JP2007206990A - Demand and supply contract value calculation system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To improve overall customer satisfactions as a service provider by suppressing the total sum of losses due to the adjustment of electric energy. <P>SOLUTION: This demand and supply contract value calculation system is provided with a result demand quantity database in which power demand quantity in the past is stored for each demander and a contract content database in which the adjustment rate and discount unit of the electric energy are stored, wherein a discount acquired when the demander makes the adjustment contract of the electric energy and an expected profit as the difference of residual adjustment quantity achievement costs on the demander in the case of adjusting the electric energy are calculated for every generation possibility of the demand quantity. The calculated values are applied to an approximate formula so that a graph can be prepared, and rates at which an expected value is 0 or more and 0 or less are calculated. The demander terminal displays the graph and the calculated result. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a technique for evaluating an effect that a service user enjoys by introducing a service in a service business such as an electric power business.

As a method for evaluating the effect that a service user enjoys by introducing a service, there is, for example, Japanese Patent Application Laid-Open No. 2002-297832. Patent Document 1 discloses a future charge for a resource (service) provided by a service provider from a service user's consumption (usage) and a predicted future consumption calculated based on the consumption. Predict.
Japanese Patent Application Laid-Open No. 2002-296299 (Patent Document 2) sets a charge setting value for each time zone when calculating a power charge for the amount of power used, and sets the charge charge associated with the change of the charge setting value. Calculate changes.

JP 2002-297832 A JP 2002-296299 A

  In the charge simulation in the conventional power service, the charge for using the service is calculated from the power charge menu to be used using the past actual demand data. In addition, the supply and demand adjustment contract is an adjustment method in which the number of contracts is increased / decreased in relation to the total supplyable amount on the power service provider side.

  However, it is actually given to the main business by the profit (discount amount) obtained by entering into a supply-demand adjustment contract, the possibility of achieving power amount adjustment when the amount of power is insufficient, and at the time of adjustment and power outage Losses vary from customer to customer. In addition, the relationship between temperature and power demand varies widely among customers.

  In the charge simulation in the conventional power service, profit loss at the time of power outage that differs depending on each customer is not taken into consideration. For this reason, it has not been able to deal with fine-tuned services such as adjustment of power when the amount of power is insufficient, effective use of resources due to power failure, and calculation of customer's appropriate fee structure.

  The object of the present invention is achieved by the following configurations.

  The present invention has a demand demand database in which the supply and demand contract value calculation system stores a past power demand amount for each consumer, and a contract content database that stores a power amount adjustment ratio and a discount unit price. An expected profit that is the difference between the discount amount obtained when the power amount adjustment contract is made and the residual adjustment amount achievement cost applied to the consumer when the power amount is adjusted is calculated for each occurrence probability of the demand amount. Apply the calculated value to an approximate expression to create a graph, and calculate the ratio of the expected profit between 0 and 0. The graph and the calculated result are displayed on the consumer terminal.

  According to the present invention, the supply / demand adjustment contract has been an adjustment method for increasing / decreasing the number of contracts / contract capacity based on the relationship with the total supplyable amount of the power service provider side. It is possible to recommend a contract to a customer that is easy to introduce, and it is possible to suppress the total loss due to adjustment, and it is possible to improve overall customer satisfaction as a service provider.

  Embodiments of the present invention will be described below in detail with reference to the drawings. FIG. 1 is a diagram illustrating a network configuration example including a supply and demand contract value calculation system according to the present embodiment. The supply and demand contract value calculation system 100 (hereinafter, system 100) of the present invention stores a program 102 stored in a program database 101 such as a rewritable memory in order to realize a function for executing the supply and demand contract value calculation method of the present invention. And executed by the CPU 104 which is an arithmetic unit.

  In addition, the system 100 includes various keyboards 12 and buttons generally provided in a computer device, an input / output interface 105 such as a display 11, a customer terminal 150, past actual demand data 161 and contract content data 162. It has a contract information system 160 that enters, an environmental information system 170 that contains temperature data 171, etc., and a communication device 106 that handles data exchange. The past actual demand data 161, the contract content data 162, and the temperature data 171 are stored in the past actual demand DB 140, the contract content DB 141, and the temperature DB 142 of the supply and demand contract value calculation system 100 via the communication device 106, respectively.

  Next, the structure of the database used by the supply and demand contract value calculation system 100 of this embodiment will be described. FIG. 2A shows a past actual demand amount database 140 storing the demand amount consumed in the past for each consumer. FIG. 2B shows a power service provider contract content database 141 for each consumer. FIG. 2C is a diagram showing each data structure of the past temperature database 142 for each customer.

  In the first embodiment, an example will be described in which the contract value fluctuation range is calculated based on the past actual demand data 140 and the contract content data 141 of the target customers of the supply and demand adjustment contract, and the contract value evaluation is estimated. As a result, consumers can evaluate the validity of the contract based on the variation in the past actual demand data and the remaining adjustment amount, and the power service provider can set the adjustment contract and contract fee setting according to the characteristics of each customer. It becomes possible.

  The processing of the first embodiment will be described based on the processing flowchart of FIG.

  In step 201, the customer information input from the customer terminal 150 is input to the target customer via the input / output device 107 and stored in the memory 103. The customer information includes customer ID, name, address, telephone number, and the like.

  Next, in step 202, the data of the target customer is extracted from the past actual demand database 140 using the customer ID as a key and stored in the memory 103. Here, the date, day of the week, operation day, time, and demand (electric power) are extracted.

  In step 203, the amount of power corresponding to the time for each date is calculated by the demand amount fluctuation range calculation unit 110, and the result is stored in the memory 103. The demand amount fluctuation range calculation unit calculates the maximum power amount, the minimum power amount, and the occurrence probability (frequency) of each demand amount within the demand fluctuation range for the day. Note that the power amount, the maximum / minimum power amount, and the occurrence probability may be calculated for each day of the week.

  In step 204, the contract contents of the target consumer are extracted from the contract contents database 141 using the customer ID as a key and read into the memory 103. Here, for each contract type, the ratio of the electric energy to be adjusted, the period start and end of the contract, and the discount unit price discounted from the cost by the contract are extracted.

  In step 205, the remaining adjustment amount calculation unit calculates the remaining adjustment amount for the portion exceeding the demand amount restricted by the contract from the calculation of the demand amount fluctuation range performed in step 203 and the contract content information performed in step 204. The calculation is performed at 111 and the result is stored in the memory 103. The remaining adjustment amount is the amount of power used exceeding the demand amount restricted by the contract. For example, when the contract power is 500 kW and a -30% adjustment contract is made, 350 kW is the adjustment contract power. In this case, when 380 kW is used exceeding 350 kW, the amount of power exceeding 30 kW is referred to as the remaining adjustment amount.

  In step 206, the demand amount fluctuation range, the contract information, and the remaining adjustment amount in the memory 103 are processed by the output processing unit 130, and the demand / supply adjustment contract suitability analysis screen shown in FIG. In the suitability analysis screen, the vertical axis indicates the electric energy, the horizontal axis indicates the date, and the fluctuation range 301 of the electric energy for each date is displayed. The contract power and each adjusted contract power, for example, −10%, −30%, and −50% are displayed on the horizontal axis. Taking the contract −30% as an example, an amount exceeding −30% is displayed as the remaining adjustment amount 302. From this, the consumer determines whether there is a residual adjustment amount with a contract of -30% and whether adjustment is possible. Further, in the example of contract-10%, it can be determined that there is no power demand exceeding contract-10% and the contract is possible.

  Reference numeral 303 in FIG. 4 indicates a power shortage (amount obtained by adding the remaining adjustment amount 302) and a discount amount when the adjustment contract power from August 15 to August 21 is −30%. Here, the discount amount is calculated by calculating the adjusted amount of demand when the contract is -30% (when the supply power is insufficient, it is calculated with the maximum amount of power supplied). Multiplying the discount unit price. This multiplication method changes so that the unit to be multiplied matches the unit of the discount unit price. Further, the discount amount may vary depending on the contract, and may be determined uniformly according to the contract without depending on the demand amount.

  In step 207, when the amount of power is insufficient from the customer terminal 150, input of such cost information is accepted. This cost is a loss such as a business loss that occurs when the residual adjustment amount is generated to make the residual adjustment amount zero. Here, as shown in the parameter setting screen example of FIG. 5, the cost is expressed in terms of business loss, and the amount 311 per unit of the remaining adjustment amount (power adjustment) is input. Here, an amount 311 per a plurality of remaining adjustment amounts is input. The input information is stored in the memory 103.

  In step 208, the remaining adjustment amount achievement cost calculation is performed by the remaining adjustment amount achievement cost calculation unit 112 from the amount 311 input in step 207 and stored in the memory 103. For example, as shown in the detailed adjustment power cost setting in FIG. 6, an approximate expression is calculated assuming that the remaining adjustment amount achievement cost is proportional to the remaining adjustment amount, and the remaining adjustment amount is achieved in proportion to the remaining adjustment amount. Calculate the cost. In order to increase the accuracy here, it is shown in Japanese Patent Application No. 2005-203980, the title of the invention “Power Supply Adjustment Loss Prediction System, Power Supply Adjustment Loss Prediction Method, Power Supply Adjustment Loss Prediction Program”. It is also possible to calculate the cost using the equipment characteristics as in the method.

  In step 209, based on the discount amount obtained by the contract (a positive factor) (the product of the discount unit price and time in FIG. 2B) and the remaining adjustment amount achievement cost in step 208 (a negative factor), The expected profit calculation unit 113 performs calculation, and the result of the expected profit is stored in the memory 103. The expected profit is calculated by subtracting the residual adjustment amount achievement cost from the discount amount obtained by the contract.

  In step 210, the contracted value fluctuation range calculation unit 116 calculates the result of the expected profit. In this calculation, profit is calculated for each demand amount within the fluctuation range of demand, and the probability (frequency) of each demand is calculated for each calculated profit amount, and the probability distribution of profit is calculated as shown in FIG. And stored in the memory 103. FIG. 7 shows an example in which the totaled result is a normal distribution. Here, the occurrence probability of the demand amount is obtained by extracting the demand amount of the customer from the past actual demand amount DB 140, obtaining the frequency of the demand amount for each certain range, and dividing the frequency by the number of demand amounts extracted. calculate.

  In step 211, based on the result of the calculated contract value fluctuation range, the output processing unit 130 displays the probability distribution screen on the supply and demand adjustment contract value evaluation screen as an example of FIG. The frequency on the vertical axis indicates the probability of occurrence of each demand, and the contract value (yen) on the horizontal axis indicates the amount of expected profit. The contract value of 0 yen means that the cash flow (in: discount amount, out: residual adjustment amount achievement cost) remaining at hand becomes 0 yen by making the contract. The contract value indicates that the larger the right area obtained by integration with respect to 0 yen, the greater the probability that the contract value will be obtained (the cash flow becomes 0 or more). On the contrary, the larger the area on the left side, the more likely it is to lose due to the contract (the cash flow becomes 0 or less). As a result, it is possible to provide a material for determining whether the consumer can make a profit or not by losing the contract.

  Further, when the graph 702 is integrated, the probability that the contract value is 0 or less when the ratio of the area on the left side is 0.25 and the ratio of the area on the right side is 0.75 on the basis of the line where the contract value is 0 yen Is 25%, and the probability of 0 or more is 75%.

  The ratio based on the line where the contract value is 0 yen changes depending on the average and the standard deviation, for example, when the graph has a normal distribution. The graph 701 and the graph 702 are common in that the average value (expected value) of the probability distribution graph is contract value = 2,200,000 yen, but the graph 701 has a smaller variance. In the case of the graph 701, the contract value hardly becomes 0 yen or less. That is, for example, even if the average value is 2,200,000 yen, the ratio is as close as 50% to 50% as long as the distribution is large to the left and right, and conversely if the distribution is small, the ratio is close to 0 to 100. In other words, even if the average (expected value) is 2,200,000 yen, the probability of loss (contract value is 0 yen or less) is 49.999999 ...%, but the probability of loss (contract value is 0 yen or less) is 0.000000 ...% There is also.

  703 of FIG. 7 has shown the result of the value evaluation of the graph 702. FIG. The expected value is the average of the graph, which in this case is 2,200,000 yen. The discount amount obtained by the contract is 3,000,000 yen, and the remaining adjustment achievement cost (loss) is 800,000 yen. And the probability of getting a contract is 75% and the probability of losing is 25%. The consumer can determine whether or not to make a contract from the value shown in 703 and the graph 702.

  Next, by changing the position of the mouse pointer P, it is possible to know the probability of obtaining or losing the contract value (yen) or more indicated by the position of the mouse pointer. The command for changing the position of the mouse pointer is received by the demand-and-supply contract value calculation system 100 from the customer terminal 150 via the input / output device 107. The CPU 104 controls to change the position of the mouse pointer of FIG. 7 displayed on the customer terminal 150 from the output processing unit 130.

  For example, FIG. 7 shows a case where the position of the mouse pointer is 1,000,000 yen. By matching the position of the mouse pointer to 1,000,000 yen, you can know the probability of getting at least 1,000,000 yen and the probability of losing. Reference numeral 704 denotes a result when the position of the mouse pointer is set (changed). When the position (P) of the mouse pointer is 1,000,000 yen, the probability of obtaining 1,000,000 yen or more is 65%, and the probability of being 1,000,000 yen or less is 35%. Customers can use these values in their business strategies.

  Subsequently, as Example 2, in addition to the supply and demand adjustment contract value evaluation as in Example 1, the temperature database 142 of the date corresponding to the past actual demand database 140 is used, and how much the current fiscal year varies from the normal temperature. A function is provided for calculating fluctuations in power demand due to temperature fluctuations and estimating the value of supply and demand adjustment contracts due to fluctuations in temperature.

  Thus, by adding a temperature condition that affects the maximum power demand, the evaluation accuracy of the supply-demand adjustment contract value is further improved, and more detailed judgment materials are provided as to whether or not the consumer should make a contract.

  The processing of the second embodiment will be described based on the processing flowchart of FIG.

  In step 221, the information received from the customer terminal 150 on the parameter input screen 312 in FIG.

  In step 222, using the customer ID already stored in the memory 103 as a key, the past actual demand is read from the past actual demand DB and the temperature corresponding to the past actual demand is read from the temperature database 142 and stored in the memory 103. .

  In step 223, the estimation of power demand fluctuation due to the predicted temperature fluctuation is estimated from the fluctuation information with the predicted temperature input in step 221 and the past actual demand read in step 222 and the corresponding temperature. The demand amount fluctuation range calculation unit 115 performs this. For example, as shown in FIG. 10, the correlation between the air temperature and the demand amount is derived from the past actual demand amount and the corresponding air temperature, and the approximate expression 351 is calculated. When the information on the predicted temperature fluctuation is information that the temperature drops from 28 degrees to 26 degrees, the fluctuation amount of the power demand amount such as the demand amount dropping by 40 kW is calculated from the approximate expression 351 and stored in the memory 103. .

  In step 224, the contract value calculation for the temperature fluctuation is performed by the contract value fluctuation width calculation unit 116 for the temperature fluctuation from the fluctuation amount of the power demand amount due to the temperature fluctuation calculated in step 223, and is stored in the memory 103.

  Specifically, with respect to the demand amount (power amount) in the past actual demand amount DB, addition or subtraction is made by the amount of fluctuation in the power demand amount (for example, when the demand amount is reduced by 40 kW, 40 kW is subtracted from the demand amount). The processing from step 202 to step 210 in the first embodiment is performed with the calculated value.

  In step 225, the contract value with respect to the calculated temperature fluctuation is displayed on the customer terminal 150 from the output processing unit 130 as an example of FIG. In FIG. 9, a contract value probability distribution screen is displayed for a case 341 where there is no temperature fluctuation compared to the normal year and a case 342 where the temperature is two degrees lower than the normal year. As can be seen from this figure, if the temperature drops twice this year, the probability of losing is almost zero and it is considered that the contract is well worth it.

  In this way, by adding the temperature condition, it is possible to compare the value of the supply and demand adjustment contract value with and without the temperature fluctuation, and by adding the temperature condition from the long-term weather forecast this year This will increase the accuracy of the contract value assessment this year, and provide more detailed information on whether or not customers should enter into a contract.

  Subsequently, as a third embodiment, as in the first embodiment, a supply and demand adjustment contract value evaluation is calculated for each contract type, and a function for calculating an optimum contract from the contract value evaluation calculated for each contract type is provided, and the customer is provided with provide.

  As a result, it is possible to determine whether the customer is satisfied with the current contract or whether it is more effective to enter into another contract, and the satisfaction of the consumer is improved.

  The process of Example 3 is demonstrated based on the process flowchart of FIG.

  The processing from step 201 to step 203 performed in the first embodiment is performed in advance, the target consumer is read, and the past actual demand is read and stored in the memory 103. In step 241, all contract type information is read from the contract content database 141 using the customer ID as a key, regardless of whether there is a contract, and stored in the memory 103. The contract types are 50% and 30% for summer operation adjustment contracts, and there are a number of contract types such as August 20th to August 24th and July 23rd to July 27th. N.

  Next, the process from step 205 performed in the first embodiment to contract value fluctuation range calculation in step 210 is performed for each contract. In step 242, it is determined whether or not the contract value fluctuation range of N contract type information has been calculated. If not, the process proceeds to steps 205 to 210. If so, the contract value for each contract type is determined. The result of the fluctuation range is stored in the memory 103, and the process proceeds to step 243.

  In step 243, the optimal contract determination calculation unit 117 calculates the optimal contract determination and stores it in the memory 103. The calculation method uses a calculation formula of C = w1 × C1 + w2 × C2. C1 is the average value of the expected value part in the contract value probability distribution, C2 is the average value of the loss part (part where the contract value is 0 or less) in the contract value probability distribution, and w1 and w2 are weighting factors. .

  The contract value probability distribution screen of FIG. 12 will be described. Here, the distribution of two contracts is shown, and the case of the A contract is indicated by a graph 361 and the case of the B contract is indicated by a graph 365. In the A contract, C1 is 362 and C2 is 363. On the other hand, in the B contract, C1 is 366, and C2 is 367. From these values, the optimum contract value C is obtained using the above formula.

  The optimum contract value C is not higher as the expected value is larger, and is calculated in consideration of the loss. This differs depending on whether the importance value is important or the loss value is important depending on the weighting factor. In the example of FIG. 12, the A contract has a higher expected value than the B contract, but conversely the loss is also greater. When obtaining the optimum contract value C, if the weighting factor of w2 is increased, the optimum contract value of the B contract becomes higher than that of the A contract. For example, 362 of the A contract in FIG. 12 is 4 million yen, 363 is -1.6 million yen, 366 of the B contract is 2 million yen, and 367 is -200,000 yen. Expected value is 4 million yen for A contract and 2 million yen for B contract. However, importance is attached to the loss by the weighting coefficient, and w1 is 1 and w2 is 1.5. In the A contract, the optimum contract value C is 1 × 400 + 1.5 × −160 = 160. In the B contract, the optimal contract value C is 1 × 200 + 1.5 × −20 = 170. From this result, the optimum contract value is higher in the B contract. From now on, the weighting coefficient is determined according to the characteristics of the consumer. These optimum contract values are calculated for N contract types, and the contract types are displayed in descending order of the optimum contract value.

  As a result, the customer can calculate a contract that has not been contracted so far, and can select a contract that matches the consumer. In addition, the power service provider can make adjustment contracts and charge settings according to the characteristics of each consumer, which contributes to improving the satisfaction of consumers.

  The present invention can be applied to a service that presents the value enjoyed from a provided service in a business such as an information communication business, an energy business, and a utility business that is premised on service provision.

It is a figure which shows the network structural example containing the supply-and-demand contract value calculation system of this embodiment. It is a figure which shows each data structure of (a) past performance demand amount database, (b) contract content database, (c) temperature database in this embodiment. It is a figure which shows the main flow example 1 of the supply-and-demand contract value calculation method of this embodiment. It is a figure which shows the example of a screen which presents a supply-and-demand adjustment contract compatibility analysis. It is a figure which shows the example of a screen which performs parameter setting required for a supply-and-demand adjustment contract value. It is a figure which shows the relationship between adjustment electric power and expense. It is a figure which shows the example of a screen which presents supply-and-demand adjustment contract value evaluation. FIG. 10 is a flowchart of processing of Example 2. It is a figure which shows the example of a screen which presents the supply-and-demand adjustment contract value evaluation which added the temperature fluctuation. It is a figure which shows the relationship between a demand amount and temperature. FIG. 10 is a flowchart of processing of Example 3. It is a figure which shows the relationship with the optimal contract determination process of Example 3. FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Supply-and-demand contract value calculation system 101 ... Program database 102 ... Program 103 ... Memory 104 ... CPU
105 ... Input / output interface 106 ... Communication device 107 ... I / O unit 110 ... Demand amount fluctuation range calculation unit 111 ... Remaining adjustment amount calculation unit 112 ... Residual adjustment amount achievement cost calculation unit 113 ... Expected profit calculation unit 114 ... Contract value fluctuation Width calculation unit 115 ... Temperature fluctuation demand amount fluctuation calculation unit 116 ... Temperature fluctuation contract value fluctuation calculation unit 117 ... Optimal contract determination calculation unit 130 ... Output processing unit 140 ... Past actual demand amount database 141 ... Contract content database 142 ... Temperature database 150 ... Customer terminal 151 ... Network 160 ... Contract information system 170 ... Environmental information system

Claims (3)

The actual demand volume database that stores the power demand for each customer for a certain period of time, the adjustment ratio that defines the adjustment power amount that is the maximum value of the supplied power amount, and the adjustment of the power amount by the adjustment ratio A contract content database storing discounted unit price of the power supply and demand contract value calculation system connected to the consumer terminal used by the consumer,
An identifier for identifying the consumer from the consumer terminal, and the amount of cost generated when the residual adjustment amount used exceeding the amount of electricity demand restricted by the contract is set to 0 is at least 2 per unit of the residual adjustment amount. Receiving means for receiving the above,
Extraction means for extracting the power demand (A) from the actual demand database and extracting the adjustment ratio and the discount unit price from the contract content database;
When the power demand amount (A) exceeds the adjustment power amount determined by the adjustment ratio, the difference between the power demand amount (A) and the adjustment power amount is calculated as a residual adjustment amount (A), Calculate the discount amount obtained when the customer makes a contract for adjusting the amount of electricity from the discount unit price,
The residual adjustment amount achievement cost, which is a loss on the consumer when adjusting the amount of electric power, is expressed in the relational expression between the residual adjustment amount achievement cost calculated from two or more of the expenses and the residual adjustment amount (A )
And a calculating means for calculating the expected profit, which is an amount obtained by subtracting the residual adjustment amount achievement cost from the discount amount, for each occurrence probability of the demand amount obtained from the power demand amount (A). Supply / demand contract value calculation system. In the supply-demand contract value calculation system according to claim 1,
The calculation means further calculates an approximate expression of the occurrence probability with respect to the expected profit, and the profit is 0 or more when the estimated profit is 0 or more and 0 or less in the calculated approximate expression. The probability and the probability of being less than or equal to 0 are calculated by integration of the approximate expression,
A supply and demand contract value calculation system, comprising: a transmission means for transmitting the calculated probability to the user terminal. In the supply-demand contract value calculation system according to claim 1,
The contract content database stores a plurality of adjustment ratios and discount unit prices corresponding to each of the adjustment ratios,
The calculation means calculates an average value of the expected profit for each occurrence probability of the demand amount for each adjustment ratio, calculates the result by substituting the calculated average value into a calculation formula, The extraction means further extracts an adjustment ratio for which the largest value is calculated and a discount unit price corresponding to the adjustment ratio from the calculation result.

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