JP5710324B2 - ENVIRONMENTAL INFORMATION MANAGEMENT DEVICE, ENVIRONMENTAL INFORMATION MANAGEMENT METHOD, AND ENVIRONMENTAL INFORMATION MANAGEMENT PROGRAM - Google Patents

Description

  The present invention relates to the fields of an environmental information management apparatus, an environmental information management method, and an environmental information management program.

  In recent years, from the viewpoints of energy saving, cost reduction, etc., companies have come to grasp energy usage and CO2 emissions and try to reduce energy usage as much as possible.

  For example, in building management, a building energy management system has been introduced. For example, environmental information such as office lighting information is monitored and collected by sensors, and this information is used to reduce energy. .

  Specifically, monthly energy consumption such as electricity, gas, and water is collected first, and this information is taken into the management system. In the management system, for example, the amount of energy used is quantified and graphed every month, so that it is possible to numerically and visually grasp analysis data such as the current amount of energy used and the amount of increase or reduction.

  Analytical data should be used to reduce energy consumption. Compared to the previous year or in light of energy-saving action guidelines, analysis results show that, for example, the power consumption of a department is extremely high. If there are too many, reduction guidance can be given while presenting specific reduction plans such as frequent light extinction and fluorescent lamp replacement.

  As a technique related to this, Patent Document 1 discloses an energy saving action guideline providing system that promotes an energy saving action that is effective and can be continued without burden for the energy consumer based on the energy consumption pattern data of the energy consumer. Is described.

  Here, for example, when a company having a plurality of bases in the national ward conducts energy conservation action guides for each base, the head office first collects energy usage (data) from each base via a network or the like. The collected data is analyzed, and the analysis results are fed back to each site together with specific reduction plans.

Japanese Patent No. 4326376

  However, although the headquarters can collect energy consumption (data) from each base and obtain the aggregated results for each base, the building / energy management system differs depending on the building situation at each base. Since the size, size, business function, and location (region) of the site are often different, the amount of energy used varies from site to site, so it is possible to analyze the aggregate results based on cross-sectional comparisons between sites. There wasn't.

  For this reason, the analysis of the total results must also be individual for each site, and the specific reduction plan that is fed back to the site has been limited to the reduction plan based on the unique data of the site. In other words, although we were able to propose a reduction plan by analyzing the aggregate results at each site and analyzing the amount of increase or decrease in energy usage by comparing each site's previous year and this year, etc. It was not possible to propose a reduction plan by analyzing the amount of increase or decrease in energy usage by means of specific comparisons.

  Therefore, the present inventor, when a company having a plurality of bases gives instructions on energy saving action guidelines to each base, in order to effectively use the energy usage (data) collected from each base, (Data) was analyzed across the board, and it was thought that a reduction plan based on comparison with other bases could not be proposed. In other words, if the conditions at each site, specifically the size of the site, the business function of the site, and the location (region) conditions are the same or close, analyze the amount of increase or decrease in energy usage by cross-sectional comparison of each site. Therefore, we thought that we could propose a more effective reduction plan.

  In view of the above points, in the present invention, when conducting energy conservation action guidelines for a plurality of bases, the energy consumption of each base is analyzed across the board, and an appropriate reduction plan based on the analysis result is proposed for each base. It is an object of the present invention to provide a possible environmental information management apparatus, environmental information management method, and environmental information management program.

In order to solve the above problems, an environmental information management apparatus according to the present invention stores, for each base, first storage means that stores attribute information of each base for each base, and energy usage obtained from each base. An environmental information management device that accesses the second storage means and the third storage means that stores the energy usage reduction plan and manages the energy usage of each site, and is a key for grouping the sites. and a reception unit that receives the setting items of the attribute information comprising a plurality of said out of each site, and grouping means for grouping a plurality bases the attribute information same set item, the energy of the multiple locations an average calculating means for calculating a group average value of the amount of energy consumption of a base of said plurality bases, a group mean value of the group that contains the 1 bases, predetermined threshold value If it exceeds the upper or higher than a predetermined ratio, determining means and reduction target based in the one bases, to the reduction target sites, and having and an output means for outputting the reduced draft .

  In order to solve the above problem, in the environmental information management device, the energy usage acquired from each base and the energy usage reduction plan are stored for each energy breakdown / system, and the average calculation means The group average value for each breakdown / system is calculated, and the determination means is configured to determine a breakdown / systematic energy use amount for one base out of a plurality of bases, When the threshold is exceeded or the predetermined ratio is exceeded, the one base is determined as the reduction target base for the breakdown / system, and the output means is configured to reduce the breakdown / system for the reduction target base. It is characterized by outputting a draft.

  In order to solve the above-mentioned problem, in the environmental information management apparatus, the output means, for the reduction target base, in addition to the reduction plan, the breakdown / systematic energy usage and breakdown / system of the reduction target base Another group average value is output.

  In order to solve the above problem, in the environmental information management apparatus, when the grouping unit groups a plurality of bases having the same attribute information, the grouping unit issues the same identifier to the plurality of bases and It is stored in the attribute information of a plurality of bases, and the average calculating means calculates a group average value of energy usage of bases having the same identifier.

  In order to solve the above-mentioned problem, in the environmental information management apparatus, the grouping means includes, among the attribute information, “area”, “scale”, “base type”, “sales scale”, “allocation staff scale”. At least one or more of the same bases are grouped.

In order to solve the above problem, a first storage unit that stores attribute information of each site for each site, a second storage unit that stores an energy usage amount acquired from each site, and an energy usage amount An environmental information management device that accesses the third storage means that stores the reduction plan and manages the amount of energy used at each site, wherein the attribute information is based on the attribute information from the sites. Grouping means for grouping the same plurality of bases, average calculating means for calculating a group average value of the energy usage amount of the plurality of bases, and an energy usage amount of one base among the plurality of bases is a group average value of the one base , A determination means for determining that the one base is a reduction target base, and an output means for outputting the reduction plan to the reduction target base If a weather information acquisition means for acquiring weather information of said each base, and average temperature calculation means for calculating the grouped mean temperature of the multiple locations, and the average temperature of one location of the plurality bases grouping When the average temperature deviation difference is equal to or greater than a predetermined value, the predetermined threshold value and the predetermined ratio used for the determination in the determination means are set so that the average temperature deviation difference is equal to or less than a predetermined value. And a first threshold value correcting means for correcting the threshold value to be larger than a predetermined threshold value and a predetermined ratio.

  In order to solve the above-mentioned problem, in the environmental information management device, as a result of the comparison, when the deviation of the average temperature is not equal to or greater than a predetermined value, the temperature difference value of the measured temperature at one of the plurality of sites, Compared to the temperature difference values of the measured air temperatures of the plurality of bases grouped, and if the deviation difference of the temperature difference of the measured air temperature is greater than or equal to a predetermined value, the predetermined threshold and the predetermined ratio used for determination in the determination means And a second threshold value correcting means for correcting the difference between the temperature difference of the actually measured temperatures to be larger than a predetermined threshold value and a predetermined ratio when the difference in temperature is equal to or lower than a predetermined value.

  In order to solve the above-mentioned problem, in the environmental information management device, meteorological information acquisition means for acquiring weather information of each of the bases, an actually measured temperature curve of one base out of the plurality of bases, and a predetermined indoor reference adjustment Area calculation for calculating a first area surrounded by a temperature line and a second area surrounded by an average measured temperature curve of the plurality of bases grouped in one day and a predetermined indoor reference adjustment temperature line When the difference between the first area and the second area is greater than or equal to a predetermined value, and the difference between the first area and the second area is greater than or equal to a predetermined value, And a third threshold value correcting means for correcting the threshold value to be larger than a predetermined threshold value and a predetermined ratio in a case where is less than a predetermined value.

  In addition, what applied the arbitrary combination of the component of this invention, expression, or a component to a method, an apparatus, a system, a computer program, a recording medium, etc. is also effective as an aspect of this invention.

  According to the present invention, when conducting energy conservation action guideline guidance for a plurality of bases, environmental information can be analyzed across the bases, and an appropriate reduction plan based on the analysis result can be proposed for each base. A management apparatus, an environmental information management method, and an environmental information management program can be provided.

It is a system configuration figure of environment information management system 1 concerning this embodiment. 2 is a hardware configuration diagram illustrating a main configuration of an embodiment of an environment information management server 10. FIG. 2 is a functional block diagram illustrating main functions of an embodiment of an environment information management server 10. FIG. The example of data of attribute DB111 is shown. The example of data of usage-amount DB112 is shown. The example of data of reduction plan DB113 is shown. It is a flowchart explaining a grouping process. The conceptual diagram of a store group is shown. It is a flowchart explaining a group average calculation process. It is a flowchart explaining a reduction object base process. It is a figure which shows the comparison (the 1) according to type | system | group of electric power consumption. It is a figure which shows the comparison (the 2) according to system | strain of electric power consumption. It is a flowchart explaining an output process. A screen example (part 1) is shown. A screen example (part 2) is shown. A screen example (No. 3) is shown. The graph figure of the actual temperature and average temperature of August in a certain store and group is shown. The graph figure of the measured air temperature of one day and indoor reference adjustment temperature in a certain store and group is shown.

  DESCRIPTION OF EMBODIMENTS Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings in each embodiment. Hereinafter, an example in which the environmental information management system according to the present invention is introduced and applied to a convenience store chain (hereinafter referred to as a convenience store or a convenience store chain) including a head office and a plurality of stores will be described.

  As a salient feature of the convenience store chain, each store is basically operated under the guidance of the headquarters, so the business scale (retail business) as well as the store size and store layout are generally uniform. In other words, the energy usage of each store is approximate. However, the amount of energy used (especially air conditioning such as air conditioning) can vary greatly depending on the region. For example, if it is a convenience store chain developed only in the Kanto region, the energy consumption is generally the same. If it is deployed nationwide, the amount of energy used will also vary depending on the region.

[System configuration]
(overall structure)
First, before describing specific contents of the present invention, an overall configuration for carrying out the present invention will be described. FIG. 1 is a system configuration diagram of an environment information management system 1 according to the present embodiment. As shown in the figure, the environment information management system 1 according to the present embodiment includes an environment information management server 10 and a collection terminal 20, and is connected via a network 30.

  An environmental information management server 10 is installed at the headquarters of the convenience store chain. The headquarters regularly collects energy usage data from each store in the convenience store chain. Since the collected data is DB-managed by the environmental information management server 10, the headquarters can grasp the energy usage for each store numerically and visually (graph).

  Convenience store chains are real stores under the chain that run retail businesses every day using various types of energy such as electricity, gas and water. In the case of a convenience store, the amount of electric power used is particularly large, and in particular, the proportion of energy usage of lighting in the store, air conditioning (cooling / heating), and refrigerator (or freezer) is high. Since electric power is supplied from the distribution board of the store, the power consumption is collected by the distribution board meter. In addition, since the distribution board distributes power by system, in this embodiment, system-specific meters (sensors) are installed, and power usage by system such as lighting system, air conditioning system, and refrigerator system is collected.

  The network 30 is a WAN network that connects the head office and each store. For example, it may be realized by a public line or the Internet.

  Note that this system configuration is merely an example embodiment, and the method of collecting energy usage data from each store can be configured in various other forms. For example, when electricity usage data is provided in detail from an electric power company, the data can be collected by connecting the electric power company and the headquarters via the network 30. In addition, the environmental information management server 10 of the headquarters can be built in an external data center, for example. In this case, the data center and the headquarters are connected via the network 30 and the environment information management server 10 is accessed from the PC terminal of the headquarters.

(hardware)
Here, the hardware configuration of the environment information management server 10 according to the present embodiment will be described. FIG. 2 is a hardware configuration diagram showing a main configuration of one embodiment of the environment information management server 10. The environment information management server 10 includes, as main components, a CPU 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, an auxiliary storage device 14, a storage medium reader 15, an input device 16, a display device 17, and The configuration includes the communication device 18.

  The CPU 11 is composed of a microprocessor and its peripheral circuits, and is a circuit that controls the entire apparatus. The ROM 12 is a memory that stores a predetermined control program (software component) executed by the CPU 11. The RAM 13 executes various control operations by the CPU 11 executing a predetermined control program (software component) stored in the ROM 12. This is a memory used as a work area (work area) when performing.

  The auxiliary storage device 14 is a device for storing various information including a general-purpose OS (Operating System) and programs, and an HDD (Hard Disk Drive), which is a nonvolatile storage device, is used.

  In addition to the auxiliary storage device 14, the various types of information are stored in various storage media such as portable media such as CD-ROM (Compact Disk-ROM), DVD (Digital Versatile Disk), and USB memory, and other media. Various information stored in these storage media can be read via a drive device such as the storage medium reader 15.

  The input device 16 is a device for a user to perform various input operations. The input device 16 includes a mouse, a keyboard, a touch panel switch provided so as to be superimposed on the display screen of the display device 17, and the like. The display device 17 is a device that displays various data on a display screen. For example, it is composed of LCD (Liquid Crystal Display), CRT (Cathode Ray Tube) and the like.

  The communication device 18 is a device that communicates with other devices via the network 30. Supports communication according to various network forms including wired and wireless networks.

(function)
Next, the main functional configuration of the environment information management server 10 will be briefly described. FIG. 3 is a functional block diagram showing the main functions of one embodiment of the environment information management server 10. The environment information management server 10 includes a storage unit 110, a grouping unit 120, a group average calculation unit 130, a determination unit 140, and an output unit 150 as main functions.

  The storage unit 110 is realized by an auxiliary storage device 14 such as an HDD. As shown in the figure, the storage unit 110 includes a usage DB 112 storing energy usage data acquired from each site, an attribute DB 111 storing attribute data of each site, and energy usage reduction plan data. The stored reduction plan DB 113 is constructed. Among them, energy usage data is periodically collected from each base (for example, a store) as described above, and attribute data and energy usage reduction plan data for each base are prepared in advance by an administrator or the like. This reduction plan data is prepared mainly for publicly recommended environmental protection regulations. Specific examples of these DBs will be described later.

  The grouping unit 120 groups (classifies) the bases among the bases based on the attribute data of the bases. As will be described later, for example, one attribute area information is stored in the attribute data. In this case, a plurality of sites located in the same area are grouped as the same site group.

  The group average calculation unit 130 calculates a group average value of energy usage at a plurality of grouped bases. For example, if there are 100 sites in the group, the group average value at the 100 sites can be calculated by “group / total energy consumption / 100”.

  The determination unit 140 compares the energy usage amount of one site with the group average value of the one site among the grouped sites, and the energy usage amount of the one site determines the group average value of the one site, If it exceeds a predetermined threshold or exceeds a predetermined ratio, the one base is determined as a reduction target base. In other words, a base compares the bases within its own group and determines the relative amount of energy usage. When the amount of energy used is large, it is determined that the base needs to make efforts to reduce the amount of energy used, that is, it is determined as a base targeted for reduction.

  The output unit 150 outputs (presents) a reduction plan to promote the reduction of energy consumption to the base determined as the reduction target base. The reduction plan is acquired from the storage unit 110, and a specific countermeasure menu classified according to breakdown and system is presented.

  These functions described above are actually realized by a program executed by the CPU 11. Details of specific functions of the functional units will be described later with specific details.

(DB)
Next, specific examples of the attribute DB 111, the usage amount DB 112, and the reduction plan DB 113 in the storage unit 110 are shown below. Convenience store stores operate a retail business using various types of energy such as electricity, gas, and water. In this embodiment, the example of “electric power” (electricity) will be described below. explain. In particular, as a breakdown / system of power consumption, examples of “air conditioning” (air conditioning), “lighting”, and “refrigerator” (or freezer) that occupy a high percentage in the store will be described below.

  FIG. 4 shows an example of data in the attribute DB 111. Store attribute data is prepared in advance by an administrator or the like as described above, and one attribute data per store is stored in the DB. The data example of FIG. 4 is attribute data of A store, for example. The details of the “attribute item” are as shown in the figure. Of these, “scale” indicates the size classification of the store in the same convenience store chain, for example, large store, medium store, small store, etc. . The “location type” indicates the store type classification of the store, and is classified into, for example, an independent store type, a borrowed store type (within a part of a commercial facility), and the like. “Sales scale” indicates the sales scale classification in the same convenience store chain, and is classified into, for example, A (from 10,000 yen or more), B, C, D, and the like. Further, “placement clerk scale” indicates the clerk scale classification to be placed in the store. For example, A (10 or more), B (6 to 9), C (3 to 6), D (3 or less) ) Etc. The “group classification” indicates a classification code (for example, 01) in which the stores are grouped and classified. Details thereof will be described later.

  FIG. 5 shows an example of data in the usage amount DB 112. As described above, the energy usage data is periodically collected from each base (for example, a store) via the network 30. The data example in FIG. 5 is an example of power usage data collected from, for example, store A. As shown in the figure, it can be seen that the amount of power used for each 1H is tabulated for each system (air conditioning, lighting, refrigerator).

  FIG. 6 shows an example of data in the reduction plan DB 113. The reduction plan data is prepared in advance by the administrator or the like as described above, and the reduction plan (measure menu) is stored in the DB for each system. (A), (b), (c) are air conditioning, lighting, refrigerator / freezer / reduction plan examples, respectively. As shown in the figure, a reduction plan (measure menu) is maintained for each system, and when it is determined that a power reduction measure is required for each system, the reduction plan is output (suggested) for each system. In addition, specific values of “Effect (yen conversion)” and “Effect (CO2)” are held together as a guideline value when implementing the reduction plan, and the effect is output together with the reduction plan.

[Information processing]
(Grouping process)
First, the grouping process will be described. As described above, the grouping unit 120 groups (classifies) stores based on the store attribute data from among the bases and stores. A plurality of “attribute items” are stored in the attribute DB 111 of FIG. 4, and stores having the same “attribute value” of predetermined “attribute items” are grouped (classified) as belonging to the same group.

  FIG. 7 is a flowchart for explaining the grouping process. This operating subject is the grouping unit 120 unless otherwise specified. Hereinafter, description will be given with reference to the drawings.

  S1: First, “attribute item” (a plurality of items) as a key is acquired. That is, an “attribute item” which is a key for narrowing down as a condition when grouping is acquired, but this can be set in advance by an administrator or the like. Here, it is assumed that the “area”, “scale”, “base form”, “sales scale”, and “location staff size” are set in advance as the “attribute item” as a key. Therefore, “area”, “scale”, “location type”, “sales size”, and “allocation staff size” are acquired as “attribute items” as keys. Note that the “attribute item” that is the key here is not limited to these, but the energy usage between the stores grouped here is the comparison target, so the energy usage is almost the same. The attribute item that can narrow down the stores that are likely to become the standard is set as an “attribute item” as a key. That is, in this case, it can be said that stores having the same “region”, “scale”, “base type”, “sales size”, and “allocation staff size” have almost the same energy consumption.

  S2: Stores having the same attribute value are extracted using “attribute item” as a key. Here, for example, stores whose attribute data is “region”: Kanto area, “scale”: small store, “base type”: independent store type, “sales scale”: B, “assignment staff size”: B are grouped. Extract as much as possible. As shown in FIG. 4, the store A corresponds to a store having these attribute values and is extracted here. Similarly to the store A, stores having the same attribute value are extracted. Here, for convenience of explanation, it is assumed that store A, store B, and store C are all extracted as stores having the same attribute value.

  S3: A group classification code is issued. This is to identify the group to which it belongs. Here, for example, “01” is issued.

  S4: The same classification code is input to the extracted stores. That is, in the attribute DB 111 of FIG. 4, the classification code “01” is input to the “group classification” attribute value for all the stores extracted in S2. As a result, the same classification code is stored in the stores classified into the same group. Therefore, the stores of the same group can be easily extracted by referring to the classification code. Here, for convenience of explanation, since store A, store B, and store C are all extracted as stores having the same attribute value, classification code “01” is input to all of them.

  As described above, by performing the same process for all stores, it is possible to input classification codes (multiple inputs are possible) to all stores. When a new store is registered (added) in the attribute DB 111 of FIG. 4, the same processing is performed to calculate which existing classification code is classified, and the classification code is input. If it is not classified into any existing classification code, a new classification code may be issued and the same classification code may be input.

If the grouping process is performed in advance and each store is classified into codes in advance, it is not necessary to perform the grouping process every time the group average calculation process described later. Can contribute to the improvement of processing. Since the classification code does not change so frequently, the key is “attribute item” (for example, “sales scale”, “location staff size”).
) May be reprocessed every period during which the attribute value can change.

  FIG. 8 shows a conceptual diagram of a store group. As shown in the figure, a state in which stores are grouped using “attribute item” as a key is shown. Also, it can be understood from the figure that even if the attribute values of other “attribute items” are different in the same area (“region”), they are classified as different groups.

(Group average calculation process)
Next, the group average calculation process will be described. The processing timing is, for example, when the headquarters user selects (designates) A store by operating the environment information management server 10 in order to output a reduction plan for A store (see FIG. 14). As described above, the group average calculation unit 130 calculates the group average value of the energy usage at the grouped multiple stores.

  FIG. 9 is a flowchart for explaining the group average calculation process. This operating subject is the group average calculation unit 130 unless otherwise specified. Hereinafter, description will be given with reference to the drawings.

  S11: 1 store is selected (designated). Here, store A is selected by the head office user. This is because, for example, the headquarters user outputs a reduction plan for store A.

  S12: Acquire a store of the same group as the selected store. Here, store A is selected by the headquarters user, so the store A's classification code “01” is acquired from the attribute DB 111, and stores having the classification code “01” are acquired from all stores. That is, here, A store, B store, and C store are all acquired as being in the same group.

  S13: Acquire usage data of all stores in the same group. As described above, since the energy usage data from each store is periodically collected in the usage amount DB 112, the energy usage amount data of the stores A, B, and C is stored here by referring to the usage amount DB 112. Acquired by system (air conditioning, lighting, refrigerator). Note that the usage data is collected every 1H, for example, but the target period range of the acquired data can be arbitrarily determined by the administrator, for example, every week, every month, every quarter period, and so on.

S14: A group average value is calculated for each energy use amount data. For example, the power consumption of each store for a certain month is as follows.
・
A store / air conditioning power consumption: 1200 kWh, lighting power usage: 2500 kWh, refrigerator power usage: 1800 kWh
・
Store B / Air conditioning power consumption: 900 kWh, lighting power usage: 1700 kWh, refrigerator power usage: 1600 kWh
・
Store C / Air conditioning power consumption: 1000 kWh, lighting power usage: 1600 kWh, refrigerator power usage: 1400 kWh
In this case, the air conditioning power consumption / group average value is (1200 + 900 + 1000) / 3≈1033 kWh. Similarly, the lighting power usage / group average value is calculated as 1933 kWh, and the refrigerator power usage / group average value is calculated as 1600 kWh.

  The group average value may be an average value of other stores (B store, C point) excluding A store. Even if the A store is not excluded, the influence of the A store can be ignored as the number of other stores increases.

(Reduction target site judgment processing)
Next, reduction target site processing will be described. As described above, the determination unit 140 compares the energy usage amount of one store among the grouped stores with the group average value of the one store, and the energy usage amount of one store is the group average of the one store. If the value exceeds a predetermined threshold value or exceeds a predetermined ratio, that one store is determined as a reduction target base.

  FIG. 10 is a flowchart for explaining the reduction target site processing. This operating subject is the determination unit 140 unless otherwise specified. Hereinafter, description will be given with reference to the drawings.

  S31: The energy consumption of the selected store is compared with the group average value of the store for each system. Here, the A store and the group average value of the A store are compared for each system. More specifically, the air conditioning power consumption amount of the store A: 1200 kWh, the lighting power consumption amount: 2500 kWh, the refrigerator power consumption amount: 1800 kWh, and the group air conditioning power consumption amount / group average value of the group including the A store: 1033 kWh Lighting power consumption / group average: 1933 kWh, refrigerator power usage / group average: 1600 kWh, respectively.

  S32: As a result of the comparison, it is determined whether there is a system whose difference value exceeds a predetermined threshold. If there is even one system that exceeds the threshold, it is determined that the amount of use should be reduced for that system, and the process proceeds to a reduction plan output process as a reduction target base for that system (S41). At this time, the determination unit 140 passes the system information to the output unit 150. On the other hand, if there is no system that exceeds the threshold, the energy usage of the store is appropriate compared to other stores of the same condition, and the process is terminated, not a store for special reduction. Reduction plan output processing is not performed. This may be displayed on the screen for the headquarters user operating at this time.

  FIG. 11 is a diagram illustrating comparison of power consumption by system (part 1). The total power consumption of the A store and the group average, and the power consumption (kWh) by system are displayed in a graph.

  In the above (S32), it is determined whether or not there is a system whose difference value exceeds a predetermined threshold value. The threshold value (parameter) used for the determination is stored in advance in the environmental information management server 10 for each system for each store. The The threshold value itself may be determined for each store by the headquarters user in consideration of various circumstances (for example, store scale, cost, sales performance, rule of thumb / know-how, energy saving action guidelines, environment variables, etc.). For example, because stores with large store sizes have large power consumption errors and fluctuations, thresholds are set higher, and new stores where sales have increased (growth) have become more active. The threshold is determined to be higher. Further, for example, in stores where experience rules and know-how are accumulated, since energy saving measures have permeated, errors and fluctuations are small and the threshold value is determined to be low. Here, for convenience of explanation, the threshold values are assumed to be an air conditioning system 200 kWh, an illumination system 300 kWh, and a refrigerator system 250 kWh, respectively.

  First, regarding the air conditioning system, the amount of air-conditioning power used at store A: 1200 kWh is compared with the amount of air-conditioning power used at group A / group average value: 1033 kWh, and the difference value is 167 kWh. Since the threshold value of the air conditioning system is 200 kWh, the difference value does not exceed the threshold value.

  Further, regarding the lighting system, the amount of lighting power used at store A: 2500 kWh is compared with the amount of lighting power used at group A / group average value: 1933 kWh, and the difference value is 567 kWh. Since the threshold value of the illumination system is 300 kWh, the difference value exceeds the threshold value. Therefore, it is determined that the usage amount should be reduced for the lighting system, and the store A is set as a reduction target base for the lighting system.

  Moreover, regarding the refrigerator system, the refrigerator power usage amount of the store A: 1800 kWh is compared with the refrigerator power usage amount / group average value of the group average value of the store A: 1600 kWh, and the difference value is 200 kWh. Since the threshold value of the refrigerator system is 250 kWh, the difference value does not exceed the threshold value.

  In addition, referring to the A graph display of FIG. 10, the total power consumption 5500 kWh of the store A is slightly higher than the group average total power consumption 4566 kWh. Similarly, it is possible to determine whether the difference value exceeds a predetermined threshold for the total power consumption. However, even if this is fed back to store A, it can be seen that the total power consumption of the entire store A is large, but the overall and general reduction plan is only presented. I have to work hard. Therefore, in this embodiment, in order to promote more proactive and appropriate energy saving activities and increase the reduction efficiency, in order to determine the amount of power usage for each system, it is possible to determine which system has the most power usage. And provide specific reduction plans corresponding to the system.

  FIG. 12 is a diagram illustrating comparison of power consumption by system (part 2). The total power consumption of the A store and the group average, and the power consumption (percentage conversion) by system are displayed in a graph. In the rate conversion, the total power usage is 100%, and the power usage for each system is displayed as a ratio of the power usage for each system to the total power usage.

  In the above (S32), it is determined whether or not there is a system in which the difference value (%) exceeds a predetermined threshold value (%). Here, for convenience of explanation, the threshold values are assumed to be 2.7% for the air conditioning system, 4% for the lighting system, and 3.3% for the refrigerator system, respectively.

  First, regarding the air conditioning system, the amount of air-conditioning power used at store A: 21% is compared with the amount of air-conditioning power used by the group average value at store A / group average value: 23%, and the difference value is 2%. Since the threshold value of the air conditioning system is 2.7%, the difference value does not exceed the threshold value.

  Further, regarding the lighting system, the lighting power consumption of store A: 46% is compared with the lighting power usage / group average of the group average value of store A: 42%, and the difference value is 4%. Since the threshold value of the illumination system is 4%, the difference value exceeds the threshold value. Therefore, it is determined that the usage amount should be reduced for the lighting system, and the store A is set as a reduction target base for the lighting system.

  Moreover, regarding the refrigerator system, the refrigerator power usage amount of the store A: 33% is compared with the refrigerator power usage amount / group average value of the group average value of the store A: 35%, and the difference value is 2%. Since the threshold value of the refrigerator system is 2.7%, the difference value does not exceed the threshold value.

  As mentioned above, the convenience store chain stores use different power depending on “region”, “scale”, etc., so the total power consumption (and power usage by system) is determined by the grouping process described above. ) Were extracted from stores with the same level. This is to compare the amount of power used and determine its validity. However, there is a possibility that some unspecified factor that cannot be considered only by the attribute affects the power consumption of the store. That is, there is a possibility that stores with a slightly higher level of total power consumption than other stores may be extracted in the group. For example, in such a store, assuming that the total power usage is large and the power usage is also increasing in proportion to all of the individual power systems, when performing the determination based on the threshold (kWh) in FIG. Another amount of power usage will greatly exceed the threshold (kWh).

  If the total power consumption is high because it is only due to the large amount of power used by only one system, the problem system can be determined appropriately. As for the stores where the power consumption is large, it is not appropriate to determine that the power usage by all the systems exceeds the threshold (kWh) and that all the systems use too much power. Therefore, by converting the power usage and power usage by system to a percentage (%), and comparing the threshold by system with the ratio (%), the ratio balance of the power usage by system to the total power usage A system that has collapsed can be determined as a reduction target base for that system. That is, the comparison method in FIG. 11 is based on the absolute amount of power usage, and the comparison method in FIG. 12 is based on the relative amount of power usage.

  Note that it is possible to determine whether the comparison method of FIG. 11 or the comparison method of FIG. For example, thresholds are prepared in stages, such as threshold level 1, threshold level 2, and threshold level 3. If the threshold level is 1 or more and threshold level 2 or less, “review” is required, threshold level 2 or more and threshold level 3 or less. If this is the case, it is possible to output to the headquarters user the information “Implementation required” and “Urgent implementation” if the threshold level is 3 or more, together with a reduction plan.

(Output processing)
Next, output processing will be described. As described above, the output unit 150 outputs (presents) a reduction plan according to each system in order to promote reduction of energy consumption to the base determined as the reduction target base.

  FIG. 13 is a flowchart for explaining output processing. The operating subject is the output unit 150 unless otherwise specified. Hereinafter, description will be given with reference to the drawings.

  S41: In the reduction target site determination process, it is determined whether or not the system whose difference value exceeds the threshold value is “air conditioning system” (determines whether or not “air conditioning system” is included). If applicable, the process proceeds to S42, and if not, the process proceeds to S43.

  S42: Refer to the reduction plan DB 113 (FIG. 6) to obtain the air conditioning / reduction plan. This is to present a plan for reducing the power consumption of the air conditioning system.

  S43: Next, in the reduction target site determination process, it is determined whether or not a system whose difference value exceeds a threshold value is “lighting system” (determines whether or not “lighting system” is included). If applicable, the process proceeds to S44, and if not, the process proceeds to S45.

  S44: Refer to the reduction plan DB 113 (FIG. 6) to obtain the lighting / reduction plan. This is to present a plan for reducing the power consumption of the lighting system.

  S45: Next, in the reduction target site determination process, it is determined whether or not the system having the difference value exceeding the threshold value is “refrigerator system” (determines whether or not “refrigerator system” is included). If applicable, the process proceeds to S46, and if not, the process proceeds to S47.

  S46: Refer to the reduction plan DB 113 (FIG. 6) to obtain the refrigerator / reduction plan. This is to present a plan for reducing power consumption of the refrigerator system.

  S47: The obtained reduction plan is output (displayed) for each system. As long as the output process is performed, since it is determined that the difference value exceeds the threshold value in at least one system in the reduction target site determination process, at least one of “air conditioning system”, “lighting system”, and “refrigerator system” is reduced. The draft will be output.

[Screen example]
Based on the above description, a screen example of the environment information management server 10 is shown. As described above, for example, the headquarters user first operates the environment information management server 10 to select a store in order to perform an operation for outputting a reduction plan for an arbitrary store.

  FIG. 14 shows a screen example (part 1). The headquarters user operates this screen to select an arbitrary store (for example, store A). You can select stores from the list by narrowing down the area. In addition, “target period” is selected or input. The target period means a target period in which the amount of energy used this time is aggregated and analyzed, and can be selected from a list such as one week, one month, or every quarter period, and can be arbitrarily input. When the selection is completed, the headquarters user presses the “OK” button.

  FIG. 15 shows a screen example (No. 2). After pressing the “OK” button, as shown in the figure, the power usage data 1501 of the store A, the store type average data 1502, the comparison graph 1503, and the attribute data 1504 of the store A are output in the “target period”. On this screen, the power usage status (actual result) of the store A can be grasped. Thereafter, the headquarters user presses the “analysis” button.

  FIG. 16 shows a screen example (No. 3). After pressing the “Analyze” button, as shown in the figure, an analysis result 1601 for each system based on the comparison with the same store type average and a reduction plan 1602 based on the analysis result are output. In this analysis result 1601, it is displayed that the amount of illumination power used exceeds 567 kWh from the store type average and exceeds the standard level. Therefore, a reduction plan 1602 for reducing the amount of illumination power used is specifically displayed (suggested).

  Thereafter, when the headquarters user presses the “notify to store” 1603 button, the contents of FIGS. 15 and 16 are notified to the store (for example, the store staff). The notification method may be e-mail, or the person in charge of the store may refer from the system. The person in charge of the store confirms this content, grasps the power usage status (actual result) of the store A, and implements energy saving measures for the lighting system in accordance with a specific reduction plan.

  “Urgent execution” 1604 expresses a threshold level when the above-described threshold value is multi-level, and here, for example, “Urgent execution” is output as an expression when the threshold level is 3 or more. When the threshold value is not multi-stage but single, it may always be output as “urgent execution” from the viewpoint of strongly urging implementation.

[About threshold correction in reduction target site determination processing]
In the “reduction target site determination process” of the above-described embodiment, the determination unit 140 compares the energy usage amount of one store among the grouped stores with the group average value of the one store, When the energy usage exceeds the group average value of the one store over a predetermined threshold or over a predetermined ratio, the one store is determined as a reduction target base.

  At this time, the predetermined threshold (and the predetermined ratio) used in the determination is stored in advance in the environment information management server 10 for each store system, and the threshold value itself is determined by the headquarters user in various circumstances (for example, store scale, cost). , Sales results, rules of thumb and know-how, energy conservation action guidelines, environmental variables, etc.). For this reason, since the threshold value is related to the accuracy of determination, it is desirable to determine an appropriate threshold value that is more suitable for the situation (actual situation) of the store.

  Here, among the circumstances considered in determining the threshold value and among the environmental variables therein, “temperature” is mentioned in particular. In general, it can be said that the change in temperature affects the power consumption of the “air conditioning system” of the store. Specifically, for example, in summer, the higher the temperature (the hotter), the more power is consumed by the air conditioner (cooling). For example, in winter, the lower the temperature (cold), the more power is consumed by the air conditioner (heating).

  In the above-described embodiment, the amount of electric power used is relatively compared by comparing the energy usage of one store with the group average value of the one store. Here, the group is grouping stores where energy consumption will be approximately the same level based on the attribute item, and if the “region” (narrow region) of the attribute item is the same, it is due to changes in temperature. If the energy usage at one store is increasing, the energy usage is also increasing at group stores in the same area. That is, if the energy usage of one store is increased, the group average value of that one store is also increased to the same extent. Therefore, for example, in summer (winter), as the temperature is higher (lower), even if the power of the air conditioner (cooling) is consumed, the relative amount of power usage is compared as described above. In this case, it is not necessary to influence the determination of the threshold value.

  On the other hand, there is no problem if a store with uniform energy consumption can be selected by grouping stores as described above, but this may not always be the case. For example, this is a case where the range of “region” is wide enough to have different weather conditions. In order to calculate the group average value, the group requires a certain number of store members. On the contrary, if there are not a certain number of stores, the group average value is not valid. However, in the case of a business entity that does not have such a large number of stores, since there are not so many stores in the same region, there is a situation that the “region” attribute item has to be taken in a wide area. In this case, even if the stores in the same group have different weather conditions, even if the energy usage of one store is increasing due to changes in temperature, the energy usage is also the same in group stores in the same area. The amount is not increasing. In other words, in one store area, even if the energy consumption increased as a result of high air temperature and power consumption of the air conditioner (cooling), the group average value of that one store also has the same amount of energy usage. Is not necessarily increasing.

  Therefore, the “average temperature” at a certain store is compared with the “average temperature” at the group of that store, and if there is a difference in the average temperature value, a predetermined threshold (and a predetermined ratio) used in the determination To correct.

(Correction based on average temperature)
First, the “average temperature” in August at a certain store is compared with the “average temperature” in August in the group of that one store. Calculate the difference in average temperature (absolute value of average temperature difference) between a store and a group by “| Average temperature at a store-“ Average temperature ”in the group of that store |” If the discrepancy is greater than or equal to a predetermined value (for example, 3 degrees), the threshold value is increased. Note that meteorological information such as “average temperature” is obtained from the Japan Meteorological Agency or forecast business licensed business operators.

  For example, if the “average temperature” in August at a certain store is 28 degrees and the “average temperature” in August in the group of that store is 28 degrees, stores in the same group may have a positive difference, for example. Since it is within the minus 3 degree range, it can be determined that the weather conditions are the same, and it is not necessary to correct the predetermined threshold value (and the predetermined ratio) used in the determination.

  On the other hand, for example, when the “average temperature” in August at a certain store is 28 degrees and the “average temperature” in August in the group of that store is 24 degrees, stores in the same group, for example, For example, since it is outside the range of plus or minus 3 degrees, it can be determined that the weather conditions are not the same, and a predetermined threshold (and a predetermined ratio) used in the determination is corrected. In this case, even if the power consumption of the “air-conditioning system” is high, it is due to the temperature factor, so some power usage is unavoidable. Therefore, when determining the threshold value used in the summer (August) judgment, by determining (correcting) the threshold value slightly higher than the threshold value when the “average temperature” is the same in the group, The threshold value becomes a more appropriate (appropriate) value.

  In addition, when the “average temperature” in January at a certain store is 1 degree and the “average temperature” in August in the group of that store is 5 degrees, the stores in the same group have, for example, a positive divergence, for example. Since it is outside the minus 3 degree range, it can be determined that the weather conditions are not the same, and the predetermined threshold (and predetermined ratio) used in the determination is corrected. In this case, even if the power consumption of the “air-conditioning system” is high, it is due to the temperature factor, so some power usage is unavoidable. In this case, when determining the threshold value used in the winter (January) determination, the threshold value is determined (corrected) slightly higher than the threshold value when the “average temperature” is the same in the group. Thus, the threshold value becomes a more appropriate (appropriate) value.

(Correction 1 based on temperature difference between temperatures)
FIG. 17 shows a graph of the measured actual temperature and average temperature in August at a certain store and group. That is, (a) shows the actually measured temperature and average temperature in August at a certain store, and (b) shows the actually measured temperature and average temperature in August at the group average of that one store.

  Here, since both “average temperatures” are 28 degrees, it can be determined that the weather conditions are the same, and it is considered that the correction of the predetermined threshold (and the predetermined ratio) used in the determination is not necessary. However, when paying attention to the measured temperature, since the temperature difference between the temperatures is severe, even if the power consumption of the “air conditioning system” is higher than the group average value at a certain store, it can be said that some power usage is unavoidable.

  In other words, in this case, even when the “average temperature” is about the same when determining the summer threshold value, if the temperature difference between the measured temperatures is severe, the threshold value is more appropriate by determining a slightly higher threshold value. (Appropriate) value. Similarly, when determining the threshold value in winter, even if it is the same level, if the temperature difference between the measured temperatures is severe, the threshold value is more appropriate (appropriate) by determining (correcting) the threshold value slightly higher. Value.

  Specifically, the temperature difference between the measured temperatures (absolute value of the measured air temperature) at a certain store and group is calculated by “| maximum measured temperature−minimum measured temperature |”, and the difference between the temperature and the temperature is predetermined. As described above, when the value is larger, the threshold value is determined (corrected) higher. On the contrary, when the difference between the temperature difference is not larger than a predetermined value, the special threshold value is not corrected.

(Correction 2 based on temperature difference)
FIG. 18 shows a graph of the measured daily temperature and the indoor reference adjusted temperature in one store and group. That is, (a) shows the actual measured temperature for one day at a certain store, and (b) shows the measured actual temperature (average) for one day in the group average of that one store.

  When the measured temperature is viewed on a daily basis, the temperature difference between the temperatures may be large depending on the area of the store. In the case of a normal sunny day, the measured temperature becomes maximum at the time after the afternoon, and the measured temperature becomes minimum from midnight to early morning.

  Here, in the case of a convenience store, the room temperature is generally kept constant by an air conditioner, and this room temperature is referred to as an indoor reference adjustment temperature (for example, 20 degrees). Considering the relationship between the power consumption of the “air conditioning system” and the outside air (actual temperature), when the outside air is 20 degrees, the power consumption of the “air conditioning system” is 0 (more accurately, it is consumed) . In addition, when the outside air exceeds 20 degrees Celsius and the measured air temperature is maximum, the power consumption of the “air conditioning system” (cooling) is maximized. The maximum power consumption is. In other words, the amount of power used by the “air conditioning system” (air conditioning) is consumed as the fluctuation range of the measured air temperature increases up and down with the indoor reference adjustment temperature as a reference.

  On the other hand, by calculating the integral of the actually measured temperature curve and the indoor reference adjustment temperature line, the area of the hatched portion in the figure is calculated. It can be said that the larger the area of the hatched portion, the larger the electric power consumption, and the smaller the area of the hatched portion, the smaller the electric power consumption.

  In this way, the temperature difference of the daily temperature at one store is severe, so even if the power consumption of the “air conditioning system” is higher than the group average at one store, Use is unavoidable. In other words, in this case, when it is desired to make a determination on a certain day, when determining the threshold value for the day, if the temperature difference of the measured temperature is severe, the threshold value is made more appropriate by determining the threshold value slightly higher. (Appropriate) value.

  Specifically, as described above, by calculating the integral of the measured temperature curve and the indoor reference adjustment temperature line, the area of the hatched portion in the figure at a certain store and group average is calculated, respectively, and the difference in area difference is calculated. If is greater than or equal to a predetermined value, the threshold value is determined (corrected) higher. On the other hand, when the deviation of the area difference is not larger than a predetermined value, the special threshold is not corrected.

  As described in the above-described embodiment, the reduction target site determination process determines a reduction target site, and a reduction plan for energy use is proposed for the reduction target site. Therefore, in most cases, for example, based on the power consumption of each store (base) every month (or several months), an operation is proposed in which a reduction plan for energy use is proposed every month. However, in this (Correction 2 based on temperature difference of temperature), the threshold value can be corrected based on temperature difference of temperature even on a daily basis regardless of every month.

  As described above, in the “reduction target site determination process” of the above-described embodiment, the predetermined threshold (and the predetermined ratio) used in the determination of the determination unit 140 is determined as an appropriate threshold that is more in line with the store situation (actual situation). It is desirable to keep it. Here, among the circumstances that are considered in determining the threshold value, and among the environmental variables in that, in particular, when a store that is homogeneous with respect to “temperature” cannot be selected, the determination is made by correcting the threshold as described above. Accuracy can be improved.

[Summary]
As described above, the environmental information management server 10 according to the present embodiment extracts stores having the same or similar energy usage conditions based on the store attribute information, and stores the energy usage (by breakdown and system) of each store among the same group. Analyze across the board. Further, since a reduction plan based on comparison with other stores can be proposed, a more effective reduction plan can be proposed for each store.

  In other words, when conducting energy conservation action guidelines for multiple bases, an environmental information management device, etc. that can analyze the energy consumption of each base cross-sectionally and propose an appropriate reduction plan for each base based on the analysis results. It becomes possible to provide.

  Note that the present invention is not limited to such specific embodiments, and various modifications and changes can be made within the scope of the gist of the present invention described in the claims. For example, in the present embodiment, power (electricity) has been described as the energy used, but it goes without saying that the present invention can be applied to gas, water, and other energy as well. In addition, the example of a convenience store chain has been described, but it goes without saying that the present invention can be similarly applied to, for example, a restaurant / chain, a branch, a factory, a branch office, and the like.

1 Environmental Information Management System 10 Environmental Information Management Server 11 CPU
12 ROM
13 RAM
14 Auxiliary storage device 15 Storage medium reading device 16 Input device 17 Display device 18 Communication device 20 Base (store)
30 network 110 storage unit 111 attribute DB
112 Usage DB
113 Reduction plan DB
120 Grouping unit 130 Group average calculation unit 140 Determination unit 150 Output unit

Claims (10)

First storage means for storing attribute information of each base for each base;
Second storage means for storing the energy usage acquired from each of the sites for each site;
An environmental information management device for accessing the third storage means storing the energy usage reduction plan and managing the energy usage at each site;
Accepting means for accepting the setting of the attribute information item that is a key for grouping the bases;
A plurality of said out of each site, and grouping means for grouping a plurality bases the attribute information same set item,
Average calculating means for calculating a group average value of the energy consumption of the plurality of bases;
Determining energy usage one location of the plurality bases, a group mean value of the group that contains the 1 bases, if it exceeds more than or more than a predetermined ratio a predetermined threshold, the reduction target based in the 1 bases Determination means to perform,
Output means for outputting the reduction plan to the reduction target base;
An environmental information management apparatus comprising: The energy usage acquired from each base and the energy usage reduction plan are stored for each energy breakdown / system,
The average calculating means calculates the group average value by breakdown / system,
When the breakdown / systematic energy usage of one base out of a plurality of bases exceeds the group average for each base / system, a determination threshold is 1 or more. the bases is determined that the reduction target based on internal translation and lines,
The environmental information management apparatus according to claim 1, wherein the output unit outputs the reduction plan for the breakdown / system to the reduction target base. The output means outputs, to the reduction target base, in addition to the reduction plan, a breakdown / systematic energy usage amount and a breakdown / system group average value of the reduction target base,
The environmental information management apparatus according to claim 2. When grouping a plurality of sites having the same attribute information, the grouping unit issues the same identifier to the plurality of sites and stores the identifier in the attribute information of the plurality of sites.
The environmental information management apparatus according to any one of claims 1 to 3, wherein the average calculation means calculates a group average value of energy usage at a base having the same identifier. The grouping unit groups a plurality of bases in which at least one of at least one of “region”, “scale”, “base type”, “sales scale”, and “allocation staff size” is the same among the items of the attribute information The environmental information management apparatus according to claim 1, wherein First storage means for storing attribute information of each base for each base;
Second storage means for storing the energy usage acquired from each of the sites for each site;
An environmental information management device for accessing the third storage means storing the energy usage reduction plan and managing the energy usage at each site;
A grouping means for grouping a plurality of bases having the same attribute information based on the attribute information from the bases;
Average calculating means for calculating a group average value of the energy consumption of the plurality of bases;
A determination means for determining, when the energy usage amount of one base among the plurality of bases exceeds a group average value of the one base over a predetermined threshold or a predetermined ratio, the one base is a reduction target base;
Output means for outputting the reduction plan to the reduction target base;
Weather information acquisition means for acquiring weather information of each of the bases;
An average temperature calculating means for calculating an average temperature of the plurality of bases grouped;
When the average temperature of one of the plurality of bases is compared with the average temperature of the grouped multiple bases, and the difference in average temperature is greater than or equal to a predetermined value, the predetermined threshold used for determination in the determination means And a first threshold correction means for correcting the predetermined ratio so as to be larger than the predetermined threshold and the predetermined ratio when the difference in average temperature is less than or equal to a predetermined value;
An environmental information management apparatus comprising: As a result of the comparison, the difference in average temperature is not more than a predetermined value,
When the temperature difference between the measured temperatures at one of the multiple sites is compared with the temperature difference between the measured temperatures at the grouped multiple sites, and the difference between the measured temperatures is greater than or equal to a predetermined value The second threshold correction for correcting the predetermined threshold and the predetermined ratio used for determination in the determination means so as to be larger than the predetermined threshold and the predetermined ratio when the difference in the temperature difference between the actually measured temperatures is equal to or less than a predetermined value. The environment information management apparatus according to claim 6, further comprising: means. Weather information acquisition means for acquiring weather information of each of the bases;
A first area surrounded by a daily measured temperature curve and a predetermined indoor reference adjustment temperature line of one of the plurality of sites, and an average measured temperature curve of the plurality of sites in one day An area calculating means for calculating a second area surrounded by a predetermined indoor reference adjustment temperature line;
When the first area and the second area are compared, and the difference in area is greater than or equal to a predetermined value, the predetermined threshold and the predetermined ratio used for determination in the determination unit are set to be equal to or less than the predetermined value. 6. The environment information management apparatus according to claim 1, further comprising: a third threshold value correcting unit that corrects the predetermined threshold value and the predetermined ratio to be larger than the predetermined threshold value. First storage means for storing attribute information of each base for each base;
Second storage means for storing the energy usage acquired from each of the sites for each site;
An environmental information management method in an environmental information management apparatus for accessing the third storage means storing the energy usage reduction plan and managing the energy usage at each site ,
An acceptance procedure for accepting the setting of the attribute information item that is a key for grouping the bases;
A plurality of said out of each site, the grouping procedure of the attribute information group the same multiple locations of the items set,
An average calculation procedure for calculating a group average value of the energy consumption of the plurality of bases;
The energy usage of one location of the plurality bases group average value of said one location, if it exceeds more than a predetermined threshold value or a predetermined ratio, a judgment procedure as reduction target based in the 1 bases,
An output procedure for outputting the reduction plan to the reduction target base;
An environmental information management method characterized by comprising: An environmental information management program for causing a computer to execute the environmental information management method according to claim 9.

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