JP2024045565A - Air conditioning system control device, control program and air conditioning system - Google Patents

Abstract

[Problem] An air conditioning control technology is disclosed that can speed up calculation processing when changing the one to be prioritized in control from among multiple performance indexes in an air conditioning system having multiple types of heat source machines. [Solution] A first process is performed for each load allocation while gradually changing the load allocation based on characteristic data for each of the multiple types of performance indexes to calculate the performance index of each heat source machine when the performance index of each heat source machine is optimal when each heat source machine is operated with a specific load allocation, and a second process is performed to extract the load allocation of each heat source machine that optimizes the performance index selected from the multiple types of performance indexes among the performance indexes of the entire air conditioning system based on the total value of the performance indexes of each heat source machine calculated by the first process, and to identify the operating conditions of each heat source machine that optimize the selected performance index in the extracted load allocation from the calculation result of the first process. [Selected Figure] Figure 3

Description

The present invention relates to an air conditioning system control device, a control method, a control program, and an air conditioning system.

In recent years, computers have been used to control air conditioning systems (see, for example, Patent Documents 1 to 5).

JP2018-031536A Japanese Patent Application Publication No. 2018-031538 JP 2018-031537 A Japanese Patent Application Publication No. 2018-031534 JP 2018-031535 A

Performance indicators for an air conditioning system include, for example, primary energy consumption, energy consumption cost, carbon dioxide emissions, and system COP (Coefficient of Performance). The air conditioning system manager then selects from among multiple performance indicators the one that will be given priority for control, and operates the air conditioning system so that the selected performance indicator is at an optimal value.

By the way, there are various types of heat source devices used in air conditioning systems, such as turbo refrigerators, absorption type water chillers, air-cooled heat pumps, heat storage tanks, and others. Each heat source device has different characteristics. Therefore, in an air conditioning system that has multiple types of heat source equipment, in order to operate the air conditioning system so that a specific performance index becomes the optimal value, each heat source equipment must be operated while taking into account the characteristics and operating conditions of each heat source equipment. Load distribution needs to be determined. Therefore, in order to operate an air conditioning system so that a specific performance index has an optimal value, it is necessary to perform complex calculations that take into account the characteristics and operating conditions of each heat source device. Changing priorities is not easy.

Therefore, this application discloses an air conditioning control technology that can speed up calculation processing when changing the performance index that is prioritized for control in an air conditioning system that has multiple types of heat source units.

In order to solve the above problem, in the present invention, the calculation of the performance index of each heat source machine when each heat source machine is operated with a specific load distribution is performed for each load distribution while gradually changing the load distribution based on characteristic data for each of multiple types of performance indexes, and the load distribution of each heat source machine when the entire air conditioning system is optimal with one performance index is extracted based on the total value of the calculated performance index of each heat source machine.

Specifically, the present invention provides a control device for an air conditioning system having multiple types of heat source devices, including a storage section in which characteristic data of each heat source device is stored, and a load on each heat source device based on the data in the storage section. a processing unit that determines the distribution, the processing unit calculates the performance index of each heat source machine when the performance index of each heat source machine becomes optimal when each heat source machine is operated with a specific load distribution. , a first process performed for each load distribution while gradually changing the load distribution based on the characteristic data for each of the plurality of types of performance indicators, and in any one performance indicator selected from the plurality of types of performance indicators, The load distribution of each heat source device that optimizes the selected performance index among the performance indexes of the entire air conditioning system is extracted based on the total value of the performance index of each heat source device calculated in the first process, and A second process is executed in which the operating conditions of each heat source device for which the selected performance index is optimal in the extracted load distribution are specified from the calculation results of the first process.

Here, a performance index is something that quantitatively represents performance, and examples of such indicators include primary energy consumption, energy consumption cost, carbon dioxide emissions, and coefficient of performance (COP).

In the above control device, the first process and the second process are executed to extract the load distribution of each heat source machine that optimizes the performance index and to specify the operating conditions of each heat source machine. The load distribution of each heat source machine that optimizes the performance index is simply extracted from the calculation results already obtained for all types of performance index by the first process. Therefore, even if the performance index prioritized in the control of the air conditioning system is changed, for example, the load distribution of each heat source machine that optimizes the newly selected performance index and the operating conditions of each heat source machine can be extracted and the operating conditions of each heat source machine can be specified without executing the first process again. Therefore, with the above control device, even if the performance index prioritized in the control is changed from among multiple performance indexes, the load distribution of each heat source machine that optimizes the performance index selected by the change can be extracted and the operating conditions of each heat source machine can be specified without performing complex calculations again taking into account the characteristics and operating conditions of each heat source machine.

The processing unit may perform the first process within a load distribution range in which the power consumption of the air conditioning system does not exceed an upper limit, or within a load distribution range in which the power consumption does not fall below the minimum gas consumption required for the air conditioning system. A control device equipped with such a processing unit can further reduce the load of the first process.

Furthermore, when the selected performance index is changed, the processing unit may further execute a third process to extract a load distribution for each heat source machine that optimizes the performance index selected by the change among the performance indexes of the entire air conditioning system based on the total value of the performance indexes for each heat source machine calculated by the first process, and to extract, from the calculation result of the first process, the operating conditions for each heat source machine that optimize the selected performance index in the extracted load distribution. A control device equipped with such a processing unit can extract the load distribution for each heat source machine and the operating conditions for each heat source machine that optimize the performance index selected by the change.

The present invention can also be understood from the aspects of a method, a program, and a system. For example, the present invention may be a control method for an air-conditioning system in which a control device of an air-conditioning system having multiple types of heat source machines performs a first process of calculating the operating conditions and performance indexes of each heat source machine when the performance index of each heat source machine is optimal when each heat source machine is operated with a specific load distribution, for each load distribution while gradually changing the load distribution based on the characteristic data of each heat source machine for each of the multiple types of performance indexes, and a second process of extracting the load distribution of each heat source machine for which the selected performance index of the entire air-conditioning system is optimal based on the total value of the performance indexes of each heat source machine calculated by the first process, and extracting the operating conditions of each heat source machine for which the selected performance index is optimal in the extracted load distribution from the calculation result of the first process.

With the above air conditioning system control device, control method, control program, and air conditioning system, it is possible to speed up the calculation process when changing the one to be prioritized in control from among a plurality of performance indicators.

FIG. 1 is a diagram showing an example of an air conditioning system. FIG. 2 is a flowchart showing an overview of the processing executed by the control device. FIG. 3 is a diagram illustrating the contents of the series of processes described above. FIG. 4 is a first flowchart showing a specific example of processing executed by the control device. FIG. 5 is a second flowchart showing a specific example of the process executed by the control device 2. As shown in FIG. FIG. 6 is a flow chart showing the process contents of step S104. FIG. 7 is a flow chart showing the process content of step S106. FIG. 8 is a table comparing energy consumption costs of heat source devices. FIG. 9 is a table comparing the amount of carbon dioxide emissions from heat source equipment. FIG. 10 is a table comparing the primary energy consumption of heat source equipment.

Embodiments of the present invention will be described below. The embodiment shown below is an example of the embodiment of the present invention, and the technical scope of the present invention is not limited to the following aspects.

FIG. 1 is a diagram showing an example of an air conditioning system. As shown in FIG. 1, the air conditioning system 1 includes a control device 2 and multiple types of heat source devices. As shown in FIG. 1, heat source devices included in the air conditioning system 1 include, for example, a centrifugal chiller 3A, an absorption type water chiller/heater 3B, an air-cooled (or water-cooled) heat pump 3C, and a heat storage tank 3D. The system 1 is not limited to having all of these. Furthermore, the air conditioning system 1 may include heat source devices other than the turbo chiller 3A, the absorption type water chiller/heater 3B, the air-cooled heat pump 3C, and the heat storage tank 3D. Heat from each heat source device of the air conditioning system 1 is transported by liquid or air to the air conditioner, and from the air conditioner to the room 4 to be air-conditioned by air or liquid.

The control device 2 is a device that controls the operation of each heat source unit and other air conditioning equipment. The control device 2 may be located either in the building in which the room 4 is located, or in a remote location from where the building is located. The control device 2 receives information from the controllers of each heat source unit and other air conditioning equipment, information from various sensors provided in the air conditioning system 1, the set temperature input via the operation panel in the room 4, information sent via a network, and various other information. Based on this information, the control device 2 determines the load distribution and operating conditions of each heat source unit.

An overview of the processing executed by the control device 2 will be described below. FIG. 2 is a flowchart showing an overview of the processing executed by the control device 2. As shown in FIG. The control device 2 is a computer that includes a storage device in which characteristic data of each heat source device is stored, a CPU (Central Processing Unit) that determines load distribution of each heat source device based on the data in the storage device, an input/output interface, etc. , the following processing is realized by the CPU executing the computer program developed in the memory.

That is, when processing the thermal load required for the entire air conditioning system 1, the control device 2 determines the optimal performance index of each heat source device when each heat source device is operated with a specific load distribution. A first process (S1 to S5) that calculates the operating conditions and performance indicators of each heat source device for each load distribution while gradually changing the load distribution based on the characteristic data for each of the multiple types of performance indicators; In any one of the performance indicators selected from the performance indicators of extracting based on the total value of the performance index of each heat source device, and extracting the operating conditions of each heat source device that optimizes the selected performance index in the extracted load distribution from the calculation results of the first process. A second process (S6) is executed.

Here, a performance index is something that quantitatively represents performance, and examples of such indicators include primary energy consumption, energy consumption cost, carbon dioxide emissions, and system COP.

In the process of step S1, the control device 2 gradually assumes the load allocation of each heat source machine within the range of 0% to 100% so that the sum of the load allocations of all the heat source machines is 100% when the load allocation ratio of each heat source machine is expressed as a percentage. For example, if the control device 2 assumes that the load allocation of the turbo chiller 3A is 40%, the load allocation of the absorption chiller/heater 3B is 20%, and the load allocation of the air-cooled heat pump 3C is 20%, then the control device 2 assumes that the load allocation of the heat storage tank 3D is 20%. Each time the control device 2 executes the process of step S1, it changes the load allocation of each heat source machine by a predetermined rate of change (for example, 1%).

In the process of step S2, the control device 2 calculates the optimal operating conditions for each heat source. The optimal operating conditions are the operating conditions when the performance index of the heat source is optimal when producing the amount of heat determined from the load distribution in step S1, and are calculated using characteristic data of each heat source unit pre-stored in the storage device of the control device 2. For example, in the case of the optimal operating conditions for the turbo chiller 3A, the power consumption of the turbo chiller 3A is calculated by repeated calculations while gradually changing the values of the operating conditions such as the cooling water temperature, thereby identifying the values of the operating conditions when the power consumption of the turbo chiller 3A, including auxiliary equipment such as pumps, is minimized.

In the process of step S3, the control device 2 calculates the values of all performance indicators for each heat source. The control device 2 provides four performance index options that can be prioritized in the operation of the air conditioning system 1: primary energy consumption, energy consumption cost, carbon dioxide emissions, and system COP. The administrator of the air conditioning system 1 can select any one of these performance indicators. Therefore, in the process of step S3, the control device 2 calculates performance index values for each heat source for all four performance indexes: primary energy consumption, energy consumption cost, carbon dioxide emissions, and system COP.

In the process of step S4, the control device 2 adds up the values of the performance indicators calculated in step S3, and calculates the total value of the performance indicators of all heat source devices for each of the four performance indicators.

In the process of step S5, the control device 2 judges whether or not the series of calculation processes from step S1 to step S4 has been completed for all combinations of all load distributions. For example, in step S1, if the load distribution of four types of heat source machines is changed by 1%, a positive judgment is made in the process of step S5 when the series of calculation processes from step S1 to step S4 have been performed for all 1 million combination patterns.

In the process of step S6, the control device 2 compares the total values of the performance indexes for each combination of load distribution calculated in the process of step S4, and extracts a load distribution for each heat source unit that optimizes one of the performance indexes selected by the manager of the air conditioning system 1 from among the performance indexes of the entire air conditioning system 1. The control device 2 also extracts optimal operating conditions for the extracted load distribution from the calculation results of step S2. The control device 2 then sends control signals to the controllers of each heat source unit and other equipment of the air conditioning system 1 so that each heat source unit and other equipment of the air conditioning system 1 operates according to the load distribution and optimal operating conditions extracted in the process of step S6.

The outline of the processing executed by the control device 2 is as described above. FIG. 3 is a diagram illustrating the contents of the series of processes described above. When processing the thermal load (heat source required load) required for the entire air conditioning system 1, the control device 2 uses a method (rule engine) for determining the optimal operating conditions realized by the above-mentioned series of processing flows. Therefore, it is possible to determine the load distribution of each heat source device and the operating conditions of each heat source device for which the performance index is optimal. In addition, the load distribution of each heat source device and the operating conditions of each heat source device for which the performance index extracted in step S6 is optimal have already been obtained for all types of performance indexes through a series of processes from step S1 to step S5. Since it is only extracted from the calculation results, for example, when the administrator of the air conditioning system 1 changes the performance index prioritized in controlling the air conditioning system 1, the series of processes from step S1 to step S5 is executed again. By simply executing the process in step S6, it is possible to extract the load distribution of each heat source device and the operating conditions of each heat source device for which the newly selected performance index is optimal.

Specific examples of the processing executed by the control device 2 will be described in detail below. FIG. 4 is a first flowchart showing a specific example of the processing executed by the control device 2. FIG. 5 is a second flowchart showing a specific example of the processing executed by the control device 2. Specific examples of the processing executed by the control device 2 will be described with reference to the flowcharts of FIG. 4 and FIG. 5.

When the total amount of thermal load required to be processed by the entire air conditioning system 1 (required heat load of the entire air conditioning system 1) is input and an evaluation item is selected, the control device 2 executes a series of processes from step S101 to step S106, which correspond to step S1 described above.

That is, when the load distribution ratio of each heat source machine is expressed as a percentage, the control device 2 gradually assumes the load distribution of each heat source machine within the range of 0% to 100% so that the sum of the load distribution of all heat source machines is 100% (S101). Since this load distribution is the ratio of the load distribution of each heat source machine expressed as a percentage, it is hereafter referred to as the load distribution ratio. If the priority order of the heat sources is set by the administrator of the air conditioning system 1, the control device 2 corrects the assumed range of the load distribution ratio according to that order. Furthermore, if the constraint conditions for the air conditioning system 1 are set by the administrator of the air conditioning system 1, the control device 2 corrects the assumed range of the load distribution ratio so as to satisfy those conditions.

For example, due to a contract between the administrator of the air conditioning system 1 and the electric power company, an upper limit is set for the power consumption of the entire air conditioning system 1, and the administrator of the air conditioning system 1 has to set the upper limit of the power consumption (power demand value), the control device 2 makes an affirmative determination in the process of determining the presence or absence of the upper limit value (S103). Then, the control device 2 refers to the characteristic data regarding the power consumption of each heat source device and corrects the assumed range of the load distribution ratio so that the power consumption of the entire air conditioning system 1 does not exceed the upper limit value (S104).

Figure 6 is a flow chart showing the processing contents of step S104. In the graph of Figure 6, the heat quantity (load distribution quantity) on the horizontal axis is expressed as a percentage of the production capacity of the heat source machine. In the processing of step S104, the control device 2 specifies the relationship between the required load heat quantity and the power consumption for each heat source machine based on the characteristic data of each heat source machine (S104A), and corrects the upper limit value of the assumed range of the load distribution rate for each type of heat source machine so that the power consumption of the entire air conditioning system 1 does not exceed the power demand value (S104B). Since the system power consumption of the heat source machine system is a value obtained by dividing the production heat quantity by the system COP of the system, for example, if the relationship between the system COP and the production heat quantity of the heat source machine system is already prepared as the characteristic data of the heat source machine, the formula representing the characteristic data can be modified to make the left term (vertical axis) the power consumption and the right term (horizontal axis) the value obtained by dividing the production heat quantity by the system COP, thereby obtaining characteristic data (graph) showing the relationship between the required load heat quantity and the power consumption of the heat source machine. Therefore, by using this characteristic data, the control device 2 can identify a required load heat quantity that does not exceed the power demand value.

Referring again to the flowchart of FIG. 4, the processing after step S104 will be described. For example, due to a contract between the administrator of air conditioning system 1 and the gas company, air conditioning system 1
If a lower limit is set for the consumption amount of gas to be processed in the entire air conditioning system 1, and the administrator of the air conditioning system 1 has set the minimum gas consumption amount, the control device 2 controls the minimum gas consumption amount. An affirmative determination is made in the process (S105) of determining the presence or absence of. Then, the control device 2 refers to the characteristic data regarding the gas consumption of each heat source device, and corrects the assumed range of the load distribution ratio so that the gas consumption of the entire air conditioning system 1 does not fall below the minimum gas consumption. S106).

Figure 7 is a flow chart showing the processing content of step S106. In the graph of Figure 7, the heat quantity (load allocation amount) on the horizontal axis is expressed as a percentage of the production capacity of the heat source machine. In the processing of step S106, the control device 2 refers to characteristic data showing the relationship between the required load heat quantity and the gas consumption amount for each heat source machine (S106A), and modifies the lower limit value of the assumed range of the load allocation rate for each type of heat source machine so as not to fall below the minimum gas consumption amount (S106B).

Referring again to the flowchart in FIG. 4, the process after step S105 will be described. After the control device 2 determines the assumed range of the load distribution ratio by the series of processes from step S101 to step S106, it executes a series of processes from step S107 to step S118, which corresponds to the series of processes from step S2 to step S5 described above.

That is, the control device 2 first calculates the amount of produced heat (load distribution amount) that each heat source device should produce from the above load distribution ratio (S107). For example, the control device 2 assumes that the required load heat amount of the entire air conditioning system 1 is 100 kW, the load distribution rate of the turbo chiller 3A is 30%, the load distribution rate of the absorption type water chiller/heater 3B is 30%, and the load distribution rate of the air-cooled heat pump 3C is 30%. If the load distribution rate is 20% and the load distribution rate of the heat storage tank 3D is 20%, the production heat amount of the centrifugal chiller 3A is 30 kW, the production heat amount of the absorption type water cooler/heater 3B is 30 kW, and the production of the air-cooled heat pump 3C. Calculation is performed assuming that the amount of heat is 20 kW and the amount of heat produced by the heat storage tank 3D is 20 kW.

Next, the control device 2 specifies optimal operating conditions for each heat source device based on outside air conditions such as temperature and relative humidity and the amount of heat produced (S108). The optimal operating conditions for each heat source device are specified as follows. For example, the centrifugal chiller 3A is provided with a pump that circulates cold water, a pump that circulates cooling water, and the like. Therefore, when processing a specific required load heat amount, an example of an operating condition that minimizes the total power consumption of the entire heat source device system including these auxiliary machines can be said to be an optimal operating condition. In order to identify such optimal operating conditions, the control device 2 reads characteristic data that shows the correlation between the operating state of each device and the device-specific COP, and calculates each condition when the COP of the heat source system is maximized. Identify control target values for equipment. In this specification, the control device 2 infers various parameters such as chilled water temperature based on virtual indoor design conditions and virtual air conditioner design prepared in advance for calculation, and based on this inference, controls target value. Identify. When a plurality of heat source devices and auxiliary devices are prepared in parallel, the number of these devices in operation is determined, for example, based on an operation design sheet in which the number of devices in operation is defined in advance for each chilled water temperature and each cooling water temperature. Note that the optimal operating conditions for each heat source device are determined by whether the performance index selected for optimization calculation at each heat source and the performance index selected for multiple calculations are the same or different. There may be. For example, primary energy consumption may be selected in the optimization calculation for each heat source, and energy cost may be selected in the performance index selected for calculation of multiple heat sources. If any one of the performance indicators selected for the optimization calculation is selected, the optimization calculation for each heat source and the performance indicators selected for multiple calculations will both be the selected performance indicator. It may be set or may be individually settable. Furthermore, the performance index selected for the optimization calculation may be any one of the four primary energy consumption, energy consumption cost, carbon dioxide emissions, and COP, or may be any other index. .

Next, the control device 2 derives the individual COP of each heat source unit from the characteristic data of each heat source unit based on the operating conditions specified in step S108 (S109). Then, the control device 2 calculates the energy consumed by each heat source unit alone (heat source input energy) by dividing the amount of heat produced by the individual COP (S110). That is, the control device 2 calculates the energy consumed by each heat source unit alone using the following formula (1).

Heat source input energy (kW) = heat produced (kW) / unit COP (1)

Next, the control device 2 calculates the performance index of each heat source device. That is, the control device 2 determines the type of energy (electricity or gas) consumed by each heat source device (S111). Then, if the heat source device consumes electricity, the control device 2 executes a process (S112) to calculate the power consumption of the heat source device and the auxiliary device, and then calculates the power consumption of the auxiliary device based on the calculated power consumption amount. A process (S113) for calculating the performance index of the included heat source device system is executed. In addition, if the heat source device consumes gas, the control device 2 executes a process (S114) for calculating the gas consumption amount of the heat source device, and then calculates the performance of the heat source device system based on the calculated gas consumption amount. A process for calculating an index (S115) is executed.

The control device 2 calculates the power consumption amount in step S112 using, for example, the following formula (2).

Power consumption (kWh) = Σ (heat source input energy (kW) + auxiliary power (kW)) x predetermined time (h) ... (2)

Furthermore, the control device 2 calculates the primary energy consumption amount, which is one of the performance indexes in step S113, by using, for example, the following formula (3).

Primary energy consumption (MJ) = power consumption (kWh) × primary energy consumption conversion coefficient (MJ/kWh) (3)
(The primary energy consumption conversion coefficient varies depending on the region and where the electricity is purchased.)

Furthermore, the control device 2 calculates the energy cost, which is one of the performance indexes in step S113, by using, for example, the following formula (4).

Energy cost (yen) = power consumption (kWh) × electricity price (yen/kW) (4)
(Electricity prices vary depending on the contract and time of day)

In addition, the control device 2 calculates carbon dioxide emissions among the performance indicators in step S113 using, for example, the following formula (5).

CO ₂ emissions (t-CO ₂ ) = power consumption (kWh) x CO ₂ emissions coefficient (t-CO ₂ /kWh) (5)
(The _CO2 emission coefficient varies depending on the region and where you purchase electricity.)

Furthermore, among the performance indicators in step S113, the control device 2 calculates the system COP of the heat source device system using, for example, the following equation (6).

System COP = (manufacturing heat amount (kW) x predetermined time (h)) / power consumption (kWh) ... (6)

Furthermore, the control device 2 calculates the gas consumption amount in step S114 using, for example, the following formula (7).

Gas consumption (Nm ³ )=heat source input energy (kW)×predetermined time (h)×3.6 (MJ/kWh)/heat generation amount (MJ/Nm ³ ) (7)

In addition, the control device 2 calculates the primary energy consumption among the performance indicators in step S115 using, for example, the following equation (8).

Primary energy consumption (MJ) = Gas consumption (Nm ³ ) x Calorific value (MJ/Nm ³ ) ... (8)
(Primary energy consumption conversion coefficients vary depending on the region and where you purchase electricity)

Furthermore, the control device 2 calculates the energy cost, which is one of the performance indexes in step S115, by using, for example, the following formula (9).

Energy cost (yen) = gas consumption (Nm ³ ) × gas/electricity (yen/Nm ³ ) (9)
(Gas prices vary depending on the contract)

Furthermore, the control device 2 calculates the amount of carbon dioxide emissions, which is one of the performance indexes in step S115, using, for example, the following formula (10).

_CO2 emission amount (t- _CO2 )=primary energy consumption (MJ)× _CO2 emission amount coefficient (t- _CO2 /MJ) (10)

Furthermore, among the performance indicators in step S115, the control device 2 calculates the system COP of the heat source device system using, for example, the following equation (11).

System COP = (manufactured heat amount (kW) x predetermined time (h)) / (input energy (kWh) + auxiliary power (kWh)) ... (11)

The control device 2 repeatedly executes a series of processes from step S107 to step S115 until the calculation is completed for all types of heat source devices (S116). That is, since the air conditioning system 1 is equipped with four types of heat source devices: a turbo chiller 3A, an absorption type water chiller/heater 3B, an air-cooled heat pump 3C, and a heat storage tank 3D, the control device 2 performs the steps from step S107 to step S115. Repeat the series of processes four times.

When the control device 2 performs a series of processes from step S107 to step S115 until the calculation is completed for all types of heat source devices, the control device 2 then adds up each performance index of all types of heat source devices and calculates the air conditioning system 1. An overall performance index is calculated for each combination of load distribution ratios (S117).
That is, the control device 2 calculates the primary energy consumption, energy consumption cost, carbon dioxide emissions, and system COP of the entire air conditioning system 1 for each combination of load distribution ratios. The control device 2 calculates each performance index of the entire air conditioning system 1 until completion for all combination patterns of load distribution ratios within the assumed range (S118).

After the control device 2 completes the calculation of each performance index of the entire air conditioning system 1 for all combination patterns of load distribution ratios within the assumed range, the control device 2 performs a series of steps from step S119 to step S121, which corresponds to step S6 described above. Execute the process.

That is, the control device 2 controls the air conditioning system 1 based on the calculation results of each performance index of the entire air conditioning system 1 in the combination pattern of all the load distribution ratios within the assumed range obtained by repeating the processing from step S101 to step S118. A combination of load distributions (load distribution amounts) for which the performance index selected by the administrator of the system 1 has an optimal value is extracted (S119). If the performance index selected by the administrator of the air conditioning system 1 is, for example, primary energy consumption, the control device 2 extracts the load distribution amount when the primary energy consumption becomes the smallest value. Further, if the performance index selected by the administrator of the air conditioning system 1 is, for example, energy consumption cost, the control device 2 extracts a combination of load distribution amounts for which the energy consumption cost is the smallest value. Further, if the performance index selected by the administrator of the air conditioning system 1 is, for example, carbon dioxide emissions, the control device 2 extracts a combination of load distribution amounts that will result in the smallest value of carbon dioxide emissions. . Further, if the performance index selected by the administrator of the air conditioning system 1 is, for example, the system COP, the control device 2 extracts a combination of load distribution amounts for which the system COP becomes the highest value.

In addition, when the administrator of the air conditioning system 1 changes the performance index to be prioritized in controlling the air conditioning system 1 (S120), the control device 2 selects from among the calculation results of each performance index of the entire air conditioning system 1 that has already been calculated. , a combination of load distribution amounts is extracted when the performance index newly selected by the administrator of the air conditioning system 1 becomes the optimal value.

Figure 8 is a table comparing the energy consumption costs of heat source equipment. Also, Figure 9 is a table comparing the carbon dioxide emissions of heat source equipment. Also, Figure 10 is a table comparing the primary energy consumption of heat source equipment. The values shown in each table of Figures 8 to 10 are examples, and the equipment provided in the air conditioning system 1 of this embodiment is not limited to those having such capabilities. For example, when comparing a turbo chiller 3A and an absorption type chiller/heater 3B with the same cooling capacity, if the COP is the value shown in the figure, it can be seen that even if the turbo chiller 3A has a higher COP, the absorption type chiller/heater 3B has a lower energy cost. It can also be seen that the carbon dioxide emissions and primary energy consumption are lower for the turbo chiller 3A. As such, since each heat source equipment has various characteristics, in the case of a system equipped with multiple types of heat source equipment such as the air conditioning system 1, the load distribution amount at which the performance index of the air conditioning system 1 is optimal changes depending on the type of performance index selected by the manager of the air conditioning system 1.

In this regard, in the air conditioning system 1, the load allocation amount of each heat source machine and the operating conditions of each heat source machine that optimize the performance index are determined by the control device 2 executing the above-mentioned series of processes from step S101 to step S121. The load allocation amount of each heat source machine and the operating conditions of each heat source machine that optimize the performance index are simply extracted from the calculation results already obtained for all types of performance indexes by the series of processes from step S101 to step S118. Therefore, even if the manager of the air conditioning system 1 changes the performance index prioritized in the control of the air conditioning system 1, the load allocation amount of each heat source machine and the operating conditions of each heat source machine that optimize the newly selected performance index can be extracted by simply executing the process of step S121. Therefore, even if the one prioritized in the control is changed from among multiple performance indexes, the load allocation amount of each heat source machine and the operating conditions of each heat source machine that optimize the performance index selected by the change can be extracted without performing complex calculations again taking into account the characteristics and operating conditions of each heat source machine.

The air conditioning system 1 of the above embodiment is not limited to the one in which the control device 2 executes all of the above series of processes from step S101 to step S121. For example, the air conditioning system 1 of the above embodiment may be one in which the control device 2 omits the processes from step S102 to step S106, or other changes may be added. In addition, in the air conditioning system 1 of the above embodiment, the control device 2 performs calculations using relative values that are the ratios of the heat production amount of each heat source unit in the above series of processes, but the control device 2 may perform calculations using absolute values that are the ratios of the heat production amount to the heat production amount or rated capacity of each heat source unit. In addition, in the air conditioning system 1 of the above embodiment, the control device 2 calculates the values of the performance indexes for each heat source for all four performance indexes, namely, primary energy consumption, energy consumption cost, carbon dioxide emission amount, and system COP, but the control device 2 may calculate the value of any one of these four performance indexes for each heat source.

1. Air conditioning system 2. Control device 3A. Turbo refrigerator 3B. Absorption type hot and cold water machine 3C. Air-cooled heat pump 3D. Heat storage tank 4. Indoor

Claims (9)

A control device for an air conditioning system having a plurality of types of heat source machines,
A memory unit in which characteristic data of each heat source device is stored;
A processing unit that determines a load distribution of each of the heat source machines based on the data in the storage unit,
The processing unit includes:
A first process calculates a performance index of each heat source machine when the performance index of each heat source machine is optimal when the heat source machine is operated with a specific load distribution when processing a thermal load required for the entire air conditioning system, while gradually changing the load distribution based on the characteristic data for each of a plurality of types of performance indexes;
a second process of extracting a load distribution of each of the heat source machines that optimizes the selected performance index among the performance indexes of the entire air conditioning system, based on a total value of the performance indexes of each of the heat source machines calculated by the first process, for any one performance index selected from the multiple types of performance indexes, and specifying, from the calculation result of the first process, operating conditions of each of the heat source machines that optimize the selected performance index in the extracted load distribution;
completing the first operation before executing the second operation;
Air conditioning system control device. In the first process, the processing unit calculates the performance index of each of the heat source machines for all combinations of load allocations for each load allocation while gradually changing the load allocation based on the characteristic data for each of a plurality of types of performance indexes.
The control device for an air conditioning system according to claim 1 . The multiple types of performance indexes include two or more of primary energy consumption, energy consumption cost, carbon dioxide emissions, and performance coefficients.
The control device for an air conditioning system according to claim 1 or 2. The processing unit performs the first process within a load distribution range in which the power consumption of the air conditioning system does not exceed an upper limit value.
The control device for an air conditioning system according to any one of claims 1 to 3. The processing unit performs the first processing within a load distribution range that does not fall below a minimum gas consumption required for the air conditioning system.
A control device for an air conditioning system according to any one of claims 1 to 4. When the selected performance index is changed, the processing unit determines the load distribution of each of the heat source devices such that the performance index selected by the change among the performance indexes of the entire air conditioning system is optimal. The operating conditions of each heat source device are extracted based on the total value of the performance index of each heat source device calculated by the process of further executing a third process extracted from the calculation result of the process;
A control device for an air conditioning system according to any one of claims 1 to 5. A control device for an air conditioning system having multiple types of heat source machines,
A first process calculates a performance index of each heat source machine when the performance index of each heat source machine is optimal when each heat source machine is operated with a specific load distribution when processing a thermal load required for the entire air conditioning system, while gradually changing the load distribution based on characteristic data of each heat source machine for each of a plurality of types of performance indexes;
a second process of extracting a load distribution of each of the heat source machines that optimizes the selected performance index among the performance indexes of the entire air conditioning system, based on a total value of the performance indexes of each of the heat source machines calculated by the first process, for any one performance index selected from the multiple types of performance indexes, and specifying, from the calculation result of the first process, operating conditions of each of the heat source machines that optimize the selected performance index in the extracted load distribution;
completing the first operation before executing the second operation;
A method for controlling an air conditioning system. For computers in air conditioning systems that have multiple types of heat sources,
The performance of each heat source device when the performance index of each heat source device is optimized when each heat source device is operated with a specific load distribution when processing the thermal load required for the entire air conditioning system. a first process of calculating an index for each load distribution while gradually changing the load distribution based on the characteristic data of each heat source device for each of the plurality of types of performance indicators;
In any one performance index selected from the plurality of types of performance indexes, the load distribution of each heat source device is determined so that the selected performance index among the performance indexes of the entire air conditioning system is optimal. The operating conditions of each heat source device under which the selected performance index is optimal in the extracted load distribution are extracted based on the total value of the performance index of each heat source device calculated by the process of step 1. a second process specified from the calculation result of the process;
completing the first process before executing the second process;
Air conditioning system control program. Multiple types of heat source machines,
A control device having a memory unit in which characteristic data of each heat source unit is stored and a processing unit that determines load distribution of each heat source unit based on the data in the memory unit,
The processing unit includes:
A first process calculates a performance index of each heat source machine when the performance index of each heat source machine is optimal when the heat source machine is operated with a specific load distribution when processing a thermal load required for the entire air conditioning system, for each load distribution while gradually changing the load distribution based on the characteristic data for each of a plurality of types of performance indexes;
a second process of extracting a load distribution of each of the heat source machines that optimizes the selected performance index among the performance indexes of the entire air conditioning system, based on a total value of the performance indexes of each of the heat source machines calculated by the first process, for any one performance index selected from the multiple types of performance indexes, and specifying, from the calculation result of the first process, operating conditions of each of the heat source machines that optimize the selected performance index in the extracted load distribution;
completing the first operation before executing the second operation;
Air conditioning system.

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