JPWO2016121107A1 - Air conditioning management device - Google Patents

Abstract

A plant (10) having facilities including a mechanical facility (11), a lighting facility (12), and an air conditioner, and an air conditioner so that a worker (15) enters and leaves the room and the factory (10) has a target temperature. An air conditioning management system comprising an air conditioning management device (20) that controls the heat, and the air conditioning management device (20) uses the weather data and the production plan information to predict the heat load generated in the factory (10). A load prediction unit (25); an operation plan unit (26) that creates an operation plan of the air conditioning equipment based on the thermal load; and a control command unit (27) that controls the operation of the air conditioning facility according to the operation plan. The operation planning unit (26) uses the secondary planning method based on the temperature and humidity set in the factory (10) and the operation model of the air conditioning equipment for the heat load. Energy consumption of individual air conditioning equipment Make a driving plan to minimize with respect to the total sum of the energy consumed when driving.

Description

  The present invention relates to an air conditioning management system that performs air conditioning management in a factory.

  Conventionally, an energy demand optimization system that optimizes the amount of demand energy in a factory where products are produced has been proposed (for example, see Patent Document 1). Here, the correlation between past outside air information and production volume and energy consumption is obtained, and the energy consumption corresponding to the outside air information and production volume on the day is obtained from the correlation, and the production plan of the product is determined based on this energy consumption. Correct it.

JP 2004-151830 A

  However, the outdoor air information on that day in Patent Document 1 is used for obtaining energy consumption on the day of similar outdoor air information in the past, and is not used for calculating energy required for production. Absent. Patent Document 1 is for correcting a production plan, and is not for controlling the operation of an air conditioning facility provided in a factory. That is, Patent Document 1 does not disclose that the amount of heat generated in a factory is predicted and an operation plan for each air conditioning facility is created in consideration of energy efficiency.

  The present invention has been made in view of the above, and predicts the amount of heat generated in a factory where air conditioning equipment is installed according to the production plan, creates an operation plan for each air conditioning equipment in consideration of energy efficiency, and based on this The purpose is to obtain an air conditioning management system for air conditioning management in factories.

  In order to achieve the above object, an air conditioning management system according to the present invention has equipment including operating mechanical equipment, lighting equipment, and air conditioning equipment, and a factory in which an operator enters and leaves, and the inside of the factory is a target temperature. In the air conditioning management system comprising the air conditioning management device for controlling the air conditioning equipment as described above, the air conditioning management device uses the amount of heat generated in the factory calculated using production plan information, and weather data A heat load predicting unit that predicts a heat load including the calculated amount of intrusion heat entering the factory every unit time, and an operation that creates an operation plan of the air conditioning equipment based on the heat load per unit time A planning unit, and a control command unit that controls the operation of the air conditioning equipment according to the operation plan, and the operation planning unit includes a temperature set in the factory with respect to the thermal load, and The energy consumption of the entire air conditioning management system using the quadratic programming method, based on the operation model of the air conditioning equipment and the total energy consumption when the individual air conditioning equipment is rated. The operation plan is made so that

  According to this invention, the amount of heat generated in the factory where the air conditioning equipment is installed is predicted according to the production plan, the operation plan of each air conditioning equipment is created in consideration of energy efficiency, and the air conditioning management in the factory is performed based on this. It has the effect of being able to.

Block diagram schematically showing the configuration of related technology The block diagram which shows an example of the typical structure of the air-conditioning management system by Embodiment 1 The figure which shows an example of a structure of the air-conditioning management apparatus by Embodiment 1 with the flow of a process The figure which shows the outline | summary of the heat_generation | fever model of illumination by Embodiment 1 The figure which shows the outline | summary of the heat_generation | fever model of the electric motor part for conveyance by Embodiment 1 The figure which shows the outline | summary of the heat_generation | fever model of the electric heater part by Embodiment 1 The figure which shows the outline | summary of the heat_generation | fever model of the furnace air blower part by Embodiment 1 The figure which shows the outline | summary of the heat generation model of the reflow furnace by Embodiment 1. The figure which shows the outline | summary of the heat generation model of the worker by Embodiment 1. The figure which shows typically an example of the arrangement | positioning information of illumination, a machine, and a worker at the time of dividing the factory by Embodiment 1 into several air-conditioning zone The figure which shows an example of the heat_generation | fever model corresponding information for every air-conditioning zone by Embodiment 1 The figure which shows an example of the list of the predicted value of the emitted-heat amount per unit time and air-conditioning removal calorie | heat amount by Embodiment 1 The figure which displayed the predicted value of the emitted-heat amount of each component for every unit time and air-conditioning removal calorie | heat amount for Embodiment 1 by the graph The figure which shows typically an example of the structure of the air conditioner in the factory by Embodiment 1, and an external air conditioner The figure which shows an example of the operation plan output item of the air conditioner by the Embodiment 1, a heat source machine, and an external air conditioner. The figure which shows an example of the output characteristic curve of the medium of the heat-source apparatus by Embodiment 1 The flowchart which shows an example of the procedure of the air-conditioning management process by Embodiment 1. The figure which shows an example of the operating condition in case the machine by Embodiment 1 is a reflow furnace. The block diagram which shows typically the functional structure of the air-conditioning management apparatus by Embodiment 2. FIG. The figure which shows typically an example of the relationship between the number of production per unit time in the machine equipment in a factory by Embodiment 3, and internal calorific value. The figure which shows typically an example of a structure of the air-conditioning management system by Embodiment 4. The figure which shows an example of a structure of the mechanical installation by Embodiment 4. The figure which shows an example of production amount-calorific value correspondence information The figure which shows typically an example of a structure of the air-conditioning management system by Embodiment 5.

  Hereinafter, an air conditioning management system according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. Note that the present invention is not limited to these embodiments. Also, in the following, related applications by the applicant and their problems will be described first, and then embodiments of the present invention will be described.

  FIG. 1 is a block diagram schematically showing the configuration of the related technology, (a) is a block diagram schematically showing an example of the configuration of the air conditioning system control device according to the first related technology, and (b) It is a block diagram which shows typically an example of a structure of the secondary planning problem calculation apparatus by a 2nd related technique.

  As a 1st related technique, there exists an air-conditioning system control apparatus described in Unexamined-Japanese-Patent No. 2011-214794. As shown in FIG. 1A, the air conditioning system control apparatus 700 includes an air conditioner operation data acquisition unit 701 that acquires air conditioner operation data from the outside, a weather data acquisition unit 702 that acquires weather data, and a heat A parameter learning unit 703 that has a general-purpose building model 703a based on the conduction equation and obtains physical parameters of the building model 703a by learning; a thermal load prediction unit 704 that predicts a thermal load based on the physical parameters and the building model 703a; And a schedule creation unit 705 that determines an operation schedule of each air conditioner based on the predicted heat load, and an operation schedule output unit 706 that transmits the operation schedule to each air conditioner.

  Here, one or more air conditioners are acceptable. The air conditioner may be a large heat source machine such as a building multi-air conditioner, a packaged air conditioner, a room air conditioner, or an absorption chiller composed of an outdoor unit and an indoor unit.

  The control device of this air conditioning system realizes a building model that predicts the air conditioning load according to a physical equation. Further, the air conditioning load predicted by the building model is used as an input variable to determine the operating state of the air conditioning system that minimizes the total required power of the air conditioners constituting the air conditioning system. And each air conditioner is controlled according to the determined target value, air-conditioning of several air-conditioning object space is performed efficiently, and energy saving is implement | achieved.

  As a second related technique, there is a quadratic programming problem calculation apparatus described in Japanese Patent Application Laid-Open No. 2010-79323. As shown in FIG. 1B, the secondary programming problem calculation apparatus 800 obtains initial values of variables that are Lagrange multiplier groups of control variables and constraint equation groups, and stores them in the variable storage means 801. 802, a mismatch amount calculation unit 803 that calculates a mismatch amount that is an optimality condition divergence amount of the quadratic programming problem, a correction amount calculation unit 804 that calculates a variable correction direction and a correction amount so that the mismatch amount decreases, The correction amount storage means 805 for storing the correction direction and the correction amount of the variable calculated by the correction amount calculation means 804, and the variable storage means 801 corresponding to the control variable or the slack variable of the control variable whose correction amount is the first threshold value or less are fixed. Fixed variable setting means 806 for setting the flag, and updating the numerical value of the variable storage means 801 with the correction direction and the correction amount for the variable having no fixed flag That the variable correcting means 807, the repeating unit 810 to output the value of the stored control variables in the variable storage unit 801 and convergence determination, and a.

  The air conditioning system is configured by combining air conditioning equipment having various efficiency characteristics. The heat exchange capacity of each air conditioning facility is a multivariable system that changes under the influence of use conditions such as the outside air temperature and humidity, or the temperature and flow rate of the heat medium circulating in the heat exchanger. The secondary planning problem calculation apparatus of the second related technology is effective as a means for obtaining an optimal solution that minimizes the energy consumption of the entire air conditioning system in consideration of the use conditions of these air conditioning facilities.

  Generally, in factories, it is necessary to take in fresh outside air for the residents in the building. However, in the first related technology, the amount of heat in the outside air that has been taken into It is difficult to predict. Moreover, the fluctuation pattern of the air conditioning load in an office building tends to be almost constant every day depending on residents, lighting, OA (Office Automation) equipment, and weather conditions. On the other hand, the variation pattern of the air conditioning load in the factory varies greatly based on the production plan information. Furthermore, even in a zone where production is completed based on the production plan in the factory, the air conditioning equipment may operate to maintain the specified temperature and consume unnecessary power, and energy saving is possible by changing the specified temperature for each zone. It is requested. However, the first related technology does not support control of an air conditioning system in a factory. Therefore, an embodiment in which the first related technology can be applied to control of an air conditioning system in a factory using the second related technology will be described below.

Embodiment 1 FIG.
FIG. 2 is a block diagram illustrating an example of a schematic configuration of the air conditioning management system according to the first embodiment. The air conditioning management system includes a factory 10 that manufactures products and has air conditioning equipment, and an air conditioning management apparatus 20 that manages the air conditioning equipment in the factory 10.

  The factory 10 is a facility that manufactures products while operating mechanical equipment 11 that performs processing or assembly according to a production plan. The factory 10 is a clean room equipped with a device for manufacturing a semiconductor device, a machine tool such as a lathe or machining center, a factory that processes materials using a device such as a laser machining device or an electric discharge machining device, or a mechanical controller using a programmable controller. Examples include factories that assemble products while controlling. In FIG. 1, a clean room 10 </ b> A and an assembly room 10 </ b> B having an exhibition room and an office are shown as the factory 10.

  The factory 10 includes mechanical equipment 11 that performs processing or assembly, lighting equipment 12 in the factory 10, and air conditioning equipment that controls the indoor environment such as temperature and humidity in the factory 10 to be within a predetermined range. Have. The air conditioner includes an air conditioner 13 that removes the amount of heat generated in the factory 10 in which the mechanical equipment 11 is arranged and adjusts the factory 10 so as to have a set temperature and a set humidity, and a set temperature and a set value in the factory 10. And an external air conditioner 14 for introducing outside air into the factory 10 so as to be in humidity. The external air conditioner 14 includes heat source devices 141a and 141b, a pump 142, and a heat exchanger 143.

  FIG. 3 is a diagram illustrating an example of the configuration of the air-conditioning management apparatus according to Embodiment 1 together with the flow of processing. The air conditioning management device 20 includes a weather data acquisition unit 21, an air conditioner characteristic data acquisition unit 22, a production plan information acquisition unit 23, a data storage unit 24, a thermal load prediction unit 25, an operation planning unit 26, and a control. And a command unit 27.

  The meteorological data acquisition unit 21 acquires meteorological data for each unit time of the day when air conditioning management is performed in the area where the factory is installed, via the network. As weather data, the amount of solar radiation every 30 minutes, outside temperature humidity, etc. can be mentioned. The weather data is obtained from a weather data distribution company.

  The air conditioner characteristic data acquisition unit 22 is characteristic information of the air conditioner used in the factory 10 to be controlled. The air conditioner characteristic data is information including the relationship between the power consumption of each air conditioner and the amount of heat supplied. In addition, when it is necessary to calculate the amount of heat supplied by the air conditioner, that is, the amount of heat removed by the air conditioner, the air conditioner characteristic data includes the operating frequency, evaporation temperature, condensation temperature, supply heat amount and power consumption of each outdoor unit. Including the relationship.

  The production plan information acquisition unit 23 acquires production plan information in the factory 10. The production plan information includes the number of machine facilities 11 to be operated in the factory 10, the time and conditions for operation, the number of lighting facilities 12 to be lit in the factory 10, the lighting time, and the number of workers 15 entering the factory 10. , Including entry time. Moreover, in the example shown below, the case where the inside of the factory 10 is divided into the air-conditioning zone C from the several air-conditioning zone A is shown. The air conditioning zone is a range in which the temperature and humidity can be adjusted by the air conditioning equipment. In the production plan information, it is possible to classify in which air-conditioning zone each mechanical equipment 11, lighting equipment 12, and worker 15 are present. Further, for the worker 15, more detailed information may be defined regarding which area in the factory 10 is located at what time, or the area and time in which no person in the factory 10 exists.

  The data storage unit 24 stores data acquired via the weather data acquisition unit 21 and the air conditioner characteristic data acquisition unit 22.

  The thermal load predicting unit 25 uses air conditioner characteristic data, meteorological data, and production plan information as input data and an operation model for a heating element in the factory 10 and a building heat model. The amount of heat generated in each air conditioning zone and the amount of heat flowing into each air conditioning zone are calculated. In the production plan information, the type or number of the machine equipment 11 to be moved varies depending on the time, so that the amount of heat generated by the machine also changes. In addition, since the amount of solar radiation, the outside air temperature, and the outside air humidity differ depending on the time, the amount of heat flowing into the factory 10 also varies depending on this. Therefore, it is desirable to perform the calculation every unit time. The unit time is 30 minutes, 1 hour, or the like. Moreover, it is desirable to calculate the amount of heat until the time when the weather data can be acquired in units of one day. Then, the heat load predicting unit 25 obtains the air conditioning removal heat amount of each air conditioning zone obtained by summing the calculated heat amount flowing into each air conditioning zone and the heat amount generated in each air conditioning zone per unit time.

  The heat load prediction unit 25 includes a heat generation amount prediction unit 251, an intrusion heat prediction unit 252, and a removal heat amount prediction unit 253. The heat generation amount prediction unit 251 predicts the heat generation amount in each air conditioning zone per unit time based on the production plan information. The intrusion heat prediction unit 252 predicts the intrusion heat that enters the air conditioning zones per unit time. The removal heat quantity prediction unit 253 predicts the removal heat quantity in each air conditioning zone per unit time based on the set temperature and humidity of the air conditioner. In addition, when the production plan information does not divide the factory 10 into a plurality of air conditioning zones, the heat generation amount prediction unit 251, the intrusion heat prediction unit 252 and the removal heat amount prediction unit 253 divide the entire factory 10 into one air conditioning zone. As a prediction, heat generation amount per unit time, intrusion heat and removal heat amount are predicted.

  As shown in FIG. 3, the heat generation amount prediction unit 251 calculates a heat generation amount using an operation model for a device that exists in the factory 10 and generates heat. Illuminating equipment 12, mechanical equipment 11, worker 15 and the like can be exemplified as those that generate heat in factory 10. Hereinafter, the lighting equipment 12 is referred to as the lighting 12, and the mechanical equipment 11 is referred to as the machine 11. In the production plan information, the operating state of the machine 11, the lighting state of the lighting 12, or the arrangement state of the worker 15 is defined in time series for each unit time. Therefore, the calorific value per unit time can be predicted in cooperation with the production plan information.

FIG. 4 is a diagram illustrating an outline of a heat generation model of illumination according to the first embodiment. The heat generation model of the illumination 12 is a function having the production plan information about the illumination 12 as input, the rated power of the illumination as a predetermined constant, and the illumination heat generation amount as output. The production plan information for the illumination 12 is an instruction to turn on or off the illumination 12 for each unit time defined in the production plan information. This illumination heat generation model can be expressed by a function of the following equation (1). However, the production plan information when the illumination 12 is ON is “1”, and the production plan information when the illumination 12 is OFF is “0”.
Lighting calorific value = production plan information (time, ON or OFF) x number of lights x lighting rated power (1)

  There are many machines 11 used in the factory 10, such as a lathe, a laser processing machine, a film forming apparatus, an etching apparatus, a reflow furnace, and a belt conveyor. Here, an example of calculating the calorific value of the machine will be described by taking the case of a reflow furnace as an example. The reflow furnace is composed of an electric motor part for conveyance, an electric heater part, and a furnace blower part, considering the components that generate heat. Therefore, each of these component parts is modeled, and a combination of these models is the amount of heat generated in the reflow furnace.

FIG. 5 is a diagram illustrating an outline of a heat generation model of the electric motor unit for conveyance according to the first embodiment. The heat generation model of the transfer motor unit is input with the production plan information for the transfer motor unit, and the rated power, load factor, and motor efficiency of the transfer motor unit are set as predetermined constants. It is a function which makes the calorific value of a part output. The production plan information for the transfer motor unit is the transfer speed of the transfer motor unit of the reflow furnace per unit time defined in the production plan information. The heat generation model of the conveying motor unit can be expressed by a function of the following equation (2).
Conveyor motor heating value = production plan information (time, speed) x motor rated power x load factor x (1-motor efficiency) (2)

FIG. 6 is a diagram showing an outline of a heat generation model of the electric heater unit according to the first embodiment. The heat generation model of the electric heater unit receives the production plan information for the electric heater unit, sets the rated power, load factor, and heater efficiency of the electric heater unit to predetermined constants, and the amount of heat generated by the electric heater unit. Is a function that outputs. The production plan information for the electric heater unit is the temperature of the electric heater unit of the reflow furnace per unit time defined in the production plan information. This heat generation model of the electric heater part can be expressed by a function of the following equation (3).
Electric heater calorific value = production plan information (time, temperature) x electric heater rated power x load factor x (1-electric heater efficiency) (3)

FIG. 7 is a diagram showing an outline of a heat generation model of the furnace blower unit according to the first embodiment. The heat generation model of the furnace blower section takes the production plan information about the furnace blower section as input, the air volume, total pressure, coefficient, and fan efficiency as predetermined constants, and the heat generation amount of the furnace blower section This is the output function. The production plan information for the furnace blower section is the air volume of the furnace blower section of the reflow furnace for each unit time defined in the production plan information. The heat generation model of the furnace blower unit can be expressed by a function of the following equation (4).
Furnace blower heat generation = production plan information (time, air volume) × (air air volume × total pressure) / (9.8 × 6120 × fan efficiency) (4)

  FIG. 8 is a diagram showing an outline of a heat generation model of the reflow furnace according to the first embodiment. The heat generation model of the reflow furnace has a structure in which the heat generation model of the transfer motor section shown in FIGS. 5 to 7, the heat generation model of the electric heater section, and the heat generation model of the furnace blower section are added together. Specifically, the production plan information is used as a common input for the heat generation model of the transfer motor section, the heat generation model of the electric heater section, and the heat generation model of the furnace blower section. The outputs of the heat generation model of the transfer motor section, the heat generation model of the electric heater section, and the heat generation model of the furnace blower section are added, and the sum is the reflow furnace heat generation amount that is the output of the reflow furnace model.

FIG. 9 is a diagram showing an outline of a worker heat generation model according to the first embodiment. The heat generation model of the worker 15 is a function having the production plan information about the worker 15 as input, the human body heat generation amount as a predetermined constant, and the heat generation amount of the worker 15 as output. The production plan information for the worker 15 is the number of workers 15 per unit time defined in the production plan information. The calorific value model of the worker 15 can be expressed by a function of the following equation (5).
Worker calorific value = production plan information (time, number of people) x human body calorific value (5)

  Note that the heat generation model of the worker 15 is only how many people are in the factory 10 based on the production plan information, but more detailed worker 15 is used by using the position information of the worker in the factory 10. The amount of generated heat may be calculated. For example, when the worker 15 moves between a plurality of air-conditioning zones by patterning position information such as the work position and action range of the worker 15, the amount of heat generated by the worker 15 in each air-conditioning zone can be reduced. It can be estimated more accurately.

  These models are set for each of the models with different characteristics. In the case of the heat generation model of the illumination 12, the rated power of the illumination 12 is set for each different one. The same applies to the heat generation model of the machine 11.

  FIG. 10 is a diagram schematically illustrating an example of lighting, machine, and worker arrangement information when the factory according to Embodiment 1 is partitioned into a plurality of air conditioning zones. As shown in this figure, three air conditioners 14A to 14C are arranged in the factory 10, and an area in which air conditioning can be controlled by each of the air conditioners 14A to 14C is an air conditioning zone A to an air conditioning zone C. In each air-conditioning zone A to air-conditioning zone C, illumination, machines, and workers are arranged as shown in the figure. Thus, when the factory 10 is divided into a plurality of air conditioning zones A to C, the heating heat generation amount, the mechanical heat generation amount, and the worker heat generation amount are obtained for each air conditioning zone C from the air conditioning zone A. . At this time, using the heat generation model correspondence information for each air-conditioning zone C from the air-conditioning zone A including the lighting, machinery, and workers present in each air-conditioning zone A to the air-conditioning zone C, the heat generation amount for each air-conditioning zone C from the air-conditioning zone A Ask for.

  FIG. 11 is a diagram illustrating an example of heat generation model correspondence information for each air-conditioning zone according to Embodiment 1. In the heat generation model correspondence information for each air conditioning zone, the lighting model of the lighting 12 included in the air conditioning zone, the machine model of the machine 11, the worker model and the number of workers 15 are defined for each air conditioning zone. Yes. The heat generation model correspondence information for each air conditioning zone in FIG. 11 is created based on the lighting, machine, and worker arrangement information in FIG. And the total calorific value calculated | required for every air-conditioning zone C from the air-conditioning zone A turns into an air-conditioning zone calorific value. The heat generation amount prediction unit 251 is configured to be able to predict the heat generation amount for each air conditioning zone based on the factory-specific production plan in the heat load prediction unit of the first related technology.

  As shown in FIG. 3, the intrusion heat prediction unit 252 calculates an air-conditioning zone intrusion heat amount that is an amount of heat entering the air-conditioning zone of the factory building per unit time using the building heat model and weather data. To do. The thermal model of a building is a function for calculating the amount of heat entering from a building wall, roof, glass, and the like using weather data such as outside air temperature and solar radiation. The building heat model includes the heat transfer rate and heat capacity from the outside air temperature, the amount of solar radiation, the amount of heat generated by the worker 15, the machine 11 and the lighting 12, and the measured value of the heat treatment by the air conditioner 13 for the set room temperature. A function is estimated that estimates the heat characteristics of the building and uses this heat transfer coefficient and heat capacity to estimate the amount of heat that enters the building from the outside.

  As shown in FIG. 3, the heat removal amount prediction unit 253 sets the heat generation amount calculated by the heat generation amount prediction unit 251, the intrusion heat calculated by the intrusion heat prediction unit 252, and each air conditioning zone in the factory 10. The amount of heat removed per unit time in each air-conditioning zone is calculated using the temperature and humidity. Hereinafter, the amount of heat removed from the air conditioning zone is referred to as the amount of heat removed from the air conditioning zone. The set temperature and humidity and the amount of heat to be removed are output to the operation planning unit 26.

  FIG. 12 is a diagram illustrating an example of a list of predicted values of the heat generation amount and the air conditioning removal heat amount per unit time according to the first embodiment. Here, predicted values of the heat generation amount and the air conditioning removal heat amount per unit time are calculated for the air conditioning zone C from the plurality of air conditioning zones A partitioned as shown in FIG. The time indicates a time zone to be predicted. The length of this time zone is a unit time, which is 1 hour in this example. For each air-conditioning zone A to air-conditioning zone C, the lighting heat generation amount, machine heat generation amount and worker heat generation amount predicted by the heat generation amount prediction unit 251 described above, and the intrusion predicted by the intrusion heat prediction unit 252 for each unit time The amount of heat and the value of the air conditioning removal heat amount predicted by the removal heat amount prediction unit 253 are shown. In this example, the machine-generated heat amounts of all the machines existing in the air-conditioning zone are collectively displayed. However, in order to perform more detailed control, the machine-generated heat amounts can be displayed for each machine 11. desirable. Further, the heat load prediction unit 25 displays the generated heat amount, the intrusion heat amount, and the air conditioning removal heat amount calculated using each operation model in a table format, but may be displayed in a graph on a display unit (not shown). .

  FIG. 13 is a diagram in which the calorific value of each component and the predicted value of the air conditioning removal calorie per unit time according to the first embodiment are displayed in a graph. Here, the amount of heat generated by the machine is divided into three types of machines (1) to (3) and displayed. In these figures, the horizontal axis represents time, and the vertical axis represents the amount of heat generated or the amount of heat removed. Also in this example, a graph of predicted values of the heat generation amount and the air conditioning removal heat amount is created for each air conditioning zone C from the air conditioning zone A. In FIG. 13, a graph G1 is a diagram showing a temporal change in the amount of heat generated by the illumination, a graph G2 to a graph G4 are diagrams showing a time change in the mechanical calorific value of each of the machines (1) to (3), and a graph G5 is a graph It is a figure which shows the time change of a worker's calorie | heat amount, The graph G6 is a figure which shows the time change of an intrusion heat amount, The graph G7 is a figure which shows the time change of an air-conditioning removal heat amount.

  As shown in the graph G6 of FIG. 13, the amount of heat entering the building increases from morning until around 13:00 and decreases from there until evening. This is due to the amount of solar radiation from the sun and the outside air temperature. Further, as shown in the graphs G2 to G4 in FIG. 13, the machines (1) and (3) are turned on before 9 o'clock in order to make them usable from 9 o'clock. (2) is a machine facility for processing the machine (1) and (3) and may be turned on at 9 o'clock. Thus, by performing processing according to the production plan, the power-on start time varies depending on the mechanical equipment. In addition, since the worker 15 has a lunch break from 12:00 to 13:00, the mechanical equipment is also in a dormant state, and the amount of generated heat is temporarily reduced. However, since the work starts again from 13:00, and it takes time until the machine is restarted when all the power of the mechanical equipment is turned off, only the portions that may be put into a dormant state are in the dormant state.

  As shown in the graphs G1 and G5 in FIG. 13, the heating heat generation amount and the worker heat generation amount are mainly between 9:00 to 12:00 and 13:00 to 20:00 when the worker 15 exists in the factory 10. Has occurred. Further, since 12:00 to 13:00 is a lunch break for the worker 15, the worker 15 does not exist in the factory 10 during this period, so the amount of generated heat becomes zero. Moreover, since the illumination 12 at this time is also almost turned off, the amount of generated heat is a value close to zero.

  A graph G7 in FIG. 13 is obtained by adding all the generated heat amounts of the graph G1 to the graph G6 in FIG. 13 and shows the total generated heat amount. In other words, the total amount of generated heat is the amount of heat that must be removed by the air conditioning equipment, and is the amount of heat removed from the air conditioning. The amount of heat removed from the air conditioning is also referred to as a demand for air conditioning heat load because it also gives a demand for heat load on the air conditioning equipment.

  The operation planning unit 26 makes an operation plan for removing the air conditioning removal heat amount predicted by the heat load prediction unit 25 using the air conditioner 13 and the external air conditioner 14 installed in the factory. An operation plan is made for each air conditioning zone. FIG. 14 is a diagram schematically illustrating an example of the configuration of the air conditioning equipment and the external air conditioner in the factory according to the first embodiment. In this example, the air conditioning facility includes an air conditioner 13, a heat source device 141, a pump 142, and an external air conditioner 14.

  The air conditioner 13 sucks air in the factory 10 and adjusts the temperature and humidity of the sucked air so as to remove the air-conditioning removal heat amount, and then returns the air to the factory 10 again. An example of the air conditioner 13 is a packaged air conditioner. The air conditioner 13 is an air conditioning facility that removes the amount of heat generated in the factory 10, that is, the amount of heat removed from the air conditioning.

  The heat source device 141 is a heat source when heating or cooling the air outside the factory 10, and heats or cools a medium such as water and circulates between the heat exchanger 143. As the heat source 141, a cooling heat source 141a and a heating heat source 141b are installed. This is because the air dehumidified by the heating heat source 141b is heated to a predetermined temperature after the humidity of the air outside the factory 10 is dehumidified by the cooling heat source 141a. The pump 142 is used to flow the medium between the heat source device 141 and the external conditioner 14. The external air conditioner 14 includes a heat exchanger 143 that cools or heats air outside the factory 10 to a predetermined temperature with a medium sent from the heat source apparatus 141, and air that has been set to a predetermined temperature inside the factory 10. And a fan 144 for feeding to the fan. The heat exchanger 143 also has a function of setting the air outside the factory 10 to a predetermined humidity. Thus, the external air conditioner 14 is an air conditioning facility that supplies the outside air to the factory 10 by using the heat source apparatus 141 to change the outside air to the set temperature and the set humidity in the factory 10.

  In the operation planning unit 26, in the operation planning unit of the first related technology, a heat source model that models the heat source unit 141, an external conditioner model that models the external conditioner 14, and an air conditioner that models the air conditioner 13 The operation plan of the air conditioner 13, the heat source device for cooling 141a, the heat source device for heating 141b, and the external air conditioner 14 so as to achieve the optimum energy saving operation for the entire air conditioning system using the second related technology. create. The operation planning unit 26 corresponds to the schedule creation unit of the first related technology and corresponds to the secondary planning problem calculation apparatus of the second related technology. That is, the operation plan unit 26 creates an operation plan for the heat source device 141, the external air conditioner 14, and the air conditioner 13 using the secondary planning method. At this time, an operation plan for the heat source device 141, the external air conditioner 14, and the air conditioner 13 is created so as to achieve an optimum energy saving operation in the entire air conditioning system.

  The operation plan shows operation parameters for operating the air conditioning equipment in each air conditioning zone per unit time. FIG. 15 is a diagram illustrating an example of operation plan output items of the air conditioner, the heat source unit, and the external air conditioner according to the first embodiment. The air conditioner model outputs operation or stop, temperature setting, and blowing capacity setting as operation plan output items. The air blowing capacity setting is the air volume, and the air volume varies depending on the compressor frequency f. The cooling heat source machine model outputs operation or stop and cold water temperature setting as operation plan output items. The heating heat source unit model outputs operation or stop and hot water temperature setting as operation plan output items. The external air conditioner model outputs operation or stop, supply air temperature setting, and supply air humidity setting as operation plan output items.

  Here, the case where the water supply temperature setting of the cold water and the hot water of the heat source unit 141 is optimized in accordance with the predicted amount of heat removed from the air conditioning, the supply temperature of the external air conditioner, and the humidity condition will be described. As described above, heating elements such as the machine 11, the lighting 12, and the worker 15 exist in the factory 10. In addition, it is required to send fresh outside air into the factory 10. Therefore, significant energy saving can be realized by effectively utilizing the temperature and humidity of the outside air.

  In the air conditioning system in which the air conditioner 13, the external air conditioner 14, and the heat source apparatus 141 are combined, first, an optimum operation plan that saves energy of the external air conditioner 14 and the heat source apparatus 141 serving as a base is calculated. This is to determine the output temperatures of the cooling heat source 141a and the heating heat source 141b so that the temperature and humidity in the factory 10 or each air-conditioning zone become set values and power consumption is minimized.

  FIG. 16 is a diagram illustrating an example of an output characteristic curve of a medium of the heat source apparatus according to the first embodiment, where (a) illustrates a cold water output characteristic curve and (b) illustrates a hot water output characteristic curve. In these diagrams, the horizontal axis represents the output temperature of the medium, and the vertical axis represents the coefficient of performance COP representing the efficiency of the cooling heat source unit model and the heating heat source unit model, respectively. In general, the relationship between the cooling heat source machine model and the output temperature of the cold water is expressed as shown in FIG. 16A, and the relationship between the coefficient of performance COP representing the efficiency of the heating heat source machine model and the output temperature of the hot water. Is expressed as shown in FIG.

The coefficient of performance COP of the heat source device 141 is expressed by the following equation (6), where R [W] is the output of the heat source device 141 and ER [W] is the input energy. Then, the output R [W] of the heat source device 141 can be converted as in the following equation (7) from the equation (6).
COP = R / ER (6)
R = COP × ER (7)

Here, the coefficient of performance COP of the heat source unit 141 is expressed by the following equation (8), where the outside air temperature is Ta [K], a is a coefficient, and c is a constant.
COP (Ta) = a × Ta + c (8)

As described above, the output R (j, t) [W] of the heat source machine j considering the time t and the outside air temperature Ta [K] is expressed as the following equation (9). However, j is a natural number.
R (j, t) = COP (Ta) × ER (j, t) (9)

Further, the output R [W] of the heat source device 141 is expressed by the following equation (10) depending on the temperature and flow rate of the circulating water. Where CP is the specific heat of water, 4.218 J / (Kg · K), ρ is the density [Kg / m ³ ], Tin is the heat source return temperature [K], and Tout is the heat source machine. The water supply temperature [K], and Rf is the heat source machine water supply flow rate [m ³ / s].
R = CP × ρ × (Tin-Tout) × Rf (10)

The output R (j, t) [W] of the heat source machine j considering the time t is expressed by the following equation (11) from the equation (10).
R (j, t) = CP × ρ × (Tin (j, t) −Tout (j, t)) × Rf (j, t) (11)

Further, from the equations (9) and (11), the input energy ER [W] is expressed as the following equation (12).
ER (j, t) = R (j, t) / COP (Ta)
= (CP × ρ × (Tin (j, t) -Tout (j, t)) × Rf (j, t)) / COP (Ta) (12)

Note that the calculation formula of the input energy ER [W] can be expressed not by the equation (12) but also by the regression equation of the following equation (13). However, a1 to a9 are coefficients of the characteristic formula of the heat source device, and can be calculated by, for example, an air conditioning facility simulation tool (LCEM tool) provided by the Ministry of Land, Infrastructure, Transport and Tourism.
ER (j, t) = a1 × Ta + a2 × Tout (j, t) + a3 × Tin (j, t) + a4 × Rf (j, t) + a5 × Ta × Rf (j, t) + a6 × Tout (j, t) × Rf (j, t) + a7 × Tin (j, t) × Rf (j, t) + a8 × Rf (j, t) ² + a9 (13)

  Note that the formulas (12) and (13), which are the calculation formulas for the two ER (j, t), are properly used depending on the obtained input conditions.

Here, the pump power consumption Pp [W] of the heat source water is expressed by the following equation (14). However, a10 to a11 are coefficients specific to the pump.
Pp (j, t) = a10 × Rf (j, t) + a11 (14)

Next, let us consider the heat supply-demand balance. That is, the relationship of the heat source machine output R [W] required for the predicted heat load demand prediction value is expressed as the following equation (15).
Thermal load demand forecast value -ΣR (j, t) = 0 (15)

In addition, an objective function which is an evaluation function for calculation by quadratic programming is obtained. From the sum of the input energy ER [W] of the heat source unit 141 of the entire air conditioning system at time t and the pump power consumption Pp [W] of the heat source water and the power unit price CD, the power cost f (x) is expressed by the following equation (16). Seek like. Then, the following equation (17) that minimizes the power cost f (x) is an objective function.
f (x) = {ΣER (j, t) + ΣPp (j, t)} × CD (16)
minf (x) = {ΣER (j, t) + ΣPp (j, t)} × CD (17)

As control variables for calculation by quadratic programming, the heat source water supply temperature Tout [K] and the heat source return temperature included in the equations of ER (j, t) expressed by the equations (12) and (13) Tin [K] and the heat source water supply flow rate Rf [m ³ / s] and the pump power consumption Pp [W] included in the equation (17).

The constraint equation for calculation by the quadratic programming method is the output R (j) [W], the water supply temperature Tout [K], and the water supply flow rate Rf [m ³ / s] in the heat source machine j. The output R (j) [W], the water supply temperature Tout [K] and the water supply flow rate Rf [m ³ / s] in the heat source machine j are the upper and lower limits as shown in the following equations (18) to (20), respectively. These ranges are constraint equations.
R (j) min ≦ R (j) ≦ R (j) max (18)
Tout (j) min ≦ Tout (j) ≦ Tout (j) max (19)
Rf (j) min ≦ Rf (j) ≦ Rf (j) max (20)

  In the above, for example, the power cost f (x) is obtained by using the quadratic programming method and the equation (17) as an objective function using the equation (15) as the constraint equation, the equations (18) to (20) as the constraint equation. The output temperatures of the cooling heat source unit 141a and the heating heat source unit 141b are determined as operating parameters so as to be minimized. Here, the term “minimum” means that the air conditioner 13 that is actually operated with respect to the amount of energy consumed when the air conditioner 13, the heat source device 141, and the external air conditioner 14 perform the rated value operation, that is, the total amount of electric power, This means minimizing the amount of energy consumed by the heat source device 141 and the external air conditioner 14.

  The control command unit 27 controls the operation of the air conditioning equipment including the air conditioner 13, the heat source device 141, and the external air conditioner 14 provided in the factory 10 based on the operation parameters of the air conditioning equipment calculated by the operation planning unit 26. By the operation control by the control command unit 27, the air conditioning removal heat amount shown in FIGS. 12 and 13 can be removed, and the temperature in the factory 10 can be kept at the set temperature.

  Next, processing in the air conditioning management device 20 will be described. FIG. 17 is a flowchart illustrating an example of a procedure of air conditioning management processing according to the first embodiment. Here, it is assumed that the arrangement information of the lighting 12, the machine 11, and the worker 15 about the factory 10, the heat generation model correspondence information for each air conditioning zone, and the building heat model have already been created by the user. First, the air conditioner characteristic data acquisition unit 22 reads the air conditioner characteristic data and stores it in the data storage unit 24 (step S11). Moreover, the weather data acquisition part 21 acquires the weather data of the day which performs air-conditioning management via a network, and memorize | stores it in the data storage part 24 (step S12). Furthermore, the production plan information acquisition unit 23 acquires the production plan information on the day when air conditioning management is performed (step S13).

  Next, the thermal load predicting unit 25 calculates the amount of heat generated in each air conditioning zone in the factory 10 at a certain time for each unit time (step S14). As described above, the heat generation amount corresponding to each air conditioning zone is used to calculate the heat generation amount of the air conditioning zone per unit time. Further, the thermal load predicting unit 25 calculates intrusion heat into each air conditioning zone in the factory 10 at a certain time for each unit time (step S15). This is calculated using the building thermal model and weather data as described above. Furthermore, the heat load predicting unit 25 calculates the air-conditioning removal heat amount in each air-conditioning zone in the factory 10 for each unit time using the calculated heat generation amount, intrusion heat, and the temperature and humidity set in the factory 10. (Step S16).

  Next, the operation planning unit 26 calculates the operation parameters of the air conditioning equipment in each air conditioning zone using the secondary planning method (step S17). For example, the temperature of the medium flowing into the heat source unit 141 and the temperature of the medium flowing out of the heat source unit 141 that can remove the amount of heat removed from the air conditioning at each time and can minimize the power consumption in the air conditioning facility. Obtain the operating parameters of the air conditioning equipment.

  And the control instruction | command part 27 controls the air conditioning equipment of the factory 10 using the calculated operation parameter of the air conditioning equipment (step S18). Thus, the air conditioning management process ends.

  The thermal load predicting unit 25 uses the production plan information as an input to predict the heat generation amount of each machine 11 from the heat generation model of the machine. However, the heat load prediction unit 25 predicts the heat generation amount considering the characteristics of the individual machines 11. Also good. FIG. 18 is a diagram illustrating an example of an operation situation when the machine according to the first embodiment is a reflow furnace, (a) is a cross-sectional view schematically showing the state of the reflow furnace, and (b) is a machine. It is a figure which shows an example of the temperature in a furnace when not considering a characteristic, and the driving | running state of a belt conveyor, (c) is a figure which shows an example of the operating temperature of a furnace and a belt conveyor when considering a mechanical characteristic. It is.

  The reflow furnace 200 includes a belt conveyor 201 that conveys products in a predetermined direction, a heating unit 202 that heats products 210 on the belt conveyor 201, and a heat insulating material 203 that is provided so as to cover the belt conveyor 201. Have. By supplying electric power to the heating unit 202, the region surrounded by the heat insulating material 203 is heated. Then, the solder placed on the product 210 is reflowed.

  As shown in FIG. 18B, when the temperature in the furnace is set to 200 ° C. by the heating unit 202, the temperature in the furnace does not suddenly reach 200 ° C. For this reason, electric power is supplied to the heating unit 202 in advance so that the temperature in the furnace becomes 200 ° C. at 9 o'clock when the production of the product 210 starts. Between 12 o'clock and 13 o'clock when the factory 10 is in the lunch break, if the power of the reflow furnace 200 is turned off, the temperature in the reflow furnace 200 decreases, but at 13 o'clock, it must be again 200 ° C and becomes 200 ° C. Is not predictable due to the ambient temperature. For this reason, the heating unit 202 was in an operating state even during the lunch break.

  On the other hand, as shown in FIG. 18 (c), when the room temperature is known, the temperature in the furnace decreases after the supply of power to the heating unit 202 is stopped, and when the temperature is raised to 200 ° C. by 13:00. It is possible to determine by calculation whether the supply of power to the unit 202 should be started. In this way, the power consumption of the factory 10 when viewed as a whole can be reduced by minimizing the supply of power to the mechanical equipment 11 during the lunch break.

In a drying furnace, a reflow furnace, or the like that performs heat conversion in a machine, the amount of heat required for operation is expressed by the following equation (21).
Necessary heat quantity of machine = {Volume of heating object [Vol] x Specific heat of heating object [j / deg · kg] x (Mechanical device target temperature-Room temperature)} x Safety factor + (Mechanical device target temperature-Room temperature) x Mechanical equipment insulation Coefficient (21)

  By acquiring the material (metal, bakelite, etc.), volume, and quantity of the heating object for each machine equipment 11 from the production plan information and entering it into the above equation (21), it cools down from the start-up through the continuous operation It is possible to estimate the amount of input energy required before operation and the amount of internal heat generation load that leaks from the apparatus. In this way, the startup pattern for each mechanical facility 11 is modeled, so that the startup pattern can be efficiently used for estimating the amount of heat generated by the mechanical facility 11.

  In the first embodiment, the thermal load prediction unit 25 uses the thermal model of the building of the factory 10 and the thermal model of the machine 11, the lighting 12 and the worker 15 arranged in the factory 10 that generates heat. The weather data, production plan information, and air conditioner characteristic data were input, and the air conditioning removal heat quantity, which is the heat quantity per unit time to be removed using the air conditioning equipment in the factory 10, was calculated over a period of one day. As a result, the amount of heat to be removed in the factory 10 can be accurately predicted, and the air conditioning equipment can be controlled based on this prediction.

  In addition, the operation planning unit 26 inputs the heat source unit 141 in the entire air conditioning system in a state where the amount of air conditioning removal heat per unit time predicted by the thermal load prediction unit 25 is equal to the output of the heat source unit 141 in the entire air conditioning system. The heat source unit for cooling 141a and the heat source unit for heating 141b are used by the quadratic programming method so that the power cost obtained by multiplying the sum of the energy and the power consumption of the heat source water pump in the entire air conditioning system by the unit price of electric power is minimized. The operating parameters of the air conditioning equipment including the output temperature were calculated. Then, the control command unit 27 controls the air conditioning equipment based on the operation parameters of the air conditioning equipment. As a result, the temperature in the factory 10 can be precisely maintained at the target temperature.

  In the conventional method of measuring the indoor temperature and detecting the deviation from the set temperature to feedback control the air conditioning equipment, it takes more than 15 minutes to reach the set temperature after the temperature is detected. It was. However, in the method according to the first embodiment, instead of feedback control, the amount of heat generated in advance is predicted and controlled so as to be removed, so the temperature in the factory 10 at each time is set to the set temperature with high accuracy. It becomes possible to set. Furthermore, conventionally, since the rated capacity of the air conditioning equipment is determined under the maximum load condition, the energy efficiency is reduced at light loads. However, in Embodiment 1, the energy efficiency can be reduced even at light loads. Absent.

Embodiment 2. FIG.
As described in the first embodiment, since the daily weather information and the production plan information are used as input data, the amount of heat removed from the air conditioning at each hour of the day is calculated using the factory heat model. Temperature and humidity control can be performed with less variation than the method. Conventionally, air conditioning control in a building such as a factory has been performed by feedback control having a delay of 15 minutes or more as described above, so temperature control is difficult, and the set temperature in the factory 10 is 23 ° C. ± 2 ° C. The set temperature was set in such a way as to give a large error range. In the second embodiment, a method for changing the set temperature in the factory 10 according to the outside air temperature will be described.

  FIG. 19 is a block diagram schematically illustrating a functional configuration of the air conditioning management device according to the second embodiment. The air conditioning management device 20 further includes an outside air processing amount prediction unit 254 in the heat load prediction unit 25. The outside air processing amount prediction unit 254 determines the amount of outside air to be introduced into the factory 10 per unit time based on the number of workers 15 existing in the factory 10 and the exhaust amount of exhaust fans that are forcibly operated. Predict. The exhaust fan that is forcibly operated is provided in the machine 11 that is operated at a high temperature. The worker 15 existing in the factory 10 and the exhaust amount by the exhaust fan that is forcibly operated are information that can be acquired from the production plan information.

  The operation planning unit 26 minimizes the power consumption of the air conditioning system in which the external air conditioner 14 and the heat source unit 141 are combined with the outside air processing amount calculated by the heat load prediction unit 25 by the secondary planning method. Solve with conditions. As a result, the operation planning unit 26 calculates the supply air temperature and supply air humidity set values of the external air conditioner 14 within the indoor environmental condition range as operation parameters of the air conditioning equipment.

  The control command unit 27 sets the supply air temperature and supply air humidity obtained by the operation planning unit 26 in the external air conditioner 14. In addition, the same code | symbol is attached | subjected to the component same as what was demonstrated in Embodiment 1, and the description is abbreviate | omitted. Further, the processing procedure of the air conditioning management apparatus according to the second embodiment is the same as that described in the first embodiment, and thus the description thereof is omitted.

  Here, an example of calculating the operation parameters of the air conditioning equipment in the operation planning unit 26 according to the second embodiment will be described. By solving the power consumption of the heat source device 141 and the external air conditioner 14 with the power consumption minimization condition by the quadratic programming method with respect to the predicted outside air processing amount of the predicted heat load demand, The set values of the supply air temperature and supply air humidity of the external air conditioner 14 can be obtained.

  First, the heat exchange amount is obtained by the heat exchanger characteristic model QH. The chilled water heat exchanger 143 of the external air conditioner 14 connects the cold water supplied from the cooling heat source device 141 a and exchanges heat with the outside air taken in by the fan 144 of the external air conditioner 14. Moreover, the hot water heat exchanger 143 of the external air conditioner 14 connects the hot water supplied from the heating heat source device 141b, and exchanges heat with the outside air taken in by the fan 144 of the external air conditioner 14.

The amount of heat QH (j, t) of the heat exchanger characteristic model at the outside air enthalpy amount ei of the heat exchanger j at time t is expressed by the following equation (22). The outside air enthalpy amount ei is expressed by the following equation (23). Where Tain is the air temperature [K] at the heat exchanger inlet, Taout is the air temperature [K] at the heat exchanger outlet, W is the water flow rate [m ³ / s], and w is the air flow rate [K]. m ³ / s], and cp is the specific heat of air, which is 1.006 J / (Kg · K).
QH (j, t) = W (j, t) × Cp (j, t) × (Tin (j, t) -Tout (j, t))
= w (j, t) × cp (j, t) × (Taout (j, t) -Tain (j, t)) (22)
ei = w (j, t) × cp (j, t) × (Taout (j, t) −Tain (j, t)) (23)

The heat exchange rate HXR of the heat exchanger is classified as follows according to the control conditions.
<When controlling temperature only>
In the case of controlling only the temperature, the heat exchange rate HXR of the heat exchanger is represented by the following equation (24). However, the dew point temperature will not be reached.
HXR × W (j, t) × Cp (j, t) × (Tin (j, t) -Tout (j, t))
= w (j, t) × cp (j, t) × (Taout (j, t) -Tain (j, t)) (24)

<When controlling temperature and humidity>
When controlling the temperature and humidity, the heat exchange rate HXR of the heat exchanger is expressed by the following equation (25). However, Denv is the air density [kg / m ³ ] of the outside air, Dsup is the density of the supply air [kg / m ³ ], Eenv is the specific enthalpy [KJ / (kg · K)] of the outside air, Esup is the specific enthalpy of supply air [KJ / (kg · K)].
HXR × W (j, t) × Cp (j, t) × (Tin (j, t) -Tout (j, t))
= w (j, t) × (Denv (t) × Eenv (t) -Dsup (j, t) × Esup (j, t)) (25)

Further, the power consumption amount Fp (t) [W] at the time t of the fan 144 is expressed by the following equation (26). However, a12 and a13 are coefficients of power consumption characteristics of the fan 144.
Fp (t) = a12 × w (j, t) + a13 (26)

Next, let us consider the heat supply-demand balance. The relationship between the heat quantity QH [W] of the heat exchanger characteristic model required for the predicted heat load demand is expressed as the following equation (27).
Thermal load demand forecast value -QH (j, t) = 0 (27)

In addition, an objective function which is an evaluation function for calculation by quadratic programming is obtained. From the heat quantity QH [W] of the heat exchanger characteristic model at time t, the power consumption Fp (t) [W] of the fan 144, and the power unit price CD, the power cost f (x) is obtained as in the following equation (28). . Then, the following equation (29) that minimizes the power cost f (x) is an objective function.
f (x) = {ΣQH (j, t) + ΣFp (j, t)} × CD (28)
minf (x) = {ΣQH (j, t) + ΣFp (j, t)} × CD (29)

As control variables for calculation by the quadratic programming method, the heat source unit return temperature Tin [K], the heat source unit water supply temperature Tout [K] included in the equation of QH (j, t) represented by the equation (22), The air flow rate w [m ³ / s] of the fan 144 and the power consumption Fp [W] of the fan 144 are obtained.

As a constraint condition equation for calculation by the quadratic programming method, heat quantity QH [W], which is an output of the heat exchanger characteristic model, heat source water supply temperature Tout [K], water flow rate W [m ³ / s], and air The flow rate becomes w [m ³ / s]. The heat quantity QH [W], the heat source water supply temperature Tout [K], the water flow rate W [m ³ / s] and the air flow rate w [m ³ / s] in the heat exchanger characteristic model are expressed by the following formula (30): As shown in 33), there are upper and lower limits, and these ranges are constraint equations.
QH (j) min ≦ QH (j) ≦ QH (j) max (30)
Tout (j) min ≦ Tout (j) ≦ Tout (j) max (31)
W (j) min ≦ W (j) ≦ W (j) max (32)
w (j) min ≦ w (j) ≦ w (j) max (33)

  The operation planning unit 26 solves the power consumption of the heat source device 141 and the external air conditioner 14 with the power consumption minimization condition by the second-order programming method with respect to the predicted outside air processing amount of the heat load demand. The set values of the supply temperature and humidity of the external air conditioner 14 within the range are obtained. Specifically, for example, equation (27) is a constraint equation, equations (30) to (33) are constraint conditions, and quadratic programming is used, and equation (29) is used as an objective function to calculate power cost f (x ) Is determined as operating parameters such that the supply air temperature and humidity of the external air conditioner 14 are minimized. The temperature and humidity can be controlled with little variation by the operation parameters thus obtained. Therefore, the energy consumption of the heat source device 141 and the external air conditioner 14 can be minimized in the range of the set temperature 21 ° C. to 25 ° C. depending on the outside air temperature and in the range of the set humidity 40% to 60% depending on the outside air humidity. .

  In the second embodiment, the outside air processing amount per unit time is predicted using the number of workers 15 in the factory 10 and the exhaust fan exhaust amount, and the predicted heat load demand is equal to the heat exchanger heat amount. Under such conditions, the air supply temperature and the air supply humidity of the external air conditioner 14 are obtained using the quadratic programming method so that the sum of the heat quantity of the heat exchanger and the power consumption of the fan is minimized. Then, the external air conditioner 14 is operated using the obtained supply air temperature and supply air humidity. As a result, the temperature and humidity can be controlled with little variation. In addition, when the outside air is introduced into the factory 10, the difference between the temperature of the air introduced into the factory 10 and the temperature inside the factory 10 before the introduction is reduced, so that the power consumed by the air conditioning management system It has the effect that can be suppressed.

Embodiment 3 FIG.
In the first embodiment, the amount of generated heat is calculated using an operation model of mechanical equipment. The amount of heat generated by mechanical equipment accounts for a large proportion of the air conditioning heat load, and the fluctuation range is also large. Therefore, in the third embodiment, a method capable of predicting the amount of heat generated by mechanical equipment with higher accuracy will be described.

  FIG. 20 is a diagram schematically showing an example of the relationship between the number of products produced per unit time and the internal heating value in the machine equipment in the factory according to the third embodiment. Here, internal calorific values A, B, and C when the number of productions per unit time are a, b, and c are calculated in advance, and a curve L1 indicating the relationship of the internal calorific value with respect to the production number is calculated from these data. It was created and is shown as a solid line in the figure. Note that a curve L2 indicated by a dotted line in the figure indicates the internal heat generation amount with respect to the actual number of production per unit time. Curves L1 and L2 are production amount-heat generation amount correspondence information. In the curve L1, when the number of produced units per unit time is in the range of 0 to a, the calorific value is shown as a straight line that monotonously increases from 0 to A, in the range of a to b is a constant value A, and in the range of b to c Is a constant value B, and is a constant value C in the range after c. The curve L1 approximates the actual curve L2.

  The heat generation amount prediction unit 251 calculates the internal heat generation amount of the mechanical equipment 11 using information as shown in FIG. 20 from the number of production per hour obtained from the production plan information regarding the generated heat of the mechanical equipment 11. In the above description, the number of production per unit time is used, but it may be the operating rate of the machine. Further, in FIG. 20, the curve L1 is created by measuring three points, but by increasing the number of points to be measured, the degree of deviation of the curve L1 from the actual curve L2 is reduced, so that more precise It is possible to predict the heat generation amount of the mechanical equipment 11.

  In the third embodiment, a correlation between the number of units produced per unit time or the operation rate of the machine and the calorific value of the machine equipment 11 is obtained in advance, and from this relationship, the number of units produced per hour obtained from the production plan information or The calorific value corresponding to the machine operation rate was obtained. As a result, the amount of heat generated by the mechanical equipment 11 can be estimated more precisely.

Embodiment 4 FIG.
In the fourth embodiment, an air conditioning management system capable of generating a correlation between the number of units produced per unit time or the operation rate of a machine and the amount of heat generated by machine equipment will be described.

  FIG. 21 is a diagram schematically illustrating an example of a configuration of an air conditioning management system according to the fourth embodiment. In the configuration of the first embodiment, the air-conditioning management system has the production amount indicating the correspondence between the production amount per unit time and the heat generation amount of the mechanical equipment 11 -the production amount for acquiring the heat generation correspondence information from each mechanical equipment 11- A calorific value correspondence information acquisition unit 255 is further provided. The production amount-heat generation amount correspondence information acquisition unit 255 stores the acquired production amount-heat generation amount correspondence information in the data storage unit 24 in association with the operation model of the corresponding mechanical equipment 11. In addition, the same code | symbol is attached | subjected to the component same as the component demonstrated in Embodiment 1, and the description is abbreviate | omitted.

  FIG. 22 is a diagram illustrating an example of a configuration of mechanical equipment according to the fourth embodiment. As shown in this figure, the machine equipment 11 includes a machine 111 to be controlled, a control device 112 that controls the machine 111, a display 113 that displays a control state of the control device 112, and the machine equipment 11. And a power monitor 114 that is a power consumption measuring device that monitors the power consumption in the network is connected via a communication cable 115. The power monitor 114 is connected to an air conditioning management system (not shown) via a communication cable.

  FIG. 23 is a diagram illustrating an example of the production amount-heat generation amount correspondence information. The information shown in FIG. 23 acquired by the power monitor is acquired by the production amount-heat generation amount correspondence information acquisition unit 255 of the air conditioning management system. Since the power consumption of each mechanical equipment 11 is equal to the heat generation amount, the heat generation amount prediction unit 251 of the air conditioning management device 20 acquires a finer heat generation amount than in the case of the third embodiment using this relationship. Can do.

  In the fourth embodiment, the power monitor 114 is provided in the mechanical equipment 11 in the factory 10 and the relationship between the number of units produced per unit time or the operation rate and the power consumption is accumulated as production quantity-heat generation correspondence information. And this was acquired with the air-conditioning management apparatus 20, and it was made to use when calculating | requiring the calorific value of the mechanical installation 11. FIG. As a result, a more accurate value can be obtained for the calorific value of each mechanical facility 11 than in the case of the third embodiment, and air conditioning management in the factory 10 can be performed more accurately.

  In the above description, the case where the production amount-heat generation amount correspondence information acquisition unit 255 is attached to the configuration of the first embodiment has been described. However, the production amount / heat generation amount correspondence information acquisition unit 255 may be attached to the configuration of the second embodiment.

Embodiment 5. FIG.
In the fifth embodiment, a case will be described in which the operation state of the air conditioning management system is recorded periodically and compared with the normal operation state to determine whether there is an abnormality in the air conditioning management system.

  FIG. 24 is a diagram schematically illustrating an example of a configuration of an air conditioning management system according to the fifth embodiment. The air conditioning management system further includes an operation state acquisition unit 256, an operation state storage unit 257, and a preventive maintenance unit 258 in the configuration of the first embodiment.

  The operation state acquisition unit 256 records operation state values including operation data of facility operation information corresponding to a production plan, an air conditioning unit corresponding to a production amount, and estimated information obtained from each operation model at certain time intervals. Examples of the facility operation information include a heat source device 141, an air conditioning facility, and a mechanical facility 11. The operation data can include power consumption, the number of activations per unit time, equipment process values, and the like. As the estimation information, device operation efficiency, generated heat amount and the like can be mentioned. The operation state storage unit 257 stores the operation state value acquired by the operation state acquisition unit 256.

  The preventive maintenance unit 258 compares an operation state value serving as a reference during normal operation with the acquired operation state value, and determines whether there is an abnormality. Specifically, the preventive maintenance unit 258 notifies the user of a warning message when the deviation amount of the operation state value to be determined from the reference operation state value is outside a preset threshold value. Perform processing to do. The preventive maintenance process does not need to be performed every time, and may be performed periodically such as once a day or once a week. Moreover, it is desirable that the operation data by the operation state acquisition unit 256 is shorter than the prediction period of the air conditioning heat load by the heat load prediction unit 25.

  The power consumption of the mechanical equipment 11 tends to increase as the mechanical equipment 11 continues to be used. For this reason, when the amount of deviation exceeds a preset value, it indicates that the mechanical equipment 11 is near the end of its life, so a notification is given to the user. Then, the user performs processing such as replacement of parts of the mechanical equipment 11 based on the notification. In addition, the same code | symbol is attached | subjected to the component same as the component demonstrated in Embodiment 1, and the description is abbreviate | omitted.

  In the fifth embodiment, the operation state value in the air conditioning management system is recorded, and it is determined whether there is an abnormality in comparison with the reference operation state value for each predetermined period. As a result, the determination result can be used for preventive maintenance of equipment failure and deterioration accompanying secular change.

  As described above, the air conditioning management system according to the present invention is useful for air conditioning management in a factory that produces products.

  10 factories, 10A clean room, 10B assembly room, 11 mechanical equipment, 12 lighting equipment, 13 air conditioner, 14 air conditioner, 14A, 14B, 14C air conditioner, 15 workers, 20 air conditioning management device, 21 meteorological data acquisition unit, 22 air conditioner characteristic data acquisition unit, 23 production plan information acquisition unit, 24 data storage unit, 25 thermal load prediction unit, 26 operation planning unit, 27 control command unit, 111 machine, 112 control device, 113 display, 114 power monitor , 115 Communication cable, 141 Heat source machine, 141a Heat source machine for cooling, 141b Heat source machine for heating, 142 Pump, 143 Heat exchanger, 144 Fan, 200 Reflow furnace, 201 Belt conveyor, 202 Heating unit, 203 Heat insulation material, 210 Products 251 Heat generation amount prediction unit 252 Intrusion heat prediction unit 253 Removal heat amount prediction Unit, 254 outside air processing amount prediction unit, 255 production amount-heat generation amount correspondence information acquisition unit, 256 operation state acquisition unit, 257 operation state storage unit, 258 preventive maintenance unit, 700 air conditioning system control device, 701 air conditioner operation data acquisition unit 702 Meteorological data acquisition unit 703 Parameter learning unit 703a Building model 704 Thermal load prediction unit 705 Schedule creation unit 706 Operation schedule output unit 800 Secondary planning problem calculation device 801 Variable storage unit 802 Initialization unit , 803 Mismatch amount calculation means, 804 Correction amount calculation means, 805 Correction amount storage means, 806 Fixed variable setting means, 807 Variable correction means, 810 Repeat means.

In order to achieve the above object, an air conditioning management device according to the present invention includes an operation model of a heating element that is a function of the amount of heat generated by a heating element in a factory, and an operation state of the heating element defined by production plan information, Unit using a first process for predicting the amount of heat generated per unit time by using a heat function of a building including a heat transfer coefficient and a heat capacity of the building constituting the factory, and meteorological data. The second process for predicting the amount of intrusion heat per hour, the temperature and humidity set in the factory, the generated heat amount and the intrusion heat amount per unit time, and the unit time to be removed by the air conditioning equipment A heat load predicting unit that executes a third process for predicting the amount of heat to be removed, and an operation plan for creating an operation plan for the air conditioning equipment for removing the amount of heat removed per unit time by the air conditioning equipment per unit time And the operation meter Wherein the control command section for controlling the operation of air conditioning equipment, wherein the operation plan unit has a quantity of heat removed per unit time, the temperature and humidity are set in said plant the air conditioning operation model according to based on the bets, the energy consumption in the entire air conditioning plant erected the operation plan of removing the quantity of heat removed per unit time for minimization, the production plan information, the number of mechanical equipment to run in said plant , Characterized in that it includes operating time .

The air conditioner characteristic data acquisition unit 22 reads air conditioner characteristic data that is characteristic information of the air conditioner used in the factory 10 to be controlled. The air conditioner characteristic data is information including the relationship between the power consumption of each air conditioner and the amount of heat supplied. In addition, when it is necessary to calculate the amount of heat supplied by the air conditioner, that is, the amount of heat removed by the air conditioner, the air conditioner characteristic data includes the operating frequency, evaporation temperature, condensation temperature, supply heat amount and power consumption of each outdoor unit. Including the relationship.

Note that the calculation formula of the input energy ER [W] can be expressed not by the equation (12) but also by the regression equation of the following equation (13). However, a1 to a9 are coefficients of the characteristic formula of the heat source unit, and can be calculated by, for example, an air conditioning facility simulation tool (LCEM tool) provided by the Ministry of Land, Infrastructure, Transport and Tourism.
ER (j, t) = a1 × Ta + a2 × Tout (j, t) + a3 × Tin (j, t) + a4 × Rf (j, t) + a5 × Ta × Rf (j, t) + a6 × Tout (j, t) × Rf (j, t) + a7 × Tin (j, t) × Rf (j, t) + a8 × Rf (j, t) ² + a9 (13)

In the above, for example (15) and constraint from (18) to (20) as a constraint condition expression using the quadratic programming (17) Power costs f (x) as the objective function of formula The output temperatures of the cooling heat source unit 141a and the heating heat source unit 141b are determined as operating parameters so as to be minimized. Here, the term “minimum” means that the air conditioner 13 that is actually operated with respect to the amount of energy consumed when the air conditioner 13, the heat source device 141, and the external air conditioner 14 perform the rated value operation, that is, the total amount of electric power, This means minimizing the amount of energy consumed by the heat source device 141 and the external air conditioner 14.

In addition, the operation planning unit 26 inputs the heat source unit 141 in the entire air conditioning system in a state where the amount of air conditioning removal heat per unit time predicted by the thermal load prediction unit 25 is equal to the output of the heat source unit 141 in the entire air conditioning system. energy and, as the power cost by multiplying the electric energy unit price to the sum of the heat source water pump power consumption in the entire air conditioning system is minimized, heating heat source device 141b and the cooling heat source apparatus 141a using a quadratic programming The operating parameters of the air conditioning equipment including the output temperature were calculated. Then, the control command unit 27 controls the air conditioning equipment based on the operation parameters of the air conditioning equipment. As a result, the temperature in the factory 10 can be precisely maintained at the target temperature.

The operation planning unit 26 solves the power consumption of the heat source device 141 and the external air conditioner 14 with the power consumption minimization condition by the second-order programming method with respect to the predicted outside air processing amount of the heat load demand. The set values of the supply temperature and humidity of the external air conditioner 14 within the range are obtained. Specifically, for example, the (27) equation constraint equation, as from (30) (33) a constraint condition expression using the quadratic programming (29) the power equation as an objective function cost f (x ) Is determined as operating parameters such that the supply air temperature and humidity of the external air conditioner 14 are minimized. The temperature and humidity can be controlled with little variation by the operation parameters thus obtained. Therefore, the energy consumption of the heat source device 141 and the external air conditioner 14 can be minimized in the range of the set temperature 21 ° C. to 25 ° C. depending on the outside air temperature and in the range of the set humidity 40% to 60% depending on the outside air humidity. .

In the second embodiment, the outside air processing amount per unit time is predicted using the number of workers 15 in the factory 10 and the exhaust fan exhaust amount, and the predicted heat load demand is equal to the heat exchanger heat amount. Under such conditions, the air supply temperature and the air supply humidity of the external air conditioner 14 are obtained using the quadratic programming method so that the sum of the heat quantity of the heat exchanger and the power consumption of the fan is minimized. Then, the external air conditioner 14 is operated using the obtained supply air temperature and supply air humidity. This has the effect that temperature and humidity can be controlled with little variation . In addition, when the outside air is introduced into the factory 10, the difference between the temperature of the air introduced into the factory 10 and the temperature inside the factory 10 before the introduction is reduced, so that the power consumed by the air conditioning management system It has the effect that can be suppressed.

In order to achieve the above object, an air conditioning management device according to the present invention includes an operation model of a heating element that is a function of the amount of heat generated by a heating element in a factory, and an operation state of the heating element defined by production plan information, Unit using a first process for predicting the amount of heat generated per unit time by using a heat function of a building including a heat transfer coefficient and a heat capacity of the building constituting the factory, and meteorological data. The second process for predicting the amount of intrusion heat per hour, the temperature and humidity set in the factory, the generated heat amount and the intrusion heat amount per unit time, and the unit time to be removed by the air conditioning equipment A heat load predicting unit that executes a third process for predicting the amount of heat to be removed, and an operation plan for creating an operation plan for the air conditioning equipment for removing the amount of heat removed per unit time by the air conditioning equipment per unit time And the operation meter Wherein and a control instruction unit for controlling the operation of air conditioning equipment, and a display unit, the following, the operation plan unit has a quantity of heat removed per unit time, the temperature and humidity are set in said plant conditioning Based on the operation model of the facility, the operation plan for removing the amount of heat removed per unit time that minimizes the energy consumption in the entire air conditioning facility is established, and the production plan information is a machine that is operated in the factory. the number of facilities, viewed including the time to run, the heat load prediction unit, the heating value of the heating element per unit time, and the penetration amount of heat, and having a function of displaying the graph on the display unit .

Claims (11)

An air conditioner having facilities including operating mechanical equipment, lighting equipment, and air conditioning equipment, and a factory where workers enter and leave the room, and an air conditioning management device that controls the air conditioning equipment so that the inside of the factory has a target temperature. In the management system,
The air conditioning management device
A heat load that predicts, every unit time, a heat load that includes the amount of heat generated in the factory that is calculated using production plan information and the amount of heat that enters the factory that is calculated using weather data. A predictor;
An operation planning unit that creates an operation plan of the air conditioning equipment on a unit time basis based on the heat load;
A control command unit for controlling the operation of the air conditioning equipment according to the operation plan;
With
The operation planning unit uses the secondary planning method based on the temperature and humidity set in the factory and the operation model of the air conditioning equipment for the heat load. An air conditioning management system characterized in that the operation plan is made so that energy is minimized with respect to the total energy consumption when the individual air conditioning facilities are rated-operated. The factory is divided into a plurality of air conditioning zones,
The thermal load prediction unit predicts the thermal load per unit time for the air conditioning zones,
The air conditioning management system according to claim 1, wherein the operation planning unit creates the operation plan for each unit time for each air conditioning zone.   The thermal load prediction unit calculates the calorific value of the mechanical equipment, the lighting equipment, and the worker created according to the arrangement information of the mechanical equipment, the lighting equipment, and the worker in the air conditioning zone. Using the heat generation model correspondence information for each air conditioning zone that associates the model with the air conditioning zone, the amount of generated heat in each air conditioning zone per unit time is calculated, and the amount of heat entering the inside from the outside of the factory is calculated. The air conditioning management system according to claim 2, wherein the intrusion heat amount is calculated using a thermal model of the building to be calculated. The air conditioning management device further includes a display unit,
The thermal load prediction unit has a function of displaying the mechanical equipment per unit time, the lighting equipment, the calorific value of the worker, and the intrusion heat amount on the display unit for each air conditioning zone. The air conditioning management system according to claim 3. The air conditioning equipment is set by bringing a heat source for cooling that cools the first medium, a heat source for heating that heats the second medium, and air outside the factory in contact with the first medium or the second medium. An external air conditioner to be introduced into the factory at a high temperature and humidity,
The operation planning unit is configured so that the heat load per unit time predicted by the heat load prediction unit is equal to the outputs of the cooling heat source unit and the heating heat source unit, and the cooling heat source unit and the heating unit. The cooling heat source using quadratic programming so as to minimize the sum of the input energy of the heat source machine and the power consumption of the pump connected to the cooling heat source machine and the heating heat source machine, respectively. The air-conditioning management system according to claim 2, wherein an output temperature of each of the air-conditioning zones is determined for each air-conditioning zone. The thermal load prediction unit further has a function of predicting the outside air processing amount to be introduced into the factory every other time,
The operation planning unit is connected to the cooling heat source unit and the heating amount heat source unit, with respect to the predicted outside air processing amount, the thermal load for each unit time predicted by the thermal load prediction unit. A quadratic programming method so as to minimize the sum of the heat quantity of the heat exchanger and the power consumption of the fan that blows air outside the factory into the factory in a state equal to the heat quantity in the heat exchanger. The air conditioning management system according to claim 5, wherein an air supply temperature and an air supply humidity of the external air conditioner are obtained using   The air conditioning management system according to claim 3, wherein the heat generation model correspondence information further includes the number of workers present in each air conditioning zone from the production plan information. The operation model of the machine facility is production amount-heat generation amount correspondence information that defines a relationship between an operation rate of the machine facility or a production number per unit time and a heat generation amount,
The thermal load prediction unit obtains the heat generation amount of the mechanical equipment corresponding to the operation rate of the mechanical equipment or the number of production per unit time in the production plan information from the production amount-heat generation amount correspondence information. The air conditioning management system according to claim 3, wherein It further comprises a power consumption measuring device for measuring the power consumption of the mechanical equipment,
The thermal load prediction unit further has a function of acquiring a calorific value of the mechanical equipment from the power consumption measuring device and acquiring the operating rate or the number of production per unit time from the production plan information. The air conditioning management system according to claim 8.   The thermal load predicting unit obtains the material, volume and quantity of the object to be heated from the production plan information when the mechanical equipment is a machine accompanied by heat treatment, and performs the continuous operation from the startup of the mechanical equipment. The heat generation amount of the mechanical equipment is predicted by estimating the amount of electric energy required until the cool-down operation and the amount of heat leaked from the mechanical equipment. Air conditioning management system. The air conditioning management device
An operation state acquisition unit for acquiring an operation state value including power consumption or heat generation amount of the facility;
The acquired operation state value is compared with a reference operation state value to determine whether or not the threshold value is deviated, and a preventive maintenance unit that notifies the user when there is a deviation,
The air conditioning management system according to claim 2, further comprising:

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