JP2001317792A - Overtime air conditioning operating system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an air conditioning operating system which can reduce the burden of energy on tenants and make efficient total energy consumption of a building. SOLUTION: The overtime air conditioning operating system operating the air conditioning in the overtime band of a tenant building for each tenant comprises means for operating total energy consumption in the overtime band of the tenant building based on input data concerning to overtime application from tenants and prestored outdoor air temperature prediction data, and means for dividing total energy consumption in the overtime band of the tenant building thus operated proportionally by the load of each tenant and displaying the results for each tenant.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a building management system, and more particularly to a system for efficiently operating an air conditioner during overtime hours.

[0002]

2. Description of the Related Art Generally, air conditioners in tenant buildings are
In normal working hours, the system is operated according to a predetermined schedule (schedule operation), and in overtime hours, the system is operated according to a method of extending the schedule time by application from individual tenants (overtime operation). In addition, the energy burden associated with this overtime operation is often simply calculated from the operation time, etc., including the schedule operation at the end of the month.

[0003]

However, in the whole building, since the operation efficiency on the heat source side varies depending on the load,
The heat source operation cost in overtime operation is higher in the overtime operation zone than in the daytime when the load is heavy.

[0004] When applying for overtime, the tenant manager does not know the actual situation related to the cost mentioned above, and the overtime application itself is applied only for the work of the tenant, and in some cases, inefficient and expensive operation is required. In many cases. For this reason, waste of thermal energy increases, and the thermal energy burden on the tenant also increases.

[0005] It is an object of the present invention to provide an air-conditioning operation system capable of reducing the energy burden on tenants and improving the energy consumption of the entire building.

Another object of the present invention is to provide an air-conditioning operation system capable of presenting information to a tenant at the time of application for overtime work so that the user can grasp today's overtime energy efficiency and cost.

[0007]

In order to achieve the above object, the present invention relates to an overtime air conditioning operation system for operating air conditioning in a tenant building during overtime hours for each tenant, the invention relates to an overtime application from the tenant. Calculating means for calculating the energy consumption of the entire tenant building during overtime hours based on the input data and the external temperature prediction data held in advance; and calculating the energy consumption of the entire tenant building during overtime hours obtained by the calculating means. A display means for apportioning the load for each overtime target tenant and displaying the load for each tenant.

According to the present invention, when a tenant applies for overtime work, information is provided for each tenant so that he can grasp today's overtime energy efficiency and cost, so that the tenant can consciously suppress energy consumption. As a result, the energy burden on the tenants can be reduced and the energy consumption of the entire building can be made more efficient.

[0009] To achieve the above object, the present invention provides:
In an overtime air conditioning operation system for operating air conditioning in a tenant building during overtime hours for each tenant, the air conditioning load for each tenant in the overtime hours is determined by inputting data relating to an overtime application from the tenant and the outside air temperature held in advance. Overtime load calculation means for calculating based on the forecast data, actual load calculation means for calculating the air-conditioning load for each tenant in the overtime hours by actual measurement, and a relationship between the actually measured value, the input data and the outside air temperature prediction data Means for storing the overtime load calculation, the actually measured load calculation, and the table storage are repeated, and the relationship between the outside air temperature predicted value and the outside air load actual value and / or the number of overtime workers and the indoor load are stored. Means for calculating a coefficient while improving the accuracy of the relationship with the actual value by learning.

As described above, according to the present invention, the coefficient indicating the relationship between the predicted outside air temperature value and the actual outdoor load value and the coefficient indicating the relationship between the number of overtime employees and the actual indoor load value are obtained by learning and the coefficient is calculated. Since the accuracy of the conversion is increased, it is possible to accurately calculate the energy according to the contents of the tenant's overtime application input, and to present the calculated value to the tenant or the administrator related to the air conditioning area at the time of overtime application, for example. By
Tenants themselves can make overtime plans with energy in mind, resulting in increased energy efficiency,
This will contribute to reducing the energy consumption of the entire building.

[0011]

(First Embodiment) FIG. 1 shows the overall configuration of an overtime air-conditioning operation system according to a first embodiment of the present invention.
Shown in As shown in FIG. 1, in the tenant building,
The tenant terminal 20 and the overtime energy conversion device 30 are connected via the network 10. The overtime energy conversion device 30 includes a control device 40 such as a BA system.
Is connected.

Here, the tenant terminal 20 is installed in each tenant or air-conditioning area in the building, and an administrator of the tenant or the air-conditioning area can input data for applying for overtime air conditioning and display a predicted value of energy consumption. Done. The overtime energy conversion device 30 receives the overtime application content input from the tenant terminal 20 and performs energy conversion based on the overtime application content and various data. The control device 40 such as a BA system executes schedule control of the air conditioner and the like.

Next, details of the tenant terminal 20 and the overtime energy conversion device 30 will be described with reference to FIG. First, the tenant terminal 20 can exchange data with the network 10 and has a computer function.
Overtime application input unit 20A and display unit 20 unique to this embodiment
B.

The overtime application input unit 20A is used by a tenant or an administrator of the air conditioning area to input the date, time, set temperature, and number of overtime workers of the overtime application. Is transmitted to the device 30 and becomes data required for calculation of energy conversion.

The display unit 20B receives, via the network 10, data on the overtime energy prediction, the fee prediction, the application status of other tenants or air conditioning areas, etc., calculated by the overtime energy conversion device 30, and displays them. Things.

The overtime energy conversion device 30 includes an air conditioning load calculation unit 31, an outside temperature prediction data storage unit 32, an air conditioner data storage unit 33, a heat source energy conversion unit 34, a heat source equipment data storage unit 35, a charge calculation unit 36, a charge Data storage unit 3
And an apportioning calculator 38.

The overtime energy conversion device 30 will be described in detail. First, the air-conditioning load calculation unit 31 calculates data (date, time, set temperature, number of overtime workers) related to overtime application from the overtime application input unit 20A of the tenant terminal 20. ), The outside air temperature prediction data from the outside temperature prediction data storage unit 32, and the air conditioner data from the air conditioner data storage unit 33 to calculate the air conditioning load.

The heat source energy conversion section 34 includes data relating to the air conditioning load during the overtime hours calculated by the air conditioning load calculation section 31, the outside air temperature prediction data from the outside air temperature prediction data storage section 32, and the heat source equipment data storage section. Based on the heat source facility data from 35, the heat source energy for the overtime hours related to the application is converted.

The charge calculation unit 36 calculates the charge of the heat source energy for the overtime work pertaining to the application converted by the heat source energy conversion unit 34 based on the charge data from the charge data storage unit 37.

The apportioning calculator 38 apportions the energy charge calculated by the charge calculator 36 in accordance with the load for each tenant or air-conditioning area which has already been calculated by the air-conditioning load calculator 31.

The overtime energy charges and the like for each tenant or air-conditioning area, which are apportioned by the apportionment calculation section 38, are sent to the tenant terminal 20 as charge forecasts, and data on overtime energy forecasts, application status of other tenants, and the like are also provided. The charge prediction and the data are sent to the terminal 20 and displayed on the display unit 20B.

Next, the operation of the system according to the present embodiment will be described with reference to FIG. 3 over time.
Then, the administrator of each tenant or air conditioning area operates the overtime application input unit 20A of the tenant terminal 20, and inputs the date, time, set temperature, the number of overtime workers, etc., which are data relating to the overtime application. These data are sent to the air conditioning load calculator 31 of the overtime energy conversion device 30.

In step S2, the air-conditioning load calculator 31
Is based on data relating to overtime application from the overtime application input unit 20A of the tenant terminal 20, outside temperature prediction data from the outside temperature prediction data storage unit 32, and air conditioner data from the air conditioner data storage unit 33. Calculate the load.

In step S 3, the heat source energy conversion unit 34 calculates the data on the air conditioning load during the overtime hours calculated by the air conditioning load calculation unit 31, the outside air temperature prediction data from the outside air temperature prediction data storage unit 32, Based on the heat source equipment data from the heat source equipment data storage unit 35, the heat source energy for the overtime hours related to the application is converted.

In step S 4, the charge calculation unit 36 calculates the heat source energy charge for the overtime hours related to the application converted by the heat source energy conversion unit 34 based on the charge data from the charge data storage unit 37.

In step S5, the apportioning calculator 38 calculates the energy rate of the heat source calculated by the rate calculator 36 in accordance with the load for each tenant or air conditioning area which has already been calculated in the air conditioner load calculator 31. Perform apportionment.

In step S6, the rate of overtime energy and the like for each tenant apportioned by the apportionment calculation section 38 is used as a rate forecast together with data on overtime energy forecasting, the application status of other tenants, and the like.
And display on the display unit 20B.

As described above, the prediction of the outside air temperature during the overtime hours, the overtime hours, the number of overtime employees, the set room temperature, and the air-conditioner air volume data,
The air conditioning load during overtime hours is predicted and calculated for each tenant, and the energy consumption on the heat source side is calculated for each hour from the total value of the entire building. The result is converted into a fee, and a value proportionally divided by the load for each tenant or air conditioning area is displayed on each tenant or area side terminal. In the display, it is performed that the rate is cheaper in the time zone and the day of the week when there are many overtime tenants.

As described above, according to the present embodiment, the tenant side can view expensive energy consumption prediction and fee prediction as a guide when applying for overtime, so that the tenant can make an overtime plan conscious of energy. As a result, energy efficiency will increase and energy consumption of the whole building will be reduced.

(Second Embodiment) Next, a second embodiment of the overtime air conditioning operation system according to the present invention will be described with reference to FIGS. The overtime air conditioning operation system according to the present embodiment includes an overtime air conditioning load calculation processing unit 50 shown in FIG.

The overtime air-conditioning load calculation processing section 50 of the present embodiment.
Includes an overtime air conditioning load calculation unit 51, a tenant input data storage unit 52, an outside air temperature prediction data storage unit 53, and an actual measurement load calculation unit 5 that calculates an actual air conditioning load value during actual air conditioning operation.
4 and a file unit 55 for storing relational data between the air-conditioning load actual value calculation unit 54 and a learning unit 56 for calculating a coefficient that minimizes an error of the storage file unit 55 by learning.
It is composed of

Here, the operation of the overtime air conditioning load calculation processing unit 50 will be described with reference to FIG. In FIG. 5, as a step T1, the tenant manager inputs overtime application data such as the number of overtime workers to the overtime air conditioning load calculation unit 51 via the tenant terminal 10 in FIG. Also,
As step T2, the outside air temperature prediction data from the outside air temperature prediction data storage unit 53 is also input to the overtime air conditioning load calculation unit 51.

Next, as steps T3 and T4, the measured load calculating unit 54 calculates the air conditioning load during the overtime hours from the measured data according to the following equation. This calculated value is given to, for example, the heat source energy conversion unit 34 and the like.

Air-conditioning load = indoor load + outdoor air load Indoor load = return air flow x (indoor temperature-supply air temperature) x multiplication constant (for example, 0.29) Outdoor air load = outdoor air flow x (external air temperature-supply air temperature) x multiplication constant The air conditioning load in the overtime hours calculated by the measured load calculation unit 54 is, for example, the heat source energy conversion unit 3 in FIG.
4 given.

Next, as step T5, the relationship between the calculated energy value obtained by the actual measurement and the number of overtime employees and the outside air temperature prediction data input in advance on that day is stored in the file unit 55 as a table. In this case, the administrator relating to each tenant or the air conditioning area inputs overtime application data such as the number of overtime workers using the tenant terminal 10 in FIG. 1, for example.

Next, as steps T6 and T7, the overtime air-conditioning load calculator 51 and the actually measured load calculator 54
The actual measurement, calculation, and table storage processing by the file unit 55 and the learning unit 56 are repeated, and the learning unit 56 obtains the following relationships (a) and (b) by learning and converts them into coefficients.

(A) Coefficient conversion between predicted outside air temperature and actual outside air load value (b) Coefficient conversion between number of overtime employees and actual indoor load value The overtime air conditioning load calculation 51 uses the above (a) and (b). Then, the air conditioning load is obtained from the overtime application input value by the following formula. In this case, the accuracy is improved by learning by the learning unit 56.

Indoor load = number of people × coefficient Outside air load = outside air temperature prediction × coefficient Here, the coefficient is a value corresponding to the indoor temperature set value input by the tenant or the manager of the air conditioning area through the tenant terminal 10 in FIG. To be changed.

As described above, according to this embodiment, the actual measurement, calculation, and table storage processing are repeated by the overtime air conditioning load calculation unit 51, the measured load calculation unit 54, the file unit 55, and the learning unit 56, and A coefficient indicating the relationship between the predicted temperature value and the actual outdoor load value and a coefficient indicating the relationship between the number of overtime employees and the actual indoor load value are obtained by learning in the learning unit 56, and the accuracy of the coefficient conversion is increased. Therefore, it is possible to accurately calculate the energy according to the content of the tenant's overtime application input, and present the calculated value to the tenant or the administrator related to the air conditioning area at the time of overtime application, for example, as in the first embodiment. By doing so, tenants themselves can make overtime plans with an awareness of energy, and as a result, contribute to improving energy efficiency and reducing energy consumption in the entire building It made.

[0040]

As described above, according to the present invention, the tenant can make an overtime plan with the energy in mind, and as a result, the energy efficiency can be increased and the energy consumption of the entire building can be reduced. Can be.

Further, according to the present invention, the tenant can make an overtime plan conscious of energy, and as a result, it is possible to contribute to improvement of energy efficiency and reduction of energy consumption of the whole building.

[Brief description of the drawings]

FIG. 1 is a configuration diagram showing an embodiment of an air conditioning operation system according to the present invention.

FIG. 2 is a detailed block diagram of the embodiment.

FIG. 3 is a flowchart showing the operation of the embodiment.

FIG. 4 is a configuration diagram showing another embodiment of the air conditioning operation system according to the present invention.

FIG. 5 is a flowchart showing the operation of the embodiment.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 10 ... Network, 20 ... Tenant terminal, 20A ... Overtime application input part, 20B ... Display part, 30 ... Overtime energy conversion device, 31 ... Air-conditioning load calculation part, 32 ... Outdoor temperature prediction data storage part, 33 ... Air conditioner data storage Unit, 34: heat source energy conversion unit, 35: heat source equipment data storage unit, 36 ...
Charge calculation unit, 37: charge data storage unit, 38: apportionment calculation unit, 40: control device, 50: learning calculation unit, 51: overtime air conditioning load calculation unit, 52: tenant input data storage unit, 53
... Ambient air temperature prediction data storage unit, 54 ... Load calculation unit by actual measurement, 55 ... Table storage unit, 56 ... Learning unit.

Claims (3)

[Claims] 1. An overtime air-conditioning operation system for operating air conditioning in a tenant building during overtime hours for each tenant, wherein the tenant building is based on input data relating to an overtime application from the tenant and external temperature prediction data held in advance. Calculating means for calculating the energy consumption during the entire overtime hours; and the energy consumption during the overtime hours of the entire tenant building obtained by the calculating means is apportioned by load for each overtime target tenant and displayed for each tenant Overtime air-conditioning operation system comprising: 2. The overtime air-conditioning operation system according to claim 1, wherein said arithmetic means and said display means are responsive to data transfer from a tenant terminal provided for each tenant. 3. An overtime air-conditioning operation system for operating air conditioning in a tenant building during overtime hours for each tenant, wherein the air conditioning load for each tenant during overtime hours is determined by input data relating to an overtime application from the tenant. Overtime load calculation means for calculating based on the external temperature prediction data held in advance, actual load calculation means for calculating the air conditioning load for each tenant during the overtime hours by actual measurement, the actual value, the input data and the external temperature A table storage unit for storing the relationship with the prediction data as a table; and repeating the overtime load calculation, the actually measured load calculation, and the table storage, and the relationship between the outside air temperature prediction value and the outside air load actual value and / or Means for calculating a coefficient while increasing the accuracy by learning the relationship between the number of overtime employees and the actual indoor load value. Business air conditioning operating system.