Load control device, load control method, and load control program

Abstract

To provide a load controller, a load control method and a load control program which appropriately perform excessive suppression of a demand to a target value.SOLUTION: In a load control system, a load controller 10 comprises: a demand prediction section 101 which predicts integral demand during a predetermined period of consumer loads including a control object instrument; a determination section 102 which determines whether or not the integral demand excesses a target value in a state that control of output of the control object instrument is not performed, based on a prediction value of the integral demand by the demand prediction section; a first control section (a temporary control execution section ) 103 which calculates a first reduction amount for making the integral demand after first control equal to or less than the target value, and performs the first control of output of the control object instrument based on the first reduction amount, assuming that the control object instrument operates at a rating output, in accordance with a result of the determination by the determination section; and a second control section (a permanent control execution section) 105 which calculates a second reduction amount for making the integral demand after second control equal to or less than the target value based on a result of the first control by the first control section and performs second control of output of the control object instrument based on the second reduction amount.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a load control device, a load control method, and a load control program. [Background technology]

[0002] Some consumers of electricity enter into contracts with electric power companies under a fee structure based on the contracted power demand, which is determined by the maximum power demand over the past year. Corporations, in particular, often use contracted power.

[0003] Contract power is determined based on the demand value. Demand value is data measured by a 30-minute maximum demand watt-hour meter installed by the electric power company, and is expressed as the average power consumption (kW) of electricity used over a 30-minute period. The maximum demand value is the largest demand value over the past year. For customers receiving less than 500kW of high-voltage power, the maximum demand value is used to calculate the basic electricity charge, and if a large demand value is detected even once, that large demand value will be applied for the entire year. In addition, for customers receiving 500kW or more of high-voltage power, the contract power is determined through negotiation. If the maximum demand value exceeds the contract power, a penalty fee will be paid, and negotiations to change the contract power will be held based on that maximum demand value. Therefore, in order to reduce electricity charges, it is important not to exceed the maximum demand value.

[0004] The peak demand for a year is concentrated during the daytime in summer. Therefore, it is desirable for each consumer to control the load when demand is high, by setting the maximum demand value as a target value and suppressing the demand from exceeding the target value. Conventionally, load control aimed at suppressing the demand from exceeding the target value has been carried out by measuring the output of each load device with a sensor and issuing a control command based on the measurement results.

[0005] Other demand prediction techniques have been proposed to effectively suppress excess power demand. For example, one technique counts the number of power pulses input every time the amount of power consumed reaches a reference amount of power, calculates a predicted demand value for each period based on the reference amount of power and the number of pulses, and derives the end-point power consumption at the end of each period to correct the predicted demand value. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Laid-Open No. 2016-116381 Summary of the Invention [Problem to be solved by the invention]

[0007] However, the measurement information available for control is often limited to pulse information from master metering, and it is often difficult to obtain information on the actual operating output of each device. Therefore, conventional load control methods assume that the device is operating at its rated output, and issue a control command value obtained by subtracting the target reduction amount from the rated output. However, the actual operating output of the device may be less than the rated output, in which case the demand cannot be reduced sufficiently, and there is a risk that the demand may exceed the target value.

[0008] Furthermore, the technology that corrects the demand based on the end-point power consumption derived from the predicted demand value predicted from the power pulse input each time the power consumption reaches the reference power amount does not take into account fluctuations in demand depending on the season, day of the week, time of day, etc. Since power demand varies greatly depending on the season, day of the week, time of day, etc., there is a risk that the demand may exceed the target value even when this technology is used.

[0009] The present invention has been made in view of the above, and has an object to provide a load control device, a load control method, and a load control program that appropriately suppress excess demand relative to a target value. [Means for solving the problem]

[0010] In the present invention, a demand prediction unit predicts an accumulated demand of a consumer load including a control-target device for a predetermined period. A determination unit determines, based on a value of the accumulated demand predicted by the demand prediction unit, whether the accumulated demand would exceed a target value if the output of the control-target device is not controlled. A first control unit, in accordance with a determination result by the determination unit, calculates a first reduction amount for making the accumulated demand after first control equal to or less than the target value when the control-target device operates at rated output, and performs a first control of the output of the control-target device based on the first reduction amount. A second control unit, based on a result of the first control by the first control unit, calculates a second reduction amount for making the accumulated demand after second control equal to or less than the target value, and performs a second control of the output of the control-target device based on the second reduction amount. [Effects of the Invention]

[0011] According to the present invention, it is possible to appropriately suppress excess demand relative to a target value. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a schematic diagram of a load control system. [Figure 2] FIG. 2 is a block diagram of the load control device according to the first embodiment. [Figure 3] FIG. 3 is a diagram showing an example of numerical values ​​when the provisional control is executed in the case where the load control is not performed before the provisional control. [Figure 4] FIG. 4 is a diagram showing an example of numerical values ​​when the main control is executed in the case where the load control is not executed before the provisional control. [Figure 5] FIG. 5 is a diagram showing an example of numerical values ​​when the temporary control is executed in a case where the load control is performed at 80% of the rated output before the temporary control. [Figure 6] FIG. 6 is a diagram showing an example of numerical values ​​when main control is executed in the case where load control is performed at 80% of the rated output before the temporary control. [Figure 7]FIG. 7 is a flowchart of the load control process performed by the load control device according to the first embodiment. [Figure 8] FIG. 8 is a diagram for explaining the effect of load control by the load control device according to the first embodiment. [Figure 9] FIG. 9 is a block diagram of a load control device according to the second embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of calculation of a correlation function between the total output of all load devices and an actual output reduction value by the load control device according to the second embodiment. [Figure 11] FIG. 11 is a block diagram of a load control device according to the third embodiment. [Figure 12] FIG. 12 is a diagram showing an example of the usage amount before and after the change when the control level is changed from LV0 to LV2. [Figure 13] FIG. 13 is a diagram showing changes in usage amount for each change in control level. [Figure 14] FIG. 14 is a diagram showing a change in the usage amount when the control level is changed from LV0 to LV1. [Figure 15] FIG. 15 is a hardware configuration diagram of the load control device. DETAILED DESCRIPTION OF THE INVENTION

[0013] The following describes in detail embodiments of a load control device, a load control method, and a load control program disclosed in the present invention with reference to the accompanying drawings. Note that the load control device, the load control method, and the load control program disclosed in the present invention are not limited to the following embodiments. [Example]

[0014] Fig. 1 is a schematic diagram of a load control system. The load control system 1 is arranged as part of the power system of each high-voltage consumer. As shown in Fig. 1, the load control system 1 has a load control device 10, a master meter 11, and a pulse meter 12. The load control system 1 also has various load devices that are loads that consume power, such as air conditioning equipment 21 and lighting equipment 22. Here, load control refers to control that controls the output of control-target devices provided in the load control system 1 to keep the demand, which is the cumulative demand for the output of all load devices of the high-voltage consumer, within a demand target value.

[0015] Master meter 11 is connected to electric utility company 2. Master meter 11 receives power from the electric utility company. Master meter 11 then supplies power to various devices including air conditioning equipment 21 and lighting equipment 22. Master meter 11 then detects changes in power consumption of high-voltage consumers. Master meter 11 includes pulse meter 12.

[0016] The pulse meter 12 extracts the total value and instantaneous value of the outputs of all the load devices of the high voltage consumer as pulses, and outputs the extracted pulses to the load control device 10.

[0017] The load control device 10 controls the cumulative demand of all load devices of high-voltage consumers by outputting control command values ​​to the control target devices such as the air conditioners 21, thereby reducing the output of the control target devices. Since the demand is given as a 30-minute demand integrated value, the load control device 10 calculates a control amount every 30 minutes, for example, and outputs a control command value. However, the output timing of the control command value is not limited to this and may be other timing.

[0018] The following describes in detail the load control by the load control device 10. Here, an example is described in which the load control device 10 controls the air conditioning equipment 21 as the control target equipment, which accounts for a large portion of power consumption in the summer when maximum demand is likely to occur. However, the load control device 10 may also control the load of all the load equipment of the high-voltage consumer by controlling other equipment or a combination of such equipment as the control target equipment, as long as they are equipment that serves as a load in the load control system 1.

[0019] Fig. 2 is a block diagram of a load control device according to Example 1. As shown in Fig. 2, the load control device 10 includes a demand prediction unit 101, a determination unit 102, a tentative control execution unit 103, an output estimation unit 104, and a main control execution unit 105.

[0020] The demand prediction unit 101 acquires pulse data by receiving pulses output from the pulse meter 12. Next, the demand prediction unit 101 uses the acquired pulse data to calculate the integrated demand from 0 to 15 minutes in the 30-minute control period.

[0021] Next, the demand prediction unit 101 predicts the cumulative demand for 15 to 30 minutes using the cumulative demand for 0 to 15 minutes and the demand at the 15 minute point. Any prediction method may be used for this prediction. For example, before the provisional control, the demand prediction unit 101 may use the cumulative demand for 0 to 15 minutes as a predicted value for the cumulative demand for 15 to 30 minutes. Here, the demand prediction unit 101 can determine whether the provisional control has been performed by receiving a notification of the execution of the provisional control from the provisional control execution unit 103, for example.

[0022] Furthermore, when the provisional control is ended and the main control is performed, the demand prediction unit 101 receives an input of the actual output reduction value due to the provisional control from the output estimation unit 104. Then, the demand prediction unit 101 predicts the accumulated demand for 15 to 30 minutes after the provisional control, taking into account the actual output reduction value due to the provisional control. The predicted value of the accumulated demand for 15 to 30 minutes after the provisional control is the predicted value of the accumulated demand for 15 to 30 minutes when the provisional control is performed at the 15th minute. Any prediction method may be used as long as it takes into account the amount of output reduction when the provisional control is performed. For example, the demand prediction unit 101 may use a value obtained by subtracting the demand actually reduced by the provisional control from the accumulated demand for 0 to 15 minutes as the predicted value of the accumulated demand for 15 to 30 minutes after the provisional control.

[0023] In this way, the demand prediction unit 101 predicts the cumulative demand of the consumer load including the control target device for a predetermined period. In this embodiment, the predetermined period corresponds to 30 minutes corresponding to the demand.

[0024] Next, the demand prediction unit 101 calculates a predicted value of the 30-minute integrated demand by adding the predicted value of the integrated demand from 0 to 15 minutes and the predicted value of the integrated demand from 15 to 30 minutes, and multiplies the calculated value by 2 to calculate a predicted demand value per hour. That is, by multiplying by 2, the demand prediction unit 101 converts the 30-minute integrated demand value in units of kWh into a demand value in units of kW. Here, in the case after the provisional control but before the execution of the main control, the demand prediction unit 101 calculates the predicted demand value after the provisional control, that is, the predicted demand value when the provisional control is executed.

[0025] After that, if the current state is before the provisional control, the demand prediction unit 101 outputs the calculated predicted demand value to the determination unit 102. On the other hand, if the current state is after the provisional control but before the main control, the demand prediction unit 101 outputs the calculated predicted demand value to the main control execution unit 105 together with an instruction to execute the main control.

[0026] The determination unit 102 has in advance a demand target value determined from the contracted power. Before the tentative control, the determination unit 102 receives an input of a demand prediction value, which is a predicted value of the integrated demand before the tentative control, from the demand prediction unit 101. Next, the determination unit 102 determines whether the demand prediction value exceeds the demand target value.

[0027] If the demand prediction value does not exceed the demand target value, the determination unit 102 determines that load control is unnecessary. In this case, the load control device 10 ends the load control process. On the other hand, if the demand prediction value exceeds the demand target value, the determination unit 102 outputs the demand prediction value after the tentative control to the tentative control execution unit 103 together with an instruction to execute tentative control.

[0028] The tentative control execution unit 103 also has a demand target value in advance. The tentative control execution unit 103 receives an instruction to execute tentative control as well as an input of a demand prediction value from the determination unit 102. Then, the tentative control execution unit 103 subtracts the demand target value from the demand prediction value to calculate a reduction target value of the integrated demand from 15 to 30 minutes.

[0029] The tentative control execution unit 103 also stores in advance information on the rated output of the air conditioner 21, which is the control target device. The tentative control execution unit 103 then multiplies the target reduction value of the integrated demand from 15 to 30 minutes by 60 / 15 to calculate the target reduction value of the output for one hour. That is, by multiplying by 60 / 15, the tentative control execution unit 103 converts the integrated demand value for 15 minutes, in units of kWh, into an output value in units of kw.

[0030] Next, the tentative control execution unit 103 calculates the ratio of the output reduction target value to the rated output of the air conditioning equipment 21, and sets the calculated value as a command value. Then, the tentative control execution unit 103 outputs the command value to the air conditioning equipment 21, and controls the air conditioning equipment 21 so as to reduce the output to the ratio indicated by the command value. As a result, the demand prediction unit 101 receives pulse data after the tentative control.

[0031] The tentative control execution unit 103 is an example of a "first control unit." Then, in accordance with the determination result by the determination unit 102, the tentative control execution unit 103 calculates a first reduction amount that makes the integrated demand after the first control equal to or less than a target value, assuming that the control-target equipment operates at rated output, and performs a first control of the output of the control-target equipment based on the first reduction amount. That is, the tentative control execution unit 103 calculates the first reduction amount, assuming that the control-target equipment operates at rated output. Here, the target value of output reduction by the tentative control is an example of a "first reduction amount." More specifically, the tentative control execution unit 103 calculates the first reduction amount based on the difference between the predicted value of the integrated demand in the case where control is not performed and the target value, and the rated output.

[0032] The output estimation unit 104 receives pulses output from the pulse meter 12 and acquires pulse data. Then, the output estimation unit 104 uses the pulse data to calculate the demand 15 minutes before the execution of the tentative control. The output estimation unit 104 also uses the pulse data to calculate the demand 15 minutes before the execution of the main control. Then, the output estimation unit 104 subtracts the demand 15 minutes after the execution of the main control from the demand 15 minutes before the execution of the tentative control to calculate the actual output reduction value of the air conditioner 21. Thereafter, the output estimation unit 104 outputs the calculated actual output reduction value to the demand prediction unit 101.

[0033] The main control execution unit 105 also has a demand target value in advance. The main control execution unit 105 receives an input of the actual output reduction value of the air conditioning equipment 21 from the output estimation unit 104. The main control execution unit 105 also receives an input of a demand prediction value after the tentative control from the demand prediction unit 101 along with an instruction to execute the main control. The main control execution unit 105 then subtracts the demand target value from the demand prediction value after the tentative control to calculate a reduction target value of the integrated demand from 15 to 30 minutes.

[0034] The control execution unit 105 also stores in advance information on the rated output of the air conditioning equipment 21, which is the equipment to be controlled. The control execution unit 105 then multiplies the target reduction value of the integrated demand from 15 to 30 minutes by 60 / 15 to calculate the target reduction value of the output for one hour. In other words, by multiplying by 60 / 15, the control execution unit 105 converts the integrated demand value for 15 minutes, in units of kWh, into an output value in units of kw.

[0035] Next, the control execution unit 105 calculates the ratio of the output reduction target value to the rated output of the air conditioning equipment 21. In this case, since load control is performed by provisional control, the control execution unit 105 calculates the ratio of the output reduction target value including the control amount by provisional control. That is, the control execution unit 105 multiplies the rated output by the command value used in the provisional control to calculate the output after provisional control, and then subtracts the output reduction target value from the calculated output after provisional control to calculate the ratio to the rated output, thereby calculating the ratio of the output reduction target value to the rated output. Next, the control execution unit 105 sets the calculated value as the command value. Then, the control execution unit 105 outputs the command value to the air conditioning equipment 21 and controls the air conditioning equipment 21 to reduce the output to the ratio indicated by the command value. In this way, the control execution unit 105 can control the output of the air conditioning equipment 21 so that the integrated value of demand due to all load equipment of high-voltage consumers does not exceed the demand target value.

[0036] This actual control execution unit 105 is an example of a "second control unit." Then, based on the result of the tentative control by the tentative control execution unit 103, which is the first control unit, the actual control execution unit 105 calculates a second reduction amount that makes the accumulated demand after the second control equal to or less than the target value, and performs a second control of the output of the control-target device based on the second reduction amount. More specifically, the actual control execution unit 105 calculates the second reduction amount based on the difference between the first accumulated demand and the target value when the first control is performed, which is predicted by the demand prediction unit 101 based on the actual reduction amount due to the tentative control of the output of the control-target device, and the rated output. Here, the target value of output reduction due to this control is an example of a "second reduction amount."

[0037] FIG. 3 is a diagram showing an example of numerical values ​​when temporary control is executed when load control is not performed before the temporary control. FIG. 4 is a diagram showing an example of numerical values ​​when full control is executed when load control is not performed before the temporary control. Next, with reference to FIGS. 3 and 4, calculation of a command value for suppressing exceeding of the demand target value when load control is not performed before the temporary control will be described. Here, four patterns of power demand, Cases #1 to #4, will be described. In each of Cases #1 to #4, the integrated demand from 0 to 15 minutes is 26.5 (kWh), and the demand at 15 minutes is 106 (kW). The demand target value is 100 (kW), and the rated output of the air conditioner 21 is 30 (kW).

[0038] Case #1 will be described. The demand prediction unit 101 uses pulse data acquired from the pulse meter 12 to calculate the integrated demand from 0 to 15 minutes as 26.5 (kWh). Here, the integrated demand from 0 to 15 minutes is represented as (A). Next, the demand prediction unit 101 uses the integrated demand from 0 to 15 minutes as a predicted value of the integrated demand from 15 to 30 minutes, and calculates the predicted value of the integrated demand from 15 to 30 minutes as 26.5 (kWh). However, this method of calculating the predicted value is just an example, and other calculation methods can also be adopted. Here, the predicted value of the integrated demand from 15 to 30 minutes is represented as (C). Next, if the predicted demand value is (D), the calculation formula for the demand prediction value by the tentative control execution unit 103 in this case is represented as D = (A + C) × 2. Therefore, the demand prediction unit 101 calculates the demand prediction value as (26.5 + 26.5) × 2 = 106 (kWh). In this case, since the demand prediction value exceeds the demand target value, the determination unit 102 determines to execute load control.

[0039] Next, if the target reduction value of the integrated demand from 15 to 30 minutes is (F), the calculation formula for the target reduction value of the integrated demand from 15 to 30 minutes by the tentative control execution unit 103 in this case is expressed as F = (DE) / 2. Therefore, the tentative control execution unit 103 calculates the target reduction value of the integrated demand from 15 to 30 minutes as (106 - 100) / 2 = 3 (kWh). Next, if the target reduction value of the output is (I), the calculation formula for the target reduction value of the output by the tentative control execution unit 103 in this case is expressed as I = F × 60 / 15. Therefore, the tentative control execution unit 103 calculates the target reduction value of the output as 3 × 60 / 15 = 12. Next, if the rated output is expressed as (G) and the command value is expressed as (J), the calculation formula for the command value by the tentative control execution unit 103 in this case is expressed as J = (GI) / G × 100. Therefore, the tentative control execution unit 103 calculates the command value as (30-12) / 30×100=60(%).The tentative control execution unit 103 then outputs the calculated command value to the air conditioner 21, and controls the air conditioner 21 to operate at 60(%) of the rated output.

[0040] In case #1, the output estimation unit 104 uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the provisional control as 106 (kW), as shown in FIG. 3. The output estimation unit 104 also uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the main control as 94 (kW), as shown in FIG. 4. If the demand 15 minutes before the provisional control is represented as (B), the demand 15 minutes before the main control is represented as (B'), and the actual output reduction value is represented as (K), the calculation formula for the actual output reduction value by the output estimation unit 104 is expressed as K = B - B'. Therefore, the output estimation unit 104 calculates the actual output reduction value due to the provisional control as 106 - 94 = 12 (kW). In this case, if the excess of the demand after the provisional control over the demand target value is represented as L, then L = (IK) × 15 / 30. That is, the excess over the demand target value after the provisional control is (12-12) x 15 / 30 = 0, as shown in Fig. 3. In this case, the load control device 10 is able to suppress the integrated demand amount of all the load devices of the high-voltage consumer within the demand target value through the provisional control.

[0041] Therefore, in practice, the command value of the provisional control is maintained even in this control. Here, the processing of this control in this case will be explained step by step. In this control, the demand prediction unit 101 calculates the cumulative demand from 0 to 15 minutes as 26.5 (kWh) using pulse data acquired from the pulse meter 12, as shown in FIG. 4. Next, the demand prediction unit 101 subtracts the output reduction value per 15 minutes due to the provisional control from the cumulative demand from 0 to 15 minutes before the provisional control to calculate a predicted value of the cumulative demand from 15 to 30 minutes when the provisional control is performed. Here, if the predicted value of the cumulative demand from 15 to 30 minutes after the provisional control is represented as (C'), the predicted value of the cumulative demand from 15 to 30 minutes after the provisional control by the demand prediction unit 101 is expressed as C' = A - (K × 15 / 60). Therefore, the demand prediction unit 101 calculates the predicted value of the integrated demand from 15 to 30 minutes after the provisional control as 26.5-12×15 / 60=23.5 (kWh). Next, if the predicted demand value is (D'), the calculation formula for the predicted demand value by the control execution unit 105 is expressed as D'=(A+C')×2. Therefore, the control execution unit 105 calculates the predicted demand value as (26.5+23.5)×2=100 (kWh). Next, if the reduction target value of the integrated demand from 15 to 30 minutes is (F'), the calculation formula for the reduction target value of the integrated demand from 15 to 30 minutes by the control execution unit 105 in this case is expressed as F'=(D'-E) / 2. Therefore, the control execution unit 105 calculates the target reduction value of the integrated demand from 15 to 30 minutes as (100-100) / 2=0 (kWh). Next, if the target reduction value of output is (I'), the calculation formula for the target reduction value of output by the control execution unit 105 is expressed as I'=F'×60 / 15. Therefore, the control execution unit 105 calculates the target reduction value of output as 0×60 / 15=0. Next, if the command value is expressed as (J'), the calculation formula for the command value by the control execution unit 105 is expressed as J'=(G×J / 100-I') / G×100. Therefore, the control execution unit 105 calculates the command value as (30×60 / 100-0) / 30×100=60(%). Then, the main control execution unit 105 outputs the calculated command value to the air conditioner 21, and controls the air conditioner 21 to operate at 60(%) of the rated output.Here, as described above, the provisional control can suppress the accumulated demand of all load devices of high-voltage customers within the demand target value, so the control execution unit 105 may actually use the provisional control command value as is without calculating the command value described here.

[0042] Next, case #2 will be described. As shown in Fig. 3, the numerical values ​​in the state before the tentative control are the same in case #2 as in case #1. In this case, as in case #1, the tentative control execution unit 103 outputs the calculated command value to the air conditioner 21 and controls the air conditioner 21 to operate at 60(%) of the rated output.

[0043] In case #2, the output estimation unit 104 also uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the provisional control as 106 (kW), as shown in FIG. 3 . Furthermore, the output estimation unit 104 also uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the full control as 99 (kW), as shown in FIG. 4 . The output estimation unit 104 then calculates the actual output reduction value due to the provisional control as 106-99=7 (kW), as shown in FIG. 3 . Here, the reason why the actual output reduction value differs from that in case #1, even though the same control was performed on the air conditioner 21 in the provisional control, is likely because the output of the air conditioner 21 was not at its rated output. In this case, the excess over the demand target value after the provisional control is (12-7)×15 / 30=2.5, as shown in FIG. 3 . In this case, the load control device 10 is unable to suppress the integrated demand of all load devices of the high-voltage consumer within the demand target value through the provisional control.

[0044] Next, in this control, the demand prediction unit 101 calculates the cumulative demand from 0 to 15 minutes as 26.5 (kWh) using pulse data acquired from the pulse meter 12, as shown in FIG. 4. Next, the demand prediction unit 101 calculates the predicted value of the cumulative demand from 15 to 30 minutes after the provisional control as 26.5-7×15 / 60=24.75 (kWh). Next, the control execution unit 105 calculates the predicted value of the demand as (26.5+24.75)×2=102.5 (kWh). Next, the control execution unit 105 calculates the reduction target value of the cumulative demand from 15 to 30 minutes as (102.5-100) / 2=1.25 (kWh). Next, the control execution unit 105 calculates the reduction target value of the output as 1.25×60 / 15=5. Next, the control execution unit 105 calculates the command value as (30×60 / 100−5) / 30×100=43.33(%). Then, the control execution unit 105 outputs the calculated command value to the air conditioning equipment 21, and controls the air conditioning equipment 21 to operate at 43.33(%) of the rated output. This allows the load control device 10 to keep the accumulated demand amount of all load equipment of high-voltage customers within the demand target value.

[0045] In case #3, the calculation process for each numerical value is the same as in case #2 except for the difference in values, so the explanation will be omitted.

[0046] Next, case #4 will be described. As shown in Fig. 3, the numerical values ​​before the provisional control are the same in case #4 as in case #1. In this case, as in case #1, the provisional control execution unit 103 outputs the calculated command value to the air conditioner 21 and controls the air conditioner 21 to operate at 60(%) of the rated output.

[0047] In case #4, the output estimation unit 104 also uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the provisional control as 106 (kW), as shown in FIG. 3 . The output estimation unit 104 also uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the main control as 106 (kW), as shown in FIG. 4 . The output estimation unit 104 then calculates the actual output reduction value due to the provisional control as 106 − 106 = 0 (kW), as shown in FIG. 3 . In this case, the output of the air conditioner 21 remains unchanged during the first provisional control. That is, it is considered that the air conditioner 21 was operating at 60% or less of its rated output before the provisional control. Therefore, in this case, the command value is reduced by a predetermined amount to perform the second provisional control. Here, the predetermined amount may be, for example, 5%. The load control device 10 then calculates the actual output reduction value after the second provisional control based on the command value, and performs the main control similar to case #2 using the calculated reduction value. In FIG. 4, since the first provisional control shown in FIG. 3 cannot be used to move on to the actual control, the numerical values ​​obtained in the actual control are not displayed.

[0048] FIG. 5 is a diagram showing an example of numerical values ​​when temporary control is performed when load control is performed at 80% of the rated output before the temporary control. FIG. 6 is a diagram showing an example of numerical values ​​when full control is performed when load control is performed at 80% of the rated output before the temporary control. Next, with reference to FIGS. 5 and 6, calculation of a command value for suppressing exceedance of the demand target value when load control is performed at 80% of the rated output before the temporary control will be described. Here, four patterns of power demand, Cases #5 to #8, will be described. In each of Cases #5 to #8, the integrated demand from 0 to 15 minutes is 26 (kWh), and the demand at 15 minutes is 104 (kW). The demand target value is 100 (kW), and the rated output of the air conditioner 21 is 30 (kW). When load control has already been performed before the temporary control, the command value is calculated taking into account the ratio of that load control, which differs from when load control is not performed before the temporary control.

[0049] Case #5 will be described. As shown in FIG. 5, the demand prediction unit 101 uses pulse data acquired from the pulse meter 12 to calculate the integrated demand from 0 to 15 minutes as 26 (kWh). Next, the demand prediction unit 101 uses the integrated demand from 0 to 15 minutes as a predicted value of the integrated demand from 15 to 30 minutes, and calculates the predicted value of the integrated demand from 15 to 30 minutes as 26 (kWh). Next, the tentative control execution unit 103 calculates the predicted demand value as (26 + 26) × 2 = 104 (kWh). In this case, since the predicted demand value exceeds the target demand value, the determination unit 102 decides to execute load control.

[0050] The temporary control execution unit 103 calculates the target reduction value for the integrated demand from 15 to 30 minutes as (104-100) / 2 = 2 (kWh). Next, the temporary control execution unit 103 calculates the target reduction value for output as 2 x 60 / 15 = 8. Next, the calculation formula for the command value by the temporary control execution unit 103 when load control is being performed at 80% of the rated output is expressed as J = (G x 0.8 - I) / G x 100. Therefore, the temporary control execution unit 103 calculates the command value as (30 x 0.8 - 8) / 30 x 100 = 53.33 (%). Then, the temporary control execution unit 103 outputs the calculated command value to the air conditioner 21 and controls the air conditioner 21 to operate at 53.33 (%) of the rated output.

[0051] Next, the output estimation unit 104 uses the pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the provisional control as 104 (kW), as shown in FIG. 5. Furthermore, the output estimation unit 104 uses the pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the main control as 96 (kW), as shown in FIG. 6. Then, the output estimation unit 104 calculates the actual output reduction value due to the provisional control as 104-96=8 (kW), as shown in FIG. 5. In this case, the excess over the demand target value after the provisional control is (8-8)×15 / 30=0, as shown in FIG. 5. In this case, the load control device 10 is able to suppress the integrated demand amount of all load devices of the high-voltage consumer within the demand target value through the provisional control.

[0052] Therefore, in practice, the command value of the provisional control is maintained even in this control. Here, the processing of this control in this case will be explained step by step. In this control, the demand prediction unit 101 calculates the integrated demand from 0 to 15 minutes as 26 (kWh) using pulse data acquired from the pulse meter 12, as shown in FIG. 6. Next, the demand prediction unit 101 calculates the predicted value of the integrated demand from 15 to 30 minutes after the provisional control as 26-8×15 / 60=24 (kWh). Next, the control execution unit 105 calculates the predicted value of the demand as (24+24)×2=100 (kWh). Next, the control execution unit 105 calculates the reduction target value of the integrated demand from 15 to 30 as (100-100) / 2=0 (kWh). Next, the control execution unit 105 calculates the reduction target value of the output as 0×60 / 15=0. Next, the main control execution unit 105 calculates the command value as (30×53.33 / 100−0) / 30×100=53.33(%). Then, the main control execution unit 105 outputs the calculated command value to the air conditioner 21, and controls the air conditioner 21 to operate at 53.33(%) of the rated output.

[0053] Next, case #6 will be described. As shown in Fig. 5, the numerical values ​​before the provisional control are the same in case #6 as in case #5. In this case, as in case #5, the provisional control execution unit 103 outputs the calculated command value to the air conditioner 21 and controls the air conditioner 21 to operate at 53.33(%) of the rated output.

[0054] In case #6, the output estimation unit 104 also uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the provisional control as 104 (kW), as shown in FIG. 5 . Also, using pulse data acquired from the pulse meter 12, the output estimation unit 104 calculates the demand 15 minutes before the main control as 99 (kW), as shown in FIG. 6 . The output estimation unit 104 then calculates the actual output reduction value due to the provisional control as 104-99=5 (kW), as shown in FIG. 5 . Here, the reason why the actual output reduction value differs from that in case #5, even though the same control was performed on the air conditioner 21 in the provisional control, is likely because the output of the air conditioner 21 was not 80% of its rated output. In this case, the excess over the demand target value after the provisional control is (8-5)×15 / 30=1.5, as shown in FIG. 5 . In this case, the load control device 10 is unable to suppress the integrated demand of all load devices of the high-voltage consumer within the demand target value through the provisional control.

[0055] Next, in this control, the demand prediction unit 101 calculates the integrated demand from 0 to 15 minutes as 26 (kWh) using pulse data acquired from the pulse meter 12, as shown in FIG. 6. Next, the demand prediction unit 101 calculates the predicted value of the integrated demand from 15 to 30 minutes after the provisional control as 26-5×15 / 60=24.75 (kWh). Next, the control execution unit 105 calculates the predicted value of the demand as (26+24.75)×2=101.5 (kWh). Next, the control execution unit 105 calculates the reduction target value of the integrated demand from 15 to 30 minutes as (101.5-100) / 2=0.75 (kWh). Next, the control execution unit 105 calculates the reduction target value of the output as 0.75×60 / 15=3. Next, the control execution unit 105 calculates the command value as (30×53.33 / 100−3) / 30×100=43.33(%). Then, the control execution unit 105 outputs the calculated command value to the air conditioning equipment 21, and controls the air conditioning equipment 21 to operate at 43.33(%) of the rated output. This allows the load control device 10 to keep the accumulated demand amount of all load equipment of high-voltage customers within the demand target value.

[0056] In case #7, the calculation process for each numerical value is the same as in case #6 except for the difference in values, so the explanation will be omitted.

[0057] Next, case #8 will be described. As shown in Fig. 5, the numerical values ​​before the provisional control are the same in case #8 as in case #5. In this case, as in case #5, the provisional control execution unit 103 outputs the calculated command value to the air conditioner 21 and controls the air conditioner 21 to operate at 53.33(%) of the rated output.

[0058] In case #8, the output estimation unit 104 also uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes before the provisional control as 104 (kW), as shown in FIG. 5. The output estimation unit 104 also uses pulse data acquired from the pulse meter 12 to calculate the demand 15 minutes after the provisional control as 104 (kW), as shown in FIG. 6. The output estimation unit 104 then calculates the actual output reduction value due to the provisional control as 104-104=0 (kW), as shown in FIG. 5. In this case, the output of the air conditioner 21 remains unchanged during the first provisional control. That is, it is considered that the air conditioner 21 was operating at 53.33% or less of its rated output before the provisional control. Therefore, in this case, the command value is reduced by a predetermined amount to perform the second provisional control. The load control device 10 calculates the actual output reduction value after the second provisional control based on the command value, and performs the same main control as in case #6 using the calculated reduction value.

[0059] 7 is a flowchart of the load control process by the load control device according to the embodiment 1. Next, the flow of the load control process by the load control device 10 according to the present embodiment will be described with reference to FIG.

[0060] The demand prediction unit 101 acquires pulse data that indicates the total value of the outputs of all the load devices of the high-voltage consumer from the pulse meter 12. Then, the demand prediction unit 101 uses the acquired pulse data to predict the demand, which is an integrated value for 30 minutes (step S1).

[0061] The determination unit 102 compares the demand prediction value calculated by the demand prediction unit 101 with the demand at the 15-minute point in time and determines whether the demand prediction value exceeds the demand target value (step S2). If the demand prediction value does not exceed the demand target value (step S2: No), the load control device 10 ends the load control process.

[0062] On the other hand, if the demand prediction value exceeds the target value (step S2: Yes), the tentative control execution unit 103 calculates a reduction target value for the output of the control-target device from the demand prediction value and the demand target value.Then, the tentative control execution unit 103 calculates a command value for tentative control using the rated output and reduction target value of the control-target device (step S3).

[0063] Next, the tentative control execution unit 103 executes tentative control of the control-target device using the calculated command value (step S4).

[0064] The output estimation unit 104 calculates the output before the temporary control and the output after the temporary control using pulse data indicating the total value of the outputs of all the load devices of the high-voltage consumer transmitted from the pulse meter 12. Then, the output estimation unit 104 estimates the output of the target device using the output before the temporary control and the output after the temporary control (step S5).

[0065] Next, the main control execution unit 105 determines whether the output of the target device has decreased due to the tentative control (step S6). If the output of the target device has not decreased due to the tentative control (step S6: No), the main control execution unit 105 instructs the tentative control execution unit 103 to re-execute the tentative control. Upon receiving the instruction to re-execute the tentative control, the tentative control execution unit 103 calculates a new tentative control command value by subtracting a predetermined amount from the calculated tentative control command value (step S7). Thereafter, the tentative control execution unit 103 returns to step S4.

[0066] On the other hand, if the output of the target device is reduced by the provisional control (step S6: Yes), the main control execution unit 105 acquires a demand prediction value that takes into account the output reduction value due to the provisional control from the demand prediction unit 101. Then, the main control execution unit 105 calculates a command value for the main control using the output estimation result, the demand prediction value, and the demand target value (step S8).

[0067] Thereafter, the main control execution unit 105 executes the main control of the control target device using the calculated command value (step S9).

[0068] FIG. 8 is a diagram for explaining the effect of load control by the load control device according to the first embodiment. Graph 201 is a graph showing a comparison of the amount of output reduction when no load control is performed, when load control is performed assuming that the controlled equipment is operating at rated output, and when load control according to this embodiment is performed. Graph 201 has output on the vertical axis, and the cases when no load control is performed, when load control is performed assuming that the controlled equipment is operating at rated output, and when load control according to this embodiment is performed are arranged in order from left to right on the page. Rated output 211 represents the rated output of the controlled equipment. Operating output 212, which corresponds to the output when no load control is performed, represents the actual operating output of the controlled equipment before control is performed.

[0069] When load control is performed assuming that the controlled device is operating at rated output, the load control device 10 calculates an estimated reduction amount 213 so as not to exceed the demand target value, and outputs the value obtained by subtracting the estimated reduction amount 213 from the rated output 211 as a control command value. In this control, if the operating output 212 is lower than the rated output 211, the actual reduction amount 214 is actually reduced from the output of the controlled device, making it difficult to sufficiently reduce the output.

[0070] In contrast, when load control according to this embodiment is performed, the load control device 10 uses past demand data and the like as learning data to calculate an estimated reduction amount 215 so as not to exceed the demand target value. In this case, the estimated reduction amount 215 coincides with the actual reduction amount 216. Therefore, the load control device 10 can issue an appropriate control command to the controlled device so as not to exceed the demand target value.

[0071] The changes in the cumulative amount of power due to these controls are shown in graph 202. Line 223 represents the changes when no control is performed. Line 224 represents the changes when load control is performed assuming that the controlled device is operating at rated output. Line 225 represents the changes when load control according to this embodiment is performed. Value 222 represents the target demand value. Time point 221 is the timing when control is started.

[0072] As shown by line 223, if no control is performed, the cumulative amount of power will continue to increase after time point 221 in the same way as before, and the predicted demand value will exceed the target demand value, as shown by line 223. Therefore, control is performed at time point 221, but if load control is performed assuming that the controlled device is operating at rated output, the amount of reduction will be insufficient, and the cumulative amount of power will ultimately exceed the target demand value, as shown by line 224. In contrast, when load control according to this embodiment is performed, the amount of reduction can be appropriately estimated, and the cumulative amount of power can be kept within the target demand value.

[0073] In the above examples, the timing for prediction and control has been described as being 15 minutes after the demand count time limit, but the timing is not limited to this and can be any timing such as 5 minutes, 10 minutes, 20 minutes, etc., or it can be performed every minute.

[0074] As described above, the load control device 10 according to this embodiment performs provisional control based on the demand prediction result, estimates the output of the controlled device when provisional control is performed, and calculates a command value for suppressing the cumulative amount of power to within the target value based on the estimated output and taking into account the actual operating output. By using the command value calculated in this way to control the controlled device and reduce the output, it is possible to appropriately suppress excess demand relative to the target value. [Example]

[0075] FIG. 9 is a block diagram of a load control device according to a second embodiment. The load control device 10 according to this embodiment performs provisional control for a certain period of time as a learning period, and after the learning period has elapsed, estimates the output of the controlled device from pulse data using the control results of the provisional control and performs control. Details of the load control device 10 according to this embodiment will be described below. The load control device 10 according to this embodiment has a correlation function generation unit 106 in addition to the units of the first embodiment. Here, a description of the operation of each unit similar to that of the first embodiment will be omitted.

[0076] If the judgment unit 102 judges that the demand prediction value has exceeded the demand target value for a predetermined period of time, such as one month, the tentative control execution unit 103 assumes that the controlled equipment is operating at rated output and performs load control so that the demand falls within the demand target value.

[0077] During the learning period, the output estimation unit 104 calculates an actual output reduction value of the controlled equipment each time load control is executed by the tentative control execution unit 103. Thereafter, the output estimation unit 104 outputs to the demand prediction unit 101 the calculated actual output reduction value together with the total output of all loads of the high-voltage consumers at the current 15-minute point, which is obtained from pulse data acquired from the pulse meter 12.

[0078] During the learning period, each time load control is executed by the tentative control execution unit 103, the correlation function generation unit 106 acquires and collects the total output of all loads of high-voltage consumers and the actual output reduction value at that time from the output estimation unit 104. After the learning period has elapsed, the correlation function generation unit 106 generates a correlation function that represents the relationship between the total output of all loads of high-voltage consumers collected during the learning period and the estimated result of the actual output reduction value. Then, the correlation function generation unit 106 outputs the generated correlation function to the actual control execution unit 105. In other words, the correlation function generation unit 106 generates a correlation function that represents the relationship between the output of the demand overload during a certain period and the actual reduction amount calculated by the output estimation unit 104.

[0079] FIG. 10 is a diagram illustrating an example of calculation of a correlation function between the total output of all load devices and the actual output reduction value by the load control device according to the second embodiment. In FIG. 10, the horizontal axis represents the total output of all load devices, which is the total output of all load devices of high-voltage consumers, and the vertical axis represents an estimated value of the actual output reduction value of the air conditioning device 21, which is the controlled device. For example, as shown in FIG. 10, the correlation function generation unit 106 plots each of the collected data on a two-dimensional plane having axes representing the total output of all load devices of high-voltage consumers and the actual output reduction value. In FIG. 10, points included in a frame 231 represent the actual output reduction value with respect to the total output of all load devices when a command value of 70% of the rated output is set. Furthermore, points included in a frame 232 represent the actual output reduction value with respect to the total output of all load devices when a command value of 50% of the rated output is set. Next, the correlation function generation unit 106 generates a straight line 233 that approximates the plotted points. Then, the correlation function generating unit 106 outputs the generated function representing the straight line 233 to the demand predicting unit 101 as a correlation function.

[0080] After the learning period has elapsed, the demand prediction unit 101 acquires a correlation function representing the relationship between the total output of all loads of the high-voltage consumers and the estimated output of the controlled devices from the correlation function generation unit 106. The demand prediction unit 101 also calculates the total output of all loads of the high-voltage consumers from pulse data acquired from the pulse meter 12. The demand prediction unit 101 then calculates the output of the controlled devices corresponding to the calculated total output of all load devices using the correlation function. For example, if the correlation function is a function representing the straight line 233 in FIG. 10 , and the demand prediction unit 101 acquires value 234 as the total output of all load devices, it acquires value 235 as an estimate of the actual output reduction value. The demand prediction unit 101 then predicts the demand after the provisional control using the estimate of the actual output reduction value. The demand prediction unit 101 then outputs the demand prediction value to the actual control execution unit 105.

[0081] Here, the output estimation unit 104 may estimate the output of the controlled device from the actual output reduction value each time load control is executed by the tentative control execution unit 103 during the learning period. In this case, the correlation function generation unit 106 generates a correlation function that represents the relationship between the total output of all loads of high-voltage consumers collected during the learning period and the estimated result of the output of the controlled device. Then, the correlation function generation unit 106 outputs the generated correlation function to the demand prediction unit 101.

[0082] The control execution unit 105 receives an input of a demand prediction value determined using a correlation function from the demand prediction unit 101. Then, the control execution unit 105 determines a command value using the acquired demand prediction value, demand target value, and rated output. The method of calculating the command value here is the same as in the first embodiment. Then, the control execution unit 105 transmits the command value to the control-target device to perform load control of the control-target device.

[0083] As described above, the load control device according to this embodiment repeats tentative control during a learning period and generates a correlation function between the total output of all load devices and the estimated value of the output of the controlled devices using the data collected thereby. The load control device then estimates the output of the controlled devices corresponding to the measured total output of all load devices using the generated correlation function, and controls the controlled devices using the estimated result. In this way, by estimating the output of the controlled devices corresponding to the measured total output of all load devices based on the results of multiple tentative controls, the influence of results in unusual cases can be reduced, and the output of the controlled devices can be accurately estimated. Therefore, excess demand suppression relative to the target value can be more appropriately performed. [Example]

[0084] FIG. 11 is a block diagram of a load control device according to a third embodiment. In the first and second embodiments, the fluctuation in demand when the control amount is changed is estimated based on the rated output of the controlled device. However, fluctuations in demand of devices not subject to control due to controlling the output of the controlled device, and fluctuations in demand due to other external factors are also possible. Therefore, the load control device 10 according to this embodiment analyzes and learns the extent of change in demand when a predetermined control level is changed in actual performance, and performs load control based on the learning results. The load control device 10 according to this embodiment has an actual average reduction amount calculation unit 107 in addition to the respective units of the first embodiment. In the following explanation, explanations of the operations of the same units as those of the first embodiment will be omitted.

[0085] The load control device 10 according to this embodiment has in advance control levels in which the control amount is divided into stages. In this embodiment, the load control device 10 has control levels LV0 to LV4 set in advance. Control level LV0 is a case where no load control is performed, and the control amount is 0. The control amounts increase in the order of control levels LV0 to LV4. For example, the load control device 10 outputs a command value for 80% of the rated output at control level LV1, a command value for 70% of the rated output at control level LV2, a command value for 60% of the rated output at control level LV3, and a command value for 50% of the rated output at control level LV4.

[0086] The tentative control execution unit 103 performs load control to suppress demand to the demand target value, assuming that the controlled equipment operates at rated output during a certain learning period, such as one month. However, in this embodiment, the tentative control execution unit 103 outputs a command value according to a control level that provides the closest control amount equal to or greater than the control amount that suppresses demand to the demand target value. The tentative control execution unit 103 outputs information about the control level of the load control executed for the air conditioning equipment 21 to the actual average reduction amount calculation unit 107.

[0087] During the learning period, the actual average reduction amount calculation unit 107 receives input of the control level from the tentative control execution unit 103. Furthermore, the actual average reduction amount calculation unit 107 acquires pulses representing the output values ​​of all the load devices of the high-voltage consumer at each timing output from the pulse meter 12. Then, the actual average reduction amount calculation unit 107 acquires pulse data based on the pulses, and calculates the usage amount, which is the one-minute value in kWh of the output of all the load devices of the high-voltage consumer, using the acquired pulse data.

[0088] Next, the actual average reduction amount calculation unit 107 acquires the usage amounts for 5 to 10 minutes immediately before and after the control level change. Then, the actual average reduction amount calculation unit 107 calculates a pre-change usage amount, which is the average value of the usage amounts for 5 to 10 minutes immediately before the control level change, and a post-change usage amount, which is the average value of the usage amounts for 5 to 10 minutes immediately after the control level change.

[0089] FIG. 12 is a diagram illustrating an example of the pre-change usage amount and the post-change usage amount when the control level changes from LV0 to LV2. In FIG. 12, the control level changes at 14:01:20, and the value for one minute before 14:02 includes both control level LV0 and control level LV2. Therefore, the actual average reduction amount calculation unit 107 does not use the value for one minute before 14:02 to calculate the pre-change usage amount and the post-change usage amount. In the case of FIG. 12, the actual average reduction amount calculation unit 107 calculates 0.8726 kWh, which is the average of the usage amount for 10 minutes from 13:52 to 14:01, which is included in the range 301, as the pre-change usage amount. In this way, to reduce the impact of demand fluctuations, the actual average reduction amount calculation unit 107 does not include the usage amount at 13:51, which is 10 minutes before the change time, in its calculation. Furthermore, the actual average reduction amount calculation unit 107 calculates 0.9984 kWh as the post-change usage amount, which is the average usage amount for the eight minutes from 14:03 to 14:10, before the next control level change, which is included in range 302. In this case, since 0.9984 - 0.8726 × 60 ≒ 7.55, it is considered that changing from control level LV2 to control level LV0 increased demand by approximately 7.55 kW.

[0090] Fig. 13 is a diagram showing changes in usage amount for each change in control level. Fig. 14 is a diagram showing changes in usage amount when changing from control level LV0 to control level LV1. In each graph shown in Figs. 13 and 14, the horizontal axis represents usage amount before the change and the vertical axis represents usage amount after the change. Here, changes in usage amount due to changes in control level will be described with reference to Figs. 13 and 14.

[0091] Figure 13 is a diagram in which graphs are arranged in a matrix, plotting points on a coordinate plane that represent the correspondence between the usage amount before and after each change in control level collected during the learning period. Although the scales are omitted from each graph in Figure 13, they are on the same scale as the graphs in Figure 14. Furthermore, for each graph in Figure 13, the number written either above or below the graph as you face the page represents the control level of the usage amount before the change, and the number written either to the left or right represents the control level of the usage amount after the change.

[0092] For example, the top graph in the leftmost column of Fig. 13 is a graph showing the change in usage when changing from control level LV0 to control level LV1, the same as the graph in Fig. 14. Here, since there were no records of changes from control level LV1 to control level LV4 and from control level LV4 to control level LV1 during the learning period, no points are plotted on the corresponding graphs.

[0093] Each point 311 in FIG. 13 is a point plotted on a coordinate plane representing the correspondence between the usage amount before the change and the usage amount after the change when the control level collected during the learning period changes. Each point 311 in FIG. 14 is a point plotted on a coordinate plane representing the correspondence between the usage amount before the change and the usage amount after the change when the control level is changed from LV0 to LV1, which is collected during the learning period. Furthermore, a straight line 312 in FIGS. 13 and 14 is a line on which the usage amount before the change and the usage amount after the change coincide. For example, in FIG. 14, many of the points 311 are distributed below the straight line 312, which indicates that applying control at control level LV1 tends to reduce demand more than when the control level is LV0, which is uncontrolled.

[0094] Referring to FIG. 13, the graphs positioned to the upper right of the diagonal line on which the control levels are plotted generally show changes in which the control levels decrease, and therefore the points 311 tend to be distributed above the line 312. Also, the graphs positioned to the lower left of the diagonal line on which the control levels are plotted show changes in which the control levels increase, and therefore the points 311 tend to be distributed below the line 312. Comparing the graphs in the leftmost column of FIG. 13, which show a control level of LV0 before the change, shows that the higher the control level after the change, the greater the amount of usage before the change. This reflects the fact that the greater the demand between 0 and 15 minutes, the greater the amount of output suppressed between 15 and 30 minutes.

[0095] During the learning period, the actual average reduction amount calculation unit 107 accumulates information on the usage amount before the change and the usage amount after the change for each change in the control level by the tentative control execution unit 103. After the learning period has elapsed, the actual average reduction amount calculation unit 107 calculates the actual average reduction amount, which is the amount of output reduction based on the actual results, using the information on the usage amount before the change and the usage amount after the change for each change in the control level.

[0096] Here, the actual average reduction amount is d i (i=0~4), d i is the expected decrease in usage when control level LV0 is changed to control level LVi, and this value is called the expected decrease. However, d0 = 0. Also, the expected decrease in usage when control level LVi is changed to control level LV0 is also d i Control level d i to control level d j The expected decrease when changing to (j=0~4, k≠i) is d i -d k The above conditions are satisfied. i The actual average reduction amount calculation unit 107 calculates as a solution to the minimization problem of the following equations (1) to (3).

[0097]

number

number

number

[0098] Here, K(i,j) is the number of pre-change usage amounts and post-change usage amounts obtained when changing from control level LVi to control level LVj during the learning period. Also, b(i,j,k) is the kth value among the differences between the pre-change usage amount and the post-change usage amount when changing from control level LVi to control level LVj. For example, when the kth change in usage amount when changing from control level LV2 to control level LV0 is shown in Figure 12, b(2,0,k) = 0.9984 - 0.87266.

[0099] As a result, the actual average reduction amount calculation unit 107 calculates d i (i=0 to 4) can be calculated. Thereafter, the actual average reduction amount calculation unit 107 outputs the actual average reduction amount corresponding to each of the control levels LV1 to LV4 to the main control execution unit 105.

[0100] In this way, the actual average reduction amount calculation unit 107 calculates the output of the demand overload, and calculates the actual average reduction amount, which is the actual reduction amount of the output of the consumer load according to the first reduction amount, based on the output of the demand overload over a certain period of time and the first reduction amount due to the provisional control.

[0101] The control execution unit 105 receives input of the actual average reduction amount corresponding to each of the control levels LV1 to LV4 from the actual average reduction amount calculation unit 107. Thereafter, when actually performing load control, the control execution unit 105 calculates a reduction target value of the integrated demand from 15 to 30 minutes from the demand prediction value and the demand target value acquired from the demand prediction unit 101. Then, the control execution unit 105 identifies a control level that results in the smallest actual average reduction amount that is equal to or greater than the calculated reduction target value of the integrated demand from 15 to 30 minutes from the information on the actual average reduction amount corresponding to each of the control levels LV1 to LV4. Then, the control execution unit 105 outputs a command value at the identified control level to the controlled equipment such as the air conditioner 21.

[0102] In this way, the main control execution unit 105 according to this embodiment calculates the difference between the predicted value of the integrated demand in the case where the control predicted by the demand prediction unit 101 is not performed and the target value. Then, the main control execution unit 105 specifies the actual average reduction amount according to the calculated difference, and sets the first reduction amount in the tentative control corresponding to the specified actual average reduction amount as the second reduction amount in the main control.

[0103] As described above, the load control device according to this embodiment acquires usage amounts, which are one-minute values ​​in kWh of the output of all load devices of high-voltage consumers before and after the control level change in the tentative control performed during the learning period. The load control device then uses the usage amounts to calculate pre-change and post-change usage amounts, and calculates an actual average reduction amount, which represents the reduction in demand compared to the uncontrolled state when controlled at each control level, using the calculated actual average reduction amount. The load control device then determines a control level and controls the controlled devices so as to achieve the demand target value using the calculated actual average reduction amount.

[0104] This allows control to be performed taking into account fluctuations in demand for devices other than the controlled device and fluctuations in demand due to other external factors, thereby enabling appropriate control of the overall demand for load devices of higher voltage consumers. Therefore, excess demand suppression relative to the target value can be more appropriately performed.

[0105] (Hardware configuration) 15 is a hardware configuration diagram of the load control device. Here, an example of a hardware configuration for realizing each function of the load control device 10 according to each embodiment will be described with reference to FIG.

[0106] 15, the load control device 10 according to each embodiment includes a CPU (Central Processing Unit) 91, a memory 92, a hard disk 93, and a network interface 94. The CPU 91 is connected to the memory 92, the hard disk 93, and the network interface 94 via a bus.

[0107] The network interface 94 is an interface for communication between the load control device 10 and an external device. The network interface 94 relays communication between the CPU 91 and devices to be controlled, such as the pulse meter 12 and the air conditioner 21, for example.

[0108] The hard disk 93 is an auxiliary storage device. The hard disk 93 stores various programs including programs for realizing the functions of the demand prediction unit 101, the determination unit 102, the tentative control execution unit 103, the output estimation unit 104, and the main control execution unit 15, as illustrated in FIG. 2. The hard disk 93 also stores various programs including programs for realizing the functions of the demand prediction unit 101, the determination unit 102, the tentative control execution unit 103, the output estimation unit 104, the main control execution unit 15, and the correlation function calculation unit 16, as illustrated in FIG. 9. The hard disk 93 also stores various programs including programs for realizing the functions of the demand prediction unit 101, the determination unit 102, the tentative control execution unit 103, the main control execution unit 15, and the actual average reduction amount calculation unit 107, as illustrated in FIG. 11.

[0109] The memory 92 is a main storage device and may be, for example, a dynamic random access memory (DRAM).

[0110] The CPU 91 reads out various programs from the hard disk 93, loads them into the memory 92, and executes them. As a result, the CPU 91 realizes the functions of a demand prediction unit 101, a determination unit 102, a tentative control execution unit 103, an output estimation unit 104, and a main control execution unit 105, which are illustrated in Fig. 2. The CPU 91 also realizes the functions of the demand prediction unit 101, the determination unit 102, the tentative control execution unit 103, the output estimation unit 104, the main control execution unit 105, and a correlation function calculation unit 106, which are illustrated in Fig. 9. The CPU 91 also realizes the functions of the demand prediction unit 101, the determination unit 102, the tentative control execution unit 103, the main control execution unit 105, and a performance average reduction amount calculation unit 107, which are illustrated in Fig. 11. [Explanation of symbols]

[0111] 1 Load Control System 2. Electricity suppliers 10 Load control device 11. Meter for custody 12 Pulse meter 21 Air conditioning equipment 22 Lighting equipment 101 Demand Forecasting Department 102 Judgment section 103 Provisional Control Execution Unit 104 Output Estimation Unit 105 Main control execution unit 106 Correlation function generator 107 Actual average reduction calculation section

Claims

1. a demand prediction unit that predicts an integrated demand of a consumer load including the controlled device for a predetermined period; a determination unit that determines whether or not the integrated demand in a state where the output of the control-target device is not controlled exceeds a target value based on a predicted value of the integrated demand by the demand prediction unit; a first control unit that calculates a first reduction amount that makes the integrated demand after a first control equal to or less than the target value, assuming that the control-target device operates at a rated output, according to a determination result by the determination unit, and performs a first control of the output of the control-target device based on the first reduction amount; a second control unit that calculates a second reduction amount that makes the integrated demand after a second control equal to or less than the target value based on a result of the first control by the first control unit, and performs a second control of an output of the control-target device based on the second reduction amount; A load control device comprising:

2. The load control device according to claim 1, characterized in that the first control unit calculates the first reduction amount based on the difference between the predicted value of the integrated demand in a state where no control is performed and the target value and the rated output.

3. an output estimation unit that calculates an actual reduction amount due to the first control based on information from a meter that measures the output of the consumer load; the demand prediction unit predicts a first integrated demand in a case where the first control is performed, based on the actual reduction amount calculated by the output estimation unit; The second control unit calculates the second reduction amount based on the difference between the first integrated demand and the target value and the rated output.

3. The load control device according to claim 1 or 2.

4. a correlation function generating unit that generates a correlation function representing a relationship between an output of the consumer load during a certain period and the actual reduction amount calculated by the output estimating unit, The demand prediction unit predicts the first integrated demand by acquiring the actual reduction amount corresponding to the output of the consumer load based on the correlation function generated by the correlation function generation unit.

4. The load control device according to claim 3.

5. an actual average reduction amount calculation unit that calculates the output of the consumer load based on information from a meter that measures the output of the consumer load, and calculates an actual average reduction amount, which is an actual reduction amount of the output of the consumer load according to the first reduction amount, based on the output of the consumer load over a certain period of time and the first reduction amount; The second control unit specifies the actual average reduction amount according to a difference between the predicted value of the integrated demand in the case where the control predicted by the demand prediction unit is not performed and the target value, and sets the first reduction amount corresponding to the specified actual average reduction amount as the second reduction amount.

2. The load control device according to claim 1.

6. Forecasting the cumulative demand for a consumer load, including the controlled equipment, for a predetermined period of time; determining whether the integrated demand would exceed a target value if the output of the control-target device were not controlled based on the predicted value of the integrated demand; According to the determination result, assuming that the control-target device operates at a rated output, a first reduction amount is calculated to make the integrated demand after a first control equal to or less than the target value, and a first control is performed on the output of the control-target device based on the first reduction amount; Based on the result of the first control, a second reduction amount is calculated to make the integrated demand after the second control equal to or less than the target value, and the output of the control target device is subjected to a second control based on the second reduction amount. A load control method characterized by causing a computer to execute processing.

7. Forecasting the cumulative demand for a consumer load, including the controlled equipment, for a predetermined period of time; determining whether the integrated demand would exceed a target value if the output of the control-target device were not controlled based on the predicted value of the integrated demand; According to the determination result, assuming that the control-target device operates at a rated output, a first reduction amount is calculated to make the integrated demand after a first control equal to or less than the target value, and a first control is performed on the output of the control-target device based on the first reduction amount; Based on the result of the first control, a second reduction amount is calculated to make the integrated demand after the second control equal to or less than the target value, and the output of the control target device is subjected to a second control based on the second reduction amount. A load control program that causes a computer to execute a process.

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