Information processor and information processing method

Abstract

To provide an information processor and an information processing method capable of analyzing consumption of energy resources in consideration of characteristics of consumers.SOLUTION: An information processor (100) includes: an index information acquisition part (12) for acquiring information indicating a value of a first index indicating an influence degree of temperature variance on consumption of energy resources of a plurality of demands, information indicating a value of a second index indicating an influence degree of price variance on consumption of energy resources, and information indicating a third index related to purchase amounts of the energy resources, for each of the consumers; a first partition part (13) for partitioning the plurality of consumers into a plurality of groups, on the basis of the value of the first index and the value of the second index acquired by the index information acquisition part (12); and a second partition part (14) for partitioning each of the groups partitioned by the first partition part (13) into one or a plurality of groups on the basis of the value of the third index acquired by the index information acquisition part (12).SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device and an information processing method. [Background technology]

[0002] It has been known that the temperature dependence of energy consumption for energy resources such as electricity, gas, and kerosene has been achieved, and attempts have been made to derive a regression equation showing the relationship between energy consumption and temperature (see, for example, Non-Patent Document 1). [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Kazuhiro Fukushiro and Eriko Iwamoto, "Temperature Dependence of Monthly Energy Consumption in the Residential Sector in Cities in the Kanto and Chubu Regions," Journal of the Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, 33(130), January 2008, pp. 25-32 Summary of the Invention [Problem to be solved by the invention]

[0004] However, since the relationship between the amount of energy resource consumption and temperature generally differs between consumers, there is a problem in that it is difficult to carry out efficient sales activities when sales activities in response to temperature fluctuations are uniformly carried out for multiple consumers based on the technology described in Non-Patent Document 1. For this reason, there is a demand for a device that can classify consumers based on the characteristics related to the amount of energy resource consumption.

[0005] The present disclosure was made in response to the recognition of the above-mentioned problem, and aims to provide an information processing device and an information processing method that can classify consumers based on characteristics related to the consumption of energy resources. [Means for solving the problem]

[0006] The information processing device of the present disclosure is characterized by comprising: an index information acquisition unit that acquires, for each of a plurality of consumers, information indicating the value of a first index that indicates the degree of influence of temperature fluctuations on the consumption of energy resources, information indicating the value of a second index that indicates the degree of influence of price fluctuations on the consumption of energy resources, and information indicating the value of a third index related to the purchase price of the energy resources; a first division unit that divides the plurality of consumers into a plurality of groups based on the value of the first index and the value of the second index acquired by the index information acquisition unit; and a second division unit that divides each group divided by the first division unit into one or more groups based on the value of the third index acquired by the index information acquisition unit. [Effects of the Invention]

[0007] According to the present disclosure, information indicating the value of a first index indicating the degree of influence of temperature fluctuations on the consumption of energy resources, information indicating the value of a second index indicating the degree of influence of price fluctuations on the consumption of energy resources, and information indicating the value of a third index related to the purchase price of the energy resources are obtained, and therefore, based on this obtained information, multiple consumers can be classified according to their characteristics related to the consumption of energy resources. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a schematic configuration of an information processing system according to a first embodiment. [Figure 2] FIG. 2 is a diagram showing an example of a hardware configuration of an information processing device according to the first embodiment. [Figure 3] FIG. 2 is a diagram showing an example of a hardware configuration of an information processing device according to the first embodiment. [Figure 4] 4 is a flowchart showing an example of processing performed by the information processing device according to the first embodiment. [Figure 5] 4 is a scatter diagram showing the result of clustering of consumers by a first division unit of the information processing device according to the first embodiment. [Figure 6] 10 is a table showing a result of clustering of consumers by a first classification unit of the information processing device according to the first embodiment. [Figure 7]6 is a scatter diagram showing the result of clustering of consumers by a second classification unit of the information processing device according to the first embodiment. [Figure 8] 10 is a table showing a result of clustering of consumers by a second sorting unit of the information processing device according to the first embodiment. [Figure 9] 10 is a table showing a result of integrating the results of clustering of consumers by the first sorting unit and the second sorting unit of the information processing device according to the first embodiment. [Figure 10] 3 is a bubble chart displayed on the display device according to the first embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Embodiment 1 FIG. 1 is a block diagram showing a schematic configuration of an information processing system 1 according to the first embodiment. As shown in FIG. 1, the information processing system 1 according to the first embodiment includes a database DB1, an information processing device 100, and a display device 30. The information processing device 100 is a device that classifies a plurality of consumers in order to analyze the amount of LPG consumption according to the characteristics of each consumer. The information processing device 100 is connected to the database DB1, the input device 20, and the display device 30 wirelessly or via a wire so that they can communicate with each other.

[0010] The database DB1 accumulates and stores various types of data. For example, the database DB1 is configured by a data server, and acquires information from a computer (not shown) connected via a communication network and stores the acquired information. For example, the database DB1 stores information indicating the daily consumption of liquefied petroleum (LP) gas as an energy resource for each of multiple consumers to be analyzed, in a manner that makes it possible to identify which consumer's consumption corresponds to the information. For example, the database DB1 is connected via a communication network to smart meters (not shown) installed at each consumer, and acquires information indicating the daily consumption of LP gas for each consumer from each smart meter. Note that in the first embodiment, "LP gas consumption" may also be simply referred to as "gas consumption."

[0011] Furthermore, for example, database DB1 stores weather data for each consumer's location. For example, database DB1 is connected to a server of the Japan Meteorological Agency via the Internet, and acquires weather data for each consumer's location published by the Japan Meteorological Agency. For example, database DB1 stores information on the selling price of LP gas for each consumer's location. For example, database DB1 is connected to a server of the Japan Agency for Natural Resources and Energy via the Internet, and acquires LP gas price survey results published by the Agency for Natural Resources and Energy as information on LP gas selling prices. For example, database DB1 stores data related to economic fluctuations. For example, database DB1 is connected to a server of the Cabinet Office of Japan via the Internet, and acquires information on the Regional Domestic Expenditure Index (hereinafter referred to as "RDEI") published by the Cabinet Office of Japan as data related to economic fluctuations.

[0012] The input device 20 outputs a signal to the information processing device 100, thereby inputting information to be used when the information processing device 100 performs various processes. For example, the input device 20 is configured by a keyboard, a mouse, a touch panel, a microphone, or other device that can input information. The input device 20 accepts an input operation by an operator and outputs a signal according to the input operation to the information processing device 100.

[0013] The display device 30 acquires information from the information processing device 100 and displays the acquired information as visual information by imaging it. For example, the display device 30 is configured with a liquid crystal display panel, an organic or inorganic EL (Electroluminescence) panel, a dot matrix display, or other display devices.

[0014] The information processing device 100 includes a data acquisition unit 11, an index information acquisition unit 12, a first division unit 13, a second division unit 14, a scatter plot generation unit 15, and a display control unit 16. The data acquisition unit 11 acquires data stored in the database DB1 from the database DB1. For example, the data acquisition unit 11 acquires data indicating past gas consumption for each consumer from the database DB1. Furthermore, for example, the data acquisition unit 11 acquires data on past average temperature, humidity, precipitation, atmospheric pressure, and sunshine hours at the location of each consumer as weather data from the database DB1. Furthermore, for example, the data acquisition unit 11 acquires data on past LPG sales prices at the location of each consumer from the database DB1. Furthermore, for example, the data acquisition unit 11 acquires data on past RDEI at the location of each consumer from the database DB1. Note that the data acquisition unit 11 is not limited to acquiring these data as different data for each consumer. For example, if the locations of multiple consumers to be analyzed are located within an area small enough that the differences in the locations of each data item between consumers can be ignored, the data acquisition unit 11 may be configured to acquire these data items as identical data between consumers.

[0015] The index information acquiring unit 12 acquires information indicating the value of a first index indicating the degree of influence of temperature fluctuations on gas consumption and information indicating the value of a second index indicating the degree of influence of price fluctuations on gas consumption for each consumer, based on the data acquired by the data acquiring unit 11. For example, the index information acquiring unit 12 calculates information indicating the value of the first index and information indicating the value of the second index based on a regression model in which the gas consumption for each consumer during a specific past period is used as the objective variable and values ​​related to the price of LP gas and values ​​related to temperature are used as explanatory variables. The index information acquiring unit 12 also acquires information indicating the value of a third index related to the purchase price of LP gas for each consumer. For example, the index information acquiring unit 12 acquires information indicating the cumulative payment amount for LP gas for each consumer during a specific past period as the value of the third index. Details of the processing performed by the index information acquiring unit 12 will be described later.

[0016] The first division unit 13 divides the plurality of consumers into a plurality of groups based on the value of the first index and the value of the second index acquired by the index information acquisition unit 12. In other words, the first division unit 13 divides the plurality of consumers into a plurality of groups, the number of which is smaller than the number of the consumers, based on the value of the first index and the value of the second index acquired by the index information acquisition unit 12. For example, the first division unit 13 divides the plurality of consumers into a plurality of groups (clusters) by clustering the plurality of consumers based on the value of the first index and the value of the second index acquired by the index information acquisition unit 12. Details of the processing performed by the first division unit 13 will be described later.

[0017] The second division unit 14 divides each group divided by the first division unit 13 into one or more groups based on the value of the third index acquired by the index information acquisition unit 12. For example, the second division unit 14 divides each group divided by the first division unit 13 into one or more groups based on the value of the first index, the value of the second index, and the value of the third index acquired by the index information acquisition unit 12. Specifically, the second division unit 14 first divides the multiple consumers into multiple groups (clusters) by clustering the multiple consumers based on the value of the first index, the value of the second index, and the value of the third index acquired by the index information acquisition unit 12. Next, the index information acquisition unit 12 combines the result of the clustering performed based on the value of the first index, the value of the second index, and the value of the third index with the result of dividing the multiple consumers into multiple groups by the first division unit 13, thereby dividing each group divided by the first division unit 13 into one or more groups. Details of the processing performed by the second division unit 14 will be described later.

[0018] The scatter diagram generating unit 15 generates scatter diagram data in which the multiple groups divided by the second dividing unit 14 are arranged in positions according to the value of the third index acquired by the index information acquiring unit 12 and the characteristics of each group divided by the first dividing unit 13. For example, the scatter diagram generating unit 15 generates data as the scatter diagram data for showing each group divided by the second dividing unit 14 as a bubble chart with a size according to the number of consumers included in each group. Details of the data generated by the scatter diagram generating unit 15 will be described later.

[0019] Display control unit 16 controls display device 30 to display an image on display device 30. Specifically, display control unit 16 controls display device 30 based on the data generated by scatter plot generation unit 15 to display a scatter plot on display device 30. Note that display control unit 16 may also cause display device 30 to display an image based on information input from input device 20 in addition to the data generated by scatter plot generation unit 15.

[0020] Next, the hardware configuration of the information processing device 100 will be described with reference to FIGS. 2 and 3. FIG. 2 is a block diagram showing an example of the hardware configuration of the information processing device 100 according to the first embodiment, and FIG. 3 is a block diagram showing an example of the hardware configuration of the information processing device 100 according to the first embodiment, which is different from that shown in FIG. 2. For example, as shown in FIG. 2, the information processing device 100 includes a processor 100a, a memory 100b, and an I / O port 100c, and is configured so that the processor 100a reads and executes a program stored in the memory 100b. The memory 100b may be, for example, a non-volatile or volatile semiconductor memory such as RAM, ROM, flash memory, EPROM, or EEPROM. The memory 100b may also be a magnetic disk, a flexible disk, an optical disk, a compact disk, a minidisk, a DVD, or the like. The memory 100b may also be an HDD or an SSD.

[0021] 3, the information processing device 100 includes a processing circuit 100d and an I / O port 100c, which are dedicated hardware. The processing circuit 100d is configured, for example, by a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a system LSI (Large-Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. Each function of the information processing device 100 is realized by the processor 100a or the processing circuit 100d, which is dedicated hardware, executing a program that is software, firmware, or a combination of software and firmware. The information processing device 100 may also include hardware and circuit elements other than those described above. The information processing device 100 may be configured as a single device, or its functions may be distributed across multiple devices, with each function being realized through the cooperation of these multiple devices.

[0022] Next, with reference to FIGS. 4 to 10, a process performed by the information processing device 100 according to the first embodiment will be described. FIG. 4 is a flowchart illustrating an example of a process performed by the information processing device 100 according to the first embodiment. The process performed by the information processing device 100 illustrated in FIG. 4 is a process for classifying a plurality of consumers based on information acquired by the data acquisition unit 11 and displaying a bubble chart on the display device 30 based on the classification results. As illustrated in FIG. 4, when the process starts, the information processing device 100 first acquires various data from the database DB1 (step ST01). In this process, the information processing device 100 acquires various data used in the process from the database DB1. For example, in this process, the information processing device 100 acquires, from the database DB1, data on daily gas usage for each consumer over the past year, data on average daily temperature, humidity, precipitation, atmospheric pressure, and sunshine hours for each consumer's location over the past year, data on monthly LPG sales prices for each consumer's location over the past year, and data on RDEI for each consumer's location over the past year.

[0023] After performing the processing of step ST01, the information processing device 100 acquires the values ​​of the first index, the second index, and the third index for each consumer (step ST02). In this processing, the information processing device 100 calculates, for each consumer, information indicating the value of the first index indicating the degree of influence of temperature fluctuations on gas consumption and information indicating the value of the second index indicating the degree of influence of price fluctuations on gas consumption, based on the data acquired by the data acquisition unit 11, using the index information acquisition unit 12.

[0024] For example, in the processing of step ST02, the index information acquisition unit 12 first calculates the heating degree-days hdd at the location of each consumer based on the data acquired by the data acquisition unit 11. The heating degree-days hdd is calculated, for example, by the following formula (1) using a reference temperature of 16°C. TIFF2025162589000002.tif25166

[0025] Next, in the processing of step ST02, the index information acquisition unit 12 acquires information indicating the cumulative amount of LP gas paid for each consumer over the past year as the value of the third index related to the LP gas purchase amount, based on the daily gas usage amount for each consumer over the past year and the monthly LP gas sales price data for each consumer's location over the past year. Note that in the first embodiment, the "cumulative amount of LP gas paid for each consumer over the past year" is also simply referred to as the "cumulative payment amount."

[0026] Next, in the processing of step ST02, the index information acquisition unit 12 calculates monthly data for each data based on the daily data among the acquired data. For example, the index information acquisition unit 12 calculates the past monthly gas usage for each consumer by summing up the acquired daily gas usage for each consumer over the past year for each month. Also, for example, the index information acquisition unit 12 calculates the monthly air pressure data for each consumer over the past year at their residence by calculating the monthly average value of the acquired daily air pressure data for each consumer over the past year at their residence.

[0027] Next, in the processing of step ST02, the index information acquisition unit 12 calculates the monthly sunshine rate for the past year at the residence of each consumer based on the acquired data on the sunshine hours for the past year at the residence of each consumer. The sunshine rate is calculated using the following formula (2). (Sunshine rate)=(Sunshine hours)×100 / (Sunshine hours) ···(2)

[0028] Next, in the processing of step ST02, the index information acquisition unit 12 calculates information indicating the value of a first index and information indicating the value of a second index, with the monthly gas consumption amount for each consumer over the past year as the dependent variable. For example, the index information acquisition unit 12 calculates information indicating the value of the first index and information indicating the value of the second index based on a regression model with the monthly gas consumption amount for each consumer over the past year as the dependent variable and a value indicating LPG price fluctuations for each consumer over the past year, a value indicating climate change for each consumer over the past year, and a value indicating economic fluctuations as explanatory variables. The following formula (3) is an example of a regression model used by the index information acquisition unit 12 to calculate the information indicating the value of the first index and the information indicating the value of the second index. ln(Q i,t )=β0+β p ×∂p r,t +β w ×ln(w r,t )+β e ×e r,t + m i +u i,t ···(3)

[0029] In equation (3), i is an identifier for each consumer, r is a value indicating the regional variation that varies depending on the location of each consumer, t is a value indicating the month, and Q i,t is the gas consumption per customer, β0, β p , β w and β e is the matrix of regression coefficients, ∂p r,t is a vector showing the price difference between the previous month and the current month, and w r,t is a vector of climate variables, e, which represents the HDD, humidity, precipitation, atmospheric pressure, sunshine hours and sunshine rate. r,t is the value indicating the economic fluctuations indicated by RDEI, m i is a value that indicates the unobserved effect specific to the consumer, u i,t are the values ​​that indicate the specific errors specific to the consumer. r,t is a value that fluctuates depending on the price of LPG, so it is a price-related value, and the climate change value w r,tSince r is a value that varies depending on the HDD, it can be considered a value related to temperature. In addition, the regional variation value r can be treated as a constant value if the locations of the multiple consumers being analyzed are located within a small enough area that the differences in the locations of each data point between consumers can be ignored.

[0030] In the process of step ST02, the index information acquisition unit 12 acquires, for example, a regression coefficient β as information on the value of the first index indicating the degree of influence of temperature fluctuations on the gas consumption amount in the regression model shown in Equation (3). w The information showing the components related to the HDD is obtained, and the regression coefficient β is used as information on the value of the second index showing the impact of price fluctuations on gas consumption. p In other words, in the process of step ST02, the index information acquiring unit 12 acquires information indicating the value of the first index indicating the temperature dependency of the gas consumption amount. w The information showing the components related to the HDD is obtained, and the value of the second index showing the price dependency on gas consumption is calculated as β p In other words, in the processing of step ST02, the index information acquisition unit 12 acquires information indicating the value of the first index and information indicating the value of the second index based on the regression coefficients in a regression model in which the gas consumption amount for each consumer is used as the objective variable and the value related to the price of LPG and the value related to the temperature are used as explanatory variables. Note that in the first embodiment, β w The components related to the HDD are temperature sensitivity, β p The value of is also called price sensitivity.

[0031] As described above, in the processing of step ST02, the index information acquisition unit 12 acquires information indicating temperature sensitivity and price sensitivity as characteristics related to gas consumption for each consumer. Note that the first index and second index acquired by the index information acquisition unit are not limited to the temperature sensitivity and price sensitivity described above. The first index and second index acquired by the index information acquisition unit may be an index indicating the degree of influence of temperature fluctuations on gas consumption and an index indicating the degree of influence of price fluctuations on gas consumption, respectively, and various indexes calculated based on the relationship between gas consumption, temperature, and the price of LP gas are conceivable.

[0032] After performing the processing of step ST02, the information processing device 100 clusters the multiple consumers into a first number of groups, which is less than the number of the multiple consumers, based on the values ​​of the first index and the second index (step ST03). In other words, the information processing device 100 classifies the multiple consumers into multiple groups by performing a first clustering based on the values ​​of the first index and the second index. For example, the information processing device 100 clusters the multiple consumers based on two-dimensional data consisting of temperature sensitivity and price sensitivity acquired for each consumer in the processing of step ST02. For example, in this processing, the information processing device 100 clusters the multiple consumers using the first classification unit 13 by using a known clustering method such as the k-means algorithm or the x-means algorithm. As a result, the information processing device 100 classifies the multiple consumers according to their characteristics based on the temperature dependency of gas consumption and the price dependency of gas consumption.

[0033] Fig. 5 is a scatter diagram showing the result of clustering of consumers by the first division unit 13 of the information processing device 100 according to the first embodiment. Fig. 5 is a scatter diagram in which each consumer is plotted on a two-dimensional plane with the temperature sensitivity of each consumer acquired in the processing of step ST02 on the X axis and the price sensitivity on the Y axis, and shows a state in which the consumers are clustered into three groups: consumers indicated by x's, consumers indicated by circles, and consumers indicated by triangles. Fig. 6 is a table showing the result of clustering of consumers by the first division unit 13 of the information processing device 100 according to the first embodiment.

[0034] As shown in Figures 5 and 6, for example, if multiple consumers are clustered and the characteristics of each group show significant differences in the degree to which temperature fluctuations affect gas consumption, then based on the differences in each group's tendency toward temperature sensitivity, consumers in the group indicated by an X and with cluster ID A can be treated as a temperature-insensitive layer whose gas consumption is little affected by temperature fluctuations, consumers in the group indicated by a triangle and with cluster ID B can be treated as a temperature-sensitive layer whose gas consumption is greatly affected by temperature fluctuations, and consumers in the group indicated by a circle and with cluster ID C can be treated as an intermediate response layer whose degree of influence of temperature fluctuations on gas consumption is between that of the temperature-insensitive layer and the temperature-sensitive layer.

[0035] After performing the processing of step ST03, the information processing device 100 clusters the multiple consumers into a second number of groups, the number of groups being smaller than the number of the multiple consumers, based on the values ​​of the first index, the second index, and the third index (step ST04). In other words, the information processing device 100 classifies the multiple consumers into multiple groups by performing a second clustering based on the values ​​of the first index, the second index, and the third index. For example, the information processing device 100 clusters the multiple consumers based on three-dimensional data consisting of the temperature sensitivity, price sensitivity, and cumulative payment amount acquired for each consumer in the processing of step ST02. For example, in this processing, the information processing device 100 clusters the multiple consumers using a known clustering method such as the k-means algorithm or the x-means algorithm using the second classification unit 14.

[0036] FIG. 7 is a scatter diagram showing the results of clustering of consumers by the second division unit 14 of the information processing device 100 according to the first embodiment. FIG. 7 is a scatter diagram in which each consumer is plotted in a three-dimensional space, with the temperature sensitivity of each consumer acquired in the processing of step ST02 on the X axis, the price sensitivity on the Y axis, and the cumulative payment amount on the Z axis. The scatter diagram shows a state in which the consumers are clustered into four groups: consumers indicated by crosses, consumers indicated by circles, consumers indicated by triangles, and consumers indicated by squares. FIG. 8 is a table showing the results of clustering of consumers by the second division unit 14 of the information processing device 100 according to the first embodiment. As shown in FIGS. 7 and 8, for example, as a result of clustering multiple consumers, the multiple consumers are classified into a group of consumers indicated by crosses and having a cluster ID of 1, a group of consumers indicated by triangles and having a cluster ID of 2, a group of consumers indicated by circles and having a cluster ID of 3, and a group of consumers indicated by squares, based on the differences in the tendency of each group to temperature sensitivity.

[0037] Next, in the processing of step ST04, the second partitioning unit 14 integrates the result of the clustering (first clustering) by the first partitioning unit 13 and the result of the clustering (second clustering) by the second partitioning unit 14. Specifically, each group partitioned by the clustering by the first partitioning unit 13 is further partitioned into multiple groups based on the result of the clustering by the second partitioning unit 14.

[0038] 9 is a table showing a result of integrating the results of clustering of consumers by the first division unit 13 and the second division unit 14 of the information processing device 100 according to the first embodiment. As shown in FIG. 9, the second division unit 14 further divides each of the three groups with cluster IDs A to C, into which multiple consumers have been divided by the first clustering, into four groups with cluster IDs 1 to 4, into which multiple consumers have been divided by the second clustering, thereby generating a total of 12 groups (clusters) with group IDs 1 to 12. For example, the second division unit 14 further divides each of the groups of the temperature insensitive layer, the intermediate reaction layer, and the temperature sensitive layer, into which multiple consumers have been divided by the first clustering, into four groups into which multiple consumers have been divided by the second clustering.

[0039] After performing the process of step ST04, the information processing device 100 generates a bubble chart that visualizes the clustering result based on the clustering result (step ST05). In other words, in this process, the information processing device 100 generates bubble chart data as a scatter plot that visualizes the clustering result based on the clustering result.

[0040] After performing the process of step ST05, information processing device 100 displays a bubble chart (step ST05). In this process, information processing device 100 outputs a signal based on the data of the bubble chart generated by scatter plot generating unit 15 from display control unit 16 to display device 30, thereby causing display device 30 to display the bubble chart.

[0041] Fig. 10 is a bubble chart displayed on the display device 30 according to the first embodiment. The bubble chart shown in Fig. 10 is a scatter plot in which a plurality of groups with group IDs from 1 to 12, which have been divided by the second division unit 14, are arranged at positions corresponding to the value of the cumulative payment amount acquired by the index information acquisition unit 12 and the characteristics of each group divided by the first division unit 13. Specifically, the bubble chart shown in Fig. 10 is a scatter plot in which a plurality of groups with group IDs from 1 to 12, which have been divided by the second division unit 14, are arranged at positions corresponding to the value of the cumulative payment amount acquired by the index information acquisition unit 12 and any one of the groups divided by the first division unit 13, namely, the temperature insensitive layer, the intermediate reaction layer, and the temperature sensitive layer.

[0042] The information processing device 100 may be configured to label each group divided by the first dividing unit 13 as a temperature insensitive group, an intermediate response group, or a temperature sensitive group based on an input operation by the operator of the input device 20, or may be configured to label each group by selecting a label corresponding to the characteristics of each group from a plurality of preset labels. The labels assigned to each group divided by the first dividing unit 13 are not limited to those described above. For example, if the characteristics of each group divided by the first dividing unit 13 are such that there is a significant difference in the degree of influence of price fluctuations on gas consumption, the labels assigned to each group divided by the first dividing unit 13 may be a price insensitive group whose gas consumption is less influenced by price fluctuations, a price sensitive group whose gas consumption is more influenced by price fluctuations, or an intermediate response group whose gas consumption is influenced by price fluctuations to a degree between the price insensitive group and the price sensitive group. The number of divided groups may be other than three, and various labels may be assigned to each group according to the differences in characteristics between the groups.

[0043] In addition, the bubble chart shown in Figure 10 shows each group with group IDs from 1 to 12 divided by the second division unit 14, with the size corresponding to the number of consumers included in each group, and the a in ``Ga, b'' written in the center of the bubble indicates the group ID and b indicates the number of consumers included in the group.

[0044] For example, the bubble chart shown in FIG. 10 indicates that consumers classified as the temperature-insensitive group are divided into four groups, groups 1 to 4, based on their cumulative payment amounts, and that the numbers of consumers included in each group are 53, 72, 34, and 7. Also, for example, the bubble chart shown in FIG. 10 indicates that consumers classified as the intermediate-response group are divided into four groups, groups 5 to 8, based on their cumulative payment amounts, and that the numbers of consumers included in each group are 65, 82, 21, and 5. Also, for example, the bubble chart shown in FIG. 10 indicates that consumers classified as the temperature-sensitive group are divided into two groups, groups 9 and 10, based on their cumulative payment amounts, and that the numbers of consumers included in each group are 13 and 11. This indicates that there were no consumers in the temperature-sensitive group whose cluster IDs were 3 and 4, as determined by the second clustering, i.e., no consumers included in groups 11 and 12.

[0045] In this way, the second division unit 14 is not limited to dividing all groups into which multiple consumers were divided by the first clustering into the same number of groups as divided by the second clustering, but may be configured to divide each group into which multiple consumers were divided by the first clustering into one or more groups in cases where there are no corresponding consumers, etc. The information processing device 100 according to the first embodiment divides multiple consumers and displays a bubble chart on the display device 30 based on the division results, thereby visualizing the characteristics related to gas consumption for each consumer and facilitating the analysis of the consumer characteristics.

[0046] As described above, the information processing device 100 according to the first embodiment includes an index information acquisition unit 12 that acquires, for each of a plurality of consumers, information indicating a value of a first index indicating the degree of influence of temperature fluctuations on gas consumption, information indicating a value of a second index indicating the degree of influence of price fluctuations on gas consumption, and information indicating a value of a third index related to the purchase price of LPG; a first division unit 13 that divides the plurality of consumers into a plurality of groups based on the value of the first index and the value of the second index acquired by the index information acquisition unit 12; and a second division unit 14 that divides each group divided by the first division unit 13 into one or more groups based on the value of the third index acquired by the index information acquisition unit 12. With this configuration, the information processing device 100 according to the first embodiment can classify the plurality of consumers according to their characteristics related to gas consumption based on the information acquired by the index information acquisition unit 12. Furthermore, by classifying the plurality of consumers in this manner, the information processing device 100 according to the first embodiment can analyze the characteristics of the consumers related to gas consumption.

[0047] Furthermore, the information processing device 100 according to the first embodiment includes a forecast information acquisition unit that acquires at least one of temperature forecast information and energy resource price forecast information. This enables the information processing device 100 to predict the energy resource consumption of each consumer based on the results of segmenting the multiple consumers and at least one of the temperature forecast information and the energy resource price forecast information. For example, the information processing device 100 can predict that the gas consumption of consumers in the temperature-sensitive segment in the winter of the current year will be higher than the gas consumption of consumers in the winter of the previous year by acquiring, via the data acquisition unit 11, temperature forecast information indicating that the temperature in the winter of the current year will be lower than the temperature in the winter of the previous year. Furthermore, for example, the information processing device 100 can predict that the gas consumption of consumers in the price-sensitive segment in the current year will be lower than the gas consumption of consumers in the winter of the previous year by acquiring, via the data acquisition unit 11, LPG price forecast information indicating that the price of LPG in the current year will be higher than the price of LPG in the previous year. The information processing device may include a prediction unit that performs such predictions.

[0048] Furthermore, the information processing device 100 according to the first embodiment includes a prediction information acquisition unit that acquires temperature prediction information and energy resource price prediction information, thereby making it possible to predict the energy resource consumption of each consumer based on the values ​​of the first and second indexes, the temperature prediction information, and the energy resource price prediction information. For example, the information processing device 100 acquires next year's temperature prediction information and next year's LP gas price prediction information using the data acquisition unit 11, thereby making it possible to predict each consumer's gas consumption by a regression model using the values ​​of the first and second indexes of each consumer, with the temperature and LP gas price as explanatory variables and the gas consumption as a response variable. The information processing device may include a prediction unit that makes such predictions.

[0049] Furthermore, the information processing device 100 according to the first embodiment includes a scatter diagram generation unit 15 that generates scatter diagram data in which the multiple groups divided by the second division unit 14 are arranged in positions according to the value of the third index acquired by the index information acquisition unit 12 and the characteristics of each group divided by the first division unit 13. Configured in this way, the information processing device 100 according to the first embodiment makes it possible to visualize the characteristics of the multiple divided consumers based on the results of dividing the multiple consumers according to their characteristics related to gas consumption, and makes it easy to analyze the characteristics of the consumers related to gas consumption.

[0050] Furthermore, the information processing device 100 according to the first embodiment is configured to generate data for displaying, as scatter plot data, each group divided by the second division unit 14 as a bubble chart with a size corresponding to the number of consumers included in each group. Configured in this way, the information processing device 100 according to the first embodiment makes it possible to visualize the characteristics of the divided multiple consumers and the number of consumers included in each group, making it easier to analyze the characteristics of consumers regarding gas consumption.

[0051] The following is an example of an analysis that allows gas utilities to conduct sales activities tailored to the characteristics of each customer by categorizing LPG consumers. For example, in the bubble chart shown in Figure 10, consumers with group IDs 3 and 4, who are classified as temperature-insensitive consumers and have relatively large cumulative payments, can be inferred to be business users of LPG. Such business users are consumers whose gas consumption is less affected by temperature changes and who generate stable, high sales for gas utilities. New contracts and contract changes with such consumers have a significant impact on the gas business, so aggressive sales are desirable. Furthermore, in the bubble chart shown in Figure 10, consumers with group IDs 1 and 2, who are classified as temperature-insensitive consumers and have relatively small cumulative payments, can be inferred to be general household users of LPG. Furthermore, by offering convenient gas appliances to consumers with group IDs 1 to 4, who are classified as temperature-insensitive consumers, these consumers are likely to purchase new gas appliances.

[0052] Furthermore, for example, in the bubble chart shown in Figure 10, it can be inferred that consumers with group IDs 9 and 10, who are included in the temperature-sensitive group and have relatively small cumulative payments, are general households and are frugal consumers who reduce their gas usage outside of winter. By appealing to such consumers that using gas outside of winter will improve their quality of life, it will be possible to create new gas demand among these consumers.

[0053] Furthermore, in the bubble chart shown in Figure 10, there were no customers who were classified as temperature-sensitive and had relatively large maximum payments, but if there were such customers, interviewing them about the reasons why they are susceptible to temperature changes could serve as an opportunity to generate new demand. Gas companies can approach each customer based on this analysis and conduct effective sales activities.

[0054] In the first embodiment, the information processing device 100 is configured to classify LP gas consumers, but the energy resource handled by the information processing device is not limited to LP gas. The information processing device may be configured to classify energy resource consumers, for example, it may be configured to classify city gas consumers, or it may be configured to classify consumers of energy resources such as electricity or kerosene, or it may be configured to classify consumers of multiple energy resources among these energy resources. When the information processing device is configured in this way, the index information acquisition unit acquires, for each consumer, information indicating the value of a first index indicating the degree of influence of temperature fluctuations on the consumption of the target energy resource, information indicating the value of a second index indicating the degree of influence of price fluctuations on the consumption of the energy resource, and a third index related to the purchase price of the energy resource, based on the data acquired by the data acquisition unit.

[0055] Furthermore, in the first embodiment, the second partitioning unit 14 is configured to partition each group partitioned by the first partitioning unit 13 into one or more groups based on the value of the first index, the value of the second index, and the value of the third index acquired by the index information acquisition unit 12, but is not limited to this. The second partitioning unit may be configured to partition each group partitioned by the first partitioning unit into one or more groups based on at least the value of the third index acquired by the index information acquisition unit, and may be configured to partition each group partitioned by the first partitioning unit into one or more groups based only on the magnitude of the value of the third index, or may be configured to partition into one or more groups based on the value of either the first index or the second index and the value of the third index. Specifically, the second division unit may be configured to divide each group divided by the first division unit based on whether the value of the third index of each consumer is less than or greater than one or more predetermined threshold values, or may be configured to divide each group divided by the first division unit into one or more groups by clustering these groups based on the value of either the first index or the second index and the value of the third index.

[0056] Furthermore, in the first embodiment, the information processing device 100 is configured to generate data for displaying each group divided by the second division unit 14 as a bubble chart, with the size of the bubble chart indicating the number of consumers included in each group, but is not limited to this. The information processing device may be configured to generate data for visualizing the multiple groups divided by the second division unit and the characteristics of each group. For example, the information processing device may generate scatter plot data, in which the multiple groups divided by the second division unit are arranged at positions according to the value of the third index acquired by the index information acquisition unit and the characteristics of each group divided by the first division unit, as three-dimensional graph data, and may be configured to indicate the number of consumers included in each group by the length of the three-dimensional bar graph, or may be configured to indicate the number of consumers included in each group numerically, or may be configured to indicate the number of consumers included in each group by different colors. Various visualization modes are possible.

[0057] Furthermore, in the first embodiment, the information processing device 100 is configured to acquire data used to classify multiple consumers from the database DB1, but is not limited to this. For example, the information processing device may be configured to acquire data used to classify multiple consumers from a storage device (not shown) included in the information processing device, the data being stored in the storage device, or the information processing device may be configured to acquire data directly from each smart meter and a government server, or may be configured to acquire data based on input information from an input device, and there may be multiple sources for obtaining various data for the information processing device.

[0058] In addition, in the present disclosure, any component of the embodiments may be modified or any component of the embodiments may be omitted. [Explanation of symbols]

[0059] 1: Information processing system 11: Data acquisition section 12: Index information acquisition section 13: 1st section 14:Second section 15: Scatter plot generation section 16: Display control section 20: Input device 30:Display device 100: Information processing device DB1 : Database

Claims

1. an index information acquisition unit that acquires, for each of a plurality of consumers, information indicating the value of a first index that indicates the degree of influence of temperature fluctuations on the consumption of energy resources, information indicating the value of a second index that indicates the degree of influence of price fluctuations on the consumption of the energy resources, and information indicating the value of a third index related to the purchase price of the energy resources; a first division unit that divides the plurality of consumers into a plurality of groups based on the value of the first index and the value of the second index acquired by the index information acquisition unit; a second division unit that divides each group divided by the first division unit into one or more groups based on the value of the third index acquired by the index information acquisition unit; 1. An information processing device comprising:

2. The second division unit divides each group divided by the first division unit into one or more groups based on the value of the first index, the value of the second index, and the value of the third index acquired by the index information acquisition unit.

2. The information processing apparatus according to claim 1, wherein:

3. a scatter diagram generating unit that generates data of a scatter diagram in which the plurality of groups divided by the second dividing unit are arranged at positions according to the value of the third index acquired by the index information acquiring unit and the characteristics of each group divided by the first dividing unit; 2. The information processing apparatus according to claim 1, wherein:

4. The scatter diagram generation unit generates, as data for the scatter diagram, data for displaying each group divided by the second division unit in a bubble chart with a size according to the number of consumers included in each group.

4. The information processing apparatus according to claim 3.

5. The index information acquisition unit acquires information indicating a value of the first index and information indicating a value of the second index based on a regression coefficient in a regression model in which the consumption amount of the energy resource for each consumer is a response variable, and a value related to the price of the energy resource and a value related to temperature are explanatory variables.

5. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer.

6. a forecast information acquisition unit that acquires at least one of temperature forecast information and energy resource price forecast information; a prediction unit that predicts the consumption of energy resources of each of the plurality of consumers based on the classification result by the second classification unit and the information acquired by the prediction information acquisition unit.

5. The information processing apparatus according to claim 1, wherein the information processing apparatus is a computer.

7. An information processing method performed by a device including an index information acquisition unit, a first division unit, and a second division unit, The index information acquisition unit acquires, for each of a plurality of consumers, information indicating a value of a first index indicating the degree of influence of temperature fluctuations on the consumption of energy resources, information indicating a value of a second index indicating the degree of influence of price fluctuations on the consumption of the energy resources, and information indicating a value of a third index related to the purchase price of the energy resources; a step in which the first division unit divides the plurality of consumers into a plurality of groups based on the value of the first index and the value of the second index acquired by the index information acquisition unit; The second division unit divides each group divided by the first division unit into one or more groups based on the value of the third index acquired by the index information acquisition unit. An information processing method comprising:

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