JP2015097084A - Estimation system, home energy consumption management system, district energy management system, actual condition of energy consumption evaluation system, actual condition of energy consumption visualization system, improvement of energy consumption behavior proposal system, method therefor, and electronic device and server incorporating system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an estimation system which, in estimating the amount of energy consumption in the home, reduces the load of inputting the data associated with the household of the home and accurately estimates the amount of energy consumption of the home in time series.SOLUTION: A plurality of living activity items are preset as living activity items in the home of one household, and an energy consumption coefficient for each of the living activity items set and another coefficient are stored after being classified for each classified atmospheric temperature, classified into spring, summer, fall, and winter, and for each day of the week. An average doer rate per time of day for each of the living activity items set after being classified for each classified atmospheric temperature and each day of the week is stored for each life stage of the one household. An estimated amount of energy consumption per time of day in the one household is calculated from the sum of products of the average doer rate per time of day and the energy consumption coefficient plus the other coefficient.

Description

  The present invention is a technique relating to estimation of energy consumption at home of each household, domestic energy consumption management, regional energy management, evaluation of actual energy consumption, visualization of actual energy consumption, and suggestions for improving energy consumption behavior.

Energy conservation at homes and business establishments is important from the viewpoints of both environmental conservation and economic efficiency. In business establishments such as factories that consume a large amount of energy, various devices have been devised to monitor the amount consumed for each device and plan rational energy consumption.
In addition, at home, as described in Patent Document 1, etc., a utility cost prediction system that can promptly propose to customers who purchase homes the effects of improving the housing performance of newly built houses and homes during renovations and introducing solar systems is proposed. It is trying to contribute to energy saving.

  Furthermore, on the power generator side, as described in Patent Document 2, etc., the power generated by the generator installed in the consumer is supplied to the consumer to cover the power demand of the power load, and the exhaust heat accompanying the power generation is reduced. There has been proposed a power generation system that covers heat demand such as heat load of consumers by collecting and storing heat. This power generation system has very high energy efficiency compared to conventional power generation systems such as thermal power generation, and can contribute to energy saving.

JP 2005-332165 A JP 2010-071493 A

  In the technology of Patent Document 1, energy consumption is calculated by accumulating and calculating the energy consumption in the entire house by inputting how often each device installed in the house is used, such as cooling, heating and hot water supply. The amount is estimated. However, when using the stacked calculation method, there is a problem that a lot of work is required because there is a large amount of data to be input. Moreover, since the accuracy of the input data is not certain, there is a problem that it is difficult to accurately estimate the time series energy consumption in the house.

Moreover, in the technology of the power generation system of Patent Document 2, it is necessary to operate the power generation system suitable for the power demand of the customer's power load in order to maximize energy saving. Therefore, this power generation system also requires a function for estimating the time-series energy consumption of the home and planning the operation of the power generation system based on the estimation. However, the technique of Patent Document 2 also has a problem that it is difficult to accurately estimate the time-series energy consumption at home, as in Patent Document 1.
An object of the present invention is to reduce the burden of inputting data related to a household in the estimation of energy consumption at home, and to accurately estimate the time-series energy consumption of the home.

In order to solve the above-described problem, one aspect of the present invention is an energy consumption estimation system in a home,
As an item of living behavior in one household, multiple items of living behavior are set in advance,
Coefficients for living behavior that are stored by classifying and storing the energy consumption coefficient and other constants for each item of the set living behavior for each temperature classification classified as spring, summer, autumn, and winter and for each day of the week. Data storage means;
For each household life stage, classify by temperature class and weekday, and store the average actor rate by time for each set item of living behavior. Storage means;
From the value obtained by adding the other constants to the sum of the average actor rate for each time and the product of the energy consumption coefficient, an hourly power consumption calculation unit that calculates an estimate of energy consumption for each time of a household; ,
It is characterized by providing.

Another aspect of the present invention is a system for estimating energy consumption in the home,
Temperature data input means for inputting temperature data;
Power consumption demand response communication means for performing demand response communication with the local energy management system;
Power consumption adjustment amount calculating means for calculating a household power consumption plan amount using an estimate of energy consumption for each time of the household determined by the estimation system in response to a demand signal from the regional energy management system; ,
Transmitting means for transmitting household power consumption plan amount data to the regional energy management system via the power consumption demand response communication means;
Power consumption adjusting means for controlling the power consumption of controlled household appliances at home according to the household power consumption plan amount;
It is a domestic energy consumption management system characterized by comprising.

Another aspect of the present invention is the above-described home energy consumption estimation system, life stage household number storage means, average temperature data input means, total process power consumption estimation means, and power consumption per time other than home. An estimation means, a power supply / demand adjustment means, a power consumption demand response communication means for performing demand response communication, and a generator operation control means,
The power supply and demand adjustment means is
A calculating means for calculating a load pattern for each time of the total power consumption in the region by totaling an estimate of energy consumption for each time of the household determined by the estimation system;
A transmission means for transmitting a demand signal corresponding to the load pattern to a domestic energy consumption management system of a local household via the power consumption demand response communication means;
Receiving means for receiving household power consumption plan data from the household energy consumption management system of the local household;
A second calculation means for calculating a load pattern for each time of the total power consumption of the area again using the data of the planned power consumption of the household,
The generator operation control means is a regional energy management system characterized in that an operation plan amount of a generator is calculated based on the load pattern calculated by the second calculation means and the operation of the generator is controlled. .

Another aspect of the present invention is a method for estimating energy consumption at home,
The items of living behavior in one household are “sleep”, “meal”, “personal affairs”, “cooking / cleaning / washing”, “watching TV”, and “internet operation”. ‘Required Action’ and ‘Other Actions’,
The energy consumption coefficient and other constants for each item of the set living behavior are stored for each temperature classification classified as spring, summer, autumn, and winter and for each day of the week,
For each life stage of a household, classify for each class of temperature and for each day of the week, store the average actor rate per time for each item of the set living behavior,
The computer calculates an estimate of energy consumption for each time of a household from a value obtained by adding the other constants to the sum of the average actor rate for each time and the product of the energy consumption coefficient. This is an estimation method of energy consumption at home.

According to another aspect of the present invention, demand response communication is performed with a local energy management system, and an estimation of energy consumption for each time of the household determined by the estimation system according to a demand signal from the local energy management system. To calculate the household power consumption plan using
Send household energy consumption plan data to the local energy management system,
A home energy consumption management method characterized by controlling power consumption of controlled household appliances in a home according to a household power consumption plan amount.

Another aspect of the present invention is to calculate a load pattern for each time of the total power consumption in a region by summing up the estimation of energy consumption for each time of the household obtained by the energy consumption estimation system in the household. And
A demand signal corresponding to the load pattern is transmitted to a domestic energy consumption management system of a household in the region, and further, data of a household power consumption plan amount is received from the household energy consumption management system, and the received household power Calculate the load pattern for each hour of the total power consumption of the region again using the planned consumption data, calculate the operation plan amount of the generator based on the recalculated load pattern, and control the operation of the generator It is a regional energy management method characterized by

Another aspect of the present invention is an evaluation system for actual energy consumption at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The energy consumption coefficient for each item of the set second living behavior and other second constants are classified and stored for each temperature classification classified as spring, summer, autumn, and winter and for each day of the week. Coefficient data storage means according to daily activities;
For each household life stage, classify according to the temperature classification and weekday, and store the average rate of actors at each time for each item of the set first living behavior. Actor rate storage means,
From the value obtained by adding the other second constant to the sum of the average actor rate for each time and the product of the energy consumption coefficient, the energy consumption amount for each item of the set second living behavior of one household And an hourly power consumption calculation unit for calculating an action time,
For each item of the set second living behavior, set each energy device used in the living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption amount for each item of the set second living behavior of the household is set using the set action time of the second living behavior and the energy consumption amount of each set energy device as an index. It is characterized by having an energy consumption actual state quantitative evaluation calculating section that quantitatively evaluates the energy consumption for each item of the living behavior of 2.

Another aspect of the present invention is a visualization system of actual energy consumption at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The energy consumption coefficient for each item of the set second living behavior and other second constants are classified and stored for each temperature classification classified as spring, summer, autumn, and winter and for each day of the week. Coefficient data storage means according to daily activities;
For each household life stage, classify according to the temperature classification and weekday, and store the average rate of actors at each time for each item of the set first living behavior. Actor rate storage means,
From the value obtained by adding the other second constant to the sum of the average actor rate for each time and the product of the energy consumption coefficient, the energy consumption amount for each item of the set second living behavior of one household And an hourly power consumption calculation unit for calculating an action time,
Set each energy device used in the living behavior for each item of the set second living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption amount for each item of the set second living behavior of the household is set as the index of the set action time of the second living behavior and the energy consumption amount of each set energy device as an index. Quantitative evaluation of energy consumption for each item of daily living
It has an energy consumption actuality visualization calculation part which visualizes the breakdown of the energy consumption for each item of the set second living behavior as an index of energy consumption of the energy device and the action time.

Another aspect of the present invention is an improvement suggestion system for energy consumption behavior at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The energy consumption coefficient for each item of the set second living behavior and other second constants are stored for each temperature category classified as spring, summer, autumn, and winter and for each day of the week. Coefficient data storage means;
For each life stage of each household, the average actor rate by living behavior that stores the average actor rate at each time for each item of the set first living behavior for each temperature category and for every day of the week Storage means;
From the value obtained by adding the other second constant to the sum of the average actor rate for each time and the product of the energy consumption coefficient, the energy consumption amount for each item of the set second living behavior of one household And an hourly power consumption calculation unit for calculating the action time,
Set each energy device used in the living behavior for each item of the set second living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption for each item of the set second living behavior of the household is set as the index of the set action time of the second living behavior and the energy consumption of the set energy device as an index. It has an energy consumption behavior improvement suggestion calculation unit that quantitatively evaluates energy consumption for each item of living behavior,
Based on the quantitative evaluation, an improvement proposal of energy consumption behavior corresponding to the life stage is posted.

Another aspect of the present invention is a method for evaluating energy consumption at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
In the gas analysis, “TV (in-home)” corresponds to “bathing”, “hobby entertainment (net)” corresponds to “free action”
The energy consumption coefficient and the other second constant for each item of the second living behavior set above are classified and stored for each temperature category classified as spring, summer, autumn, and winter and for each day of the week. ,
For each life stage of a household, classify for each class of temperature and each day of the week, and store the average actor rate for each time for each item of the set first living behavior,
From the value obtained by adding the second constant to the sum of the average actor rate at each time and the product of the energy consumption coefficient, the computer calculates the energy for each item of the set second living behavior of one household. Calculate consumption and action time of each living behavior,
Set each energy device used in the living behavior for each item of the set second living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption for each item of the set second living behavior of the household is set using the set second life structure as an index and the action time of the set second living structure and each energy consumption of the set energy device as an index. It is characterized by quantitative evaluation of energy consumption for each item of daily activities.

Another aspect of the present invention is a method for visualizing the actual energy consumption at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
In the gas analysis, “TV (in-home)” corresponds to “bathing”, “hobby entertainment (net)” corresponds to “free action”
The energy consumption coefficient and the other second constant for each item of the second living behavior set above are classified and stored for each temperature category classified as spring, summer, autumn, and winter and for each day of the week. ,
For each life stage of a household, classify for each class of temperature and each day of the week, and store the average actor rate for each time for each item of the set first living behavior,
Energy consumption for each item of second living behavior set by one household from a value obtained by adding the other second constant to the sum of the average actor rate at each time and the product of the energy consumption coefficient Calculate, and act time,
Set each energy device used in the living behavior for each item of the set second living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption amount for each item of the set second living behavior of the household is used as an index of the action time of the set living behavior and the energy consumption amount of the set energy device as an index. Quantitative evaluation of energy consumption for each item,
Based on the quantitative evaluation, the breakdown of the energy consumption for each item of the set second living behavior is visualized using the energy consumption of the energy device and the action time as an index.

Another aspect of the present invention is a method for suggesting improvement of energy consumption behavior at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
In the gas analysis, “TV (in-home)” corresponds to “bathing”, “hobby entertainment (net)” corresponds to “free action”
The energy consumption coefficient and the other second constant for each item of the second living behavior set above are classified and stored for each temperature category classified as spring, summer, autumn, and winter and for each day of the week. ,
For each life stage of a household, classify for each class of temperature and each day of the week, and store the average actor rate for each time for each item of the set first living behavior,
Energy consumption for each item of the set second living behavior of one household from a value obtained by adding the second constant to the sum of the average actor rate at each time and the product of the energy consumption coefficient Calculate quantity, and action time,
Set each energy device to be used in the living behavior for each item of the set living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
For each item of the set second living behavior, the energy consumption amount for each item of the set second living behavior of the household is used as an index for the action time of the living behavior and the energy consumption of the set energy device. Quantitative evaluation of energy consumption
Based on the quantitative evaluation, an improvement proposal of energy consumption behavior corresponding to the life stage is posted.

Another aspect of the present invention is an electronic device or server equipped with at least one of the systems described above.
Here, the electronic device is, for example, a personal computer, a home appliance, or a mobile terminal. The server is a web server, for example.

ADVANTAGE OF THE INVENTION According to this invention, when designing the residence of one household, the energy system of a house can be reviewed by referring to the information of the estimation of the energy consumption for every time of one household, and energy saving of a house can be promoted. . The present invention is a technique that makes it possible to periodically and continuously evaluate representative results using only statistical data, for example.
That is, according to the present invention, it is possible to easily estimate the actual time-series energy consumption at home. This makes it possible to quantitatively evaluate the effects of energy saving measures corresponding to living activities at home, and thus has the effect of expanding the range of provision of energy saving measure information that is effective for each life stage of the home, for example.

It is the value of the coefficient data according to the living activity for weekdays used when the estimation system of the energy consumption in the home which concerns on embodiment of this invention calculates. It is the value of coefficient data according to living activity for Saturday used when the estimation system of energy consumption at home according to the embodiment of the present invention calculates. It is the value of the coefficient data classified by the daily activity for Sunday used when the estimation system of the energy consumption in the home which concerns on embodiment of this invention calculates. It is a block block diagram of the estimation system of the household energy consumption of 1st Embodiment which concerns on embodiment of this invention. It is an operation | movement flowchart of the estimation system of the energy consumption in a 1st Embodiment which concerns on embodiment of this invention. The figure which shows the example of the graph of the estimation P of the energy consumption of the electric power for every time per household which the estimation system of the energy consumption in the home of 1st Embodiment which concerns on embodiment of this invention displays on a display means. It is. It is a block block diagram of the domestic energy consumption management system of 2nd Embodiment which concerns on embodiment of this invention. It is an operation | movement flowchart (the 1) of the household energy consumption management system of 2nd Embodiment which concerns on embodiment of this invention. It is an operation | movement flowchart (the 2) of the household energy consumption management system of 2nd Embodiment which concerns on embodiment of this invention. It is a block block diagram of the local energy management system of 3rd Embodiment which concerns on embodiment of this invention. It is the operation | movement flowchart (the 1) of the local energy management system of 3rd Embodiment which concerns on embodiment of this invention. It is an operation | movement flowchart (the 2) of the local energy management system of 3rd Embodiment which concerns on embodiment of this invention. It is the value of the coefficient data according to the living activity for weekdays used when the evaluation system of the energy consumption actual condition in the home which concerns on embodiment of this invention calculates. It is the value of coefficient data according to daily activities for Saturday used when the evaluation system for the actual state of energy consumption at home according to the embodiment of the present invention calculates. It is the value of the coefficient data according to daily activity for Sunday used when the evaluation system of the actual state of energy consumption at home according to the embodiment of the present invention calculates. It is a block block diagram of the evaluation system of the energy consumption actual condition in the home of 4th Embodiment which concerns on embodiment of this invention. It is the value of the energy consumption data of the energy equipment used when the evaluation system of the energy consumption actual condition in the home which concerns on embodiment of this invention calculates. It is the value of the energy consumption data of the energy equipment used when the evaluation system of the energy consumption actual condition in the home which concerns on embodiment of this invention calculates. It is the energy equipment used for every item of the set living action used when the evaluation system of the energy consumption actual condition in the home concerning the embodiment of the present invention calculates. It is the energy equipment used for every item of the set living action used when the evaluation system of the energy consumption actual condition in the home concerning the embodiment of the present invention calculates. It is an operation | movement flowchart of the evaluation system of the energy consumption actual condition in the home of 4th Embodiment which concerns on embodiment of this invention. It is the figure which showed the quantitative evaluation result of the summer weekday of the evaluation system of the energy consumption actual condition in the home of 4th Embodiment which concerns on embodiment of this invention. It is the figure which showed the quantitative evaluation result of the winter weekday of the evaluation system of the energy consumption actual condition in the home of 4th Embodiment which concerns on embodiment of this invention. It is the figure which showed the quantitative evaluation result of the winter weekday of the evaluation system of the energy consumption actual condition in the home of 4th Embodiment which concerns on embodiment of this invention. It is a block block diagram of the visualization system of the energy consumption actual condition in the home of 4th Embodiment which concerns on embodiment of this invention. It is the energy consumption actual condition figure visualized with the visualization system of the energy consumption actual condition in the home of 4th Embodiment which concerns on embodiment of this invention. It is the energy consumption actual condition figure visualized with the visualization system of the energy consumption actual condition in the home of 4th Embodiment which concerns on embodiment of this invention. It is a block block diagram of the improvement proposal system of the home energy consumption action of 5th Embodiment which concerns on embodiment of this invention. It is an example of the proposal table | surface proposed in the improvement proposal system of the energy consumption action in a home of 5th Embodiment which concerns on embodiment of this invention. It is the value of the coefficient data according to the living activity used when the evaluation system of the energy (gas) consumption actual condition at home according to the embodiment of the present invention calculates.

(Principle of the present invention)
The present invention is a data obtained by a public institution for each household using HEMS (Home Energy Management System), and data on power consumption for each time of each individual device in the household, and gas and water consumption for each time. This is a technology that performs evaluation using public statistical data of data, household member information obtained from questionnaires to household members, and information on patterns of living behavior of each member. By applying multiple regression analysis to these statistical data, the following formula 1 for calculating and estimating the energy consumption estimate P of electric power at each time per household is obtained, and FIGS. The coefficient data shown was derived and stored in advance as a set value.
P = B1 * A1 + B2 * A2 + B3 * A3 + B4 * A4
+ B5 × A5 + B6 × A6 + B7 × A7 + C1
... Formula 1
Here, the other constant (C1) represents standby power in terms of power. In addition, in gas, it is regarded as 0.

In the present invention, the energy consumption estimation system 10 at home as shown in FIG. 4 calculates the energy consumption estimate P in Equation 1 in units of electric power (W) per unit time for each time.
In this energy consumption estimate P, the type of energy to be targeted is not limited to electric power, and energy obtained by gas combustion can also be included in the energy consumption estimate P. In addition, the estimated amount P of energy consumption of each type of energy can also be calculated by Equation 1 prepared for each type of energy.

  The values B1 to B7 in this formula 1 are the average actor rate by living behavior that represents the average actor rate by each living activity by the members of one household (the value in the case of 100% is 1). This is expressed as array data with different values for each time. Table 1 below shows examples of living behaviors respectively corresponding to the average actor rates B1 to B7 by living behavior in the present embodiment. The classification of items of living behavior to be set is not limited to this. What is necessary is just to select and set main living behaviors appropriately according to the actual situation such as lifestyle.

[Table 1]
(First living action performed independently)
B4: Cooking / Cleaning / Selection ... Food preparation / cleaning up, cleaning, washing / ironing, etc. B6: Hobby entertainment (net)
... Use the Internet as a hobby, entertainment, or play (except e-mail)
(First living behavior performed simultaneously by multiple people)
B1: Sleep ... 30 minutes or more of continuous sleep, nap, nap, etc. B2: Meals ... Breakfast, lunch, dinner, dinner, lunch, etc. , Makeup, haircut, etc. B5: TV (at home)
... Watching TV at home B7: Other / Unknown

Here, in the following estimation system, consumption management system, and regional energy management system, the living activities are tabulated so that there is no overlap in classification. (Living behavior that is not used is living behavior that is not implemented in the home or that does not affect energy estimation.)
In addition, in the energy consumption actual state evaluation system, the visualization system, and the improvement proposal system, which will be described later, there is an overlap in classification. This is because when using an energy device such as a television, a plurality of daily activities are performed simultaneously. Therefore, in the analysis regarding power, the item “TV (at home)) was changed to“ home activity ”and the item“ hobby entertainment (net) ”was changed to“ free action ”. In the gas analysis, the items were changed from "TV (in-home)" to "Bathing" and "Hobby entertainment (net)" to "Free action".
Average activist rates B1 to B7 by living behavior are classified into Table 1 for each set of live behavior items related to the average activists rates B1 to B7 by living behavior, and for each of the broadly classified live behavior items. The calculation method for calculating the average actor rate according to the living behavior is changed as follows.

(Living activities performed simultaneously by multiple people)
Actor rate is the average percentage of the total number of people in a single household who have made the corresponding living behavior (for 15 minutes or more) within one hour at a certain time. Is an array of data. The average actor rates B1, B2, B3, B5, and B7 classified as living behaviors performed simultaneously by a plurality of persons in the large classification of Table 1 define the average of the respective actor rates as the average actor rate.

(Living activities performed independently)
In the case of actors classified as living activities performed independently in the major classification of Table 1, there is a person who has even a little (15 minutes or more) of the corresponding living behavior within the time width of one hour at a certain time In addition, the actor rate of the living behavior at that time is set to 1, and otherwise, the actor rate of the living behavior is set to 0.
And the average activist rates B4 and B6 by living behavior are the averages of those actor rates 1 or 0 at multiple households at that time, averaged by multiple live behaviors at that time. Defined as person ratios B4 and B6.

  The array data based on the hourly data of the average actor ratios B1 to B7 according to the living behavior is to the members of the household for each household where the public institution acquires the power consumption for each hour using the HEMS. Derived from data obtained through questionnaires. That is, for each life stage of the household acquired by the questionnaire, based on the data of the actor rate of the living behavior of each household obtained by the questionnaire, the data for each time of the average actor rate B1 to B7 by living behavior is obtained. Obtained. In this embodiment, the life stages are classified as shown in Table 2 below.

[Table 2]
(1) Single life stage:
A person living alone who is 59 years old or younger.
(2) Couple life stage:
A married couple of workers who are assumed to be 59 years old or younger.
(3) Baby family life stage:
A working couple with preschoolers.
(4) Kids Family Life Stage:
The youngest child is a couple of elementary and junior high school students.
(5) Adult Family Early Life Stage:
The youngest child is a high school or college couple.
(6) Adult family late life stage:
A working couple with the youngest child working.
(7) Senior single life stage:
Unemployed living alone assuming the age of 60 or older.
(8) Senior couple life stage:
An unemployed couple living for 60 years or older.

(Constant C1 and coefficient An)
The constant C1 and the coefficients A1 to A7 in Equation 1 are coefficient data for each living activity that is a coefficient for each set item of living activity of the members of one household. FIG. 1 to FIG. 3 show coefficients A1 to A7 that are coefficient data according to living activities obtained by performing multiple regression analysis on public statistical data in an urban area of Japan, and other constants C1. The coefficients A1 to A7 and C1 for each living action item in FIG. 1 to FIG. 3 are measured by HEMS using the average activists ratios B1 to B7 according to living actions acquired based on questionnaires to household members as explanatory variables. The average power consumption at each time was obtained by multiple regression analysis with the dependent variable.

(Average temperature classification)
The classification of the average temperature applied to the calculation is determined by calculating the season according to the date of the day. In Tokyo, Japan, the average temperature is classified as 10 ° C to 13.8 ° C to 20 ° C in spring, 20 ° C to 27.2 ° C to 23 ° C in summer, and 23 ° C to 19.3 ° C to 12 ° C in autumn. In winter, the temperature is about 12 ° C to 5.6 ° C to 13 ° C.
The constant data C1 and coefficients A1 to A7, which are coefficients based on daily behavior obtained by multiple regression analysis, differ according to the average temperature category divided by the season of spring, summer, autumn, and winter. Different coefficients were obtained for each Sunday category.

The present invention uses the coefficients A1 to A7 of coefficient data for each living behavior and other constants C1 for each living behavior item of the members of one household, as a first of the estimation system 10 for energy consumption at home. Is stored in the coefficient data storage means 14 for each living activity. It is desirable that the coefficients A1 to A7 and other constants C1 which are the coefficient data for each living activity are acquired for each region and subjected to multiple regression analysis.
Note that n in An and Bn represents a subscript.

<First Embodiment>
(Home energy consumption estimation system)
FIG. 4 is a block diagram of the energy consumption estimation system 10 in the home according to the first embodiment.
The home energy consumption estimation system 10 is a computer system that is installed in an office or business office of a housing contractor and is executed by a computer. And, when a housing contractor can build a new home or renovate a housing customer, the customer can review the housing energy system and consider introducing energy-saving equipment cost-effectively. It is used to display information that estimates energy consumption for each time.

As shown in the block configuration diagram of FIG. 4, the household energy consumption estimation system 10 includes a life stage setting unit 11, a temperature classification / day classification setting unit 12, and a first average acter rate storage by living activity. Means 13, coefficient data storage means 14 according to daily activities, power consumption calculation unit 15 for each time, and power consumption estimated value storage means 16 for each time.
In this household energy consumption estimation system 10, the hourly power consumption calculation unit 15 calculates an estimation P of energy consumption for each hour per household according to Equation 1.

In the household energy consumption estimation system 10, the life stage setting means 11 classifies one household into a life stage, and the temperature classification and day classification setting means 12 classifies a predetermined day by its season and day of the week. To do.
In addition, the first behavioral average actor rate storage means 13 classifies the temperature behavior and the weekly day of the week for each life stage of the household, and sets the lifestyle behavior as the main item. The average actor rate for each item for each time is stored. In addition, the first behavioral coefficient data storage means 14 divides the energy consumption coefficient for each lifestyle behavior item and other constants C1 into categories of temperatures classified as spring, summer, autumn, and winter, and every day of the week. To remember.
Then, the hourly power consumption calculation unit 15 calculates an estimate P of energy consumption for each time per household in the classification for each living action item.

At the time of renovation of a new house or a house, a housing contractor uses the energy consumption estimation system 10 in this household to calculate an estimate P of energy consumption (electric power consumption) for each time per household. Then, an estimate P of energy consumption for each time per household is presented to the customer.
As a result, the customer reviews the residential energy system and uses it to consider the introduction of energy-saving equipment cost-effectively. Thereby, there is an effect that the customer can select a house with reduced energy consumption and promote energy saving of the house.

Next, processing of each unit of the energy consumption estimation system 10 in the home according to the present embodiment will be described in detail.
(Life stage setting means)
The life stage setting means 11 allows the operator of the household energy consumption estimation system 10 to select and designate the eight life stage classifications shown in Table 2 for one household and store the designated life stages. Store in the means.

(Temperature classification, day classification setting means)
The temperature classification / day-of-week classification setting means 12 allows the operator to input the area name and the date data using input means such as a keyboard or a touch panel. Next, the following data is calculated from the input data. Based on the date data, the average daily temperature of the house is classified into spring, summer, autumn and winter. The average temperature classification frame is not limited to spring, summer, autumn, and winter, and the temperature classification frame can be varied depending on the region. For example, in the tropics, the temperature classification frame can be made one.
The temperature classification / day-of-week classification setting unit 12 classifies the day of the week for calculating data into, for example, weekdays, Saturdays, Sundays, or holidays based on the input region name and date data. This classification frame is not limited to this. For example, a specific period in one month can be classified into a specific type of time frame depending on the country, the religious customs and culture of the family.

(Means for storing average actor rate data by daily behavior)
The first activist average actor rate storage means 13 stores the daily activist average actor rate data B1 to B7 for each life item, for each life stage, for each temperature category, and for each day of the week category. The array data for each time is stored. This set of average actuarial rate data by living behavior has data for each region to which the household belongs.
As described above, the actor rate data for each life activity for each life stage is stored in the first activist average actor rate storage means 13 for each living activity. For this reason, the operator of the energy consumption estimation system 10 at home is not required to input the rate of actors for each living activity at each time, so that there is an effect that the operator does not need to input data. .

(Coefficient data storage means for daily activities)
The coefficient data storage means 14 for each first living activity is provided with coefficients A1 to A7 and constants C1 of coefficient data for each living activity for each temperature category and each day of the week obtained by multiple regression analysis performed for each living activity. Remember. This set of coefficient data for each living activity has data for each region to which the household belongs.

(Power consumption calculator for each time)
The hourly power consumption calculation unit 15 obtains the average actor rate data B <b> 1 by life activity of the life stage, temperature classification, and day of week classification specified for the household from the first average action rate storage means 13 by life action. Read the array data for each time of B7. Further, C1 and A1 to A7, which are coefficient data by living activity, of the designated temperature classification and day of the week classification are read from the first living activity coefficient data storage unit 14.
Then, the hourly power consumption calculation unit 15 calculates an energy consumption estimate P for each time per household by calculating Equation 1 using those data, and the result is an estimated hourly power consumption value. The data is stored in the storage means 16 and the data is output.
Here, each storage means in the present embodiment is composed of, for example, a database or other storage device.

(Operation procedure)
The household energy consumption estimation system 10 according to this embodiment operates according to the following procedure according to the operation flowchart shown in FIG.
(Step S1)
The life stage setting means 11 allows the operator to select and designate the life stage classification of one household, and stores the designated life stage in the storage means.
(Step S2)
The temperature classification / day-of-week classification setting unit 12 allows the operator to input the area name and month / day data using an input unit such as a keyboard or touch panel.

(Step S3)
Based on the input data, the temperature classification / day-of-week classification setting means 12 performs calculation to classify the average daily temperature of the house into spring, summer, autumn, and winter.
(Step S4)
The temperature classification / day-of-week classification setting means 12 performs calculation for classifying the day of the week for calculating data into weekdays, Saturdays, Sundays or holidays based on the date data.
(Step S5)
The hourly power consumption calculation unit 15 stores the life stage specified for the household from the first activist average actor rate storage means 13 and the average acterial rate data B1 by life activity of the temperature classification and day of the week classification. Read the array data for each time of B7.

(Step S6)
The hourly power consumption calculation unit 15 reads the coefficient data C1 and A1 to A7 according to the living behavior of the specified temperature classification and day of the week classification from the first coefficient of behavior data storage means 14.
(Step S7)
The hourly power consumption calculation unit 15 calculates Equation 1 using those data, thereby calculating an estimate P of energy consumption for each hour per household, and calculating the result of the calculation for the hourly power consumption. The data is stored in the value storage means 16, and the data is edited and displayed on the display means to notify the operator.

FIG. 6 shows a display example of the estimation P of the energy consumption of electric power for each time per household displayed by the display means. FIG. 6 shows a case where the estimated value P of the energy consumption at each time per household on weekdays when the average temperature distribution of the household in the baby family life stage is spring is displayed as a bar graph for each time. In FIG. 6, the bar of the bar graph represents the breakdown of Equation 1 for each life activity. That is, the added value of the product of the average action rate Bn for each living behavior and the coefficient data An for each living behavior of Equation 1 is represented on the bar of the bar graph.
In this way, the breakdown of Equation 1 for each living behavior is represented in the graph, which has an effect of expressing information on which living behavior is main at a certain time.

Thus, the home energy consumption estimation system 10 according to the present embodiment performs, for each life activity item at each time, a calculation for estimating the power consumption of the device mainly used in the life activity item. The result can be notified to the operator at each time.
The housing contractor uses this household energy consumption estimation system 10 so that when a housing customer plans a new home or a home renovation, the housing contractor The transition of the estimated amount P of the energy consumption (power consumption) for each time can be quickly displayed.

  The energy generated by the estimation system 10 for energy consumption in the home according to the present embodiment is used to estimate the amount of power generation per hour when a photovoltaic power generation system or storage battery system is installed in the customer's household or the estimation data of the charging energy of the storage battery system. By summing up with the calculation result of the consumption estimate P, the total power required by the energy system of the household can be calculated.

The contractor of the house shows the specific effects of introducing the solar power generation system and storage battery system to the customer, and the customer reviews the energy system of the house with reference to the information, and considers the introduction of energy-saving equipment cost-effectively. Served for use. Accordingly, there is an effect that the customer can promote the construction of a house with a reduced energy consumption, such as a solar power generation system or a storage battery system, and promote energy saving of the house.
As another effect, the energy consumption estimation system 10 displays information for estimating a device that consumes a large amount of power in the household, so that the customer can reduce the power consumption of the device. It has the effect of making it possible to accurately formulate a power saving plan that reduces energy consumption of households.

<Second Embodiment>
(Home energy consumption management system)
The functional block diagram of the domestic energy consumption management system 20 which is the computer system of 2nd Embodiment performed with a computer is shown in the block block diagram of FIG. The home energy consumption management system 20 of the second embodiment incorporates the home energy consumption estimation system 10 described in the first embodiment as shown in the block configuration diagram of FIG. The temperature data input means 21, the power consumption demand response communication means 22, the power consumption adjustment amount calculation means 23, and the power consumption adjustment means 24 that controls the power consumption of the controlled home appliance 25. This home energy consumption management system 20 is installed and used in a house of each home.

The home energy consumption management system 20 includes the home energy consumption estimation system 10 similar to that of the first embodiment, and in addition to the following functional means.
(Temperature data input means)
That is, the home energy consumption management system 20 has temperature data input means 21, and the temperature data input means 21 measures the temperature data of the outside air of the house. Alternatively, the temperature data input means 21 may be means for receiving weather data through a communication line.
(Power consumption demand response communication means)
Further, the home energy consumption management system 20 has a power consumption demand response communication means 22 via which the power price to be added from the local energy management system 30 to the power exceeding the predetermined power at the time of peak power demand. A demand signal for notifying is received.
The household energy consumption management system 20 that has received the demand signal performs a calculation for planning the amount of power used, and returns the calculated power consumption plan amount to the local energy management system 30.

(Power consumption adjustment amount calculation means)
That is, the power consumption adjustment amount calculation means 23 of the household energy consumption management system 20 obtains predetermined power at the time when the demand for power peaks from the local energy management system 30 via the power consumption demand response communication means 22. A demand signal including data of an electric power price that is excessively required when using more electric power is received.

Next, the power consumption adjustment amount calculation means 23 displays the data of the power price and the estimated power consumption value of the output of the energy consumption estimation system 10 at home to the members of the household. Then, in response to an instruction from a member of the household, the power consumption plan amount of the household at the time when the power demand reaches a peak is determined and stored.
Then, the household energy consumption management system 20 of each household transmits the data of the planned power consumption of the household to the regional energy management system 30 via the power consumption demand response communication means 22.

(Power consumption adjustment means)
Then, the power consumption adjustment amount calculation means 23 of the home energy consumption management system 20 uses the power consumption adjustment means 24 to calculate the total power consumption amount of the controlled home appliance 25 at the time when the demand for power peaks. Control to limit power consumption to the planned power consumption or less. For example, control is performed to change the set temperature value of the controlled household electrical appliance 25 of the air conditioner, or the upper limit of the maximum power consumption of the controlled household electrical appliance 25 of the electromagnetic cooker is limited.

(Operation procedure)
The household energy consumption management system 20 of this embodiment operates in the following procedure shown in the flowcharts of FIGS.
(Step S1)
As an initial setting of the home energy consumption management system 20, an initial setting of communication with the local energy management system is performed.
Further, the life stage setting means 11 of the household energy consumption estimation system 10 allows the system operator in the household to select and specify the life stage classification of one household, and use the designated life stage as the storage means. Remember. In addition, as an initial setting, the operator inputs the name of the area to which the household belongs. Then, the coefficients A1 to A7 of the coefficient data for living activities and the constant C1 for the input region name are prepared in the first coefficient data storage means 14 for living activities as coefficient data for calculation.

(Step S2)
Next, the temperature classification / day-of-week classification setting means 12 reads the date data from the date / time clock 17.
(Step S3)
Next, the temperature classification / day-of-week classification setting unit 12 reads the temperature data of the house from the temperature data input unit 21.
(Step S4)
Next, the temperature classification / day-of-week classification setting means 12 classifies the average daily temperature of the house of the household into spring, summer, autumn, and winter using the data of the month and the temperature. Perform the calculation.

(Step S5)
The temperature classification / day-of-week classification setting means 12 performs calculation for classifying the day of the week for calculating data into weekdays, Saturdays, Sundays or holidays based on the date data.
(Step S6)
The hourly power consumption calculation unit 15 stores the life stage specified for the household from the first activist average actor rate storage means 13 and the average acterial rate data B1 to B1 of the living behavior of the temperature classification and the day of the week classification. Read array data for each time of B7.
(Step S7)
The hourly power consumption calculation unit 15 reads the constant C1 and the coefficients A1 to A7, which are coefficient data for each living activity, of the specified temperature classification and day of the week classification from the first living activity-specific coefficient data storage means 14.

(Step S8)
The hourly power consumption calculation unit 15 calculates Equation 1 using those data, thereby calculating an estimate P of energy consumption for each hour per household, and the calculated result is an estimated hourly power consumption value. Store in the storage means 16.
(Step S9)
The power consumption adjustment amount calculating means 23 receives a demand signal for notifying the power price to be added to the power exceeding the predetermined power at the time of peak power demand from the local energy management system 30 via the power consumption demand response communication means 22. To do.

(Step S10)
The power consumption adjustment amount calculation means 23 displays the cost estimate data which is received from the regional energy management system 30 and is necessary when using power exceeding the predetermined power at the time when the demand for power peaks. By displaying with, let the members of the household observe the data. Further, the power consumption adjustment amount calculation means 23 displays information on the estimated energy consumption P for each time per household on the display means, thereby allowing the members of the household to observe the data.
(Step S11)
Next, in response to an instruction from a household member, the power consumption adjustment amount calculating means 23 determines and stores the power consumption plan amount of the household at the time when the demand for power peaks.

(Step S12)
Next, the power consumption adjustment amount calculation unit 23 transmits the power consumption plan amount data of the household to the local energy management system 30 via the power consumption demand response communication unit 22.
(Step S13)
Then, the power consumption adjustment amount calculation means 23 of the home energy consumption management system 20 uses the power consumption adjustment means 24 to calculate the total power consumption amount of the controlled home appliance 25 at the time when the demand for power peaks. Control to limit power consumption to the planned power consumption or less.
For example, control is performed to change the set temperature value of the controlled household electrical appliance 25 of the air conditioner, or the upper limit of the maximum power consumption of the controlled household electrical appliance 25 of the electromagnetic cooker is limited.

In this way, the home energy consumption management system 20 according to the present embodiment calculates the estimate P of the energy consumption of the home by using the home energy consumption estimation system 10 while communicating with the local energy management system 30. Then, the power demand is estimated, the planned power consumption in the home is calculated, and the planned power consumption in the home is returned to the local energy management system 30. Further, the power consumption of the controlled home appliance 25 in the home is controlled in accordance with the planned power consumption in the home.
By using the household energy consumption management system 20 of the present embodiment, the household members can calculate the energy consumption estimate P for each time per household and display it. There is an effect that it is possible to accurately plan the power consumption plan amount of the household at the peak time.

<Third Embodiment>
(Regional energy management system)
The block configuration diagram of FIG. 10 shows the configuration of the functional means of the regional energy management system 30 according to the third embodiment. The regional energy management system 30 of the third embodiment incorporates the home energy consumption estimation system 10 described in the first embodiment as shown in the block configuration diagram of FIG. Household number storage means 31, average temperature data input means 32, total household power consumption estimation means 33, hourly power consumption estimation means 34 other than households, power supply / demand adjustment means 35, and generator operation control means 36 And power consumption demand response communication means 37.

  The local energy management system 30 is a small generator or storage battery system such as a generator using a fuel cell or a gas engine per one building such as a school or a building or a small group of a plurality of households. The generator 40 is installed to manage the power generation amount of the reserve power. That is, the local energy management system 30 estimates the power consumption at each time of the one building, etc. by using the output from the generator 40 and the commercial power from the electric power company, and estimates the power consumption. Then, the generator 40 is operated.

This regional energy management system 30 includes the following functional means in addition to the energy consumption estimation system 10 at home as shown in the block diagram of FIG.
(Means for storing the number of households per life stage)
That is, the local energy management system 30 has a life stage household number storage means 31, which stores the number of households for each life stage of the household to which energy (electric power) is supplied. Further, the local energy management system 30 has an average temperature data input means 32, which measures the average temperature of the outside air in the area or receives weather data through a communication line.

(All household power consumption estimation means)
Moreover, the local energy management system 30 has the total household power consumption estimation means 33, which totals the estimated power consumption values of all households in the household.
(Measuring method for power consumption by time at locations other than home)
Further, the local energy management system 30 has hourly power consumption estimation means 34 for bases other than homes, which calculate energy consumption estimates for bases other than homes to which energy (electric power) is supplied.

(Power supply / demand adjustment means)
Further, the local energy management system 30 has power supply and demand adjustment means 35, which receives data on the estimated power consumption at every time of all households from the total household power consumption estimation means 33, and also has a base other than the home. From the hourly power consumption estimation means 34, energy consumption estimation data for each time at a base other than the home is received. The power supply / demand adjustment unit 35 includes a calculation unit, a transmission unit, a reception unit, and a second calculation unit.

(Generator operation control means)
Then, the power supply / demand adjustment means 35 calculates a load pattern for each time of the total power consumption from the received data (calculation means). Next, based on the load pattern obtained by the power supply / demand adjustment means 35, the generator operation control means 36 operates the generator 40 to generate power to compensate for the insufficient power. Here, the storage battery system that supplies electric power is also classified as a kind of generator 40.

(Power consumption demand response communication means)
Further, the power supply / demand adjustment means 35 calculates the increased cost associated with the operation of the generator 40 that needs to be operated according to the power supply / demand relationship. Then, the amount charged for power exceeding the predetermined power is calculated. Then, the power consumption demand response communication means 37 adds the power exceeding the predetermined power at the peak of power demand to the home energy consumption management system 20 of each home and the energy consumption management system of the base other than the home. A demand signal for notifying the power price is transmitted (transmission means).

  When the household energy consumption management system 20 of each household receives the data of the amount charged for the power exceeding the predetermined power, the household power consumption management system 20 determines the power consumption plan amount of the household at the time when the power demand in the area peaks. Calculate and remember. Then, the household energy consumption management system 20 of each household transmits data on the planned power consumption of the household to the regional energy management system 30.

The power supply / demand adjustment means 35 of the local energy management system 30 receives data on the planned power consumption of each household from each household via the power consumption demand response communication means 37, and the energy consumption of all bases other than the household. Receives power consumption plan data from the management system (reception means).
Then, the power supply / demand adjustment means 35 calculates the load pattern of the total power consumption for each time again using the estimated power consumption values and the power consumption plan amount for all the households and all the bases (second time). Calculation means). Based on the load pattern, the power supply / demand adjustment means 35 operates the generator 40 via the generator operation control means 36 to perform power generation to compensate for the insufficient power.

(Operation procedure)
The regional energy management system 30 of the present embodiment operates according to the following procedure shown in the flowcharts of FIGS.
(Step S1)
In the initial stage of the operation of the system, the local energy management system 30 performs initial communication settings for performing communication with the household energy consumption management system 20 of each household in the area via the power consumption demand response communication means 37. Do.
Further, the local energy management system 30 stores the life stage classification of each household in the area in the household number storage means 31 for each life stage. Thereby, the household number storage means 31 for each life stage stores the number of households for each life stage of households in the area.

Moreover, the local energy management system 30 prepares coefficient data for calculating the activity-specific coefficient data C1 and A1 to A7 for the area in the first activity-specific coefficient data storage means 14.
In addition, the local energy management system 30 uses the array data for each time of the daily behavioral average actor rate data B1 to B7 for each life stage of the household for the region, as the first average behavioral rate by daily behavioral activity. Store in the storage means 13.

(Step S2)
Next, the temperature classification / day-of-week classification setting means 12 reads the date data from the date / time clock 17.
(Step S3)
Next, the temperature classification / day-of-week classification setting unit 12 reads the average temperature data of the area from the average temperature data input unit 32.
(Step S4)
Next, the temperature classification / day-of-week classification setting means 12 performs calculation for classifying the average daily temperature classification of the area into spring, summer, autumn, and winter using the data of the month and the temperature. Do.

(Step S5)
The temperature classification / day-of-week classification setting means 12 performs calculation for classifying the day of the week for calculating data into weekdays, Saturdays, Sundays or holidays based on the date data.
(Step S6)
For each life stage in the region, the hourly power consumption calculation unit 15 reads the average actor rate by life activity of the life stage, temperature classification and day of the week classification from the first activist average actor rate storage means 13. Array data for each time of data B1 to B7 is read.

(Step S7)
The hourly power consumption calculation unit 15 reads the constant C1 and the coefficients A1 to A7, which are coefficient data for each living activity, of the designated temperature classification and day of the week classification from the first living activity-specific coefficient data storage unit 14.
(Step S8)
The hourly power consumption calculation unit 15 calculates Equation 1 using those data, thereby calculating an estimate P for the energy consumption per hour per household in the life stage, and the result is calculated for each hour. This is stored in the power consumption estimated value storage means 16.
(Step S9)
The total household power consumption estimation means 33 reads the data of the estimated energy consumption P for each time per household in the life stage from the hourly power consumption estimated value storage means 16 and multiplies the number of households in the life stage. Thus, an estimate of energy consumption for every household in the same life stage is calculated and stored.

(Step S10)
The total household power consumption estimation means 33 repeats the processing from step S6 to step S9, calculates all life stages, and totals the calculation results, thereby estimating the energy consumption for each time of all households in all life stages. Calculate and store the amount.
(Step S11)
Next, the hourly power consumption estimation means 34 of the base other than the home calculates an estimate of the energy consumption for each time of all the bases other than the homes in the area.

(Step S12)
Next, the power supply / demand adjustment means 35 receives the data of the estimated power consumption at every time of all households from the total household power consumption estimation means 33, and the home power from the hourly power consumption estimation means 34 at a base other than the home. Data on estimation of energy consumption for each time at a base other than the above are received, and a load pattern for each time of total power consumption in that region is calculated (calculation means).
(Step S13)
Next, the power supply / demand adjustment means 35 calculates the increased cost associated with the operation of the generator 40 that needs to be operated according to the power supply / demand relationship. Then, the amount charged for power exceeding the predetermined power is calculated.

(Step S14)
Next, the home energy consumption management system 20 of the home that the power supply / demand adjustment means 35 has estimated that the power consumption is large at the time of the power demand peak via the power consumption demand response communication means 37 and the base other than the home A demand signal for notifying the energy consumption management system of the power price to be added to the power exceeding the predetermined power at the time of peak power demand is transmitted (transmission means).
(Step S15)
Next, the power supply / demand adjustment unit 35 receives household power consumption plan data from the household energy consumption management system 20 of each household via the power consumption demand response communication unit 37 (reception unit). Moreover, the data of the power consumption plan amount of bases other than homes are received from the energy consumption management system of all bases other than homes.

(Step S16)
The power supply / demand adjustment means 35 again calculates the load pattern for each time of the total power consumption using the estimated power consumption values and the power consumption plan amounts for all households and all bases at each time (second calculation). means).
(Step S17)
Based on the load pattern, the power supply / demand adjustment means 35 calculates an operation plan for the generator 40 on that day.
(Step S18)
Based on the operation plan of the generator 40 on that day, the generator operation control means 36 operates the generator 40 to generate power to compensate for the insufficient power.
The regional energy management system 30 repeats the processing from step S2 to step S18 every day. In addition, whenever the number of households in the area changes, the process of step S1 is performed to update the data on the number of households for each life stage.

(Principle according to the following embodiment)
The present invention according to the embodiment to be described below is based on data obtained by a public institution for each household using HEMS (Home Energy Management System), data of power consumption for each individual device of the household, and gas and We used official statistical data of consumption data for each hour of water supply, information on household members obtained from questionnaires to household members, and information on lifestyle patterns of each member . By applying multiple regression analysis to these statistical data, the following formula 2 for calculating and estimating the energy consumption estimate P for each time per household and the coefficient data shown in FIGS. Was derived.
P = B1 * A1 + B2 * A2 + B3 * A3 + B4 * A4
+ B5 × A5 + B6 × A6 + B7 × A7 + C2
... Formula 2
Here, the other constant (C2) represents standby power in power. In addition, in gas, it is regarded as 0.

In the present invention, the energy consumption actuality evaluation system 50 in the home as shown in FIG. 16 calculates the estimated energy consumption P in Equation 2 in units of power (W) per unit time for each time. .
In this energy consumption estimate P, the type of energy to be targeted is not limited to electric power, and energy obtained by gas combustion can also be included in the energy consumption estimate P. In addition, the estimated amount P of energy consumption of each type of energy can also be calculated by Equation 2 prepared for each type of energy.

The values B1 to B7 in this formula 2 are the average actor rate by living behavior that represents the average actor rate by each living behavior by the members of one household (the value in the case of 100% is 1). This is expressed as array data with different values for each time. Table 3 below shows the items of the second living behavior set in the embodiment described below corresponding to the average acting rates B1 to B7 by living behavior. The example of the item of the 1st living action is the same as that of above-mentioned Table 1.
It should be noted that the classification of items of living behavior is not limited to this. What is necessary is just to select and set the item of main living behavior suitably.

[Table 3]
(Second living behavior performed independently)
B4: Cooking, cleaning and selection.
B6: Free behavior (second living behavior performed simultaneously by multiple people)
B1: Sleep B2: Meal B3: Personal affairs B5: Home behavior B7: Other / unknown

That is, in the following embodiment, as the items of living behavior in one household, the first plurality of items of living behavior and the second plurality of items of living behavior are set in advance.
The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, and “Cooking” in the same manner as the items of living behavior in the above-described embodiment. -“Cleaning and washing”, “Personal affairs”, “Meals”, and “Other actions”.
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And “meal” and “other actions”.

  Depending on the energy equipment, in the analysis related to power, “TV (at home)” corresponds to “at-home behavior”, “hobby entertainment (net)” corresponds to “free behavior”, and in the analysis related to gas, “TV (at home)” corresponds to “bathing”, and “hobby entertainment (net)” corresponds to “free action”. Thus, the analysis accuracy of the actual energy consumption increases by selecting the living behavior depending on the energy equipment to be used.

here,
Staying home (Waking up at national life time) ... It is the time when you get up and are active.
Free actions: Actions with high discretion to maintain and improve humanity.
It consists of mass media contact, active leisure activities, conversation / community centered on meeting / speaking with people, rest centered on resting mind and body.
Bathing ... Bathing at home (including bathing in the bathtub and shower)
Other / Unknown ... An action that does not apply to any of the above.
The contents of other living behaviors are the same as described above.

The average activist rates B1 to B7 by living behavior are classified into Table 3 for each item of living behavior related to the average activist rates B1 to B7 by living behavior, The calculation method for calculating the average actor rate according to daily activities is changed as follows.
(Second living behavior performed simultaneously by multiple people)
Actor rate is the average percentage of the total number of people in a single household who have made the corresponding living behavior (for 15 minutes or more) within one hour at a certain time. Is an array of data. The average actor rates B1, B2, B3, B5, and B7 classified as living behaviors performed simultaneously by a plurality of persons in the large classification of Table 3 define the average of the respective actor rates as the average actor rate.

(Second living behavior performed independently)
In the case of actors classified as living activities performed independently in the major classifications in Table 3, there is a person who has even a little (15 minutes or more) of the corresponding living behavior within the time width of one hour at a certain time In addition, the actor rate of the living behavior at that time is set to 1, and if not, the actor rate of the living behavior is set to 0.
And the average activist rates B4 and B6 by living behavior are the averages of those actor rates 1 or 0 at multiple households at that time, averaged by multiple live behaviors at that time. Defined as person ratios B4 and B6.

  The array data based on the hourly data of the average actor ratios B1 to B7 according to the living behavior is to the members of the household for each household where the public institution acquires the power consumption for each hour using the HEMS. Derived from data obtained through questionnaires. That is, for each life stage of the household acquired by the questionnaire, based on the data of the actor rate of the living behavior of each household obtained by the questionnaire, the data for each time of the average actor rate B1 to B7 by living behavior is obtained. Obtained. The life stages are classified as shown in Table 4 below.

[Table 4]
(1) Single life stage:
A person living alone who is 59 years old or younger.
(2) Couple life stage:
A married couple of workers who are assumed to be 59 years old or younger.
(3) Baby family life stage:
A working couple with preschoolers.
(4) Kids Family Life Stage:
The youngest child is a couple of elementary and junior high school students.
(5) Adult Family Early Life Stage:
The youngest child is a high school or college couple.
(6) Adult family late life stage:
A working couple with the youngest child working.
(7) Senior single life stage:
Unemployed living alone assuming the age of 60 or older.
(8) Senior couple life stage:
An unemployed couple living for 60 years or older.

(Constant C2 and coefficient An)
The other second constant C2 and coefficients A1 to A7 in Equation 2 are coefficient data for each living activity, which is a coefficient for each second living activity item of a member of one household. FIG. 13 to FIG. 15 show constant C2 and coefficients A1 to A7 of coefficient data for each second living activity obtained by performing multiple regression analysis of public statistical data in an urban area in Japan. The coefficients for each living behavior item in FIGS. 13 to 15 are the average of each time measured by HEMS, using the average activist rates B1 to B7 by living behavior obtained based on questionnaires to members of the household as explanatory variables. Obtained by multiple regression analysis with power consumption as the dependent variable.
In addition, when energy (apparatus) is gas, the coefficient data according to the second living action as shown in FIG. 30 is adopted. The calculation method is similarly obtained by multiple regression analysis.

In the following description, the case of using the coefficient data according to the living activities in FIGS. 13 to 15 will be described as a main example.
(Average temperature classification)
The classification of the average temperature applied to the calculation is determined by calculating the season according to the date of the day. In Tokyo, Japan, the average temperature is classified as 10 ° C to 13.8 ° C to 20 ° C in spring, 20 ° C to 27.2 ° C to 23 ° C in summer, and 23 ° C to 19.3 ° C to 12 ° C in autumn. In winter, the temperature is about 12 ° C to 5.6 ° C to 13 ° C.

C2 and coefficients A1 to A7, which are coefficient data based on daily behavior obtained by multiple regression analysis, differ according to the category of average temperature divided by spring, summer, autumn, and winter season. Different coefficients were obtained for each category.
The present invention stores the coefficient data C2 and coefficient A1 to A7 for each living activity of each member of one household, and the coefficient data storage means for each living activity of the evaluation system 50 for the actual energy consumption at home. Store at 54. The coefficient data C2 and the coefficients A1 to A7 for each living activity are desirably acquired for each region and subjected to multiple regression analysis.

<Fourth Embodiment>
(Evaluation system for energy consumption at home)
FIG. 16 shows a block configuration diagram of an evaluation system 50 for the actual state of energy consumption at home in the fourth embodiment.
The energy consumption actuality evaluation system 50 in this home is a computer system that is installed in an office or business office of a housing contractor and is executed by a computer. And, when a housing contractor can build a new home or renovate a housing customer, the customer can review the housing energy system and consider introducing energy-saving equipment cost-effectively. It is used to display information that estimates energy consumption for each time.

  As shown in the block configuration diagram of FIG. 16, this household energy consumption evaluation system 50 includes a life stage setting means 51, a temperature classification / day of the week classification setting means 52, and a first average average actor rate memory for each living activity. Means 53, second daily activity-specific coefficient data storage means 54, second daily activity-specific action time storage means 63, hourly consumption energy calculation unit 55, and second daily activity item energy consumption calculation unit 56, energy consumption storage means 57 for each energy device, second use energy device storage means 58 for each living behavior, energy consumption actual state quantitative evaluation calculation unit 59 for each second living behavior item, and second living behavior item Each energy consumption actual condition quantitative evaluation result storage means 60 is provided.

In this household energy consumption evaluation system 50, the hourly power consumption calculation unit 15 calculates an estimate P of energy consumption per hour per household according to Equation 2.
In the household energy consumption evaluation system 50, the life stage setting means 51 classifies one household into a life stage, and the temperature classification and day classification setting means 52 classifies a predetermined day by its season and day of the week. To do.

Further, the first activist average actor rate storage means 53 for each life stage of each household, for each temperature category and for each day of the week, for each time of each item of the first act of living. Memorize the average actor rate. In addition, the second daily behavior coefficient data storage means 54 classifies the energy consumption coefficients A1 to A7 and other constants C2 for each item of the second daily behavior into the spring, summer, autumn, and winter temperatures. Remember every classification and every weekday.
Then, the hourly consumption energy calculation unit 55 calculates an estimate P of energy consumption for each hour per household in the classification for each item of the second living behavior.

At the time of renovation of a new house or house, a housing contractor calculates an estimate P of energy consumption (electric power consumption) per household using the evaluation system 50 for actual energy consumption in this household. Then, an estimate P of energy consumption for each time per household is presented to the customer.
As a result, the customer reviews the residential energy system and uses it to consider the introduction of energy-saving equipment cost-effectively. Thereby, there is an effect that the customer can select a house with reduced energy consumption and promote energy saving of the house.

The processing content of each means in the evaluation system 50 for the actual state of energy consumption at home in this embodiment will be described in detail below.
(Life stage setting means)
The life stage setting means 51 allows the operator of the household energy consumption evaluation system 50 to select and designate the eight life stage classifications shown in Table 2 for one household and store the designated life stages. Store in the means.

(Temperature classification, day classification setting means)
The temperature classification / day-of-week classification setting means 52 allows the operator to input the area name and month / day data using an input means such as a keyboard or a touch panel. Next, the following data is calculated from the input data. Based on the date data, the average daily temperature of the house is classified into spring, summer, autumn and winter. The average temperature classification frame is not limited to spring, summer, autumn, and winter, and the temperature classification frame can be varied depending on the region. For example, in the tropics, the temperature classification frame can be made one.
Further, the temperature classification / day-of-week classification setting unit 52 classifies the day of the week for calculating the data into, for example, weekdays, Saturdays, Sundays or holidays based on the input region name and date data. This classification frame is not limited to this. For example, a specific period in one month can be classified into a specific type of time frame depending on the country, the religious customs and culture of the family.

(First means of storing the average actor rate by living behavior)
The first activist average actor rate data storage means 53 for each first life item, for each life stage, temperature class, and day of week class, the average acterial rate data B1 to B7 by act of life Each sequence data is stored. This set of average actuarial rate data by living behavior has data for each region to which the household belongs.
As described above, the actor rate data for each life stage and for each living activity is stored in the average actor rate storage means 53 for each living activity, so the operator of the energy consumption actual state evaluation system 50 at home. Since there is no need to input the actor rate for each living activity at every time, there is an effect that the operator does not need to input data.

(Second life activity coefficient data storage means)
The coefficient data storage means 54 for each second living activity is a constant C2 and a coefficient which are coefficient data for each living activity and for each day of the week obtained by multiple regression analysis performed for each second living activity. A1 to A7 are stored. This set of coefficient data for each living activity has data for each region to which the household belongs.

(Time energy consumption calculator)
The hourly consumption energy calculating unit 55 obtains the second average acterial rate according to the living behavior of the life stage, the temperature category, and the day of the week category specified for the household from the first activistic average actor rate storage unit 53. Array data for each time of data B1 to B7 is read. Further, the constant C2 and the coefficients A1 to A7, which are the coefficient data for each living action of the second living action, of the designated temperature classification and day of the week classification are read from the second living action coefficient data storage means 54.
And the hourly consumption energy calculating part 55 calculates the estimation P of the energy consumption for every hour per household by calculating Formula 2 using those data.

(Second life activity item energy consumption calculator)
The energy consumption amount calculation unit 56 for each second living action item is calculated for each second living action item from the estimated energy consumption P for each time per household calculated by the hourly consumption energy calculation unit 55. Calculate energy consumption.
(Second action-by-life action storage means)
Based on the information from the life stage setting means 51, the second action time storage means 63 for each living action calculates and stores the action time T for each second living action in advance.

(Energy consumption storage means by energy device)
The energy consumption storage unit 57 for each energy device stores the energy consumption amount e per unit calculated by using the published value in the energy device data. 17 and 18 show examples of energy consumption e for each device.
(Second use energy device storage means according to daily activities)
The second energy-use-use energy device storage means 58 stores energy device data set to be used for each second life activity. 19 and 20 show examples of the set energy device data.

(Second Life Action Item Energy Consumption Quantitative Evaluation Calculation Unit)
The energy consumption actual condition quantitative evaluation calculating unit 59 for each second living action item is calculated for each second living action item from the second living action item energy consumption calculating unit 56 and the second action time storing means 63 for each living action. Energy consumption and the action time for each second living action item are read out. Further, the energy consumption data for each device is read from the energy consumption storage unit 57 for each energy device. Further, energy device data set to be used for each second living behavior is read from the second used energy behavior storage device 58 for each living behavior.

And the energy consumption actual condition quantitative evaluation calculating part 59 for every 2nd living action item calculates the energy consumption e for every item of the set 2nd living action by calculating Formula 3 using those data, Quantitative evaluation is performed using the action time T of each living action and the energy consumption in the energy device as indices.
P = e × T Equation 3
The quantitative evaluation result is stored in the energy consumption actual state quantitative evaluation result storage means 60 for each second living action item, and the data is output.

(Operation procedure)
The energy consumption actual state evaluation system 50 in this embodiment operates according to the following procedure according to the operation flowchart shown in FIG.
(Step S1)
The life stage setting means 51 causes the operator to select and designate the life stage classification of one household, and stores the designated life stage in the storage means.
(Step S2)
The temperature classification / day-of-week classification setting means 52 allows the operator to input the area name and date data using input means such as a keyboard or a touch panel.
(Step S3)
The temperature classification / day-of-week classification setting means 52 performs a calculation for classifying the average daily temperature of the house into spring, summer, autumn, and winter from the input data.

(Step S4)
The temperature classification / day-of-week classification setting means 52 performs calculation to classify the day of the week for calculating data into weekdays, Saturdays, Sundays or holidays based on the date data.
(Step S5)
The hourly consumption energy calculating unit 55 stores the life actors, temperature classifications, and day of week classifications of the average actor percentage data B1 to B1 of the household specified by the household from the first average behavioral percentage storage means 53. Read the array data for each time of B7.
(Step S6)
The hourly consumption energy calculation unit 55 reads the constant C and the coefficients A1 to A7, which are the coefficient data for each living activity, of the specified temperature classification and day of the week classification from the coefficient data storage means 54 for each living activity.

(Step S7)
The hourly energy consumption calculation unit 55 calculates an estimate P of energy consumption for each hour per household by calculating Equation 2 using these data.
(Step S8)
By calculating the energy consumption amount calculation unit 56 for each second living action item using the estimated energy consumption P for each time per household, the estimated energy consumption P for each time per household is calculated. The energy consumption for each second living action item and the action time T for each second living action item are calculated.
(Step S9)
The energy consumption actual condition quantitative evaluation calculation unit 59 for each second living action item reads the energy consumption e for each device from the energy consumption storage means 57 for each energy device.

(Step S10)
The energy consumption actual condition quantitative evaluation calculation unit 59 for each second living activity item reads out energy device data set for each second living activity from the second energy usage storage device 58 for each living activity.
(Step S11)
The energy consumption actual condition quantitative evaluation calculating unit 59 for each second living action item calls the action time T for each second living action from the second action action storing means 63 for each living action.
(Step S12)
The energy consumption actual condition quantitative evaluation calculation unit 59 for each second living action item calculates Equation 3 using those data, and the energy consumption amount for each item of the set living action is calculated as the second living action item. Quantitative evaluation is performed using each action time T and energy consumption e in the energy equipment as an index. The evaluation result is stored in the energy consumption actual condition quantitative evaluation calculation unit 59 for each second living action item, and the data is displayed on the display means to notify the operator.

22 to 24 are examples of quantitative evaluation results. 22 to 24 are scatter diagrams created with the action time on the horizontal axis and the consumption per unit time of various energies on the vertical axis.
FIG. 22 is a diagram showing the quantitative evaluation results by household composition on summer weekdays.
As shown in FIG. 22, in summer, the free behavior is that households with children who are not adults, such as kids families and adult families (first half), have a large power consumption per unit time. It is confirmed that senior households tend to have long hours of action. It is confirmed that the average actor rate and action time for free behavior have a strong correlation with the average actor rate and action time for getting up at home. In other words, it is confirmed that senior households have a higher percentage of free behavior when they are awake and have longer action times than households with minor children. On the other hand, senior households have lower power consumption per unit time than households with minor children, so households with elderly people are considered to be taking efficient free actions. Therefore, when considering measures to reduce power consumption in free behavior, it is considered appropriate to apply the approach of elderly households.

Cooking, washing, and cleaning are characterized by large power consumption and long hours of action, especially for households with housewives. Therefore, it can be confirmed that measures for cooking, cleaning and washing are particularly effective for households with housewives.
For single households, the overall action time is short, so efficient use of equipment as a whole is required. On the other hand, for senior households, the action time is generally long, so measures that can reduce the action time in the home as a whole are considered effective.

FIG. 23 is a diagram showing quantitative evaluation results by household composition on winter weekdays.
Comparing the winter (FIG. 23) and the summer (FIG. 22), it is confirmed that there is no significant difference in the tendency. However, since the power consumption per unit time is larger in the winter than in the summer, it is confirmed that priority should be given to measures in the winter to reduce power consumption throughout the year. .

FIG. 24 is a diagram showing the results of quantitative evaluation using the gas usage by household composition on winter weekdays as an index.
As for gas, the gas consumption per unit time in bathing is the largest, especially for senior households and single households. Therefore, it can be said that measures that can reduce the amount of hot water for bathing are effective.
For households with non-adult children, the amount of gas consumption per unit time in free behavior is large, so it can be said that measures that can make free behavior more efficient are effective except for bathing.
In households with housewives, gas consumption per unit time for cooking, cleaning, and washing is large. Therefore, measures that can improve the efficiency of cooking, cleaning, and washing are effective, except for bathing.
Moreover, the accuracy of analysis of the actual energy consumption can be increased by selecting living behavior depending on the energy equipment to be used.

<Fifth Embodiment>
(Visualization system for energy consumption at home)
FIG. 25 shows a block configuration diagram of a visualization system 70 of the actual state of energy consumption at home according to the fifth embodiment.
The visualization system 70 of the actual energy consumption in the home is a computer system that is installed in an office or business office of a housing contractor and is executed by a computer. And, when a housing contractor can build a new home or renovate a housing customer, the customer can review the housing energy system and consider introducing energy-saving equipment cost-effectively. It is used to display information that estimates energy consumption for each time.

As shown in the block configuration diagram of FIG. 25, the household energy consumption actualization visualization system 70 includes a household energy consumption actuality evaluation system 50, a second living behavior item energy consumption actualization visualization calculation unit 61, 2 and the energy consumption actual state visualization data storage means 62 for each living activity item.
Since the evaluation system 50 for the actual state of energy consumption at home has the same configuration as the system described in the fourth embodiment, description thereof is omitted.

(Second life behavior item energy consumption actualization visualization calculation part)
The energy consumption actual state visualization calculation unit 61 for each second living behavior item reads and estimates the energy consumption estimation P for each time per household from the hourly consumption energy calculation unit 55 of the energy consumption actual state evaluation system 50 in the home. Perform calculations to As an example of the calculated visualization, FIG. 26 shows a case where the estimated value P is displayed as a bar graph for each time.

Alternatively, the energy consumption actual state quantitative evaluation result storage unit 60 for each second living behavior item is read from the second living behavior item energy consumption actual state quantitative evaluation result, and the energy consumption for each living behavior item for which the quantitative evaluation result is set. Perform calculations to visualize the breakdown of quantities by energy consumption of energy equipment. As an example of the calculated visualization, FIG. 27 shows a case where the energy consumption and its breakdown are displayed for each living behavior in a bar graph.
The above-described visualization calculation is a process of processing / editing data and performing calculation for display.
The calculation result calculated by the energy consumption actual state visualization calculation unit 61 for each second living action item is stored in the energy consumption actual state visualization data storage means 62 for the second living action item.

<Sixth Embodiment>
(Home energy consumption behavior improvement proposal system)
FIG. 28 shows a block configuration diagram of an improvement proposal system 80 for energy consumption behavior at home according to the fifth embodiment.
The improvement proposal system 80 for energy consumption behavior in a home is a computer system that is installed in the office or business office of a housing contractor and is executed by a computer. And, when a housing contractor can build a new home or renovate a housing customer, the customer can review the housing energy system and consider introducing energy-saving equipment cost-effectively. It is used to display information that estimates energy consumption for each time.

As shown in the block diagram of FIG. 28, this home energy consumption behavior improvement proposal system 80 includes a home energy consumption actuality evaluation system 50, an energy consumption behavior improvement proposal calculation unit 81, and energy consumption behavior improvement proposal data. Storage means 82.
Since the evaluation system 50 for the actual state of energy consumption at home has the same configuration as the system described in the fourth embodiment, description thereof is omitted.

(Energy consumption behavior improvement proposal calculation unit)
The energy consumption behavior improvement suggestion calculation unit 81 reads the energy consumption actual state quantitative evaluation result storage unit 60 for each second living behavior item and reads the second energy consumption actual state quantitative evaluation result for each life behavior item, and the energy corresponding to the life stage Calculate the improvement proposal for consumption behavior. As an example of the calculation result, FIG. 29 shows an improvement proposal for energy consumption behavior.
The above-described improvement proposal calculation is a process of processing / editing data and performing an operation for displaying the improvement proposal contents.
The calculation result calculated by the energy consumption behavior improvement proposal calculation unit 81 is stored in the energy consumption behavior improvement proposal data storage means 82.

  In addition, this invention is not limited to the value of the energy consumption coefficient for every item of the living action set as main living action of one household shown in the above all embodiment, and the other constant C1, constant C2. Moreover, the energy handled by the home estimation system, domestic energy consumption management system, local energy management system, estimation method, energy consumption actuality evaluation system, energy consumption actuality visualization system, and energy consumption behavior improvement proposal system of the present invention is: Not limited to electricity, estimation system in the garden to estimate the energy consumption of gas or coal / oil, household energy consumption management system, regional energy management system, estimation method, energy consumption actuality evaluation system, visualization of energy consumption actuality It is also possible to configure an improvement proposal system for system and energy consumption behavior.

  Also, the household energy consumption estimation system 10, the household energy consumption management system 20, the local energy management system 30, the energy consumption actuality evaluation system 50, the energy consumption actuality visualization system 70, and the energy consumption behavior described above. At least one of the improvement proposal systems 80 may be mounted on an electronic device and used.

  Also, the household energy consumption estimation system 10, the household energy consumption management system 20, the local energy management system 30, the energy consumption actuality evaluation system 50, the energy consumption actuality visualization system 70, and the energy consumption behavior described above. The processing by at least one of the improvement proposal systems 80 may be provided in a server and executed by the server.

As described above, the present invention provides a home energy consumption estimation system, home energy consumption management system, regional energy management system, estimation method, energy consumption actuality evaluation system, energy consumption actuality visualization system, energy consumption behavior By performing calculation for estimating the actual energy consumption at each time using the improvement proposal system, the household energy consumption management system 20 on the demand side can perform peak cut / shift of household power consumption. In addition, the local energy management system 30 that performs power supply management on the power supply side calculates power demand forecasts for peak cuts and shifts and operation plans for distributed power sources and storage batteries to efficiently reduce power shortages. The power generation to supplement can be controlled.
Alternatively, it is possible to visualize and display the actual energy consumption, and it is possible to propose a further improvement plan for energy consumption behavior.

10 ... Estimating system for energy consumption at home 11 ... Life stage setting means 12 ... Temperature classification, day classification setting means 13 ... Average actor rate storage means 14 according to first living behavior 14 ... First life activity coefficient data storage means 15... Hourly power consumption calculation unit 16... Hourly power consumption estimated value storage means 17... Consumption management system 21 ... temperature data input means 22 ... power consumption demand response communication means 23 ... power consumption adjustment amount calculation means 24 ... power consumption adjustment means 25 ... controlled home appliance 30 ..Regional energy management system 31 ... Number of households per life stage 32. Mean temperature data input means 33 ... Total household power consumption estimation means 34 ... Bases other than homes Time-based power consumption estimation means 35 ... power supply and demand adjustment means 36 ... generator operation control means 37 ... power consumption demand response communication means 40 ... (including storage battery) generator 50 ... home Energy consumption actuality evaluation system 51 ... life stage setting means 52 ... temperature classification, day of the week classification setting means 53 ... first activist average actor rate storage means 54 ... second life Coefficient data storage means 55 for each action ... Energy consumption calculation section for each time 56 ... Energy consumption calculation section for each second life action item 57 ... Energy consumption storage means for each energy device 58 ... Second Use energy device storage means 59 for each living activity ... Energy consumption actual quantity quantitative evaluation calculation unit 60 for each second living action item ... Energy consumption actual condition for each second living action item Quantity evaluation result storage means 61 ... Energy consumption actual state visualization calculation unit 62 for each second living action item ... Energy consumption actual state visualization data storage means 70 for each second living action item ... Energy consumption actual condition at home Visualization system 80 ... home energy consumption behavior improvement proposal system 81 ... energy consumption behavior improvement proposal calculation unit 82 ... energy consumption behavior improvement proposal data storage means A1, A2, A3, A4, A5, A6, A7, C1, C2 ... Coefficient data by living activity B1, B2, B3, B4, B5, B6, B7 ... Average actor rate by living activity

Claims (20)

A system for estimating energy consumption at home,
As an item of living behavior in one household, multiple items of living behavior are set in advance,
Coefficients for living behavior that are stored by classifying and storing the energy consumption coefficient and other constants for each item of the set living behavior for each temperature classification classified as spring, summer, autumn, and winter and for each day of the week. Data storage means;
For each household life stage, classify by temperature class and weekday, and store the average actor rate by time for each set item of living behavior. Storage means;
From the value obtained by adding the other constants to the sum of the average actor rate for each time and the product of the energy consumption coefficient, an hourly power consumption calculation unit that calculates an estimate of energy consumption for each time of a household; ,
A system for estimating energy consumption at home, characterized by comprising:   The items of living behavior to be set are “sleep”, “meal”, “personal affairs”, “cooking / cleaning / laundry”, “watching TV”, and “behavior requiring internet operation”. The home energy consumption estimation system according to claim 1, wherein the system is “other behavior”. The estimation system of energy consumption in the home according to claim 1 or 2,
Temperature data input means for inputting temperature data;
Power consumption demand response communication means for performing demand response communication with the local energy management system;
In accordance with a demand signal from the regional energy management system, a power consumption adjustment amount calculating means for calculating a household power consumption plan amount using an estimation of energy consumption for each household time determined by the estimation system;
Transmitting means for transmitting the power consumption plan amount data of the household to the regional energy management system via the power consumption demand response communication means;
Power consumption adjusting means for controlling the power consumption of controlled household appliances in the home according to the household power consumption plan amount;
A domestic energy consumption management system comprising: The estimation system of energy consumption in the home according to claim 1 or 2,
Household number storage means per life stage, average temperature data input means, whole process power consumption estimation means, power consumption estimation means for each time other than household, power supply / demand adjustment means, power consumption demand response for demand response communication Comprising communication means and generator operation control means,
The power supply and demand adjustment means is
A calculating means for calculating a load pattern for each time of the total power consumption in the region by totaling an estimate of energy consumption for each time of the household determined by the estimation system;
A transmission means for transmitting a demand signal corresponding to the load pattern to a domestic energy consumption management system of a local household via the power consumption demand response communication means;
Receiving means for receiving household power consumption plan data from the household energy consumption management system of the local household;
A second calculation means for calculating a load pattern for each time of the total power consumption in the area again using the data on the planned power consumption of the household,
The local energy management system characterized in that the generator operation control means calculates an operation plan amount of a generator based on the load pattern calculated by the second calculation means and controls the operation of the generator. A method for estimating energy consumption at home,
The items of living behavior in one household are “sleep”, “meal”, “personal affairs”, “cooking / cleaning / washing”, “watching TV”, and “internet operation”. ‘Required Action’ and ‘Other Actions’,
The energy consumption coefficient and other constants for each item of the set living behavior are stored for each temperature classification classified as spring, summer, autumn, and winter and for each day of the week,
For each life stage of a household, classify for each class of temperature and for each day of the week, store the average actor rate per time for each item of the set living behavior,
The computer calculates an estimate of energy consumption for each time of a household from a value obtained by adding the other constants to the sum of the average actor rate for each time and the product of the energy consumption coefficient. How to estimate energy consumption at home. Demand response communication with the local energy management system, and estimation of energy consumption for each time of the household obtained by the estimation system according to claim 1 or 2 according to a demand signal from the local energy management system To calculate the household power consumption plan using
Sending the household power consumption plan data to the regional energy management system;
A domestic energy consumption management method, comprising: controlling power consumption of controlled household appliances in a home according to the household power consumption plan amount. Calculate the load pattern of the total power consumption in each region by summing up the estimation of energy consumption of each household obtained by the household energy consumption estimation system according to claim 1 or 2 And
A demand signal corresponding to the load pattern is transmitted to a domestic energy consumption management system of a household in the region, and further, data of a household power consumption plan amount is received from the household energy consumption management system, and the received household power Calculate the load pattern for each hour of the total power consumption of the region again using the planned consumption data, calculate the operation plan amount of the generator based on the recalculated load pattern, and control the operation of the generator A regional energy management method characterized by An evaluation system for the actual energy consumption at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The energy consumption coefficient for each item of the set second living behavior and other second constants are classified and stored for each temperature classification classified as spring, summer, autumn, and winter and for each day of the week. Coefficient data storage means according to daily activities;
For each household life stage, classify according to the temperature classification and weekday, and store the average rate of actors at each time for each item of the set first living behavior. Actor rate storage means,
From the value obtained by adding the other second constant to the sum of the average actor rate for each time and the product of the energy consumption coefficient, the energy consumption amount for each item of the set second living behavior of one household And an hourly power consumption calculation unit for calculating an action time,
For each item of the set second living behavior, set each energy device used in the living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption amount for each item of the set second living behavior of the household is set using the set action time of the second living behavior and the energy consumption amount of each set energy device as an index. An energy consumption actuality evaluation system in a home, comprising an energy consumption actuality quantitative evaluation calculation unit that quantitatively evaluates energy consumption for each item of life activity of 2. The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
The energy in the home according to claim 8, wherein in the analysis relating to gas, “TV (in home)” corresponds to “bathing”, and “hobby entertainment (net)” corresponds to “free action”. Evaluation system for actual consumption. It is a visualization system for the actual energy consumption at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The energy consumption coefficient for each item of the set second living behavior and other second constants are classified and stored for each temperature classification classified as spring, summer, autumn, and winter and for each day of the week. Coefficient data storage means according to daily activities;
For each household life stage, classify according to the temperature classification and weekday, and store the average rate of actors at each time for each item of the set first living behavior. Actor rate storage means,
From the value obtained by adding the other second constant to the sum of the average actor rate for each time and the product of the energy consumption coefficient, the energy consumption amount for each item of the set second living behavior of one household And an hourly power consumption calculation unit for calculating an action time,
Set each energy device used in the living behavior for each item of the set second living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption amount for each item of the set second living behavior of the household is set as the index of the set action time of the second living behavior and the energy consumption amount of each set energy device as an index. Quantitative evaluation of energy consumption for each item of daily living
An energy consumption actualization visualization unit that visualizes the breakdown of the energy consumption amount for each item of the set second life behavior using the energy consumption of the energy device and the action time as an index. Visualization system for actual consumption. The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
The energy in the home according to claim 10, characterized in that, in the gas analysis, “TV (in-home)” corresponds to “bathing” and “hobby entertainment (net)” corresponds to “free action”. Visualization system for actual consumption.   The said energy consumption actual condition visualization calculating part visualizes the breakdown of the energy consumption for every item of the set said living action according to the energy consumption of the said corresponding energy equipment, The Claim 10 or Claim 11 characterized by the above-mentioned. Visualization system for energy consumption in Japanese homes.   The energy consumption actual state visualization calculation unit calculates the breakdown of the energy consumption for each item of the set daily behavior as the sum of the average actor rate and the product of the energy consumption coefficient for each time. The visualization system for the actual state of energy consumption at home according to claim 12, wherein the visualization is based on a value obtained by adding a constant. A system for suggesting improvement of energy consumption behavior at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The energy consumption coefficient for each item of the set second living behavior and other second constants are stored for each temperature category classified as spring, summer, autumn, and winter and for each day of the week. Coefficient data storage means;
For each life stage of each household, the average actor rate by living behavior that stores the average actor rate at each time for each item of the set first living behavior for each temperature category and for every day of the week Storage means;
From the value obtained by adding the other second constant to the sum of the average actor rate for each time and the product of the energy consumption coefficient, the energy consumption amount for each item of the set second living behavior of one household And an hourly power consumption calculation unit for calculating the action time,
Set each energy device used in the living behavior for each item of the set second living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption for each item of the set second living behavior of the household is set as the index of the set action time of the second living behavior and the energy consumption of the set energy device as an index. It has an energy consumption behavior improvement suggestion calculation unit that quantitatively evaluates energy consumption for each item of living behavior,
An improvement suggestion system for energy consumption behavior at home, wherein an improvement proposal for energy consumption behavior corresponding to the life stage is posted based on the quantitative evaluation. The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
The energy consumption behavior according to claim 14, characterized in that, in the gas analysis, "TV (in-home)" corresponds to "bathing" and "Hobby entertainment (net)" corresponds to "Free behavior". Improvement proposal system. A method for evaluating the actual energy consumption at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
In the gas analysis, “TV (in-home)” corresponds to “bathing”, “hobby entertainment (net)” corresponds to “free action”
The energy consumption coefficient and the other second constant for each item of the second living behavior set above are classified and stored for each temperature category classified as spring, summer, autumn, and winter and for each day of the week. ,
For each life stage of a household, classify for each class of temperature and each day of the week, and store the average actor rate for each time for each item of the set first living behavior,
From the value obtained by adding the second constant to the sum of the average actor rate at each time and the product of the energy consumption coefficient, the computer calculates the energy for each item of the set second living behavior of one household. Calculate consumption and action time of each living behavior,
Set each energy device used in the living behavior for each item of the set second living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption for each item of the set second living behavior of the household is set using the set second life structure as an index and the action time of the set second living structure and each energy consumption of the set energy device as an index A method for evaluating the actual state of energy consumption in a home, characterized by quantitatively evaluating energy consumption for each item of living behavior. A method for visualizing the actual energy consumption at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
In the gas analysis, “TV (in-home)” corresponds to “bathing”, “hobby entertainment (net)” corresponds to “free action”
The energy consumption coefficient and the other second constant for each item of the second living behavior set above are classified and stored for each temperature category classified as spring, summer, autumn, and winter and for each day of the week. ,
For each life stage of a household, classify for each class of temperature and each day of the week, and store the average actor rate for each time for each item of the set first living behavior,
Energy consumption for each item of second living behavior set by one household from a value obtained by adding the other second constant to the sum of the average actor rate at each time and the product of the energy consumption coefficient Calculate, and act time,
Set each energy device used in the living behavior for each item of the set second living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
The energy consumption amount for each item of the set second living behavior of the household is used as an index of the action time of the set living behavior and the energy consumption amount of the set energy device as an index. Quantitative evaluation of energy consumption for each item,
Based on the quantitative evaluation, the breakdown of energy consumption for each item of the set second living behavior is visualized by using the energy consumption of the energy device and the action time as an index. Visualization method. A method for suggesting improvement of energy consumption behavior at home,
As items of living behavior in one household, a first plurality of items of living behavior and a second plurality of items of living behavior are preset,
The items of the first living behavior to be set are “TV (at home)”, “Hobby entertainment (net)”, “Sleep”, “Cooking / Cleaning / Laundry”, and “Personal activities” ”,“ Meal ”and“ other actions ”
The items of the second living behavior to be set are “at home behavior”, “free behavior”, “sleep”, “cooking / cleaning / laundry”, “personal affairs”, and “bathing”. And "meal" and "other actions"
In the power analysis, “TV (at home)” corresponds to “at home behavior”, “Hobby entertainment (net)” corresponds to “free behavior”
In the gas analysis, “TV (in-home)” corresponds to “bathing”, “hobby entertainment (net)” corresponds to “free action”
The energy consumption coefficient and the other second constant for each item of the second living behavior set above are classified and stored for each temperature category classified as spring, summer, autumn, and winter and for each day of the week. ,
For each life stage of a household, classify for each class of temperature and each day of the week, and store the average actor rate for each time for each item of the set first living behavior,
Energy consumption for each item of the set second living behavior of one household from a value obtained by adding the second constant to the sum of the average actor rate at each time and the product of the energy consumption coefficient Calculate quantity, and action time,
Set each energy device to be used in the living behavior for each item of the set living behavior,
Set energy consumption per unit in each energy device,
Set an action time for each second living action,
For each item of the set second living behavior, the energy consumption amount for each item of the set second living behavior of the household is used as an index for the action time of the living behavior and the energy consumption of the set energy device. Quantitative evaluation of energy consumption
An improvement proposal method for energy consumption behavior at home, wherein a proposal for improvement of energy consumption behavior corresponding to the life stage is posted based on the quantitative evaluation.   The estimation system according to claim 1, the domestic energy consumption management system according to claim 3, the regional energy management system according to claim 4, the energy consumption actuality evaluation system according to claim 8, and the claim 10 according to claim 10, An electronic apparatus equipped with at least one of the energy consumption actuality visualization system according to claim 14 and the energy consumption behavior improvement proposal system according to claim 14. The estimation system according to claim 1, the domestic energy consumption management system according to claim 3, the regional energy management system according to claim 4, the energy consumption actuality evaluation system according to claim 8, and the claim 10 according to claim 10, A server comprising at least one of the energy consumption actuality visualization system according to claim 14 and the energy consumption behavior improvement proposal system according to claim 14.

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