information processing method is corrected using the first life event plan P1A before correction and history information P1B of life events that have occurred from the start of the period to the time of determination. The step of creating the second life event plan P1C (S17 in FIG. 11) and the step of displaying the power consumption plan corresponding to the second life event plan P1C on the tablet terminal 8 (S18 in FIG. 11) are included. .

A program for causing a computer to execute such an information processing method is stored in the storage unit 11 in FIG. 2, and the HEMS controller 10 performs these steps ( It operates as a computer that executes S17, S18).

FIG. 12 is a flowchart for explaining a process for updating the charge / discharge schedule of the storage battery using the corrected power consumption prediction information. The process of this flowchart is called from the main routine and executed every predetermined time or every time a predetermined condition is satisfied in the HEMS controller 10 operating as the energy management unit 12D of FIG.

When the processing of this flowchart is started, first, in step S51, the HEMS controller 10 acquires the power generation information of the solar power generation device 19. The power generation information includes information on the transition of the power generation amount predicted by the cloud server 2 of FIG. 1 based on the weather forecast, the position of the solar power generation device 19, the specifications, and the like.

Subsequently, in step S52, the HEMS controller 10 obtains power consumption prediction information obtained by statistical processing of family behavior schedules and past performance values of power consumption. The power consumption prediction information reflects the correction executed by the processing of the flowchart of FIG. And the HEMS controller 10 produces | generates the charging / discharging schedule of the storage battery 20, and the operation schedule of the electric equipment 30 in step S53.

The charge / discharge schedule of the storage battery 20 is basically the following schedule. First, the storage battery 20 is charged up to the amount planned in the low-night time when the electricity rate is cheap. If the weather is fine, the remaining power of the storage battery 20 is charged using the generated surplus power while covering the household power consumption with the amount of power generated by the solar power generator 19 during the daytime. From the evening to the night, the storage battery 20 is discharged to reduce the amount of power purchased from the power company (power purchase).

The operation schedule of the electric device 30 is such that, for example, when the storage amount of the storage battery 20 has a margin, normal operation is performed, and when the storage amount of the storage battery 20 has no margin, an energy saving operation is performed. The charge / discharge schedule of the storage battery 20 is changed.

Subsequently, in step S54, the HEMS controller 10 is a control time for executing charging / discharging of the storage battery 20 or a control time for changing the operation of the electric device 30 in the charging / discharging schedule in which the current time is generated. Determine whether or not. If the current time is the control time in step S54 (YES in S54), execution of charge / discharge control of the storage battery 20 or operation of the electric device 30 is instructed in step S55.

If the process of step S55 is executed, or if the current time is not the control time in step S54 (NO in S54), the process proceeds to step S56, and the control is returned to the main routine.

You may make it notify a user about the change of the charging / discharging plan of a storage battery. For example, when the predicted power consumption is corrected, if the increase or decrease in the predicted power consumption exceeds a certain value due to the correction, the charge / discharge plan is reviewed. When there is a change in the charge / discharge schedule of the storage battery 20, the user is notified of the change in the discharge / charge / charge / discharge plan, the life event digest and schedule are displayed, and the user inputs the change in the schedule of the life event. It may be possible.

The basics of the power consumption prediction correction process and the storage battery charge / discharge process of the present embodiment have been described above. A specific application example will be described below.

(Application pattern 1)
This pattern is a plan that the storage battery 20 is charged at around 12:00 to 14:00 when the surplus power of the solar power generation device 19 is expanded and can be fully charged. A schedule is planned in which the storage battery 20 is fully charged by charging at 17:00, and discharging of the storage battery 20 is started from 17:00. It is assumed that the storage battery is charged to 40% with midnight power and then charged to 100% with surplus power of the solar power generation device 19.

(Planning stage of application pattern 1)
FIG. 13 is a diagram for explaining a storage battery control mode in each time zone in the planning stage. FIG. 14 is a diagram showing the transition of the remaining battery level in the planning stage.

13 and 14, the control mode of the storage battery 20 is set to the discharge mode during the time period from 6 o'clock to 11:59. In this time zone, the amount of power generated by the solar power generation device 19 is not so large, and therefore the surplus power of the solar power generation device 19 is small. Execute electricity discharge to suppress electricity purchase.

During the time period from 12:00 to 15:59, the control mode of the storage battery 20 is set to the charging mode. In this time zone, the amount of power generated by the solar power generation device 19 increases, and stable surplus power can be expected. Therefore, the storage battery 20 is charged.

In the time zone from 16:00 to 16:59, the control mode of the storage battery 20 is set to the discharge mode. In this time zone, the amount of power generated by the solar power generation device 19 is not so large, and therefore the surplus power of the solar power generation device 19 is small. Execute electricity discharge to suppress electricity purchase.

In the time zone from 17:00 to 22:59, the control mode of the storage battery 20 is set to the discharge mode. In this time zone, the amount of power generated by the solar power generation device 19 is zero or close to zero. Therefore, the purchase of electric power is suppressed by covering the power consumption in the home with the discharge power from the storage battery as much as possible.

After 23:00, the control mode of the storage battery 20 is set to the charging mode. During this time, the battery is charged with late-night power up to the capacity (for example, 40%) determined by the life event schedule of the next day.

(Execution stage of application pattern 1)
In the execution stage, a case will be described where power consumption related to lunch preparation, which is predicted to occur at 11 o'clock in the daytime, has not occurred.

FIG. 15 is a diagram showing the transition of the remaining battery level when the charging / discharging plan is not corrected. In the example shown in FIG. 15, the remaining battery level at 12 o'clock is lower than that in FIG. 14. This is because the preparation for lunch was shifted to 12:00, so that the power generated by the solar power generator 19 was consumed for lunch preparation at around 12:00 and the storage battery 20 could not be charged. Therefore, the storage battery 20 does not reach full charge at 15:00, and due to the power consumption after sunset, the remaining battery level becomes zero at 22:00 and power purchase occurs.

FIG. 16 is a diagram showing that the power consumption prediction is corrected. FIG. 17 is a diagram showing the transition of the remaining battery level when the purchase / suppression is performed by correcting the charge / discharge plan in accordance with the actual power consumption and the corrected power consumption prediction.

Referring to FIG. 16, a lunch event is expected to occur at 12:00 by detecting no lunch event at 11:00. Therefore, the predicted power is corrected so that the power consumption increases from the initial plan at around 12:00. If power consumption occurs at 12:00, surplus power at 12:00 is expected to decrease. For this reason, in order to suppress the risk of purchasing electricity due to charging, the charging / discharging plan of the storage battery 20 is changed so that the 12 o'clock range is set to the discharge mode and the start to the charging mode is set to 13:00.

Moreover, as a result of the discharge being performed at around 12:00, the charging power at 17:00 does not become 100% as shown in FIG. 17, so that the energy saving mode of each device should be strengthened from 17:00 to 22:00. Notify the user and confirm the user's intention. As a result of the user's approval for strengthening the energy saving mode, the power consumption plan in FIG. 16 is corrected to be reduced by, for example, 5% from the initial plan, and the decrease in the remaining battery level from 17:00 to 22:00 in FIG. The slope is gentle. As a result, in FIG. 15, the remaining battery level is zero at 22:00 and power purchase occurs. In FIG. 17, the remaining battery level remains at 22:00 in FIG. Is shown to be suppressed.

As described above, the HEMS controller according to the first embodiment changes the prediction of power consumption after the determination according to the occurrence state of the life event. This improves the accuracy of power consumption prediction. When the accuracy of power consumption prediction is improved, it can be used for a charging / discharging plan of a storage battery, and efficient energy management becomes possible.

[Embodiment 2]
In the first embodiment, it is detected that the occurrence time of the life event is deviated, the life event occurrence schedule is corrected accordingly, and the power consumption is predicted according to the corrected schedule. Improved prediction accuracy.

In the second embodiment, in addition to the first embodiment, it corresponds to the case where the life event does not occur when the user goes out. The second embodiment is different from the first embodiment in that the process of FIG. 18 is executed instead of FIG. Since the first embodiment and the second embodiment are common to the other drawings, the overlapping description will not be repeated.

In the second embodiment, when there is no change in the usage amount of water, gas, and electricity, the absence of the user going out is detected, and the subsequent power consumption plan is corrected.

FIG. 18 is a flowchart for explaining the process of correcting the power consumption plan in the second embodiment. The process of this flowchart is executed by the predicted value correction unit 12C in the HEMS controller 10 of FIG. The process of the flowchart of FIG. 18 is obtained by adding the processes of steps S101 to S103 to the flowchart of FIG. 11 described in the first embodiment. Therefore, since the processing of steps S1 to S18 has already been described, description thereof will not be repeated here.

Referring to FIG. 18, when the determination time comes in step S2, in step S101, the HEMS controller 10 determines whether or not the user is at home. There are various conditions for determining home stay. For example, if the amount of water and gas used is zero during the 2 hours, and only about standby power is consumed, check at home at the life event determination time. Notifications can be made and absent if there is no response from the user. In addition, the HEMS controller 10 can grasp | ascertain the usage-amount of water supply with the pulse transmitted from the water meter 9 of FIG. Moreover, the HEMS controller 10 can grasp | ascertain the usage-amount of gas with the pulse transmitted from the gas meter 7 of FIG.

As another method, the presence of a person cannot be detected by using the human detection function or the human sensor of each device.

In addition, in order to improve the accuracy, it is preferable to notify absence confirmation to a display unit such as a tablet terminal and confirm the presence or absence of a user's operation, regardless of which method is used to detect absence. When the operation of the tablet terminal is detected, it can be surely confirmed that the user is at home.

In step S101, when it is confirmed that the user is at home (YES in S101), the processing after step S4 is executed as in the first embodiment. On the other hand, if it is confirmed in step S101 that the user is absent (NO in S101), the process of step S102 is executed.

In step S102, the HEMS controller 10 changes the life event up to a preset return home time (for example, 17:00) to a plan for absence. In step S103, the HEMS controller 10 corrects the power consumption prediction, and then the process proceeds to step S18. The absence plan is returned to the original plan when the home is detected in step S101.

FIG. 19 is a diagram showing the power consumption corrected to the absence plan in the second embodiment. FIG. 20 is a diagram illustrating the transition of the remaining battery level when the charging / discharging plan is corrected and power purchase suppression is performed in accordance with the actual power consumption and the corrected power consumption prediction in the second embodiment.

In FIG. 19, at 11 o'clock, there was no use of water and gas for 2 hours, and the power consumption was about standby power, so the user was inquired about being at home, but there was no response from the user.

Accordingly, the HEMS controller 10 predicts that the user is absent from 11:00 to 17:00 in FIG. 19, and changes the life event to a plan that matches the absence. For this reason, the predicted value of power consumption from 11:00 to 17:00 is corrected less than the predicted value of the initial plan.

Based on the correction, the discharge mode setting from 11:00 to 11:59 was changed to the charge mode setting, so that the storage battery could be charged more reliably. For this reason, the remaining battery level at 11:00 in FIG. 20 is larger than the remaining battery level at 11:00 in FIG.

For this reason, as shown in FIG. 20, the time until 100% charging is completed can be shortened. As a result, it is possible to provide power that can be used without purchasing power from the completion of charging until recharging at midnight.

[Modification]
In the above embodiment, an example is shown in which the HEMS controller executes prediction of power consumption, life event planning, and the like, but the HEMS controller itself does not necessarily have to perform. For example, in the above embodiment, all or some of the processes executed by the control unit of the HEMS controller may be executed by the control unit of the cloud server. For example, when the power consumption prediction process is executed by the cloud server, the cloud server acquires data necessary for the process from the HEMS controller via the communication unit, the cloud server executes the process, and the process result is sent to the HEMS controller. You may send it.

FIG. 21 is a diagram showing the overall configuration of a modified energy management system 1A. Referring to FIG. 21, in the modified example, in addition to the power generation prediction, the cloud server 2 </ b> A performs the power consumption prediction and power consumption prediction value correction processing illustrated in FIGS. 11 and 18, and FIG. 12. The battery usage optimization process is performed. Data for measuring household power consumption is transmitted to the server 5B of the power management service company via the network 6 for billing. In addition to this, the smart meter 5A also transmits to the cloud server 2A via the HEMS controller 10A. Sent.

The HEMS controller 10A collects home information and transmits it to the cloud server 2A, and the cloud server transmits power generation amount prediction data, power consumption prediction data, and the control schedule of the storage battery 20 and the electrical device 30 to the HEMS controller 10A. . The HEMS controller 10A executes charge / discharge control of the storage battery 20 and energy saving operation control of the electric device 30 based on the received control schedule.

As described above, in the energy management systems shown in the first and second embodiments, the probability that the prediction accuracy after the current time is increased by correcting the prediction of power consumption based on the occurrence of life events. Can be raised.

In particular, if the accuracy of forecasting in the afternoon increases, it will be possible to appropriately select whether to sell the power generated by the solar power generation device or to charge the storage battery, etc., and to effectively use the solar power generation device it can. For this reason, it is possible to suppress the loss due to the prediction failure than the conventional day-ahead prediction type system.

In the example of the definition of the life event in FIG. 6, the time zone is set in advance, but the time zone may be set from statistical processing of the occurrence time of the past life event. For example, the range of ± 2σ may be adopted as the definition of the time zone of the life event when the fluctuation range is extracted for each start time and end time of each life event and the standard deviation is σ.

In addition, the coefficient of variation (standard deviation / average value) is obtained from past results for the two factors of occurrence time and power consumption for each life event, and for life events exceeding the judgment value, the predicted power consumption of this embodiment is calculated. It may be determined whether or not to execute the correction process, or to notify the user of a confirmation message and execute the correction process based on the response.

The number of detected life events is aggregated every day, the coefficient of variation indicating the degree of variation is calculated for the number of occurrences of life events, and correction processing for predicted power consumption is not performed for users (housing) whose coefficient of variation exceeds the judgment value Anyway.

Also, the coefficient of variation may be aggregated for each day of the week or each day, and this correction may be executed if there is little variation on a specific day of the week or a specific date.

Further, in the second embodiment, an example in which the usage amount of gas, water, or the like is used for determination at home is described. However, the usage amount of gas, water, or the like is added to the definition in FIG. It may be used to detect the occurrence of a life event. For example, in a home where a gas range is installed, if the gas usage fee increases during the day, it may be determined that cooking has been performed as a lunch preparation.

In the present embodiment, the prediction of the power consumption with improved accuracy is used as an example for the storage battery charging / discharging plan. However, the present invention is not limited to this. For example, the predicted value of power consumption improved in accuracy in the present embodiment, such as at the time of presenting a prediction to the user or cost estimation, can be used for various purposes.

The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is shown not by the above description of the embodiments but by the scope of claims, and is intended to include all modifications within the meaning and scope equivalent to the scope of claims.

1,1A energy management system, 2,2A cloud server, 4,5B server, 5 power measurement unit, 5A smart meter, 6 network, 7 gas meter, 8 tablet terminal, 9 water meter, 10, 10A HEMS controller, 11 storage unit , 12 arithmetic unit, 12A power consumption prediction unit, 12B life event management unit, 12C predicted value correction unit, 12D energy management unit, 12E control execution unit, 13 operation / display management unit, 18 device interface unit, 19 solar power generation Equipment, 20 storage batteries, 30 electrical equipment, 31A-31D air conditioner, 32A-32C lighting, 33 cooking heater, 34 microwave oven, 35 refrigerator, 36 kitchen lighting.

Claims (8)

An information collection unit that collects information on electrical equipment and displays a power consumption plan corresponding to the event plan on the display unit,
The event plan includes information on a time at which an event defined by at least one of an operation time zone, an operation time length, and the number of operations and an electric device to be used is scheduled to occur,
The information collecting unit is
Using the first event plan and the history information of the event completed from the start time of the first event plan to the determination time, a portion from the determination time to the end time of the first event plan is obtained. A controller configured to create a modified second event plan and the power consumption plan corresponding to the second event plan;
A display management unit that transmits an instruction to switch the image indicating the power consumption plan from a first image corresponding to the first event plan to a second image corresponding to the second event plan to the display unit. , Information gathering unit. The control unit includes occurrence of a first event in history information of the event that has occurred from the start time to the determination time, and the determination time from the start time of the first event plan. If the occurrence of the first event is not planned by the time, the occurrence of the first event is deleted from the portion from the determination time to the end time of the first event plan, and the second event The information collecting unit according to claim 1, wherein an event plan is created. The control unit does not include the occurrence of the first event in the history information of the event that has occurred from the start time to the determination time, and the determination from the start time of the first event plan. If the occurrence of the first event is planned by the time, the occurrence of the first event is added to the portion from the determination time to the end time of the first event plan, The information collecting unit according to claim 1, wherein the information collecting unit creates a second event plan. The control unit does not include the occurrence of the first event in the history information of the event that has occurred from the start time to the determination time, and the determination from the start time of the first event plan. If the occurrence of the first event is planned by the time and the determination time is before a predetermined point in time, the end of the first event plan from the determination time to the end Create the second event plan by adding the occurrence of the first event to the first part divided into a plurality of parts up to the time point,
The control unit does not include the occurrence of the first event in the history information of the event that has occurred from the start time to the determination time, and from the start time of the first event plan. If the occurrence of the first event is planned by the time of determination and the determination time is after reaching the predetermined time, the first event plan includes the first event. The information collecting unit according to claim 1, wherein the second event plan is created without adding an event occurrence. The information collecting unit according to any one of claims 1 to 4, wherein the event includes at least one of a breakfast event, a lunch event, and a dinner event in which a plurality of electric devices arranged in a kitchen are used. . A solar power generator is connected to the information collection unit,
The information collection unit according to any one of claims 1 to 5, wherein the power consumption plan is used to create a storage battery charge / discharge plan together with prediction data of the power generation amount of the solar power generation device. An information processing method for displaying a power consumption plan corresponding to an event plan on a display unit,
The event plan includes information on a time at which an event defined by at least one of an operation time zone, an operation time length, and the number of operations and an electric device to be used is scheduled to occur,
The information processing method includes:
Using the first event plan and the history information of the event completed from the start time of the first event plan to the determination time, a portion from the determination time to the end time of the first event plan is obtained. Creating a modified second event plan and the power consumption plan corresponding to the second event plan;
And a step of transmitting, to the display unit, an instruction to switch an image indicating the power consumption plan from an image corresponding to the first event plan to an image corresponding to the second event plan. A program for displaying a power consumption plan corresponding to an event plan on a display unit,
The event plan includes information on a time at which an event defined by at least one of an operation time zone, an operation time length, and the number of operations and an electric device to be used is scheduled to occur,
The program is
Using the first event plan and the history information of the event completed from the start time of the first event plan to the determination time, a portion from the determination time to the end time of the first event plan is obtained. Creating a modified second event plan and the power consumption plan corresponding to the second event plan;
A program for causing a computer to execute an instruction to switch an image indicating the power consumption plan from an image corresponding to the first event plan to an image corresponding to the second event plan to the display unit.

Images