WO2014109290A1 - Room temperature estimating device, program - Google Patents

Abstract

This room temperature estimating device (10) is provided with a storage unit (13), a predictive expression generating unit (15), a predicted shift acquisition unit (16) and a room temperature estimating unit (17). The predictive expression generating unit (15) uses data which is stored in the storage unit (13) and which relates to the outside temperature and room temperature at a specific time on multiple days in a prescribed extraction period to generate a predictive expression which represents the relation between the room temperature and the outside temperature for said specific time. The room temperature estimating unit (17) uses the shifts in the outside temperature acquired by the predicted shift acquisition unit (16) to calculate the outside temperature for a day and time of interest corresponding to the aforementioned specific time, and estimates the room temperature of said day and time of interest by substituting the outside temperature into the predictive expression.

Description

Room temperature estimation device, program

The present invention relates to a room temperature estimation device that predicts a room temperature on a target date and time, and a program that causes a computer to function as the room temperature estimation device.

Conventionally, there is known a technique for setting the room temperature to a desired set temperature at a scheduled time by using the transition of the room temperature and the predicted outside temperature (see, for example, Japanese Patent Application Laid-Open No. 6-42765). , Hereinafter referred to as "Document 1"). In addition, with regard to the room temperature of a vehicle, a technique is known that predicts a change in room temperature from a change in the amount of solar radiation estimated and the measured outside air temperature and room temperature, and notifies when room temperature reaches a predetermined threshold. (See, for example, Japanese Patent Application Publication No. 2005-343386, hereinafter referred to as "Document 2").

Document 1 describes a technique for predicting a change in room temperature based on the history of the measured room temperature, where the information of the environment to be measured is room temperature. Furthermore, in Document 1, the operation start time and the heating start time of the heating device are determined from the predicted change in room temperature and outside temperature, the heat amount required for heating the room (heating load heat amount) and the heating capacity of the heating device. ing. That is, in the document 1, a predicted value of the room temperature and the outside air temperature is determined, and a heating load heat amount for setting the room temperature to a desired set temperature is determined based on the predicted value.

The arrangement described in reference 1 predicts room temperature to determine the heating load heat. However, in Document 1, prediction of room temperature is based on history, and a technique for predicting room temperature using other factors that determine room temperature is not described.

Document 2 describes a technology for predicting the temperature in a vehicle compartment by using the amount of solar radiation predicted together with the measured room temperature and the outside air temperature, where the information of the environment to be measured is room temperature and the outside air temperature. It is done.

The configuration described in Document 2 is a technology for predicting the temperature in the passenger compartment, and since the temperature in the passenger compartment follows a change in the outside air temperature in a short time, the temperature inside the passenger compartment is predicted from the outside air temperature and the amount of solar radiation. It is relatively easy to do. However, the temperature of the room of the building does not change immediately even if the outside air temperature changes, and depends on the thermal characteristics such as the thermal insulation performance of the room. It is difficult to predict room temperature from ambient temperature.

On the other hand, a computer simulation technology is known to obtain the room temperature of a building from various factors such as the outside air temperature, the heat insulation performance of the building, solar radiation, ventilation, rainfall, the presence or absence of people, and the like. However, to perform this type of computer simulation, a large amount of information is required, and information that may require another measurement to obtain an accurate value may be included. Can not be used conveniently.

An object of the present invention is to provide a room temperature estimation device for estimating the room temperature of a room in a building without performing complicated computer simulation based on information of the measured environment, and further, a computer is used as the room temperature estimation device. It aims to provide a program that makes it work.

The room temperature estimation apparatus according to the present invention includes a room temperature acquisition unit that acquires room temperature data from a room temperature measurement unit, an outside air temperature acquisition unit that acquires data of an outside air temperature from an outside air temperature measurement unit, and the room temperature acquired by the room temperature acquisition unit. A storage unit for storing data of the data and data of the outside air temperature acquired by the outside air temperature acquisition unit in association with the date and time when each was measured, and specifying each of a plurality of days in a predetermined extraction period stored in the storage unit A prediction equation generation unit that generates a prediction equation that represents the relationship between the room temperature and the outside air temperature with respect to the specific time using the data of the room temperature and the outside air temperature at time, and a predicted transition acquisition unit that acquires the predicted change for the outside air temperature The room temperature at the time of interest is obtained by applying the outside air temperature of the time of interest corresponding to the specific time to the prediction equation using the transition of the outside air temperature acquired by the predicted transition acquisition unit. Characterized in that it comprises a room temperature estimation unit for constant.

In this room temperature estimation apparatus, the prediction formula generation unit generates at least first and second prediction formulas respectively corresponding to at least first and second specific times as the prediction formula, and the first prediction formula is The second prediction formula is generated using data of room temperature and ambient temperature at a first specific time of each of a plurality of days in the extraction period, and the second prediction formula is a second specific time of each of a plurality of days in the extraction period The room temperature estimation unit is generated using the data of the room temperature and the outside air temperature, and the room temperature estimation unit applies the outside air temperature of the first target time corresponding to the first specific time to the first prediction formula. The room temperature at the second focus time is estimated by estimating the room temperature at the first focus time and fitting the outside temperature at the second focus time corresponding to the second specific time to the second prediction formula. It is preferable to estimate.

In this room temperature estimation apparatus, preferably, the prediction equation generation unit obtains a regression equation from the data of the room temperature and the data of the outside air temperature, and generates the regression equation as the prediction equation.

In this room temperature estimation apparatus, it is preferable that the prediction equation generation unit generates the prediction equation by simple regression analysis using data of the outside air temperature as an independent variable and data of the room temperature as a dependent variable.

In this room temperature estimation apparatus, the extraction period is determined for each divided period obtained by dividing one year into a plurality of parts based on the weather environment, and the room temperature estimation unit determines the divided period during prediction of room temperature in a predetermined divided period. It is desirable to apply the said prediction formula produced using the data of the room temperature in the said extraction period defined with respect to it, and external temperature.

The room temperature estimation apparatus further includes a correction information acquisition unit that influences the room temperature in addition to the outside air temperature and acquires correction information selected from a plurality of states, and the prediction equation generation unit acquires the correction information It is preferable that a correction prediction equation is generated by correcting the prediction equation according to the state of the correction information acquired by the unit, and the room temperature estimation unit estimates room temperature using the correction prediction equation.

It is preferable that the room temperature estimation apparatus further include a notification output unit that outputs the room temperature estimated by the room temperature estimation unit to an alarm.

In this room temperature estimation device, the outside air temperature acquisition unit preferably acquires data of the outside air temperature provided through a telecommunication line.

A program according to the present invention is for causing a computer to function as any of the room temperature estimation devices described above.

According to the configuration of the present invention, it is possible to estimate the room temperature of a room in a building only with easily measurable information without performing complicated computer simulation.

FIG. 1 is a block diagram showing a first embodiment. It is a figure for demonstrating a principle same as the above. It is a figure for demonstrating a principle same as the above. FIG. 7 is a block diagram showing a second embodiment. 5A and 5B are diagrams for explaining the above principle. FIG. 7 is a block diagram showing a third embodiment.

Below, the technology which presumes room temperature when not performing indoor air conditioning by using transition of predicted outside air temperature is explained. The factors that determine the room temperature are the outside air temperature, room insulation performance, solar radiation (with and without solar radiation and the amount of solar radiation), ventilation (with and without ventilation and ventilation), rainfall (with and without rainfall and rainfall) without cooling and heating. , And the number of people in the room.

The heat insulation performance of a room is a characteristic unique to a house, and a guide can be obtained from the construction method of the house and the building materials used in the house, but it is not easy to measure quantitatively. Although the number of people in the room can be measured, the degree of raising the room temperature is not constant depending on the amount of metabolism and the amount of clothing of individuals, so it is not easy to theoretically obtain the relationship of the number of people to the room temperature. Similarly, solar radiation, ventilation, and rainfall can be monitored, but it is not easy to theoretically determine the effect on room temperature.

In short, although it is possible to measure factors that determine room temperature, it is not easy to create an appropriate model that links these factors with room temperature. Therefore, it is not easy to determine the room temperature by computer simulation from the measured values of these factors. Also, when estimating room temperature by computer simulation, in order to obtain the required degree of accuracy, a large amount of information to be input is required and correction is required, and experts are required to estimate room temperature for each room Requires a great deal of effort.

The following describes a room temperature estimation apparatus capable of estimating room temperature with relatively high accuracy from easily measurable information without performing computer simulation using a complex model. In the first embodiment, a technique for estimating the room temperature only by the outside air temperature will be described. In the second embodiment, a technique for estimating the room temperature in consideration of the heat insulation performance of the room based on the outside air temperature will be described. In the third embodiment, a technique for estimating the room temperature in consideration of solar radiation, ventilation, rainfall, and the number of people in the room will be described.

(Embodiment 1)
The room temperature estimation device 10 according to the present embodiment estimates the room temperature at a target date and time from the outside air temperature, using a prediction formula that relates the outside air temperature to the room temperature. Therefore, the room temperature estimation apparatus 10 has a configuration for obtaining a prediction equation, and a configuration for estimating the room temperature from the outside air temperature using the prediction equation.

The room temperature estimation apparatus 10 includes, as main hardware elements, a device including a processor that implements the following functions by executing a program and a device for interface. As a device including a processor, a microcomputer including a memory, a processor to which a memory is externally attached, or the like is used. In addition, it is possible to cause a computer that executes a program that implements the following functions to function as the room temperature estimation device 10. This kind of program is provided as a computer readable recording medium, or provided by communication through a telecommunication line.

First, in the room temperature estimation apparatus 10, a configuration for obtaining a prediction formula will be described. In order to obtain the prediction formula, it is necessary to measure the room temperature and the outside temperature in association with the date and time. Therefore, as shown in FIG. 1, the room temperature estimation device 10 acquires the room temperature acquisition unit 11 that acquires room temperature data (measurement value) from the room temperature measurement unit 21 and the outside air temperature data (measurement value) from the outside air temperature measurement unit 22. And an outside air temperature acquisition unit 12 for acquiring the information. In addition, the room temperature estimation device 10 stores a storage unit 13 that stores room temperature data (measurement value) and outside air temperature data (measurement value) in association with each measured date and time, and a clock unit 14 that counts time and date. , And a prediction formula generation unit 15 for generating a plurality of prediction formulas respectively corresponding to a plurality of times.

The room temperature measurement unit 21 is provided inside a predetermined building room, and measures the temperature (room temperature) of the place where the room temperature measurement unit 21 is provided. The outside air temperature measurement unit 22 is provided outside the building and measures the temperature (outside air temperature) of the place where the outside air temperature measurement unit 22 is provided.

The room temperature measurement unit 21 and the outside air temperature measurement unit 22 each include a temperature sensor such as a thermistor that can obtain an analog output according to the ambient temperature, and a sensor amplifier that amplifies the output of the temperature sensor. Further, each of the room temperature measurement unit 21 and the outside air temperature measurement unit 22 transmits, to the room temperature estimation apparatus 10, a conversion unit that converts the output of the sensor amplifier into data of digital values, and data of digital values output from the conversion unit. And a communication unit.

Each of the room temperature measurement unit 21 and the outside air temperature measurement unit 22 may have a configuration in which the communication unit is omitted, or a configuration in which the conversion unit and the communication unit are omitted. Preferably, a converter and a communication unit are provided for transmission. When the conversion unit is omitted, each of the room temperature measurement unit 21 and the outside air temperature measurement unit 22 provides data of an analog value to the room temperature estimation device 10.

Communication between each of the room temperature measurement unit 21 and the outside air temperature measurement unit 22 and the room temperature estimation device 10 is preferably performed using a wireless communication channel using radio waves as a transmission medium, but a wired communication channel can also be used. is there. The room temperature measurement unit 21 may share the housing with the room temperature estimation device 10. When the room temperature measurement unit 21 shares the casing with the room temperature estimation device 10, the communication unit is not necessary for the room temperature measurement unit 21.

The data (measurement value) of the room temperature acquired by the room temperature acquisition unit 11 and the data (measurement value) of the outside air temperature acquired by the outside air temperature acquisition unit 12 are stored in the storage unit 13 in association with the measured date and time. . That is, the storage unit 13 stores two pairs of (room temperature, date and time) (outside temperature, date and time) or stores three pairs of (room temperature, outside temperature, date and time) as one set. The latter has a smaller amount of data and saves the storage capacity of the storage unit 13.

The clock unit 14 provided in the room temperature estimation device 10 counts the date and time stored in the storage unit 13. In the room temperature acquisition unit 11 and the outside air temperature acquisition unit 12, dates and times at which data of the room temperature and the outside air temperature are acquired are set in advance. The room temperature acquisition unit 11 and the outside air temperature acquisition unit 12 each acquire data of the room temperature and the outside air temperature at a preset date and time using the date and time counted by the clock unit 14. In this case, it is desirable that the storage unit 13 store three of (room temperature, outside temperature, date and time) as one set.

The room temperature acquisition unit 11 and the outside air temperature acquisition unit 12 acquire data, for example, every hour. The room temperature acquisition unit 11 and the outside air temperature acquisition unit 12 acquire data, for example, every hour. However, the time interval at which the room temperature acquisition unit 11 and the outside air temperature acquisition unit 12 acquire data does not have to be every hour, and may be selected as needed from 10 minutes, 15 minutes, 30 minutes, 2 hours, etc. . If the time interval is short, the amount of information increases, and it is considered that a prediction formula with high estimation accuracy can be obtained, but the amount of data stored in the storage unit 13 also increases. Therefore, it is preferable to set a time interval for acquiring data in a range from a fraction of an hour to several times of one hour on the basis of one hour. The time interval at which the room temperature acquisition unit 11 and the outside air temperature acquisition unit 12 acquire data is preferably set to a value obtained by dividing 24 hours by an integer value.

The room temperature measurement unit 21 and the outside air temperature measurement unit 22 may each be provided with a clock unit for measuring the date and time. In this case, the room temperature measurement unit 21 and the outside air temperature measurement unit 22 transmit, to the room temperature estimation device 10, the data of the room temperature and the outside air temperature acquired on the date and time clocked by each clock unit. That is, the room temperature measurement unit 21 and the outside air temperature measurement unit 22 transmit data of the room temperature and the outside air temperature to the room temperature estimation device 10 in association with the date and time when the respective clock units clock.

In this configuration, it is desirable that the storage unit 13 store two types of pairs: (room temperature, date and time) (outside temperature, date and time). Here, the timing at which the room temperature measurement unit 21 and the outside air temperature measurement unit 22 transmit the data of the room temperature and the outside air temperature does not have to be the date and time when the room temperature and the outside air temperature are measured. It is possible to send together.

Even when there is a gap between the date when the room temperature data was acquired and the date when the outside air temperature data was acquired, the size of the deviation is not more than half the data acquisition interval (for example, 1/1 of the data acquisition interval). If it is 10 or less), it is desirable that these data be regarded as acquired at the same date and time, and be associated with the same date and time.

By the way, when the room temperature does not receive the influence of solar radiation and the change in the outside air temperature is small, the heat quantity flowing into the room and the heat quantity flowing out from the room become substantially equilibrium, and the outside air temperature at the same time The hypothesis is obtained that there is a nearly linear relationship between and and room temperature.

The inventor measured the room temperature and the outside temperature at a plurality of times for a plurality of relatively long days. Then, as a result of graphing the relationship between the room temperature and the outside air temperature for each time, as shown in FIG. 2, it was found that the outside air temperature and the room temperature become substantially linear at a specific time. That is, it has been found that the room temperature at a specific time can be represented by a prediction equation of a linear function with the outside air temperature as a variable, and the room temperature can be estimated from the outside air temperature using this prediction equation. Specifically, a linear relationship is established between the ambient temperature measured at the first specific time of the plurality of days and the room temperature, and the ambient temperature and the room temperature measured at the second specific time of the plurality of days It has been found that a linear relationship holds between

Therefore, the prediction formula generation unit 15 of the room temperature estimation device 10 of the present embodiment generates a prediction formula using the outside air temperature and the room temperature at specific times of a plurality of days. The prediction formula generation unit 15 extracts data of room temperature and outside temperature at a specific time for a plurality of days in a predetermined extraction period stored in the storage unit 13, and performs regression from data of room temperature and outside temperature at the same time in a plurality of days An equation is obtained, and this regression equation is used as a prediction equation. That is, prediction equation generation unit 15 uses the data of room temperature and outside air temperature at specific times (same time) of a plurality of days in a predetermined extraction period stored in storage unit 13 to calculate room temperature and outside air temperature for the specific time. Generate a prediction equation that represents the relationship.

Since the prediction equation is predicted to be a linear function of the outside temperature, the data of the room temperature and the outside temperature used to generate the regression equation needs three days or more. That is, the extraction period needs to include multiple days of 3 days or more, and for example, it is desirable to select from the range of 15 to 90 days. The lower limit of 15 days is the number of days corresponding to one relief (half moon), and the upper limit of 90 days is the number of days corresponding to one season in spring, summer, autumn, and winter. This number of days is an example, and may be, for example, 30 days (about 1 month), or 1 year if it is a region where the change in the outside temperature is small throughout the year. Moreover, the acquisition date of the data used for the production | generation of a prediction equation may contain two or more continuous days, and may be two or more non-consecutive days. For example, the prediction equation may be generated using data of room temperature and ambient temperature measured every one day, once every two days, once a week, etc. for one to several years.

The prediction equation generation unit 15 uses the fact that a linear relationship is established between the room temperature θ1 (t) and the outside air temperature θ2 (t) at time t to which attention is paid in the extraction period, and θ1 (t) = α · θ2 (t Generate a prediction expression of the form +) + β. In generating the prediction equation, the room temperature θ1 (t) and the outside air temperature θ2 (t) are fitted to a linear function using a known method such as the least squares method. That is, the prediction formula generation unit 15 obtains the regression prediction formula from the data of the room temperature θ1 (t) and the outside air temperature θ2 (t) at the time (specific time) t to which attention is paid in the extraction period.

In this regression prediction equation, the outside temperature at the time is used as an explanatory variable, and the room temperature at the time is used as a dependent variable. That is, the prediction formula generation unit 15 obtains the prediction formula by simple regression analysis with the data of the outside air temperature as the independent variable and the data of the room temperature as the dependent variable. However, the time to find the regression prediction formula (specific time) is a time zone in which the room temperature is not affected by solar radiation and depends only on the outside temperature, and from a time zone in which the change in the outside temperature is relatively moderate. It is selected. The prediction formula generation unit 15 uses the regression prediction formula obtained as described above for the prediction formula for obtaining the room temperature from the outside air temperature.

Further, the prediction formula generation unit 15 obtains regression prediction formulas for a plurality of times. Then, the prediction formula generation unit 15 generates the obtained regression prediction formula as a prediction formula at each time. That is, the prediction formula generation unit 15 generates a plurality of prediction formulas respectively corresponding to a plurality of specific times. Each of the plurality of prediction formulas is obtained using data of room temperature and ambient temperature for the corresponding specific time. Specifically, the prediction formula generation unit 15 generates at least first and second prediction formulas respectively corresponding to at least first and second specific times. The first prediction formula is generated using the data of the room temperature and the outside temperature at the first specific time of each of the plurality of days in the extraction period. The second prediction formula is generated using the data of the room temperature and the ambient temperature at the second specific time of each of the plurality of days in the extraction period.

The room temperature estimation apparatus 10 generates a plurality of prediction formulas respectively corresponding to a plurality of time points by the method described above, and estimates the room temperature from the outside air temperature using the obtained prediction formulas. That is, the room temperature estimation device 10 generates (at least) the first prediction formula corresponding to the first specific time and the second prediction formula corresponding to the second specific time. Then, the room temperature estimation device 10 uses the first prediction formula when estimating the room temperature of the time corresponding to the first specific time, and the second prediction when estimating the room temperature of the time corresponding to the second specific time. Use the formula.

For example, the room temperature estimation apparatus 10 generates a first prediction formula using the data of the room temperature and the outside air temperature obtained at 4:00 am (first specific time) of multiple days, and generates the first prediction equation at 5:00 am of multiple days The data of the room temperature and the outside air temperature obtained at (second specified time) is used to generate a second prediction equation. Then, the room temperature estimation apparatus 10 uses the first prediction formula when estimating the room temperature at 4 am (time corresponding to the first specific time) on a predetermined day, and uses the first prediction formula, at 5 am (second time) on the predetermined day. The second prediction equation is used when estimating the room temperature of the time corresponding to the specific time of.

Below, in the room temperature estimation apparatus 10, the structure which estimates room temperature from external temperature is demonstrated concretely. The room temperature estimation device 10 acquires a predicted transition acquisition unit 16 that acquires a predicted transition of the outside air temperature using a time series of data (measurement values) of the outside air temperature acquired by the outside air temperature acquisition unit 12 from the outside air temperature measurement unit 22 , And a room temperature estimation unit 17 for estimating the room temperature from the transition of the outside air temperature.

The forecasted transition acquisition unit 16 fits the time series of data of the outside temperature to any of a plurality of templates (templates) of transition of the outside temperature registered in advance, and uses the fitted typical Predict the transition. When applying the time series of data of the outside air temperature to the representative of the transition of the outside air temperature, the predicted transition acquiring unit 16 narrows down the examples to be fitted in consideration of the weather and the season of the day.

Instead of using the data (measurement value) of the outside air temperature acquired by the outside air temperature acquisition unit 12 from the outside air temperature measurement unit 22, the outside air temperature acquisition unit 12 acquires the transition of the outside air temperature through a telecommunication line such as the Internet. It is also good. That is, the outside air temperature acquisition unit 12 has a function of acquiring data of the outside air temperature from the service provider who provides the information of the weather for each region through the telecommunication line. When adopting this configuration, the predicted transition acquisition unit 16 uses data of the outside air temperature acquired by the outside air temperature acquisition unit 12 from the service provider.

The data on the outside air temperature provided through the telecommunication line is data on a specific point in the area where the room for which the room temperature is to be estimated exists, and is not the outside air temperature for the room. It is expected that the temperature is in a linear relationship. Therefore, if the room temperature estimation unit 17 calibrates the room temperature estimated from the data of the outside air temperature based on the measured value of the room temperature, it can estimate the room temperature using the data of the outside air temperature acquired through the telecommunication line It is.

The room temperature estimation unit 17 uses the predicted transition of the outside air temperature acquired by the predicted transition acquisition unit 16 to obtain the outside air temperature at the time of interest. When the outside air temperature is determined, the room temperature estimation unit 17 estimates the room temperature by fitting the determined outside air temperature to the prediction equation generated by the prediction equation generation unit 15. That is, the room temperature estimation unit 17 obtains the outside air temperature obtained for the date and time when the room temperature is to be estimated using the predicted transition of the outside air temperature, and applies the outside air temperature to the prediction equation to obtain Estimate the room temperature.

It is desirable that the room temperature estimation device 10 includes a notification output unit 18 that outputs the room temperature estimated by the room temperature estimation unit 17 to the annunciator 23. The annunciator 23 may be a device including a display device such as a smartphone, a tablet terminal, or a personal computer, as well as a dedicated device including a display device, and a communication function. When these devices are used as the annunciator 23, the notification output unit 18 is configured to communicate with these devices. The annunciator 23 may be integrally provided in the housing of the room temperature estimation device 10, like the annunciator 23 indicated by a broken line in FIG.

Further, the room temperature estimated by the room temperature estimation unit 17 is not only notified to the user by the annunciator 23, but is also a device that affects the room temperature, such as a ventilation fan, an air conditioner, an electric shutter, an electric curtain, and an electric window. You may use for control. In particular, when controlling heating and cooling with a heating and cooling device (for example, air conditioner), if room temperature is estimated based on the transition of the outside air temperature, it becomes possible to appropriately determine the timing for stopping the operation of the heating and cooling device. It is possible to reduce the energy consumed for heating and cooling.

For example, if it is predicted that the room temperature can be reduced at night in the summer and the room temperature can be maintained at a comfortable temperature even if the cooling system is stopped, the time to stop the operation of the cooling system can be determined. Energy saving can be achieved by preventing such driving. Similarly, if it is predicted that the room temperature can be maintained at a comfortable room temperature even if the room temperature is raised in the daytime in winter, even if the room temperature system is stopped, the time for stopping the operation of the room heat system is determined. It is possible to save energy by preventing unnecessary operation.

By the way, it is easily expected that the relational expression representing the relationship between the outside air temperature and the room temperature will change depending on the season. For example, in FIG. 2, the left side shows the relationship between room temperature and outside temperature in winter, and the right side shows the relationship between room temperature and outside temperature in summer. At first glance, the left group and the right group are the same. It looks like it can be represented by a linear function. However, as shown in FIG. 3, when the left group (the group plotted with squares in FIG. 3) and the right group (the group plotted with triangles in FIG. 3) are respectively applied to linear functions, Different prediction formulas (each shown by a straight line) are obtained.

From this, it is desirable to set the extraction period for measuring the room temperature and the outside air temperature used for generating the prediction equation for each season. Therefore, the extraction period is set for each division period set by dividing one year into a plurality. Division period is period (the period which divided 1 year on the basis of the meteorological environment) which divided 1 year into 4 to 24 division (a unit of 4 division is a unit reflecting spring, summer and winter and 24 division is a unit of half a month). It is desirable to select appropriately. The number of days of the division period is 15 to 90 days, and the extraction period may be 3 days or more for each division period. The extraction period and the division period are stored, for example, in the storage unit 13 in advance.

In one example, the prediction formula generation unit 15 generates a plurality of prediction formulas in accordance with the number of division periods. That is, the prediction formula generation unit 15 generates a plurality of prediction formulas respectively corresponding to a plurality of times for each division period. Then, when estimating the room temperature at a predetermined date and time, the room temperature estimation unit 17 selects a prediction formula generated for the target time in the division period to which the target day belongs, from the plurality of prediction expressions obtained for each division period. Estimate the room temperature from the transition of the outside temperature using the selected prediction formula.

In another example, when the date and time counted by the clock unit 14 shifts from one division period to the next division period (for example, a period indicating “summer” to “autumn”). When it moves to the next), newly generate a plurality of prediction formulas respectively corresponding to a plurality of times. After the prediction equation is generated, the room temperature estimation unit 17 estimates the room temperature using the newly generated prediction equation.

Second Embodiment
In the first embodiment, since the prediction equation generation unit 15 generates the prediction equation using the room temperature and the outside air temperature in a time zone in which the room temperature is not affected by solar radiation, the room temperature is estimated from the outside air temperature using the prediction equation. There is a limit to the time that can be done. That is, during the time zone in which the room temperature is affected by solar radiation, the room temperature can not be accurately estimated by the prediction equation obtained in the first embodiment, and the prediction equation obtained in the first embodiment As such, it can be adopted only in the time zone where the change of the outside air temperature is relatively small.

The present embodiment describes a technique for setting a prediction formula that can be used in a daytime time zone in which room temperature is affected by solar radiation. Therefore, the prediction equation obtained by the technique of the first embodiment is adopted in a time zone where it is not necessary to consider the influence of solar radiation at night, and in the time zone where the influence of solar radiation is considered in the daytime, the prediction described below The formula is adopted. That is, this embodiment adopts a configuration in which the type of prediction equation is changed between a time zone in which solar radiation does not affect room temperature (a time zone in which solar radiation does not occur) and a time zone in which solar radiation affects room temperature. The prediction formula generation unit 15 in the room temperature estimation device 10 of the present embodiment has a function of generating two types of prediction formulas.

As shown in FIG. 4, the room temperature estimation apparatus 10 will be described below with a first prediction formula generation unit 151 that generates a prediction formula (first kind of prediction formula) using the same technology as that of the first embodiment. And a second prediction formula generation unit 152 that generates a prediction formula (a second type of prediction formula) by a technology.

The first prediction formula generation unit 151 generates a prediction formula in the same manner as the prediction formula generation unit 15 in the first embodiment. The first prediction formula generation unit 151 generates a regression prediction formula using data of room temperature and ambient temperature at specific times of a plurality of days stored in the storage unit 13, and uses the generated regression prediction formula as a prediction formula .

On the other hand, the second prediction formula generation unit 152 considers that the relationship between the room temperature and the outside air temperature depends on the thermal characteristics of the room (heat insulation, heat storage property, etc.), and the prediction formula is Generate Now, assuming that the room temperature depends only on the outside air temperature, a model is assumed in which heat is conducted through partitions consisting of a wall, a ceiling, and a floor surrounding the room, and the room temperature changes following the outside air temperature. According to this model, the influence of the outside air temperature on the room temperature is considered to change depending on the degree of heat conduction of the partitions and the degree of heat storage of the partitions. However, room temperature is taken as the temperature of the air in a room, without considering the radiant heat from a partition.

According to the above-mentioned model, it is considered that the room temperature changes behind the change of the outside air temperature. As a result of the experiment, the inventor of the present invention has a correlation between the change in the outside air temperature and the change in the room temperature, and the room temperature is a delay time according to the heat characteristics of the partition (heat insulation, heat storage property, etc.). We find that it is delayed and changes. In addition, if this delay time can be determined, the relationship between the room temperature at a specific time and the outside air temperature at a time shifted from the specific time by the delay time can be expressed by a simple prediction equation. It has been found that the room temperature can be estimated from the outside air temperature.

The graph which plotted the relationship of the room temperature and external temperature which were measured on the same date and time is shown to FIG. 5A. Just looking at the illustrated example, it is not possible to find a relationship between room temperature and ambient temperature. On the other hand, as described above, the present embodiment is based on the assumption that the change in the outside air temperature and the change in the room temperature are correlated with a delay time corresponding to the thermal characteristic of the room.

Therefore, the room temperature estimation apparatus 10 according to the present embodiment uses the data of the room temperature (measurement value), the data of the outside air temperature (measurement value), and the date and time stored in the storage unit 13 to determine the phase relationship between the room temperature and the outside air temperature. An evaluation unit 19 is provided for obtaining a delay time at which the number is maximized. The evaluation unit 19 shifts the date and time when the room temperature was measured and the date and time when the outside temperature was measured relative to the data of the room temperature and the data of the outside air temperature on a predetermined day (referred to as “extraction day”) The delay time at which the correlation coefficient between the data of room temperature and the data of the outside air temperature becomes maximum (hereinafter, also referred to as “optimal time difference”) is determined. The extraction date is not limited to one day, and may be multiple days. The following describes an example of shifting the date and time when the outside air temperature was measured based on the date and time when the room temperature was measured, but the date and time when the room temperature was measured based on the date and time when the outside air temperature was measured are shifted You may

Here, the data of the room temperature and the outside air temperature at the date and time t are denoted as θ1 (t) and θ2 (t), and the time interval for acquiring the data θ1 (t) of the room temperature and the data θ2 (t) of the outside air temperature is p It is written as The date and time t is expressed as t = t0 + n · p, and the predetermined time difference Δt is expressed as Δt = m · p. t0 is a reference value given according to the extraction date, and m and n are natural numbers.

When the above-mentioned notation is adopted, data of room temperature are expressed as θ1 (t0 + p), θ1 (t0 + 2p), θ1 (t0 + 3p), ..., and data of outside temperature are θ2 (t0 + p), θ2 (t0 + 2p), θ2 It is expressed as (t0 + 3p),. Further, the data of the outside air temperature of the date and time before the time difference Δt with respect to the room temperature data θ1 (t0 + n · p) is θ2 (t0 + n · p−Δt) = θ2 (t0 + (n−m) p).

Assuming that the extraction date period is [t0 + p, t0 + q · p], the average value a (θ1) of the room temperature θ1 (t) in the extraction date period is {θ1 (t0 + p), θ1 (t0 + 2p), ..., θ1 (t0 + q) The average value of p)}. Further, the average value a (θ2) of the outside air temperature θ2 (t) in a period preceding the “extraction date” by the time difference Δt is {θ2 (t0 + (1-m) p), θ2 (t0 + (2-) m) p),... θ2 (t0 + (q−m) p)} is an average value. [T0 + p, t0 + q · p] is a closed section and represents q discrete values of {t0 + p, t0 + 2p, t0 + 3p,..., T0 + q · p}.

By using these values, evaluation unit 19 uses data θ1 (t) of room temperature at date and time t and data θ2 (t of outside air temperature at date and time (t−Δt) earlier by time difference Δt (= m · p). Determine the correlation coefficient with -Δt). The calculation of the correlation coefficient is a generally known operation, and the covariance of θ 1 (t) and θ 2 (t-Δt) is calculated by the standard deviation of θ 1 (t) and the standard deviation of θ 2 (t-Δt) It is obtained by dividing by the product of However, as the average values a (θ1) and a (θ2) for obtaining the covariance and the standard deviation, the values described above are used. The range of the date and time t in the room temperature data θ 1 (t) and the outside air temperature data θ 2 (t−Δt) uses the period of the extraction date (closed interval [t0 + p, t0 + q · p]).

The evaluation unit 19 changes the time difference Δt by changing the value of m, and obtains a correlation coefficient for each value of m. In the present embodiment, the maximum value of m is limited so that the product m · p with the time interval p does not exceed one day. For example, if the time interval p is one hour, the maximum value of m is limited not to exceed 24. The evaluation unit 19 obtains the value mm of m when the correlation coefficient is maximized. Then, the optimal time difference Δt _A is calculated as Δt _A = mm · p.

The relationship between the room temperature θ1 (t) and the outside air temperature θ2 (t-Δt _A ) is plotted as shown in FIG. 5B using the time difference (optimum time difference) Δt _A calculated by the evaluation unit 19 as described above. In the illustrated example, the room temperature θ 1 (t) and the outside air temperature θ 2 (t−Δt _A ) have a substantially linear relationship, and it can be seen that the linear function can be fitted.

The second prediction formula generation unit 152 generates a prediction formula for estimating the room temperature from the outside air temperature, using the relationship shown in FIG. 5B. The second prediction formula generation unit 152 extracts the data of the extraction date from the data of the room temperature and the data of the outside air temperature stored in the storage unit 13, and the evaluation unit 19 at the date and time corresponding to the extracted data of the outside air temperature. The time difference (optimum time difference) Δt _{A determined} by Furthermore, the second prediction formula generation unit 152 regards the relationship between the room temperature θ1 (t) and the outside air temperature θ2 (t−Δt _A ) as a linear relationship, and estimates the prediction equation θ1 (t) = α · θ2 (t) The coefficients α and β are determined by a well-known operation such as the method of least squares, expressed in the form of −Δt _A ) + β. Specifically, the second prediction formula generation unit 152 obtains the prediction formula by single regression analysis using the data of the outside air temperature after giving the time difference Δt _A as an independent variable and the data of room temperature as a dependent variable. In this manner, the evaluation unit 19 obtains the time difference Δt _A and the second prediction equation generation unit 152 determines the coefficients α and β, whereby the prediction equation (the second type of prediction equation) is obtained. The coefficients α and β usually have different values from the coefficients α and β included in the prediction equation generated by the first prediction equation generation unit 151.

That is, the second prediction formula generation unit 152 determines the time difference (optimum time difference) by using the data of the room temperature and the outside air temperature on the predetermined extraction date stored in the storage unit 13 and gives this time difference. The prediction formula is generated from the data of the room temperature and the data of the outside air temperature.

The prediction equation generated by the second prediction equation generation unit 152 can be applied regardless of whether the room temperature is affected by solar radiation. In addition, it is possible to estimate room temperature using one prediction equation regardless of time. However, if the room temperature is a time zone not affected by solar radiation, the second prediction formula can be obtained with relatively good accuracy by the prediction formula (first kind of prediction formula) generated by the first prediction formula generation unit 151. It is possible to estimate the room temperature from the outside air temperature (with higher accuracy than the prediction equation of the generation unit 152).

Therefore, the prediction equation generated by the first prediction equation generation unit 151 is adopted in the time period where the room temperature can be predicted by the prediction equation generated by the first prediction equation generation unit 151, and in the other time periods. It is desirable to share roles so as to use the prediction formula generated by the second prediction formula generation unit 152. That is, the prediction equation (first kind of prediction equation) generated by the first prediction equation generation unit 151 is adopted in a time zone in which the room temperature is not affected by solar radiation (a time zone in which there is no solar radiation). The prediction equation (the second type of prediction equation) generated by the second prediction equation generation unit 152 is adopted as the time zone affected.

When the room temperature estimation device 10 estimates the room temperature from the outside air temperature using the prediction equation generated by the second prediction equation generation unit 152, the time difference (delay time) Δt calculated by the evaluation unit 19 with respect to the date and time of interest _It is necessary to acquire the data of the outside temperature at the date and time that went back by _A. Here, the time of interest means the time of day when it is intended to estimate the room temperature.

Therefore, the room temperature estimation unit 17 uses the predicted transition of the outside air temperature acquired by the predicted transition acquisition unit 16 and the time difference (optimum time difference) calculated by the evaluation unit 19 and dates back to the time of interest by the time difference Determine the ambient temperature (actual or predicted value) of When the outside air temperature is determined, the room temperature estimation unit 17 estimates the room temperature by fitting the determined outside air temperature to the prediction equation generated by the prediction equation generation unit 15. That is, the room temperature estimation unit 17 obtains the outside temperature at the time when the evaluation unit 19 goes back by the time difference calculated from the date and time to estimate the room temperature using the predicted transition of the outside temperature, and predicts this outside temperature. By applying the equation, the room temperature of the date and time of interest is estimated.

As apparent from the above description, the prediction formula generation unit 15 of the present embodiment includes a first prediction formula generation unit 151 and a second prediction formula generation unit 152. The room temperature estimation unit 17 determines whether the room temperature is not affected by solar radiation or the room temperature is affected by solar radiation, according to the date and time kept by the clock unit 14. The prediction equation generated by the first prediction equation generation unit 151 is adopted in a time zone in which the room temperature is not affected by solar radiation, and in the time zone in which the room temperature is affected by solar radiation, the second prediction equation generation unit 152 The prediction equation generated by is adopted.

In the first embodiment, it has been described that a change due to the season occurs in the prediction formula generated by the first prediction formula generation unit 151. The prediction formulas generated by the second prediction formula generation unit 152 are also easily expected to change depending on the season. Therefore, it is desirable to set the extraction date for measuring the room temperature and the outside air temperature used to generate the prediction formula for each season.

That is, a divided period in which one year is divided into plural is set, and an extraction date is determined for each divided period. The division period is appropriately selected from the period in which 1 year is divided into 4 to 24 divisions (4 division is a unit reflecting spring, summer, and winter, and 24 division is a unit with half a month as a unit).

Then, the second prediction formula generation unit 152 generates a number of prediction formulas corresponding to the number of division periods. Further, the room temperature estimation unit 17 selects the prediction formula generated for the division period to which the target date and time belongs from the plurality of prediction formulas obtained for each division period, and changes the outside temperature using the selected prediction formula Estimate

Since the thermal characteristics of the room may change with time, it is also desirable to use the time difference obtained for each division period when the room temperature estimation unit 17 estimates the room temperature. That is, the evaluation unit 19 newly obtains a time difference (optimum time difference) Δt _A each time the division period elapses, and the second prediction formula generation unit 152 generates a prediction formula (second type) corresponding to the obtained time difference Δt _A It is desirable that the prediction equation be newly generated, and the room temperature estimation unit 17 estimate the room temperature using the newly generated prediction equation (the second type of prediction equation). However, the room temperature estimation unit 17 can estimate the room temperature using the time difference obtained in any of the divided periods. In addition, it is possible to estimate the room temperature using an average value of time differences obtained in a plurality of division periods.

As described above, since the room temperature estimation unit 17 according to the present embodiment uses different types of prediction formulas depending on whether or not the room temperature is affected by solar radiation, the outside air temperature to be substituted into the prediction formulas is also different. Compared with the configuration of the first embodiment, the prediction accuracy of the room temperature can be enhanced. Other configurations and operations are the same as in the first embodiment.

(Embodiment 3)
In the first embodiment and the second embodiment, the room temperature estimation device 10 estimates the room temperature only by the outside air temperature, but as described above, the factors determining the room temperature are solar radiation, ventilation, rainfall, when air conditioning is not performed. Including the number of people in the room. In addition, when performing heating and cooling, if the heating and cooling system has the function of managing room temperature, the room temperature depends on the operating state of the heating and cooling system, and the room temperature can not be predicted by the prediction formula. We do not consider about

When considering information on solar radiation, ventilation, rainfall, and people in addition to the outside air temperature, it is possible to set a model that links the information to room temperature, quantify these information, and apply it to the model. However, such a model has a complex causal relationship and requires complicated computer simulation, resulting in an increase in parameters to be input and an increase in processing load.

Therefore, this embodiment uses these pieces of information as correction information, limits the number of states that each correction information can take, and sets prediction formulas for each state of correction information, thereby increasing the number of parameters and the processing load. To prevent. That is, when using a plurality of correction information, the prediction formula generation unit 15 divides the state into a plurality of stages for each correction information, and generates a prediction formula (corrected prediction formula) associated with a combination of these stages. In addition, although the example which applied the technical thought of this embodiment to the structure of Embodiment 1 shown in FIG. 1 is demonstrated, it is also possible to apply the technical thought of this embodiment to the structure of Embodiment 2. FIG.

Here, regarding solar radiation, ventilation, and rainfall, each state is divided into two stages of only presence or absence, and it is considered that the number of persons is raised by a predetermined temperature (for example, 0.5 ° C.) per person. Thus, if the type of correction information is simplified and the number of possible states is limited, the number of combinations of correction information is limited and becomes relatively small.

The prediction formula generation unit 15 sets a prediction formula in accordance with a combination of individual states of correction information. Since the number of people in the room is reflected only on the coefficient β of the prediction equation, it is not necessary to generate a prediction equation for each person, and the room temperature estimation unit 17 doubles the number of people at a predetermined temperature to the room temperature obtained from the prediction equation. Correction to add. Therefore, in the above example, eight prediction equations are generated from the correction information of solar radiation, ventilation, and rainfall.

The prediction equation generation unit 15 generates a corrected prediction equation by correcting the coefficients α and β of the prediction equation according to the state of the correction information. For example, the storage unit 13 stores correction amounts of the coefficients α and β according to the state of each correction information. The prediction equation generation unit 15 reads out the correction amount of the coefficients α and β corresponding to this state from the storage unit 13 when certain correction information is in the one state (for example, the state with ventilation), and reads the correction By applying the quantities to the coefficients α, β of the prediction equation, a corrected prediction equation is generated.

The room temperature estimation apparatus 10 of the present embodiment further includes a correction information acquisition unit 32 that acquires correction information from the solar radiation detection unit 33, the ventilation detection unit 34, the rainfall detection unit 35, and the number detection unit 36, as shown in FIG. .

The solar radiation detection unit 33 may include a light receiving element such as a photodiode or a phototransistor, and a determination unit that determines the light amount by comparing the output of the light receiving element with a threshold. Further, since the influence of solar radiation on the room also depends on the open / close state of the curtain or shutter, it is preferable that the solar radiation detection unit 33 has a function of detecting the open / close state of the curtain or shutter.

The ventilation detection unit 34 is selected from a configuration that detects whether the ventilation fan is operating, a configuration that detects the open / close state of the window, a configuration that measures the airflow in the room, and the like. The rainfall detection unit 35 adopts a configuration in which raindrops are collected to measure a mass every predetermined period, or a configuration in which raindrops are detected from an image outdoors. Also, correction information on rainfall may be obtained by information provided by a service provider through a telecommunication line such as the Internet. The number detection unit 36 adopts a configuration that measures the number of people in the room from the image in the room.

In addition, about solar radiation, ventilation, and rainfall, you may make it express not only presence or absence but in multiple steps of three or more steps. For example, solar radiation can be divided into four stages: strong, moderate, weak, and weak. The same applies to ventilation and rainfall, and can be divided into three or more stages.

The room temperature estimation unit 17 corrects the prediction formula based on the correction information acquired by the correction information acquisition unit 32, generates a correction prediction formula, and estimates the room temperature from the outside air temperature using the correction prediction formula. The correction amounts of the coefficients α and β according to solar radiation, ventilation, rainfall, and the number of persons are statistically determined based on the measured values. Other configurations and operations are the same as in the first and second embodiments.

Claims (9)

1. A room temperature acquisition unit for acquiring room temperature data;
   An outside air temperature acquisition unit that acquires outside air temperature data,
   A storage unit that stores the data of the room temperature acquired by the room temperature acquisition unit and the data of the outside air temperature acquired by the outside air temperature acquisition unit in association with the date and time when each was measured;
   A prediction formula generation unit that generates a prediction formula representing the relationship between the room temperature and the outside air temperature with respect to the specific time using the data of the room temperature and the outside air temperature at specific times of a plurality of days in the predetermined extraction period stored in the storage unit When,
   A forecasted transition acquisition unit that acquires a forecasted transition of outside temperature;
   A room temperature estimation unit for estimating the room temperature at the time of interest by fitting the outside air temperature of the time of interest corresponding to the specific time to the prediction formula using the transition of the outside air temperature acquired by the predicted transition acquisition unit; Room temperature estimation device.
2. The prediction formula generation unit generates at least first and second prediction formulas respectively corresponding to at least first and second specific times as the prediction formula, and the first prediction formula includes a plurality of prediction formulas in the extraction period. The second prediction formula is generated using data of room temperature and ambient temperature at a second specified time of a plurality of days in the extraction period, using data of room temperature and ambient temperature at the first specified time of day Generated,
   The room temperature estimation unit estimates the room temperature at the first focused time by fitting the outside air temperature of the first focused time corresponding to the first specified time to the first prediction formula. The room temperature estimation apparatus according to claim 1, wherein the room temperature at the second focused time is estimated by applying the outside air temperature of the second focused time corresponding to the specific time of 2 to the second prediction formula.
3. The room temperature estimation device according to claim 1 or 2, wherein the prediction equation generation unit obtains a regression equation from the data of room temperature and the data of the outside air temperature, and generates the regression equation as the prediction equation.
4. The extraction period is determined for each divided period in which one year is divided into a plurality based on the weather environment,
   The room temperature estimation unit applies the prediction formula generated using data of the room temperature and the outside air temperature in the extraction period determined for the division period to the prediction of the room temperature in a predetermined division period. The room temperature estimation apparatus according to any one of the above.
5. In addition to the outside air temperature, the system further includes a correction information acquisition unit that affects room temperature and acquires correction information selected from a plurality of states,
   The prediction equation generation unit generates a correction prediction equation by correcting the prediction equation according to the state of the correction information acquired by the correction information acquisition unit.
   The room temperature estimation apparatus according to any one of claims 1 to 4, wherein the room temperature estimation unit estimates the room temperature using the correction prediction equation.
6. The room temperature estimation apparatus according to any one of claims 1 to 5, further comprising: a notification output unit that outputs the room temperature estimated by the room temperature estimation unit to an alarm.
7. The room temperature estimation apparatus according to any one of claims 1 to 6, wherein the outside air temperature acquisition unit acquires data of the outside air temperature provided through a telecommunication line.
8. The room temperature estimation apparatus according to claim 3, wherein the prediction equation generation unit generates the prediction equation by simple regression analysis using data of the outside air temperature as an independent variable and data of the room temperature as a dependent variable.
9. A program for causing a computer to function as the room temperature estimation apparatus according to any one of claims 1 to 8.

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