JP2008250637A - Information processor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To change an analysis axis without changing a database. <P>SOLUTION: Energy consumption data including an existing analysis axis and a measurement point number are stored in an energy consumption DB 2, a user axis different from the existing analysis axis is shown in a definition information storage part 7, user axis information 11 designated with the measurement point number to a user axis item that is a breakdown of the user axis is stored, a preprocessing part 1 (3) extracts the energy consumption data according to a request from a user, a preprocessing 2 (4) generates analysis axis setting information 9 based on the user axis of the user axis information and the existing analysis axis of the extracted extraction data, adds the user axis item to the extraction data based on the measurement point number of the extraction data and the measurement point number of the user axis information, and generates the energy consumption data 8 for analysis, and a GUI (Graphical User Interface) part 5 displays a screen wherein the user axis and the user axis item are included in the analysis axis and an analysis axis item list by use of the energy consumption data 8 for the analysis, the analysis axis setting information 9, and setting information 10 for the GUI part. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to, for example, a technique for collecting and displaying measured values of energy consumption using various analysis axes.

Conventional energy-saving (hereinafter also referred to as energy-saving) systems visualize energy consumption based on user-specified conditions using multiple analysis axes prepared in advance when visualizing energy consumption at each location. By doing so, the user can grasp the energy consumption.
In addition, even when there are a large number of analysis axes, the user has to select an analysis axis by himself and perform analysis (Patent Document 1).
Here, the analysis axis is a data retrieval unit that serves as a reference for analyzing energy consumption data. Details of the analysis axis will be described later.
The “management classification” in Patent Document 1 corresponds to the analysis axis information in this specification.
Japanese Patent Laid-Open No. 2006-185318, pages 4 to 9, FIGS. 1 and 3

Conventional energy-saving systems can see energy consumption from various angles, but it was necessary to create a database of analysis axis information in advance.
Therefore, there is a problem that the database needs to be changed when changing the analysis axis information such as addition / deletion.

  Conventionally, there has been a problem that the user himself / herself has to search for an analysis axis that affects the analysis.

One of the main objects of the present invention is to solve the above-described problems, and the main object of the present invention is to enable analysis axis information to be changed without changing the database.
It is another object of the present invention to realize a system that can perform energy saving analysis without requiring know-how by narrowing down analysis axis information in advance.

An information processing apparatus according to the present invention includes:
A database for storing energy consumption measurement data with multiple types of data search units;
A definition information storage unit that stores definition information that defines a data search unit that is different from any of the multiple types of existing data search units included in the energy consumption measurement value data as an additional data search unit;
Data processing for designating additional data search units defined in the definition information for the extracted extracted energy consumption measurement value data when any of the energy consumption measurement value data is extracted from the database And
The additional data search unit designated by the data processing unit is displayed as a data search unit of the extracted energy consumption measurement value data together with at least one of the existing data search units included in the extracted energy consumption measurement value data. And a display processing unit.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to add and display an additional data search unit as a data search unit of extraction energy consumption measured value data, without changing a database, and a user uses an additional data search unit. Thus, energy consumption can be analyzed from various angles.

Embodiment 1 FIG.
FIG. 1 is a diagram illustrating a system configuration example including an information processing apparatus according to the present embodiment.
In FIG. 1, the information processing apparatus 100 acquires energy consumption measurement value data (hereinafter simply referred to as energy consumption data) collected by the energy consumption data collection tool 201 of the measurement target base 200 via the network 300, Search, aggregate, and display energy consumption data according to user requests.

The measurement target base 200 is a facility that measures energy consumption, and is, for example, a commercial facility such as an office building, a factory, or a shopping mall.
In FIG. 1, for simplicity of explanation, only one measurement target base 200 is displayed, but the information processing apparatus 100 can target a plurality of measurement target bases 200.

The energy consumption data collection tool 201 is a tool for measuring and collecting energy consumption data at the measurement target base 200.
The energy consumption data collected by each energy consumption data collection tool 201 is aggregated and transmitted to the information processing apparatus 100 via the network 300.

  In the information processing apparatus 100, the energy consumption data reception unit 1 receives energy consumption data collected by the energy consumption data collection tool 201 from the network 300.

The energy consumption database 2 stores the energy consumption data received by the energy consumption data receiving unit 1 and creates a database.
The energy consumption data stored in the energy consumption database 2 has a plurality of types of analysis axes (data search units) in advance. An analysis axis included in advance in energy consumption data stored in the energy consumption database 2 is referred to as an existing analysis axis (existing data search unit).
In the present embodiment and the following embodiments, the analysis axis is meant to include both the user axis added based on the user axis information 11 and the existing analysis axis.

  The preprocessing unit 1 (3) extracts energy consumption data to be analyzed, and processes the extracted energy consumption data.

The pre-processing unit 2 (4) is a processing unit that generates information necessary for displaying energy consumption data in a GUI (Graphical User Interface) unit 5.
Specifically, the preprocessing unit 2 (4) is defined in the user axis information 11 described later with respect to the energy consumption data (extracted energy consumption measurement value data) extracted by the preprocessing unit 1 (3). Specify the user axis.
The preprocessing unit 2 (4) is an example of a data processing unit.

The GUI unit 5 receives a request from a user and displays a result of counting energy consumption data and an evaluation result.
The GUI unit extracts the user axis specified by the preprocessing unit 2 (4) together with any of the existing analysis axes included in the energy consumption data extracted by the preprocessing unit 1 (3), and extracts the energy consumption data extracted Display as the analysis axis.
The GUI unit is an example of a display processing unit.

The engine unit 6 calculates data and calculates a result.
Specifically, the engine unit 6 is added by the preprocessing unit 2 (4) when a data search / aggregation of energy consumption data for any of the analysis axes displayed by the GUI unit 5 is requested. Data search and aggregation are performed using the user axis or existing analysis axis.
The engine unit 6 is an example of a data search unit.
Further, as described in the second embodiment, the engine unit 6 is also an example of a data comparison unit.

The definition information storage unit 7 stores user axis information 11 (definition information).
The user axis information 11 is information relating to an axis serving as a data display.
In other words, the user axis information 11 is information that defines an analysis axis (data search unit) that is different from any of the existing analysis axes included in the energy consumption data as a user axis (additional data search unit).

The energy consumption data for analysis 8 is data to be displayed on the GUI unit 5.
The energy consumption data 8 for analysis is data after the energy consumption data extracted by the preprocessing unit 1 (3) is processed by the preprocessing unit 2 (4).
The analysis axis setting information 9 is generated by the preprocessing unit 2 (4) and is information related to the analysis axis in the GUI unit 5.
The GUI unit setting information 10 is setting information for the GUI unit 5. The GUI unit setting information 10 is, for example, information for designating a layout or the like for displaying the screen shown in FIG. 3, and is default information.
The analysis energy consumption data 8, the analysis axis setting information 9, and the GUI unit setting information 10 are information used for display by the GUI unit 5, and are stored in a storage area (register or the like) for GUI display.

An example of visualization by the GUI unit 5 is shown in FIG.
In FIG. 3, 20 is an analysis axis, and 21 is an analysis axis item list existing in the analysis axis. When the user selects any analysis axis item shown in the analysis axis item list 21, it becomes a condition, and the total result is displayed on the energy consumption data display part 22.
For example, when “air conditioner” is selected in the analysis axis item list 21, a tabulation result of data meeting the condition “area = air conditioner” is displayed.
Thus, the analysis axis is a unit in which the user designates search and aggregation of energy consumption data, and is an example of a data search unit. The analysis axis includes a plurality of analysis axis items that are constituent elements (breakdowns). These analysis axis items are examples of a plurality of data search items that are constituent elements of a data search unit. It is.
Also, as shown in FIG. 3, analysis axis items that are constituent elements of each axis are displayed in correspondence with each axis of the analysis axis.
In addition, when “Maximum Value” is selected from the aggregation method designation menu 24 in the aggregation method designation part 23 in FIG. 3, the transition of the maximum value of energy consumption can be seen, and the energy consumption at the peak time can be checked. It is effective when

An example of the analysis axis setting information 9 for displaying the screen of FIG. 3 is shown in FIG.
In this file, axis information displayed on the analysis axis 20 in FIG. 3 is defined.
In the analysis axis setting information 9 in FIG. 4, the “month” axis, “day” axis, “time” axis, “day of week” axis, and “power consumption” axis are energy consumption data stored in the energy consumption database 2. It is an existing analysis axis that exists in advance and is an example of an existing data search unit.
On the other hand, in the analysis axis setting information 9 in FIG. 4, “Attendance” axis, “Area” axis, “Use” axis, and user axis not included in the energy consumption data stored in the energy consumption database 2 These are the axes added in the user axis information 11. The user axis is an example of an additional data search unit.
Each axis definition section defines items as a breakdown of each axis. For example, “5, 6, 7... 4” is defined as a component of the “month” axis in the “month” axis definition unit. Similarly, “1F, 2F, 3F, 4F, and 5F” are defined as components of the “area” axis in the “area” axis definition unit.
The component of the user axis is called a user axis item, and is an example of the additional data search item that is a component of the additional data search unit.
In the analysis axis setting information 9, each axis and the analysis axis item of each axis are associated with each other by a pointer, for example.

Moreover, the example of the energy consumption data 8 for analysis at the time of performing the display of the GUI part 5 shown in FIG. 3 is shown in FIG.
The analysis axis setting information 9 shown in FIG. 4 is based on an arbitrary item included in the energy consumption data 8 for analysis.
The analysis energy consumption data 8 in FIG. 5 includes the user axes “Attendance Day”, “Area”, and “Use” analysis axes, and the user axes that are the components of each axis. Items “holiday”, “5F”, “lighting power”, and the like are shown.

FIG. 14 shows an example of energy consumption data stored in the energy consumption database.
As shown in FIG. 14, the energy consumption data stored in the energy consumption database includes a plurality of management units. In the example of FIG. 14, the management unit includes date, month, day, time, day of the week, model name, group name measurement point name, power consumption, and measurement point number. An arbitrary management unit in these management units becomes an existing analysis axis (existing data search unit).
For example, as shown in FIG. 3, the management units “month”, “day”, “time”, and “day of the week” are management units used as existing analysis axes. On the other hand, the energy consumption data stored in the energy consumption database does not include the user axis “attendance date”, “area”, and “use” which are additional data search units.
Further, the energy consumption data shown in FIG. 14 includes measurement point numbers not included in FIG.
The points that can be measured by the energy consumption data collection tool 201 are common in any building, and are near the power source for each application on each floor.
The point where the energy consumption data collection tool 201 is installed is referred to as an energy consumption measurement point, and is also referred to as a measurement point for brevity.
The measurement point number shown in FIG. 14 is an identifier of each measurement point. The number of the measurement point is an example of an energy consumption measurement point identifier.
A setting file that defines the user axis based on the measurement point number is the user axis information 11 stored in the definition information storage unit 7.

FIG. 10 shows an example of the user axis information 11.
In FIG. 10, user axis information 11 defines a user axis and a user axis item by an analysis axis (user axis), an analysis item (user axis item), and a measurement point number.
For example, the user axis information 11 defines the analysis items 1F, 2F, etc. as the breakdown of the analysis axis “area”, and also defines the measurement point numbers associated with the respective analysis items. A plurality of measurement point numbers can be designated.
The same applies to the analysis axis “use” and “influence of outside air”.
For example, when viewing the measurement point information for “the power consumption of the air conditioner on the first floor without windows” from the “Area” section at “1F”, when viewing at the “Application” section. In the case of “air conditioner” in “Usage”, when viewed from the section “influence of outside air”, it is defined to be viewed in “closed room” in “influence of outside air”.
In this way, by specifying “analysis axis, analysis item, measurement point number (multiple designation is possible)”, for example, when the equipment of the energy consumption data collection tool 201 is increased and the measurement points are increased, By adding information, analysis can be performed without changing the existing database.

The preprocessing unit 2 (4) includes the extracted energy consumption data (FIG. 14) when any energy consumption data is extracted from the energy consumption database 2 by the preprocessing unit 1 (3). Analysis item (user axis item) in the extracted energy consumption data based on the measured measurement point number and the measurement point number for each analysis item (additional data search item) shown in the user axis information 11 (FIG. 10) ) Is added to generate the energy consumption data 8 for analysis shown in FIG.
Thus, a new analysis axis that is not included in the energy consumption data of the energy consumption database 2 can be added by the preprocessing unit 2 (4).

Moreover, instead of the measurement point number in the user axis information 11 of FIG. 10, the user axis may be defined using other elements included in FIG.
For example, in order to add the “working day” shown in FIG. 4 as the user axis, it is possible to define the user axis using “day of the week” in FIG.
The user axis information 11 in this case defines “attendance day” as an analysis axis (user axis), “attendance day” and “holiday” as analysis items (user axis items), For example, “Monday, Tuesday, Wednesday, Thursday, Friday” is defined, and “Saturday, Sunday” is defined for “Holiday”.

Next, the operation will be described.
First, the energy consumption data collected by the energy consumption data collection tool 201, received by the energy consumption data receiving unit 1, stored in the energy consumption database 2, and the user axis information 11 stored in the definition information storage unit 7 Are processed by the pre-processing unit 1 (3) and the pre-processing unit 2 (4) to generate analysis energy consumption data 8, analysis axis setting information 9, and GUI unit setting information 10.
At this time, for example, in the user axis information 11, the analysis items related to the measurement point numbers of the energy consumption data on the energy consumption database 2 are set to “area” (eg, 1F, 2F, 3F,...), “Use” ( Example: Air conditioner, lighting, etc.) “Influence of outside air” (Example: near entrance / exit, closed room, window room, etc.) Define definitions to show one piece of information in various cuts.
Thus, the energy consumption for analysis generated by the pre-processing unit 2 (4) having the function of processing the user axis information 11 by defining the analysis axis (section for showing data) with the user axis information 11 from the viewpoint of energy saving. Based on the data 8, the analysis axis setting information 9, and the GUI unit setting information 10, the user performs analysis through the visualization unit of the GUI unit 5.

Next, an operation example of the information processing apparatus 100 will be described with reference to FIG.
First, as a premise, the energy consumption database 2 stores, for example, energy consumption data including a plurality of types of existing analysis axes and measurement point numbers as shown in FIG. 14, and the definition information storage unit 7 stores, for example, Suppose that user axis information in which a measurement point number is designated for an analysis axis (user axis) and an analysis item (user axis item) as shown in FIG. 10 is stored.

First, a user requests extraction of energy consumption data using an input device such as a mouse or a keyboard, and the GUI unit 5 inputs a data extraction request (S201).
In this data extraction request, for example, if there are a plurality of extraction target periods or a plurality of measurement target bases, the measurement target bases to be extracted are specified.

Next, the preprocessing unit 1 (3) extracts the corresponding energy consumption data from the energy consumption database 2 in accordance with the data extraction request (S202).
The extracted energy consumption data is hereinafter referred to as extracted data.
As described above, the extracted data includes a plurality of types of existing analysis axes and measurement point numbers, but does not include a user axis.

Next, the preprocessing unit 2 (4) acquires the extracted data from the preprocessing unit 1 (3), acquires the user axis information 11 from the definition information storage unit 7, the user axis included in the user axis information 11, Based on the user axis item, the existing analysis axis included in the extracted data, and the analysis axis item, for example, analysis axis setting information 9 as shown in FIG. 4 is generated (S203).
The preprocessing unit 2 (4) determines which management unit of the energy consumption information management unit is the existing analysis axis and what analysis axis items are included as components of the existing analysis axis. It can be recognized from the data generated by the preprocessing unit 1 (3) and the user axis information (11).
The pre-processing unit 2 (4) adds the user axis and user axis item shown in the user axis information 11 to the existing analysis axis and the analysis axis item which are the default information, and sets the analysis axis setting information. Generate.

Next, the preprocessing unit 2 (4) adds the user axis item to the extracted data based on the measurement point number included in the extracted data and the measurement point number indicated in the user axis information 11, and analyzes energy. Consumption data 8 is generated (S204).
For example, the measurement point number “5” is shown in the record in the second line of FIG. 14, whereas the measurement point number “5” is “area” in the user axis information 11 of FIG. ”,“ 2F ”,“ use ”, and“ air conditioner ”. Therefore, as shown in FIG. 5, the pre-processing unit 2 (4) adds “area”, “2F”, “use”, and “air conditioner” to the record in the second row, and uses energy for analysis. Data 8 is assumed.
For convenience of explanation, “influence of outside air” is not shown in FIG. 5, but “influence of outside air” can be added in the same procedure.
In addition, the user axis of “working day” described above may be added.
Then, the preprocessing unit 2 (4) sets the energy consumption data for analysis 8 and the analysis axis setting information 9 in a register for the GUI unit 5 or the like.
Further, the pre-processing unit 2 (4) acquires GUI unit setting information for displaying the screen shown in FIG. 3 on the GUI unit 5 from a storage area not shown, and similarly for the GUI unit 5 Set to the register etc.

Finally, the GUI unit 5 displays, for example, the screen shown in FIG. 3 using the analysis energy consumption data 8, the analysis axis setting information 9, and the GUI unit setting information 10 (S205).
At this timing, nothing may be displayed on the energy consumption data display part 22 of FIG.
At least an analysis axis 20 and an analysis axis item list 21 corresponding to each analysis axis are displayed.

When an arbitrary analysis axis item is selected by the user (multiple selection is possible), the engine unit 6 searches and aggregates corresponding data according to the selected analysis axis item, and the aggregation result is obtained by the GUI unit 5. Is displayed.
Note that the search and aggregation of data according to the selected analysis axis item by the engine unit 6 can be realized by an existing database technology.
Also, extraction of energy consumption data from the energy consumption database 2 by the preprocessing unit 1 (3) can be realized by existing database technology.

Also, a plurality of pieces of analysis axis setting information 9 can be set for one analysis energy consumption data 8.
FIG. 6 shows an example of the screen, and FIG. 7 shows an example of the analysis axis setting information 9.
The axis information defined in FIG. 7 is the analysis axis 30 in FIG.
In the example of FIGS. 6 and 7, only “area” and “use” are displayed as the user axis. Further, in the examples of FIGS. 3 and 4, the “day” axis included as the existing analysis axis is deleted.
In this case, the “day” axis is defined in the definition information as an existing analysis axis (deleted data search unit) to be deleted. The definition information in this case may be the user axis information 11 or other types of definition information.
The preprocessing unit 2 (4) generates analysis axis setting information 9 excluding the “day” axis in accordance with the definition of the definition information for the extracted data.
The GUI unit 5 does not display the “day” axis because it is not included in the analysis axis setting information 9 even if it is an existing analysis axis.

In this way, by changing the appearance of the GUI unit 5 by setting the analysis axis setting information 9, it is possible to create an environment according to the user's situation and purpose.
Then, by omitting unnecessary information and displaying necessary information (axis), it becomes possible to analyze without depending on the skill of the user.

If you want to see the data at a different angle, define a new user axis with the user axis information 11, perform the processing with the preprocessing unit 1 (3) and the preprocessing unit 2 (4), and use the energy consumption data for analysis. 8. It is also possible to regenerate the analysis axis setting information 9 and the GUI unit setting information 10 and add a new axis for analysis. That is, you may make it add the definition information change part which changes the user axis information 11 (definition information) to the information processing apparatus 100 shown in FIG.
In this case, there is no need to change the energy consumption data stored in the energy consumption database 2 or to modify the settings of the energy consumption data collection tool 201.

  As described above, by selecting various conditions, it becomes possible to link to specific energy saving activities by grasping factors that have particularly large energy consumption and factors that do not have an influence.

  In addition to the results of aggregation / analysis of average values, it is possible to grasp the status of maximum energy consumption by performing the same operation for the maximum value. It is effective for any energy-saving activities that reduce energy consumption.

Furthermore, the effect verification when the energy saving activity is advanced can be realized in the present embodiment.

As described above, in the present embodiment, the energy data analysis method for energy saving using the measured energy consumption data, analysis axis setting information, and other setting files as input data has been described.
And this analysis method provides the function to expand any item of energy consumption data to multiple analysis axes, and uses the analysis axis setting information including the expanded analysis axes to To show energy consumption from various angles.

Embodiment 2. FIG.
In the present embodiment, on the screen visualized by the GUI unit 5, as shown in FIG. 8, the similarity with the basic pattern under each condition is calculated in a state where the transition of the basic pattern is shown, and the color shading is calculated. Provides the functions expressed in
The function of calculating such similarity is provided by the engine unit 6.

Here, the basic pattern is data (model energy transition data) indicating a model of temporal transition of energy consumption. Basic patterns include, for example, data on the total energy consumption of an entire office building, data on average energy consumption over the past several years in the same office building, and average energy consumption over the same period in the same type of office building Model data to be compared.
On the other hand, the data to be compared with the basic pattern by the engine unit 6 is the time transition of the energy consumption generated by using any analysis axis displayed by the GUI unit 5 with respect to the extracted data. It is the data shown, and is the actual data (actual energy transition data) of energy consumption. For example, energy consumption data for a specific use in one office building, energy consumption data for a specific area in one office building, and the like.
By analyzing the similarity shown in FIG. 8, the user can know how much the actual energy consumption data is similar to the basic pattern, which is model data, and obtain guidelines for energy conservation measures. Can do.

In FIG. 8, as indicated by 41, the darker portion of the analysis axis items is a condition with lower similarity.
For example, in the application, the actual value of the energy consumption of the outlet and the lighting power is low in similarity with the basic pattern (for example, the total energy consumption of the entire office building).

  When calculating the degree of similarity, the difference in value (average value if displayed as an average value, maximum value if displayed as a maximum value is compared with the absolute value of the reference pattern), slope (average value) There is a method such as a mean value transition when displayed, a maximum value transition when displayed at the maximum value, and a total value of differences from the reference pattern of the inclination of adjacent coordinates). In order to find a similar pattern based on the shape of the graph, the similarity based on the slope is calculated.

  The user uses the analysis axis with the most similar degree of similarity (analysis axis with shading variation, for example, “use” is more dissimilar than the analysis axis “day”) because of the similar pattern. Promote trend analysis and energy conservation measures in each pattern as the axis of Trend analysis in each pattern can be performed by selecting 41 other items and performing recalculation display by adding conditions.

The information processing apparatus 100 can also display a graph of another condition while always displaying the basic pattern.
For example, it is possible to compare and display the total result 51 of the basic pattern and the total result 52 when the condition 50 is given on the condition 50 (outlet) in FIG.
Since the similarity is a relative value, comparative display is effective when actually confirming the shape of the graph in each pattern.
If the degree of similarity is different but the shape of the graph is not significantly different, the patterns may be combined into one similar pattern.

In the state of FIG. 9, when 53 other item items (for example, “1F” of “Area”) are selected, it is possible to display the total result with the condition added (that is, the outlets arranged in 1F) Only energy consumption data is displayed).
In this way, it is possible to analyze a pattern different from the basic pattern.
When the button 54 is pressed, the totaling result at that time is stored as a selection condition in 55.
An example in which the tabulation results are stored in 55 is shown in FIG.

  Thus, by proceeding with the analysis divided into similar patterns, it is possible to plan an appropriate energy saving activity according to the situation and to verify the result of the activity.

  As described above, in the present embodiment, the energy data analysis method for energy saving that can check the energy consumption status for each pattern by obtaining a condition having a similarity different from the reference pattern has been described.

Embodiment 3 FIG.
In the present embodiment, a method when the energy consumption database 2 collected by the energy consumption data collection tool 201 exists and the user axis information 11 and the analysis axis setting information 9 are created will be described.
Specifically, the following procedure is followed.

1. The user defines the following in the user axis information 11. In addition, there is no need to define 1.3 and 1.4.
1.1 Area (1F, 2F, etc. for the same building with multiple floors, 1 building, 2 buildings, etc. for each building)
1.2 Applications (information that can be identified at measurement points, such as air conditioning and lighting)
1.3 Effects of outside air and windows (near entrances, windows, closed rooms, etc.)
1.4 Influence of the flow of people (customer service floor, warehouse, break room, room assuming the entry and exit of a specific person, common meeting room, etc.)

  2. In the preprocessing unit 1 (3) and the preprocessing unit 2 (4), in addition to the above analysis axis, the user defines items (maximum all items) included in the energy consumption database 2 as analysis axes. The analysis axis setting information 9 is as follows.

3. The user displays the transition of the day as an average value of energy consumption according to the present invention, and calculates the difference between the reference value and the similarity according to the present invention. The user selects an axis including item items with low similarity and high energy consumption.
4). The user displays the transition of the day with the average value of the energy consumption in the present invention, and the user selects the axis including the item item with the highest peak time.
5. The user displays the transition of the day with the maximum value of energy consumption in the present invention, and calculates the difference between the reference value and the similarity. The user selects an axis including item items with low similarity and high energy consumption.
6). The user displays the transition of the day with the maximum value of energy consumption in the present invention, and the user selects the axis including the item item whose maximum value increases.
The axis selected in the above 3 to 6 as the analysis axis is set as the analysis axis setting information 9 and the information including the application type, scale, and region is added as the item axis table information.

In creating the item axis table, the user adds information on the application type, scale, and region to the item axis information obtained above.
In addition, information for discriminating the user axis information 11 and the analysis axis setting information 9, derivation source information when the user axis information 11 and the analysis axis setting information 9 refer to other cases as original data, It includes the introduction effect when introduction effect information is obtained.
An example of the item axis table is shown in FIG.

With this method, an axis including item items that affect energy consumption is set as an analysis axis, and the user of the analysis method of the present embodiment operates only the analysis axis that affects energy consumption. Thus, it is possible to grasp the energy consumption trend with less effort than when all axes are displayed.
Since analysis axes related to energy consumption are displayed in advance, there is no need to rely on user know-how.

  By proceeding with the energy saving activities of both the maximum value and the average value, when the energy consumption is electric power, it is possible to proceed with activities for both the contracted electric energy and the total electric energy consumption.

  When determining the analysis axis, it is only necessary to change the file of the user axis information 11 and the analysis axis setting information 9, so that the operation can be performed without rewriting the database information ("energy consumption database 2 information").

In the present embodiment, the method of selecting the item axis under the following conditions and proceeding with the energy saving analysis has been described.
Adding analysis axes,
The transition of the average value of energy consumption is displayed, and the difference between the reference value and the similarity is calculated. Axis containing item items that have a lower similarity and a higher average energy consumption than the reference value when compared with the reference value.
An axis that includes the item item that shows the transition of the average value of energy consumption and has the highest peak.
The transition of the maximum value of energy consumption is displayed, and the difference between the reference value and the similarity is calculated.
Axis containing item items that have lower similarity and higher maximum energy consumption than the reference value when compared with the reference value.
Axis with item items that show the transition of the maximum value of energy consumption and the maximum value increases,
Based on the item information selected above, the energy status of the affected item is confirmed.

Embodiment 4 FIG.
The analysis axis table created in the second embodiment when the user provides the energy data analysis method for energy saving described in this specification as a service to the energy saving activity target person or when the user proceeds with the energy saving activity target person. It is possible to provide an appropriate analysis environment by extracting the analysis axis information from the data and applying it with customization according to the situation of the energy conservation activity target person.

Here, the customization according to the situation of the energy saving activity target person is the following two points.
1. For example, in the case of the “Area” axis, 8F and 9F item items are added according to the height of the building, and in the case of the “use” axis, a separate power supply is used for a special device. Add item items such as cases.
2. Update of Measurement Point Information The measurement point information is each measurement point of the “energy consumption data collection tool” 1. Since the measurement points differ depending on the customer, it is necessary for the user to change according to the actual measurement.

  As a result, the effect of reducing the labor for setting the analysis axis when the user deploys to the energy conservation activity target, and the information about the analysis axis and the energy conservation effect when the user deploys to the energy conservation activity target This leads to the accumulation of energy-saving know-how.

  In addition, when viewed from the user, it is possible to expect an effect that the skill for setting the analysis axis is unnecessary.

For example, as shown in FIG. 12, the types of energy saving activity target persons to which the energy saving system is applied are classified as “factory”, “office”, “commercial facility”, etc., depending on the energy consumption form.
If there is an application example in which analysis axes are set for each category, it is possible to customize and apply analysis axis information that has already been created when setting analysis axes for other cases belonging to the same category. is there.
In this way, users can categorize the analysis axis information according to the difference in energy consumption form and utilize the analysis axis information of highly effective application examples, thereby reducing the labor for new applications and at the same time expecting high effects can do.

In the present embodiment, a method has been described in which the item axis information is obtained by adding the application type, scale, and region information of the analysis source to the item axis information.
Thus, when providing energy-saving services to energy-saving activity target persons or when the energy-saving activity target persons introduce the systems shown in the first to third embodiments, by applying items that match in the item axis table, it is possible to save energy. It becomes possible to provide an analysis system for energy saving that is most suitable for the target person.
When matching in the analysis axis table, priority is given to the application type, and the area and scale information need not match.

Finally, a hardware configuration example of the information processing apparatus 100 shown in the first to fourth embodiments will be described.
FIG. 15 is a diagram illustrating an example of hardware resources of the information processing apparatus 100 illustrated in the first to fourth embodiments. Note that the configuration in FIG. 15 is merely an example of the hardware configuration of the information processing apparatus 100, and the hardware configuration of the information processing apparatus 100 is not limited to the configuration illustrated in FIG. Also good.

In FIG. 15, the information processing apparatus 100 includes a CPU 911 (also referred to as a central processing unit, a central processing unit, a processing unit, an arithmetic unit, a microprocessor, a microcomputer, and a processor) that executes a program. The CPU 911 is connected to, for example, a ROM (Read Only Memory) 913, a RAM (Random Access Memory) 914, a communication board 915, a display device 901, a keyboard 902, a mouse 903, and a magnetic disk device 920 via a bus 912. Control hardware devices. Further, the CPU 911 may be connected to an FDD 904 (Flexible Disk Drive), a compact disk device 905 (CDD), a printer device 906, and a scanner device 907. Further, instead of the magnetic disk device 920, a storage device such as an optical disk device or a memory card read / write device may be used.
The RAM 914 is an example of a volatile memory. The storage media of the ROM 913, the FDD 904, the CDD 905, and the magnetic disk device 920 are an example of a nonvolatile memory. These are examples of a storage device or a storage unit.
The communication board 915, the keyboard 902, the scanner device 907, the FDD 904, and the like are examples of an input unit and an input device.
Further, the communication board 915, the display device 901, the printer device 906, and the like are examples of an output unit and an output device.

As shown in FIG. 1, the communication board 915 is connected to a network. For example, the communication board 915 may be connected to a LAN (local area network), the Internet, a WAN (wide area network), or the like.
The magnetic disk device 920 stores an operating system 921 (OS), a window system 922, a program group 923, and a file group 924. The programs in the program group 923 are executed by the CPU 911, the operating system 921, and the window system 922.

The program group 923 stores programs for executing the functions described as “˜units” in the description of the first to fourth embodiments. The program is read and executed by the CPU 911.
In the file group 924, in the description of the first to fourth embodiments, “determination of”, “calculation of”, “comparison of”, “evaluation of”, “update of”, “setting of” ”,“ Registration of ”,“ search for ”,“ extraction of ”,“ aggregation of ”, etc., information, data, signal values, variable values, and parameters indicating the results of the processing are“ It is stored as each item of "~ file" and "~ database". The “˜file” and “˜database” are stored in a recording medium such as a disk or a memory. Information, data, signal values, variable values, and parameters stored in a storage medium such as a disk or memory are read out to the main memory or cache memory by the CPU 911 via a read / write circuit, and extracted, searched, referenced, compared, Used for CPU operations such as calculation, calculation, processing, editing, output, printing, and display. Information, data, signal values, variable values, and parameters are stored in the main memory, registers, cache memory, and buffers during the CPU operations of extraction, search, reference, comparison, calculation, processing, editing, output, printing, and display. It is temporarily stored in a memory or the like.
In addition, arrows in the flowcharts described in the first to fourth embodiments mainly indicate input / output of data and signals, and the data and signal values are the RAM 914 memory, the FDD 904 flexible disk, the CDD 905 compact disk, and the magnetic field. Recording is performed on a recording medium such as a magnetic disk of the disk device 920, other optical disks, mini disks, DVDs, and the like. Data and signals are transmitted online via a bus 912, signal lines, cables, or other transmission media.

  In addition, what is described as “to part” in the description of Embodiments 1 to 4 may be “to circuit”, “to device”, and “to device”, and “to step”. , “˜procedure”, and “˜processing”. That is, what is described as “˜unit” may be realized by firmware stored in the ROM 913. Alternatively, it may be implemented only by software, or only by hardware such as elements, devices, substrates, and wirings, by a combination of software and hardware, or by a combination of firmware. Firmware and software are stored as programs in a recording medium such as a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, and a DVD. The program is read by the CPU 911 and executed by the CPU 911. That is, the program causes the computer to function as “to part” in the first to fourth embodiments. Alternatively, the computer executes the procedure and method of “to unit” in the first to fourth embodiments.

  As described above, the information processing apparatus 100 described in the first to fourth embodiments includes a CPU as a processing device, a memory as a storage device, a magnetic disk, a keyboard as an input device, a mouse, a communication board, and a display device as an output device and a communication device. A computer including a board or the like, and implements the functions indicated as “to part” as described above using these processing devices, storage devices, input devices, and output devices.

2 is a diagram illustrating a configuration example of an information processing device according to Embodiment 1. FIG. FIG. 3 is a flowchart showing an operation example of the information processing apparatus according to the first embodiment. FIG. 4 shows a screen display example according to the first embodiment. FIG. 6 is a diagram illustrating an example of analysis axis setting information according to the first embodiment. The figure which shows the example of the energy consumption data for analysis which concerns on Embodiment 1. FIG. FIG. 4 shows a screen display example according to the first embodiment. FIG. 6 is a diagram illustrating an example of analysis axis setting information according to the first embodiment. FIG. 6 shows a screen display example according to the second embodiment. FIG. 6 shows a screen display example according to the second embodiment. FIG. 6 is a diagram showing an example of user axis information according to the first embodiment. The figure which shows the example of storage display of the total result which concerns on Embodiment 2. FIG. FIG. 10 is a diagram illustrating an example of customization according to the fourth embodiment. FIG. 10 shows an example of an item axis table according to the third embodiment. FIG. 4 shows an example of energy consumption data according to the first embodiment. FIG. 3 is a diagram illustrating a hardware configuration example of the information processing apparatus according to the first to fourth embodiments.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 Energy consumption data receiving part, 2 Energy consumption database, 3 Preprocessing part 1, 4 Preprocessing part 2, 5 GUI part, 6 Engine part, 7 Definition information storage part, 8 Analysis energy consumption data, 9 Analysis axis setting information 10 GUI section setting information, 11 User axis information, 100 Information processing device, 200 Measurement target base, 201 Energy consumption data collection tool, 300 Network.

Claims (9)

A database for storing energy consumption measurement data with multiple types of data search units;
A definition information storage unit that stores definition information that defines a data search unit that is different from any of the multiple types of existing data search units included in the energy consumption measurement value data as an additional data search unit;
Data processing for designating additional data search units defined in the definition information for the extracted extracted energy consumption measurement value data when any of the energy consumption measurement value data is extracted from the database And
The additional data search unit designated by the data processing unit is displayed as a data search unit of the extracted energy consumption measurement value data together with at least one of the existing data search units included in the extracted energy consumption measurement value data. An information processing apparatus comprising: a display processing unit. The definition information storage unit
For each additional data search unit, store definition information defining a plurality of additional data search items that are components of the additional data search unit,
The data processing unit
When any energy consumption measurement value data is extracted from the database, for the extracted extracted energy consumption measurement value data, specify an additional data search unit defined in the definition information, Specify a plurality of additional data search items of the additional data search unit,
The display processing unit
The additional data search unit specified by the data processing unit is displayed, and a plurality of additional data search items specified by the data processing unit are displayed in correspondence with the display of the additional data search unit. The information processing apparatus according to claim 1. The display processing unit
Displaying at least one existing data search unit of the plurality of types of existing data search units and the additional data search unit as a data search unit of the extracted energy consumption measurement value data, and extracting the extracted energy consumption measurement value data As a data search item, a plurality of data search items included in the existing data search unit to be displayed are displayed in correspondence with the display of the existing data search unit to be displayed, and the plurality of additional data search items are added to the display The information processing apparatus according to claim 2, wherein the information processing apparatus displays data corresponding to display of a data search unit. The definition information storage unit
Stores definition information that defines any of the multiple types of existing data search units included in the energy consumption measurement data as a deleted data search unit,
The data processor
When any of the energy consumption measurement value data is extracted from the database, the deleted data search unit defined in the definition information is specified for the extracted extracted energy consumption measurement value data,
The display processing unit
The information processing apparatus according to claim 1, wherein the deletion data search unit designated by the data processing unit is not displayed as a data search unit of the extracted energy consumption measurement value data. The data processing unit
When any energy consumption measurement value data is extracted from the database, an additional data search item is added to the extracted energy consumption measurement value data based on the data value included in the extracted extraction energy consumption measurement data. Add
The information processing apparatus further includes:
When a data search of the extracted energy consumption measurement value data is requested for any additional data search item displayed by the display processing unit, the additional data search item added by the data processing unit is used. The information processing apparatus according to claim 3, further comprising a data search unit that performs data search of the extracted energy consumption measurement value data. The database is
Stores energy consumption measurement value data that includes an energy consumption measurement point identifier that indicates the energy consumption measurement point at which the energy consumption was measured,
The definition information storage unit
For each additional data search item, the definition information defining the corresponding energy consumption measurement point identifier is stored,
The data processing unit
When any energy consumption measurement value data is extracted from the database, the energy consumption measurement point identifier included in the extracted energy consumption measurement data and the additional data search item indicated in the definition information 6. The information processing apparatus according to claim 5, wherein a corresponding additional data search item is added to the extracted energy consumption measurement value data based on the energy consumption measurement point identifier. The information processing apparatus further includes:
The actual energy transition data indicating the temporal transition of the energy consumption generated using any of the data search items displayed by the display processing unit with respect to the extracted energy consumption measurement value data, the energy consumption A data comparison unit that compares the model energy transition data with the model energy transition data, and calculates the degree of similarity between the actual energy transition data and the model energy transition data,
The display processing unit
The information processing apparatus according to claim 2 or 3, wherein the similarity calculated by the pattern comparison unit is displayed for a data search item used for generating the actual energy transition data. The information processing apparatus further includes:
The information processing apparatus according to claim 1, further comprising: a definition information changing unit that changes the contents of the definition information stored in the definition information storage unit. The definition information storage unit
At least one of the installation floor of the energy consumption measurement point in the building where the energy consumption is measured, the use of the equipment where the energy consumption measurement point is installed, and the influence of outside air at the installation location of the energy consumption measurement point 7. The information processing apparatus according to claim 6, wherein definition information that defines an additional data search unit is stored.

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