JP7353096B2 - Power storage control device - Google Patents

Description

The present invention relates to a power storage control device that controls power storage in a power storage device in a system including a solar power generation device, a power storage device, and one or more power consuming devices.

When the current FIT (Feed-in Tariff) system, which stipulates the purchase price of energy by law, ends, the purchase price of electricity generated in-house using renewable energy such as solar power generation is expected to decline. Therefore, there is a need for self-supply and demand for self-generated power without selling it. However, power generation using renewable energy such as solar power generation has the characteristic that the amount of power generation tends to fluctuate due to the influence of the natural environment.

In order to cope with this situation, an increase in the number of households and businesses that have power storage devices in addition to private power generation devices is expected.
It is important for each household and each business to not only appropriately manage the amount of electricity consumed by their load, but also to wisely manage their own generated electricity to achieve economical energy management.

In this regard, the following technology has been proposed for a device that generates an operating schedule for each device based on the predicted power generation amount of the solar power generation device and the predicted load amount by each device, and controls each device. (For example, see Patent Document 1).
In other words, when generating a device operation schedule, if the operating time of a specific device is set during a time period in which the predicted power generation amount is lower than the predicted load amount, the operation time of that device is set so that the predicted power generation amount is lower than the predicted load amount. Change the time period to a time when the amount exceeds the amount, and reduce surplus electricity from solar power generation. Then, the late-night power amount to be charged is calculated from the predicted power load and the amount of remaining power in the power storage device, and the amount of charge of the power storage device is controlled. In this way, if there is a time period when there is a lot of surplus power from the solar power generation device, the equipment is made to consume as much of the surplus power as possible, so that the power storage device is not fully charged by charging with the surplus power.

Japanese Patent Application Publication No. 2011-92002

In order to realize economical energy operation, it is necessary to predict the amount of power generated by the solar power generation device and the amount of power consumed by the equipment.
However, it is inevitable that errors will occur between predicted values and actual values depending on the natural environment and usage conditions of the equipment.
However, if more precise charging/discharging control is performed on the power storage device based on predictions of the amount of power generation and power consumption, economic losses may occur due to prediction errors, which would be putting the cart before the horse.
Therefore, it would be convenient if user trends could be analyzed based on past performance and it would be possible to determine how precise energy management is appropriate to avoid negative economic effects.
This invention was made in consideration of the above circumstances, and provides energy management that is designed to prevent economic disadvantage to users due to errors between predicted values and actual values. It is something to do.

The present invention provides a power generation device that generates electricity using sunlight, a power storage device that stores power from the power generation device and an external commercial power system, and a power storage device that operates with the power from the power generation device, the commercial power system, and the power storage device. A device that controls power storage in the power storage device in a system including one or more devices, the device comprising: a predicted power generation amount that is a predicted value of the power generation amount of the power generation device every predetermined time; and a power consumption of the device every predetermined time. a predicted value acquisition unit that acquires a predicted surplus power generation amount from a predicted amount of power consumption, which is a predicted value of the amount of electricity consumed; and a control unit that controls storage of electricity in the power storage device, and the control unit determining whether or not to suppress the amount of electricity stored in the electricity storage device from the commercial power system during late-night power hours in order to reduce the amount of electricity purchased, based on the predicted surplus power generation amount; Based on the actual value of the past power generation amount of the device and the past actual value of the power consumption of the device, determine the magnitude of the possibility that economic disadvantage will occur due to the error between the predicted value and the actual value, and Provided is a power storage control device that controls the amount of stored power not to be suppressed when the power exceeds a predetermined standard.

From a different perspective, the present invention also provides a power generation device that generates electricity using sunlight, a power storage device that stores power from the power generation device and an external commercial power system, and a power storage device that stores power from the power generation device, the commercial power system, and the power storage device. A program executed by a control unit to control power storage in the power storage device in a power control system including one or more devices that operate with power of A process of obtaining a predicted surplus power generation amount from a certain predicted power generation amount and a predicted power consumption amount that is a predicted value of the power consumption amount of the device at a predetermined time, and a process of obtaining a predicted surplus power generation amount from a certain predicted power generation amount and a predicted power consumption amount that is a predicted value of the power consumption amount of the device at a predetermined time. A process of determining whether or not to suppress the amount of electricity stored in the power storage device from the commercial power system during the time period based on the predicted surplus power generation amount, and a process of determining the actual value of the past power generation amount of the power generation device A process of determining the possibility of economic disadvantage occurring due to an error between the predicted value and the actual value based on the past actual value of power consumption of the device, and a criterion for determining the possibility in advance. A power storage control program is provided that performs a process of controlling the amount of stored power not to be suppressed when the amount of stored power is exceeded.

In the power storage control device according to the present invention, the control unit is configured to cause economic damage due to an error between the predicted value and the actual value based on the past actual value of the power generation amount of the power generation device and the past actual value of the amount of power consumption of the device. The system determines the degree of possibility of profit generation and controls the amount of electricity stored not to be suppressed if the possibility exceeds a predetermined standard. It is possible to realize energy management that takes into consideration not to cause any economic disadvantage.
The same effect can be said for the above-mentioned energy storage business program.

1 is a block diagram showing a configuration example of a power control system according to Embodiment 1. FIG. 2 is a block diagram showing details of the controller shown in FIG. 1. FIG. 2 is an explanatory diagram that extracts and shows elements related to power flow in the power control system of FIG. 1. FIG. FIG. 2 is an explanatory diagram showing the flow of power during the late night power hours in a mode that is a reference for the economic effect of the power control system in FIG. 1; FIG. 2 is an explanatory diagram showing the flow of power in a state where there is surplus power during the day in a mode that is a standard for the economic effect of the power control system of FIG. 1; FIG. 2 is an explanatory diagram showing the flow of power in a state where there is no surplus power during the day in a mode that serves as a standard for the economic effect of the power control system in FIG. 1; FIG. 2 is an explanatory diagram showing the flow of power during the late night power period in a mode for suppressing the amount of stored electricity in the power control system of FIG. 1; FIG. 2 is an explanatory diagram showing the flow of power in a state where there is surplus power during the day in a mode for suppressing the amount of stored power in the power control system of FIG. 1; FIG. 2 is an explanatory diagram showing the flow of power in a state where there is no surplus power during the day in a mode in which the amount of stored power is suppressed in the power control system of FIG. 1; 7 is a graph illustrating an example of data that is referred to as a basis for determining the amount of stored electricity and whether or not boiling can be suppressed in a late-night power period in the first embodiment. FIG. 6 is an explanatory diagram illustrating an example of whether or not the controllability determination unit can suppress the amount of stored electricity, etc. during the late-night power hours in the first embodiment;

Hereinafter, this invention will be explained in further detail using the drawings. Note that the following description is illustrative in all respects and should not be construed as limiting the invention.
(Embodiment 1)
<<Configuration example of power control system>>
First, as an example of a system configuration in this embodiment, a power control system of a certain household that is connected to a commercial power system and includes a solar cell module, a storage battery, and a hot water storage type water heater will be described. Note that the target is not limited to homes, but may also be equipment, equipment, etc. of offices and factories.

FIG. 1 is a block diagram showing a configuration example of a power control system 100 according to the first embodiment. The power control system 100 is a power generation system that includes a solar cell module 91 and a storage battery 94, and is a distributed power source that supplies power using a power generation method that converts sunlight into electric power. Power control system 100 is connected to commercial power system 96 via transmission line P and power receiving point R. Further, a power consuming device 92 is also connected to the transmission line P. The power consumption device 92 is, for example, a household appliance, and consumes the power supplied to the transmission line P in the power control system 100. Note that the power consumption equipment 92 may or may not include a hot water storage type water heater as shown in FIG. 2, which will be described later.
As shown in FIG. 1, it includes a solar cell module 91, a storage battery 94, a power conditioner 93, and a controller 10.

The solar cell module 91 is a power generation device including a plurality of solar cells, generates power by receiving sunlight, and outputs DC power.
The storage battery 94 is a power storage device including a secondary battery that can be repeatedly stored and discharged. The storage battery 94 stores electricity using DC power supplied from the power conditioner 93, discharges DC power corresponding to the stored power, and operates the hot water storage type water heater via the bidirectional inverter 32. It supplies power to the power consuming devices 92 included in the power supply, and supplies power (sells power) to an external commercial power system 96. Note that the storage battery 94 may include not only a fixed storage battery but also a battery for an electric vehicle (EV).

The power conditioner 93 is connected to the solar cell module 91 and the storage battery 94, and is also connected to the commercial power system 96 via the transmission line P, and controls storage and discharge of the storage battery 94.
The power conditioner 93 converts DC power supplied from the solar cell module 91 and the storage battery 94 into AC power. Further, AC power supplied from the commercial power system 96 is converted into DC power and provided to the storage battery 94 . Furthermore, the power conditioner 93 controls the sale of electricity from the solar cell module 91 and the storage battery 94 to the commercial power system 96 .

The power meter 37 detects the power value transmitted between the power control system 100 and the commercial power system 96 via the transmission line P and the power receiving point R. Power purchased or sold to the commercial power grid 96 is detected. The detection result of the electricity meter 37 is output to the IC 39.
This power meter 37 includes a power selling power meter 371 and a purchasing power meter 372.
When power is transmitted from the power control system 100 to the commercial power grid 96 at the power receiving point R, the power selling amount meter 371 detects the value of the sold power as the amount of sold power, and integrates the amount of sold power. Then, the electricity sales meter 371 outputs these results to the IC 39.

When power is transmitted from the commercial power system 96 to the power control system 100 at the power receiving point R, the purchased power meter 372 detects the value of the purchased power as the amount of purchased power, and integrates the amount of purchased power. Then, the power purchase meter 372 outputs these results to the IC 39.
The voltmeter 38 is a voltage detection means that detects the voltage at the output terminal 93a of the power conditioner 93. The detection result of the voltmeter 38 is output to the IC 39. Further, the voltage detected by the voltmeter 38 indicates the voltage of the power transmitted through the transmission line P.

The IC 39 controls each component of the power conditioner 93 using information and programs stored in the memory 36. Further, the IC 39 performs power storage control to store power in the storage battery 94 using the power generated by the solar cell module 91 .
The IC 39 includes a conversion control section 392 as a functional component.
The conversion control unit 392 controls the bidirectional inverter 32 based on the detection results of the wattmeter 37 and the voltmeter 38, and particularly controls the direction of power conversion and the amount of power conversion.

The controller 10 controls the storage battery 94 and the bidirectional DC/DC converter 34, and receives user input. The controller 10 includes an input section 51, a controller communication section 52, a controller memory 53, and a controller IC 54.
The input unit 51 receives input from a user and outputs an input signal according to the input to the controller IC 54.

The controller communication unit 52 is a communication interface that communicates with the communication unit 35 of the power conditioner 93 wirelessly or by wire. The controller communication unit 52 receives the detection results of the power meter 37 and information on the solar cell module 91 and the storage battery 94 from the communication unit 35 . That is, the power purchased from the commercial power system 96 detected by the power system 37, the power sold to the commercial power system 96, the actual value of the power generated by the solar cell module 91, and the actual value of the stored power/discharged power of the storage battery 94. receive time series data.
The controller memory 53 is a nonvolatile storage medium that non-temporarily retains stored information even when power is not supplied. The controller memory 53 stores control information and programs used in each functional element of the controller 10 (particularly the controller IC 54). Furthermore, the actual values of purchased power, sold power, generated power, and stored power/discharged power received via the controller communication unit 52 are stored as history.

The controller IC 54 is a control unit that controls each component of the controller 10 using information and programs stored in the controller memory 53. The controller IC 54 includes a storage amount monitoring section 541 and an energy management section 542 as functional components.
The power storage amount monitoring unit 541 monitors the power storage amount of the storage battery 94 and determines whether or not the storage battery 94 has reached a fully charged power storage capacity.
The energy management unit 542 determines the power conversion direction, power conversion operation, etc. of the bidirectional DC/DC converter 34 based on the detection result of the electricity meter 37 and the monitoring result of the stored power amount monitoring unit 541. Control.

When the monitoring result of the storage battery amount monitoring unit 541 indicates that the storage battery 94 has reached a fully charged state, overcharging will occur if the storage battery 94 is further stored. In this case, the energy management unit 542 controls the bidirectional DC/DC converter 34 so as not to convert power in the power storage direction A. For example, the power conversion direction of the bidirectional DC/DC converter 34 is set to discharge direction B, or the amount of power conversion in the bidirectional DC/DC converter 34 is set to 0, and the power conversion in the bidirectional DC/DC converter 34 is performed. or stop the operation. In this way, the energy management unit 542 prevents overcharging of the storage battery 94, thereby suppressing its damage, deterioration of its power storage capacity, and reduction in its lifespan.

FIG. 2 is a block diagram showing details of the controller 10 shown in FIG. 1.
As shown in FIG. 2, the controller 10 includes a power generation amount prediction section 110, a power consumption amount prediction section 120, a remaining amount acquisition section 150, and a predicted value acquisition section 130. Furthermore, it includes an energy management section 542, a storage battery control section 170, a water heater control section 180, a power generation/consumption history 101, and a power storage (boiling) schedule 103.
The power generation history of the solar cell module 91 is recorded at predetermined intervals (for example, every 30 minutes or every hour) via a smart meter, a distribution board 81 with a measurement function (see FIG. 1), or using a separate sensor. and stored in the power generation/consumption history 101.
The same applies to the power consumption history of the power consumption equipment 92 (including the history of the amount of power used for boiling by the hot water storage type water heater 95) and the history of the amount of hot water stored in the hot water storage type water heater 95.
The controller 10 can read and analyze the power generation/consumption history 101.
Note that the power generation/consumption history 101 is included in the controller memory 53 shown in FIG.

The power consumption device 92 is a device that consumes (AC) power. Specific examples include home appliances such as air conditioners, microwave ovens, televisions, refrigerators, and washing machines. The hot water storage type water heater 95 is one of the power consuming devices 92, but since it has the function of converting electrical energy into thermal energy and storing energy, in FIG. It is shown separately from the consumer equipment 92. The power consumption device 92 is connected to the power distribution board 81 and consumes power supplied from the power distribution board 81.

The controller 10 is connected to at least some of the power consuming devices 92 via a home network using communication lines (not shown), and can comprehensively control these devices. In FIG. 2, at least a hot water storage type water heater 95, which is one of the power consumption devices 92, can be controlled. This may be called a home energy management system (HEMS). The protocol used by HEMS for communication between devices (devices) is, for example, EchonetLite.
The information collection server 97 communicates with the controller 10 via the web network 98, and can read and analyze the power generation/consumption history 101. The information collection server 97 also stores the zip code of the location where the power control system 100 is installed, and acquires weather conditions from a weather information company based on the zip code information.

The hot water storage type water heater 95 is connected to the electricity distribution board 81 . The hot water storage type water heater 95 performs boiling using electric power supplied via the electricity distribution board 81 . As a general rule, boiling is done during late night hours when electricity is cheap.
The late-night power period is typically from 11:00 PM to 7:00 AM, but it varies depending on the power company or the contract details (rate plan) entered into between the power company and the power user. The late night power time period may be any time period when power is cheap.

As described above, the external commercial power system 96 supplies power to the power control system (power purchase from the power control system side) and purchases power from the power control system (power purchase) in accordance with the control of the power conditioner 93. electricity sales from the control system side).
The weather information company provides the controller 10 with weather information necessary for predicting the next day's power generation amount via the web network 98. In addition, weather information on other days may be provided if necessary.

The power generation/consumption history 101 shown in FIG. 2 is historical data of power generation and consumption of a home in which a power control system is installed.
[Power generation amount prediction unit 110]
The power generation amount prediction unit 110 acquires weather information via the web network 98. Further, the power generation amount prediction unit 110 acquires the power generation history, that is, the actual value of the power generation amount from the power generation/consumption history 101. The power generation amount prediction unit 110 predicts the power generation amount for the next day based on the acquired weather information and power generation history. Note that the beginning and end of the day in this specification do not necessarily start from midnight. For example, the amount of power generated during the period from 11:00 p.m., which is the start time of the late-night power period, to 23:00 the next day, is predicted. Alternatively, the start and end of the day may be from the end time of the late night power period to the start time of the late night power period.

The start time for predicting the amount of power generation is typically one hour before the start of the late-night power period (generally 11 p.m.), but is not limited to this, and may even be 11 p.m. good. In addition, after predicting the amount of power generation, if the target state (setting state of available capacity for boiling, available capacity for electricity storage, electricity storage (boiling) schedule, etc.) at the end of the late-night power period can be secured by the process described later. , or after 23:00. As a result, processing can be performed over a wider time period, and processing can be performed in an appropriate time period for each power rate and contract details.

Specifically, the method for predicting the power generation amount is as follows. First, the power generation amount prediction unit 110 uses the next day's solar radiation prediction data of the area included in the weather information and multiplies it by a specific coefficient to predict the power generation amount. The coefficient is derived from the correlation between past solar radiation amount information and power generation amount. By using past power generation history data, the value takes into account factors such as the installation location and orientation, surrounding environment (such as shadows), equipment performance and deterioration status. Past power generation history data typically uses data for a period of about one week, but the optimal period may vary depending on the usage status of the user. Therefore, the optimal period may be derived separately. By using the power generation history based on the season, weather, temperature, or deterioration of the solar cell module 91, highly accurate predictions can be made.

The power generation amount prediction unit 110 transmits time-series data of the predicted power generation amount (predicted value of the daily power generation amount by the solar cell module 91) to the predicted value acquisition unit 130. Note that, since the time at which natural energy can generate electricity varies depending on the season, the time series of the amount of power generation is not limited to the above-mentioned times.
[Power consumption prediction unit 120]
Similar to the power generation amount prediction section 110, the power consumption prediction section 120 acquires weather information and consumption history, that is, the actual value of the total power consumption of each power consumption device 92 and the hot water storage type water heater 95, and calculates the power consumption. Predict the amount. The power consumption prediction unit 120 transmits the obtained time series of predicted power consumption to the predicted value acquisition unit 130.

[Predicted value acquisition unit 130]
The predicted value acquisition unit 130 calculates a time series of surplus power amount based on the received time series of predicted power generation amount and time series of predicted power consumption amount. The predicted value acquisition unit 130 transmits the time series of the calculated surplus power amount to the energy management unit 542, which will be described later. Further, the calculated surplus power amount is stored in the controller memory 53.
[Remaining amount acquisition unit 150]
In response to the request from the power storage allocation unit 164, the remaining amount acquisition unit 150 transmits the remaining amount of the storage battery 94 at the start time of the late night power period to the power storage allocation unit 164. Further, a time series of the amount of electricity stored in the storage battery 94 is stored in the controller memory 53. This part corresponds to the power storage amount monitoring unit 541 shown in FIG.
In addition, in response to a request from the boiling allocator 163, the remaining amount acquisition section 150 transmits the remaining amount of the hot water storage water heater 95 at the start time of the late night power period to the boiling allocating section 163.

[Energy management department 542]
The energy management unit 542 includes a surplus determination unit 161, a heating allocation unit 163, and a power storage allocation unit 164.
The energy management unit 542 transmits the time series of predicted surplus power received from the predicted value acquisition unit 130 to the surplus presence/absence determination unit 161. Note that if there is no predicted surplus power amount, the energy management unit 542 controls the storage battery 94 to store power until the storage battery 94 reaches the full power storage amount during the late night power period. However, if the predicted power consumption for the next day is smaller than the storage capacity of the storage battery 94, the battery 94 will not charge up to the full amount of power, but will charge up to the amount of power corresponding to the predicted power consumption. In addition, if there is no predicted surplus power, the hot water is boiled during the midnight power period, if possible, until the hot water stored in the hot water storage type water heater 95 is full.
On the other hand, control when there is predicted surplus power will be described in the surplus presence determination unit 161 below.

[Surplus presence/absence determination unit 161]
The surplus presence/absence determination unit 161 uses the received predicted surplus power amount to determine the presence or absence of the predicted surplus power amount, that is, whether or not there is a time period in the time series of the surplus power amount in which the predicted surplus power amount>0. do. When it is determined that there is a predicted surplus power amount, the surplus presence/absence determination unit 161 transmits a time series of the predicted surplus power amount to the power storage allocation unit 164.

[Boiling allocation section 163]
The boiling allocation unit 163 sends a request to the remaining amount acquisition unit 150 to transmit the current amount of hot water stored in the hot water storage type water heater 95, and acquires the remaining amount. Thereafter, using the time series of the received predicted surplus electric energy, the amount of power to be supplied to the hot water storage water heater 95 (power supply period) corresponding to the time and amount of boiling for boiling is determined as the scheduled amount of electric power for boiling. . In other words, it is based on the data received from the power generation/consumption history 101 indicating when and how much hot water storage is required, and the predicted data received from the predicted value acquisition unit 130 indicating when and how much surplus power will be generated. determine when and how much to boil. If there is no predicted surplus electricity, the water will be heated until the storage capacity of the hot water storage type water heater 95 is full, whereas if there is a predicted surplus electricity capacity, the boiling capacity of the storage type water heater 95 will be increased accordingly. In other words, the amount of power supplied to the hot water storage type water heater 95 is suppressed.
However, whether or not to actually suppress the amount of power supplied to the hot water storage type water heater 95 is determined by a controllability determination unit 165, which will be described later.
Then, the boiling allocation unit 163 stores the suppressed amount of power supplied to the hot water storage type water heater 95 in the controller memory 53 to leave a history.
By setting a power purchase schedule during the late-night power period and a heating schedule during the surplus power period, the controller 10 can secure free capacity of the hot water storage type water heater 95 at the end of the late-night power period.

[Electricity storage allocation unit 164]
The power storage allocation unit 164 determines the amount of power obtained by subtracting the expected amount of power for boiling from the time series of the predicted surplus amount of power as the scheduled amount of power to be stored, which is the scheduled amount of charge of the storage battery 94 . That is, first, the amount of power supplied to the hot water storage type water heater 95 is allocated, and if there is a surplus, the amount of power stored in the storage battery 94 is allocated, and the amount of power stored in the storage battery 94 is adjusted.
If there is no difference in the amount of electricity that is obtained by subtracting the amount of electricity scheduled for boiling from the predicted surplus electricity amount, the storage battery 94 will store electricity until it reaches its full storage capacity (however, if the difference in electricity amount is smaller than the storage capacity, the storage battery 94 will store electricity up to the corresponding amount of electricity) If there is a subtracted amount of power, the adjustment amount for suppressing the storage of power in the storage battery 94 is determined accordingly.
However, whether or not to actually suppress power storage is determined by a controllability determination unit 165, which will be described later.
Then, the power storage allocation unit 164 stores the suppressed adjustment amount of power storage in the controller memory 53 to leave a history.

The power storage (boiling) schedule 103 is a future schedule of power generation, consumption, power purchase, power storage, discharging, and boiling of the power control system 100, which is set by the power storage allocation unit 164 and the heating allocation unit 163.
Note that the power storage (boiling) schedule 103 is included in the controller memory 53 shown in FIG.
By setting a power purchase schedule during the late-night power period and a power storage schedule during the surplus power period, the controller 10 can secure free capacity of the storage battery 94 at the end of the late-night power period.
[Controlability determining unit 165]
The control possibility determination unit 165 refers to the power generation/consumption history 101 and determines the amount of power stored in the storage battery 94 or the power supply to the hot water storage type water heater 95 when the state of the power control system 100 is predicted to indicate that there is surplus power. It is determined whether there is a possibility that the user will suffer an economic disadvantage if the amount is suppressed. That is, the degree of possibility that a negative economic effect will occur is determined. If it is determined that this possibility is high, the electricity storage allocation unit 164 prevents the amount of electricity stored in the storage battery 94 from being suppressed during the late night power hours, and similarly the boiling allocation unit 163 prevents the storage type water heater 95 from suppressing the amount of electricity stored in the storage battery 94 during the late night power hours. Avoid restricting the amount of power supplied.

[Storage battery control unit 170]
The storage battery control unit 170 controls the storage battery 94 according to the set electricity storage (boiling) schedule 103.
The storage battery control unit 170 stores electricity in the storage battery 94 according to the schedule during the late night power period. After the late-night power period ends, if the amount of power generated by the solar cell module 91 is less than the total amount of power consumed by the power consuming equipment 92 (including the amount of power consumed for heating the hot water storage type water heater 95), the solar cell module 91 is discharged. The amount of electricity purchased from the commercial power system 96 is suppressed. Conversely, if the amount of power generated by the solar cell module 91 exceeds the total amount of power consumed by the power consuming devices 92, the surplus power is stored in the storage battery 94. Note that the amount of power generated by the solar cell module 91 is due to fluctuations in the natural environment, specifically, fluctuations in the amount of sunlight, and fluctuates on a scale shorter than the time interval of the power generation/consumption history 101, for example, on a second-by-second basis. As a result of the storage battery control unit 170 controlling the charging and discharging of the storage battery 94 after the midnight power period as described above, the storage battery 94 absorbs fluctuations on a short time scale.

If the prediction deviates to the side where the amount of power generation is small, the storage battery control unit 170 may cause the storage battery 94 to perform a discharging operation. For example, if the predicted amount of power generation is incorrect while the hot water storage type water heater 95 is heating water, the insufficient power is compensated for by discharging from the storage battery 94. Thereby, the amount of power purchased from the commercial power grid 96 can be suppressed by allocating the amount of power from natural energy.
[Water heater control unit 180]
The water heater control unit 180 controls the hot water storage type water heater 95 according to the set electricity storage (boiling) schedule 103. In other words, the amount of power supplied to the hot water storage type water heater is suppressed.

≪Energy management standard mode≫
Next, the standard mode of energy management in the power control system 100 will be described.
The control possibility determining unit 165 determines the possibility that the user will suffer economic disadvantage if the amount of electricity stored in the storage battery 94 or the amount of electricity supplied to the hot water storage type water heater 95 is suppressed when it is predicted that there is surplus electricity. judge. That is, the degree of possibility that a negative economic effect will occur is determined. Here, the determination as to whether the economic effect is positive or negative is made based on some standard, and the energy management mode that is the standard is referred to as a standard mode in this specification.
Energy management in the standard mode is performed as follows.

In the case of the reference mode, the energy management unit 542 stores electricity during the late night power period until the storage battery 94 is fully charged. Further, the water heater control unit 180 performs boiling until the hot water storage type water heater 95 is full.
That is, energy management in the standard mode does not perform storage of electricity and suppression of heating during the late-night power hours based on the amount of surplus electricity predicted to occur the next day.
During the daytime after the end of the midnight power period, during the time period when the total power consumption by the power consuming devices 92 is greater than the power generated by the solar cell module 91, the storage battery 94 is discharged to suppress the amount of power purchased.
During the daytime period when the generated power is larger than the total consumed power, that is, during the time period when surplus power is generated, the storage battery 94 is stored with the surplus power. The stored electricity is used for power consumption at night when solar power is not available, reducing the amount of electricity purchased.

≪Energy management based on predicted surplus electricity and its economic effects≫
In contrast to the above-described reference mode, in this embodiment, the amount of electricity stored in the storage battery 94 during the late night power hours is suppressed based on the predicted surplus electricity amount, and the boiling of the hot water storage type water heater 95 is suppressed.
Specifically, based on the time series of predicted power consumption provided by the power generation amount prediction unit 110 and the time series of predicted power consumption provided by the power consumption prediction unit 120, the predicted value acquisition unit 130 calculates the amount of surplus power. Calculate the time series.
If it is predicted that no surplus electricity will be generated the next day, electricity storage and heating are performed in the same way as in the standard mode.
On the other hand, when it is predicted that surplus power will be generated the next day, the energy management unit 542 suppresses the amount of power stored in the storage battery 94 during the late night power period based on the time series of the calculated surplus power. If there is a margin in the predicted surplus electric power, the heating of the hot water storage type water heater 95 is also suppressed.

FIG. 3A is an explanatory diagram that extracts and shows elements related to power flow in the power control system of FIG. 1. The arrows in FIG. 3A indicate the flow of power in the reference direction. That is, the flow of power in the direction of the arrow is defined as a positive value. Regarding the storage battery 94, discharging is a positive power flow, and charging is a negative power flow. Regarding the commercial power system 96, power purchase is a positive power flow, and power sale is a negative power flow.
FIG. 3B shows a typical example of the power flow during the late night power period in the reference mode described above. For parts where the magnitude and direction of power flow are different from those in FIG. 3A, the power symbol is enclosed in a frame. As shown in FIG. 3B, there is a high possibility that the solar cell module 91 will not generate power during the late night power period. In addition, during the late night power hours, the storage battery 94 is stored with inexpensive power from the commercial power system 96 so that it is fully charged. The hot water storage type water heater 95 is also heated so that it becomes full.

FIG. 3C shows a typical example of power flow in the reference mode with surplus power during the day. During the day, the solar cell module 91 generates power. The storage battery 94 is basically fully charged with the power stored during the late night power hours, and there is no room for storing surplus power. The surplus power is sold to the commercial power system 96. However, if the amount of surplus electricity is small, the electricity will not be sold.
FIG. 3D shows a typical example of power flow in the reference mode with no surplus power during the day. During the day, the solar cell module 91 generates power, and the storage battery 94 discharges to cover the power consumption of the power consumption equipment 92. Even so, the power consumption of the power consumption equipment 92 exceeds the power consumption, so power is purchased from the commercial power grid 96.

3E to 3G correspond to FIGS. 3B to 3D, respectively, and illustrate typical power flows in the energy management mode (hereinafter also referred to as energy management mode) according to this embodiment.
That is, FIG. 3E shows a typical example of power flow during the late night power period in the energy management mode. The power flow shown in FIG. 3E is the same as in FIG. 3B. However, this differs from FIG. 3B in that the amount of electricity stored in the storage battery 94 and the boiling of the hot water storage type water heater 95 may be suppressed based on the predicted surplus power generation amount.

FIG. 3F shows a typical example of power flow in energy management mode with surplus power during the day. The difference from FIG. 3C is that power is stored in a storage battery 94 instead of selling power to a commercial power system 96. Since the generation of surplus power is predicted and the amount of power stored during the late night power hours is suppressed, the storage battery 94 has room to store power during the day. However, if the amount of surplus power is too large to be stored in the storage battery 94, it will be sold.
FIG. 3G shows a typical example of power flow in energy management mode with no surplus power during the day. The power flow when there is no surplus power is the same as in FIG. 3D.
The differences in typical power flow between the standard mode and the energy management mode according to this embodiment have been described above.

However, a prediction error occurs between the predicted power generation amount and the actual power generation amount. A prediction error also occurs between the predicted power consumption amount and the actual value of the power consumption amount.
Negative economic effects occur, for example, when it rains even though weather information predicts it will be sunny.
If it is predicted that the weather will be sunny, the energy management mode will hardly store electricity in the storage battery 94 during the late night power hours. On the other hand, in the reference mode, electricity is stored so that the storage battery 94 is fully charged during the late night power hours.
If it rains in this state, in the energy management mode, the amount of electricity stored in the storage battery 94 will quickly become empty, and the shortage will be made up by purchasing electricity. In this case, the amount of electricity purchased will obviously be larger than in the standard mode.
In other words, energy management using the energy management mode has a negative economic effect compared to energy management using the reference mode.

On the other hand, a positive economic effect occurs when, for example, it is predicted that the weather will be sunny based on weather information, and it is sunny as predicted.
When it is predicted that the weather will be sunny, the energy management mode suppresses the storage of electricity in the storage battery 94 during the late night power hours as described above. For example, almost no electricity is stored. On the other hand, in the reference mode, electricity is stored so that the storage battery 94 is fully charged during the late night power hours.
When the weather clears in this state, surplus power can be stored in the storage battery 94 in the energy management mode, but in the standard mode there is no room to store the surplus power in the storage battery 94 and the power is sold. It is assumed that the unit price of electricity purchased during the late night electricity hours when electricity is stored in 94 is expected to be lower.
In other words, in the standard mode, surplus power during the day cannot be stored because the storage battery 94 is charged during the late-night power period, and electricity is sold at a low unit price, but in the energy management mode, surplus power during the day is stored in the storage battery 94. to be able to store electricity. Energy management using the energy management mode improves the balance of electricity charges compared to energy management using the standard mode, and produces a positive economic effect.

≪Determination of the possibility that negative economic effects will occur≫
This embodiment not only suppresses power storage and heating during late-night power hours based on the predicted surplus power generation amount, but also determines the possibility of negative economic effects for users as a result of the suppression control. However, if there is a strong possibility, suppressive control should not be performed.
The possibility of negative economic effects is determined based on past performance. The past performance may be based on the performance of the entire commercial power system 96, but it may also be based on the performance of each power control system, which is particularly preferable when considering recent trends in performance. .
Note that in this specification, it is assumed that the users are different for each power control system. That is, each user means each power control system.

FIG. 4 is a graph illustrating an example of data that is referred to by the controllability determining unit 165 as a basis for determining the amount of stored electricity and whether or not boiling can be suppressed in the late-night power hours in this embodiment. The graph is based on data stored in the power generation/consumption history 101. A graph is plotted for a plurality of users based on the actual values of monthly power consumption and amount of power generation. Based on each user's performance over multiple months. The unit of one month is for convenience, and the aggregation period is not limited to this. For example, the aggregation period may be half a month, or may be any other predetermined period.
In addition, in order to show that the determination index is effective for a plurality of users, FIG. 4 calculates a correlation based on the performance values of a plurality of users. However, the actual determination may be made based on the correlation for each user.

In FIG. 4, the horizontal axis is the number of days in each month where the "actual value of power consumption"/"actual value of power generation amount" exceeds 1. The vertical axis represents the magnitude of the economic effect for that month (both positive and negative). Here, the economic effect for each month is calculated as follows.
The control possibility determining unit 165 refers to the controller memory 53 and records the history of the amount of electricity stored in the storage battery 94 during the late night power period and the history of the amount of electricity supplied to the hot water storage type water heater 95 based on the predicted surplus electricity amount for the next day. get. In addition, the actual value of the amount of power generation and the actual value of power consumption for each day stored in the power generation/consumption history 101 is acquired.

Then, on the day when the amount of stored electricity and the amount of electricity supplied are suppressed based on the predicted surplus electricity amount for the next day, the electricity cost required for storing electricity in the storage battery 94 and supplying electricity to the hot water storage type water heater 95 during the late night power hours is calculated. do. That is, the electricity cost required for the power storage and power supply during the late night power period in the energy management mode is calculated.
In addition, the electricity bill is calculated when the storage battery 94 is stored to a fully charged state and the hot water storage type water heater 95 is heated until it is fully charged in the same late-night power period. That is, the electricity cost required for the power storage and power supply during the late night power period in the reference mode is calculated.
Furthermore, the electricity bill corresponding to the amount of power consumed during the day after that is calculated. That is, the electricity bill is calculated based on the actual power consumption in the energy management mode. Furthermore, the amount of power consumed during the day in the case of the standard mode and the electricity bill based on the amount of power consumed are calculated. Surplus power that cannot be stored because the storage battery 94 is fully charged is sold, and the electricity bill obtained by selling the power is calculated.

The economic effect is
Economic effect = electricity bill in standard mode - electricity bill in energy management mode.

If the suppressed power amount and the purchased power amount are equal, that is, if the power amount suppressed during the late-night power period is completely purchased during the daytime, the economic effect will be zero. In this case, it is equivalent to the reference mode.
In the standard mode, the power is stored until it is fully charged during the late night power hours, so the amount of power to be suppressed is zero. If the battery is fully charged during the late night power hours in energy management mode, the economic effect of the above equation is always zero.
On the other hand, if the amount of purchased electricity exceeds the amount of suppressed electricity, a negative economic effect will occur. If a negative economic effect occurs, it can be said that it would have been more economical not to suppress the amount of electricity stored in the storage battery 94 and the amount of power supplied to the hot water storage type water heater 95 based on the predicted surplus power generation amount.

According to Figure 4, users whose "actual value of power consumption"/"actual value of power generation amount" exceeds 1 for more than 15 days, such as user 1 and user 2, may experience zero or negative economic effects. Highly sexual. On the other hand, users whose "actual power consumption value"/"actual power generation value" exceeds 1 for 15 days or less, such as users 5 and 6, may experience positive economic effects. expensive.
Regarding User 4, although there are some cases in which the number of days exceeds 15, in most cases it is 15 days or less, which is likely to result in a positive economic effect.
For user 3, cases in which the number of days exceeds 15 days and cases in which the number of days is 15 days or less are almost equal, and correspondingly there are cases in which there is a positive economic effect and cases where there is a negative economic effect.
From this, we can calculate the difference between the number of days for which the "actual value of power consumption"/"actual value of power generation" exceeds 1 for each predetermined aggregation period (one month in the case of Figure 4) and the economic effect for each aggregation period. By determining the correlation, it is possible to determine the magnitude of the possibility that a negative economic effect will occur.
Note that "15 days" is just an example of the reference number of days selected based on the graph of actual values shown in FIG.

Note that although Figure 4 shows the correlation based on the monthly results of different users, even for the same user, such as user 3, the correlation may be positive or negative depending on the natural environment or usage status of power consumption equipment. It may also have an economic effect. Therefore, the correlation may be determined for each user to determine the likelihood of negative economic effects.
In addition, since there is a high possibility that negative economic effects will occur, the correlation between actual values is also determined regarding the standard that does not limit the amount of electricity stored in the storage battery 94 or the amount of electricity supplied to the hot water storage type water heater 95 during late night hours. A suitable standard may be set based on the following.

≪Energy management based on judgments related to economic effects≫
Next, the processing executed by the controllability determination unit 165 will be described.
FIG. 5 is a diagram illustrating an example of switching whether or not the amount of stored electricity, etc. can be suppressed during the late night power hours by the controllability determining unit 165.
In the example shown in FIG. 5, the aggregation period is one month, and the reference number of days is 15 days. The top row of Figure 5 shows each month from August of a certain year to March of the next year, and the center row shows the "actual value of power consumption"/"actual value of power generation" in each month. Indicates the number of days exceeding 1, that is, the total number of days in each month. The bottom row shows the determination result of whether or not to suppress the amount of electricity stored in the late-night power period in the next month based on the predicted surplus power amount, based on the tally result shown in the middle row.

The controllability determining unit 165 determines whether control is possible for the next month at each end of the aggregation period, that is, at the end of each month.
For example, as shown in FIG. 5, the total number of days in August is less than or equal to the reference number of days (the specific example in FIG. 5 is 15 days). Based on the results, it will be determined that suppression control is possible for the following September. In other words, we judge that the possibility of negative economic effects occurring in September is small. Therefore, based on the predicted surplus power amount, the amount of electricity stored during the late night power hours, etc. is suppressed. The “〇” for September on the bottom line represents this.

The number of days for data collection in September is also below the standard number of days. Based on the results, the determination result is that suppression control is possible in October as well as in September (see "O" for October in the bottom row).
The number of days in October was 16, which exceeds the standard number of days of 15. Based on the results, we judge that there is a high possibility of negative economic effects starting from the following November. Therefore, starting from November, the system will stop suppressing the amount of electricity stored during late-night power hours based on the predicted surplus power amount (see November's "Closed" on the bottom line).

Once it has been determined not to suppress the amount of electricity stored during late-night power hours, the control will not resume suppressing the amount of stored electricity during late-night power hours until three consecutive months in which the number of aggregation days is equal to or less than the reference number of days continues.
Note that 3 months is an example. The number of months at which it is determined that the inhibitory control is to be resumed may be appropriately set depending on whether the transition of the determination of whether or not control is possible based on the number of days of aggregation is stable or unstable. If the trend is stable, set it to a smaller number of months, and if it is unstable, set it to a larger number of months. Further, the setting of the number of months may be different for each user.

In Figure 5, there are three consecutive months from November to January in which the number of days counted is less than the standard number of days. Therefore, in February, the month following January, restrictions on the amount of electricity stored, etc. will be resumed (see "〇" for February on the bottom line).
Until then, from November to January, there will be a period in which the amount of electricity stored will not be curtailed (see "〇" for November to January on the bottom line).
By setting the criteria for restarting the inhibitory control more strictly than the criteria for suspending the inhibitory control, instability in determining whether control is possible is prevented.

(Embodiment 2)
In Embodiment 1, the number of days during which the "actual value of power consumption"/"actual value of power generation amount" exceeds 1 throughout one month of the aggregation period, in other words, the actual value of power generation amount exceeds the actual value of power consumption. Although we have counted the number of days in which the amount of power consumption is less than 1, it is also possible to count the number of days in which the "actual value of power consumption"/"actual value of power generation amount" exceeds 1 for the most recent predetermined period of the aggregation period. .
By doing so, it is possible to make a determination based on the most recent situation during the aggregation period.
For example, assume that the aggregation period is "one month" and the predetermined number of days is half the number of days in the month. The control possibility determination unit 165 counts the number of days for which the "actual value of power consumption"/"actual value of power generation amount" is 1 or more for the second half of this month, and determines whether or not the reference number of days has been exceeded. .

(Embodiment 3)
Furthermore, in the first embodiment, the reference number of days for determining that a negative economic effect is likely to occur is a fixed value. It's okay.
According to this aspect, the reference number of days for judgment can be updated based on the latest situation and corrected to an appropriate value.

For example, if the control feasibility determining unit 165 determines that the number of days in which disadvantages have occurred has increased in the recent past even though the amount of stored electricity was not suppressed because it was determined that there was a small possibility that a negative economic effect would occur. If it is determined, the controllability determining unit 165 reduces the reference number of days to make it easier to suppress the amount of stored electricity. On the other hand, if it is determined that there is a recent increase in the number of days without any disadvantages even though the amount of electricity storage has been curtailed because it is determined that there is a high possibility of negative economic effects occurring, it may be determined whether control is possible or not. The determination unit 165 increases the reference number of days to make it more difficult to suppress the amount of stored electricity.

(Embodiment 4)
In the embodiments described above, the probability of negative economic effects occurring is calculated based on the correlation between the economic effects and the number of days for which the "actual power consumption amount"/"power generation amount actual value" is 1 or more. Deciding.
In contrast, in this embodiment, the possibility of a negative economic effect occurring is determined depending on the magnitude of the prediction error. Here, since the prediction error is the difference between the predicted value and the actual value, this method is similar to the method of the first embodiment in that the possibility of a negative economic effect is determined based on past results.

In this embodiment, the controllability determining unit 165 obtains the predicted value and actual value of daily generated power, and the predicted value and actual value of daily power consumption. Then, the average prediction error during the aggregation period is calculated. If the calculated average error exceeds a predetermined threshold, the amount of stored electricity is not suppressed during the late night power hours.
According to this embodiment, the magnitude of the possibility that a negative economic effect will occur is determined based on the prediction error.
For example, if the aggregation period is "one month" and the average of the sum of the prediction errors of this month's generated power and power consumption exceeds a predetermined threshold, the control possibility determination unit 165 Restraints are suspended.

(Embodiment 5)
In Embodiment 4, the magnitude of the possibility that a negative economic effect will occur was determined based on the average of prediction errors over one month of the aggregation period. The average of prediction errors may be calculated.
According to this aspect, it is possible to determine the magnitude of the possibility that a negative economic effect will occur based on the average of prediction errors for the most recent predetermined number of days in the aggregation period. That is, the determination can be made based on the most recent average error situation.
For example, assume that the aggregation period is "one month" and the predetermined number of days is half the number of days in the month. In that case, the control unit calculates the average error between the predicted value and the actual value for the second half of this month, and determines whether the calculated average error exceeds the threshold value.

(Embodiment 6)
Further, in the fourth embodiment, the threshold value for determining that there is a high possibility that a negative economic effect will occur is a fixed value. good.
In this way, the threshold value for determination can be updated based on the most recent situation and corrected to an appropriate value.

For example, if it is determined that the possibility of negative economic effects occurring is small and the amount of electricity stored, etc. has not been curtailed, but it is determined that the number of days on which disadvantages have occurred has increased in the recent past, the control In this section, the threshold value is made smaller to make it easier to suppress the amount of stored electricity. On the other hand, even though we have decided that there is a high possibility of economic disadvantage for users and have curtailed the amount of electricity stored, etc., we have determined that the number of days without any disadvantage has increased in the recent past. In this case, the control unit increases the threshold value to make it more difficult to suppress the amount of stored electricity.

(Embodiment 7)
In this embodiment, the controllability determination unit 165 determines whether the "actual value of power consumption amount"/"actual value of power generation amount" described in the first embodiment is 1 or more, and the prediction error described in the fourth embodiment. The probability of a negative economic effect occurring is determined by combining the average of
In this way, the number of days in which the actual value of power generation amount was lower than the actual value of power consumption in the aggregation period, that is, the number of days where "actual value of power consumption"/"actual value of power generation amount" is 1 or more. , and the average of the prediction errors, it is possible to determine the degree of possibility that a negative economic effect will occur due to the error between the predicted value and the actual value.
For example, assume that the aggregation period is "one month." Throughout the aggregation period, if the number of days where the "actual value of power consumption"/"actual value of power generation amount" exceeds 1 exceeds the standard number of days, and the average prediction error throughout the aggregation period exceeds the threshold, The controllability determination unit 165 suspends suppression of the amount of stored electricity, etc. from the next month.

(Embodiment 8)
In Embodiment 1, when the number of days in which the "actual value of power consumption"/"actual value of power generation amount" is 1 or more exceeds the standard number of days, the amount of stored electricity, etc. is suppressed during the late night power hours from the next aggregation period. will be suspended. Thereafter, when a predetermined number of aggregation periods in which the number of aggregation days does not exceed the reference number of days continues, suppression of the amount of stored electricity, etc. is resumed during the late night power hours from the next aggregation period.
The same method is applied to the judgment based on the prediction error described in the fourth embodiment. That is, when the average of the prediction errors in the aggregation period exceeds the threshold value, the suppression of the amount of stored electricity, etc. is stopped during the late night power hours from the next aggregation period. After that, when a predetermined number of aggregation periods in which the average prediction error does not exceed the threshold value continue, the control system resumes suppressing the amount of stored electricity, etc. during the late-night power hours from the next aggregation period.
In this way, it is determined that there is a high possibility of a negative economic effect occurring based on the average error between the predicted value and the actual value, and after suspending the suppression of the amount of electricity stored, etc. from the next aggregation period, a predetermined number of aggregations are performed. Suppression of the amount of stored electricity, etc. can be resumed based on changes in the situation over a period of time.

(Embodiment 9)
In the first embodiment, after stopping the suppression of the amount of stored electricity, etc. during the late-night power period, when a predetermined number of aggregation periods in which the number of days of aggregation does not exceed the reference number of days continues, the suppression of the amount of stored electricity, etc. is resumed.
Similarly, in the eighth embodiment, after stopping the suppression of the amount of stored electricity, etc. during the late-night power period, if a predetermined number of aggregation periods in which the average prediction error does not exceed the threshold value continue, suppression of the amount of stored electricity, etc. is resumed. .
The number of aggregation periods involved in determining restart is assumed to be a fixed value.
On the other hand, in this embodiment, the controllability determination unit 165 updates the number of aggregation periods related to the restart determination based on the most recent changes.
According to this aspect, the number of aggregation periods related to the determination of restart can be updated based on the latest trends and corrected to an appropriate value.

As mentioned above,
(i) A power storage control device according to the present invention includes a power generation device that generates electricity using sunlight, a power storage device that stores power from the power generation device and an external commercial power system, and a power storage device that stores power from the power generation device, the commercial power system, and the power storage system. A device that controls the storage of electricity in the power storage device in a system including one or more devices that operate with electric power from the device, the predicted power generation amount being a predicted value of the power generation amount for each predetermined time of the power generation device, and the device. a predicted value acquisition unit that acquires a predicted surplus power generation amount from a predicted power consumption amount that is a predicted value of the power consumption amount for each predetermined time; and a control unit that controls storage of power in the power storage device, the control unit , determine whether or not to suppress the amount of electricity stored in the power storage device from the commercial power system during the late-night power period in order to reduce the amount of electricity purchased outside of the late-night power period, based on the predicted surplus power generation amount. and the possibility of economic disadvantage arising due to an error between the predicted value and the actual value based on the past actual value of the power generation amount of the power generation device and the past actual value of the amount of power consumption of the equipment. It is characterized by determining the magnitude and controlling the amount of stored electricity not to be suppressed if the possibility exceeds a predetermined standard.

In the present invention, a power storage control device including a predicted value acquisition section and a control section typically includes a CPU, a memory, an input/output circuit, and the like as hardware resources. That is, the functions of the power storage control device are realized by the CPU executing the control program stored in the memory. However, the specific form of the hardware resources is not limited to this, and any form may be used as long as it realizes equivalent functions.
Specifically, the controller 10 in the above-described embodiment corresponds to the power storage control device in the present invention. Further, the predicted value acquisition unit 130 in the embodiment corresponds to the predicted value acquisition unit in the present invention. Furthermore, the energy management unit 542 in the embodiment corresponds to the control unit in the present invention.

Moreover, power purchase means receiving power supply from an external commercial power system to the power control system. Electric power supplied from a commercial power system is consumed by power consuming devices in a power control system or stored in a storage battery.
On the other hand, power selling means sending power from the power control system to an external commercial power system. Normally, surplus power generated by a power generation device in a power control system but not consumed by a power consuming device is charged into a storage battery, and power that cannot be stored in the storage battery is sold.

The unit price of electricity purchase and sale is determined by a contract between a user (power user) of a power control system and an electric power company that operates a commercial power system. Generally, the unit price of electricity purchased varies depending on the time of day. That is, the electricity purchase unit price is set lower during the late-night power hours when the demand for electricity is low compared to outside the late-night power hours when the demand for electricity is high. Through this rate structure, electric power companies are trying to level out power demand. The late night power period is typically from 11pm to 7am. However, the start and end of the late-night power period may be set at different times depending on the power company or contract.

Further, in this specification, it is assumed that the unit price of electricity sold is set lower than the unit price of electricity purchased during late-night electricity hours. Therefore, reducing the amount of electricity purchased is in the economic interest of the user.
The amount of power generated by solar power fluctuates from moment to moment depending on the natural environment. Furthermore, the amount of power consumed by power consuming devices also fluctuates from moment to moment. In order to reduce the amount of electricity purchased, it is necessary to predict these fluctuations and control the timing and amount of electricity storage in advance based on it.
Advance control ensures that when surplus power is generated, there is free capacity that can be stored in the power storage device, and on the other hand, when there is no surplus power and electricity is to be purchased, the power stored in the storage battery is The ideal is to be able to allocate this amount to reduce electricity purchases.
However, it is inevitable that an error will occur between the predicted value and the actual value. Further, the magnitude of the error cannot be calculated in advance. This is because if the error can be calculated in advance, the error can be reduced to zero, and the occurrence of the error can therefore be avoided.
However, it is possible to statistically predict the magnitude of the error based on past results.

Furthermore, preferred embodiments of this invention will be explained.
(ii) The control unit calculates, in a plurality of past aggregation periods, (1) the amount of power consumption based on the actual value of the amount of power generation for that day for the day on which the predicted surplus power generation amount is predicted to occur during any one of the aggregation periods; The difference between the actual surplus power generation amount after subtracting the actual value and the amount of electricity stored that was suppressed based on that day's forecast; (2) the number of days during each aggregation period when the actual value of power generation amount was lower than the actual value of power consumption; The degree of possibility of economic disadvantage occurring may be determined based on the correlation between
In this way, it is possible to determine the degree of possibility that an economic disadvantage (negative economic effect) will occur based on the correlation between (1) and (2) above.

(iii) The control unit predicts the presence or absence of predicted surplus power generation on a daily basis, makes judgments regarding the possibility of economic disadvantage occurring every predetermined aggregation period, and calculates the actual amount of power generation during the current aggregation period. The above judgment is made based on whether the number of days in which the amount of electricity consumption is lower than the actual value exceeds a predetermined standard number of days, and if the standard number of days is exceeded, it is predicted that the predicted surplus power generation will occur in the next aggregation period. The amount of stored electricity may also be controlled not to be suppressed on days when the amount of electricity is stored.
In this way, the number of days in which the actual value of power generation amount is lower than the actual value of power consumption in the current aggregation period, that is, the number of days where "actual value of power consumption" / "actual value of power generation amount" is 1 or more. If the number of days exceeds the standard number of days, it is judged that there is a high possibility that a negative economic effect will occur due to the error between the predicted value and the actual value, and the suppression of the amount of stored electricity can be suspended from the next aggregation period.
An example of the aggregation period is "one month." In that case, if the number of days in which the "actual value of power consumption"/"actual value of power generation amount" for this month is 1 or more exceeds the reference number of days, the control unit does not suppress the amount of stored electricity from the next month.

(iv) The control unit determines whether or not the number of days on which the actual value of power generation amount is lower than the actual value of power consumption exceeds the reference number of days for the most recent predetermined number of days within the current aggregation period. Good too.
In this way, it is possible to determine the magnitude of the possibility that a negative economic effect will occur based on the results for the most recent predetermined number of days within the current aggregation period. That is, the determination can be made based on the most recent situation.

(v) The control unit may update the reference number of days based on the most recent change in whether or not the actual surplus power amount exceeds the amount of stored electricity that was suppressed based on the prediction.
In this way, the reference number of days for judgment can be updated based on the latest situation and corrected to an appropriate value.

(vi) The control unit predicts on a daily basis whether or not predicted surplus power generation will occur, makes judgments regarding the possibility of economic disadvantage for each aggregation period, and compares the predicted value and actual value for the current aggregation period. The average error is calculated, and if the calculated average error exceeds a predetermined threshold, the amount of stored electricity will not be suppressed in the next aggregation period even on days when predicted surplus power generation will occur. Good too.
In this way, if the average error between the predicted value and the actual value exceeds the threshold, it is determined that there is a high possibility that a negative economic effect will occur due to the average error, and the amount of stored electricity will be reduced from the next aggregation period. Suppression can be suspended.

(vii) The control unit predicts on a daily basis whether or not predicted surplus power generation will occur, makes judgments regarding the possibility of economic disadvantage for each aggregation period, and The average error between the predicted value and the actual value is calculated, and if the calculated average error exceeds a predetermined threshold, the amount of stored electricity will be suppressed during the next aggregation period even on days when predicted surplus power generation is expected to occur. You may choose not to do so.
In this way, it is possible to determine the magnitude of the possibility that a negative economic effect will occur based on the average error for the most recent predetermined number of days in the current aggregation period. That is, the determination can be made based on the most recent average error situation.

(viii) The control unit may update the threshold based on the most recent change in error between the predicted value and the actual value.
In this way, the threshold value for determination can be updated based on the most recent situation and corrected to an appropriate value.
According to this aspect, for example, even though it was determined that the possibility of negative economic effects occurring was small and the amount of electricity stored was not suppressed, the number of days on which disadvantages occurred has increased in the recent past. If determined, the control unit reduces the threshold value to make it easier to suppress the amount of stored electricity. On the other hand, if it is determined that the number of days without any disadvantage has increased in the recent past, even though the user has decided that there is a high possibility that the user will experience economic disadvantage and has suppressed the amount of electricity stored. , the control unit increases the threshold value to make it more difficult to suppress the amount of stored electricity.

(ix) The control unit predicts the presence or absence of predicted surplus power generation on a daily basis, makes judgments regarding the possibility of economic disadvantage for each aggregation period, and in the current aggregation period, the actual value of power generation is If the number of days when the actual amount of electricity is below the actual value exceeds the predetermined standard number of days, and if the average error between the predicted value and the actual value in the current aggregation period exceeds the predetermined threshold, the next aggregation period will be The amount of stored electricity may not be suppressed even on days when the predicted surplus power generation amount is expected to occur.
In this way, the number of days in which the actual value of power generation amount is lower than the actual value of power consumption in the current aggregation period, that is, the number of days where "actual value of power consumption" / "actual value of power generation amount" is 1 or more. Based on both the average error between the predicted value and the actual value, it is determined that there is a high possibility that a negative economic effect will occur due to the error between the predicted value and the actual value, and the amount of electricity stored will be reduced from the next aggregation period. Suppression can be suspended.

(x) After determining that the amount of stored electricity will not be suppressed even on days when the predicted surplus power generation amount is expected to occur due to exceeding the standard number of days, the control unit determines that the amount of electricity stored will not be suppressed for a predetermined number of consecutive aggregation periods in which the standard number of days is not exceeded. In this case, the amount of stored electricity may be suppressed for the day when the predicted surplus power generation amount is expected to occur from the next aggregation period.
In this way, it is determined that there is a high possibility that a negative economic effect will occur based on the number of days when the "actual value of power consumption" / "actual value of power generation" is 1 or more, and the storage of electricity is started from the next aggregation period. After stopping the suppression of the amount of stored electricity, it is possible to resume the suppression of the amount of stored electricity based on the transition of the situation over a predetermined number of aggregation periods.

(xi) After determining that the amount of stored electricity will not be suppressed even on days when predicted surplus power generation is expected to occur due to exceeding the threshold, the control unit determines that the amount of stored electricity will not be suppressed for a predetermined number of consecutive aggregation periods in which the threshold is not exceeded. In this case, the amount of stored electricity may be suppressed for the day when the predicted surplus power generation amount is expected to occur from the next aggregation period.
In this way, it is determined that there is a high possibility of a negative economic effect occurring based on the average error between the predicted value and the actual value, and after suspending the suppression of the amount of electricity stored from the next aggregation period, Suppression of the amount of stored electricity can be resumed based on changes in the situation over time.

(xii) The control unit may update the predetermined number based on the most recent change in the determination.
In this way, the length of the aggregation period related to the determination of restart can be updated based on the latest trends and corrected to an appropriate value.

(xiii) The control unit determines the possibility of economic disadvantage for the power control system based on the actual value of the amount of power generation for each of the power control systems and the actual value of the amount of power consumption for each of the power control systems. You may make a judgment.
In this way, it is possible to determine the degree of possibility that a negative economic effect related to the power control system will occur based on the performance of each power control system, rather than the performance of the entire commercial power system.

Preferred embodiments of the invention include combinations of any of the above-mentioned embodiments.
In addition to the embodiments described above, there may be various modifications of this invention. Such variations are not to be construed as falling outside the scope of this invention. This invention should include the meaning equivalent to the scope of the claims and all modifications within the said scope.

93a: Output terminal, 10: Controller, 34: Bidirectional DC/DC converter, 35: Communication section, 36: Memory, 37: Energy meter, 38: Voltmeter, 39: IC, 51: Input section, 52: Controller Communication section, 53: Controller memory, 54: Controller IC
81: Distribution board, 91: Solar cell module, 92: Power consumption equipment, 94: Storage battery, 93: Power conditioner, 95: Hot water storage type water heater, 96: Commercial power system, 98: Web network, 100: Power control System, 101: Power generation/consumption history, , 103: Power storage (boiling) schedule, 110: Power generation amount prediction unit, 120: Power consumption amount prediction unit, 130: Predicted value acquisition unit, 150: Remaining amount acquisition unit, 161: Surplus presence/absence determination unit, 163: Boiling allocation unit, 164: Electricity storage allocation unit, 165: Control possibility determination unit, 170: Storage battery control unit, 180: Water heater control unit 371: Sales energy meter, 372: Purchase energy meter , 541: Energy storage amount monitoring unit, 542: Energy management unit Efc1, Efc2, Efc: Predicted differential electric energy, Erc1, Erc2, Erc: Actual differential electric energy, Pfg: Predicted power generation, Pfc: Predicted power consumption, Prg: Actual Generated power, Prc: Actual power consumption P: Transmission line, R: Power receiving point

Claims (8)

A power generation device that generates electricity using sunlight, a power storage device that stores power from the power generation device and an external commercial power system, and one or more devices that operate with power from the power generation device, the commercial power system, and the power storage device. A device for controlling power storage in the power storage device in a power control system including:
A predicted value acquisition unit that acquires a predicted surplus power generation amount from a predicted power generation amount that is a predicted value of the power generation amount of the power generation device every predetermined time and a predicted power consumption amount that is a predicted value of the power consumption amount of the device every predetermined time. and,
and a control unit that controls power storage in the power storage device,
The control unit suppresses the amount of electricity stored in the power storage device from the commercial power system during the late-night power period in order to reduce the amount of electricity purchased outside the late-night power period, based on the predicted surplus power generation amount. or not, and economic disadvantage occurs due to an error between the predicted value and the actual value based on the past actual value of the power generation amount of the power generation device and the past actual value of the amount of power consumption of the device. A power storage control device that determines the magnitude of the possibility that the power storage will occur, and controls the amount of stored power not to be suppressed if the possibility exceeds a predetermined standard. The control unit predicts the presence or absence of predicted surplus power generation on a daily basis, makes a judgment regarding the possibility of the occurrence of economic disadvantage every predetermined aggregation period, and in the current aggregation period, the actual value of the power generation amount is If the number of days in which the amount of electricity is below the actual value exceeds a predetermined standard number of days, a request is made to control the amount of stored electricity so that it will not be suppressed even on days when predicted surplus electricity generation will occur in the next aggregation period. Item 1. The power storage control device according to item 1 . The power storage control device according to claim 2 , wherein the control unit updates the reference number of days based on the most recent change in whether the actual surplus power amount exceeds the power storage amount suppressed based on prediction. The control unit predicts on a daily basis whether or not predicted surplus power generation will occur, makes a judgment regarding the possibility of the occurrence of economic disadvantage for each aggregation period, and calculates the error between the predicted value and the actual value in the current aggregation period. A claim in which the average is calculated, and if the calculated average error exceeds a predetermined threshold, the amount of stored electricity is not suppressed in the next aggregation period even on days when predicted surplus power generation is expected to occur. 1. The power storage control device according to 1. The power storage control device according to claim 4 , wherein the control unit updates the threshold value based on the most recent change in error between the predicted value and the actual value. The control unit predicts the presence or absence of predicted surplus power generation on a daily basis, makes a judgment regarding the possibility of occurrence of the economic disadvantage for each aggregation period, and in the current aggregation period, the actual value of the power generation amount is equal to the amount of power consumption. If the number of days below the actual value of The power storage control device according to claim 1 , wherein the amount of stored power is not suppressed even on days when the amount of power generation is predicted to occur. After determining that the amount of stored electricity will not be suppressed even on days when predicted surplus power generation is expected to occur due to exceeding the reference number of days , the control unit determines that a predetermined number of consecutive aggregation periods that do not exceed the reference number of days have occurred. 3. The power storage control device according to claim 2 , wherein the amount of stored power is suppressed for a day when the predicted surplus power generation amount is expected to occur from the next aggregation period. The control unit determines that the amount of stored electricity will not be suppressed even on days when the predicted surplus power generation amount is expected to occur due to exceeding the threshold value, and then a predetermined number of consecutive aggregation periods in which the threshold value is not exceeded continues; 5. The power storage control device according to claim 4, wherein the power storage amount is suppressed for a day on which a predicted surplus power generation amount is expected to occur from the next aggregation period.