JP7076306B2 - Consumer configuration output device - Google Patents

Description

The present invention is a consumer configuration output device that outputs a consumer configuration that minimizes the adjustment cost required to deal with an error indicating the difference between the actual value representing the power demand and the predicted value representing the result of the prediction for the power demand. Regarding.

Electricity retailers are required to have the same 30-minute planned value for electricity supply and demand in order to stabilize the electric power system. Electricity retailers will be penalized for paying an imbalance fee if they violate the 30-minute planned simultaneous equal amount imposed. For this reason, it is important for electric power retailers to predict electric power demand and accurately supply electric power according to the predicted electric power demand. However, the actual power demand fluctuates from the predicted power demand due to the influence of the weather and the like. Therefore, the electricity retailer must bear the adjustment costs required to deal with the demand forecast error, which indicates the difference between the actual electricity demand and the predicted electricity demand. The adjustment cost includes the cost of procuring electricity to the market, the cost of requesting power saving by demand response, the imbalance fee that must be paid, and the like. The demand forecast error increases or decreases depending on the consumer composition indicating the consumer to which the electric power is supplied from the electric power retailer. For example, if the number of consumers with small daily changes in electricity demand increases, the demand forecast error will decrease, and the adjustment cost required to deal with the demand forecast error will also be suppressed.

In the electric power transaction determination method described in Patent Document 1, an objective function is composed of profit / loss, returns, and penalty terms (paragraph 0024). The objective function includes the amount of power required to supply the consumer (paragraph 0052). Further, a set of consumers whose objective function is maximized and a distribution ratio of each consumer are derived under the constraint equation (claim 1 and paragraph 0027).

Japanese Unexamined Patent Publication No. 2005-352802

When the 30-minute planned value simultaneous equal amount is imposed, the demand forecast error indicating the difference between the actual power demand and the predicted power demand affects the adjustment cost.

However, in the conventional technique represented by the electric power transaction determination method described in Patent Document 1, the electric power demand is taken into consideration, but the demand forecast error is not taken into consideration. Therefore, in the conventional technique, the adjustment cost cannot be calculated quantitatively, and the consumer composition that minimizes the adjustment cost cannot be output.

The present invention has been made in view of this problem. The problem to be solved by the present invention is to provide a consumer configuration output device capable of outputting a consumer configuration that minimizes the adjustment cost required to cope with the difference between the power demand and the result of the prediction. That is.

In the first aspect of the present invention, the consumer configuration output device includes an error calculation unit, a total error calculation unit, an adjustment cost calculation unit, a total prediction value calculation unit, and an update unit.

The error calculation unit shows the difference between the actual value for each time zone that shows the past power demand and the predicted value for each time zone that shows the result of the forecast for the past power demand for each consumer included in multiple consumers. Calculate the band error.

The total error calculation unit calculates the total error for each time zone, which indicates the sum of the errors for each of the two or more time zones calculated for each of the two or more consumers included in the consumer composition.

The adjustment cost calculation unit calculates the total error for each time zone and the adjustment cost required for dealing with the total error for each time zone from the unit price of the adjustment cost for each time zone required for dealing with the unit error.

In the total forecast value calculation unit, the forecast value for each time zone is input for each consumer. The total forecast value calculation unit calculates a total forecast value indicating the sum of two or more time zone-specific forecast values input for each of the two or more consumers.

The updater determines whether the adjustment cost is minimized by including a combination of consumers with opposite errors in two or more consumers within the range where the total predicted value satisfies the constraint. .. Further, the update unit outputs the consumer composition when it is determined that the adjustment cost is minimized. On the other hand, when the update unit determines that the adjustment cost is not minimized, the update unit updates the consumer composition to reduce the adjustment cost.

In the second aspect of the present invention, the consumer configuration output device includes an error calculation unit, an error estimation unit, a total error calculation unit, an adjustment cost calculation unit, a total prediction value calculation unit, and an update unit.

The error calculation unit shows the difference between the actual value for each time zone that shows the past power demand and the predicted value for each time zone that shows the result of the forecast for the past power demand for each consumer included in multiple consumers. Calculate the band error. The actual value for each time zone, the predicted value for each time zone, and the error for each time zone are associated with each condition included in a plurality of conditions.

The error estimation unit identifies a conforming condition that meets a specific condition from a plurality of conditions for each consumer. Further, the error estimation unit estimates the time zone error under a specific condition from the time zone error associated with the conforming condition.

The total error calculation unit calculates the total error for each time zone, which indicates the sum of the errors for each of the two or more time zones estimated for each of the two or more consumers included in the consumer composition.

In the adjustment cost calculation unit, the adjustment cost unit price for each time zone, which is associated with each condition and is required to deal with the unit error, is input. The adjustment cost calculation unit calculates the total error for each time zone and the adjustment cost required for dealing with the total error for each time zone from the unit price of the adjustment cost for each time zone associated with the conforming condition.

The total forecast value calculation unit specifies the forecast value for each time zone associated with the conformity condition for each consumer. In addition, the total forecast value calculation unit calculates a total forecast value indicating the total sum of two or more time zone-specific forecast values specified for each of the two or more consumers.

The updater determines whether the adjustment cost is minimized by including a combination of consumers with opposite errors in two or more consumers within the range where the total predicted value satisfies the constraint. .. Further, the update unit outputs the consumer composition when it is determined that the adjustment cost is minimized. On the other hand, when the update unit determines that the adjustment cost is not minimized, the update unit updates the consumer composition to reduce the adjustment cost.

In the present invention, it is possible to provide a consumer configuration output device that outputs a consumer configuration that minimizes the adjustment cost required to cope with the difference between the power demand and the result of the prediction.

Objectives, features, aspects, and advantages of the present invention will be made clearer by the following detailed description and accompanying drawings.

It is a block diagram which illustrates the hardware of the consumer configuration output device of Embodiments 1, 2 and 3. It is a block diagram which illustrates the consumer composition output device of Embodiment 1. FIG. It is a figure which illustrates the relationship between the data handled in the consumer composition output apparatus of Embodiment 1. FIG. It is a figure which illustrates the table which described the example of the plurality of actual values input to the consumer composition output device of Embodiment 1. FIG. It is a figure which illustrates the table which described the example of the plurality of predicted values input to the consumer composition output apparatus of Embodiment 1. FIG. It is a figure which illustrates the table which described the example of the plurality of errors processed inside the consumer composition output device of Embodiment 1. FIG. FIG. 5 is a diagram illustrating a table in which an example of a consumer configuration processed inside the consumer configuration output device of the first and second embodiments is described. It is a figure which illustrates the table which described the example of the adjustment cost unit price input to the consumer composition output apparatus of Embodiment 1. FIG. It is a figure which illustrates the table which described the example of the constraint parameter input to the consumer composition output device of Embodiments 1 and 2. It is a block diagram which illustrates the consumer composition output device of Embodiment 2. It is a figure which illustrates the relationship between the data handled in the consumer composition output device of Embodiment 2. It is a figure which illustrates the relationship between the data handled in the consumer composition output device of Embodiment 2. It is a figure which illustrates the table which described the example of the plurality of actual values input to the consumer composition output apparatus of Embodiments 2 and 3. It is a figure which illustrates the table which described the example of the plurality of predicted values input to the consumer composition output apparatus of Embodiments 2 and 3. It is a figure which illustrates the condition table which is input to the consumer composition output device of Embodiment 2. It is a figure which illustrates the table which described the example of the plurality of adjustment cost unit price input to the consumer composition output device of Embodiment 2. FIG. 3 is a block diagram illustrating a consumer configuration output device according to the third embodiment. It is a figure which illustrates the relationship between the data handled in the consumer composition output apparatus of Embodiment 3. FIG. FIG. 5 is a diagram illustrating a table in which an example of contracted consumer information input to the consumer configuration output device of the third embodiment is described. It is a figure which illustrates the table which described the example of the uncontracted consumer information input to the consumer composition output device of Embodiment 3.

1 Embodiment 1
1.1 Hardware of the Consumer Configuration Output Device FIG. 1 is a block diagram illustrating the hardware of the consumer configuration output device according to the first embodiment.

The consumer configuration output device 1000 illustrated in FIG. 1 is a computer and includes a CPU 1010, a memory 1012, a hard disk drive 1014, and a communication unit 1016. The consumer configuration output device 1000 may include elements different from these elements.

The program 1020 is installed on the hard disk drive 1014. The CPU 1010 loads the installed program 1020 into the memory 1012 and executes the loaded program 1020. The communication unit 1016 communicates with the smart meter 1040, the server 1042, and the like via the network 1030. The smart meter 1040 is installed in each consumer included in a plurality of consumers.

The hard disk drive 1014 is a recording medium on which the program 1020 is recorded. The recording medium made of the hard disk drive 1014 may be replaced with a recording medium made of a device different from that of the hard disk drive 1014. For example, the recording medium composed of the hard disk drive 1014 may be replaced with the recording medium composed of the solid state drive. The installation of the program 1020 on the hard disk drive 1014 may be performed by writing the program 1020 read from a recording medium such as a compact disc (CD) or a digital multipurpose disk (DVD) on which the program 1020 is recorded to the hard disk drive 1014. Alternatively, it may be performed by writing the program 1020 received via the network 1030 to the hard disk drive 1014.

1.2 Consumer Composition Output Device The consumer composition output device 1000 is a consumer risk analysis that analyzes the profit risk that a consumer composition including two or more consumers to which electricity is supplied poses to an electric power retailer. Consists of part or all of the device. Further, the consumer configuration output device 1000 quantitatively evaluates the difference between the power demand and the result of the prediction for the power demand, and outputs the optimum consumer configuration that minimizes the adjustment cost required to cope with the difference. ..

In the first embodiment, a past error indicating the difference between the past power demand and the result of the prediction for the past power demand is calculated for each consumer. In addition, a total error indicating the sum of the past errors of the two or more calculated for each of the two or more consumers included in the consumer composition is calculated. In addition, the optimum consumer configuration that minimizes the adjustment cost required to deal with the calculated total error is output.

FIG. 2 is a block diagram illustrating a consumer configuration output device according to the first embodiment. FIG. 3 is a diagram illustrating the relationship between the data handled in the consumer configuration output device of the first embodiment.

As shown in FIG. 2, the consumer configuration output device 1000 includes an error calculation unit 1100, a total error calculation unit 1102, an adjustment cost calculation unit 1104, a total prediction value calculation unit 1106, and an update unit 1108. The consumer configuration output device 1000 may include elements different from these elements. These elements are configured by the CPU 1010 executing the program 1020. All or part of these elements may be configured with hardware that does not execute program 1020.

Input information such as a plurality of actual values 1200, a plurality of predicted values 1202, an adjustment cost unit price 1204, and a constraint parameter 1206 are input to the consumer configuration output device 1000. Inside the consumer configuration output device 1000, internal information such as a plurality of errors 1208, consumer configuration 1210, total error 1212, adjustment cost 1214, and total predicted value 1216 is processed. Output information such as the optimum consumer configuration 1218 is output from the consumer configuration output device 1000.

1.3 Error calculation As shown in FIG. 2, a plurality of actual values 1200 and a plurality of predicted values 1202 are input to the error calculation unit 1100. As a result, as shown in FIG. 3, the error calculation unit 1100 is input with the actual value 1312 and the predicted value 1314 for each consumer 1310 included in the plurality of consumers 1300. The actual value 1312 input for each consumer 1310 is an actual value representing the past electric power demand of each consumer 1310, and is a time zone-specific actual value including the actual value in each time zone included in a plurality of time zones. It has become. The predicted value 1314 input for each consumer 1310 is a predicted value representing the result of the prediction for the past power demand of each consumer 1310, and is a time zone including the predicted value in each time zone included in a plurality of time zones. It is another predicted value. The actual value 1312 is measured by the smart meter 1040. The communication unit 1016 may receive the actual value 1312 directly from the smart meter 1040, or may receive the actual value 1312 from the smart meter 1040 via the server 1042.

FIG. 4 is a diagram illustrating a table in which an example of a plurality of actual values input to the consumer configuration output device of the first embodiment is described.

In each row after the second row of the table 1400 illustrated in FIG. 4, a consumer identifier (ID) that identifies the consumer 1310 is described in the first column. Further, after the second column, the actual value 1312 of the consumer 1310 identified by the consumer ID described in the first column is described. In each column after the second column of each row after the second row, the time from the time described in each column of the first row included in the actual value 1312 to the time 30 minutes after the time concerned. The actual value in the band is described. For example, in the second column of the second row, the second row of the first row of the consumer 1310 identified by the consumer ID "1" described in the first column of the second row. The actual value of "0.3" in the time zone from the time of "00:00" to the time of "00:30" described in the column is described. The actual value described is expressed by the amount of electric power. The unit of electric energy is "kWh" or the like.

FIG. 5 is a diagram illustrating an example of a table in which a plurality of predicted values input to the consumer configuration output device of the first embodiment are described.

In each row after the second row of the table 1402 illustrated in FIG. 5, the consumer ID is described in the first column. Further, after the second column, the predicted value 1314 of the consumer 1310 identified by the consumer ID described in the first column is described. In each column after the second column of each row, the actual value in the time zone from the time described in each column of the first row to the time 30 minutes after the time, which is included in the predicted value 1314, is described. Will be done. For example, in the second column of the second row, the second row of the first row of the consumer 1310 identified by the consumer ID "1" described in the first column of the second row. The actual value of "0.2" in the time zone from the time of "00:00" to the time of "00:30" described in the column is described. The actual value described is expressed by the amount of electric power. The unit of electric energy is "kWh" or the like.

Further, as shown in FIG. 3, the error calculation unit 1100 calculates an error 1316 indicating the difference between the input actual value 1312 and the input predicted value 1314 for each consumer 1310. As a result, the error calculation unit 1100 calculates a plurality of errors 1208 as shown in FIGS. 2 and 3. The calculated error 1316 is a time zone-specific error including an error in each time zone included in the plurality of time zones.

FIG. 6 is a diagram illustrating an example of a plurality of errors processed inside the consumer configuration output device of the first embodiment.

In each row after the second row of the table 1404 illustrated in FIG. 6, the consumer ID is described in the first column. Further, after the second column, the error 1316 of the consumer 1310 identified by the consumer ID described in the first column is described. Each column after the second row of each row after the second row has a time zone from the time described in each column of the first row to the time 30 minutes after the time, which is included in the error 1316. The error is described. The error described is expressed in electric energy. The unit of electric energy is "kWh" or the like.

The error Residual (a, ti) in the time zone starting from the time t _i of the consumer a is the actual value Demand (a, t _i ) of the consumer a in the time zone as shown in the equation (1 ₎ . It is calculated by subtracting the predicted value Predict (a, _ti ) of the customer a in the relevant time zone from. The index i is a time zone index, and if the length of each time zone is 30 minutes, each of the integers from 1 to 48 is taken.

1.4 Calculation of total error In the total error calculation unit 1102, the consumer configuration 1210 is input as shown in FIG. The consumer configuration 1210 includes two or more consumers 1320 illustrated in FIG. Two or more consumers 1320 are two or more consumers who are assumed to be power supply destinations.

FIG. 7 is a diagram illustrating a table in which an example of a consumer configuration processed inside the consumer configuration output device of the first embodiment is described.

In each row after the second row of the table 1406 illustrated in FIG. 7, the consumer ID is described in the first column. Further, in the second column, a configuration flag given to the consumer 1310 identified by the consumer ID described in the first column is described. The consumer 1310 to which the configuration flag "1" is given is included in the two or more consumers 1320. Consumers 1310 with the configuration flag "1" are not included in more than one consumer 1320.

Further, as shown in FIG. 3, the total error calculation unit 1102 shows the sum of the two or more errors 1322 calculated for each of the two or more consumers 1320 included in the input consumer configuration 1210. The total error 1212 is calculated. The calculated total error 1212 is a total error for each time zone including the total error in each time zone included in the plurality of time zones.

The total error Total_Residual (S, ti ₎ in the time zone starting from time t _i is, as shown in equation (2), for each consumer a belonging to the set S consisting of two or more consumers 1320. It is calculated by obtaining the error Residual (a, _ti ) in and taking the sum of the two or more errors obtained for each of the two or more consumers belonging to the set S.

1.5 Calculation of adjustment cost The adjustment cost unit price 1204 is input to the adjustment cost calculation unit 1104 as shown in FIG. The input adjustment cost unit price 1204 is an adjustment cost required for dealing with a unit error, and is a time zone-specific adjustment cost unit price including the adjustment cost unit price in each time zone included in a plurality of time zones.

FIG. 8 is a diagram illustrating an example of an adjustment cost unit price input to the consumer configuration output device of the first embodiment.

In the table 1408 illustrated in FIG. 8, the adjustment cost unit price 1204 is described in the second row. In each column of the second row, the adjustment cost unit price in the time zone from the time described in each column of the first row to the time 30 minutes after the time, which is included in the adjustment cost unit price 1204, is described. To. The unit of adjustment cost unit price is "yen / kWh" or the like. When the total error 1212 is dealt with by procuring the electric power to the market, the average value of the past market prices of the electric power in each time zone can be used as the adjustment cost unit price in each time zone. When the total error 1212 is dealt with by paying the imbalance fee, the past average value of the imbalance fee in each time zone can be used as the adjustment cost unit price in each time zone.

Further, as shown in FIGS. 2 and 3, the adjustment cost calculation unit 1104 calculates the calculated total error 1212 and the adjustment cost 1214 required for dealing with the total error 1212 from the input adjustment cost unit price 1204. ..

As shown in Equation (3), the adjustment cost Cost (S) is the adjustment cost unit price Cost_Rate (t _i ) in the time zone starting from time t _i and the total error Total_Residual (S, t) in the time zone. Obtain the product of the absolute value of _i ) | Total_Residual (S, t _i ) |, and take the sum of the multiple products obtained for each time zone starting from multiple times t ₁ , t ₂ , ..., t ₄₈ . It is calculated by.

1.6 Calculation of total forecast value In the total forecast value calculation unit 1106, a consumer configuration 1210 is input as shown in FIG. Further, a plurality of predicted values 1202 are input to the total predicted value calculation unit 1106. As a result, as shown in FIG. 3, the predicted value 1314 is input to the total predicted value calculation unit 1106 for each consumer 1310 included in the plurality of consumers 1300.

Further, as shown in FIG. 3, the total predicted value calculation unit 1106 is a total showing the total of two or more predicted values 1324 input for each of the two or more consumers 1320 included in the consumer configuration 1210. The predicted value 1216 is calculated. The calculated total predicted value 1216 is a total predicted value for each time zone including the total predicted value in each time zone included in the plurality of time zones.

The total predicted value Total_Predict (S, ti ₎ in the time zone starting from time t _i is, as shown in equation (4), for each consumer a belonging to the set S consisting of two or more consumers 1320. It is calculated by obtaining the predicted value Predict (a, _ti ) in the band and summing the two or more predicted values obtained for each of the two or more consumers belonging to the set S.

1.7 Update of consumer configuration Constraint parameter 1206 is input to the update unit 1108 as shown in FIG. The input constraint parameter 1206 is a constraint parameter representing the constraint imposed on the calculated total predicted value 1216, and is a time zone-specific constraint parameter including the constraint parameter in each time zone included in a plurality of time zones. ..

FIG. 9 is a diagram illustrating a table in which an example of constraint parameters input to the consumer configuration output device of the first embodiment is described.

In the table 1410 illustrated in FIG. 9, the constraint parameter 1206 is described in the second row. In each column of the second row, the constraint parameter in the time zone from the time described in each column of the first row to the time 30 minutes after the time, which is included in the constraint parameter 1206, is described. The constraint parameter described is the minimum amount of electricity that the electricity retailer must sell to achieve the desired profit. The unit of electric energy is "kWh" or the like. The lower limit electric energy may be replaced with an upper limit electric energy or a lower limit electric energy different from the lower limit electric energy. For example, the lower limit of electric energy may be replaced with the upper limit of electric energy that can be supplied by the electric power retailer.

Further, the update unit 1108 determines whether or not the calculated adjustment cost 1214 is minimized within the range in which the calculated total predicted value 1216 satisfies the constraint represented by the constraint parameter 1206. When the update unit 1108 determines that the adjustment cost 1214 is minimized, the update unit 1108 outputs the consumer configuration 1210. The output consumer configuration 1210 is the optimum consumer configuration 1218. On the other hand, when the update unit 1108 determines that the adjustment cost 1214 is not minimized, the update unit 1108 updates the consumer configuration 1210 to reduce the adjustment cost 1214. The updated consumer configuration 1210 is input to the total error calculation unit 1102 and the total predicted value calculation unit 1106. As a result, even if the calculated adjustment cost 1214 is not minimized, the adjustment cost 1214 is finally minimized, and the optimum consumer configuration 1218 is output.

In the process of minimizing the adjustment cost 1214, the consumer 1310 with a small error is included in the two or more consumers 1320, and the consumer 1310 with the opposite error is combined with the two or more consumers 1320. Is included. As a result, the total error 1212 from the viewpoint of the electric power retailer can be reduced.

The update unit 1108 determines whether or not the adjustment cost 1214 is minimized by, for example, a particle swarm optimization method, and updates the consumer configuration 1210 to reduce the adjustment cost 1214.

1.8 Effect of Embodiment 1 In Embodiment 1, the consumer configuration output device 1000 is optimized to minimize the adjustment cost 1214 required to cope with the difference between the power demand and the expected result. The consumer configuration 1218 can be output.

2 Embodiment 2
2.1 Differences from Embodiment 1 Embodiment 2 differs from Embodiment 1 mainly in the following points: In Embodiment 1, two or more consumers included in the consumer configuration 1210. A total error 1212 is calculated, which indicates the sum of the two or more past errors 1322 calculated for each 1320. On the other hand, in the second embodiment, a total error indicating the sum of the two or more future errors estimated for each of the two or more consumers included in the consumer composition is calculated.

In the following, the configuration of the second embodiment related to the above difference will be described. The configuration not described will be adopted in the second embodiment as it is or after the configuration adopted in the first embodiment is modified.

2.2 Consumer Configuration Output Device FIG. 1 is also a block diagram illustrating the hardware of the consumer configuration output device according to the second embodiment.

FIG. 10 is a block diagram illustrating a consumer configuration output device according to the second embodiment. 11 and 12 are diagrams illustrating the relationship between the data handled in the consumer configuration output device of the second embodiment.

As shown in FIG. 10, the consumer configuration output device 2000 includes an error calculation unit 2100, an error estimation unit 2102, a total error calculation unit 2104, an adjustment cost calculation unit 2106, a total prediction value calculation unit 2108, and an update unit 2110. Be prepared. These elements are configured by the CPU 1010 executing the program 1020.

The consumer configuration output device 2000 contains input information such as a plurality of actual values 2200, a plurality of predicted values 2202, a condition table 2204, a condition influence degree 2206, a future condition 2208, a plurality of adjustment cost unit prices 2210, and a constraint parameter 2212. Entered. Inside the consumer configuration output device 2000, internal information such as a plurality of errors 2214, a plurality of future errors 2216, a consumer configuration 2218, a total error 2220, an adjustment cost 2222, and a total predicted value 2224 are processed. Output information such as the optimum consumer configuration 2226 is output from the consumer configuration output device 2000.

2.3 Error calculation As shown in FIG. 10, a plurality of actual values 2200 and a plurality of predicted values 2202 are input to the error calculation unit 2100. As a result, as shown in FIG. 11, the error calculation unit 2100 has the actual value associated with each condition 2330 included in the plurality of conditions 2320 for each consumer 2310 included in the plurality of consumers 2300. 2332 and the predicted value 2334 are input. The actual value 2332 input for each consumer 2310 represents the past electric power demand of each consumer 2310, and is a time zone-specific actual value including the actual value in each time zone included in a plurality of time zones. The forecast value 2334 input for each consumer 2310 represents the result of the forecast for the past power demand of each consumer 2310, and is a forecast value for each time zone including the forecast value in each time zone included in a plurality of time zones. It has become. The actual value 2332 is measured by the smart meter 1040. The communication unit 1016 may receive the actual value 2332 directly from the smart meter 1040, or may receive the actual value 2332 from the smart meter 1040 via the server 1042. Each of the plurality of conditions 2320 is identified by a plurality of condition IDs. The plurality of conditions 2320 are conditions that affect the power demand and are considered to affect the plurality of errors 2214 calculated.

FIG. 13 is a diagram illustrating a table in which an example of a plurality of actual values input to the consumer configuration output device of the second embodiment is described.

In each row after the second row of the table 2500 illustrated in FIG. 13, a consumer ID that identifies the consumer 2310 is described in the first column. In addition, the date is described in the second column. Further, a condition ID for identifying the condition 2330 is described in the third column. In addition, after the 4th column, the actual results of the consumer 2310 identified by the consumer ID described in the 1st column are associated with the conditions identified by the condition ID described in the 3rd column. The value 2332 is described. In each column after the fourth column of each row after the second row, the time described in each column of the first row of the date described in the second column of each row included in the actual value 2332. The actual value in the time zone from to the time 30 minutes after the time concerned is described. For example, in the fourth column of the second row, the second row of the second row of the consumer 2310 identified by the consumer ID "1" described in the first column of the second row. The "" in the time zone from the time "00:00" described in the fourth column of the first row of the date "2017/1/1" described in the column to the time "00:30" The actual value of "0.3" is described. The actual value described is expressed by the amount of electric power. The unit of electric energy is "kWh" or the like.

FIG. 14 is a diagram illustrating a table in which examples of a plurality of predicted values input to the consumer configuration output device of the second embodiment are described.

In each row after the second row of the table 2502 illustrated in FIG. 14, the consumer ID is described in the first column. In addition, the date is described in the second column. Further, the condition ID is described in the third column. Further, after the fourth column, the customer 2310 identified by the consumer ID described in the first column is associated with the condition 2330 identified by the condition ID described in the third column. A predicted value of 2334 is described. In each column after the fourth column of each row after the second row, the time described in each column of the first row of the date described in the second column of each row included in the predicted value 2334. The predicted value in the time zone from to the time 30 minutes after the time concerned is described. For example, in the fourth column of the second row, the second row of the second row of the consumer 2310 identified by the consumer ID "1" described in the first column of the second row. The "" in the time zone from the time "00:00" described in the fourth column of the first row of the date "2017/1/1" described in the column to the time "00:30" The actual value of "0.2" is described. The predicted value described is expressed by electric energy. The unit of electric energy is "kWh" or the like.

Further, as shown in FIG. 10, the condition table 2204 is input to the error calculation unit 2100. As shown in FIG. 11, a plurality of conditions 2320 identified by a plurality of condition IDs are described in the input condition table 2204. Each condition 2330 included in the plurality of conditions 2320 includes a plurality of first condition elements 2400 as shown in FIG. The plurality of first conditional elements 2400 are conditional elements that affect the power demand.

FIG. 15 is a diagram illustrating a condition table input to the consumer configuration output device of the second embodiment.

In each row of the condition table 2204 shown in FIG. 15 from the second row onward, the condition ID is described in the first column. In the second and subsequent columns, a plurality of first condition elements 2400 included in the condition 2330 identified by the condition ID described in the first column of each row are described. In the second column, the third column, and the fourth column of each row after the second row, the weather, the temperature, and the day of the week included in the plurality of first conditional elements 2400 are described. For example, in the second column, the third column, and the fourth column of the second row, the weather of "sunny", the temperature of "25", and the day of the week of "month" are described, respectively. Further, in the second column, the third column, and the fourth column of the third row, the weather of "rain", the temperature of "24", and the day of the week of "Saturday" are described, respectively. The unit of air temperature is "℃" or the like.

Further, as shown in FIG. 10, the condition influence degree 2206 is input to the error calculation unit 2100. The input condition influence degree 2206 includes a plurality of condition influence degrees 2402 associated with each of the plurality of first condition elements 2400, as shown in FIG. For example, when the plurality of first condition elements 2400 include the weather, the temperature, and the day of the week, the plurality of condition influence degrees 2402 are associated with the weather-related degree of influence of "10" and the temperature of "3". The degree of influence of "1" and the degree of influence of "1" associated with the day of the week are included.

Further, as shown in FIG. 11, the error calculation unit 2100 is associated with the actual value 2332 and each condition 2330 associated with each condition 2330 for each consumer 2310 included in the plurality of consumers 2300. The difference from the predicted value 2334 is shown, and the error 2336 associated with each condition 2330 is calculated. As a result, a plurality of errors 2214 are calculated as shown in FIGS. 10 and 11. The calculated error 2336 is a time zone-specific error including an error in each time zone included in the plurality of time zones.

The error Residual (a, k, ti) in the time zone starting from the time t _i of the consumer a, which is associated with each condition k, is associated with each condition k as shown in Eq. (5). Also, from the actual value Demand (a, j, ti) of the consumer a in the relevant time zone, the predicted value Predict (a, j, ti ₎ of the consumer a in the relevant time zone associated with each condition _k . ) Is subtracted for each date j, and the error is calculated by averaging the N errors obtained for each of the N dates.

2.4 Calculation of future error Future condition 2208 is input to the error estimation unit 2102 as shown in FIG. The future condition 2208 to be input is a specific condition for a period in which it is desired to reduce the adjustment cost 2222, and as shown in FIG. 12, a plurality of conditions to be compared with the plurality of first condition elements 2400, respectively. Includes a second conditional element of 2410. For example, if the period in which the adjustment cost 2222 is desired to be reduced is the next day and the plurality of first condition elements 2400 include the weather, temperature and day of the week, the plurality of second condition elements 2410 are the next day's weather. , Temperature and day of the week. The next day's weather and temperature will be obtained from the weather forecast.

Further, as shown in FIG. 11, the error estimation unit 2102 specifies a conforming condition 2340 that meets the future condition 2208 from a plurality of conditions 2320 for each consumer 2310. Further, the error estimation unit 2102 estimates a future error 2344 under the future condition 2208 from the error 2342 associated with the conforming condition 2340. The estimated future error 2344 is a future time zone error including a future error in each time zone included in the plurality of time zones. The estimated future error 2344 may be the error 2342 itself associated with the conforming condition 2340, or the error obtained by correcting the error 2342 associated with the conforming condition 2340. You may.

When the plurality of conditions 2320 include a condition that matches the future condition 2208, the error estimation unit 2102 sets the condition that matches the future condition 2208 as the conforming condition 2340.

On the other hand, when the error estimation unit 2102 does not include the condition matching the future condition 2208 in the plurality of conditions 2320, the error estimation unit 2102 sets the condition similar to the future condition 2208 to the conforming condition 2340. Specifically, as shown in FIG. 12, the error estimation unit 2102 has at least one of the first condition elements 2400 to be compared with respect to each condition 2330 included in the plurality of conditions 2320. At least one first condition element 2432 that matches the second condition element 2430 of the above is specified. Further, the error estimation unit 2102 calculates a total of 2436 of at least one condition influence degree 2434 to which at least one specified first condition element 2432 is associated with each condition 2330. Further, the error estimation unit 2102 specifies the conforming condition 2340 in which the sum 2438 calculated for the conforming condition 2340 is the maximum sum in the plurality of sums 2440 calculated for each of the plurality of conditions 2320.

2.5 Calculation of total error In the total error calculation unit 2104, the consumer configuration 2218 is input as shown in FIG. The consumer composition 2218 includes two or more consumers 2350 illustrated in FIG.

The consumer configuration 2218 is the same information as the consumer configuration 1210 processed inside the consumer configuration output device 1000 of the first embodiment. Therefore, FIG. 7 is also a diagram illustrating a table 1406 showing an example of a consumer configuration 2218 processed inside the consumer configuration output device 2000 of Embodiment 2.

Further, as shown in FIG. 11, the total error calculation unit 2104 is the sum of the two or more future errors 2352 estimated for each of the two or more consumers 2350 included in the input consumer configuration 2218. The total error 2220 indicating the above is calculated. The calculated total error 2220 is a total error for each time zone including the total error in each time zone included in the plurality of time zones.

When the conformance condition 2340 is the condition k', the total error Total_Residual (S, k', ti ₎ in the time zone starting from the time t _i is two or more consumers as shown in the equation (6). For each consumer a belonging to the set S consisting of 2350, the error Residual (a, _k ', ti) in the time zone is obtained, and for each of the two or more consumers belonging to the set S, the error of two or more obtained. It is calculated by taking the sum.

2.6 Calculation of adjustment cost As shown in FIG. 10, a plurality of adjustment cost unit prices 2210 are input to the adjustment cost calculation unit 2106. As a result, as shown in FIG. 11, the adjustment cost unit price 2470 associated with each condition 2330 included in the plurality of conditions 2230 is input to the adjustment cost calculation unit 2106. The input adjustment cost unit price 2470 indicates the adjustment cost required for dealing with the unit error, and is the adjustment cost unit price for each time zone including the adjustment cost unit price in each time zone included in the plurality of time zones.

FIG. 16 is a diagram illustrating a table in which an example of a plurality of adjustment cost unit prices input to the consumer configuration output device of the second embodiment is described.

In each row after the second row of the table 2504 illustrated in FIG. 16, the adjustment cost ID that identifies the adjustment cost unit price 2470 is described in the first column. Further, a condition ID for identifying the condition 2330 is described in the second column. Further, after the third column, the adjustment cost unit price 2470 associated with the condition 2330 identified by the condition ID described in the second column is described. In each column after the third column of each row after the second row, from the time described in each column of the first row included in the adjustment cost unit price 2470 to the time 30 minutes after the time. The adjustment cost unit price in the time zone is described. The unit of adjustment cost unit price is "yen / kWh" or the like. When the total error 2220 is dealt with by procuring electric power to the market, the average value of the past market prices of electric power in each time zone can be used as the adjustment cost unit price in each time zone. When the total error 2220 is dealt with by paying the imbalance charge, the past average value of the imbalance charge in each time zone can be used as the adjustment cost unit price in each time zone.

Further, as shown in FIG. 11, the adjustment cost calculation unit 2106 has the calculated total error 2220, and the adjustment cost 2222 required to deal with the total error 2220 from the adjustment cost unit price 2348 associated with the conformity condition 2340. Is calculated.

If the conformance condition 2340 is condition k', the adjustment cost Cost (S, k') is, as shown in equation (7), for the time zone starting from time t _i to the unit error in that time zone. The product of the adjustment cost unit price Cost_Rate (k', ti) required for correspondence and the absolute value of the total error _{Total_Residual} (S, _k ', ti) in the relevant time zone | Total_Residual (S, _k ', ti) | Obtained, calculated by taking the sum of multiple products obtained for each time zone starting from multiple times t ₁ , t ₂ , ..., t ₄₈ .

2.7 Calculation of total forecast value In the total forecast value calculation unit 2108, the consumer configuration 2218 is input as shown in FIG. Further, a plurality of predicted values 2202 are input to the total predicted value calculation unit 2108. As a result, as shown in FIG. 11, the total predicted value calculation unit 2108 is associated with each condition 2330 included in the plurality of conditions 2320 for each consumer 2310 included in the plurality of consumers 2300. The predicted value 2334 is input.

Further, as shown in FIG. 11, the total predicted value calculation unit 2108 specifies the predicted value 2346 associated with the conformity condition 2340 for each consumer 2310.

Further, the total predicted value calculation unit 2108 calculates the total predicted value 2224 indicating the sum of the two or more predicted values 2354 specified for each of the two or more consumers 2350.

When the conformance condition 2340 is the condition k', the total predicted value Total_Predict (S, k', ti ₎ in the time zone starting from the time t _i is the demand for two or more as shown in the equation (8). For each consumer a belonging to the set S consisting of the house 2350, the predicted value Predict (a, _j , ti) in the time zone is obtained, and for each of the two or more consumers belonging to the set S, two or more predictions are obtained. It is calculated by taking the sum of the values and further taking the sum of the N sums taken for each of the N dates.

2.8 Update of consumer configuration Constraint parameter 2212 is input to the update unit 2110 as shown in FIG. The input constraint parameter 2212 is a constraint parameter representing the constraint imposed on the calculated total predicted value 2224, and is a time zone-specific constraint parameter including the constraint parameter at each time included in the plurality of time zones.

The constraint parameter 2212 is the same information as the constraint parameter 1206 input to the consumer configuration output device 1000 of the first embodiment. Therefore, FIG. 9 is also a diagram illustrating a table 1410 showing an example of constraint parameters 2212 input to the consumer configuration output device 2000 of the second embodiment.

Further, the update unit 2110 determines whether or not the calculated adjustment cost 2222 is minimized within the range in which the calculated total predicted value 2224 satisfies the constraint represented by the constraint parameter 2212. When it is determined that the adjustment cost 2222 is minimized, the update unit 2110 outputs the consumer configuration 2218. The output consumer configuration 2218 is the optimum consumer configuration 2226. On the other hand, when the update unit 2110 determines that the adjustment cost 2222 is not minimized, the update unit 2110 updates the consumer configuration 2218 to reduce the adjustment cost 2222. The updated consumer configuration 2218 is input to the total error calculation unit 2104 and the total predicted value calculation unit 2108. As a result, even if the calculated adjustment cost is not minimized, the adjustment cost 2222 is finally minimized, and the optimum consumer configuration 2226 is output.

2.9 Effect of the second embodiment In the second embodiment as well, the consumer configuration output device 2000 is optimized to minimize the adjustment cost 2222 required to cope with the difference between the power demand and the result of the prediction for the power demand. The consumer configuration 2226 can be output.

In addition, in embodiment 2, the consumer configuration output device 2000 can output an optimal consumer configuration 2226 that minimizes the adjustment costs required to accommodate expected future differences.

3 Embodiment 3
3.1 Differences from Embodiment 2 Embodiment 3 differs from Embodiment 2 mainly in the following points: In Embodiment 2, a plurality of predicted values 2202 for each of the plurality of consumers 2300. Is entered. On the other hand, in the third embodiment, a plurality of predicted values are input for each of the plurality of contracted consumers included in the plurality of consumers, and a plurality of uncontracted consumers included in the plurality of consumers are input. The forecast value is estimated from the multiple forecast values entered for each of the existing contracted consumers.

3.2 Consumer Configuration Output Device FIG. 1 is also a block diagram illustrating the hardware of the consumer configuration output device according to the third embodiment.

FIG. 17 is a block diagram illustrating a consumer configuration output device according to the third embodiment. FIG. 18 is a diagram illustrating the relationship between the data handled in the consumer configuration output device of the third embodiment.

As shown in FIG. 17, the consumer configuration output device 3000 includes an error calculation unit 3100, an error estimation unit 3102, a total error calculation unit 3104, an adjustment cost calculation unit 3106, a total prediction value calculation unit 3108, and an update unit 3110. A predicted value estimation unit 3112 is provided. These elements are configured by the CPU 1010 executing the program 1020.

The consumer configuration output device 3000 includes a plurality of actual values 3200, a plurality of predicted values 3202, a condition table 3204, a condition influence degree 3206, a contracted customer information 3208, an uncontracted customer information 3210, an attribute influence degree 3212, and a future. Input information such as the condition 3214, a plurality of adjustment cost unit prices 3216, and the constraint parameter 3218 is input. Inside the consumer configuration output device 3000, internal information such as predicted value 3220, multiple errors 3222, multiple future errors 3224, consumer configuration 3226, total error 3228, adjustment cost 3230, and total predicted value 3232 is processed. Will be done. Output information such as the optimum consumer configuration 3234 is output from the consumer configuration output device 3000. Condition table 3204, Condition impact 3206, Future condition 3214, Multiple adjustment cost unit price 3216, Constraint parameter 3218, Multiple error 3222, Multiple future error 3224, Consumer configuration 3226, Total error 3228, Adjustment cost 3230, Each of the total predicted value 3232 and the optimum consumer configuration 3234 is the same information as the information to which the same name is given, which is handled in the consumer configuration output device 2000 of the second embodiment.

3.3 Actual and predicted values The plurality of consumers 3200 includes a plurality of contracted consumers 3210 and uncontracted consumers 3212 as shown in FIG. A plurality of consumers 3200 may include a plurality of uncontracted consumers. The plurality of existing contracted consumers 3210 are consumers who have already signed a contract to supply electric power by the electric power retailer. The uncontracted consumer 3212 is a consumer who has not yet signed a contract to supply electricity to the electric power retailer.

As shown in FIG. 17, a plurality of actual values 3200 and a plurality of predicted values 3202 are input to the error calculation unit 3100. As a result, for each consumer 3220 included in the plurality of consumers 3200, the actual value associated with each condition included in the plurality of conditions is input to the error calculation unit 3100, and the plurality of contracted consumers 3210 are input. For each contracted consumer 3230 included in, the predicted value associated with each condition included in the plurality of conditions is input.

The plurality of actual values 3200 are the same information as the plurality of actual values 2200 input to the consumer configuration output device 2000 of the second embodiment. Therefore, FIG. 13 is also a diagram illustrating a table 2500 in which examples of a plurality of actual values 3200 input to the consumer configuration output device 3000 of the third embodiment are described. The plurality of consumer IDs described in the table 2500 illustrated in FIG. 13 include a plurality of consumer IDs that individually identify a plurality of contracted consumers 3210, and also include a consumer ID that identifies an uncontracted consumer 3212. include.

The plurality of predicted values 3202 are the same information as the plurality of predicted values 2202 input to the consumer configuration output device 2000 of the second embodiment, except that the predicted values of each contracted consumer 3230 are included. .. Therefore, FIG. 14 is also a diagram illustrating a table 2502 in which examples of a plurality of predicted values 3202 input to the consumer configuration output device 3000 of the third embodiment are described. However, in the third embodiment, the plurality of consumer IDs described in the table 2502 illustrated in FIG. 14 include a plurality of consumer IDs that identify each of the plurality of contracted consumers 3210, but are not contracted. Does not include the consumer ID that identifies the consumer 3212.

Further, as shown in FIG. 17, the error calculation unit 3100 receives the predicted value 3220 associated with each condition included in the plurality of conditions from the predicted value estimation unit 3112 for the uncontracted consumer 3212. To. By inputting the plurality of predicted values 3202 and the predicted value 3220, a plurality of predicted values that can be used in the same manner as the plurality of predicted values 2202 input to the consumer configuration output device 2000 of the second embodiment are input to the error calculation unit 3100. To. Therefore, the error calculation unit 3100 can perform the same processing as the processing performed by the error calculation unit 2100 provided in the consumer configuration output device 2000 of the second embodiment.

3.4 Estimating the predicted value of the uncontracted consumer As shown in FIG. 17, the contracted consumer information 3208 and the uncontracted consumer information 3210 are input to the predicted value estimation unit 3112. As illustrated in FIG. 18, the contracted consumer information 3208 includes a plurality of first attributes 3250 associated with each of the plurality of contracted consumers 3210. The uncontracted consumer information 3210 includes a second attribute 3260 associated with the uncontracted consumer 3212. Each first attribute 3270 included in the plurality of first attributes 3250 comprises a plurality of first attribute elements 3280. The second attribute 3260 includes a plurality of second attribute elements 3290, each of which is compared with a plurality of first attribute elements 3280.

FIG. 19 is a diagram illustrating a table in which an example of contracted consumer information input to the consumer configuration output device of the third embodiment is described.

In each of the second and subsequent rows of the table 3400 illustrated in FIG. 19, a customer ID that identifies the contracted customer 3230 is described in the first column. Further, after the second column, the first attribute 3270 associated with the contracted consumer 3230 identified by the consumer ID described in the first column is described. In the second column, the third column, and the fourth column of each row after the second row, the voltage classification, the facility, and the contract menu included in the first attribute 3270 are described, respectively. For example, in the second column, the third column, and the fourth column of the second row, a voltage category of "low voltage", a facility of "five-person household", and a contract menu of "metered lamp" are described. Has been done. Further, in the second column, the third column, and the fourth column of the third row, a voltage category of "high voltage", a facility of "office", and a contract menu of "day and night" are described, respectively. There is.

FIG. 20 is a diagram illustrating a table in which an example of uncontracted consumer information input to the consumer configuration output device of the third embodiment is described.

In each of the second and subsequent rows of the table 3402 illustrated in FIG. 20, a customer ID that identifies the uncontracted customer 3212 is described in the first column. Further, after the second column, the second attribute 3260 associated with the uncontracted consumer 3212 identified by the consumer ID described in the first column is described. In the second column, the third column, and the fourth column of each row after the second row, the voltage classification, the facility, and the contract menu included in the second attribute 3260 are described, respectively. For example, in the second column, the third column, and the fourth column, a voltage category of "low voltage", a facility of "three-person household", and a contract menu of "metered lamp" are described, respectively. Further, in the second column, the third column, and the fourth column, a voltage category of "high voltage", a facility of "factory", and a contract menu of "metered lamp" are described, respectively.

Further, as shown in FIG. 17, the attribute influence degree 3212 is input to the predicted value estimation unit 3112. The input attribute influence degree 3212 includes a plurality of attribute influence degrees 3300 associated with each of the plurality of first attribute elements 3280, as shown in FIG. For example, when the plurality of first condition elements 3280 include the voltage division and the facility, the plurality of attribute influence degrees 3300 include the influence degree of the voltage classification of "10" and the influence degree of the facility of "3".

Further, the predicted value estimation unit 3112 identifies the conforming attribute 3310 that matches the second attribute 3260 from the plurality of first attributes 3250. Further, the predicted value estimation unit 3112 estimates the predicted value 3220 of the uncontracted customer 3212 from the predicted value 3214 of the contracted consumer 3312 to which the conformity attribute 3310 is associated. Such an estimation is possible because consumers with similar attributes, such as those with behavioral patterns such as similar lifestyles, often have similar power demands.

When the first attribute matching the second attribute 3260 is included in the plurality of first attributes 3250, the predicted value estimation unit 3112 sets the first attribute matching the second attribute 3260 to the matching attribute 3310. do.

On the other hand, when the first attribute matching the second attribute 3260 is not included in the plurality of first attributes 3250, the predicted value estimation unit 3112 conforms the first attribute similar to the second attribute 3260. Attribute 3250. Specifically, as shown in FIG. 18, the predicted value estimation unit 3112 has at least one second attribute to be compared from among a plurality of first attribute elements 3280 for each first attribute 3270. At least one first attribute element 3332 that matches each of the attribute elements 3320 of the above is specified. Further, the predicted value estimation unit 3112 calculates the total 3336 of at least one attribute influence degree 3334 associated with each of the specified at least one first attribute element 3332 for each first attribute 3270. Further, the predicted value estimation unit 3112 specifies the matching attribute 3310 in which the sum 3338 calculated for the matching attribute 3310 is the maximum sum in the plurality of sums 3340 calculated for each of the plurality of first attributes 3250.

3.5 Commonality with the second embodiment The error estimation unit 3102, the total error calculation unit 3104, the adjustment cost calculation unit 3106, the total predicted value calculation unit 3108, and the update unit 3110 each have the consumer configuration of the second embodiment. Performs the same processing as that performed by the element with the same name provided in the output device 2000.

3.6 Effect of Embodiment 3 Also in Embodiment 3, the consumer configuration output device 3000 is optimized to minimize the adjustment cost 3230 required to cope with the difference between the power demand and the expected result. The consumer configuration 3234 can be output. Further, also in the third embodiment, it is possible to output the optimum consumer configuration 3234 that minimizes the adjustment cost 3230 required to cope with the future difference.

In addition, in the third embodiment, it is possible to output the optimum consumer configuration 3224 including the uncontracted consumer 3212 for which the power demand is not predicted.

In the present invention, the embodiments can be appropriately modified or omitted within the scope of the invention.

Although the present invention has been described in detail, the above description is exemplary in all aspects and the invention is not limited thereto. It is understood that innumerable variations not illustrated can be assumed without departing from the scope of the present invention.

1000, 2000, 3000 Consumer configuration output device, 1100, 2100, 3100 Error calculation unit, 1102, 2102, 3104 Total error calculation unit, 1104, 2106, 3106 Adjustment cost calculation unit, 1106, 2108, 3108 Total forecast value calculation unit 1,108,2110 Update unit, 2104 Total error calculation unit, 3102 Error estimation unit, 3112 Predicted value estimation unit.

Claims (11)

For each consumer included in multiple consumers, the error for each time zone showing the difference between the actual value for each time zone showing the past power demand and the predicted value for each time zone showing the result of the forecast for the past power demand. The error calculation unit to be calculated and
A total error calculation unit that calculates the total error for each time zone, which shows the sum of the errors for each of the two or more time zones calculated for each of the two or more consumers included in the consumer composition.
The adjustment cost calculation unit that calculates the adjustment cost required to deal with the total error by time zone from the unit price of the adjustment cost by time zone required to deal with the total error by time zone and the unit error.
The time zone forecast value is input for each of the consumers, and the total forecast value is calculated to indicate the total sum of the two or more time zone forecast values input for each of the two or more consumers. Department and
It is determined whether or not the adjustment cost is minimized by including the consumers having opposite errors in combination with two or more of the consumers within the range where the total predicted value satisfies the constraint. If it is determined that the adjustment cost is minimized, the consumer configuration is output, and if it is determined that the adjustment cost is not minimized, the consumer configuration is updated and the adjustment cost is determined. And the update part that makes
A consumer configuration output device equipped with. For each consumer included in multiple consumers, the actual value for each time zone corresponding to each condition included in multiple conditions and showing the past power demand and the forecast for the past power demand corresponding to each condition An error calculation unit that shows the difference from the predicted value for each time zone that represents the result of, and calculates the error for each time zone associated with each of the above conditions.
For each of the consumers, the conforming condition that meets the specific condition is specified from the plurality of conditions, and the time zone error under the specific condition is estimated from the time zone error associated with the conforming condition. Error estimation unit and
A total error calculation unit that calculates the total error for each time zone, which indicates the sum of the errors for each of the two or more time zones estimated for each of the two or more consumers included in the consumer composition.
The time zone adjustment cost unit price associated with each of the conditions and required to deal with the unit error is input, and the time zone adjustment cost unit price associated with the time zone total error and the conforming condition is used. The adjustment cost calculation unit that calculates the adjustment cost required to deal with the separate total error,
For each of the consumers, the predicted value for each time zone associated with the conforming condition is specified, and for each of the two or more consumers, the total predicted value indicating the sum of the two or more predicted values for each time zone is specified. The total predicted value calculation unit to be calculated and
It is determined whether or not the adjustment cost is minimized by including the consumers having opposite errors in combination with two or more of the consumers within the range where the total predicted value satisfies the constraint. If it is determined that the adjustment cost is minimized, the consumer configuration is output, and if it is determined that the adjustment cost is not minimized, the consumer configuration is updated and the adjustment cost is determined. And the update part that makes
A consumer configuration output device equipped with. The consumer configuration output device according to claim 2, wherein the conforming condition matches the specific condition. Each of the above conditions includes a plurality of first condition elements.
The specific condition includes a plurality of second conditional elements, each of which is compared with the plurality of first conditional elements.
The error estimation unit is
A plurality of conditional influence degrees associated with each of the plurality of first conditional elements are input, and a plurality of conditional influence degrees are input.
For each of the above conditions, at least one first condition element that matches at least one second condition element to be compared is specified from the plurality of first condition elements, and at least one of the first condition elements is specified. Calculate the sum of at least one condition influence degree associated with each of the first condition elements of
The consumer configuration output device according to claim 2, wherein the sum calculated for the conforming conditions is the maximum sum of the plurality of sums calculated for each of the plurality of conditions. The plurality of consumers include a plurality of contracted consumers and uncontracted consumers.
A plurality of first attributes associated with the plurality of contracted consumers and a second attribute associated with the uncontracted consumer are input, and the second attribute is selected from the plurality of first attributes. Further, a predicted value estimation unit that identifies a conforming attribute that matches the attribute of the above and estimates the predicted value for each time zone of the uncontracted customer from the predicted value for each time zone of the contracted consumer to which the conforming attribute is associated. The consumer configuration output device according to any one of claims 1 to 4. The consumer configuration output device according to claim 5, wherein the conforming attribute matches the second attribute. Each first attribute included in the plurality of first attributes includes a plurality of first attribute elements.
The second attribute includes a plurality of second attribute elements to be compared with each of the plurality of first attribute elements.
The predicted value estimation unit is
A plurality of attribute influence degrees associated with each of the plurality of first attribute elements are input.
For each of the first attributes, at least one first attribute element that matches at least one second attribute element to be compared is specified from the plurality of first attribute elements. A plurality of totals of at least one attribute influence degree to which at least one first attribute element is associated with each other are calculated, and the total calculated for the conforming attribute is calculated for each of the plurality of first attributes. The consumer configuration output device according to claim 5, which specifies the conforming attribute that is the maximum sum in the sum. The update unit determines whether or not the adjustment cost is minimized by the particle swarm optimization method, and updates the consumer configuration to reduce the adjustment cost. Any one of claims 1 to 7. Consumer configuration output device. The actual value for each time zone is measured by a smart meter and
The consumer configuration output device according to any one of claims 1 to 8, further comprising a communication unit for receiving the actual value for each time zone. For each consumer included in multiple consumers, the error for each time zone showing the difference between the actual value for each time zone showing the past power demand and the predicted value for each time zone showing the result of the forecast for the past power demand. The error calculation unit to be calculated and
A total error calculation unit that calculates the total error for each time zone, which shows the sum of the errors for each of the two or more time zones calculated for each of the two or more consumers included in the consumer composition.
The adjustment cost calculation unit that calculates the adjustment cost required to deal with the total error by time zone from the unit price of the adjustment cost by time zone required to deal with the total error by time zone and the unit error.
The time zone forecast value is input for each of the consumers, and the total forecast value is calculated to indicate the total sum of the two or more time zone forecast values input for each of the two or more consumers. Department and
It is determined whether or not the adjustment cost is minimized within the range where the total predicted value satisfies the constraint, and if it is determined that the adjustment cost is minimized, the consumer configuration is output and the said. If it is determined that the adjustment cost is not minimized, the update unit that updates the consumer configuration to reduce the adjustment cost, and the update unit.
Equipped with
The update unit is a consumer configuration output device that determines whether or not the adjustment cost is minimized by a particle swarm optimization method, and updates the consumer configuration to reduce the adjustment cost. For each consumer included in multiple consumers, the actual value for each time zone corresponding to each condition included in multiple conditions and showing the past power demand and the forecast for the past power demand corresponding to each condition An error calculation unit that shows the difference from the predicted value for each time zone that represents the result of, and calculates the error for each time zone associated with each of the above conditions.
For each of the consumers, the conforming condition that meets the specific condition is specified from the plurality of conditions, and the time zone error under the specific condition is estimated from the time zone error associated with the conforming condition. Error estimation unit and
A total error calculation unit that calculates the total error for each time zone, which indicates the sum of the errors for each of the two or more time zones estimated for each of the two or more consumers included in the consumer composition.
The time zone adjustment cost unit price associated with each of the conditions and required to deal with the unit error is input, and the time zone adjustment cost unit price associated with the time zone total error and the conforming condition is used. The adjustment cost calculation unit that calculates the adjustment cost required to deal with the separate total error,
For each of the consumers, the predicted value for each time zone associated with the conforming condition is specified, and for each of the two or more consumers, the total predicted value indicating the sum of the two or more predicted values for each time zone is specified. The total predicted value calculation unit to be calculated and
It is determined whether or not the adjustment cost is minimized within the range where the total predicted value satisfies the constraint, and if it is determined that the adjustment cost is minimized, the consumer configuration is output and the said. If it is determined that the adjustment cost is not minimized, the update unit that updates the consumer configuration to reduce the adjustment cost, and the update unit.
Equipped with
The update unit is a consumer configuration output device that determines whether or not the adjustment cost is minimized by a particle swarm optimization method, and updates the consumer configuration to reduce the adjustment cost.

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