JP2013101057A - Electric energy management method, electric energy management device, and electric energy management program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To calculate electric energy for every power consumption factor and for every organization unit from the existing electric energy measurement value to analyze an effect of an electric energy reduction measure without newly installing a power meter.SOLUTION: In an electric energy management device having a storage area which stores use information on electric energy and information regarding thermal load factors for every organization which manages the electric energy, variables (x) are calculated for every thermal load factor from the information stored in the storage area, the electric energy for every consumption factor associated with the thermal load factors is estimated from the use information on the electric energy and the variables, the electric energy for every organization and for every consumption factor is calculated by proportionally dividing the electric energy for every consumption factor on the basis of data on the organization which manages the electric energy, and the estimated electric energy for every organization and for every consumption factor is output.

Description

  The present invention relates to an electric energy management method, an electric energy management device, and an electric energy management program.

  For the purpose of preventing global warming, the Law Concerning Promotion of Global Warming Countermeasures and the Tokyo Metropolitan Government's Global Warming Countermeasure Plan System are being implemented. While both require businesses and establishments to report CO2 emissions, the Tokyo Metropolitan Ordinance further mandates a five-year average reduction rate.

  For this reason, if only CO2 emissions are reported, for example, it is possible to grasp the amount of power that is the cause of CO2 emissions even with a single wattmeter for the entire office, but in order to satisfy the reduction rate obligations. It is necessary to grasp the situation and the possibility of reduction individually for power consumption factors such as air conditioning and lighting.

  However, installation of a wattmeter often involves not only equipment costs but also costs such as construction work, so it has not been installed and measured in detail. In addition, in order to consider reducing each power consumption factor, it is also necessary to grasp the correlation with factors that affect each power consumption factor, such as the number of people / equipment, floor area, and outside temperature.

  As a background art in this technical field, there is JP-A-2001-349909 (Patent Document 1). This publication describes that “the amount of electric power used can be obtained for each home appliance reliably and inexpensively with simple means”. Japanese Patent Laid-Open No. 2011-89677 (Patent Document 2) is available. This publication describes that “any place in a large space is efficiently controlled to a desired air-conditioning environment”.

JP 2001-349909 JP 2011-89677

  Patent Document 1 describes a method of calculating the amount of electric power used by each home appliance without installing a wattmeter for each home appliance in the home. However, it is necessary to define the power consumption per unit time in a certain usage state for each home appliance, and it can be defined when the number of devices is limited as in the home, but in the case of an office building, etc. It will be difficult.

  Patent Document 2 describes a method of controlling air conditioning by defining a human body as a heating element in addition to lighting and OA equipment and controlling the amount of generated heat in a database in order to control the air conditioning environment. However, although it is a control method based on factors that affect the amount of power for air conditioning, it does not calculate the amount of power for each power consumption factor such as other lighting or equipment.

  Therefore, in the present invention, a power amount management device that calculates the power amount for each power consumption factor and each organizational unit from the existing power amount measurement value and analyzes the effect of the power amount reduction measure without newly installing a power meter. I will provide a.

The present application includes a plurality of means for solving the above-mentioned problems. To give an example, the amount of electric power having a storage area for storing information on the amount of use of electric energy and information on the thermal load factor for each organization that manages the amount of electric power. In the management device, a power amount management method for estimating a power amount for each power consumption factor for each organization that manages the power amount from usage information of the power amount, wherein each heat is calculated from the information stored in the storage area. A pre-processing step for calculating a variable (x _i ) for each load factor, a factor-specific estimation step for estimating a power amount for each consumption factor associated with the thermal load factor from the power usage information and the variable, By allocating the power amount for each consumption factor based on the data of the organization that manages the power amount, the organization-specific estimation step for calculating the power amount for each organization and the consumption factor; And a result output step of outputting a power amount for each consumption factor.

  Further, the preprocessing step includes a power amount estimation formula.

X _i in (y _n : electric energy, i: thermal load factor, j: organization managing electric energy) is calculated for each thermal load factor from the data stored in the storage area, and the factor-specific estimation step Estimates α _i and β in the power estimation equation by regression analysis to estimate the amount of power for each consumption factor associated with the thermal load factor.

According to the present invention, since no new power meter is installed, it is possible to grasp the amount of power for each power consumption factor and analyze the power reduction and its effect at low cost.
Problems, configurations, and effects other than those described above will be clarified by the following description of embodiments.

An example of the energy management device configuration is shown. Schematic diagram of computer Flow chart showing overall processing of power amount management apparatus Control screen of energy management device An example of the concept of energy management Examples of heat load factors Flow chart showing power amount estimation processing Schematic diagram of power management unit table Schematic diagram of electric energy table Schematic diagram of organization information table Schematic diagram of the floor information table Schematic diagram of the attendance information table Schematic diagram of temperature information table Schematic diagram of heating element information table Schematic diagram of estimation formula table Schematic diagram of temporary information table Schematic diagram of the energy table by factor Schematic diagram of evaluation result table Electricity prediction screen Improvement effect analysis screen Schematic diagram of lighting information table Lighting condition screen Schematic diagram of device configuration table Schematic diagram of device information table Equipment condition screen Air conditioning: Floor condition screen Schematic diagram of shading condition table Shading table Air conditioning: Shading condition screen Schematic diagram of improvement condition table Schematic diagram of improvement result table Improvement effect screen Schematic diagram of cost information table Schematic diagram of the target reduction rate table

  Hereinafter, examples will be described with reference to the drawings.

  In this embodiment, an example of an apparatus 100 that performs power amount management will be described. FIG. 1 is an example of a configuration diagram of a power amount management apparatus 100 of the present embodiment. The power amount management apparatus 100 includes a storage unit 110, a control unit 130, an input unit 140, and an output unit 150.

  The storage unit 110 includes a power management unit storage area 111, an electric energy storage area 112, an organization information storage area 113, a floor information storage area 114, an attendance information storage area 115, an air temperature information storage area 116, and a heating element. Information storage area 117, estimation formula storage area 118, improvement condition storage area 119, equipment configuration information storage area 120, equipment information storage area 121, illumination information storage area 122, shading condition storage area 123, and cost An information storage area 124, an organization-specific result storage area 125, a temporary information storage area 126, and an evaluation result storage area 127 are provided.

  The power management unit storage area 111 stores information for specifying a measurement unit for each power consumption factor by an existing power management facility. The power amount storage area 112 stores information for specifying the power amount for each measurement unit. In the organization information storage area 113, information for identifying the organization such as the number of personnel is stored together with an index for identifying the organization. The floor information storage area 114 stores information for specifying a floor to which the organization belongs in a building. In the attendance information storage area 115, information for specifying attendance hours of personnel belonging to the organization is stored. In the temperature information storage area 116, information specifying the outside temperature and the room temperature is stored. In the heating element information storage area 117, information defining the heating element type is stored. The estimation formula storage area 118 stores information for specifying an estimation formula for the electric energy.

  In the improvement condition storage area 119, information specifying the content input as the improvement condition is stored. In the device configuration information storage area 120, information for specifying a power usage device owned by the organization is stored. In the device information storage area 121, information for specifying the power using device is stored. In the illumination information storage area 122, information for specifying illumination is stored. The light shielding condition storage area 123 stores information for specifying the light shielding conditions depending on the type of window. In the cost information storage area 124, information for specifying a cost such as a power charge is stored. The organization-specific result storage area 125 stores information for calculating the amount of power for each power consumption factor for each organization. The temporary information storage area 126 stores information received by the control unit 130, which will be described later, and information calculated by the control unit 130. The evaluation result storage area 127 stores information related to the evaluation result calculated by the control unit 130 described later.

  The control unit 130 includes an evaluation mode selection unit 131, an electric energy estimation unit 132, an improvement condition input unit 133, an improvement effect calculation unit 134, and an evaluation result output unit 135. The evaluation mode selection unit 131 receives input from the user via the input unit 140 and performs processing of the power amount estimation unit 132, the improvement effect calculation unit 134, or termination processing of the power amount management apparatus 100.

  The power amount estimation unit 132 includes a power management unit storage area 111, a power amount storage area 112, an organization information storage area 113, a floor information storage area 114, an attendance information storage area 115, and an air temperature information storage area 116. Based on the information in the heating element information storage area 117, the power amount of each power consumption factor for each organization is calculated. In addition, a process for storing the coefficient of the estimation formula for the electric energy obtained in the calculation process in the estimation formula storage area 118 is performed. Furthermore, the calculation process of the annual electric energy prediction value is performed using the estimation formula.

  The improvement condition input unit 133 performs display processing of settable improvement conditions based on information in the device information storage area 121, the illumination information storage area 122, and the light shielding condition storage area 123 via the output unit 150. Furthermore, a process of receiving an input from the user via the input unit 130 and storing it in the improvement condition storage area 119 is performed. And the process of the improvement effect calculating part 134 is performed.

  The improvement effect calculation unit 134 updates the estimation formula based on the information in the estimation formula storage area 118 and the improvement condition storage area 119, and performs the calculation process of the annual electric energy prediction value. Furthermore, the calculation processing of the expense which arises with improvement is performed by the information of the apparatus information storage area 121, the illumination information storage area 122, the light-shielding condition storage area 123, and the cost information storage area 124.

  The evaluation result output unit 135 displays the result of the power amount estimation unit 132 via the output unit 150. Further, it receives an input from the user via the input unit 140 and executes the process of the improvement condition input unit 133. Then, the processing result of the improvement effect calculation unit 134 is displayed via the output unit 150. The input unit 140 receives input of information. The output unit 150 outputs information.

  The power amount management apparatus 100 described above includes an external storage such as a CPU (Central Processing Unit) 201, a memory 202, and an HDD (Hard Disk Drive) as shown in FIG. 2 (schematic diagram of the computer 200). A device 203, a reading device 205 for reading / writing information from / to a portable storage medium 204 such as a CD (Compact Disk) or a DVD (Digital Versatile Disk), an input device 206 such as a keyboard or a mouse, a display, etc. This can be realized by a general computer 200 including an output device 207 and a communication device 208 such as a NIC (Network Interface Card) for connecting to a communication network.

  For example, the storage unit 110 can be realized by the CPU 201 using the memory 202 or the external storage device 203, and the control unit 130 loads a predetermined program stored in the external storage device 203 into the memory 202. The input unit 140 can be realized by the CPU 201 using the input device 206, and the output unit 150 can be realized by the CPU 201 using the output device 207. .

  This predetermined program is downloaded from the storage medium 204 via the reading device 205 or from the network via the communication device 208 to the external storage device 203, and then loaded onto the memory 202 and executed by the CPU 201. You may do it. Alternatively, the program may be directly loaded on the memory 202 from the storage medium 204 via the reading device 205 or from the network via the communication device 208 and executed by the CPU 201.

  Next, FIG. 3 shows the entire processing flow of the electric energy management apparatus 100 in one embodiment of the present invention. As shown in FIG. 3, the process includes four steps of processing determination S <b> 301, power amount estimation S <b> 302, effect analysis S <b> 303, and result output S <b> 304. FIG. 4 is a control screen of the power amount management apparatus 100. It consists of a power estimation button 400, an improvement effect analysis 401, and an end button 402.

  Hereinafter, the operation of the power amount management apparatus 100 according to the embodiment of the present invention will be described according to the steps in FIG. 3 and the control screen in FIG. 4.

  First, the process of step S301 will be described. Here, it corresponds to the processing operation of the evaluation mode selection unit 131 in FIG. After the power amount management apparatus 100 is activated, the control screen of the power amount management apparatus 100 shown in FIG. 4 is displayed via the output unit 150. An input from the user is accepted via the input unit 140. In the case of the power estimation button 400, the processing of the power amount estimation S302 step is executed, and in the case of the improvement effect analysis 401, the processing of the effect analysis S305 step is executed. In the case of the end button 402, the process of the power amount management apparatus 100 is ended, and the process of turning off the power is performed.

  Next, the process of step S302 for estimating the electric energy will be described. Here, it corresponds to the processing operation of the electric energy estimation unit 132 of FIG. First, FIG. 5 is a conceptual diagram of power amount management. As a simple example, in existing power management, the organizational units are A and B, the power consumption factors are air conditioning, lighting and equipment, and the power meter 500 uses the power meter 500 to determine the total value of air conditioning, lighting and equipment. Assume that measurements are taken at two locations. On the other hand, in the electric energy management apparatus 100 of the present invention, the electric energy is calculated from the measured value of the electric power meter 500 by the organization and the power consumption factor as in the case where the virtual electric power meter 501 is installed and measured. To do.

  FIG. 6 shows an example of thermal load factors that affect the air conditioning capability and the magnitude of the influence. Although it is affected by the power consumption and temperature of the equipment, it also includes the effects of lighting and equipment that are power consumption factors. Therefore, the total power consumption of the building correlates with these heat load factors.

  Therefore, in the power amount estimation step S302, processing is performed based on the power amount estimation processing flow of FIG. 7, and regression analysis is performed on (Equation 1) shown below to obtain the power amount estimation equation of (Equation 1). Are calculated, and the amount of power is calculated for each organization and power consumption factor.

However, i: Thermal load factor, j: Organization included in the same power management unit, n: Power management unit.

  As shown in FIG. 7, the power amount estimation processing flow includes four steps of pre-processing S <b> 701, factor-specific estimation S <b> 702, organization-specific estimation S <b> 703, and result output S <b> 704. First, the process of the pre-processing S701 step will be described. In the preprocessing step, the following Xi is calculated for each thermal load factor from the following various types of information stored in the storage area. Here, the following five are defined as Xi (explanatory variable) of (Formula 1).

Lighting: X1 = Floor area / Total number of equipment Equipment: X2 = Total number of persons Human body: X3 = Total number of persons / Floor area Solar heat: X4 = Window area Heat transfer: X5 = Internal / external temperature difference / Window area It is also possible to define Xi representing the characteristics of

  Next, a power management unit storage area 111, an electric energy storage area 112, an organization information storage area 113, a floor information storage area 114, and an attendance information storage area 115 provided in the storage unit 110 for calculating the above Xi. The table configurations of the temperature information storage area 116, the heating element information storage area 117, the estimation formula storage area 118, and the temporary information storage area 126 will be described below.

  First, the power management unit table shown in FIG. 8 is stored in the power management unit storage area 111. The power management unit table is composed of records including a management ID 8a, a consumption factor management unit 8b, and an organization ID 8c. FIG. 8 shows two patterns as an example. The first is a record with a management ID 8a = 1, which is a case where one wattmeter 500 shown in FIG. 5 is managed and all of lighting, equipment and air conditioning are managed. The management ID 8a and the consumption factor management unit 8b are the same. In the example of FIG. 5, since two departments are included, a value representing two departments is set in the organization ID 8c. The second is a record of management IDs 8a = 10 and 100, in which lighting and equipment are combined by the wattmeter 500 shown in FIG. 5, and air conditioning is managed independently.

  In this way, for each existing power meter, the management ID 8a and the consumption factor managed by the power meter are set in the consumption factor management unit 8b, and the organization ID 8c distinguishes the organizations included in the range managed by the power meter, Create a record. However, in the example of FIG. 8, two patterns are illustrated, but only one is defined because one building is managed.

  The power amount table shown in FIG. 9 is stored in the power amount storage area 112. The power amount table is composed of records including a year 9a, a month 9b, a management ID 9c, and a power amount 9c. Data for each management ID 9c corresponding to the management ID 8a is stored on a monthly basis. However, in this embodiment, for the sake of simplicity, the unit is a year, but the unit may be managed on a daily basis.

  The organization information table shown in FIG. 10 is stored in the organization information storage area 113. The organization information table is composed of records composed of year 10a, organization ID 10b, name 10c, personnel 10d, floor ID 10e, and device configuration ID 10f.

  The floor information table shown in FIG. 11 is stored in the floor information storage area 114. The floor information table is composed of records including a floor ID 11a, a floor area 11b, and a window area 11c. Data is managed by the floor ID 11a corresponding to the floor ID 10e of the organization information table.

  The attendance information table shown in FIG. 12 is stored in the attendance information storage area 115. The attendance information table is composed of records consisting of year 12a, month 12b, organization ID 12c, total number of people 12d, and room temperature 12e. The total number of persons 12d sets the monthly total of the number of attendees per day. For the room temperature 12e, a monthly average value or a set value of daily measurement results obtained by a separate measuring means is input.

  The temperature information table shown in FIG. 13 is stored in the temperature information storage area 116. The temperature information table is composed of records including a year 13a, a month 13b, and an outside temperature 13c. The outside air temperature 13c uses, for example, weather statistical information issued by the Japan Meteorological Agency. By selecting the location and year, monthly data for the target year can be obtained, so the daily average temperature for each month is set. The record for the year 13a = 0 has an average value for each year and month in the same weather statistical information, so that value is set.

  The heating element information table shown in FIG. 14 is stored in the heating element information storage area 117. The heating element information table is configured by a record including an ID 14a and a heating element 14b.

  The estimation formula table shown in FIG. 15 is stored in the estimation formula storage area 118. The estimation formula table is composed of records including a year 15a, a management ID 15b, a heat generation factor 15c, a calculated value 15d, and a type 15e.

  The temporary information table shown in FIG. 16 is stored in the temporary information storage area 126. The temporary information table is composed of records including the moon 16a, the lighting 16b, the device 16c, the human body 16d, the solar heat 16e, the heat transfer 16f, and the type 16g.

  Next, Xi calculation processing will be described. Since the previous year's data is used in the estimation, the explanation for the year of each table is based on the assumption that the data for the -1 year of the year obtained from the system when the energy management device 100 is started will be used unless otherwise noted. To do. Further, the following Xi calculation is performed with the number of organization IDs 10b in the organization information table as j.

  Illumination: X1 is expressed by floor area / total number of people, so the floor ID 10e of the record in which the organization ID 10b and j in the organization information table match is extracted. The floor area 11b of the record in which the extracted floor ID 10e matches the floor ID 11a of the floor information table is extracted. Further, the total number 12d of records having the same organization ID 12c and j in the attendance information table is extracted, and the floor area 11b / total number 12d is calculated for each month 12b = 1 to 12. The illumination 16b and organization ID 10b of the temporary information table are stored in the organization ID 16h according to the month 12b. The processing so far is repeated for the number j.

  Device: For X2, the month 12b of the attendance information table is the same, and the total number of people 12d of the record with the same j and organization ID 12c is extracted, and the device 16c of the temporary information table record with month 12b = month 16a and j = organization ID 16h To remember. The same process is repeated for the number of months 12b and j.

  Since the human body: X3 is represented by the total number of persons / floor area, the floor ID 10e of the record having the same organization ID 10b and j in the organization information table is extracted. The floor area 11b of the record in which the extracted floor ID 10e matches the floor ID 11a of the floor information table is extracted. Further, the total number 12d of records having the same organization ID 12c and j in the attendance information table is extracted, and the total number 12d / floor area 11b is calculated for each month 12b = 1 to 12. The above processing is repeated as long as the organization ID 10b of the organization information table is stored, and stored in the human body 16d of the temporary information table record in which month 12b = month 16a and j = organization ID 16h. The same process is repeated for the number of months 12b and j.

  For solar heat X4, the floor ID 10e of the record whose organization ID 10b and j in the organization information table match is extracted. The window area 11c of the record in which the extracted floor ID 10e matches the floor ID 11a of the floor information table is extracted. This process is repeated as long as the organization ID 10b of the organization information table is stored, and the extracted window area 11c is stored in the solar heat 16e of the temporary information table record in which j = organization ID 16h. Since it does not change depending on the month, all the same values are stored.

  Since heat transfer: X5 is represented by the internal / external temperature difference / window area, the floor ID 10e of the record having the same organization ID 10b and j in the organization information table is extracted. The window area 11c of the record in which the extracted floor ID 10e matches the floor ID 11a of the floor information table is extracted. Further, the calculation of (outside air temperature 13c−room temperature 12e) / window area 11c is performed based on the record in which the year 12a and month 12b of the record in which the organization ID 12c and j in the attendance information table match j and the year 13a and month 13b in the temperature information table match. Is repeated for the number of months 12b. However, when it becomes a negative value, it is converted to a positive value. The result calculated in each j is stored in the heat transfer 16f of the temporary information table record in which month 12b = month 16a and j = organization ID 16h.

  The above processing is stored in the temporary information storage area 126 as type 16g = result. The above processing is repeated by adding 1 to the fiscal year and stored in the temporary information storage area 126 as type 16g = prediction.

  However, since there is no forecast value of weather information, the record of the year 13a = 0 is used.

  In addition, since the total number of people is year 12a and there is no data obtained by adding 1 to the year, the personnel 10d of the records of the year 10a = year, year + 1 and organization ID 10b in the organization information table is extracted, and the year 10a = year + 1 Divide 10d by year 10a = year 10d. This number is multiplied by the total number of people 12d of the year 12a = year and the corresponding organization ID 12c to obtain the total number of people of the year 12a = year + 1. Thus, the process of step S701 in the preprocessing is finished.

  Next, the process of the factor-specific estimation S702 step will be described. In the factor-by-factor estimation step, the power amount for each consumption factor associated with the thermal load factor is estimated from the power usage information and the Xi calculated in S701. First, the combination of Xi stored in the temporary information table and the amount of power corresponding to yn in (Equation 1) is obtained.As shown in the power management unit table shown in FIG. It is necessary except when it is managed, for example, management ID 8a = 1.

When lighting and equipment are managed together and air conditioning is separate, in this example, in the case of records with management IDs 8a = 10 and 100, the lighting and equipment are separately measured. Subtract the amount of power. That is, y air-conditioning = y air-conditioning-y illumination, equipment is replaced.
Therefore, regression analysis is performed separately for the combination of y illumination, equipment and X1, X2, and the combination of y air conditioning and X3, X4, X5, and αi and β are obtained. When lighting, equipment, and air conditioning are individually managed, the regression analysis is similarly performed by replacing y air conditioning = y air conditioning− (y lighting + y equipment).

  However, as described above, FIG. 8 shows two cases where lighting, equipment, and air conditioning are all managed together, and when lighting and equipment are managed together and air conditioning is separate. However, normally only one is defined in the power management unit table.

  In the computer processing, the determination can be made based on the number of management IDs 8a defined in the power management unit table, and the calculation of the power amount is performed in the record in which the year 9a and month 9b of the power amount table match. It is calculated by calculating the power amount 9d of each record with the value of.

Moreover, as the electric energy yn of (Equation 1) in the present embodiment, three types of air-conditioning, lighting, and equipment are handled as power consumption factors, so the following combinations (1), (2), and (3) Become one.
(1) All lighting, equipment, and air conditioning are managed together (when the management ID 8a is one type)
(Formula 2) y air conditioning, lighting, equipment = α1 · X1 + α2 · X2 + α3 · X3 + α4 · X4 + α5 · X5 + β1
(2) When two of the three types are the same (when the lighting and equipment are managed together and the air conditioning is different as in this embodiment, this is also the case when the management ID 8a is two types)
(Formula 3) y illumination, equipment = α1 · X1 + α2 · X2 + β1
(Expression 4) y air conditioning = α3 · X3 + α4 · X4 + α5 · X5 + β2
(3) When lighting, equipment, and air conditioning are all different (when there are three types of management ID 8a)
(Formula 5) y illumination = α1 · X1 + β1
(Formula 6) y device = α2 · X2 + β2
(Expression 7) y air conditioning = α3 · X3 + α4 · X4 + α5 · X5 + β3
Accordingly, a record is extracted in which the yn month 9b calculated above matches the temporary information table month 16a and the type 16g = actual record. When the organization ID 8c and the organization ID 16h corresponding to the same management ID 8a match, the lighting 16b, the device 16c, the human body 16d, the solar heat 16e, and the heat transfer 16f of the matching records are added. Then, the combination data corresponding to the pattern is passed to the regression analysis tool, and the calculation results of αi and β are obtained from the tool and stored in the estimation formula table shown in FIG. However, β of the consumption factor 15c occurs only for the type of the management ID 15b, for example, 10 and 100 in this embodiment. Further, it is assumed that the type 15e = estimation. As the heat generation factor 15c, the value of the heating element 14b that matches the ID 14a of the heating element information table is set according to αi (i = 1 to 5). For regression analysis, a commercially available regression analysis tool such as spreadsheet software is used. Thus, the process of the factor-specific estimation S702 step is completed.

  Next, the processing of the tissue-specific estimation S703 step will be described. In the estimation step for each organization, the power amount for each consumption factor is calculated by apportioning the power amount for each consumption factor based on the data of the organization that manages the power amount. Here, when a plurality of power consumption factors are managed together as in (Formula 2) and (Formula 3) described above, the previous year power consumption used for estimation is calculated for each power consumption factor. In addition, the power amount for each organization is calculated from these power amounts, including the power amount of the power consumption factor managed individually.

First, calculation processing for each power consumption factor will be described. This process is performed when there are two or less types of management IDs 8a. Estimated expression table type 15e = estimated, temporary information table type 16g = records of actual results are extracted and repeated for the number of months 16a. Xi (i = 1 to 5) is set as the value of the heat transfer 16f from the illumination 16b, and the calculated value 15d of the record in which the heating element 14b of the record with ID 14a = i matches the heating factor 15c is expressed as αi (i = 1). To 5). However, Xi is added to records of organization ID 16h belonging to the same management ID 8a to make one.
Here, γk is defined as follows.
γ1 = α1 · X1
γ2 = α2 · X2
γ3 = α3 · X3 + α4 · X4 + α5 · X5
Next, γγk is defined as follows and calculated.
When there is one type of management ID 8a,
γ1 = γ1 / 2
After setting γ2 = γ2 / 2,
γ3 = γ1 + γ2 + γ3
γγk = γk (γ1 + γ2 + γ3)
When there are two types of management IDs 8a, γγk = γk (γ1 + γ2)
Subsequently, the amount of power is calculated for each power consumption factor by multiplying the amount of power 9d of the record in which the month 16a and month 9b of the power amount table match and the management ID 8a and management ID 9c match by multiplying the γγk. In this embodiment, k = 1 is illumination, k = 2 is equipment, and k = 3 is air conditioning.

  It memorize | stores in the electric energy table according to factor of the temporary information storage area 126 shown in FIG. The factor-specific power amount table is composed of records including a month 17a, a lighting 17b, a device 17c, an air conditioner 17d, and a type 17e. Here, the type 17e is stored as a record.

  Next, the calculation of electric energy for each organization is executed. Here, the electric energy is calculated for each organization based on the value of the factor-specific electric energy table calculated above according to the organization ratio of Xi in (Equation 1).

  The evaluation result table shown in FIG. 18 is stored in the evaluation result storage area 127. The evaluation result table is composed of records including a year 18a, a month 18b, an organization ID 18c, an illumination 18d, a device 18e, and an air conditioner 18f.

  First, regarding the amount of power of illumination, in the temporary information table type 16g = result record, the month 16a coincides and the sum of the illumination 16b of the organization ID 16h having the same management ID 8a is obtained. Then, the illumination 17b with the month 16a = the month 17a is multiplied by the value obtained by dividing the illumination 16b by the sum of the illumination 16b for each organization ID 16h, and the record with the month 18b = the month 16a and the organization ID 18c = the organization ID 16h is obtained. Is stored in the illumination 18d. Moreover, it repeats by the number of months 16a. Similarly, the device stores a numerical value in the device 18e of the record generated above.

Regarding air conditioning, in the temporary information table type 16g = record of results, the month 16a matches, and the sum is obtained for each human body 16d, solar heat 16e, and heat transfer 16f of the organization ID 16h having the same management ID 8a. For each tissue ID 16h, values obtained by dividing the human body 16d, solar heat 16e, and heat transfer 16f by the above sum are obtained individually, and the sum is obtained. A value obtained by dividing this sum by 3 is multiplied by the air conditioner 17d to obtain an air conditioner 18f. Moreover, it repeats by the number of months 16a. However, the above processing assumes that the type 17e = result record.
The year 18a of the above processing is set to -1 of the year of the system as described above.

Then, the process which calculates the predicted value of the electric energy according to the factor according to organization is performed. Here, the estimation formula calculated above is used instead of the actual value. First, a factor-specific power amount is calculated. The estimation formula table type 15e = estimation and temporary information table type 16g = prediction records are extracted, and the following processing is repeated for the number of months 16a.
Xi (i = 1 to 5) is set as the value of the heat transfer 16f from the illumination 16b, and the calculated value 15d of the record in which the heating element 14b of the record with ID 14a = i matches the heating factor 15c is expressed as αi (i = 1). To 5). However, Xi is added to records of organization ID 16h belonging to the same management ID 8a to make one.

Here, γk is defined as follows.
γ1 = α1 · X1
γ2 = α2 · X2
γ3 = α3 · X3 + α4 · X4 + α5 · X5
Next, γγk is defined as follows and calculated.
When there is one type of management ID 8a,
γ1 = γ1 / 2
After setting γ2 = γ2 / 2,
γ3 = γ1 + γ2 + γ3
γγk = γk (γ1 + γ2 + γ3)
When there are two types of management IDs 8a, γγk = γk (γ1 + γ2)
Further, in the estimation formula table, a calculated value 15d of a record in which the type 15e = estimated and the heat generation factor 15c = β of the management ID 15b corresponding to the management ID 8a is extracted. According to the state of the management ID 8a, the γγk × calculated value 15d is calculated according to k and is set as βk.

  In this embodiment, there are two types of management IDs 8a, and the heat generation factor 15c = β is divided into two, where k = 1 is illumination and k = 2 is equipment. When the management ID 8a is of one type, it is divided into three including the air conditioning of k = 3.

  Next, i = 1 when k = 1, heat generation factor 15c = illumination, i = 2 when k = 2, heat generation factor 15c = device, i = 3, 4, 5 when k = 3. And yk = calculated value 15d × Xi + βk is calculated from the calculated value 15d at that time as the heat generation factor 15c = human body, solar heat, and heat transfer. However, when k = 3, yk = calculated value 15d × X3 + calculated value 15d × X4 + calculated value 15d × X5 + βk.

  In the power amount table by factor, when k = 1, it is stored in the illumination 17b, when k = 2, the device 17c is stored, and when k = 3, it is stored in the air conditioner 17d. Here, it is stored as type 17e = prediction. When the number of months 16a is over, the process is terminated.

  Next, the calculation of electric energy for each organization is executed. Here, the predicted value of the electric energy for each organization is calculated according to the organization ratio of Xi in (Equation 1) for the value of the power amount table for each factor calculated above.

  First, regarding the amount of power of illumination, in the temporary information table type 16g = prediction record, the month 16a matches, and the sum of the illumination 16b of the organization ID 16h having the same management ID 8a is obtained. Then, the illumination 17b with the month 16a = the month 17a is multiplied by the value obtained by dividing the illumination 16b by the sum of the illumination 16b for each organization ID 16h, and the record with the month 18b = the month 16a and the organization ID 18c = the organization ID 16h is obtained. Is stored in the illumination 18d. Moreover, it repeats by the number of months 16a. Similarly, the device stores a numerical value in the device 18e of the record generated above.

  Regarding air conditioning, in the temporary information table type 16g = record of results, the month 16a matches, and the sum is obtained for each human body 16d, solar heat 16e, and heat transfer 16f of the organization ID 16h having the same management ID 8a. For each tissue ID 16h, values obtained by dividing the human body 16d, solar heat 16e, and heat transfer 16f by the above sum are obtained individually, and the sum is obtained. A value obtained by dividing this sum by 3 is multiplied by the air conditioner 17d to obtain an air conditioner 18f. Moreover, it repeats by the number of months 16a. However, the above processing assumes that type 17e = predicted record. The year 18a of the above processing is the year of the system. Thus, the process of the tissue-specific estimation S703 step is completed.

  Next, the result output S704 step processing will be described. The evaluation result output unit 135 executes the following processing when the execution starts from the result output S704 step.

  FIG. 19 shows a power amount prediction screen. It consists of a toggle switch 19a, an organization-specific power display area 19b, a graph display area 19c, an analysis button 19d, and an end button 19e.

  The toggle switch 19a switches the contents of the organization-specific factor-by-factor power amount display area 19b between the previous year's results and the current year's prediction. If the toggle switch 19a is a record for the previous year, the year 18a in the evaluation result table is the year-1 of the system, and if the current year is predicted, the year 18a in the evaluation result table is a record for the system year. Then, for each organization ID 18c, the sum 18 is calculated for each of the lighting 18d, equipment 18e, and air conditioner 18f of the records from month 18b = 1 to 12, and the total of the three is obtained. To display.

  Further, for each year 18a in the evaluation result table, the sum of the illumination 18d, the device 18e, and the air conditioner 18f is obtained for each month 18b without distinguishing the organization ID 18c. Then, with month 18b = 1 as the base point, the sum of each month is added to the accumulated value up to the previous month, and the result is displayed in the graph display area 19c with a broken line. At this time, when the year 18a is the system year-1, the broken line is displayed as a solid line, and when the year is the system year, the broken line is displayed as a broken line, and the prediction is displayed in the vicinity. Then, the year 18a displays the difference between the accumulated value of the system year and the year of the system year-1 as a ratio.

  When the analysis button 19d is pressed, the process of the effect analysis S303 step is executed. When the end button 19e is pressed, the display screen is closed and the control screen shown in FIG. 4 is displayed. At that time, the temporary information table in the temporary information storage area 126 is stored in the organization-specific result storage area 125 as the temporary information storage table and the factor-specific power amount table as the factor-specific power amount storage table with the same configuration. The data in the information storage area is erased.

  The above processing is displayed through the output unit 150, and the input of the toggle switch 19a, the analysis button 19d, and the end button 19e from the user is received through the input unit 140. Thus, the process in step S704 for outputting the result and the process in step S302 for estimating the electric energy are completed.

  Subsequently, the processing in step S303 of effect analysis will be described. The same process is performed in both the continuation process of the electric energy estimation S302 and the process by the input of the improvement effect analysis button 401.

  However, in the case of the input of the improvement effect analysis button 401, since the power amount prediction screen is not displayed, only the process of the result output step S704 is performed. In that case, before the execution of the result output step S704, the temporary information storage table and the factor-specific power amount storage table stored in the organization-specific result storage region 125 are temporarily stored as a temporary information table and a factor-specific power amount table, respectively. Created in the storage area 126.

  The following processing is the operation of the improvement condition input unit 133. The improvement condition table shown in FIG. 30 is stored in the improvement condition storage area 119. The improvement condition table includes a type 30a, an organization ID 30b, a change ID 30c, and a cost 30d. The contents received from the user are stored through the input unit 140 in the following processing.

  First, the improvement effect analysis screen shown in FIG. 20 is displayed via the output unit 150. When the input of the whole 20a is received from the user via the input unit 140, the organization list 20c and the air conditioning: light shielding 20g are made inoperable. Moreover, if the input of the structure | tissue 20b is received, the illumination 20d and air conditioning: The floor 20f will be made into an operation impossible state similarly. The data of the organization list 20c is generated by excluding the same data from the name 10c of the organization information table.

  Next, operations of the illumination 20d, the device 20e, the air conditioning: floor 20f, and the air conditioning: light shielding 20g will be described. First, the illumination 20d will be described. The illumination information table shown in FIG. 21 is stored in the illumination information storage area 122. The illumination information table includes illumination ID 21a, illumination type 21b, rated power 21c, thinning rate 21d, cost 21e, and selection 21f. In the cost 21e, the total cost when the illumination condition of the illumination type 21b, the rated power 21c, and the thinning rate 21d is applied is set. The record of selection 21f = 1 is set as the current condition.

  FIG. 22 shows an illumination condition screen, which includes a table 22a and a selection 22b. Displayed by input of illumination 20d. The table 22a is created using the data of the illumination type 21b, the rated power 21c, the thinning rate 21d, and the cost 21e in the illumination information table, and the record in which the selection 21f = 1 is displayed in reverse video. The record selection of the table 22 from the user is accepted and confirmed by inputting the selection 22b. If the same record remains, the following improvement condition storage processing is not performed.

  For the improvement condition table, nothing is input for the type 30a = lighting and organization ID 30b, and a record is generated and stored as a user selection value in the change ID 30c.

  Next, the device 20e will be described. The device configuration table shown in FIG. 23 is stored in the device configuration information storage area 120. The device configuration table includes a device configuration ID 23a, a monitor 23a, a PC 23c, a TEL 23d, and a COPY 23e. Also, the device information table shown in FIG. 24 is stored in the device information storage area 121. The device information table includes a device classification 24a, a device ID 24b, a rated power 24c, and a cost 24d. The rated power 24c and the cost 24d are set to values per unit.

  FIG. 25 shows a device condition screen, which includes an organization display 25a, a device display 25b, and a selection 25c. Displayed by input from the device 20e. The organization display 25a controls display according to the entire improvement effect analysis screen 20a and organization 20b. In the case of the whole 20a, all the organizations having the name 10c in the organization information table and the selected organization in the organization 20b are displayed. At that time, the monitor 23a, PC 23c, TEL 23d, and COPY 23e of the record of the device configuration ID 10f corresponding to the name 10c and the device configuration ID 23a of the device configuration table are extracted and displayed on the organization display 25a. However, the year 10a = the year of the system.

  In the device display 25b, the device classification 24a, device ID 24b, rated power 24c, and cost 24d of the device information table are displayed in order of each record.

  To change the device, click each cell of the organization display 25a other than the organization name, and click the device ID cell of the device display 25b to update the cell of the organization display 25a with the value of the device ID cell of the device display 25b. To do. And it confirms by the input of selection 25c. If nothing is changed, the following improvement condition storage processing is not performed.

  In the improvement condition table, any of monitor, PC, TEL, and COPY is input to the type 30a according to the user's selection, and the organization ID 30b is set to the organization ID 10b that matches the name 10c of the organization information table from the contents of the organization display 25a. In the change ID 30c, a record is generated and stored as a user selection value. However, only the cells that have changed are implemented.

  Next, the air conditioning: floor 20f will be described. FIG. 26 shows an air conditioning: floor condition screen, which includes an organization display 26a, a floor display 26b, and a selection 26c. Air conditioning: Displayed by input on floor 20f. The organization display 26a displays the values of the name 10c, the personnel 10d, and the floor ID 10e as the name, personnel, and floor ID in the organization information table in the year 10a = system year-1 and year 10a = system year record. To do. However, other than the floor ID of the fiscal year = system fiscal year is not selectable and displayed.

  The floor display 26b displays all records with the floor ID 11a, floor area 11b, and window area 11c of the floor table information as the floor ID, floor area, and window area. It should be noted that items other than the floor ID are displayed as unselectable.

  To change the floor, click the floor ID cell of the organization display 26a and click the floor ID cell of the floor display 26b to update the cell of the organization display 26a with the value of the floor ID cell of the floor display 26b. And it confirms by the input of selection 26c. If the same record remains, the following improvement condition storage processing is not performed.

For the improvement condition table, type 30a = floor, organization ID 30b is organization ID 10b that matches organization information table name 10c from the content of organization display 26a, and a record is generated and stored as a user-selected value in change ID 30c. .

  Next, air conditioning: light shielding 20g will be described. The light shielding condition table shown in FIG. 27 and the light shielding condition table shown in FIG. 28 are stored in the light shielding condition storage area 123. The light shielding condition table includes a light shielding ID 27a, a glass type 27b, a blind presence / absence 27c, a shielding coefficient 27d, and a cost 27e. The light shielding state table includes a year 28a, a floor ID 28b, and a light shielding ID 28c.

  FIG. 29 shows an air conditioning: light shielding condition screen, which includes a condition display 29a and a selection 29b. Air conditioning: Displayed by input of light shielding 20g. The light shielding condition 29a displays all records in the light shielding condition table. In addition, the floor ID 10e of the record in which the organization information table name 10c matches the organization selected in the organization 20b on the improvement effect analysis screen is extracted. However, year 10a = system year-1 is assumed. Then, in the light shielding state table, the light shielding ID 28c of the record in which year 28a = year 10a and floor ID 28b = floor ID 10e is extracted. A record in which the shading ID 229a = the shading ID 28c is displayed in reverse as shown in FIG.

  The change of the shading condition is confirmed by receiving a click of the corresponding shading ID from the user and inputting the selection 29b. If the same record remains, the following improvement condition storage processing is not performed.

  For the improvement condition table, type 30a = light shielding, organization ID 30b is the organization ID 10b that matches the organization 10b in the organization information table and the organization selected in the organization 20b of the improvement effect analysis screen, and the change ID 30c has a user selection value. Generate and store records. Thus, the operation of the improvement condition input unit 133 is completed.

  The operation of the improvement effect calculation unit 134 will be described by the following processing. Here, the improvement effect is calculated and displayed by the change amount of the power amount prediction created by the process of the power amount estimation unit 132 based on the items of the improvement condition table created by the improvement condition input unit 133 described above.

  As a processing procedure, processing of the variable Xi (formula 1) accompanying the floor change is performed to estimate the electric energy. Then, the amount of change in electric power due to other changes is calculated, and the electric energy is calculated based on the improvement condition. First, processing associated with floor change will be described. However, if there is no record of improvement condition table type 30a = floor, it is not implemented.

  First, the organization information table is stored in the temporary information storage area 126 with the same configuration. After the effect analysis step S303, the organization information table stored in the temporary information storage area 126 is stored again as the organization information table in the organization information storage area 113.

  Subsequently, in the year record 10a = system year record of the organization information table, the value of the change ID 30c is substituted into the floor ID 10e in which the improvement condition table type 30a = the organization ID 30b of the floor record = the organization ID 10b. The improvement condition table type 30a is repeated until there are no more floor records.

  Then, the same processing as the above-described preprocessing step S701 is performed. However, the electric energy estimation unit 132 executes the year data in the system year-1 and the system year, and stores the result as a type 16g = actual result and prediction in the temporary information table. The improvement effect calculation unit 134 executes data for the fiscal year only for the fiscal year of the system, and stores the result as type 16g = improvement.

Next, the process which calculates the predicted value of the electric energy according to the factor according to organization is performed. First, a factor-specific power amount is calculated. The estimation formula table type 15e = estimation and temporary information table type 16g = improvement records are extracted, and the following processing is repeated for the number of months 16a.
Xi (i = 1 to 5) is set as the value of the heat transfer 16f from the illumination 16b, and the calculated value 15d of the record in which the heating element 14b of the record with ID 14a = i matches the heating factor 15c is expressed as αi (i = 1). To 5). However, Xi is added to records of organization ID 16h belonging to the same management ID 8a to make one.

Here, γk is defined as follows.
γ1 = α1 · X1
γ2 = α2 · X2
γ3 = α3 · X3 + α4 · X4 + α5 · X5
Next, γγk is defined as follows and calculated.
When there is one type of management ID 8a,
γ1 = γ1 / 2
After setting γ2 = γ2 / 2,
γ3 = γ1 + γ2 + γ3
γγk = γk (γ1 + γ2 + γ3)
When there are two types of management IDs 8a, γγk = γk (γ1 + γ2)
Further, in the estimation formula table, a calculated value 15d of a record in which the type 15e = estimated and the heat generation factor 15c = β of the management ID 15b corresponding to the management ID 8a is extracted. According to the state of the management ID 8a, the γγk × calculated value 15d is calculated according to k and is set as βk.

  In this embodiment, there are two types of management IDs 8a, and the heat generation factor 15c = β is divided into two, where k = 1 is illumination and k = 2 is equipment. When the management ID 8a is of one type, it is divided into three including the air conditioning of k = 3.

  Next, i = 1 when k = 1, heat generation factor 15c = illumination, i = 2 when k = 2, heat generation factor 15c = device, i = 3, 4, 5 when k = 3. And yk = calculated value 15d × Xi + βk is calculated from the calculated value 15d at that time as the heat generation factor 15c = human body, solar heat, and heat transfer. However, when k = 3, yk = calculated value 15d × X3 + calculated value 15d × X4 + calculated value 15d × X5 + βk.

  In the power amount table by factor, when k = 1, it is stored in the illumination 17b, when k = 2, the device 17c is stored, and when k = 3, it is stored in the air conditioner 17d. Here, it is stored as type 17e = improvement. When the number of months 16a is over, the process is terminated.

  The improvement result table shown in FIG. 31 is stored in the evaluation result storage area 127. The improvement result table is composed of records composed of type 31a, month 31b, organization ID 31c, illumination 31d, device 31e, and air conditioner 31f.

  Next, the calculation of electric energy for each organization is executed. First, regarding the amount of power of illumination, in the temporary information table type 16g = improvement record, the month 16a matches and the sum of the illuminations 16b of the organization ID 16h having the same management ID 8a is obtained. Then, the illumination 17b with the month 16a = the month 17a is multiplied by the value obtained by dividing the illumination 16b by the sum of the illumination 16b for each organization ID 16h to obtain the month 31b = month 16a and the organization ID 31c = organization ID 16h. Is stored in the illumination 31d. Moreover, it repeats by the number of months 16a. Similarly, the device stores the numerical value in the device 31e of the record generated above.

  Regarding air conditioning, in the temporary information table type 16g = improvement record, the month 16a matches, and each sum is obtained for each human body 16d, solar heat 16e, and heat transfer 16f of the organization ID 16h having the same management ID 8a. For each tissue ID 16h, values obtained by dividing the human body 16d, solar heat 16e, and heat transfer 16f by the above sum are obtained individually, and the sum is obtained. A value obtained by dividing this sum by 3 is multiplied by the air conditioner 17d to obtain an air conditioner 31f. Moreover, it repeats by the number of months 16a. However, in the above processing, type 17e = improvement record. The above processing type 31a is 0. Above, the process accompanying a floor change is complete | finished.

Subsequently, processing associated with other changes is executed.
Illumination will be described. The improvement condition table type 30a = the record in which the change ID 30C in the illumination record matches the illumination ID 21a in the illumination information table is extracted. In addition, the record of selection 21f = 1 is extracted. The rated power 21c × (100−thinning rate 21d) / 100 is calculated, and the former value is divided by the latter value.

  In the improvement result table, the month 31b and organization ID 31c of the record of type 31a = 0 are copied, and a record of type 31a = 1 is generated. Also, the illumination 31d of the record of type 31a = 0 is multiplied by the calculated value to obtain the illumination 31d of the record of type 31a = 1. The lighting process ends.

  The device will be described. Records of type 30a = monitor, PC, TEL, and COPY are extracted for each organization ID 30b in the improvement condition table. In the organization information table, the device configuration ID 10f of the record of year 10a = system year and organization ID 10b = organization ID 30b is extracted. Further, a record with device configuration ID 23a = device configuration ID 10f in the device configuration information table is extracted. Type 30a = according to monitor, PC, TEL, COPY, change ID 30c and change target monitor 23b, PC 23c, TEL 23d, COPY 23e corresponding to the numerical value of device classification 24a, device ID 24b rated power 24c, cost 24d To extract. For the rated power 24c corresponding to the change ID 30c, in the record of the organization ID 10b corresponding to the organization ID 30b, the year 10a = the system year's personnel 10d is multiplied unless the type 30a = COPY, and each rated power 24c Find the sum. Similarly, the result of multiplying the cost 24d by the personnel 10d is substituted into the cost 30d corresponding to the type 30a.

  In addition, in the record of the organization ID 10b corresponding to the organization ID 30b with respect to the rated power 24c corresponding to the numerical values of the monitor 23b, the PC 23c, the TEL 23d, and the COPY 23e, when the year 10a = the personnel 10d of the system year-1 is other than the COPY 23e Multiplication is performed to obtain the sum of the rated powers 24c. Divide the former sum by the latter sum.

  In the improvement result table, in the record of type 31a = 0, according to the month 31b, the device 31e of the record in which the organization ID 31c = organization ID 30b is multiplied by the division result to obtain the device 31e of the record of the type 31a = 1. End the device processing.

  The light shielding will be described. The organization ID 30b in the improvement condition table type 30a = light shielding record is extracted. In the organization information table, the floor ID 10e with the organization ID 10b = the organization ID 30b is extracted from the year 10a = system year record. Next, in the record of year 28a = system year of the light shielding state table, the light shielding ID 28c with floor ID 28b = floor ID 10e is extracted.

  Subsequently, the light shielding ID 27a in the light shielding condition table extracts the light shielding coefficient 27d corresponding to the change ID 30c and the light shielding ID 28c, respectively, and the light value S is obtained by dividing the former value by the latter value. Further, the cost 27e where the light shielding ID 27a = the change ID 30c is set as the cost 30d.

Next, with respect to the human body 16d, solar heat 16e, and heat transfer 16f of the record with the temporary information table type 16g = improvement, organization ID 16h = organization ID 30b, the estimation formula table type 15e = the heat generation factor 15c of the improvement record is Multiply the calculated values 15d for human body, solar heat, and heat transfer to make human body S, solar heat S, and heat transfer S, respectively. Then, SS = (solar heat S + heat transfer S) / (human body S + sun heat S + heat transfer S) is obtained. In the improvement result table, in the record of type 31a = 0, the air conditioner 31f of the record in which month 31b = month 16a and organization ID 31c = organization ID 30b is extracted. The air conditioner 31f of the record of type 31a = 1 is as follows.
(Air conditioning 31f of type 31a = 1 record)
= (Organization ID 31c = Air Conditioning 31f of Record with Organization ID 30b) × SS × Shading S
+ (Organization ID 31c = Air conditioning 31f of record with organization ID 30b) × (1-SS)
This is the end of the shading process.
Above, the process of step S303 of effect analysis is complete | finished.

Next, the process of step S304 for outputting results will be described.
The evaluation result output unit 135 executes the following processing when it is executed from the result output step S304.

FIG. 32 shows an improvement effect screen. It consists of an electric energy cumulative display area 32a, a cost display area 32b, and a graph display area 32c.
The cost information table shown in FIG. 33 is stored in the cost information storage area 124. The cost information table is composed of an expense item 33a and an expense item 33b.
The target reduction rate table shown in FIG. 34 is stored in the improvement condition storage area 119. The target reduction rate table is composed of a year 34a and a reduction rate 34b.

  First, for each year 18a in the evaluation result table, the sum of the illumination 18d, the device 18e, and the air conditioner 18f is obtained for each month 18b without distinguishing the organization ID 18c. Then, with month 18b = 1 as the base point, the sum total of each month is added to the cumulative value up to the previous month, and the result is displayed in the graph display area 32c with a broken line. At this time, when the year 18a is the system year-1, the broken line is displayed as a solid line, and when the year is the system year, the broken line is displayed as a broken line, and the prediction is displayed in the vicinity. Then, the year 18a displays the difference between the accumulated value of the system year and the year of the system year-1 as a ratio. Then, the former final cumulative value is displayed in the previous year result of the electric energy cumulative display area 32a and the latter final cumulative value is displayed in the prediction.

  Similarly, in the record of improvement result table type 31a = 1, the cumulative value is displayed in units of month 31b, the graph display area 32c is displayed as a broken line, and the improvement is displayed in the vicinity. And the difference of the accumulated value with respect to the accumulated value of the year -1 of the system in the year -1 is displayed as a ratio. Further, the final cumulative value is displayed after the improvement of the electric energy cumulative display area 32a.

  Subsequently, the sum of the costs 30d of all the records in the improvement condition table is calculated and displayed in the improvement investment in the cost display area 32b. Moreover, the difference of the cumulative value of the previous year result is taken from the improved cumulative value displayed in the electric energy cumulative display area 32a. The reduction rate 34b of the record in which the year 34a = the year of the system in the target reduction rate table is extracted. If a value obtained by adding the value obtained by multiplying the cumulative value of the previous year's result by the reduction rate 34b / 100 to the difference is positive, the value is multiplied by the cost table item 33a = emission right item 33b, and the emission right is obtained. Show on purchases. If it is negative, 0 is displayed. Further, the expense item 33a = the electricity fee item 33b is multiplied by the difference, and the change is displayed in the electricity charge change.

When the end button 32d is pressed, the display screen is closed and the control screen shown in FIG. 4 is displayed. At that time, the data in the temporary information storage area is erased.
The above processing is displayed through the output unit 150, and the input of the end button 32d from the user is received through the input unit 140.
Above, the process of step S304 of result output is complete | finished.
By the process on the control screen, the process of the power amount management apparatus 100 is terminated and the process of turning off the power is performed.

  In addition, this invention is not limited to an above-described Example, Various modifications are included. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. Further, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Further, it is possible to add, delete, and replace other configurations for a part of the configuration of each embodiment.

  Each of the above-described configurations, functions, processing units, processing means, and the like may be realized by hardware by designing a part or all of them with, for example, an integrated circuit. Each of the above-described configurations, functions, and the like may be realized by software by interpreting and executing a program that realizes each function by the processor. Information such as programs, tables, and files for realizing each function can be stored in a recording device such as a memory, a hard disk, an SSD (Solid State Drive), or a recording medium such as an IC card, an SD card, or a DVD.

  Further, the control lines and information lines indicate what is considered necessary for the explanation, and not all the control lines and information lines on the product are necessarily shown. Actually, it may be considered that almost all the components are connected to each other.

100 Electric energy management device 110 Storage unit 111 Measurement unit storage area 112 Electric energy storage area 113 Organization information storage area 114 Floor information storage area 115 Attendance information storage area 116 Temperature information storage area 117 Heating element information storage area 118 Estimation formula storage area 119 Improvement condition storage area 120 Equipment configuration information storage area 121 Equipment information storage area 122 Illumination information storage area 123 Shading condition storage area 124 Cost information storage area 125 Organizational result storage area 126 Temporary information storage area 127 Evaluation result storage area 130 Control unit 131 Evaluation mode selection unit 132 Electric energy estimation unit 133 Improvement condition input unit 134 Improvement effect calculation unit 135 Evaluation result output unit 140 Input unit 140
150 Output unit 150

Claims (12)

In a power management device having a storage area that stores information on power usage and information on heat load factors for each organization that manages power consumption, power consumption by organization that manages power from the power usage information An electric energy management method for estimating electric energy for each factor,
A pre-processing step of calculating a variable (x _i ) for each thermal load factor from the information stored in the storage area;
A factor-by-factor estimation step for estimating a power amount for each consumption factor associated with the thermal load factor from the power usage information and the variable;
An organization-specific estimation step for calculating the power amount for each organization and consumption factor by apportioning the amount of power for each consumption factor based on the data of the organization that manages the power amount;
A result output step of outputting the estimated energy by organization and consumption factor;
An electric energy management method comprising: The preprocessing step includes
Electricity estimation formula

(Y _n : electric energy, i: heat load factor, j: organization that manages electric energy)
X _i for each thermal load factor is calculated from the data stored in the storage area,
The estimation step for each factor estimates the amount of power for each consumption factor associated with the thermal load factor by calculating α _i and β in the power estimation formula by regression analysis. The power amount management method according to 1. 2. The power amount management method according to claim 1, wherein, in the factor-by-factor estimation step, a past power amount for each consumption factor is estimated based on data of an organization that manages the past power amount. 2. The power amount management method according to claim 1, wherein, in the factor-by-factor estimation step, data of an organization that manages the power amount is updated to estimate a future power amount by a consumption factor. 2. The electric energy management method according to claim 1, wherein β calculated in the factor-by-factor estimation step is prorated according to the estimated electric energy for each consumption factor. The power amount management method according to claim 1, wherein the power amount for each consumption factor includes a power amount by lighting, a power amount by equipment, and a power amount by air conditioning. The thermal load factor includes any of lighting, equipment, human body, solar heat, heat transfer,
Lighting: x ₁ = floor area / total number of people Equipment: x ₂ = total number of people Human body: x ₃ = total number of people / floor area Solar heat: x ₄ = window area heat transfer: x ₅ = inside / outside temperature difference / window area The information stored in the storage area, which is calculated from the total number of persons, floor area, window area data, and internal / external temperature difference data, as information on heat load factors in the organization that manages the electric energy is stored in the storage area. The electric energy management method described. The electric energy management method according to claim 1, further comprising:
Updating information relating to the thermal load factor;
Calculating the amount of electric power according to the updated information on the thermal load factor;
A step of comparing and outputting the amount of electric power before updating the information on the thermal load factor and the amount of electric power after updating the information on the thermal load factor;
An electric energy management method comprising: A storage unit having a storage area for storing information on heat load factors for each organization that manages usage information of power amount and power amount;
From the information stored in the storage unit, for each organization that manages the power amount, a control unit that estimates the power amount for each power consumption factor,
An output unit that outputs an amount of electric energy for each organization and consumption factor estimated by the control unit, and an electric energy management device comprising:
The control unit calculates a variable (x _i ) for each thermal load factor from the information stored in the storage unit, and uses a consumption factor associated with the thermal load factor from the usage information of the electric energy and the variable. Electricity characterized by estimating another electric energy and calculating the electric energy for each organization and consumption factor by apportioning the electric energy for each consumption factor based on the data of the organization that manages the electric energy. Quantity management device. The controller is
Electricity estimation formula

(Y _n : electric energy, i: heat load factor, j: organization that manages electric energy)
X _i for each thermal load factor is calculated from the data stored in the storage area,
The estimation step for each factor estimates the amount of power for each consumption factor associated with the thermal load factor by calculating α _i and β in the power estimation formula by regression analysis. 9. The electric energy management apparatus according to 9. From the information stored in the storage unit having a storage area storing information on the amount of power used and information on thermal load factors for each organization that manages the amount of power, A program executed in a power amount management apparatus comprising: a control unit that estimates a power amount for each consumption factor; and an output unit that outputs a power amount for each organization and consumption factor estimated by the control unit. Because
A pre-processing procedure for calculating a variable (x _i ) for each thermal load factor from the information stored in the storage area;
A factor-specific estimation procedure for estimating a power amount for each consumption factor associated with the thermal load factor from the power usage information and the variable;
An organization-specific estimation procedure for calculating the amount of power for each organization and consumption factor by apportioning the amount of power for each consumption factor based on the data of the organization that manages the amount of power;
A result output procedure for outputting the estimated energy by organization and consumption factor from the output unit;
Power management program characterized by The pretreatment procedure is as follows:
Electricity estimation formula

(Y _n : electric energy, i: heat load factor, j: organization that manages electric energy)
X _i for each thermal load factor is calculated from the data stored in the storage area,
The estimation procedure for each factor estimates the amount of power for each consumption factor associated with the thermal load factor by calculating α _i and β in the power estimation formula by regression analysis. 11. An electric energy management program according to 11.

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