JP6186404B2 - Energy consumption prediction apparatus and energy consumption prediction method - Google Patents

Description

  The present invention relates to an energy consumption prediction apparatus and an energy consumption prediction method, and more particularly to an energy consumption prediction apparatus and an energy consumption capable of predicting energy consumption for air conditioning in a predetermined floor of a multi-storey building. It relates to a quantity prediction method.

  Today, where building energy conservation is rapidly progressing, how to reduce energy consumption in the building is the user of the building or who is planning to use it (hereinafter referred to as "users"). Is a place of great interest. On the other hand, when promoting energy saving, it is important to grasp the effect (that is, the energy reduction effect). Further, in order to grasp the effect of energy saving, it is necessary to predict the energy consumption amount consumed by the user or the like in the building and the fee (utility cost) corresponding to the energy consumption amount. Here, the ratio of the energy consumption for air conditioning in the energy consumption in the building is relatively large. For this reason, a technology for predicting energy consumption (and / or air conditioning load) for air conditioning has been developed so far (see, for example, Patent Document 1).

  In the technique described in Patent Document 1, information regarding the specification of a building and information regarding a user of the building are used as input values, and an air conditioning load in the building is calculated based on the input values. Here, the information related to the “building specification” includes information related to the floor plan of the building. That is, according to the technique described in Patent Document 1, it is possible to calculate the air conditioning load in the building in consideration of the floor plan of the building.

JP 2003-343894 A

  However, Patent Document 1 does not specifically describe how to deal with information related to the floor plan in actual calculation, although the floor plan of the building is taken into account when predicting the air conditioning load of the building. On the other hand, as a method of calculating the air conditioning load in consideration of the floor plan, for example, a method of modeling the structure of the entire building including the floor plan and calculating the air conditioning load based on the set value (parameter) obtained as a result is conceivable. . However, when the air conditioning load is calculated by such a method, modeling is performed every time the structure of the building to be calculated changes. In addition, there are multi-storey buildings in the building, and it is necessary to consider the number of floors in addition to the floor plan when calculating the air conditioning load for such multi-storey buildings. However, when modeling the structure of the entire building while changing both the floor plan and the number of floors, the setting value obtained by the modeling becomes enormous, resulting in a significant increase in the data capacity of the setting value. There is.

  Therefore, the present invention has been made in view of the above-described problems, and the object of the present invention is to predict energy consumption for air conditioning in consideration of floor plan and floor number with a smaller data capacity. An energy consumption prediction apparatus and an energy consumption prediction method are provided.

According to the energy consumption predicting apparatus of the present invention, the problem is an energy consumption predicting apparatus that predicts the energy consumption for air conditioning in a specific floor where a plurality of rooms are arranged in a multi-storey building. (A) a candidate presentation unit that presents candidates to the user for each of the floors of the specific floor and the floor plan on the specific floor; and (B) accepts a user's designation operation performed on the candidates. An operation receiving unit, (C) a storage unit that stores a correspondence relationship between the floor plan indicated by the candidate and the air conditioning load on the specific floor when the floor plan is adopted, and (D) the A process execution unit that executes a prediction process for predicting the energy consumption for air conditioning on a specific floor, and (E) the process execution unit is stored in the storage unit in the prediction process The air conditioning load when the floor plan indicated by the candidate specified by the designation operation is adopted from the correspondence relationship associated with the floor indicated by the candidate designated by the designation operation among the correspondence relationships And predicting the energy consumption for air conditioning on the specific floor from the air conditioning load , and (F) determining the energy consumption for air conditioning in the case where each of a plurality of groups uses the specific floor different from each other. In order to make a prediction for each group, the operation reception unit performs the user to specify the candidates indicating the floor number and the floor plan of the specific floor used by each group by the number of the groups. Receiving the designation operation, the process execution unit is solved by executing the prediction process for each group .

In the energy consumption prediction apparatus of the present invention configured as described above, the correspondence between the floor plan and the air conditioning load on the specific floor when the floor plan is adopted is stored in the storage unit for each floor of the specific floor. . Then, among the correspondence relationships stored in the storage unit, the air conditioning load on the specific floor is identified based on the correspondence relationship between the floor plan and the floor number of the specific floor, and the energy consumption for air conditioning on the specific floor is determined from the identification result. Predict the amount. Thereby, when estimating the energy consumption for air conditioning in a specific floor, it becomes possible to predict in consideration of the floor plan and the number of floors of a specific floor.
Further, in the energy consumption prediction apparatus of the present invention, the set value of the air conditioning load is set by the number corresponding to the number of types of floor plans and the number of floors of the building. In such a configuration, since the setting value of the air conditioning load is reduced as compared with the case of obtaining the setting value of the air conditioning load by modeling the structure of the entire building while changing both the floor plan and the floor number, Data capacity is reduced. That is, according to the energy consumption prediction apparatus of the present invention, when predicting the energy consumption for air conditioning on a specific floor in consideration of the floor plan and the number of floors, it is possible to predict with a smaller data capacity. Become.

Moreover, in the energy consumption prediction apparatus, the storage unit has table data that defines the air conditioning load for each predetermined time on the specific floor when the floor plan is adopted as the correspondence relationship. It is preferable to store the data according to the rank.
According to the above configuration, the table data in which the air-conditioning load for each predetermined time on the specific floor is determined for each floor plan is stored for each floor, so by referring to the table data, in the specific floor within the predetermined time It becomes possible to appropriately predict the amount of energy consumed for air conditioning.
Furthermore, according to said structure, in the case where each of a some group utilizes a mutually different specific floor, it becomes possible to estimate the energy consumption for an air conditioning for every group. Further, when predicting the energy consumption for air conditioning by group, the user designates the number of candidates indicating the number of floors and the floor plan of a specific floor used by each group in one designation operation. That is, candidate designations for all groups can be performed together in one designation operation. Thereby, the user can perform the above-described designation operation more easily.

In the energy consumption prediction apparatus, the candidate presentation unit presents the candidate to the user for each of the floor number, the floor plan, and the user attribute of the specific floor, and the storage unit The correspondence relationship is stored in association with the attribute, and the process execution unit includes the candidate indicated by the candidate specified in the designation operation among the correspondence relationship stored in the storage unit in the prediction process. Preferably, the air conditioning load is specified from the correspondence relationship associated with the attribute, and the energy consumption for the air conditioning at the specific floor is predicted from the air conditioning load.
According to the above configuration, the correspondence between the floor plan and the air conditioning load is stored in association with the attribute of the user on the specific floor. Accordingly, it is possible to predict the energy consumption for air conditioning on the specific floor while taking into account the attributes of the user on the specific floor (more specifically, the lifestyle of the user that changes according to the attribute).

Further, in the energy consumption prediction apparatus, the candidates for the floor plan presented by the candidate presentation unit may be the same as each other in the types of the rooms constituting the floor plan, and in the specific floor It is preferable that a plurality of the candidates indicating the floor plan in which at least one of the arrangement position and area of the chambers is different from each other is included.
In the above configuration, the floor plan candidates include a plurality of candidates that have the same room type that constitutes the floor plan and that have different floor layouts and areas on a specific floor. Yes. Thereby, it is possible to predict the energy consumption for air conditioning on a specific floor for a plurality of floor plans of the same room type while considering the arrangement position and area of each room.

Further, in the energy consumption prediction apparatus, the operation reception unit is performed by a user to designate the candidate indicating the floor number of the specific floor used as a living space from the candidates of the floor number. It is preferable to accept the designation operation.
According to said structure, it becomes possible to estimate the energy consumption for the air conditioning in the specific floor which the user designated as a living space in consideration of the floor plan and the floor number of the said specific floor.

Further, in the energy consumption prediction apparatus, the process execution unit predicts the total energy consumption consumed by each group within a predetermined period by executing the prediction process for each group. It is preferable to calculate the utility cost for the predetermined period from the prediction result of the energy consumption for each group.
According to said structure, a utility bill is calculated from the estimated total energy consumption. In addition, the calculation of utility costs is performed for each group. Thereby, it becomes possible to grasp | ascertain the calculation result of the utility bill for every group.

Further, according to the energy consumption prediction method of the present invention, the above-described problem is that the computer predicts the energy consumption for air conditioning in a specific floor where a plurality of rooms are arranged in a multi-storey building. A method for predicting consumption, wherein (A) the computer presents candidates to the user for each of the number of floors on the specific floor and the floor plan on the specific floor, and (B) the computer A step of accepting a user's designated operation to be performed, and (C) a computer executing a prediction process of predicting the energy consumption for air conditioning in the specific floor, and (D) the prediction In the processing, the computer displays the correspondence relationship between the floor plan indicated by the candidate and the air conditioning load on the specific floor when the floor plan is adopted according to the number of floors of the specific floor. The stored storage unit is accessed, and among the correspondence relationships stored in the storage unit, the designation operation is designated by the correspondence relationship associated with the rank indicated by the candidate designated by the designation operation. The air conditioning load when the floor plan indicated by the candidate is adopted is identified, and the energy consumption for the air conditioning at the specific floor is predicted from the air conditioning load . (E) Each of the plurality of groups is different from each other In order to predict the energy consumption for the air conditioning for each group in the case of using the specific floor, the computer sets the candidates indicating the floor number and the floor plan of the specific floor used by each group. solution by the accepting designation operation performed by the user, executes the prediction process for each of the groups in order to specify the number of groups It is.
According to said method, it becomes possible to estimate the energy consumption for air conditioning in a specific floor in consideration of the floor plan of the specific floor and the number of floors with a smaller data capacity.

ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to estimate the energy consumption for air conditioning in the specific floor of a multi-storey building in consideration of the floor plan and the number of floors of the specific floor. Further, it is possible to further reduce the data capacity for storing the set value of the air conditioning load (strictly speaking, the correspondence relationship between the floor plan and the air conditioning load).
By producing the effects as described above, it becomes possible to more easily present the prediction results regarding the energy consumption for air conditioning and the utility cost to the building users and those who have the prospect. As a result, it is possible to proactively propose energy saving of the building, or to actively recommend the sale of the building for which energy saving measures are taken.

It is a figure which shows a mode that the energy consumption prediction apparatus which concerns on one Embodiment of this invention is utilized. It is a figure which shows the structure of the energy consumption prediction apparatus which concerns on one Embodiment of this invention. It is a figure which shows the input screen for utility bill calculation. It is a figure which shows the input area of basic information among the input screens for utility bill calculation. It is a figure which shows the input area of building utilization information among the input screens for utility bill calculation. It is a figure which shows the correspondence of the floor plan of a building, and an air-conditioning load. It is a figure which shows the output screen for a utility bill calculation. It is a figure which shows the flow of a utility bill calculation.

  Hereinafter, an embodiment (this embodiment) of the present invention will be described. The embodiment described below is an example for facilitating understanding of the present invention, and does not limit the present invention. That is, the present invention can be changed and improved without departing from the gist thereof, and the present invention includes its equivalents. In addition, the screen configuration examples (screen design and layout, and information displayed on the screen) described in this specification and drawings are merely examples, and can be arbitrarily set according to product specifications, user preferences, and the like. Can be set. Furthermore, a graphic user interface (GUI) provided for receiving a user input operation on the operation screen can be freely set without departing from the gist of the present invention.

  Moreover, below, the case where the energy consumption and the utility cost in a house which is an example of a building are predicted will be described as a specific example. However, a house is merely an example of a building, and the present invention can be applied to a case of predicting energy consumption in a multi-storey building. For example, in a building other than a house, such as a commercial building or a factory. It can also be applied to predicting energy consumption in buildings, multi-storey stores and facilities. The term “house” is a concept including a single-family house and a room in an apartment house such as a condominium. Furthermore, in the house, all floors are used as living spaces, and some floors are used as commercial spaces, rental rooms, or warehouses.

<< About the use of the energy consumption prediction apparatus according to this embodiment >>
First, the use of the energy consumption prediction apparatus (hereinafter, the apparatus 1) according to the present embodiment will be described. The apparatus 1 is used as a sales support tool for a housing company, for example. More specifically, as shown in FIG. 1, a salesperson P of a housing company provides a housing for a customer C who can be a future housing user (in a simple manner, a person who is considering purchasing a housing). The apparatus 1 is used when introducing a property. FIG. 1 is a diagram illustrating a state in which a salesperson P is using the apparatus 1.

  Then, the salesperson P predicts the annual energy consumption and the annual utility cost in the introduced residential property by using the apparatus 1 and presents the prediction result to the customer C. Here, “energy” refers to resources that are supplied from infrastructure facilities outside the house, such as electricity, gas, and water, and for which charges are set according to the amount of use. By the way, the prediction range (calculation range) when the apparatus 1 predicts the energy consumption and the utility cost can be arbitrarily set without being limited to one year, and can be set to several months, one month, one week, It may be one day or one hour.

  In the present embodiment, the salesperson P is set as the user of the apparatus 1, but is not limited to this, and the customer C, that is, the user of the house is the user of the apparatus 1. Also good. Moreover, in this embodiment, although the customer C who is considering the purchase of a house is set as a user of the house, the present invention is not limited to this, and the customer C who currently resides in the house It is good also as a user. That is, when the resident of the house is considering renovation / extension of the house, the apparatus 1 may be used for predicting the energy consumption and the utility cost after the renovation / extension.

  By the way, in this embodiment, the housing property which the salesperson P introduces to the customer C is a multi-storey house, and specifically, a three- to five-story middle-floor house. However, the present invention is not limited to this, and the residential property to be introduced may be a two-story low-rise house, or a six-story or higher-rise building (that is, a condominium). .

  Then, the salesperson P proposes some or all of the above-mentioned mid-level residences as a residence space (residential floor) for the customer C. Then, when the customer C sets the residence floor, the salesperson P predicts the energy consumption amount and the utility cost in the set residence floor by the apparatus 1 and presents the prediction result to the customer C. Here, among the middle-floor houses, the floor set by the customer C as the residence floor corresponds to the “specific floor” of the present invention. In addition, a plurality of rooms (rooms) are arranged on the residence floor as the “specific floor”.

  In addition, when the sales staff P outlines the procedure for predicting energy consumption and utility costs using the apparatus 1, the sales staff P starts a predetermined program (hereinafter referred to as a utility cost calculation program) in the apparatus 1. Above, the customer C is asked a question (questionnaire) about various input items necessary for the prediction. Here, as an example of the contents of questions to customer C, the number of households using the house (number of households), the composition of each household (number of people and attributes of each person), the number of floors in the middle-floor residential floor, customer C Is a content relating to a floor set as a residence floor, a floor plan of the residence floor, and in-home equipment / facility such as kitchen equipment and air conditioning equipment used on the residence floor. However, these question contents are merely examples, and contents other than the above contents may be included.

  Then, the salesperson P asks the customer C for answers to the questionnaire for each question, and then performs an input operation corresponding to the customer C's answer through the input screen displayed on the display of the apparatus 1 by the function of the utility bill calculation program. (Specifically, a designation operation described later) is performed. When the salesperson P performs an operation for instructing the execution of the utility cost calculation after the input operation is finished, this apparatus 1 is used as a trigger for the annual energy consumption and annual light heat in the residence floor set by the customer C. Predict costs. Finally, when a screen (output screen) showing the prediction result is displayed on the display of the apparatus 1, the salesperson P displays the output screen displayed on the display or the output screen displayed on the printer (not shown). The above-mentioned prediction result is presented to the customer C by showing to the customer C what has been printed in (1).

<< About the structure of the energy consumption prediction apparatus which concerns on this embodiment >>
Next, the configuration of the apparatus 1 will be described. The apparatus 1 is constituted by a personal computer (corresponding to an example of a computer) used by a salesperson P. The hardware configuration of the apparatus 1 is the same as that of a general personal computer, and includes a CPU, a memory including a ROM and a RAM, a hard disk drive, an input device, and an output device. The CPU reads a program stored in the ROM or hard disk drive and executes various data processing. The program includes the above-mentioned utility cost calculation program. The personal computer constituting the device 1 functions as an energy consumption prediction device by reading the utility cost calculation program and executing various data processing defined by the program.

  In the present embodiment, the personal computer used by the salesperson P constitutes the apparatus 1. However, the present invention is not limited to this, and the apparatus 1 may be configured by an ASP server or a cloud service server computer connected to a personal computer used by the salesperson P via a communication network. In other words, the service of the utility cost calculation program function may be provided via a communication network.

  The RAM and the hard disk drive store (store) various data necessary for predicting the energy consumption and the utility cost. In addition, the storage destination of data necessary for predicting the energy consumption and the utility cost may be other than the RAM and the hard disk drive, for example, a record detachable from the personal computer constituting the apparatus 1. It may be a medium (specifically, a flash memory or the like) or an external server computer connected to a personal computer constituting the apparatus 1 via a communication network.

  The configuration of the apparatus 1 described above will be described again from the functional aspect. As illustrated in FIG. 2, the apparatus 1 includes a candidate presentation unit 11, an operation reception unit 12, a storage unit 13, a process execution unit 14, and a result report unit 15. FIG. 2 is a block diagram showing the configuration of the apparatus 1 in terms of functions.

The functional units (candidate presenting unit 11, operation receiving unit 12, storage unit 13, processing execution unit 14 and result reporting unit 15) described above are configured so that the hardware device of the personal computer constituting the apparatus 1 is the above-described utility cost calculation program. Realized by collaboration.
Hereinafter, each functional unit of the apparatus 1 will be described.

  The candidate presenting unit 11 presents candidates for various types of input information necessary for prediction of energy consumption and utility costs to the salesperson P. Here, the candidates are candidates (options) set for the contents that the customer C answers when the salesperson P makes a question to the customer C. This candidate is to be displayed on the input screen shown in FIGS. That is, the candidate presentation unit 11 presents the above-mentioned candidates by displaying an input screen on the display of the personal computer constituting the apparatus 1.

  In order to explain the candidates in more detail, the illustrated input screens in FIGS. 3 to 5 will be described. FIG. 3 is a schematic diagram showing an input screen for calculating utility costs (hereinafter simply referred to as input screen NS). 4 and 5 are enlarged views of a part of the area on the input screen.

  The input screen NS is displayed when the utility cost calculation program is started, and a plurality of input items are input through the screen. More specifically, the input screen NS according to this embodiment includes a plurality of input areas (three areas in the case shown in FIG. 3) as shown in FIG. The first area S1 located in the upper part of the input screen NS is an input area related to basic matters. More specifically, as shown in FIG. 4, the first area S1 is an input area regarding the number of households living in the middle-floor house and the number of hierarchies of the middle-floor house. In the present embodiment, the “household” corresponds to a group using a middle-floor house and has one or more members. In other words, each member of the household corresponds to a user of a middle-rise house. Moreover, when a plurality of households use the middle-floor house, each household is supposed to use a different residence floor.

  In the first area S1, a plurality of candidates are displayed for each of the number of households and the number of hierarchies. Specifically, with regard to the number of households, the candidates “one household” and “two households” are displayed, and the number of floors is “three stories”, “four stories” and “five stories”. Is displayed. Note that the input items in the first region S1 and the types of candidates displayed for the input items are not limited to the contents illustrated in FIG.

  The second area S2 located in the center of the input screen NS and the third area S3 located in the lower part of the input screen NS are both specific when the customer C uses the middle-floor house. This is an input area related to contents (building use information). When the candidate for the number of households specified in the first area S1 is “one household”, the salesperson P inputs only to the second area S2, and in the case of “two households” , Input is performed for both the second region S2 and the third region S3. If it explains easily, when the household using a middle-floor house is one household, building use information of the household will be inputted in the 2nd field S2. On the other hand, when there are two households using the middle-floor house, the building usage information for the first household is entered in the second area S2, and the building usage information for the second household is Input is performed in the third area S3.

  As described above, the input screen NS according to the present embodiment has a plurality of building usage information input areas (two in this embodiment) so as to correspond to a plurality of households (in this embodiment, two households). ) Is provided. For this reason, in the case where there are two households using the middle-floor house, the salesperson P inputs the building usage information for two households on the same input screen NS. That is, in the present embodiment, it is possible to collectively specify candidates for two households on the same input screen. As a result, the operation of inputting building usage information for two households becomes easier for the salesperson P who is a user.

  In the present embodiment, it is assumed that the same input screen NS includes two areas of building use information input areas (that is, the second area S2 and the third area S3). However, the present invention is not limited to this, and an input screen for building usage information for two households may be provided individually (in other words, the input screen may be divided for each household). The number of building usage information input areas (or building usage information input screens) is not limited to two households, and can be set to an arbitrary number.

  Hereinafter, the configuration of the second region S2 and the third region S3 will be described in detail. Here, since the display contents of the second area S2 and the third area S3 are substantially the same, only the display contents of the second area S2 will be described below. Description of the display contents will be omitted.

  In the second area S2, building usage information is to be input. Specifically, as shown in FIG. 5, information on households living in the middle-floor houses (family information), as the residence floor Information (equipment / facility information) on the set floor number and floor plan of the residence and equipment / equipment used on the residence floor is input. In the second region S2, a plurality of candidates are displayed for each input item.

  More specifically, as the family information, as shown in FIG. 5, the number of members of the household and the attributes of each member are set. For the number of members, the candidates “1”, “2”, “3” and “4” are displayed, and the attributes of each member are “worker man”, The candidates “working woman”, “full-time housewife”, “elementary and junior high school student”, “high school student”, “university student / nami life”, “elderly man” and “elderly woman” are displayed. Note that the input items set as family information and the types of candidates displayed for each input item are not limited to the contents shown in FIG.

For the number of floors set as the residence floor, candidates “1st floor”, “2nd floor”, “3rd floor”, “4th floor”, and “5th floor” are displayed. For the floor plan of the residence floor, candidates “LDK”, “1LDK”, “2LDK (type A)”, and “2LDK (type B)” are displayed. Here, “2LDK (type A)” and “2LDK (type B)” are both candidates for 2LDK, but the room types constituting the floor plan are the same, and the rooms on the residence floor At least one of the arrangement position and the area is a candidate indicating a different floor plan. By the way, the arrangement position and area of the room in each of type A and type B are arbitrarily set, and regarding the specific contents (arrangement position and area), salesperson P asks about the floor plan of the residence floor The customer C is to be explained when doing so.
Note that the floor plan candidates are not limited to those shown in FIG.

When the device / facility information is described, information on the device / facility that affects the energy consumption and the utility cost on the floor set as the residence floor corresponds to the device / facility information. More specifically, as shown in FIG. 5, the device / facility information includes the type of cooker used in the kitchen, the type of air conditioning device, the type of hot water supply facility, the presence / absence of photovoltaic power generation as a power generation facility, Presence / absence of storage battery, and other HEMS (Home
Whether or not there is an energy management system is set. For each piece of equipment / facility information, the candidates shown in FIG. 5 are displayed. For example, for the type of air conditioner, two candidates “air conditioner” and “air conditioner + floor heating” are displayed. Further, three types of “Eco-Jaws (registered trademark)”, “ENE-FARM (registered trademark)” and “Eco-cute (registered trademark)” are displayed for the types of hot water supply facilities.

  Note that the input items set as device / equipment information and the types of candidates displayed for each input item are not limited to the contents shown in FIG. For example, an operation mode for the power generation facility or the power storage facility may be added as an input item. In addition to the input items described above, contents that may affect energy consumption and utility costs may be added as input items. For example, whether there is an electricity bill plan or purchase of surplus power generation May be added as an input item.

  The operation receiving unit 12 receives a designation operation of the salesperson P performed on each input item candidate presented by the candidate presenting unit 11. Here, the designation operation is an input operation performed to designate a candidate according to the answer from the customer C from among a plurality of candidates set for each input item, and is performed through the above-described input screen NS. For example, the designation operation for the candidate set for the floor number set as the residence floor corresponds to an operation of selecting a candidate that matches the answer of the customer C and checking a check box provided in front of the candidate. The designation operation for the candidate set for the floor plan of the residence floor corresponds to an operation of selecting a candidate that matches the answer of the customer C from the candidates displayed in the list format and selecting and clicking it.

  The storage unit 13 stores various data necessary for predicting energy consumption and utility costs. Strictly speaking, the storage unit 13 associates setting values (parameters), arithmetic expressions, and the like used in predicting energy consumption and utility costs with each of the input item candidates presented by the candidate presentation unit 11. I remember.

  Further, the data stored in the storage unit 13 includes air conditioning load table data (hereinafter, table data Dt). The table data Dt is data that defines a correspondence relationship between the floor plan indicated by the candidate presented on the input screen NS and the air conditioning load on the residence floor when the floor plan is adopted. In this embodiment, the table data Dt is stored for each floor number of the residence floor. Hereinafter, the table data Dt will be described with reference to FIG. FIG. 6 is a diagram showing the table data Dt by rank.

  As described above, the table data Dt defines the air-conditioning load on the residence floor for each floor plan when one of the floor plans indicated by the candidates presented on the input screen NS is adopted. As shown in FIG. 6, the air conditioning load for each predetermined time is determined. Note that the table data Dt according to the present embodiment is obtained by setting the air conditioning load for each hour for 24 hours and 365 days. However, the time interval for determining the air conditioning load in the table data Dt and the amount of air conditioning load to be determined can be arbitrarily set. For example, the air conditioning load every several hours can be set for one day (or It may be determined only for weekdays and holidays).

  Incidentally, the air conditioning load for each time set in the table data Dt can be obtained by calculating in advance with dedicated air conditioning load calculation software. This air-conditioning load calculation software is used for building layouts (specifically, the area of each room, the specifications of walls and partitions between rooms), the operation schedule of air-conditioning equipment and electrical equipment in each room, The air conditioning load in the building is calculated using an action pattern or the like as an input value.

  Further, as shown in FIG. 6, the table data Dt is prepared for the number of floors of the middle-floor house, in other words, the number of floor candidates (specifically, five) set as residence floors. Yes. That is, in the present embodiment, the storage unit 13 stores table data Dt (hereinafter referred to as a table data group) for five floors. This reflects that the air conditioning load on the residence floor depends on both the floor plan and the number of floors.

  Further, in the present embodiment, a plurality of table data groups are stored in the storage unit 13 as shown in FIG. A plurality of table data groups (indicated by symbols Dt1, Dt2, Dt3, Dt4, and Dt5 in FIG. 1) stored in the storage unit 13 will be described. Among the table data Dt constituting each table data group, a certain floor The table data Dt differs between the table data groups. This is because even if the residence floor has the same floor plan and the same number of floors, if the attributes of each member of the household living on the residence floor change, the lifestyle of the member will change, and accordingly the residence floor This reflects the change in the air conditioning load.

As described above, in the present embodiment, the storage unit 13 stores a plurality of table data groups. In addition, each table data group is stored in a state associated with the attributes of the household members presented on the input screen NS. Strictly speaking, in the case assumed as a candidate designation result indicating the attributes. It is stored in an associated state. For example, the table data group Dt1 in FIG. 2 is associated with the case where “elderly man” or “elderly woman” is designated from among the candidates for the member attributes. In addition, a table data group Dt2 in FIG. 2 is associated with a case in which candidates “elementary and junior high school students”, “high school students”, or “university students / nanami life” are designated for the attributes of any member.
The association (association) described above is merely an example, and is not particularly limited.

  The process execution unit 14 predicts the energy consumption and the utility cost in the residence floor based on the content of the designated operation received by the operation accepting unit 12 (that is, the designation result). If demonstrating it in more detail, the process execution part 14 will perform the prediction process which estimates the energy consumption in a residence floor, and the calculation process which calculates the utility bill in a residence floor.

  The prediction process will be described. In this process, the energy consumption for air conditioning and other energy consumption in the residence floor are predicted, and the total value thereof is calculated as the total energy consumption in the residence floor. In this way, in the prediction process, the process execution unit 14 predicts the energy consumption for air conditioning on the floor set by the customer C as the residence floor, and further predicts the total energy consumption on the floor. Note that the total energy consumption predicted by the process execution unit 14 in the prediction process is the total energy consumption consumed within a predetermined period on the residence floor, specifically, the total energy consumption for one year. . However, the prediction range (calculation range) for predicting the total energy consumption in the prediction process can be arbitrarily set without being limited to one year, and can be set to several months, one month, one week, or one day. There may be.

  The calculation process will be described. In this process, the utility cost in the residence floor is calculated from the prediction result of the total energy consumption predicted in the prediction process. Note that the utility cost calculated by the processing unit 14 in the calculation process is the utility cost for a predetermined period in which the total energy consumption is predicted by the prediction process, and specifically, the utility cost for one year. However, the calculation range when calculating the utility cost in the calculation process is not limited to one year, and can be arbitrarily set, and may be several months, one month, one week, or one day.

  In the present embodiment, when there are a plurality of households using the middle-floor house (more precisely, when “two households” is designated from the candidates for the number of households displayed on the input screen NS), The process execution unit 14 executes both the prediction process and the calculation process for each household. That is, in this embodiment, when there are a plurality of households using the middle-floor house, the annual total energy consumption and the annual utility cost on the residence floor of each household are predicted for each household.

  The result reporting unit 15 reports the calculation result of the utility cost in the calculation process to the salesperson P. If it demonstrates more concretely, the result report part 15 will report the calculation result of a utility bill by displaying the output screen HS shown in FIG. FIG. 7 is a diagram illustrating an example of the output screen HS.

  The output screen HS will be described with reference to FIG. 7. On this screen, the calculation result of the annual energy bills on the floor set as the residence floor among the middle-floor houses introduced by the salesperson P to the customer C is displayed. Is done. In addition, in this embodiment, the annual utility cost in a general house is written together as a reference value.

  In addition, when there are a plurality of households using the middle-floor house and the process execution unit 14 performs the calculation process for two households, the calculation result of the utility cost of each household is displayed individually on the output screen HS. It has become. More specifically, in the case shown in FIG. 7, when the display switching button R provided in the output screen HS is clicked, two households are displayed from the screen showing the calculation result of the utility cost for the first household. It is supposed to switch to a screen showing the calculation result of the utility costs for the eyes.

  In addition, about the display content of the output screen HS, it is not limited to the content shown in FIG. 7, For example, the total energy consumption estimated in the prediction process may be displayed together. Or the monthly utility bill may be displayed together with the annual utility bill. Moreover, the breakdown (electricity bill and gas bill) of the utility bill may be displayed together.

<< About the flow of calculation of utility costs >>
Next, the flow of the utility cost calculation using this apparatus 1 will be described with reference to FIG. FIG. 8 is a diagram showing a flow of calculation of utility costs. By the way, in the flow of the utility cost calculation described below, the present apparatus 1 is used for predicting the energy consumption for air conditioning in the floor set by the customer C as the residence floor. And in the utility cost calculation using this apparatus 1, the energy consumption amount prediction method of this invention is employ | adopted. That is, each step of the utility cost calculation described below (in particular, a series of steps until the energy consumption for air conditioning is predicted) corresponds to a component of the energy consumption prediction method of the present invention.

  The utility cost calculation is started when the utility cost calculation program is started in the personal computer constituting the apparatus 1 as a trigger. When the utility cost calculation is started, the personal computer performs the steps shown in FIG. Specifically, first, the personal computer (strictly speaking, the candidate presentation unit 11 of the apparatus 1) displays the input screen NS shown in FIG. 3 on its display (S001). Through this input screen NS, a plurality of candidates are presented to the user (salesperson P) for various input items necessary for the calculation of utility costs. In addition, as shown in FIGS. 4 and 5, candidates to be presented are set as candidates for the number of households using the middle-floor house, candidates for the number of household members and attributes of each member, and residence floors. Candidates for the number of floors, and candidates for the floor plan of the residence.

  Next, the salesperson P performs an input operation for each input item through the input screen NS, and a personal computer (strictly, the operation receiving unit 12 of the device 1) constituting the device 1 is operated by the input device (for example, a keyboard). The above-described input operation is accepted via a mouse or a mouse (S002). The input operation accepted by the personal computer in this step is a designation operation performed for the salesperson P to designate a candidate according to the answer from the customer C from among a plurality of candidates presented for each input item.

  In addition, when there are a plurality of households (in this embodiment, two households) using the middle-floor house, the salesperson P inputs the building usage information for the two households (that is, the number of members of each household, each component The candidate attributes, the floor number of the residence floor, and the candidate designation for the floor plan) are performed on the same input screen NS. Specifically, the input for the first household is performed in the second area S2, and the input for the second household is performed in the third area S3. In such a case, the personal computer (strictly speaking, the operation receiving unit 12 of the device 1) constituting the device 1 designates the number of floors used by each household as the residence floor and candidates indicating the floor plan of the residence floor for only two households. Therefore, the input operation performed by the salesperson P is accepted.

  Thereafter, the personal computer (strictly speaking, the process execution unit 14) constituting the device 1 executes the prediction process. Specifically, after the salesperson P finishes the input operation, when the calculation execution button B shown in FIG. 3 provided at the bottom of the input screen NS is clicked, execution of the prediction process is started using this as a trigger. .

  In the prediction process, first, the contents of the input operation received in the previous step S002 are specified. More specifically, the personal computer specifies candidates designated for the number of households using the middle-floor house (S003). After that, the above-mentioned personal computer is the candidate designated for the floor number of the residence floor, the candidate designated for the floor plan of the residence floor, the candidate designated for the number of members of the household using the residence floor, and each member The designated candidate is specified (S004). Further, the personal computer identifies specified candidates for the remaining input items.

  In the prediction process, after specifying the content of the input operation, data necessary for energy consumption prediction is read out from various data stored in the storage unit 13 (S005). More specifically, in this step, data corresponding to the content of the input operation specified in the previous step S004 is read from the data stored in the storage unit 13. The data read in this step includes the air conditioning load table data Dt described above.

  The procedure for reading the table data Dt will be described in detail. The personal computer (strictly speaking, the process execution unit 14) constituting the apparatus 1 accesses the storage unit 13 in the prediction process. And said personal computer is the attribute (namely, each member of the household using a residence floor) which the candidate specified in previous step S004 shows among the several table data groups memorize | stored in the memory | storage part 13. Table data group corresponding to the attribute). Thereafter, the personal computer extracts table data Dt corresponding to the floor number of the residence floor indicated by the candidate identified in the previous step S004 from the selected table data group, and reads the extracted table data Dt.

  In the prediction process, after reading the data for energy consumption prediction, the total energy consumption for the year in the residence floor is predicted based on the read data (S006). In this step, the personal computer (strictly speaking, the processing execution unit 14) that constitutes the apparatus 1 predicts the energy consumption for air conditioning that is consumed for one year on the residence floor. More specifically, the personal computer identifies the air conditioning load when the floor plan indicated by the candidate identified in step S004 is adopted from the table data Dt read out in step S005, and the residence floor is identified from the identified air conditioning load. Predict annual energy consumption for air conditioning in

  After predicting the annual energy consumption for air conditioning, the personal computer (strictly, the processing execution unit 14) constituting the apparatus 1 predicts the annual energy consumption other than for air conditioning (other energy consumption). To do. Then, the personal computer calculates the total energy consumption for the year in the residence floor by summing the predicted energy consumption for air conditioning and other energy consumption.

  In addition, for a case where one household uses multiple floors as residence floors in a middle-floor house, steps S005 and S006 are performed for each floor set as a residence floor, and the total energy consumption for each year is calculated for each floor. Will be calculated. Then, the total annual energy consumption calculated for each floor is added together to calculate the annual total energy consumption for each household.

  After calculating (predicting) the total energy consumption for the year, the personal computer (strictly, the process execution unit 14) constituting the apparatus 1 executes an arithmetic process to calculate the annual utility cost on the residence floor ( S007). In this step, the personal computer calculates an annual utility cost on the residence floor based on the annual total energy consumption on the residence floor predicted in the previous step S006.

  In the case where a single household uses multiple floors as residential floors in a middle-floor house, as described above, the total annual energy consumption calculated for each residential floor is added to the total annual amount for each household. Energy consumption is to be calculated. As described above, in step S007 for calculating the utility cost, an annual utility cost for each household (a value obtained by adding up the annual utility costs for each residence floor) is obtained as a calculation result.

  Thereafter, the personal computer constituting the apparatus 1 determines whether the number of households (the number of households using the middle-floor house) indicated by the candidate identified in step S003 is two (S008). If there are two households using the middle-floor house, the above-described personal computer performs the above-described step S004 until calculation of utility costs (specifically, calculation for two households) is completed for all households. -S007 is repeated (S009). That is, in the case where the number of households using the middle-floor house is two, the prediction process and the calculation process are executed for each household, and the annual utility cost is calculated for each household.

After the above steps are completed, the personal computer (strictly, the result report unit 15) constituting the apparatus 1 displays the output screen HS shown in FIG. 7 on the display, and through this output screen HS, The calculation result of the utility cost is reported to the salesperson P (S010). As a result, the salesperson P can present the estimated value of the annual energy bill when he / she resides in the middle-floor house to the customer C who is considering purchasing the middle-floor house.
And when the report of the calculation result of annual utility bill is completed, a series of processes in the utility bill calculation are completed.

<< Usefulness of the energy consumption prediction apparatus according to the present embodiment >>
As described above, according to the present apparatus 1, it is possible to predict the energy consumption for air conditioning in the residence floor in consideration of the floor plan and the number of floors, and compare the capacity of data necessary for the prediction. Can be made smaller.

  More specifically, as explained in the section “Problems to be solved by the invention”, as a method of calculating the air conditioning load in consideration of the floor plan, the structure of the entire building including the floor plan is modeled. A method of calculating the air conditioning load from the set value (parameter) obtained by the above is conceivable. However, when the air conditioning load is calculated by such a method, modeling is performed every time the structure of the building changes. In addition, when calculating the air conditioning load for a multi-storey house such as a middle-floor house, it is necessary to consider the number of floors in addition to the floor plan. On the other hand, if the structure of the entire house is modeled while changing both the floor plan and the number of floors, the number of setting values obtained by the modeling becomes enormous, resulting in a significant increase in the data capacity of the setting values. There is a fear.

  On the other hand, in this device 1, table data Dt indicating the correspondence between the floor plan of the residence floor and the air conditioning load of the residence floor is stored for each floor number of the residence floor. That is, in this apparatus 1, the set value of the air conditioning load is set by the number corresponding to the number of types of floor plans and the number of floors of the middle floor house. In such a configuration, the number of air conditioning load setting values is reduced compared to the case where the entire building structure is modeled while changing both floor plan and floor number to obtain the air conditioning load setting value. Therefore, the data capacity is reduced. Therefore, according to this apparatus 1, when estimating the energy consumption for air conditioning in a residence floor in consideration of a floor plan and a floor number, it becomes possible to estimate with a smaller data capacity.

  Further, in the present apparatus 1, the table data Dt indicating the air conditioning load (strictly, the table data group for each floor number) is stored in the storage unit 13 in a state associated with the attributes of each member of the household using the residence floor. It is remembered. This reflects that the lifestyle of the member differs according to the attribute of the member, and the air conditioning load changes according to the change of the lifestyle. Since the table data Dt is stored in a state associated with the attribute of the member in this way, the energy consumption for air conditioning in consideration of the attribute (more specifically, the lifestyle that changes according to the attribute) Can be predicted.

  Further, according to the present apparatus 1, in the case where each of a plurality of households uses different residence floors, the annual energy consumption (strictly speaking, the total of the energy consumption for air conditioning and other energy consumptions is added. Total energy consumption) is predicted for each household, and the annual utility cost is calculated for each household. As a result, the salesperson P and the customer C can grasp the annual energy consumption and the annual utility cost for each household.

<< Other Embodiments >>
The embodiment described above (this embodiment) is merely an example of the present invention, and other embodiments are also conceivable. For example, in the above-described embodiment, each function of the apparatus 1 (in other words, the candidate presentation unit 11, the operation reception unit 12, the storage unit 13, the process execution unit 14, and the result report unit 15 as functional units included in the apparatus 1). ) Is realized by a single computer. However, it is not limited to this, and each function may be comprised by a separate apparatus (computer).

  Further, in the above embodiment, as a correspondence relationship between the floor plan of the residence floor and the air conditioning load when the floor plan is adopted, the air conditioning load at every predetermined time (specifically, every hour) on the residence floor is determined for each floor plan. The determined table data is stored in the storage unit 13. However, the present invention is not limited to this, and data such as a correlation equation indicating a change with time of the air conditioning load may be stored for each floor plan.

  In the above embodiment, the energy consumption prediction apparatus according to the present invention is used as a sales promotion tool for a house (that is, a sales support tool). However, the present invention is not limited to this. The person who currently resides in the house may use the energy consumption prediction apparatus of the present invention as a tool for grasping the future energy consumption.

1 This device (energy consumption prediction device)
11 candidate presentation unit 12 operation accepting unit 13 storage unit 14 process execution unit 15 result report unit B calculation execution button C customer Dt table data HS output screen NS input screen P salesperson R display switching button S1 first area S2 second Region S3 Third region

Claims (7)

An energy consumption prediction device for predicting energy consumption for air conditioning in a specific floor where a plurality of rooms are arranged among a multi-storey building,
A candidate presenting unit that presents candidates to the user for each of the number of floors on the specific floor and the floor plan on the specific floor;
An operation accepting unit that accepts a user-designated operation performed on the candidate;
A storage unit that stores a correspondence relationship between the floor plan indicated by the candidate and the air conditioning load on the specific floor when the floor plan is adopted;
A process execution unit that performs a prediction process for predicting the energy consumption for air conditioning in the specific floor,
In the prediction process, the processing execution unit, based on the correspondence relation associated with the rank indicated by the candidate designated by the designation operation among the correspondence relations stored in the storage unit, Identifying the air conditioning load when the floor plan indicated by the candidate specified in is adopted, predicting the energy consumption for the air conditioning on the specific floor from the air conditioning load ,
In order to predict the energy consumption for the air conditioning for each group in a case where each of a plurality of groups uses the different specific floor, the operation reception unit is configured to store the specific floor used by the group. Energy for specifying the candidate indicating the floor number and the floor plan by the number of the groups is received by the user, and the process execution unit executes the prediction process for each group. Consumption prediction device.   The storage unit stores, as the correspondence relationship, table data in which the air-conditioning load for each predetermined time in the specific floor when the floor plan is adopted is determined for each floor. The energy consumption prediction apparatus according to claim 1. The candidate presentation unit presents the candidate to the user for each of the floor number, the floor plan, and the attribute of the user on the specific floor,
The storage unit stores the correspondence relationship in association with the attribute,
In the prediction process, the process execution unit calculates the air conditioning load from the correspondence relationship associated with the attribute indicated by the candidate designated by the designation operation among the correspondence relationship stored in the storage unit. 3. The energy consumption prediction apparatus according to claim 1 or 2, wherein the energy consumption prediction for the air conditioning at the specific floor is specified from the air conditioning load.   Among the candidates for the floor plan presented by the candidate presentation unit, the types of the rooms constituting the floor plan are the same, and at least one of the arrangement position and area of the room on the specific floor 4. The energy consumption prediction apparatus according to claim 1, wherein a plurality of candidates indicating the floor plans differing from each other are included. 5.   The operation accepting unit accepts the designation operation performed by a user to designate the candidate indicating the floor number of the specific floor used as a living space among the candidates of the floor number. Item 5. The energy consumption prediction apparatus according to any one of Items 1 to 4. The process execution unit predicts the total energy consumption consumed by each of the groups within a predetermined period by executing the prediction process for each group, and calculates the amount of the predetermined period from the prediction result of the total energy consumption. The energy consumption prediction apparatus according to claim 1 , wherein the energy cost is calculated for each group. An energy consumption prediction method for predicting energy consumption for air conditioning in a specific floor where a plurality of rooms are arranged in a multi-storey building,
A computer presenting candidates to the user for each of the number of floors on the specific floor and the floor plan on the specific floor;
A step of receiving a user designation operation performed on the candidate;
A computer executing a prediction process for predicting energy consumption for the air conditioning in the specific floor,
In the prediction process, the computer accesses a storage unit that stores a correspondence relationship between the floor plan indicated by the candidate and the air conditioning load on the specific floor when the floor plan is adopted, according to the number of floors on the specific floor. The floor plan indicated by the candidate designated by the designation operation is adopted from the correspondence relation associated with the rank indicated by the candidate designated by the designation operation among the correspondence relations stored in the section. The air conditioning load in the case of the
In order to predict the energy consumption for the air conditioning for each group in a case where each of a plurality of groups uses the different specific floors, the computer may include the number of floors of the specific floors used by the respective groups and An energy consumption prediction method comprising: accepting the designation operation performed by a user to designate the candidates indicating the floor plan by the number of the groups; and performing the prediction process for each group .

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