Power control system

Abstract

Invention details;

Description

Power control system and program

[0001] The present disclosure relates to a power control system and a program.

[0002] Patent Document 1 describes a power control system that includes a plurality of grouped consumers, each including a power meter that measures the power consumption consumed by a load, and a control device that receives the power consumption measured by the power meter from each consumer, outputs group power consumption for each group using the power consumption of each consumer, and, if the group power consumption of any group exceeds the group contract power that is preset for each group, controls the group power consumption of the excess power group to be below the group contract power.

[0003] Japanese Patent Application Laid-Open No. 2019-30087

[0004] When a contract demand is set for a group including multiple consumers, power is supplied to the group that is the subject of the contract. However, because the ratio of power usage by each consumer to the total power usage of the group varies depending on the time of day, it is preferable to control power usage appropriately for each consumer.

[0005] The present disclosure aims to realize control that, when controlling (limiting) the power usage of a group consisting of multiple consumers, appropriately controls the power usage of each consumer, thereby maintaining the convenience of power usage for each consumer and keeping the power usage of the entire group within a predetermined range.

[0006] The power control system disclosed herein is a system that controls power consumption so as not to exceed a target value set for a group consisting of multiple consumers, and includes an acquisition means for acquiring a predicted value of power consumption for each of the multiple consumers, and a setting means for setting a limit value correlated to the available power for a specific time period set for each of the consumers, wherein the setting means sets the limit value so that when the predicted value for each of the multiple consumers for the specific time period is relatively small, the value obtained by dividing the limit value by the predicted value is larger than when the predicted value is relatively large. In this way, it is possible to appropriately allocate available power consumption to each of the consumers that make up the group while controlling the power consumption of the entire group so that it does not exceed the contracted power.

[0007] Here, the setting means may set the limit value to be equal to or greater than a predetermined lower limit value, so that when the predicted value for each of the plurality of consumers in the specific time period is relatively small, a value obtained by dividing the limit value by the predicted value becomes large. In this way, a certain amount of power or more can be secured based on the lower limit value as the power usage allocated to each consumer.

[0008] Furthermore, when the predicted value for each of the plurality of consumers in the specific time period is relatively small, the setting unit may correct the limit value so that it is larger than the predicted value, thereby increasing the value obtained by dividing the limit value by the predicted value. In this way, the correction can prevent the amount of power usage allocated to each consumer from becoming too small.

[0009] Furthermore, the setting unit may set the limit value for each of the plurality of consumers so that a value obtained by accumulating the limit values ​​for each of the plurality of consumers in the specific time period is equal to or less than the target value for the group of the plurality of consumers. In this way, even if the power usage allocated to each consumer is controlled so as not to be too small, it is possible to prevent the power usage of the entire group from exceeding the target value.

[0010] The setting unit may set the limit value for each consumer based on information on a predicted value of power usage for each consumer during the specific time period. In this way, the limit value can be set based on the predicted value of power usage for each consumer constituting a group.

[0011] The setting unit may set the limit value for each consumer based on information on the actual power usage of each consumer in a specific period in the past. In this way, the limit value can be set based on the actual power usage of each consumer in the past.

[0012] The setting unit may set the limit value for each consumer based on information on the maximum power usage for each time period during a specific period for each consumer. In this way, the limit value can be set based on the contract power set for a group.

[0013] Furthermore, when a predicted value of power usage of at least one of the consumers in the specific time period falls below a predetermined lower threshold, the setting unit may set the lower limit value as the limit value for the consumer. In this way, it is possible to ensure that a consumer to which a small allocation is set when a limit value is set using a specific method for a certain time period has room to use power in that time period.

[0014] Furthermore, when an integrated value of the predicted values ​​of power consumption of the plurality of consumers in the specific time period is lower than the target value of the group consisting of the plurality of consumers by a certain amount or more, the setting means may set the limit value of power consumption of one or more consumers included in the group in the specific time period to a value higher than the predicted value of power consumption of each consumer, as long as the power consumption of the group does not exceed the target value. In this way, even when a limit value is set, consumers can use more power than the predicted power consumption depending on the conditions.

[0015] The program disclosed herein also causes a computer that controls a system for controlling power consumption so that a target value set for a group of multiple consumers is not exceeded to function as an acquisition means for acquiring a predicted value of power consumption for each of the multiple consumers and a setting means for setting a limit value correlated to available power for a specific time period set for each of the consumers, and the setting means causes the computer to set the limit value so that when the predicted value for each of the multiple consumers for the specific time period is relatively small, the value obtained by dividing the limit value by the predicted value is larger than when the predicted value is relatively large. A computer having this program installed can appropriately allocate available power consumption to each of the consumers that make up the group while controlling the power consumption of the entire group so that it does not exceed the contracted power.

[0016] 7(B) is a diagram showing an example of the overall configuration of a facility equipment control system to which the present embodiment is applied; FIG. 7(C) is a diagram showing an example of the configuration of a facility equipment; FIG. 7(A) is a diagram showing an example of the actual power usage in the past, FIG. 7(B) is a diagram showing the predicted results of the power usage for one day, and FIG. 7(C) is a diagram showing an example of the predicted value for each time period in the prediction results; FIG. 7(A) is a diagram showing an example of the predicted power usage for each consumer constituting the group, FIG. 7(B) is a diagram showing the predicted results for the entire group, and FIG. 7(C) is a diagram showing an example of the predicted value for each time period in the prediction results for the group; FIG. 7(A) is a diagram showing an example of the predicted average power usage for each time period of the group, FIG. 7(B) is a diagram showing the distribution of the limit values ​​for each consumer constituting the group, and FIG. 7(C) is a diagram showing an example of the limit value for each time period allocated to one consumer in the group. 9(A) and 9(B) are diagrams showing examples of methods for setting limit values ​​for predicted values, where FIG. 9(A) is a diagram showing a method for setting limit values ​​according to a first aspect, FIG. 9(B) is a diagram showing a method for setting limit values ​​according to a second aspect, FIG. 9(C) is a diagram showing a method for setting limit values ​​according to a third aspect, FIG. 9(D) is a diagram showing a method for setting limit values ​​according to a fourth aspect, and FIG. 9(E) is a diagram showing a method for setting limit values ​​according to a fifth aspect.

[0034] FIG. 9 is a diagram showing an example of a case where a predicted value is relatively smaller than past actual values.

[0035] FIG. 9 is a diagram showing an example of a case where a predicted value is relatively smaller than predicted values ​​of other consumers in the group.

[0017] Hereinafter, an embodiment will be described in detail with reference to the accompanying drawings. <System Configuration> Fig. 1 is a diagram showing the overall configuration of a facility equipment control system to which this embodiment is applied. The control system of this embodiment includes a control device 100, facility equipment 200 that is a controlled device, and a server 300. The control device 100 and facility equipment 200 are connected via a network. This network may be a LAN (Local Area Network) using a dedicated line, or may be a WAN (Wide Area Network) or a VPN (Virtual Private Network) set up on the Internet.

[0018] The facility devices 200 are facilities or devices that operate using electric power. The control device 100 controls the operation of one or more facility devices 200. FIG. 1 shows an example configuration in which the control device 100 controls multiple facility devices 200. The facility devices 200 may be of any type as long as they operate using electric power and the operation of which is controlled by the control device 100. In the following description, an example in which the control system of this embodiment is applied to the control of air conditioning equipment may be described as a specific example of the facility devices 200.

[0019] The facility devices 200 also include control means for controlling the facility devices themselves in accordance with instructions from the control device 100. The control device 100 generates instructions (hereinafter referred to as "control instructions") for controlling the facility devices 200 to be controlled, and transmits the generated control instructions to each facility device 200. Each facility device 200 acquires the control instructions from the control device 100, and uses its control means to configure itself and control its operation in accordance with the acquired control instructions.

[0020] The control device 100 and the server 300 are connected via a network. In the configuration example shown in Fig. 1, one control device 100 is connected to the server 300, but in reality, multiple control devices 100 are connected to the server 300. One or multiple facility devices 200 are connected to each control device 100. The network connecting the control device 100 and the server 300 may be, for example, the Internet. Alternatively, a LAN or WAN may be used.

[0021] <Relationship Between Electricity Charges and Control of Facility Equipment 200> Here, the electricity charges will be explained. The electricity charges are mainly composed of a basic charge and an energy charge, and are specified for each month. The basic charge is calculated based on the basic charge unit price and the contracted power. The contracted power is the maximum value of the maximum demand power within one year prior to the current month. The maximum demand power is the maximum value of the average power usage for each time period (demand time period: 30 minutes) in a month. The average power usage is the average value of the demand power (power usage) for each time period. The energy charge is calculated based on the energy charge unit price and the amount of power usage for each month.

[0022] As mentioned above, the contract power is the maximum value of the maximum power demand within the past year. Therefore, if the maximum power demand for a certain month (in other words, the average power usage for a certain period in that month) becomes the contract power, the basic charge based on this contract power will be charged for the entire year, even if the maximum power demand continues to be lower than the contract power from that month onwards. Furthermore, if the average power usage for a certain period exceeds the contract power value up to that point and becomes the maximum power demand for the month that includes that period, the average power usage (maximum power demand) for that period will be used as the new contract power in calculating the basic charge thereafter.

[0023] There are various ways to set the energy rate unit price, and the energy rate unit price may be set to fluctuate based on predetermined conditions. For example, the energy rate unit price may be set to fluctuate depending on the time of day, whether it is a weekday or a holiday, the season, etc. Furthermore, as electricity becomes traded on the market, energy rate unit prices may be set to fluctuate to reflect the trading price of electricity on the market.

[0024] In controlling the facility equipment 200, control may be performed with the aim of reducing the electricity charges required to operate the facility equipment 200. In this case, it is required to control the facility equipment 200 so that the average power usage does not exceed the current contracted power. Furthermore, when the unit price of energy charges fluctuates, it is more efficient from the perspective of lowering the electricity charges to reduce the amount of power used during time periods when the unit price is high rather than during time periods when the unit price is low. However, while the unit price of energy charges only affects the energy charges for each time period, the contracted power affects the electricity charges for the entire year from the current month onwards. For this reason, control that takes into account the average power usage takes priority over control that takes into account fluctuations in the unit price of energy charges.

[0025] Electricity charges are levied on the power supply contractor. In this embodiment, the power supply contractor is assumed to be a group consisting of multiple consumers. Therefore, the average power usage is obtained as the integrated value of the average power usage per time period by each of the multiple consumers constituting this group. Furthermore, the basic fee is determined based on the maximum power demand per group (the maximum value of the average power usage per time period in a month).

[0026] Here, the maximum power demand of a group is usually smaller than the sum of the maximum power demands of each consumer in the group. This is because the time limit for the maximum power demand is generally different for each consumer in the group. Therefore, the basic charge set for the group is lower than the sum of the basic charges set based on the maximum power demand of each consumer in the group.

[0027] One or more control devices 100 are assigned to one group. The one or more control devices 100 control the facility devices 200 of each consumer that constitutes the group in accordance with the electricity rates (basic rate and energy rate) set for each group, taking into account the average power usage per predetermined unit time and the energy rate unit price.

[0028] Furthermore, each consumer has one or more pieces of equipment 200, and the control device 100 controls the equipment 200 of one or more consumers. However, one consumer does not necessarily correspond to one control device 100. Multiple pieces of equipment 200 owned by one consumer may be controlled by multiple control devices 100, or the equipment 200 owned by multiple consumers may be controlled by one control device 100. Furthermore, one control device 100 may be assigned to multiple groups. However, for simplicity, the following description will be given assuming a configuration in which one control device 100 is assigned to one consumer, and the equipment 200 of each consumer is controlled by the control device 100 corresponding to that consumer.

[0029] 2 is a diagram showing the configuration of the server 300. The server 300 is realized, for example, as a server built on a cloud environment of a network (a so-called cloud server). The server 300 includes a group management unit 310, a first prediction unit 320, a limit value setting unit 330, a control information generation unit 340, a second prediction unit 350, a performance information acquisition unit 360, a limit value adjustment unit 370, and a transmission control unit 380.

[0030] The group management unit 310 manages the above-mentioned group of consumers. As described above, this group is set as a unit of an electricity contract. The group management unit 310 acquires and stores information on the group's contracted power, maximum demand power, and average power usage per time period. The group management unit 310 also manages the consumers that make up the group. The group management unit 310 acquires and stores information on the contracted power, maximum demand power, and average power usage per time period of each consumer that makes up the group. The information on the average power usage of each consumer is obtained, for example, from the control device 100 that controls the equipment 200 of each consumer. The information on the average power usage of the group is obtained, for example, from the control device 100 that controls the equipment 200 of the consumers that make up the group (hereinafter referred to as the "equipment 200 of the group"). Specifically, for example, the average power usage of each consumer that makes up the group per time period is added up to determine the average power usage of the group.

[0031] The first prediction unit 320 predicts the average power usage per time period by the equipment 200 of each consumer constituting the group. The first prediction unit 320 is an example of a prediction means. The first prediction unit 320 is also an example of an acquisition means for obtaining a prediction result of the average power usage of each consumer constituting the group. The prediction of the average power usage per time period by the first prediction unit 320 is performed, for example, based on history information regarding the past operation of the equipment 200 of each consumer constituting the group. Here, the history information regarding operation broadly includes various information related to the operation of the equipment 200, such as information on the operating status of the equipment 200 as well as information on the operating environment of the equipment 200. Examples of information on the operating status of the equipment 200 include information such as the operating rate, continuous operating time, and number of operations. Examples of information on the operating environment include information such as weather, temperature, humidity, and other meteorological conditions, as well as information on the date and time of day. Here, the server 300 including the first prediction unit 320 is configured to predict the average power usage by the facility equipment 200 of each consumer for each time period for each consumer constituting a group, but the server 300 may be configured to acquire the prediction results from an external server. In this case, the server 300 may be configured to include, instead of the first prediction unit 320, an acquisition means for acquiring the prediction results from the external server via a network.

[0032] The prediction of the average power consumption for a specific time period on a specific date and time (hereinafter referred to as the "specific time period") may be performed, for example, by setting a reference time period for the specific time period based on historical information related to operation, and then predicting the average power consumption of the facility equipment 200 for this reference time period. The reference time period may be, for example, a past time period with weather conditions similar to those predicted for the date and time corresponding to the specific time period, or a corresponding time period on the same day and month one year ago. Furthermore, the prediction of the average power consumption of the facility equipment 200 for the specific time period may take into consideration the average power consumption of the facility equipment 200 for time periods before and after the reference time period, or the trends in the average power consumption of the facility equipment 200 for time periods over several days leading up to the day that includes the reference time period.

[0033] Based on the prediction results by the first prediction unit 320, the limit value setting unit 330 sets a limit value for the average power usage per time period by the facility equipment 200 of each consumer constituting the group. The limit value setting unit 330 is an example of a setting means. If the average power usage of a group exceeds the contract power of the group, this average power usage becomes the new contract power, which raises the basic charge in the electricity bill. Therefore, it is necessary to set a target power based on the contract power for the group and control the average power usage per time period for all of the facility equipment 200 in the group so that it does not exceed the target power. Then, a limit value for each time period of each consumer is set so that the integrated value of each consumer's limit value is equal to or less than a threshold based on the target power. In other words, the limit value is set in correlation with the available power per time period set for each consumer. The target power is set to a value equal to or less than the contract power, for example, a value lower than the contract power by a certain value. The threshold is set to a value equal to or less than the target power, for example, a value lower than the target power by a certain value.

[0034] In the above explanation, a target value (target power) was set for the average power usage (kW) for each time period in the group, and a limit value for each consumer that makes up the group was set based on this target value. Alternatively, a target value (target power amount) may be set for the amount of power usage (kWh) for each time period in the group, and a limit value for each consumer that makes up the group may be set based on this target value. The difference between these methods is simply whether the power usage (kW) or the amount of power usage (kWh) is used as the basis for setting the target value and limit value. Below, an example will be described in which the target value (target power) and limit value are set based on the average power usage as described above.

[0035] Here, the limit value for each consumer constituting the group is set, for example, based on a prediction of the average power usage for each consumer by the first prediction unit 320. From the prediction by the first prediction unit 320, the proportion of the average power usage predicted by each consumer in the group is identified for each time period. Therefore, for example, if the integrated value of the limit values ​​for each consumer is set to be equal to a threshold based on the target power described above, the average power usage corresponding to this threshold is allocated so as to be the proportion of the average power usage by each consumer predicted by the first prediction unit 320, and this is set as the limit value for each consumer. In other words, the limit value means the power usage available to each consumer for that time period.

[0036] Furthermore, the limit value may be set based on the actual average power consumption value of each consumer for each time period in the past, rather than the predicted average power consumption rate for each time period for each consumer. For example, the ratio of the actual average power consumption value of each consumer for the reference time period described in the description of the prediction by the first prediction unit 320 to the actual average power consumption value of each consumer for the reference time period described in the description may be determined. Then, the limit value for each consumer for the specific time period may be set based on this ratio of the actual values. The specific period may be determined depending on the amount of information obtained as the actual values ​​for the reference time period, and may be set, for example, to the past year or several years, or from a specific date to a specific date.

[0037] The limit value may also be set based on the maximum value of the average power usage for each consumer for each time period during a specific period. For example, if the specific period is the past year, the maximum value of the average power usage for each time period during the past year can be obtained for each consumer. Then, the maximum values ​​for each consumer may be compared, and the limit value for each consumer may be set based on the ratio. In this case, unlike when the actual value for the reference time period is used, the time period during which the average power usage reaches the maximum value may be different for each consumer.

[0038] Here, the limit value will be further explained. As described above, the limit value is set in correlation with the available power for each time period set for each consumer. More specifically, the limit value is set so that the sum of the average power usage of each consumer in the group does not exceed the target power, and the limit value for each consumer is set, for example, based on the average power usage of each consumer predicted by the first prediction unit 320. On the other hand, if the limit value set for a consumer is extremely small, that consumer may be effectively unable to use power. For example, if the baseline power of lighting and other components other than the air conditioner among the equipment 200 of a consumer is close to 20 kW, setting the limit value to 20 kW would completely disable the air conditioner. This situation is likely to occur when the predicted power usage of the equipment 200 of a consumer is smaller than the predicted power usage of other consumers or smaller than the past actual power usage of the equipment 200 of the consumer (hereinafter, these situations will be collectively referred to as "the predicted power usage value being relatively small").

[0039] For simplicity, consider the case where the limit value is set to the same value as the predicted value. In this case, the value obtained by dividing the limit value by the predicted value is 1 (limit value ÷ predicted value = 1). A consumer for which a limit value is set for a certain time period can only use up to the maximum amount of power corresponding to the predicted value. Therefore, as described above, the smaller the predicted value, the higher the possibility of interference with the operation of the facility equipment 200 of that consumer. Specifically, if the predicted value for a certain consumer is smaller than the predicted values ​​for other consumers in the group, the available power allocated to that consumer is small, and therefore the restriction based on the limit value may prevent the facility equipment 200 of that consumer from being fully operated. Furthermore, if the predicted value for a certain time period for a certain consumer is smaller than the actual power usage value of that consumer in the past, the power required by that consumer is likely to exceed the predicted value, and therefore the restriction based on the limit value may prevent the facility equipment 200 of that consumer from being fully operated.

[0040] Therefore, it is conceivable to set the limit value so that when the predicted value of average power usage of a certain consumer in a certain time period is relatively small, the value obtained by dividing the limit value by the predicted value is larger than when the predicted value is relatively large. There are various conceivable methods for setting the limit value. Some of these methods will be described below.

[0041] FIG. 9 is a diagram showing an example of a method for setting a limit value for a predicted value. FIG. 9(A) shows a method for setting a limit value according to a first aspect, FIG. 9(B) shows a method for setting a limit value according to a second aspect, FIG. 9(C) shows a method for setting a limit value according to a third aspect, FIG. 9(D) shows a method for setting a limit value according to a fourth aspect, and FIG. 9(E) shows a method for setting a limit value according to a fifth aspect. In each graph shown in FIGS. 9(A) to 9(E), the horizontal axis represents the relative magnitude of the predicted value (in the figure, this is labeled "magnitude of predicted value"), and the vertical axis represents the limit value. Furthermore, line a indicates that the predicted value and the limit value are the same value (limit value ÷ predicted value = 1), and in the area above line a, the limit value is greater than the predicted value (limit value ÷ predicted value > 1).

[0042] 9A, the smaller the relative magnitude of the predicted value, the larger the value obtained by dividing the limit value by the predicted value at a constant rate (linearly). Note that in the example shown in FIG. 9A, when the predicted value is the maximum value it can take, the predicted value and the limit value are the same value (limit value ÷ predicted value = 1), but the limit value may be any value as long as it is equal to or greater than the predicted value, and is not limited to the example shown.

[0043] In the example shown in Fig. 9(B), as the relative magnitude of the predicted value decreases, the value obtained by dividing the limit value by the predicted value increases, and the rate at which the value obtained by dividing the limit value by the predicted value increases increases. Note that, as in the example of Fig. 9(A), it is sufficient that the limit value is equal to or greater than the predicted value when the predicted value is at its maximum possible value, and the example shown is not limiting.

[0044] In the example shown in FIG. 9(C), when the relative magnitude of the predicted value is greater than the reference t, the limit value is set to the same value as the predicted value. When the relative magnitude of the predicted value is smaller than the reference t, the smaller the relative magnitude of the predicted value, the larger the value obtained by dividing the limit value by the predicted value at a constant rate (linearly). As described above, the smaller the relative magnitude of the predicted value of the power usage of a certain consumer, the higher the possibility that the operation of the equipment 200 of that consumer will be affected. Therefore, a reference t is set for the relative magnitude of the predicted value, and the limit value is manipulated within a range smaller than the reference t. Note that the method for setting the reference t is not particularly limited. For example, the reference t may be set appropriately depending on the configuration of consumers in the group and the configuration of the equipment 200 of each consumer.

[0045] In the example shown in Fig. 9(D), when the relative magnitude of the predicted value is greater than the reference t, the limit value is set to the same value as the predicted value. When the relative magnitude of the predicted value is smaller than the reference t, the smaller the relative magnitude of the predicted value, the larger the value obtained by dividing the limit value by the predicted value, and the rate at which the value obtained by dividing the limit value by the predicted value increases. As with the example shown in Fig. 9(C), the method for setting the reference t is not particularly limited.

[0046] In the example shown in FIG. 9(E), when the relative magnitude of the predicted value is greater than the reference t, the limit value is set to the same value as the predicted value. When the relative magnitude of the predicted value is smaller than the reference t, the limit value is constant (fixed). This is equivalent to setting a lower limit for the limit value. Note that in the illustrated example, the fixed limit value when the relative magnitude of the predicted value is smaller than the reference t is set as the limit value when the magnitude of the predicted value is the reference t, but this value is not necessarily limited to this, and the limit value may be set to a value greater or smaller than the limit value when the magnitude of the predicted value is the reference t. The method for setting the lower limit will be described later.

[0047] Although five exemplary limit value setting methods have been described above, possible limit value setting methods are not limited to the above examples. Furthermore, limit values ​​may be set by combining several of the above examples. Regardless of the method used to set limit values, it is assumed that limit values ​​for each consumer's time period are set so that the integrated value of each consumer's limit value does not exceed a threshold value based on the target power. Therefore, depending on the configuration of the consumers and facility equipment 200 constituting a group, the limit value for the average power usage of a certain consumer in a certain time period may not be the same as the predicted value of the average power usage of that consumer in that time period (it may be lower than the predicted value). Even in such cases, it is desirable to set limit values ​​such that the value obtained by dividing the limit value by the predicted value increases as the relative magnitude of the predicted value decreases, thereby avoiding a situation in which the facility equipment 200 of each consumer cannot operate normally.

[0048] The setting of the lower limit value in the limit value setting method will be further explained. A value greater than 0 is selected as the lower limit value. As a result, even if the first prediction unit 320 predicts that the average power usage for a certain consumer over a certain time period is 0, a limit value equivalent to the lower limit value is set.

[0049] The method for setting the lower limit value may be determined as appropriate depending on the operation and specifications of the control system, agreements between groups and individual consumers, etc. For example, a fixed value may be set in advance, or a value that varies based on a predicted value of average power usage for each time period for the entire group. When a fixed value is set as the lower limit value, the same value may be set for each consumer, or a different value may be set for each consumer depending on appropriate conditions or consumer requests. The predicted value of average power usage for each time period for the entire group is obtained by accumulating the predicted values ​​of average power usage for each time period for each consumer that makes up the group, calculated by the first prediction unit 320.

[0050] When setting a lower limit for a limit value, a lower threshold may be set for the limit value, and if the limit value assigned to a certain consumer falls below the lower threshold, the lower limit may be applied as the limit value. A value different from the lower limit may be set as the lower threshold. For example, if a value below the lower threshold is set as the lower threshold, if the limit value assigned to a certain consumer falls below the lower threshold during a certain time period, a lower limit value greater than the lower threshold is set as the limit value for that consumer during that time period.

[0051] When the above-described lower limit value is set as the limit value, some consumers among the group of consumers are assigned a limit value different (larger) than the value based on the ratio specified by the above-described limit value setting method. Therefore, if the limit value for each consumer is set by simply adding the value assigned as the lower limit value to the value calculated using the ratio using the above-described setting method, the cumulative value of each consumer's limit value may exceed the threshold based on the above-described target power. Therefore, if there is a consumer to which a lower limit value is applied as a limit value, the cumulative value of each consumer's limit value, taking the lower limit value into account, must be corrected so that it does not exceed the threshold. For example, it is possible to set the limit value for each consumer so that the sum of the value calculated using the ratio using the above-described setting method and the applied lower limit value is equal to or less than the threshold. It is also possible to subtract the total value of the applied lower limit values ​​from the limit values ​​of consumers to which the lower limit value does not apply.

[0052] Here, the description has been given assuming that a limit value is set for the average power usage by the facility equipment 200 for each consumer for each time period. However, a limit value may be set only for the average power usage for a time period that satisfies a specific condition. For example, by accumulating the predicted values ​​of average power usage for a certain time period for each consumer constituting a group by the first prediction unit 320, a predicted value of average power usage for the entire group for that time period can be obtained. A limit value may be set only for the average power usage for that time period, provided that the predicted value of average power usage for this group exceeds the above-mentioned threshold.

[0053] On the other hand, consider a case where the predicted value of the group's average power consumption falls below the threshold. The threshold is set based on the target power, which in turn is set based on the contracted power. Therefore, if many of the consumers constituting the group do not use a large amount of power during a certain time period (for example, during the period from late at night to dawn), the predicted value of the group's average power consumption for that time period may fall significantly below the threshold. Therefore, for example, if the integrated value of the predicted values ​​of the power consumption of multiple consumers during a specific time period is lower than the target value for the group consisting of multiple consumers by a certain amount or more, the limit value for each consumer in the group may be set to a value higher than the predicted value of the average power consumption of each consumer, as long as the integrated value of the limit value for each consumer does not exceed the threshold.

[0054] The control information generating unit 340 generates control information for controlling the facility equipment 200 of each consumer that constitutes a group. The control information is information that causes the control device 100 to control the facility equipment 200 so that the average power usage by the facility equipment 200 of the consumer for each time period does not exceed the limit value for that time period for that consumer that is set by the limit value setting unit 330. Therefore, the control information includes information on the limit value for each consumer that is set by the limit value setting unit 330. The control information generating unit 340 generates control information for the corresponding time period before the start of the time period for which control is performed by each control information.

[0055] Furthermore, when the limit value of each consumer set by the limit value setting unit 330 is adjusted by the limit value adjustment unit 370, the control information generation unit 340 generates control information for reflecting the result of the limit value adjustment in the control of the facility equipment 200. Hereinafter, when distinguishing between the above-mentioned control information based on the limit value set by the limit value setting unit 330 and the control information based on the limit value adjusted by the limit value adjustment unit 370, the former will be referred to as "general control information" and the latter will be referred to as "individual control information." As will be described in detail later, the limit value adjustment by the limit value adjustment unit 370 is performed within the time limit during which control is being performed to reflect the limit value adjustment. Therefore, unlike general control information, individual control information is generated within the time limit after the start of the time limit during which control based on the individual control information is being performed.

[0056] The second prediction unit 350 predicts the average power consumption of the facility equipment 200 during the current time period (hereinafter referred to as the "current time period") during which the control of the facility equipment 200 is being carried out. The prediction of the average power consumption by the second prediction unit 350 is performed, for example, based on information about the operation status of the facility equipment 200 of each consumer during the current time period. The information about the operation status includes, for example, information about the trend in power consumption of the facility equipment 200 from the start of the current time period to the prediction point within that time period, the amount of power consumption, the operating state, and operation settings. The operation settings are specifically selected depending on the type of facility equipment 200. For example, if the facility equipment 200 is an air conditioning device, information such as the difference between the set temperature and the actual room temperature may be used.

[0057] The performance information acquiring unit 360 acquires performance information regarding the operating status of the facility equipment 200 of each consumer constituting the group. The acquired performance information may include performance information for the current time period (performance information from the start of the current time period to the time the performance information is acquired), as well as performance information for a time period that has already ended. The performance information may be acquired from the control device 100 that controls the facility equipment 200, or may be acquired from the facility equipment 200 itself. The performance information for the current time period acquired by the performance information acquiring unit 360 is used by the second predicting unit 350 to predict the average power usage of the facility equipment 200.

[0058] The limit value adjustment unit 370 adjusts the limit value of each consumer constituting the group set by the limit value setting unit 330 based on predetermined conditions. As one example, the limit value adjustment unit 370 adjusts the limit value of each consumer based on a prediction by the second prediction unit 350. As another example, the limit value adjustment unit 370 adjusts the limit value of each consumer based on performance information regarding the operating status of the facility equipment 200 at the current time period acquired by the performance information acquisition unit 360. The limit value adjustment is performed so that the consumers constituting the group can share the power usage available to each consumer. For example, the limit values ​​of some of the consumers constituting the group are lowered, and the limit values ​​of the other consumers are raised by an amount corresponding to the reduction in the limit values ​​of some of the consumers.

[0059] The transmission control unit 380 transmits the control information generated by the control information generation unit 340 to the control device 100 that controls the customer's facility equipment 200 corresponding to each piece of control information. The transmission control unit 380 transmits general control information for the corresponding time period to the control device 100 before the start of the time period during which control is performed by each piece of control information. When transmitting general control information for each time period to the control device 100, the transmission control unit 380 may transmit general control information that reduces the power usage from the time period immediately before the time period to be transmitted before transmitting general control information that increases the power usage from the time period immediately before the time period to be transmitted.

[0060] Furthermore, when the individual control information is generated, the transmission control unit 380 immediately transmits it to the control device 100 that controls the facility equipment 200 that is the target of control by the generated individual control information. When transmitting the individual control information to the control device 100, the transmission control unit 380 may transmit the individual control information for the facility equipment 200 whose limit value will be reduced by adjustment before the individual control information for the facility equipment 200 whose limit value will be increased by adjustment.

[0061] <Configuration of control device 100> Figure 3 is a diagram showing the configuration of the control device 100. The control device 100 is realized as an information processing device connected to a server 300 and facility equipment 200 via a network. The control device 100 may be a device (e.g., an edge server) provided near the facility equipment 200 to be controlled, or may be a server (cloud server) built in a cloud environment. The control device 100 includes a control information acquisition unit 110, an operation information acquisition unit 120, a storage unit 130, a control instruction generation unit 140, a control instruction output unit 150, and an operation information output unit 160.

[0062] The control information acquisition unit 110 acquires control information of the facility devices 200 from the server 300. The control information acquired by the control information acquisition unit 110 includes, as control information for a certain time limit, general control information acquired before the time limit starts and individual control information acquired while the time limit is in progress. The general control information includes information on a limit value for average power usage set for each consumer. The individual control information includes information on a new limit value that adjusts the limit value included in the general control information for the ongoing time limit.

[0063] The operation information acquiring unit 120 acquires operation information of the facility equipment 200 that is the control target of the control device 100. The operation information acquired by the operation information acquiring unit 120 broadly includes various information related to the operation of the facility equipment 200. For example, the operation information includes information indicating the operating status of the facility equipment 200, such as the operation rate and continuous operation time of the facility equipment 200. The operation information may also include various information that is thought to affect the operation of the facility equipment 200, such as the time period during which the facility equipment 200 is operated and whether the facility equipment 200 operates on weekdays or holidays. Furthermore, the operation information acquiring unit 120 may acquire information on the environment in which the facility equipment 200 is installed, such as temperature and humidity. This information can be acquired using various existing methods depending on the type of information. For example, the information can be acquired from the facility equipment 200 itself, or from various sensor devices, etc. Furthermore, date and time information can be acquired, for example, using a clock function or calendar function provided in the control device 100.

[0064] The storage unit 130 stores various types of information acquired by the control information acquisition unit 110 and the operation information acquisition unit 120. The control information acquired by the control information acquisition unit 110 is used to control the facility equipment 200. Of the control information, general control information for each time period is stored in the storage unit 130 before the start of the time period during which control is performed based on the respective general control information. The operation information of the facility equipment 200 acquired by the operation information acquisition unit 120 is sent to the server 300 at a predetermined timing and used for prediction by the first prediction unit 320 and the second prediction unit 350 of the server 300.

[0065] The control instruction generation unit 140 generates control instructions for controlling the facility equipment 200 based on the control information acquired by the control information acquisition unit 110. The control instruction generation unit 140 generates control instructions to operate the facility equipment 200 so that the average power usage per time period by the facility equipment 200 of each consumer does not exceed the limit value set for the consumer for that time period. If one consumer has multiple facility equipment 200, a control instruction is generated for each time period so that the integrated value of the average power usage of all the facility equipment 200 owned by that consumer does not exceed the limit value for the corresponding time period. In this case, there are no particular limitations on the method by which the consumer allocates power to its multiple facility equipment 200 so as not to exceed the limit value set for the consumer. For example, power may be allocated evenly based on the type, size, etc. of the facility equipment 200. Alternatively, sufficient power may be allocated to a specific facility equipment 200, and the remaining power may be allocated to other facility equipment 200. Furthermore, during a certain time period, some of the facility devices 200 may not be operated, and only some of the facility devices 200 may use power. Furthermore, the control instruction generation unit 140 may generate a control instruction by taking into consideration the operation information of the facility devices 200 acquired by the operation information acquisition unit 120. The control instruction generated by the control instruction generation unit 140 based on general control information out of the control information acquired by the control information acquisition unit 110 is stored in the storage unit 130.

[0066] The control instruction output unit 150 reads out from the storage unit 130 the control instruction generated by the control instruction generation unit 140 based on the general control information among the control information acquired by the control information acquisition unit 110, at the time limit during which control based on the general control information is to be performed, and transmits the control instruction to the facility equipment 200 to be controlled. Furthermore, the control instruction output unit 150 immediately transmits the control instruction generated by the control instruction generation unit 140 based on the individual control information among the control information acquired by the control information acquisition unit 110 to the facility equipment 200 to be controlled.

[0067] The operation information output unit 160 reads out the operation information of the facility equipment 200, which is acquired by the operation information acquisition unit 120 and stored in the storage unit 130, from the storage unit 130 in accordance with predetermined conditions, and transmits the information to the server 300. The reading and transmission of the operation information may be performed in response to a request from the server 300, or may be performed periodically, such as at a fixed time each day.

[0068] <Hardware configuration of control device 100 and server 300> Fig. 4 is a diagram showing an example of the hardware configuration of the control device 100 and the server 300. The control device 100 and the server 300 are realized by, for example, a computer. Even when the control device 100 and the server 300 are realized as servers built in a cloud environment, they are configured as a virtual system using system resources of a physical computer on a network as shown in Fig. 4.

[0069] The computer that realizes the control device 100 includes a central processing unit (CPU) 101, which is a computing means, and a random access memory (RAM) 102, a read-only memory (ROM) 103, and a storage device 104, which are storage means. The RAM 102 is a main memory and is used as a working memory when the CPU 101 performs calculations. The ROM 103 stores programs and data such as pre-prepared setting values, and the CPU 101 can read programs and data directly from the ROM 103 and execute processing. The storage device 104 is a storage means for programs and data. Programs are stored in the storage device 104, and the CPU 101 loads the programs stored in the storage device 104 into the main memory and executes them. The storage device 104 also stores and saves the results of processing by the CPU 101. For example, a magnetic disk device or a solid-state drive (SSD) is used as the storage device 104.

[0070] When the control device 100 is realized by the computer shown in FIG. 4 , the functions of the control information acquisition unit 110, operation information acquisition unit 120, control instruction generation unit 140, control instruction output unit 150, and operation information output unit 160 described with reference to FIG. 3 are realized, for example, by the CPU 101 executing a program. The storage unit 130 is realized, for example, by the RAM 102 or the storage device 104. Furthermore, when the server 300 is realized by the computer shown in FIG. 4 , the functions of the group management unit 310, first prediction unit 320, limit value setting unit 330, control information generation unit 340, second prediction unit 350, performance information acquisition unit 360, limit value adjustment unit 370, and transmission control unit 380 described with reference to FIG. 2 are realized, for example, by the CPU 101 executing a program. Note that the configuration example shown in FIG. 4 is merely one example of a case in which the control device 100 is realized by a computer.

[0071] <Configuration of the facility equipment 200> Fig. 5 is a diagram showing the configuration of the facility equipment 200. The facility equipment 200 includes a receiving unit 210, an operation control unit 220, and an output unit 230. Note that the facility equipment 200 has mechanisms and devices that operate to realize the functions of the facility equipment 200 depending on its type. For example, if the facility equipment 200 is air conditioning equipment, the facility equipment 200 has an indoor unit and an outdoor unit, etc. Furthermore, if the facility equipment 200 is lighting equipment, the facility equipment 200 has lighting fixtures, control switches, etc. The types and aspects of such mechanisms vary depending on the type of facility equipment 200, and are not illustrated here.

[0072] The receiving unit 210 receives the control instruction output from the control device 100 via a network using a network interface (not shown).

[0073] The operation control unit 220 controls the operation of mechanisms and devices provided in the facility equipment 200 based on the control instructions received by the receiving unit 210. Specifically, for example, if the facility equipment 200 is an air conditioning equipment, the receiving unit 210 receives information specifying a set temperature as a control instruction, and the operation control unit 220 controls the operation of the indoor unit and the outdoor unit so that the set temperature is reached. Note that while an example of control related to temperature setting has been given here, control based on the control instructions from the operation control unit 220 can also be applied to various other gas-related controls that can be controlled by air conditioning equipment (e.g., control of humidity or gas components). Furthermore, even for various facility equipment 200 other than air conditioning equipment, the operation control unit 220 executes control appropriate to the type of facility equipment 200 in accordance with the control instructions received from the control device 100.

[0074] The output unit 230 outputs information relating to the operating state of the facility equipment 200 to the control device 100 via a network using a network interface (not shown).

[0075] The reception unit 210, the operation control unit 220, and the output unit 230 are realized, for example, by a computer. The computer realizing the operation control unit 220 may have the configuration described with reference to FIG. 4. In this case, the functions of the reception unit 210, the operation control unit 220, and the output unit 230 are realized, for example, by the CPU 101 shown in FIG. 4 executing a program. The functions of the reception unit 210, the operation control unit 220, and the output unit 230 may also be realized by dedicated hardware. For example, they may be realized by an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or other circuit. Furthermore, the reception unit 210, the operation control unit 220, and the output unit 230 may be realized by combining functions realized by the CPU 101 executing a program (software) with functions realized by dedicated hardware.

[0076] <Example of setting limit value> In this embodiment, a group consisting of multiple consumers is the subject of a contract, and the contract power is set based on the average power usage per time period for each group. This average power usage per time period for each group will be further described with reference to the drawings.

[0077] FIG. 6 is a diagram showing an example of a forecast of power usage for a single consumer. FIG. 6(A) shows an example of actual past power usage, FIG. 6(B) shows a forecast result of power usage for one day, and FIG. 6(C) shows an example of a forecast value for each time period in the forecast result. In the graphs of FIGS. 6(A) and 6(B), the horizontal axis represents the time period (48 time periods) of one day (24 hours), and the vertical axis represents the average power usage (kW) for each time period. The graphs of FIGS. 6(A) and 6(B) and the table of FIG. 6(C) show the actual and forecast results of the average power usage of the equipment 200 for each time period of one day. Furthermore, FIGS. 6(A) to 6(C) show, for the equipment 200 of a single consumer, the actual and forecast results of all the equipment 200 owned by the consumer, and the actual and forecast results of the air conditioners among the equipment 200.

[0078] FIG. 6(A) shows actual average power usage for each time period for the three days (three days, two days, and one day) prior to the day for which power usage is to be predicted. In each figure, light-colored graphs indicate the performance of the entire facility equipment 200, and dark-colored graphs indicate the performance of the air conditioning equipment. FIG. 6(B) shows an example of a prediction result of average power usage for each time period, predicted based on the performance data shown in FIG. 6(A). In the graph of FIG. 6(B), as in each of the figures in FIG. 6(A), light-colored graphs indicate the prediction results for the entire facility equipment 200, and dark-colored graphs indicate the prediction results for the air conditioning equipment. FIG. 6(C) shows a correspondence between predicted values ​​of average power usage for the entire facility equipment 200 (referred to as "building" in the figure, representing the facility in which each facility equipment 200 is installed) for each time period (first time period to forty-eighth time period) of a day and predicted values ​​of average power usage for the air conditioners among the facility equipment 200.

[0079] FIG. 7 shows an example of the integrated power consumption forecast for a group consisting of multiple consumers. FIG. 7(A) shows an example of a forecast for each consumer constituting the group, FIG. 7(B) shows the forecast results for the entire group, and FIG. 7(C) shows an example of a forecast value for each time period in the group forecast results. In the graphs of FIGS. 7(A) and (B), the horizontal axis represents the time period (48 time periods) of one day (24 hours), and the vertical axis represents the average power consumption (kW) for each time period. The graphs of FIGS. 7(A) and (B) and the table of FIG. 7(C) show the forecast results for the average power consumption of consumers and groups for each time period of one day. Here, the forecast results for the average power consumption of all the facility equipment 200 of each consumer are referred to as the forecast results for the average power consumption of the consumer or the forecast results for the consumer.

[0080] FIG. 7(A) shows the predicted results of average power usage for each time period for each consumer constituting a group. Note that FIG. 7(A) only shows the predicted results for three consumers (consumers (1) to (3)) among the multiple consumers constituting the group, and the others are omitted. In each diagram in FIG. 7(A), the light-colored graphs represent the predicted results for the entire facility equipment 200, and the dark-colored graphs represent the predicted results for the air conditioning equipment. FIG. 7(B) shows the predicted results of average power usage for each time period for the entire group including the three consumers shown in FIG. 7(A). In FIG. 7(B), the divisions (color-coded) of the graphs for each time period represent the cumulative predicted values ​​of average power usage for each consumer constituting the group for each time period. FIG. 7(C) shows the cumulative predicted values ​​of average power usage for each consumer for each time period (1st time period to 48th time period) of a day.

[0081] Here, assuming that the target power of this group (referred to as "target value" in the figures) is 1000 kW, and referring to Figures 7(B) and 7(C), the predicted value of the average power usage of the entire group exceeds the target power in the 22nd to 31st time periods. Therefore, a limit value for the power usage of each consumer constituting the group is set so that the predicted value of the average power usage of the entire group does not exceed the target power, at least in these time periods. Note that the limit value itself for each consumer may be set not only in the time period in which the predicted value of the entire group exceeds the target power, but also in other time periods in which the predicted value of the entire group does not exceed the target power.

[0082] 8A and 8B are diagrams showing examples of setting limit values ​​for each consumer constituting a group. Fig. 8A is a diagram showing an example of a forecast of average power usage for each time period of the group, Fig. 8B is a diagram showing the allocation of limit values ​​to each consumer constituting the group, and Fig. 8C is a diagram showing an example of a limit value for each time period allocated to one consumer in the group. In the graphs of Figs. 8A and 8B, the horizontal axis represents the time periods (48 time periods) of one day (24 hours), and the vertical axis represents the average power usage (kW) for each time period.

[0083] FIG. 8(A) shows the predicted average power consumption for each time period for each consumer in the group. This graph is identical to the graph shown in FIG. 7(B). FIG. 8(B) shows an example of the allocation of limit values ​​set for each consumer in the group when the average power consumption for each time period of the group is aligned with the target power. In FIG. 8(B), the divisions (colors) of the graph for each time period represent the proportion of the limit value (the power consumption available to that consumer) allocated to each consumer in that time period. In principle, the proportion of the limit value allocated to each consumer in that time period is the proportion of the predicted average power consumption of each consumer in the prediction of the average power consumption of the group shown in FIG. 8(A). Note that, depending on the predicted value of each consumer, a lower limit value may be assigned as the limit value instead of a proportion of the predicted average power consumption value. FIG. 8(C) shows the limit values ​​allocated to one consumer (consumer (1)) in the group for each time period (1st time period to 48th time period) of one day.

[0084] <Correction of Limit Value> In the description of the limit value setting unit 330, the limit value setting unit 330 sets the limit value so that when a predicted value of average power usage for a certain consumer in a certain time period is relatively small, the value obtained by dividing the limit value by the predicted value is larger than when the predicted value is relatively large. This setting method can be understood as correcting the limit value so that when the predicted value is relatively small, the value obtained by dividing the limit value by the predicted value is larger than when the predicted value is relatively large. For example, each aspect of the setting method described with reference to FIG. 9 can be considered as a correction method that corrects the limit value so that when the predicted value is relatively small, the value obtained by dividing the limit value by the predicted value is larger than when the predicted value is relatively small, for a limit value (line a) that is set to the same value as the predicted value.

[0085] Here, the correction of the limit value will be further explained using specific examples. When the predicted value of power usage is relatively small, there are cases where the predicted value for a certain time period of a certain consumer is small compared to the actual value of the consumer's past power usage, and cases where the predicted value for a certain consumer is small compared to the predicted values ​​of other consumers in the group. Specific examples will be given for each case.

[0086] Figure 10 is a diagram showing an example in which the predicted value is relatively smaller than the past actual value. Consider a case in which the past actual power consumption values ​​(e.g., annual actual values) of a certain consumer are distributed in the range of 0 kW to 120 kW, centered around 50 kW, and the predicted value for a certain time period of the consumer is 20 kW, as shown in Figure 10. In this case, the predicted value can be said to be relatively small compared to the distribution of past actual values ​​(e.g., compared to the average value or median value). Therefore, it is conceivable to correct the limit value to a value larger than the predicted value of 20 kW.

[0087] In the example shown in FIG. 10 , for example, the reference point (reference t shown in FIG. 9 ) is set to 30 kW. If the predicted value is greater than 30 kW (in other words, not relatively small), the limit value may not be corrected. However, if the predicted value is 30 kW or less (relatively small), the limit value may be corrected. As an example, if the predicted value is 30 kW or less, the limit value may be corrected according to the magnitude of the predicted value, for example, as follows: Predicted value 25 kW -> Limit value 32 kW (same value as the predicted value, with 7 kW added as a correction); Predicted value 20 kW -> Limit value 30 kW (same value as the predicted value, with 10 kW added as a correction); Predicted value 10 kW -> Limit value 15 kW (same value as the predicted value, with 5 kW added as a correction). In this example, for any of the limit values ​​for the predicted value, the value obtained by dividing the limit value by the predicted value is greater than 1 (limit value / predicted value > 1). The above correction is merely an example of correction to the limit value, and correction may be performed so that the limit value is set based on the various policies described with reference to FIG. 9, for example.

[0088] FIG. 11 illustrates an example in which a predicted value is relatively smaller than the predicted values ​​of other consumers in the group. Here, it is assumed that a group is made up of consumers A to D. In the example illustrated in FIG. 11 , the predicted value of average power usage for consumer A during a certain time period is 20 kW, the predicted value for consumer B is 120 kW, the predicted value for consumer C is 105 kW, and the predicted value for consumer D is 111 kW. The average predicted value for consumers other than consumer A (other consumers) is 112 kW. In this case, it can be said that consumer A's predicted value is relatively small compared to the predicted values ​​of the other consumers. Therefore, it is possible to correct the limit value to a value larger than the predicted value of 20 kW (e.g., 30 kW). Note that the above correction is merely an example of correction to the limit value; for example, the limit value may be corrected based on various policies described with reference to FIG. 9 .

[0089] Although the above describes the embodiments, the technical scope of the present disclosure is not limited to the above embodiments. For example, in the above embodiments, a limit value is set before the start of a time limit during which control based on control information is performed, and the limit value can be adjusted after the start of the time limit. However, a limit value may not be set before the start of the time limit, but may be set within the time limit based on the operating status of the facility equipment 200. Furthermore, in the above embodiments, the server 300 adjusts the limit value after the start of the time limit. However, the control device 100 may adjust the limit value. In this case, if there are multiple control devices 100 that control the facility equipment 200 of all consumers that make up a group, it is possible for the control devices 100 to exchange information on the operating status of the facility equipment 200 and adjust the limit value based on the obtained information. Various other modifications and alternative configurations that do not deviate from the scope of the technical concept of the present disclosure are included in the present disclosure.

[0090] The embodiment described above can be understood as follows. The power control system of the present disclosure is a system that controls power consumption so as not to exceed a target value set for a group consisting of multiple consumers, and includes a first prediction unit 320 that acquires a predicted value of power consumption for each of the multiple consumers, and a limit value setting unit 330 that sets a limit value correlated to the available power for a specific time period set for each consumer, where the limit value setting unit 330 sets the limit value so that when the predicted value for the specific time period for each of the multiple consumers is relatively small, the value obtained by dividing the limit value by the predicted value is larger than when the predicted value is relatively large. In this way, it is possible to appropriately allocate available power consumption to each consumer in the group while controlling the power consumption of the entire group so that it does not exceed the contracted power.

[0091] Here, the limit value setting unit 330 may set the limit value to be equal to or greater than a predetermined lower limit value, so that when the predicted value for each of the multiple consumers in a specific time period is relatively small, the value obtained by dividing the limit value by the predicted value becomes large. In this way, a certain amount of power or more can be allocated to each consumer based on the lower limit value.

[0092] Furthermore, when the predicted value for each of the multiple consumers in a specific time period is relatively small, the limit value setting unit 330 may correct the limit value so that it is larger than the predicted value, thereby increasing the value obtained by dividing the limit value by the predicted value. In this way, the correction can prevent the amount of power usage allocated to each consumer from becoming too small.

[0093] Furthermore, the limit value setting unit 330 may set a limit value for each consumer so that the sum of the limit values ​​for each consumer in a specific time period is equal to or less than the target value for the group of the consumers. In this way, even if the power usage allocated to each consumer is controlled so as not to be too small, it is possible to prevent the power usage of the entire group from exceeding the target value.

[0094] Here, the limit value setting unit 330 may set a limit value for each consumer based on information on a predicted value of power usage for each consumer during a specific time period. In this way, a limit value can be set based on the predicted value of power usage for each consumer constituting a group.

[0095] The limit value setting unit 330 may also set a limit value for each consumer based on information about the actual power usage of each consumer in a specific period in the past. In this way, a limit value can be set based on the actual power usage of each consumer in the past.

[0096] The limit value setting unit 330 may also set a limit value for each consumer based on information on the maximum power usage for each time period during a specific period for each consumer. In this way, a limit value can be set based on the contract power set for the group.

[0097] Furthermore, the limit value setting unit 330 may set a lower limit value as the limit value for a consumer when the predicted value of power usage for at least one consumer in a specific time period falls below a predetermined lower limit threshold. In this way, it is possible to ensure that a consumer who would be allocated a small amount of power if a limit value were set using a specific method for a certain time period has room to use power in that time period.

[0098] Furthermore, when the sum of the predicted power consumption values ​​of multiple consumers in a specific time period is lower than the target value for a group of the multiple consumers by a certain amount, the limit value setting unit 330 may set the limit value for power consumption of one or more consumers in the group in a specific time period to a value higher than the predicted power consumption value of each consumer, as long as the group's power consumption does not exceed a threshold value. In this way, even when a limit value is set, a consumer can use more power than the predicted power consumption depending on the conditions.

[0099] The program disclosed herein also causes a computer that controls a system for controlling power consumption so as not to exceed a target value set for a group of multiple consumers to function as a first prediction unit 320 that acquires a predicted value of power consumption for each of the multiple consumers and a limit value setting unit 330 that sets a limit value correlated to available power for a specific time period set for each consumer, and causes the computer, in the function of the limit value setting unit 330, to set a limit value such that when the predicted value for the specific time period for each of the multiple consumers is relatively small, the value obtained by dividing the limit value by the predicted value is larger than when the predicted value is relatively large. A computer having this program installed can appropriately allocate available power consumption to each consumer in the group while controlling the power consumption of the entire group so that it does not exceed the contracted power.

[0100] DESCRIPTION OF SYMBOLS 100...control device, 110...control information acquisition unit, 120...operation information acquisition unit, 130...storage unit, 140...control instruction generation unit, 150...control instruction output unit, 160...operation information output unit, 200...facility equipment, 210...reception unit, 220...operation control unit, 230...output unit, 300...server, 310...group management unit, 320...first prediction unit, 330...limit value setting unit, 340...control information generation unit, 350...second prediction unit, 360...performance information acquisition unit, 370...limit value adjustment unit, 380...transmission control unit

Claims

1. A power control system for performing power control in a manner that does not exceed a predetermined target value for a group of consumers. The system consists of an acquisition unit that obtains the predicted power usage for each individual consumer and a setup unit that sets a limit that is correlated with the predetermined available power for each consumer for a specific time period. The setup unit sets the limit in such a way that when the predicted value for each individual consumer for that specific time period is relatively small, the acquired value by dividing the limit by the predicted value is greater than when the predicted value is relatively large.

2. A power control system under claim 1 in which the setup unit sets the limit equal to or greater than a predetermined lower limit in such a way that when the predicted value for each individual consumer for that specific time period is relatively small, the acquired value by dividing the limit by the predicted value is greater. 3.A power control system under Claim 1 in which, when the predicted value for each consumer for a specific period is relatively small, the Setup Unit adjusts the limit to a value higher than the predicted value, which is achieved by adding the obtained value by dividing the limit by the predicted value.

4. A power control system under Claim 1 through 3 in which the Setup Unit sets the limit for each consumer in such a way that the value obtained by adding the limit values ​​for each consumer for a specific period is equal to or less than the target value for that group of consumers.

5. A power control system under Claim 1 in which the Setup Unit sets the limit for each consumer based on information on the predicted power usage of each consumer for a specific period.

6. A power control system under Claim 1 in which the Setup Unit sets the limit for each consumer based on information on the actual power usage of each consumer over a specific period in the past. 7.

8. The power control system under Claim 1, whereby the Setup Unit sets limits for each consumer based on information on the maximum power consumption of each consumer on each specific period.

9. The power control system under Claim 2, whereby when the predicted value of power consumption of at least one consumer among consumers for a specific period falls below a predetermined lower threshold limit, the Setup Unit sets the lower limit as the consumer limit.

10. Any one of the power control systems under Claim 1 through 7, whereby when the sum of the predicted values ​​of power consumption of a number of consumers for a specific period is less than the target value for that group, which includes one or more consumers by a certain quantity, the Setup Unit sets for one or more consumers included in that group a power consumption limit for the specific period that is higher than the predicted value of power consumption of each individual consumer during the period in which the group's power consumption does not exceed the target value.The program for enabling a computer-controlled system to perform power control operations in a manner that does not exceed predetermined target values ​​for a group of consumers serves as a power-generating unit that obtains the predicted power usage for each individual consumer and a power-setting unit that sets the limit, which is correlated with the available power allocated to each consumer for a specific time period. In this function, the computer power-setting unit is configured to set the limit in such a way that when the predicted value for each individual consumer for that specific time period is relatively small, the power-generating value obtained by dividing the limit by the predicted value is greater than when the predicted value is relatively large.