WO2015151363A1 - Système de climatisation et procédé de commande pour équipement de climatisation - Google Patents

Système de climatisation et procédé de commande pour équipement de climatisation Download PDF

Info

Publication number
WO2015151363A1
WO2015151363A1 PCT/JP2014/084311 JP2014084311W WO2015151363A1 WO 2015151363 A1 WO2015151363 A1 WO 2015151363A1 JP 2014084311 W JP2014084311 W JP 2014084311W WO 2015151363 A1 WO2015151363 A1 WO 2015151363A1
Authority
WO
WIPO (PCT)
Prior art keywords
ventilation
schedule
air conditioning
unit
concentration
Prior art date
Application number
PCT/JP2014/084311
Other languages
English (en)
Japanese (ja)
Inventor
隆也 山本
義隆 宇野
理 中島
昌江 澤田
Original Assignee
三菱電機株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 三菱電機株式会社 filed Critical 三菱電機株式会社
Priority to JP2015534703A priority Critical patent/JPWO2015151363A1/ja
Publication of WO2015151363A1 publication Critical patent/WO2015151363A1/fr

Links

Images

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
    • F24F11/46—Improving electric energy efficiency or saving
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements
    • F24F11/50—Control or safety arrangements characterised by user interfaces or communication
    • F24F11/61—Control or safety arrangements characterised by user interfaces or communication using timers
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/20—Humidity
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F2110/00—Control inputs relating to air properties
    • F24F2110/50—Air quality properties
    • F24F2110/65—Concentration of specific substances or contaminants
    • F24F2110/70—Carbon dioxide
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B30/00—Energy efficient heating, ventilation or air conditioning [HVAC]
    • Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating

Definitions

  • the present invention relates to an air conditioning system and a method for controlling an air conditioning facility.
  • a conventional air conditioning system there is one that includes an air conditioning facility having an air conditioner and a ventilation device, and an air conditioning facility control system that controls the operation of the air conditioning facility.
  • an air conditioning system for example, the indoor CO 2 concentration is measured, and outside air is supplied indoors so that the measured value is equal to or less than a reference value (see, for example, Patent Document 1).
  • a reference value see, for example, Patent Document 1
  • the outside air temperature and the room temperature are measured, and the outside air is supplied to the room according to the measured values and the set temperature of the air conditioner (for example, Patent Document 2). See).
  • outside air is supplied into the room according to the result of comparing the room temperature and the intermediate temperature in the comfortable temperature range (see, for example, Patent Document 3).
  • the amount of outside air supplied to the room that is, the ventilation amount is determined according to the result of comparing the outside air temperature and the room temperature (see, for example, Patent Document 4). .
  • JP 2010-71489 A (paragraph [0012] to paragraph [0042]) Japanese Patent No. 3028065 (paragraph [0031] to paragraph [0048]) International Publication No. 2010/016100 (paragraph [0021] to paragraph [0042]) JP 2005-147563 A (paragraph [0033] to paragraph [0073])
  • Patent Literature 1 to Patent Literature 4 the CO 2 concentration is reduced to a reference value or less while achieving energy saving of the air conditioning equipment, and the outside air cooling / heating is performed in order to save energy of the air conditioning equipment, It is difficult to achieve both. In other words, in order to reduce the CO 2 concentration below the reference value while saving energy in the air conditioning equipment, it is necessary to suppress ventilation. On the other hand, in order to perform outdoor air cooling and heating in order to save energy in the air conditioning equipment, Since ventilation needs to be promoted, it is difficult to balance them. For this reason, there is a problem that the energy saving performance of the air conditioning equipment as a whole is insufficient.
  • the ventilation amount is determined at the time of control, that is, energy saving at that time is achieved, so that the energy saving performance in a long period such as one day is insufficient. There was a problem.
  • the present invention has been made against the background of the above problems, and provides an air conditioning system with improved energy saving performance as an entire air conditioning facility. Further, an air conditioning system with improved energy saving performance over a long period such as one day is obtained. Moreover, the control method of the air conditioning equipment used for such an air conditioning system is obtained.
  • An air conditioning system includes an air conditioner having an air conditioner and a ventilator, and an air conditioner control system that controls the operation of the air conditioner. and the CO 2 concentration predicting section for predicting the CO 2 concentration, and the air conditioning load prediction unit for predicting a load of the air conditioner in the time horizon, and ventilation scheduling section that generates a schedule for ventilation operation of the ventilator in the time horizon, planning the period, and a control unit for controlling the ventilation operation of the ventilator based on the schedule, the ventilation scheduling unit, the CO 2 concentration expected in the CO 2 concentration prediction unit of the time horizon of at least a portion
  • a plurality of schedule candidates that are maintained in a state not exceeding the reference value over a period of time are generated, and the room temperature is selected from the plurality of schedule candidates.
  • a schedule candidate that uses a relatively small amount of power consumption or electricity charge of the air-conditioning equipment when is maintained within the reference temperature range is adopted as the schedule.
  • the ventilation scheduling unit generates a plurality of schedule candidates in which the CO 2 concentration is maintained in a state that does not exceed the reference value over at least a part of the planning target period, Among the schedule candidates, a schedule candidate having a relatively small power consumption or electricity rate of the air conditioning equipment when the room temperature is maintained within the reference temperature range is adopted as a schedule of the ventilation operation of the ventilator. Therefore, the method comprising the following reference value of CO 2 concentration while reducing the energy efficiency of the air conditioning equipment, and carrying out the outside air cooling and heating to achieve energy-saving air conditioning, is both energy saving of the whole air-conditioning equipment Be improved. In addition, energy saving performance for a long period such as one day is improved.
  • 1 is an overall configuration diagram of an example of an air conditioning system according to Embodiment 1 of the present invention.
  • 1 is an overall configuration diagram of an example of an air conditioning system according to Embodiment 1 of the present invention. It is a functional block diagram of the air-conditioning equipment control system of the air-conditioning system which concerns on Embodiment 1 of this invention. It is a functional block diagram of the optimal ventilation scheduling part of the air conditioning system which concerns on Embodiment 1 of this invention. It is the whole block diagram of the modification of the air conditioning system which concerns on Embodiment 1 of this invention. It is a functional block diagram of the optimal ventilation scheduling part of the air conditioning system which concerns on Embodiment 2 of this invention.
  • Embodiment 1 of this invention It is a functional block diagram of the air-conditioning equipment control system of the air-conditioning system which concerns on Embodiment 3 of this invention. It is a graph which shows the ventilation schedule of the summer in Embodiment 1 of this invention. It is a graph which shows the power consumption of the summer in Embodiment 1 of this invention. It is a graph which shows the ventilation schedule of the intermediate period in Embodiment 1 of this invention. It is a graph which shows the power consumption of the interim period in Embodiment 1 of this invention. It is a graph which shows the ventilation schedule of the winter season in Embodiment 1 of this invention. It is a graph which shows the power consumption of the winter season in Embodiment 1 of this invention. It is a schematic diagram which shows the execution conditions of the condition setting part 11 in Embodiment 1 of this invention. It is a graph which shows the adjacent ventilation schedule in Embodiment 1 of this invention.
  • FIG. 1 The air conditioning system according to Embodiment 1 will be described below. ⁇ Overall configuration> First, the whole structure of the air conditioning system 100 is demonstrated using FIG.1 and FIG.2.
  • FIG.1 and FIG.2 is a whole block diagram of an example of the air conditioning system which concerns on Embodiment 1 of this invention.
  • the air conditioning system 100 includes an air conditioning equipment control system 1, an air conditioner 2, and a ventilator 3.
  • the air conditioning equipment control system 1 includes an air conditioning controller 1a and a network 1n.
  • the air conditioning controller 1a, the air conditioner 2, and the ventilator 3 are connected via the network 1n, and the air conditioner controller 1a controls the air conditioner 2 and the ventilator 3.
  • FIG. 1 shows a case where the air conditioning controller 1a, the air conditioner 2, and the ventilation device 3 are each one, a plurality of each may be provided.
  • the network 1n connects devices in a state where a plurality of types of networks are mixed according to the type of cable, protocol, and the like.
  • the network 1n includes a dedicated network for measuring and controlling air conditioning equipment (air conditioner 2 and ventilator 3), LAN, and individual dedicated lines that are different for each of the air conditioning equipment (air conditioner 2 and ventilator 3). You may do it.
  • the air conditioner 2 has a heat source unit 2a and an indoor unit 2b.
  • the heat source device 2a cools or heats a heat medium such as a refrigerant and water.
  • the indoor unit 2b performs heat exchange between the heat medium and indoor air to adjust the indoor temperature.
  • a typical example of the air conditioner 2 is a multi air conditioner for buildings. In a building multi-air conditioner, a plurality of indoor units 2b are connected to one heat source unit 2a.
  • the ventilation device 3 includes a fan 3a and a heat exchange unit 3b.
  • the ventilation device 3 has a function of taking air outside the building into the room and discharging the air outside the building.
  • the fan 3a is a device for generating an air flow for that purpose.
  • a fan for taking air outside the building into the room and a fan for discharging indoor air outside the building are separate.
  • the heat exchange unit 3b is a device for exchanging heat between air taken in from outside the building and air discharged from the room to the outside of the building.
  • the structure which can be bypassed without passing through the heat exchange unit 3b according to the temperature of the air outside a building, the temperature of indoor air, etc. may be sufficient.
  • you may comprise so that it may bypass without passing through the heat exchange unit 3b according to humidity, enthalpy, etc. not only in temperature.
  • the ventilator 3 may be configured not to include the heat exchange unit 3b.
  • the air conditioning equipment control system 1 may include an air conditioning controller 1a and an air conditioning control computer 1b connected via a network 1o. Moreover, one or both of the air conditioning controller 1a and the air conditioner 2 and the ventilation device 3 may be connected via the device connection controller 1c.
  • the network 1o is, for example, a LAN or a telephone line.
  • the air-conditioning control computer 1b may be installed inside a building to be air-conditioned, or may be installed in a management center or the like that manages a plurality of buildings within a site or in a remote place.
  • FIG. 3 is a functional block diagram of the air conditioning equipment control system of the air conditioning system according to Embodiment 1 of the present invention.
  • the air conditioning equipment control system 1 includes a condition setting unit 11, an optimal ventilation scheduling unit 12, an input / output unit 13, a measurement control unit 14, and a storage unit 15.
  • the functions of the respective units are performed by the air conditioning controller 1a.
  • the functions of the respective units are carried by the air conditioning controller 1a and the air conditioning control computer 1b.
  • the condition setting unit 11 has a function of setting an execution condition for generating an optimal ventilation schedule.
  • Specific execution conditions to be set for example, best plan period for obtaining the ventilation schedule, the upper limit value of the CO 2 concentration, time zone providing an upper limit to the CO 2 concentration, the time period for controlling the room temperature to the set temperature, These are a reference temperature for determining whether or not to perform outdoor air cooling and heating, an optimization end determination condition, and the like.
  • the air conditioning equipment control system 1 has a processor for performing calculations, and the function of the condition setting unit 11 is realized by the processor.
  • FIG. 11 is a schematic diagram illustrating execution conditions of the condition setting unit 11 according to Embodiment 1 of the present invention.
  • the planning target period for obtaining the ventilation schedule is, for example, 24 hours from 0:00 to 24:00.
  • the time period for setting the upper limit value for the CO 2 concentration is from 6 o'clock just before the office worker leaves the office to 22:00 when the office worker leaves the office.
  • the time period during which the room temperature is controlled to the set temperature is from 7 o'clock when the office worker leaves the office until 22:00 when the office worker leaves the office.
  • execution conditions are only examples, and the execution conditions are set in consideration of the working status of the actual office worker, taking into account, for example, weekdays, Saturdays, Sundays, public holidays, and once-a-week scheduled leave dates. It only has to be done.
  • the upper limit value of the CO 2 concentration is, for example, 1000 ppm, which is a reference value determined by laws and regulations.
  • the set temperature is a temperature set by a building manager or office worker to maintain a comfortable office environment.
  • the set temperature in summer is, for example, 27 ° C. during cooling operation, and the set temperature in winter is, for example, 20 ° C. during heating operation.
  • the set temperature is a condition that is set in accordance with an air conditioning operation policy or the like in each of the target buildings.
  • the set temperature is not changed in order to realize energy saving.
  • the setting temperature is for independent of the change in CO 2 concentration, is not correlation between the set temperature and the CO 2 concentration.
  • the optimum ventilation scheduling unit 12 has a function of generating a ventilation schedule that reduces the evaluation function value in the planning target period according to the conditions set by the condition setting unit 11.
  • the optimal ventilation scheduling unit 12 includes an initial solution generation unit 21, an adjacent ventilation schedule generation unit 22, a CO 2 concentration prediction unit 23, an air conditioning load prediction unit 24, an adjacent ventilation schedule evaluation unit 25, and an optimal ventilation schedule candidate update. Unit 26 and end determination unit 27.
  • the air conditioning equipment control system 1 has a processor for performing calculations, and the functions of the respective units are realized by the processor. The function of each part of the optimal ventilation scheduling part 12 will be described in detail later.
  • the initial solution generation unit 21, the adjacent ventilation schedule generation unit 22, the adjacent ventilation schedule evaluation unit 25, and the optimum ventilation schedule candidate update unit 26 each correspond to a part of the “ventilation schedule generation unit” in the present invention. To do.
  • the input / output unit 13 has a function of accepting an input made by a user such as an administrator, writing information in the storage unit 15, reading out information stored in the storage unit 15, and displaying the information to the user.
  • the information that the input / output unit 13 writes in the storage unit 15 includes, for example, management information of the air conditioning system 100, an optimization execution condition output to the condition setting unit 11, and the like.
  • the information that the input / output unit 13 reads from the storage unit 15 includes, for example, an input result, an optimized ventilation schedule, an operating state of the air conditioner 2 and the ventilation device 3, and the like.
  • the input / output unit 13 includes, for example, an input unit 31 such as a keyboard, a mouse, a touch panel, and a switch, and a display unit 32 such as a display.
  • the measurement control unit 14 collects operation data from the air conditioner 2 and the ventilator 3 and writes control data to the storage unit 15 and a control command to one or both of the air conditioner 2 and the ventilator 3. Is read out from the storage unit 15 and transmitted.
  • the air conditioning system 100 may include various sensors such as a temperature sensor, a humidity sensor, and a CO 2 concentration sensor, and the measurement unit 41 may collect measurement data from these sensors and write it in the storage unit 15.
  • the storage unit 15 has a function of storing information referred to by the condition setting unit 11, the optimal ventilation scheduling unit 12, the input / output unit 13, and the measurement control unit 14.
  • the air conditioning equipment control system 1 includes a storage device such as a memory and a hard disk, and the function of the storage unit 15 is realized by the storage device.
  • FIG. 4 is a functional block diagram of the optimum ventilation scheduling unit of the air conditioning system according to Embodiment 1 of the present invention. First, an outline of the function of each part of the optimum ventilation scheduling unit 12 will be described.
  • the initial solution generation unit 21 has a function of generating an initial solution of the optimal ventilation schedule candidate and calculating an evaluation function value of the initial solution.
  • the adjacent ventilation schedule generation unit 22 has a function of generating an adjacent ventilation schedule in which a part of the schedule of the optimal ventilation schedule candidate is changed.
  • the CO 2 concentration prediction unit 23 has a function of predicting a temporal change in the CO 2 concentration in the planning target period when ventilation is performed according to the adjacent ventilation schedule.
  • the air conditioning load predicting unit 24 has a function of predicting the time change of the air conditioning load in the planning target period when ventilation is performed according to the adjacent ventilation schedule.
  • the air conditioning load refers to the amount of heat processed by the air conditioner 2 in order to maintain the room at a reference temperature, for example, 27 ° C. during cooling operation.
  • the air conditioning load includes the amount of heat generated by ventilation.
  • Adjacent ventilation schedule evaluation unit 25 CO 2 concentration and temperature of the chamber which is predicted by the CO 2 concentration prediction unit 23, thereby determining whether or not the setting constraint condition is satisfied by the condition setting unit 11, the adjacent ventilation schedule It has a function of calculating the evaluation function value.
  • the optimal ventilation schedule candidate update unit 26 compares the evaluation function value of the optimal ventilation schedule candidate with the evaluation function value of the adjacent ventilation schedule, and determines whether or not to update the optimal ventilation schedule candidate to the adjacent ventilation schedule. In addition, it has a function of updating the optimal ventilation schedule candidate according to the determination result.
  • the end determination unit 27 has a function of determining whether or not to end the optimization of the ventilation schedule.
  • the optimization of the ventilation schedule performed by the optimal ventilation scheduling unit 12 is executed at the frequency of once a day and on the previous day, the planning target period is 24 hours on the next day, and the time increment is , 30 minutes is explained. That is, for example, the optimal ventilation scheduling unit 12 performs the following day at 0:00 to 0:30, 0:30 to 1: 0, 10:00 to 1:30, ..., 23:30 to 24:00.
  • the control command to the ventilator 3, that is, the ventilation schedule is determined at 22:00 every day.
  • the optimal ventilation scheduling unit 12 determines a control command for each.
  • the air conditioning system 100 is limited to the case where the optimization of the ventilation schedule is executed once a day and on the previous day, the planning target period is 24 hours the next day, and the time increment is 30 minutes. Not.
  • the optimization of the ventilation schedule may be performed at a frequency of once per hour, the planning target period may be the next two hours, and the time increment may be 15 minutes.
  • control command to the ventilator 3 is a discrete value in four stages (strong, medium, weak, stop) is described.
  • the control command to the ventilator 3 is not limited to the case of four levels of discrete values, but is a discrete value other than the four levels according to the type of the ventilator 3, for example, 10 levels of discrete values. Alternatively, it may be a discrete value of two stages of ON and OFF.
  • the initial solution generation unit 21 reads out the optimization execution condition from the storage unit 15, executes a calculation for generating the initial solution by the processor, and stores the generated initial solution in the storage unit 15 as the optimal ventilation schedule candidate.
  • Examples of the initial solution include a default ventilation schedule set by a user such as an administrator in the input / output unit 13, an optimal ventilation schedule calculated on the previous day, a ventilation schedule actually used on the current day or in the past, the past week, etc.
  • the ventilation schedule and the ventilation schedule that is always strong during the planning period are included.
  • the adjacent ventilation schedule generation unit 22 reads out the optimization execution condition and the optimal ventilation schedule candidate from the storage unit 15, and performs an operation for generating an adjacent ventilation schedule by changing a part of the optimal ventilation schedule candidate schedule by the processor. Execute and store the generated adjacent ventilation schedule in the storage unit 15.
  • the adjacent ventilation schedule generation part 22 calculates
  • the adjacent ventilation schedule is, for example, a case where the control command at 12:00 to 12:30 in the optimum ventilation schedule candidate is weak and is changed to the inside.
  • the adjacent ventilation schedule is obtained by changing the control command in one time zone by only one step, but may be changed by changing the control command in a plurality of time zones. It may be changed only in three stages.
  • FIG. 12 is a graph showing the adjacent ventilation schedule in the first embodiment of the present invention.
  • the optimal ventilation schedule candidate is indicated by a broken line
  • the adjacent ventilation schedule is indicated by a solid line.
  • the ventilation volume is increased by one stage in the time zones (A) and (B), and the ventilation volume is decreased by two stages in the time zone (C).
  • the adjacent ventilation schedule generation unit 22 acquires the outside air temperature of the next day from the storage unit 15, and generates an adjacent ventilation schedule that reduces the ventilation amount in a time zone in which the outside air temperature is higher than the set temperature of the room temperature.
  • the adjacent ventilation schedule generation unit 22 increases the ventilation amount. Generate an adjacent ventilation schedule.
  • the adjacent ventilation schedule generation unit 22 performs ventilation. Create an adjacent ventilation schedule that reduces the amount. In this way, the adjacent ventilation schedule generation unit 22 generates the adjacent ventilation schedule in which the air conditioning load is taken into account, so that the ventilation schedule can perform appropriate outside air cooling while suppressing excessive ventilation. Will be optimized.
  • the adjacent ventilation schedule generation unit 22 acquires the outside air temperature of the next day from the storage unit 15, and generates an adjacent ventilation schedule for reducing the ventilation amount in a time zone in which the outside air temperature is lower than the set temperature of the room temperature.
  • the adjacent ventilation schedule generation unit 22 increases the ventilation amount. Generate an adjacent ventilation schedule.
  • the adjacent ventilation schedule generation unit 22 performs ventilation. Create an adjacent ventilation schedule that reduces the amount. In this way, the adjacent ventilation schedule generation unit 22 generates the adjacent ventilation schedule in which the air conditioning load is taken into account, so the ventilation schedule can be appropriately ventilated while suppressing excessive ventilation. Will be optimized.
  • the adjacent ventilation schedule generation unit 22 may generate an adjacent ventilation schedule that reduces the ventilation amount. For example, such a time zone corresponds to midnight when there is no occupant.
  • the adjacent ventilation schedule generation unit 22 may generate the adjacent ventilation schedule based on the above-described rules only in a part of the air conditioning time zones set by the condition setting unit 11.
  • the partial time zone may be selected based on the air conditioning load or the CO 2 concentration. For example, when generating an adjacent ventilation schedule that increases the ventilation volume, a time zone in which the air conditioning load is large may be selected, and when generating an adjacent ventilation schedule that decreases the ventilation volume, the air conditioning load is A small time zone should be selected.
  • the adjacent ventilation schedule generation unit 22 may generate the adjacent ventilation schedule probabilistically by a generation method in which the ventilation amount changes in the opposite direction to the above-described generation method. In such a case, the drop in the local solution in the optimization is suppressed. Further, by using the relationship between the increase / decrease in the power consumption of the air conditioner 2 and the increase / decrease in the power consumption of the ventilator 3 with respect to the increase / decrease of the ventilation amount, the total power consumption of the air conditioner 2 and the ventilator 3 is further reduced. You may give priority to changes that increase or decrease the ventilation volume.
  • the adjacent ventilation schedule generation unit 22 may generate an adjacent ventilation schedule by a combination of a plurality of generation methods.
  • the adjacent ventilation schedule generation unit 22 may combine a plurality of generation methods by a probabilistic method, or may combine the priorities by weighting or the like.
  • the search process of optimization may be stored, and various combinations may be executed in that order, or combinations that were effective in the past search may be executed preferentially, The optimization search process up to the previous day may be learned, and a more effective generation method or combination may be derived.
  • the outside air temperature is set. You may compare with the external air-conditioning determination temperature set to the temperature different from temperature.
  • the outside air cooling / heating determination temperature is set to a temperature lower by 1 ° C. than the set temperature in the outside air cooling, and is set to a temperature higher by 1 ° C. than the set temperature in the outside air heating.
  • the difference from the set temperature may be 0.5 ° C., 2 ° C. or the like.
  • the outside temperature of the next day may be acquired from the weather forecast on the Internet, or may be acquired as the same temperature as the previous day's measured value by an outside temperature sensor installed in a separate building. It may be acquired as the average temperature for every hour of the measured values for the past week with the outside air temperature sensor installed in the building, and the actual measurement data of the past years in the area where the target building is installed It may be obtained as an average.
  • the acquisition method of the outside temperature on the next day may not be limited to these.
  • CO 2 concentration prediction unit 23 The CO 2 concentration prediction unit 23 reads out the optimization execution condition and the adjacent ventilation schedule generated by the adjacent ventilation schedule generation unit 22 from the storage unit 15, and executes the adjacent ventilation schedule when the planning target period is reached. The calculation for predicting the time change of the indoor CO 2 concentration at is performed by the processor, and the predicted time change of the CO 2 concentration is stored in the storage unit 15.
  • the CO 2 concentration prediction unit 23 uses a CO 2 concentration prediction model that inputs the ventilation amount, the CO 2 concentration of the outside air, and the CO 2 generation amount from the human body, and outputs the indoor CO 2 concentration. , to adjacent ventilation schedule, to predict the time variation of the CO 2 concentration of the following day in the room.
  • the CO 2 concentration prediction model is represented by the following formula (1), for example.
  • [rho Z is a CO 2 concentration in the room [ppm].
  • CO 2 concentration prediction unit 23 calculates the [rho Z.
  • ⁇ O is the CO 2 concentration [ppm] of the outside air.
  • ⁇ O is a standard value, for example, a fixed value such as 350 ppm.
  • the CO 2 concentration of the outside air is measured by a sensor, and ⁇ O may be set as a pattern of a 24-hour time change based on past measurement values.
  • M OCC is the amount of CO 2 generated from the human body [m 3 / h].
  • the m OCC is a value set by a user such as an administrator in the input / output unit 13, a value acquired by learning of entry / exit management data, statistical processing, or the like.
  • m OCC is estimated as a value obtained by multiplying the average number of people in the room every hour by the amount of CO 2 generated per person.
  • the amount of CO 2 generated per person may be set based on literature or the like.
  • the m OCC may be acquired by learning from a past measured value of the CO 2 concentration in the room, a ventilation amount, and the like.
  • Q vent is a ventilation amount [m 3 / h].
  • Q vent is a ventilation amount at each time determined from the adjacent ventilation schedule.
  • Q draft is the clearance air volume [m 3 / h].
  • Q draft is a value set based on design data, literature, and the like. Q draft may be acquired by learning from a past measured value of the CO 2 concentration in the room, a ventilation amount, and the like.
  • V Z is the chamber volume [m 3 ].
  • VZ is a value set based on design data, literature, and the like.
  • V Z is the measured value of the CO 2 concentration in the past room, it may be obtained by learning from ventilation or the like.
  • the CO 2 concentration prediction method formulated by the differential equation is exemplified, but the CO 2 concentration prediction method is not limited to this.
  • a formula formulated by addition / subtraction including at least one of factors affecting the CO 2 concentration may be used, and in this case, the formula can be simplified.
  • the air conditioning load prediction unit 24 reads out the optimization execution condition and the adjacent ventilation schedule generated by the adjacent ventilation schedule generation unit 22 from the storage unit 15, and executes the adjacent ventilation schedule in the planning target period.
  • a calculation for predicting a temporal change in the amount of heat processed by the air conditioner 2 is executed by the processor, and the predicted amount of heat is stored in the storage unit 15 as an air conditioning load.
  • the air conditioning load is the amount of heat processed by the air conditioner 2 to maintain the room at a reference temperature, for example, 27 ° C. during cooling operation, and includes the amount of processing heat generated by ventilation.
  • a temperature range such as a set temperature ⁇ 0.5 ° C. may be provided to predict a plurality of air conditioning loads such as a reference temperature (set temperature maintenance), an upper limit temperature, a lower limit temperature, and the like.
  • the air conditioning load prediction unit 24 is modeled on the basis of a heat transport equation, which is a relational expression of changes over time such as outside air temperature, solar radiation, internal heat generation, air conditioning machine heat, room temperature, and ventilation, for example.
  • a building thermal characteristic model which is a characteristic model
  • a time change in the amount of heat processed by the air conditioner 2 necessary for maintaining the room at a reference temperature that is, a time change in the air conditioning load is predicted.
  • the building thermal characteristic model for example, receives the outside air temperature, the amount of solar radiation, the internal heat generation, the set temperature, the ventilation amount (adjacent ventilation schedule), etc.
  • the building thermal characteristics model such as building thermal resistance, heat capacity, etc., may be set based on design data, is treated as an unknown parameter, and is acquired by learning from the air conditioner 2 operation data, etc. It may be set to a value.
  • the air conditioning load prediction unit 24 uses a black box model to model the input / output relationship of the data by statistical processing from the operation data, weather data, and the like of the air conditioner 2, That is, the time change of the air conditioning load may be predicted.
  • the black box model is, for example, a neural network.
  • the air conditioning load prediction unit 24 uses a pattern of the amount of heat processed per day based on past operation data of the air conditioner 2, etc., to change the amount of heat processed by the air conditioner 2 over time, that is, change over time of the air conditioning load. May be predicted.
  • the amount of heat processed by the air conditioner 2 can be obtained directly from the operation data of the air conditioner 2 or can be calculated using the operation data of the air conditioner 2. Therefore, the next day's air conditioning load is assumed to be the same as the previous day's actual air conditioning load.
  • the amount of increase or decrease of the air conditioning load to be added is predicted as the time change of the heat treatment amount of the air conditioner 2, that is, the time change of the air conditioning load.
  • the ventilator 3 has the heat exchange unit 3b, the increase or decrease of the air conditioning load due to the previous day ventilation and the increase or decrease of the air conditioning load due to the adjacent ventilation schedule of the next day.
  • the heat exchange rate in the heat exchange unit 3b may be taken into account.
  • the average of the past week's actual air conditioning load may be used, or the actual air conditioning load of the same day of the previous week may be used.
  • a weather forecast obtained for the next day may be acquired and the past air conditioning load corrected using the weather forecast information may be used.
  • the actual processing heat of the air conditioner 2 using the measured values of the temperature sensor and the air flow sensor installed at the outlet of the air conditioner 2, the measured values of the temperature sensor and the flow sensor installed in the refrigerant pipe, and the like.
  • the load may be calculated, and the processing heat load may be used for predicting the time change of the processing heat amount of the air conditioner 2, that is, the time change of the air conditioning load.
  • the operation of the ventilator 3 often affects the air conditioning load. For this reason, in each of the above methods, when using the operation data of the actual ventilation device 3, the air conditioning load is preferably calculated in consideration of the influence of the difference from the adjacent ventilation schedule.
  • Adjacent ventilation schedule evaluation unit 25 Adjacent ventilation schedule evaluation unit 25, the execution conditions of the optimization, the CO 2 concentrations predicted in the CO 2 concentration prediction unit 23 reads the air-conditioning load predicted by the air conditioning load prediction unit 24, from the storage unit 15, The calculation of the evaluation function value J shown in the following formula (2) is executed by the processor, and the calculation result is stored in the storage unit 15. By using the air conditioning load in the air conditioning load prediction unit 24, the room is maintained at a reference temperature or temperature range.
  • the power at each time obtained using the relationship is integrated to calculate the amount of power for one day, and the amount of power is calculated.
  • the power consumption of the air conditioner 2 is assumed.
  • the power at each time obtained using the air conditioning efficiency which is a fixed value, the air conditioning efficiency for each outside temperature, etc., is integrated for one day.
  • the amount of power is calculated and the amount of power is set as the power consumption of the air conditioner 2.
  • the ventilator 3 when the relationship between fan speed, stage (strong, medium, weak), etc. and power consumption can be formulated, the power at each time determined using that relationship is integrated for one day. The amount of power is calculated, and the amount of power is set as the power consumption of the ventilator 3. In the ventilator 3, when the relationship between the fan speed, stage (strong, medium, weak), etc. and power consumption cannot be formulated, each time determined using the ventilation efficiency, etc., which is a fixed value tabulated The amount of power is integrated to calculate the amount of power for one day, and the amount of power is used as the amount of power consumed by the ventilator 3.
  • Penalty term with the upper limit value is provided to the CO 2 concentration, a penalty term for the predicted value of the CO 2 concentration is time zone exceeding the upper limit value, the relationship represented by the following formula (3) It is calculated by the formula
  • a penalty term such as equation (3), it is possible to temporarily allow the case where the predicted value of the CO 2 concentration exceeds the upper limit, and the progress of the search for optimization is delayed. It is suppressed.
  • the upper limit value of the CO 2 concentration is set to a smaller value than the true upper limit value such as the legal standard value or the like. Good.
  • the adjacent ventilation schedule evaluation part 25 may calculate the evaluation function value J shown by the following formula
  • the adjacent ventilation schedule evaluation part 25 is the following formula
  • equation (5) or (6) The evaluation function value J shown in FIG. That is, the power consumption amount of the ventilation device 3 does not have to be added to the evaluation function value J. Even in such a case, the ventilation schedule can be optimized.
  • the adjacent ventilation schedule evaluation part 25 is calculating the evaluation function value J using the power consumption in the above, it is not limited to such a case, and the adjacent ventilation schedule evaluation part 25 is classified according to time zone.
  • the evaluation function value J may be calculated using an electricity bill that takes into account the electricity unit price and the like.
  • the optimal ventilation schedule candidate update unit 26 stores, from the storage unit 15, the optimization execution conditions, the evaluation function value J0 obtained from the current optimal ventilation schedule candidate, and the evaluation function value Jx obtained from the adjacent ventilation schedule. Reading, comparing the evaluation function value J0 and the evaluation function value Jx, determining whether or not to update the optimal ventilation schedule candidate to the adjacent ventilation schedule, and calculating the optimal ventilation schedule candidate according to the determination result The calculation is executed by the processor, and the calculation result is stored in the storage unit 15.
  • the optimal ventilation schedule candidate update unit 26 updates the optimal ventilation schedule candidate. That is, the optimal ventilation schedule candidate update unit 26 replaces the optimal ventilation schedule candidate with the adjacent ventilation schedule.
  • the optimal ventilation schedule candidate update unit 26 determines whether or not to update the optimal ventilation schedule candidate constantly or to update the optimal ventilation schedule candidate by a probabilistic method, and the determination Update according to the results.
  • the optimal ventilation schedule candidate update unit 26 updates the optimal ventilation schedule candidate with the probability of P1 (k), and ⁇ x
  • the optimal ventilation schedule candidate is updated with the probability of P2 (k).
  • k is the number of searches
  • Th (k) is a threshold value in the k-th search
  • P1 (k) and P2 (k) are probabilities in the k-th search.
  • Each of Th (k), P1 (k), and P2 (k) may be changed to a different value in the optimization search process.
  • the probability of whether or not to update is not limited to two stages, and may be three or more stages.
  • the optimal ventilation schedule candidate update unit 26 has the probability of P1 (k) and is optimal.
  • the optimal ventilation schedule candidate is updated and ⁇ x ⁇ Th1 (k) and ⁇ x ⁇ Th2 (k)
  • the optimal ventilation schedule candidate is updated with the probability of P2 (k)
  • the optimal ventilation schedule candidate is updated with the probability of P3 (k).
  • Th1 (k) and Th2 (k) are threshold values in the k-th search
  • P1 (k), P2 (k), and P3 (k) are k-th times. Probability in search.
  • Each of Th1 (k), Th2 (k), P1 (k), P2 (k), and P3 (k) may be changed to a different value in the optimization search process.
  • End determination unit 27 The end determination unit 27 reads out the optimization execution condition from the storage unit 15, and executes a calculation for determining whether or not to end the optimization search by the processor.
  • the end determination unit 27 determines whether or not the elapsed time from the start of optimization has exceeded a predetermined reference time, whether or not the evaluation function value J has reached a predetermined target value or less, Whether or not the search for optimization is to be ended is determined based on whether or not the decrease rate has reached a predetermined decrease rate or less.
  • the adjacent ventilation schedule generation unit 22 may generate a plurality of adjacent ventilation schedules.
  • the adjacent ventilation schedule evaluation unit 25 evaluates all of the plurality of generated adjacent ventilation schedules.
  • the optimal ventilation schedule candidate update part 26 compares the any one adjacent ventilation schedule among several adjacent ventilation schedules with the present optimal ventilation schedule candidate, and performs the said process. Any adjacent ventilation schedule of the plurality of adjacent ventilation schedules may be compared with the current optimal ventilation schedule candidate, but the adjacent ventilation schedule with the smallest evaluation function value J, the current optimal ventilation schedule candidate, Are preferably compared.
  • air outside the building taken in by the ventilation device 3 may be mixed with air returned indoors by the air conditioner 2.
  • the control command (strong, medium, weak, stop) to the ventilation device 3 determines the amount of air outside the building that can be taken in, the temperature of the air that is actually taken in, the air that is actually taken in It may be determined in consideration of humidity and the like.
  • FIG. 5 is an overall configuration diagram of a modification of the air conditioning system according to Embodiment 1 of the present invention.
  • the ventilator 3 includes a fan 3a, a heat exchange unit 3b, a heat source unit 3c, a heat exchanger 3d, a humidifier 3e, a dehumidifier 3f, and a heater 3g. At least one of the above may be a constituent element.
  • the heat source unit 3c, the heat exchanger 3d, the humidifier 3e, the dehumidifier 3f, and the heater 3g are for adjusting the temperature and humidity of the air before taking the air outside the building into the room. Used.
  • the heat source device 3c cools or heats a heat medium such as refrigerant and water.
  • the heat exchanger 3d performs heat exchange between the heat medium of the heat source device 3c and air taken in from outside the building.
  • the humidifier 3e is for increasing the humidity of the air before taking the air outside the building into the room.
  • the dehumidifier 3f is for lowering the humidity of the air before taking the air outside the building into the room.
  • the heater 3g is for raising the temperature of the air before taking the air outside the building into the room.
  • the air conditioning load prediction unit 24 predicts the total heat load processed by the air conditioner 2 and the ventilation device 3 as the air conditioning load. Further, the adjacent ventilation schedule evaluation unit 25 calculates the evaluation function value J using the total power consumption or electricity charge of these components as the power consumption or electricity charge of the ventilation device 3.
  • FIG. 8A is a graph showing a ventilation schedule in summer in Embodiment 1 of the present invention.
  • the horizontal axis represents time
  • the vertical axis represents CO 2 concentration and ventilation volume.
  • FIG. 8B is a graph showing the power consumption in summer in Embodiment 1 of the present invention.
  • the horizontal axis represents time
  • the vertical axis represents power consumption. This power consumption is obtained by adding ventilation power to air conditioning power.
  • an optimal ventilation schedule is shown as a continuous line, and constant ventilation (normal ventilation) is shown with a broken line.
  • the added value of the air conditioning power and the ventilation power slightly increases due to the promotion of ventilation in the morning, but the added value of the air conditioning power and the ventilation power is greatly reduced by suppressing the ventilation during the day. The For this reason, the power consumption in 1 day is reduced and the optimal time shift of ventilation is realizable.
  • FIG. 9A is a graph showing a ventilation schedule in an intermediate period in the first embodiment of the present invention.
  • the horizontal axis represents time
  • the vertical axis represents CO 2 concentration and ventilation volume.
  • FIG. 9B is a graph showing the power consumption in the intermediate period in the first embodiment of the present invention.
  • the horizontal axis represents time
  • the vertical axis represents power consumption. This power consumption is obtained by adding ventilation power to air conditioning power.
  • an optimal ventilation schedule is shown as a continuous line, and constant ventilation (normal ventilation) is shown with a broken line. As shown in FIG.
  • the CO 2 concentration is kept to less than the upper limit value 1000 ppm.
  • the added value of the air conditioning power and the ventilation power is slightly reduced due to the suppression of ventilation in the morning, and the added value of the air conditioning power and the ventilation power is greatly reduced by promoting the ventilation during the day. .
  • the present invention can determine the optimum ventilation volume at each time throughout the day.
  • a ventilation schedule based on it is adopted.
  • FIG. 10A is a graph showing a ventilation schedule in winter in Embodiment 1 of the present invention.
  • the horizontal axis represents time
  • the vertical axis represents CO 2 concentration and ventilation volume.
  • FIG. 10B is a graph showing power consumption in winter in Embodiment 1 of the present invention.
  • the horizontal axis represents time
  • the vertical axis represents power consumption. This power consumption is obtained by adding ventilation power to air conditioning power.
  • an optimal ventilation schedule is shown as a continuous line, and constant ventilation (normal ventilation) is shown with a broken line.
  • FIG. 10A when heating is performed in winter, the outside air temperature is low all day, so that ventilation is suppressed.
  • the CO 2 concentration is kept to less than the upper limit value 1000 ppm.
  • the added value of the air conditioning power and the ventilation power is reduced by the morning ventilation suppression, and the added value of the air conditioning power and the ventilation power is also reduced by the daytime ventilation suppression. Note that the added value of the air conditioning power and the ventilation power slightly increases due to the execution of ventilation in the evening.
  • the increase and decrease of the air conditioning power and the ventilation power are calculated by suppressing and promoting the ventilation, and an optimal ventilation schedule is required. Thereby, the optimal ventilation volume of each time can be determined throughout the whole day.
  • a ventilation schedule is adopted in which ventilation is promoted during the day.
  • the air conditioning load prediction unit 24 determines in which time zone cooling or heating is operated. In addition, during the day, for example, the heating operation may be performed in the morning and the cooling operation may be performed in the afternoon.
  • FIGS. 8 to 10 simply show examples of the ventilation schedule of the present invention, and the ventilation schedule is not limited to these examples.
  • the constant ventilation and the optimal ventilation schedule have the same ventilation volume after the evening, but may be different.
  • the constant ventilation and the optimal ventilation schedule have a constant ventilation volume in the morning, during the day, and after the evening, but actually, for example, every 30 minutes, strong, medium, weak, One of the stops is selected.
  • the optimal ventilation schedule is compared with constant ventilation, but there is also control in which the ventilation volume is sequentially determined while measuring the CO 2 concentration. Note that such control is a part of the solution space for obtaining the optimum ventilation schedule in the present invention, and the optimum ventilation schedule in the present invention realizes further energy saving than such control.
  • the adjacent ventilation schedule evaluation unit 25 maintains an adjacent ventilation schedule (that is, a schedule candidate) in which the CO 2 concentration is maintained in a state that does not exceed the reference value for at least a part of the planning target period.
  • the optimum ventilation schedule candidate update unit 26 is generated, and the power consumption amount or the electricity rate of the air conditioning equipment among the optimum ventilation schedule candidate and the adjacent ventilation schedule (that is, among the plurality of schedule candidates) is relatively small.
  • a ventilation schedule is adopted. Therefore, the method comprising the following reference value of CO 2 concentration while reducing the energy efficiency of the air conditioning equipment, and carrying out the outside air cooling and heating to achieve energy-saving air conditioning, is both energy saving of the whole air-conditioning equipment Be improved. In addition, energy saving performance for a long period such as one day is improved.
  • Embodiment 2 FIG.
  • the air conditioning system according to Embodiment 2 will be described below.
  • the description which overlaps with the air conditioning system which concerns on Embodiment 1 is simplified or abbreviate
  • the air conditioning system according to the second embodiment is different from the air conditioning system according to the first embodiment in that the optimum ventilation scheduling unit 12 optimizes the ventilation schedule using a continuous optimization problem.
  • the control command to the ventilator 3 is a discrete value in four stages (strong, medium, weak, stop), like the air conditioning system according to the first embodiment.
  • the optimal ventilation scheduling part 12 optimizes a ventilation schedule on the assumption that the control command to the ventilation apparatus 3 is a continuous value.
  • the relationship between the air conditioning load and the power consumption may be simply modeled by a quadratic equation. If the control command to the ventilator 3 is a continuous value, such a model may be used. It becomes possible. Therefore, since the optimal ventilation scheduling unit 12 has such a function, the problem solved by the optimal ventilation scheduling unit 12 is formulated as a quadratic programming problem and a general solution can be used. It is possible to speed up the optimization calculation. Note that information such as the upper limit value of the CO 2 concentration and the restricted operation of each device may be used as the constraint condition.
  • FIG. 6 is a functional block diagram of the optimum ventilation scheduling unit of the air conditioning system according to Embodiment 2 of the present invention.
  • the optimal ventilation scheduling unit 12 includes a continuous optimization unit 51 and a continuous optimal ventilation schedule discretization unit 52 instead of the initial solution generation unit 21.
  • the continuous optimization unit 51 generates a ventilation schedule on the assumption that the control command to the ventilator 3 is a continuous value (for example, a value with a rated ratio of 0 to 100%), and the ventilation schedule is set as the continuous optimal ventilation schedule.
  • the continuous optimum ventilation schedule discretization unit 52 reads the continuous optimum ventilation schedule from the storage unit 15 and discretizes control commands to the ventilation device 3 in the continuous optimum ventilation schedule into four stages (strong, medium, weak, and stop). The function of generating a ventilation schedule and storing the ventilation schedule in the storage unit 15 as an initial value of the optimal ventilation schedule candidate is provided.
  • the rating ratio is 100%, when the control command to the ventilator 3 is medium, the rating ratio is 60%, and the control command to the ventilator 3 is weak. If the rating ratio is 40% in some cases and the rating ratio is 0% when the control command to the ventilator 3 is stopped, the output at the time with the continuous optimum ventilation schedule will be 100% to 60% rated ratio When the rating ratio is 60% to 40%, the rating is medium. When the rating ratio is 40% to 10%, the rating is weak. When the rating ratio is 10% to 0%, the rating is stopped. Other discretization methods may be used.
  • the optimum ventilation schedule is acquired by the same procedure as that of the air conditioning system according to the first embodiment.
  • the control command to the ventilator 3 may be a discrete value other than four levels (strong, medium, weak, stop), for example, a discrete value of 10 levels. The effect becomes more pronounced as the number of stages increases.
  • the ventilator 3 may be capable of giving a continuous value as a control command.
  • the continuous optimal ventilation schedule generated by the continuous optimization unit 51 becomes the optimal ventilation schedule candidate.
  • control command that can be given to the ventilator 3 may be a continuous value of 15% to 100%, for example, instead of a continuous value of 0% to 100% of the rated ratio.
  • the adjacent ventilation schedule generation unit 22 generates the adjacent ventilation schedule while calculating differently depending on whether the ventilation device 3 is in the ON state or the OFF state, and the adjacent ventilation schedule evaluation unit. 25, the continuous optimization problem may be solved by obtaining the evaluation function value J for this adjacent ventilation schedule.
  • the optimal ventilation scheduling unit 12 optimizes the ventilation schedule on the assumption that the control command to the ventilation device 3 is a continuous value. Therefore, the time required to obtain the optimal solution is shortened.
  • Embodiment 3 FIG.
  • the air conditioning system according to Embodiment 3 will be described below. In addition, below, the description which overlaps with the air conditioning system which concerns on Embodiment 1 and Embodiment 2 is simplified or abbreviate
  • the air conditioning system according to Embodiment 3 differs from the air conditioning system according to Embodiment 1 in that the air conditioning equipment control system 1 corrects the optimum ventilation schedule.
  • the optimal ventilation schedule generated by the optimal ventilation scheduling unit 12 is based on the prediction of the CO 2 concentration and the like performed on the previous day. Therefore, at the time of control execution, that is, when the optimal ventilation schedule generated by the optimal ventilation scheduling unit 12 is actually operated to control the ventilator 3, by correcting the optimal ventilation schedule by the amount that the prediction is deviated, The energy saving performance of the air conditioning system 100 is further improved.
  • FIG. 7 is a functional block diagram of the air conditioning equipment control system of the air conditioning system according to Embodiment 3 of the present invention.
  • the air conditioning equipment control system 1 includes a schedule correction unit 16 in addition to a condition setting unit 11, an optimal ventilation scheduling unit 12, an input / output unit 13, a measurement control unit 14, and a storage unit 15.
  • the measurement unit 41 has a CO 2 concentration actual measurement unit (not shown).
  • the predicted CO 2 concentration refers to the predicted result of the daily CO 2 concentration change when the optimal ventilation schedule is drawn up on the previous day.
  • the actual measured CO 2 concentration refers to data stored in the storage unit 15 measured by the CO 2 concentration actual measurement unit on the day of control.
  • the schedule correction unit 16 reads the optimal ventilation schedule from the storage unit 15, corrects the optimal ventilation schedule, and outputs it to the measurement control unit 14.
  • the schedule correction unit 16 compares the prediction error Xr ⁇ Xp with the predetermined CO 2 concentration allowable error R set in the condition setting unit 11 and performs correction according to the comparison result.
  • the schedule correction unit 16 performs the comparison and correction, for example, at a cycle of 30 minutes.
  • the schedule correction unit 16 When
  • the schedule correction unit 16 corrects the control command to the ventilation device 3 in the optimal ventilation schedule by one step, and sends it to the measurement control unit 14. Output. For example, when the control command to the ventilator 3 in the optimal ventilation schedule is medium, it is corrected strongly.
  • the schedule correction unit 16 When Xr ⁇ Xp ⁇ R, that is, when the measured CO 2 concentration is low, the schedule correction unit 16 is in the cooling mode, and if the outside air temperature ⁇ the set temperature, The control command is output to the measurement control unit 14 without being corrected.
  • the schedule correction unit 16 When Xr ⁇ Xp ⁇ R, that is, when the measured CO 2 concentration is low, the schedule correction unit 16 is in the cooling mode, and if the outside air temperature ⁇ the set temperature, The control command is corrected by one step and output to the measurement control unit 14. For example, when the control command to the ventilator 3 in the optimal ventilation schedule is medium, it is corrected to be weak.
  • the schedule correction unit 16 When Xr ⁇ Xp ⁇ R, that is, when the measured CO 2 concentration is low, the schedule correction unit 16 is in the heating mode, and if the outside air temperature ⁇ the set temperature, The control command is output to the measurement control unit 14 without being corrected.
  • the schedule correction unit 16 When Xr ⁇ Xp ⁇ R, that is, when the measured CO 2 concentration is low, the schedule correction unit 16 is in the heating mode, and if the outside air temperature ⁇ the set temperature, The control command is corrected by one step and output to the measurement control unit 14. For example, when the control command to the ventilator 3 in the optimal ventilation schedule is medium, it is corrected to be weak.
  • the schedule correction unit 16 may compare the prediction error Xr ⁇ Xp with the plurality of CO 2 concentration allowable errors R set in the condition setting unit 11 and perform correction according to the comparison result.
  • the condition setting unit 11 is set with a first CO 2 concentration allowable error R1 and a second CO 2 concentration allowable error R2 (R1> R2), and the schedule correction unit 16 sets Xr ⁇ Xp> R1. Is corrected to increase the control command to the ventilator 3 in the optimal ventilation schedule by two steps, and when Xr ⁇ Xp ⁇ R2, the control command to the ventilator 3 in the optimal ventilation schedule is corrected to increase by one step. .
  • the subsequent change in the CO 2 concentration over time is corrected based on the predicted CO 2 concentration at the time of planning the optimal ventilation schedule, and at the time of the next schedule correction. It may be used as the predicted CO 2 concentration.
  • schedule correction unit 16 may perform the same correction when the air conditioning load is not predicted or when the outside air temperature is not predicted.
  • the optimal ventilation scheduling unit 12 has an outside air temperature prediction unit (not shown), and the measurement unit 41 has an outside air temperature measurement unit (not shown). These are used, for example, when the outside air temperature is not predicted.
  • the outside air temperature predicting unit predicts the outside air temperature of the next day based on information obtained from outside the system through the Internet or the like or data measured in the past by the outside air temperature measuring unit. Then, the outside air temperature prediction unit stores the prediction result in the storage unit 15 as the predicted outside air temperature.
  • the outside air temperature measurement unit acquires the outside air temperature obtained from the weather forecast service or the like from the Internet, and stores it in the storage unit 15 as it is.
  • the schedule correction unit 16 corrects the ventilation schedule based on the prediction error of the outside temperature, that is, the difference between the predicted outside temperature of the previous day and the actually measured outside temperature of the day. For example, the schedule correction unit 16 increases the ventilation amount by one step when the measured outside air temperature is 1 ° C. or more lower than the predicted outside air temperature during the cooling operation. Further, for example, the schedule correction unit 16 increases the ventilation amount by one step when the measured outside air temperature is 1 ° C. or more higher than the predicted outside air temperature during the heating operation. Thereby, further energy saving can be realized.
  • the temperature threshold value is 1 ° C. and the increase amount of the ventilation amount is one stage is illustrated in the above, it is not limited thereto.
  • the schedule corrector 16 together with the correction by the prediction error of the CO 2 concentration also performs correction to reduce the ventilation.
  • the schedule correction unit 16 performs correction to reduce the ventilation amount within a range in which an increase in the CO 2 concentration in which standards such as laws and regulations exist is allowed.
  • Schedule correction unit 16 similarly to the correction by the prediction error of the CO 2 concentration, according to the result of the scheduling correction, the time variation of the subsequent CO 2 concentration, the correction based on the predicted CO 2 concentration at the time of optimal ventilation schedule planning Then, it may be used as the predicted CO 2 concentration at the next schedule correction.
  • amendment part 16 may acquire the newest predicted outside temperature from the internet etc. regularly, and you may make it perform the schedule correction
  • the optimal ventilation schedule is corrected by an amount that is out of prediction when the control is executed. Therefore, the energy saving performance as the whole air conditioning equipment is further improved. In addition, energy saving performance over a long period such as one day is further improved.
  • Air-conditioning equipment control system 1a Air-conditioning controller, 1b Air-conditioning control computer, 1c Device connection controller, 1n, 1o network, 2 Air-conditioning machine, 2a Heat source machine, 2b Indoor unit, 3 Ventilation device, 3a fan, 3b Heat exchange unit 3c heat source unit, 3d heat exchanger, 3e humidifier, 3f dehumidifier, 3g heater, 11 condition setting unit, 12 optimum ventilation scheduling unit, 13 input / output unit, 14 measurement control unit, 15 storage unit, 16 schedule correction unit , 21 initial solution generation unit, 22 adjacent ventilation schedule generation unit, 23 CO 2 concentration prediction unit, 24 air conditioning load prediction unit, 25 adjacent ventilation schedule evaluation unit, 26 optimum ventilation schedule candidate update unit, 27 end determination unit, 31 input unit 32 display unit 41 measurement unit 42 control unit 51 continuous optimization unit 52 continuous optimal ventilation schedule Discretization unit, 100 air conditioning system.

Abstract

L'invention concerne un système de climatisation (100) qui comprend: un équipement climatisation qui comprend un climatiseur (2) et un dispositif de ventilation (3); et un système de commande d'équipement climatisation (1) qui commande les opérations de l'équipement de climatisation. L'invention concerne un système de commande d'équipement de climatisation (1) qui génère une pluralité de programmes candidats. La concentration en CO2 est maintenue de manière à ne pas dépasser une valeur standard sur au moins une période d'une période cible planifiée, et, parmi la pluralité de programmes candidats, utilise comme programme pour les opérations de ventilation du dispositif de ventilation (3) le programme candidat dans lequel la consommation d'énergie ou les frais d'électricité pour l'équipement de climatisation lorsque la température d'une pièce est maintenue dans une plage de température standard est/sont relativement faible(s).
PCT/JP2014/084311 2014-03-31 2014-12-25 Système de climatisation et procédé de commande pour équipement de climatisation WO2015151363A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2015534703A JPWO2015151363A1 (ja) 2014-03-31 2014-12-25 空調システム、及び、空調設備の制御方法

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2014-071626 2014-03-31
JP2014071626 2014-03-31

Publications (1)

Publication Number Publication Date
WO2015151363A1 true WO2015151363A1 (fr) 2015-10-08

Family

ID=54239720

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2014/084311 WO2015151363A1 (fr) 2014-03-31 2014-12-25 Système de climatisation et procédé de commande pour équipement de climatisation

Country Status (2)

Country Link
JP (1) JPWO2015151363A1 (fr)
WO (1) WO2015151363A1 (fr)

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106679099A (zh) * 2016-12-28 2017-05-17 杭州裕达自动化科技有限公司 中央空调监控系统中末端新风系统智能节电控制方法
JPWO2017002245A1 (ja) * 2015-07-01 2018-02-22 三菱電機株式会社 空調システム制御装置及び空調システム
CN109724226A (zh) * 2018-12-13 2019-05-07 青岛海尔空调器有限总公司 空调器的控制方法
US20190264940A1 (en) * 2018-02-28 2019-08-29 Samsung Electronics Co., Ltd. Compound control apparatus and method thereof in air conditioning system
JP2019158217A (ja) * 2018-03-12 2019-09-19 株式会社東芝 空調制御装置、空調制御方法、およびプログラム
WO2020070794A1 (fr) * 2018-10-02 2020-04-09 三菱電機株式会社 Dispositif de traitement d'informations et système de climatisation doté dudit dispositif
KR20200057831A (ko) * 2018-11-14 2020-05-27 신성민 스마트팜 제어 시스템
CN111397152A (zh) * 2020-03-30 2020-07-10 广东美的制冷设备有限公司 空气调节设备及其控制方法与装置
WO2020235077A1 (fr) * 2019-05-23 2020-11-26 三菱電機株式会社 Dispositif de commande de climatiseur et climatiseur associé
CN113685914A (zh) * 2021-07-30 2021-11-23 重庆海尔空调器有限公司 空调联动除尘系统和除尘方法
WO2022269761A1 (fr) * 2021-06-22 2022-12-29 東芝キヤリア株式会社 Dispositif à cycle de réfrigération, système de détection de fuite de réfrigérant et dispositif de traitement d'informations
JP2023031247A (ja) * 2021-08-23 2023-03-08 旭化成エレクトロニクス株式会社 二酸化炭素濃度予測システム、二酸化炭素濃度予測方法および二酸化炭素濃度予測プログラム
JP7450141B2 (ja) 2019-02-27 2024-03-15 パナソニックＩｐマネジメント株式会社 空調システム、空調制御プログラムおよび空調制御プログラムを保存している記憶媒体

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108518811A (zh) * 2018-03-07 2018-09-11 青岛海尔空调器有限总公司 用于控制空气设备的方法和装置、空气处理系统和计算机可读存储介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006145070A (ja) * 2004-11-17 2006-06-08 Hitachi Ltd 空調システム及び空調システム制御方法
US20100025483A1 (en) * 2008-07-31 2010-02-04 Michael Hoeynck Sensor-Based Occupancy and Behavior Prediction Method for Intelligently Controlling Energy Consumption Within a Building
US20120064818A1 (en) * 2010-08-26 2012-03-15 Kurelowech Richard S Heat recovery and demand ventilationsystem
JP2013053836A (ja) * 2011-09-06 2013-03-21 Kimura Kohki Co Ltd 空調機能付外調機
US20130158722A1 (en) * 2011-12-14 2013-06-20 Industrial Technology Research Institute Air conditioning control device and method thereof
US20130231792A1 (en) * 2012-03-05 2013-09-05 Siemens Corporation System and Method of Energy Management Control

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030181158A1 (en) * 2002-01-31 2003-09-25 Edwards Systems Technology, Inc. Economizer control
JP2012094077A (ja) * 2010-10-28 2012-05-17 Toshiba Corp 家庭用エネルギー管理システム
US10373082B2 (en) * 2011-02-24 2019-08-06 Qcoefficient, Inc. Integration of commercial building operations with electric system operations and markets

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006145070A (ja) * 2004-11-17 2006-06-08 Hitachi Ltd 空調システム及び空調システム制御方法
US20100025483A1 (en) * 2008-07-31 2010-02-04 Michael Hoeynck Sensor-Based Occupancy and Behavior Prediction Method for Intelligently Controlling Energy Consumption Within a Building
US20120064818A1 (en) * 2010-08-26 2012-03-15 Kurelowech Richard S Heat recovery and demand ventilationsystem
JP2013053836A (ja) * 2011-09-06 2013-03-21 Kimura Kohki Co Ltd 空調機能付外調機
US20130158722A1 (en) * 2011-12-14 2013-06-20 Industrial Technology Research Institute Air conditioning control device and method thereof
US20130231792A1 (en) * 2012-03-05 2013-09-05 Siemens Corporation System and Method of Energy Management Control

Cited By (31)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPWO2017002245A1 (ja) * 2015-07-01 2018-02-22 三菱電機株式会社 空調システム制御装置及び空調システム
CN106679099A (zh) * 2016-12-28 2017-05-17 杭州裕达自动化科技有限公司 中央空调监控系统中末端新风系统智能节电控制方法
CN111788435A (zh) * 2018-02-28 2020-10-16 三星电子株式会社 空调系统中的复合控制装置及其方法
KR102472214B1 (ko) * 2018-02-28 2022-11-30 삼성전자주식회사 에어 컨디셔닝 시스템에서 복합 제어 장치 및 방법
US20190264940A1 (en) * 2018-02-28 2019-08-29 Samsung Electronics Co., Ltd. Compound control apparatus and method thereof in air conditioning system
KR20190103890A (ko) * 2018-02-28 2019-09-05 삼성전자주식회사 에어 컨디셔닝 시스템에서 복합 제어 장치 및 방법
WO2019168349A1 (fr) 2018-02-28 2019-09-06 Samsung Electronics Co., Ltd. Appareil de commande composée et procédé associé dans un système de climatisation
CN111788435B (zh) * 2018-02-28 2022-07-19 三星电子株式会社 空调系统中的复合控制装置及其方法
US10890349B2 (en) 2018-02-28 2021-01-12 Samsung Electronics Co., Ltd Compound control apparatus and method thereof in air conditioning system
EP3682170A4 (fr) * 2018-02-28 2020-08-26 Samsung Electronics Co., Ltd. Appareil de commande composée et procédé associé dans un système de climatisation
JP2019158217A (ja) * 2018-03-12 2019-09-19 株式会社東芝 空調制御装置、空調制御方法、およびプログラム
JPWO2020070794A1 (ja) * 2018-10-02 2021-05-13 三菱電機株式会社 情報処理装置およびこれを備えた空調システム
JP7170740B2 (ja) 2018-10-02 2022-11-14 三菱電機株式会社 情報処理装置およびこれを備えた空調システム
US11578889B2 (en) 2018-10-02 2023-02-14 Mitsubishi Electric Corporation Information processing apparatus and air-conditioning system provided with the same
WO2020070794A1 (fr) * 2018-10-02 2020-04-09 三菱電機株式会社 Dispositif de traitement d'informations et système de climatisation doté dudit dispositif
EP3862644A4 (fr) * 2018-10-02 2021-10-13 Mitsubishi Electric Corporation Dispositif de traitement d'informations et système de climatisation doté dudit dispositif
US20210302044A1 (en) * 2018-10-02 2021-09-30 Mitsubishi Electric Corporation Information processing apparatus and air-conditioning system provided with the same
KR20200057831A (ko) * 2018-11-14 2020-05-27 신성민 스마트팜 제어 시스템
KR102366075B1 (ko) * 2018-11-14 2022-02-22 신성민 스마트팜 제어 시스템
CN109724226A (zh) * 2018-12-13 2019-05-07 青岛海尔空调器有限总公司 空调器的控制方法
CN109724226B (zh) * 2018-12-13 2021-05-25 青岛海尔空调器有限总公司 空调器的控制方法
JP7450141B2 (ja) 2019-02-27 2024-03-15 パナソニックＩｐマネジメント株式会社 空調システム、空調制御プログラムおよび空調制御プログラムを保存している記憶媒体
JP7112054B2 (ja) 2019-05-23 2022-08-03 三菱電機株式会社 空気調和装置の制御装置、及び空気調和装置
WO2020235077A1 (fr) * 2019-05-23 2020-11-26 三菱電機株式会社 Dispositif de commande de climatiseur et climatiseur associé
JPWO2020235077A1 (ja) * 2019-05-23 2021-10-21 三菱電機株式会社 空気調和装置の制御装置、及び空気調和装置
CN111397152B (zh) * 2020-03-30 2022-05-10 广东美的制冷设备有限公司 空气调节设备及其控制方法与装置
CN111397152A (zh) * 2020-03-30 2020-07-10 广东美的制冷设备有限公司 空气调节设备及其控制方法与装置
WO2022269761A1 (fr) * 2021-06-22 2022-12-29 東芝キヤリア株式会社 Dispositif à cycle de réfrigération, système de détection de fuite de réfrigérant et dispositif de traitement d'informations
CN113685914A (zh) * 2021-07-30 2021-11-23 重庆海尔空调器有限公司 空调联动除尘系统和除尘方法
JP2023031247A (ja) * 2021-08-23 2023-03-08 旭化成エレクトロニクス株式会社 二酸化炭素濃度予測システム、二酸化炭素濃度予測方法および二酸化炭素濃度予測プログラム
JP7367134B2 (ja) 2021-08-23 2023-10-23 旭化成エレクトロニクス株式会社 二酸化炭素濃度予測システム、二酸化炭素濃度予測方法および二酸化炭素濃度予測プログラム

Also Published As

Publication number Publication date
JPWO2015151363A1 (ja) 2017-04-13

Similar Documents

Publication Publication Date Title
WO2015151363A1 (fr) Système de climatisation et procédé de commande pour équipement de climatisation
US10908578B2 (en) Temperature control system and methods for operating same
EP3497377B1 (fr) Système de régulation de température et ses procédés de fonctionnement
JP5668970B2 (ja) 運転管理装置、運転管理方法、および運転管理プログラム
JP5696877B2 (ja) 運転管理装置、運転管理方法、および運転管理プログラム
JP4363244B2 (ja) エネルギー管理装置
CN109312951B (zh) 空调机管理装置、热源设备管理装置、空调机管理方法以及热源设备管理方法
Spindler et al. Naturally ventilated and mixed-mode buildings—Part II: Optimal control
CA2795424C (fr) Unite et systeme de conservation d'energie d'un batiment au moyen d'un apprentissage interactif
JP6252673B2 (ja) パラメータ学習装置およびパラメータ学習方法
Sun et al. An integrated control of shading blinds, natural ventilation, and HVAC systems for energy saving and human comfort
JP6108333B2 (ja) 運転管理装置、運転管理方法、運転管理プログラム
CN103221755A (zh) 空调信息推定装置、空调信息推定装置的控制方法、以及控制程序
JP2004301505A (ja) 空調制御装置
WO2019008698A1 (fr) Dispositif de commande de fonctionnement, système de climatiseur, procédé de commande de fonctionnement et programme de commande de fonctionnement
Lachhab et al. A state-feedback approach for controlling ventilation systems in energy efficient buildings
JP6389599B2 (ja) 運転計画作成装置及び運転計画作成方法
JP5725364B2 (ja) 運転管理装置、運転管理方法、および運転管理プログラム
TW202014648A (zh) 儲冰量調整系統與儲冰量調整方法
Weng et al. RNN-based forecasting of indoor temperature in a naturally ventilated residential building
JP6198953B2 (ja) 管理装置、管理システム、管理方法、及び、プログラム
JP2019143909A (ja) 制御装置、空調制御システム、制御方法及びプログラム
Ren et al. Predictive optimal control of fabric thermal storage systems
KR20240018816A (ko) 기계학습모델 기반 열원공조설비 최적화 구동 제어 시스템 및 방법
JP2020101357A (ja) 空気調和機

Legal Events

Date Code Title Description
ENP Entry into the national phase

Ref document number: 2015534703

Country of ref document: JP

Kind code of ref document: A

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14887909

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase
122 Ep: pct application non-entry in european phase

Ref document number: 14887909

Country of ref document: EP

Kind code of ref document: A1