Air conditioning system

Abstract

To provide an air conditioning system for improving economical merits.SOLUTION: A server control device of the air conditioning system specifies a peak time that an actual value for a whole dissipation power in a predetermined past period is maximum, derives an actual value for the dissipation power of EHP at the peak time, proportionally divides an actual value for an air conditioning load at the peak time so that the load rate of GHP is maximized and the load rate of the EHP is minimized, to derive the dissipation power of the EHP after suppression, subtracts the dissipation power of the EHP after suppression from the actual value of the dissipation power of the EHP at the peak time to derive a differential value for the dissipation power of the EHP, subtracts a differential value for the dissipation power of the EHP from the actual value for the whole dissipation power at the peak time to derive the whole dissipation power after suppression, and determines the whole dissipation power after suppression, as a target power demand set value.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to an air conditioning system including an EHP (electric heat pump) and a GHP (gas heat pump). [Background technology]

[0002] For example, Patent Document 1 discloses an air conditioning system equipped with an EHP and a GHP. In Patent Document 1, a future facility power trend is estimated, and an air conditioning power trend, which is a trend of power available to the EHP and the GHP, is derived by subtracting the future facility power trend from the contracted power. In Patent Document 1, multiple combinations are generated by apportioning the operation load factors of the EHP and the GHP based on the air conditioning power trend, and the combination that minimizes the total of the electricity and gas charges among the combinations is determined as the operation ratio of the EHP and the GHP. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6322173 Summary of the Invention [Problem to be solved by the invention]

[0004] The basic electricity charge is set according to the contracted power, so if the contracted power can be reduced, the electricity charge can be reduced, and this improves the economic benefits for consumers.

[0005] In view of the above problems, the present invention has an object to provide an air conditioning system that can improve economic merits. [Means for solving the problem]

[0006] In order to solve the above problems, an air conditioning system of the present invention includes an EHP having at least an electrically driven compressor that compresses a heat medium using an electric motor as a drive source, a GHP having at least an engine driven compressor that compresses a heat medium using a gas engine as a drive source, a storage device that stores an actual value of the air conditioning load in association with date and time and stores an actual value of total power consumption, which is the power consumption of the entire building of a consumer, in association with date and time, and a server control device that derives a target power demand setting value that is an upper limit of allowable power consumption in the entire building of the consumer, derives an operation ratio between the EHP and the GHP based on the target power demand setting value, and instructs the EHP and the GHP of the derived operation ratio. The server control device identifies the peak time when the actual value of the overall power consumption in a specified period in the past is at a maximum value, derives the actual value of the EHP power consumption at the peak, prorates the actual value of the air conditioning load at the peak time so that the GHP load rate is maximized and the EHP load rate is minimized to derive the EHP power consumption after suppression, subtracts the EHP power consumption after suppression from the actual value of the EHP power consumption at peak to derive a difference value of the EHP power consumption, subtracts the EHP power consumption difference value from the actual value of the overall power consumption at peak to derive the overall power consumption after suppression, and determines the overall power consumption after suppression as the target power demand setting value.

[0007] The server control device also identifies a first peak time when the actual value of the overall power consumption in a specified period in the past is maximum, derives the actual value of the power consumption of the EHP during the first peak time, prorates the actual value of the air conditioning load during the first peak time so that the load rate of the GHP is maximum and the load rate of the EHP is minimum to derive the post-suppression power consumption of the EHP for the first peak time, subtracts the post-suppression power consumption of the EHP for the first peak time from the actual value of the power consumption of the EHP during the first peak time to derive a difference value of the power consumption of the EHP for the first peak time, subtracts the difference value of the power consumption of the EHP for the first peak time from the actual value of the overall power consumption during the first peak time to derive the post-first suppression overall power consumption, which is the overall power consumption after suppression for the first peak time, determines whether there is an actual value of the overall power consumption that exceeds the post-first suppression overall power consumption in the portion excluding the first peak time in the specified period in the past, and derives the post-first suppression overall power consumption that exceeds the post-first suppression overall power consumption. If it is determined that there is an actual value of the total power consumption, a second peak time when the actual value of the total power consumption is maximum, excluding the first peak time in a specified past period, is identified, the actual value of the power consumption of the EHP for the second peak time is derived, the actual value of the air conditioning load for the second peak time is prorated so that the load rate of the GHP is maximized and the load rate of the EHP is minimized to derive the post-suppression power consumption of the EHP for the second peak time, the post-suppression power consumption of the EHP for the second peak time is subtracted from the actual value of the power consumption of the EHP for the second peak time to derive a difference value of the power consumption of the EHP for the second peak time, and the difference value of the power consumption of the EHP for the second peak time is subtracted from the actual value of the total power consumption for the second peak time to derive the second post-suppression total power consumption, which is the post-suppression total power consumption for the second peak time, and a target power demand setting value may be determined based on the first post-suppression total power consumption and the second post-suppression total power consumption.

[0008] In addition, the server control device may determine the first post-suppression total power consumption as the target power demand setting value if the second post-suppression total power consumption is equal to or less than the first post-suppression total power consumption, and may determine the second post-suppression total power consumption as the target power demand setting value if the second post-suppression total power consumption exceeds the first post-suppression total power consumption.

[0009] In addition, the server control device may identify peak times at which the actual value of the overall power consumption during a specified period in the past is maximum, in order of highest overall power consumption, derive the overall power consumption after suppression for each peak time, identify the maximum value of each post-suppression overall power consumption, and if it is determined that there is no actual value of the overall power consumption that exceeds the maximum value of the overall power consumption after suppression, excluding the identified peak times during a specified period in the past, determine the maximum value of the overall power consumption after suppression as the target power demand setting value. Effect of the Invention

[0010] According to the present invention, it is possible to improve economic merits. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a schematic block diagram showing an example of the configuration of an air conditioning system according to the first embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of a gas price table. [Diagram 3] FIG. 3 is a diagram showing an example of a driving map. [Figure 4] FIG. 4 is a flowchart illustrating the determination of the operation ratio and the generation of the operation map in the first embodiment. [Diagram 5] FIG. 5 is a flowchart illustrating the flow of processing performed by the operation ratio derivation unit in the modified example of the first embodiment. [Figure 6] FIG. 6 is a schematic block diagram showing an example of the configuration of an air conditioning system according to the second embodiment. [Figure 7] FIG. 7 is a diagram for explaining an outline of a method for determining a target power demand set value. [Figure 8] FIG. 8 is a flowchart illustrating the flow of operations of the set value derivation unit. [Figure 9] FIG. 9 is a schematic block diagram showing an example of the configuration of an air conditioning system according to the third embodiment. [Figure 10] FIG. 10 is a flowchart illustrating the flow of processing related to control of the operation time of the GHP. [Figure 11] FIG. 11 is a diagram for explaining the derivation of the boundary value of the air conditioning load factor. [Figure 12] FIG. 12 is a schematic block diagram showing an example of the configuration of an air conditioning system according to the fourth embodiment. [Figure 13] FIG. 13 is a flowchart illustrating the flow of processing executed in the fourth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] A preferred embodiment of the present invention will be described in detail below with reference to the accompanying drawings. The dimensions, materials, and other specific values ​​shown in the embodiment are merely examples for facilitating understanding of the invention, and do not limit the present invention unless otherwise specified. In this specification and drawings, elements having substantially the same functions and configurations are given the same reference numerals to avoid repeated explanations, and elements not directly related to the present invention are not shown.

[0013] (First embodiment) Fig. 1 is a schematic block diagram showing an example of the configuration of an air conditioning system 1 according to the first embodiment. In Fig. 1, dashed arrows illustrate the transmission direction of signals.

[0014] The air conditioning system 1 includes an EHP 10, a GHP 12, an indoor unit 14, and a management server 16. The EHP 10 is an electric heat pump, and the GHP 12 is a gas heat pump. The indoor unit 14 is installed in a space to be air-conditioned. Hereinafter, for convenience of explanation, the space to be air-conditioned may be referred to as the air-conditioned space. The EHP 10 and the GHP 12 are installed as a set, for example, in a customer's building to which the air conditioning system 1 is applied. The EHP 10 and the GHP 12 are connected to the indoor unit 14 through a heat medium flow path 20 through which a heat medium flows.

[0015] The EHP 10 has at least an electrically driven compressor 32 that compresses the heat medium using an electric motor 30 as a drive source. The electric motor 30 drives the electrically driven compressor 32 by consuming electric power.

[0016] In addition to the electric motor 30 and the electrically driven compressor 32, the EHP 10 has an EHP outdoor heat exchanger 34, an EHP communication unit 36, and an EHP control unit 38. The electrically driven compressor 32 is connected to the EHP outdoor heat exchanger 34 and the indoor unit 14 through a heat medium flow path 20.

[0017] In the EHP 10, for example, the heat medium is circulated through the heat medium flow path 20 by an electrically driven compressor 32. The EHP outdoor heat exchanger 34 exchanges heat between the heat medium flowing through the heat medium flow path 20 and outside air, and sends the heat medium after heat exchange to the indoor unit 14. A heat exchanger (not shown) of the indoor unit 14 exchanges heat between the heat medium flowing through the heat medium flow path 20 and air supplied from the space to be air-conditioned, and sends the air after heat exchange to the space to be air-conditioned.

[0018] The EHP communication unit 36 ​​can establish communication with the indoor units 14 and the management server 16. The EHP control unit 38 is composed of a processor and a memory that stores programs. The EHP control unit 38 controls the entire EHP 10 by the processor executing the programs. For example, under the control of the management server 16, the EHP control unit 38 operates the EHP 10 with timing and output according to an operation map described below.

[0019] The GHP 12 has at least an engine-driven compressor 42 that compresses a heat medium using a gas engine 40 as a driving source. The gas engine 40 consumes gas to drive the engine-driven compressor 42.

[0020] In addition to the gas engine 40 and the engine-driven compressor 42, the GHP 12 has a GHP outdoor heat exchanger 44, a GHP communication unit 46, and a GHP control unit 48. The engine-driven compressor 42 is connected to the GHP outdoor heat exchanger 44 and the indoor unit 14 through the heat medium flow path 20.

[0021] In the GHP 12, for example, the engine-driven compressor 42 circulates the heat medium through the heat medium flow path 20. The GHP outdoor heat exchanger 44 exchanges heat between the heat medium flowing through the heat medium flow path 20 and outside air, and sends the heat medium after heat exchange to the indoor unit 14. A heat exchanger (not shown) of the indoor unit 14 exchanges heat between the heat medium flowing through the heat medium flow path 20 and air supplied from the space to be air-conditioned, and sends the air after heat exchange to the space to be air-conditioned.

[0022] The GHP communication unit 46 can establish communication with the indoor units 14 and the management server 16. The GHP control unit 48 is composed of a processor and a memory that stores a program. The GHP control unit 48 controls the entire GHP 12 by the processor executing the program. For example, under the control of the management server 16, the GHP control unit 48 operates the GHP 12 with timing and output according to an operation map described below.

[0023] The EHP 10 and the GHP 12 may be provided in separate housings, or may be provided integrally in a common housing. In the example of FIG. 1, both the heat medium from the EHP 10 and the heat medium from the GHP 12 can be supplied to one indoor unit 14. However, the heat medium flow path 20 connected to the EHP 10 and the heat medium flow path 20 connected to the GHP 12 may be separated into different systems, and the EHP 10 and the GHP 12 may be connected to different indoor units 14. In the example of FIG. 1, one indoor unit 14 is illustrated, but the number of indoor units 14 is not limited to one and may be any multiple number.

[0024] Management server 16 controls the operation of EHP 10 and GHP 12. Management server 16 may be installed in the same building in which EHP 10 and GHP 12 are installed and control EHP 10 and GHP 12, or may be installed in a location separate from the building in which EHP 10 and GHP 12 are installed and control EHP 10 and GHP 12 by remote operation.

[0025] The management server 16 includes a management communication unit 60, a storage device 62, and a server control device 64. The management communication unit 60 can establish communication with the EHP 10 and the GHP 12.

[0026] The storage device 62 is composed of a non-volatile storage element such as a HDD, a flash memory, etc. The storage device 62 stores actual value data 70, COP characteristic data 72, an electricity rate table 74, and a gas rate table 76. Note that COP (Coefficient Of Performance) means the coefficient of performance, in other words, energy consumption efficiency.

[0027] The performance value data 70 is past performance values ​​of the air conditioning load associated with the year, month, and date. The COP characteristic data 72 indicates the relationship between the load factor and the COP for each outdoor temperature. The COP characteristic data 72 is stored for each of the EHP 10 and the GHP 12.

[0028] The electricity rate table 74 associates the basic electricity charge, the unit price of the metered electricity charge, and the unit price of the renewable energy power generation promotion surcharge (hereinafter referred to as the renewable energy surcharge). The basic electricity charge is determined for each month of contract power concluded between the business entity supplying the electricity and the consumer of the electricity (for example, the consumer to which the air conditioning system 1 is applied). The metered electricity charge is added to the basic electricity charge according to the amount of electricity consumed in one month. The unit price of the metered electricity charge is a coefficient multiplied by the amount of electricity consumed in one month, and is the price per unit amount of electricity used to derive the basic electricity charge. The renewable energy surcharge is a charge for the use of electricity generated by renewable energy. The unit price of the renewable energy surcharge is a coefficient multiplied by the amount of electricity consumed in one month, and is the price per unit amount of electricity used to derive the renewable energy surcharge.

[0029] The monthly electricity bill can be calculated by adding together the basic electricity charge, which is determined based on the contracted power, the electricity metered charge, which is the unit price of the electricity metered charge multiplied by the monthly electricity consumption, and the renewable energy surcharge, which is the unit price of the renewable energy surcharge multiplied by the monthly electricity consumption.

[0030] Fig. 2 is a diagram showing an example of the gas fee table 76. In the example of Fig. 2, the gas basic fee column and the gas metered rate unit price column do not contain specific numerical values, but in reality, preset numerical values ​​are entered. Hereinafter, for ease of explanation, the gas metered rate unit price may be referred to as the gas metered rate unit price.

[0031] As shown in Fig. 2, in gas fee table 76, the basic gas fee and the unit price of the gas metered fee correspond one-to-one, and a set of the basic gas fee and the unit price of the gas metered fee is set for each range of monthly gas consumption. For example, in the example of Fig. 2, the range of monthly gas consumption is divided into six levels, from "A" to "F." In this case, six patterns of sets of the basic gas fee and the unit price of the gas metered fee are set, from "A" to "F."

[0032] The basic gas fee is set in stages according to the amount of gas consumed in a month. For example, the basic gas fee is set to a higher value as the amount of gas consumed increases. Also, the increase in the basic gas fee may be greater, for example, as the amount of gas consumed increases.

[0033] The gas metered rate is added to the basic gas rate according to the amount of gas consumed. The unit price of the gas metered rate is a coefficient multiplied by the amount of gas consumed in one month, and is the price per unit amount of gas consumed to derive the gas metered rate, and is set in stages according to the amount of gas consumed in one month. For example, the unit price of the gas metered rate is set to a lower value as the amount of gas consumed increases. Also, for example, within a standard medium range of gas consumption, the range of increase in the unit price of the gas metered rate may be narrow, and the range of increase in the unit price of the gas metered rate may be wider as the amount of gas consumed becomes extremely low or extremely high.

[0034] The monthly gas fee can be calculated by multiplying the monthly gas consumption amount by the unit price of the gas metered rate corresponding to the monthly gas consumption amount, and adding the result to the basic gas fee corresponding to the monthly gas consumption amount.

[0035] Returning to FIG. 1, the server control device 64 is composed of a processor and a memory that stores a program. The server control device 64 controls the entire management server 16 by the processor executing the program. For example, the server control device 64 functions as an operation ratio derivation unit 80 and an operation map generation unit 82 by the processor executing the program.

[0036] The operation ratio derivation unit 80 derives the operation ratio between the EHP 10 and the GHP 12. The operation ratio indicates a combination of the load factor of the EHP 10 and the load factor of the GHP 12. For example, when the load factor of the EHP 10 is 60% and the load factor of the GHP 12 is 60%, the operation ratio means "EHP:GHP=60:60". The derivation of the operation ratio will be described in detail later.

[0037] The operation map generating unit 82 generates an operation map based on the operation ratio derived by the operation ratio derivation unit 80 , and transmits the generated operation map to the EHP 10 and the GHP 12 .

[0038] FIG. 3 is a diagram showing an example of an operation map. Note that FIG. 3 illustrates the air conditioning load as a ratio. As shown in FIG. 3, the operation map is one-to-one associated with the operation ratio, the air conditioning load, and time. In the operation map, a schedule of the load rate of the EHP 10 and the load rate of the GHP 12 corresponding to the air conditioning load is defined for one day at 30-minute intervals. For example, if the air conditioning load is greater than 50% and is equal to or less than 60% at 13:00, the EHP will be operated at a load rate of 60%, and the GHP will be operated at a load rate of 60%.

[0039] The EHP control unit 38 receives an operation map including information on the operation ratio, and operates the EHP 10 at the load factor of the EHP 10 indicated in the operation map. The GHP control unit 48 receives an operation map including information on the operation ratio, and operates the GHP 12 at the load factor of the GHP 12 indicated in the operation map.

[0040] In this way, the server control device 64 derives the operation ratio of the EHP 10 and the GHP 12, and instructs the derived operation ratio through the operation map to the EHP 10 and the GHP 12. As a result, the EHP 10 and the GHP 12 operate at the instructed operation ratio.

[0041] 4 is a flowchart for explaining the determination of the operation ratio and the generation of the operation map in the first embodiment. For convenience of explanation, the current time is assumed to be the first day of the month. Hereinafter, the month to which the current time belongs may be referred to as the current month.

[0042] When a predetermined timing arrives, such as midnight on the first day of the month, the operation ratio derivation unit 80 acquires the past performance value of the air conditioning load corresponding to the current month from the performance value data 70 in the storage device 62 (S10). The past performance value corresponding to the current month may be, for example, the same month of the previous year from the current month.

[0043] Here, for example, a ratio between the load factor of the EHP 10 and the load factor of the GHP 12 that is estimated to result in a relatively low energy charge for the operation of the EHP 10 and the GHP 12 based on the history of the past operation maps is prepared in advance as a candidate. For example, when the load factor of the EHP 10 is 60% and the load factor of the GHP 12 is 60%, the ratio prepared as a candidate is 1:1.

[0044] The operation ratio derivation unit 80 extracts and provisionally sets one ratio from a plurality of ratios prepared in advance (S11).

[0045] The operation ratio derivation unit 80 allocates the acquired past performance values ​​of the air conditioning load to the load factor of the EHP 10 and the load factor of the GHP 12 at the provisionally set ratio (S12). As a result, operation ratio candidates of a pattern according to the provisionally set ratio and the past performance values ​​of the air conditioning load are generated.

[0046] The operation ratio derivation unit 80 derives a predicted value of the gas consumption for the current month based on the load factor of the GHP 12 as a result of the apportionment (S13). For example, the operation ratio derivation unit 80 acquires a predicted value of the outside air temperature at the installation position of the GHP 12 from a server device that provides a weather forecast, via the Internet, etc. The operation ratio derivation unit 80 reads out the COP characteristic data 72 for the GHP 12 stored in the storage device 62. The operation ratio derivation unit 80 derives a COP at the load factor of the GHP 12 for each hour of the day from the load factor of the GHP 12 as a result of the apportionment, the acquired predicted value of the outside air temperature, and the COP characteristic data 72 for the GHP 12. The operation ratio derivation unit 80 divides the load factor of the GHP 12 by the COP at the load factor of the GHP 12 to derive the gas consumption for each hour of the day. The operation ratio derivation unit 80 derives the gas consumption by time of day for all days of the current month, and adds them up to derive a predicted value of the gas consumption for the current month.

[0047] The operation ratio derivation unit 80 also derives a predicted value of the power consumption for the current month based on the load factor of the EHP 10 as a result of the apportionment (S14). For example, the operation ratio derivation unit 80 reads out the COP characteristic data 72 for the EHP 10 stored in the storage device 62. The operation ratio derivation unit 80 derives the COP at the load factor of the EHP 10 for each hour of the day from the load factor of the EHP 10 as a result of the apportionment, the predicted value of the acquired outside air temperature, and the COP characteristic data 72 for the EHP 10. The operation ratio derivation unit 80 divides the load factor of the EHP 10 by the COP at the load factor of the EHP 10 to derive the power consumption for each hour of the day. The operation ratio derivation unit 80 derives the power consumption for each hour of the day for all days of the current month and adds them up to derive the predicted value of the power consumption for the current month.

[0048] The operation ratio derivation unit 80 derives a predicted value of the gas fee for the current month based on the predicted value of the gas consumption for the current month and the gas fee table 76 (S15). For example, the operation ratio derivation unit 80 reads out the gas fee table 76 stored in the storage device 62. The operation ratio derivation unit 80 specifies a gas basic fee and a gas metered fee unit price based on the predicted value of the gas consumption for the current month and the gas fee table 76. The operation ratio derivation unit 80 multiplies the gas metered fee unit price corresponding to the predicted value of the gas consumption for the current month by the predicted value of the gas consumption for the current month to derive a gas metered fee. The operation ratio derivation unit 80 adds the gas metered fee corresponding to the predicted value of the gas consumption for the current month to the gas basic fee corresponding to the predicted value of the gas consumption for the current month to derive a predicted value of the gas fee for the current month.

[0049] The operation ratio derivation unit 80 also derives a predicted value of the electricity charge for the current month based on the predicted value of the electricity consumption for the current month and the electricity charge table 74 (S16). For example, the operation ratio derivation unit 80 reads out the electricity charge table 74 stored in the storage device 62. The operation ratio derivation unit 80 multiplies the unit price of the electricity metered charge by the predicted value of the electricity consumption for the current month to derive the electricity metered charge. The operation ratio derivation unit 80 multiplies the unit price of the renewable energy surcharge by the predicted value of the electricity consumption for the current month to derive the renewable energy surcharge. The operation ratio derivation unit 80 adds up the electricity basic charge, the electricity metered charge, and the renewable energy surcharge to derive the predicted value of the electricity charge for the current month.

[0050] The operation ratio derivation unit 80 adds the predicted value of the gas fee for the current month and the predicted value of the electricity fee for the current month to derive a predicted value of the energy fee for the current month (S17). The operation ratio derivation unit 80 associates the derived predicted value of the energy fee for the current month with the generated operation ratio and stores it in the storage device 62 or memory (S18).

[0051] The operation ratio derivation unit 80 determines whether or not there are any remaining ratios that have not yet been provisionally set among the multiple ratios prepared in advance (S19).

[0052] If it is determined that there is a remaining ratio (YES in S19), the operation ratio derivation unit 80 extracts one ratio from the remaining ratios that have not yet been provisionally set and provisionally sets it (S11). Then, the operation ratio derivation unit 80 repeatedly executes the processes from step S12 onwards.

[0053] In this way, the operation ratio derivation unit 80 allocates the past actual values ​​of the air conditioning load proportionally to the load factor of the EHP 10 and the load factor of the GHP 12, and generates a plurality of patterns of candidates for the operation ratio between the EHP 10 and the GHP 12. The operation ratio derivation unit 80 derives a predicted value of the energy fee for each of the plurality of patterns of candidate operation ratios.

[0054] In step S19, if it is determined that there are no remaining ratios (NO in S19), the operation ratio derivation unit 80 identifies the energy fee that has the smallest predicted value for the energy fee for the current month from among multiple candidate operation ratio patterns (S20).

[0055] The operation ratio derivation unit 80 determines the operation ratio candidates corresponding to the identified energy fees as the operation ratios to be instructed to the EHP 10 and the GHP 12 (S21).

[0056] After the operation ratios are derived by the operation ratio derivation unit 80, the operation map generation unit 82 generates an operation map based on the derived operation ratios (S22), and transmits the generated operation map to the EHP 10 and the GHP 12.

[0057] As described above, in the air conditioning system 1 of the first embodiment, for each of the multiple operation ratio candidates, a predicted gas fee for the current month is derived based on the load factor of the GHP 12, a predicted electricity fee for the current month is derived based on the load factor of the EHP 10, and a predicted energy fee for the current month is derived from the predicted gas fee and the predicted electricity fee. In the air conditioning system 1 of the first embodiment, the operation ratio candidate that minimizes the predicted energy fee for the current month among the multiple operation ratio candidates is determined as the operation ratio to be instructed to the EHP 10 and GHP 12.

[0058] As a result, in the air conditioning system 1 of the first embodiment, a predicted value of the gas fee for the current month is derived, so that a realistic minimum energy fee can be appropriately derived taking into consideration issues such as the boundary of the basic gas fee. As a result, in the air conditioning system 1 of the first embodiment, the accuracy of the operation ratio of the EHP 10 and the GHP 12 that minimizes the energy fee can be improved. Therefore, the air conditioning system 1 of the first embodiment can improve the economic merits of the user.

[0059] Furthermore, in the air conditioning system 1 of the first embodiment, a predicted value of the gas fee for the current month is derived by taking into account not only the gas metered rate but also the basic gas rate. Therefore, in the first embodiment, a more appropriate predicted value of the gas fee can be derived. As a result, in the air conditioning system 1 of the first embodiment, the accuracy of the operation ratio of the EHP 10 and the GHP 12 can be further improved.

[0060] (Modification of the first embodiment) In the above-described first embodiment, an example of deriving the operation ratio of the EHP and the GHP when the current time is the first day of the month has been shown. In contrast, as a modification of the first embodiment, when the current time is a day in the middle of the month, the operation ratio deriving unit 80 of the server control device 64 may derive the operation ratio as follows.

[0061] FIG. 5 is a flowchart for explaining the determination of the operation ratio and the generation of the operation map in the modified example of the first embodiment. Here, it is assumed that the current time is a day in the middle of the current month. Hereinafter, the remaining period of the current month from the current time may be referred to as the unexpired period (the unexpired period of the current month), and the period of the current month that has already passed may be referred to as the elapsed period (the elapsed period of the current month). The operation ratio derivation unit 80 in the modified example of the first embodiment may execute the series of processes in FIG. 5 every time a day of the current month passes.

[0062] At a preset time, such as midnight, on each day during the month, the operation ratio derivation unit 80 acquires the actual value of the air conditioning load for a specific past period corresponding to the unexpired period of the month from the actual value data 70 in the storage device 62 (S30). The specific period may be, for example, a period corresponding to the unexpired period of the same month of the previous year from the current month.

[0063] The operation ratio derivation unit 80 extracts one ratio from a plurality of ratios prepared in advance, and provisionally sets the ratio as the ratio for the unexpired period (S31).

[0064] The operation ratio derivation unit 80 allocates the acquired actual value of the air conditioning load for a specific period in the past to the load factor of the EHP 10 and the load factor of the GHP 12 at the provisionally set ratio (S32). This generates candidates for operation ratios of a pattern according to the provisionally set ratio and the actual value of the air conditioning load for a specific period in the past.

[0065] The operation ratio derivation unit 80 derives a predicted value of gas consumption for the unexpired period of the current month based on the load factor of the GHP 12 as a result of the apportionment (S33). For example, the operation ratio derivation unit 80 derives the COP at the load factor of the GHP 12 for each hour of the unexpired period from the load factor of the GHP 12 as a result of the apportionment, the predicted value of the acquired outside air temperature, and the COP characteristic data 72 for the GHP 12. The operation ratio derivation unit 80 divides the load factor of the GHP 12 by the COP at the load factor of the GHP 12 to derive the gas consumption for each hour of the unexpired period. The operation ratio derivation unit 80 derives a predicted value of gas consumption for the unexpired period of the current month by adding the gas consumption for each hour of the unexpired period for the current month.

[0066] The operation ratio derivation unit 80 also derives a predicted value of gas consumption for the unexpired period of the current month based on the load factor of the EHP 10 as a result of the apportionment (S34). For example, the operation ratio derivation unit 80 derives the COP at the load factor of the EHP 10 for each hour of the unexpired period from the load factor of the EHP 10 as a result of the apportionment, the predicted value of the acquired outside air temperature, and the COP characteristic data 72 for the EHP 10. The operation ratio derivation unit 80 divides the load factor of the EHP 10 by the COP at the load factor of the EHP 10 to derive the power consumption for each hour of the unexpired period. The operation ratio derivation unit 80 derives a predicted value of power consumption for the unexpired period of the current month by adding the power consumption for each hour of the unexpired period for the current month.

[0067] Here, the server control device 64 causes the storage device 62 to store the actual gas consumption amount and the actual power consumption amount for that day at the end of the day.

[0068] The operation ratio derivation unit 80 acquires from the memory device 62 the actual gas consumption values ​​for each day of the elapsed period of the current month, which is the period that has already passed, and derives the actual gas consumption values ​​for the elapsed period of the current month by adding the acquired daily gas consumption values ​​for the elapsed period of the current month (S35).

[0069] The operation ratio derivation unit 80 acquires from the storage device 62 the actual value of the power consumption for each day of the elapsed period of the current month, and derives the actual value of the power consumption for the elapsed period of the current month by adding the acquired daily power consumption for the elapsed period of the current month (S36).

[0070] The operation ratio derivation unit 80 adds the predicted gas consumption amount for the unexpired period of the current month to the actual gas consumption amount for the elapsed period of the current month to derive a predicted gas consumption amount for the current month (S37).

[0071] The operation ratio derivation unit 80 adds the predicted value of power consumption for the unexpired period of the current month to the actual value of power consumption for the elapsed period of the current month to derive a predicted value of power consumption for the current month (S38).

[0072] The operation ratio derivation unit 80 derives a predicted value of the gas fee for the current month based on the predicted value of the gas consumption for the current month and the gas fee table 76 (S39). For example, the operation ratio derivation unit 80 identifies a basic gas fee and a gas metered rate unit price based on the predicted value of the gas consumption for the current month and the gas fee table 76. The operation ratio derivation unit 80 multiplies the predicted value of the gas consumption for the current month by the gas metered rate unit price corresponding to the predicted value of the gas consumption for the current month to derive the gas metered rate. The operation ratio derivation unit 80 adds the gas metered rate corresponding to the predicted value of the gas consumption for the current month to the gas basic rate corresponding to the predicted value of the gas consumption for the current month to derive a predicted value of the gas fee for the current month.

[0073] The operation ratio derivation unit 80 derives a predicted value of the electricity charge for the current month based on the predicted value of the electricity consumption for the current month and the electricity charge table 74 (S40). For example, the operation ratio derivation unit 80 multiplies the unit price of the electricity metered charge by the predicted value of the electricity consumption for the current month to derive the electricity metered charge. The operation ratio derivation unit 80 multiplies the unit price of the renewable energy surcharge by the predicted value of the electricity consumption for the current month to derive the renewable energy surcharge. The operation ratio derivation unit 80 adds the electricity base charge, the electricity metered charge, and the renewable energy surcharge to derive the predicted value of the electricity charge for the current month.

[0074] The operation ratio derivation unit 80 adds the predicted value of the gas fee for the current month and the predicted value of the electricity fee for the current month to derive a predicted value of the energy fee for the current month (S41). The operation ratio derivation unit 80 associates the derived predicted value of the energy fee for the current month with the generated operation ratio and stores it in the storage device 62 or memory (S42).

[0075] The operation ratio derivation unit 80 determines whether or not there are any remaining ratios that have not yet been provisionally set among the multiple ratios prepared in advance (S43).

[0076] If it is determined that there is a remaining ratio (YES in S43), the operation ratio derivation unit 80 extracts one ratio from the remaining ratios that have not yet been provisionally set, and provisionally sets it as a ratio for the unexpired period (S11). Then, the operation ratio derivation unit 80 repeatedly executes the processes from step S12 onwards.

[0077] In this way, the operation ratio derivation unit 80 generates multiple patterns of candidates for the operation ratio between the EHP 10 and the GHP 12 in the unexpired period by apportioning the actual value of the air conditioning load for a specific period in the past to the load factor of the EHP 10 and the load factor of the GHP 12. The operation ratio derivation unit 80 derives a predicted value of the energy fee for each of the multiple patterns of candidate operation ratios.

[0078] In step S43, if it is determined that there is no remaining ratio (NO in S43), the operation ratio derivation unit 80 identifies the energy fee that has the smallest predicted value for the energy fee for the current month from among multiple candidate operation ratio patterns (S20).

[0079] The operation ratio derivation unit 80 determines the operation ratio candidate corresponding to the identified energy fee as the operation ratio to be instructed to the EHP 10 and the GHP 12 for the unexpired period (S21).

[0080] After the operation ratios are derived by the operation ratio derivation unit 80, the operation map generation unit 82 generates an operation map based on the derived operation ratios (S46), and transmits the generated operation map to the EHP 10 and the GHP 12.

[0081] As described above, in the air conditioning system 1 of the modified first embodiment, for each of the multiple operation ratio candidates in the unexpired period, a predicted gas fee for the current month is derived based on the predicted gas consumption for the unexpired period and the actual gas consumption for the elapsed period, a predicted electricity fee for the current month is derived based on the predicted electricity consumption for the unexpired period and the actual electricity consumption for the elapsed period, and a predicted energy fee for the current month is derived from the predicted gas fee for the current month and the predicted electricity fee for the current month. In the air conditioning system 1 of the modified first embodiment, the operation ratio candidate that has the smallest predicted energy fee for the current month among the multiple operation ratio candidates in the unexpired period is determined as the operation ratio to be instructed to the EHP 10 and the GHP 12 in the unexpired period.

[0082] As a result, in the air conditioning system 1 of the modified example of the first embodiment, even if the current point in time is in the middle of the current month, the actual gas consumption amount for the elapsed period is reflected in the predicted value of the gas fee for the current month, so that the predicted value of the gas fee for the current month can be derived more realistically. As a result, in the air conditioning system 1 of the modified example of the first embodiment, the accuracy of the operation ratio of the EHP 10 and the GHP 12 that minimizes the energy fee can be improved.

[0083] For example, suppose that the current month belongs to a period in which cooling is performed, and at the beginning of the month, the operation ratio was specified based on the air conditioning load of the previous year, but in reality, the outdoor temperature was higher than the previous year, and the air conditioning load increased. In this example, at the beginning of the month, the actual gas consumption at the beginning of the month is greater than the gas consumption estimated at the beginning of the month. Then, at the beginning of the month, an estimated gas fee for the current month is derived from the actual gas consumption that is greater than the initially estimated gas consumption and the estimated gas consumption for the remaining period of the month.

[0084] As a result, the estimated gas price for the current month is corrected to a more realistic value at the current time, different from the value estimated at the beginning of the current month. Then, based on the estimated gas price at the current time, the operation ratios to be instructed to EHP 10 and GHP 12 are corrected to the more realistic operation ratios that minimize the price at the current time.

[0085] In the air conditioning system 1 of the modified example of the first embodiment, as in the above-described first embodiment, the accuracy of the operation ratio of the EHP 10 and the GHP 12 that minimizes the energy fee can be improved, thereby improving the economic benefits to the user.

[0086] In the air conditioning system 1 of the modified example of the first embodiment, the above-mentioned derivation of the operation ratio is repeatedly performed each time a day passes during the current month, so that the estimated value of the gas fee for the current month can be successively corrected to a more realistic estimated value of the gas fee for the current month as the days pass during the current month. As a result, the air conditioning system 1 of the modified example of the first embodiment can indicate a more appropriate operation ratio in accordance with reality.

[0087] In the first embodiment and the modified example of the first embodiment, the operation ratio is derived such that the energy fee reflecting the actual gas consumption amount during the elapsed period of the current month is minimized. However, the operation ratio derivation unit 80 may derive an operation ratio such that the energy consumption amount is minimized by reflecting the actual gas consumption amount during the elapsed period of the current month. In addition, the operation ratio derivation unit 80 may derive an operation ratio such that the CO2 (carbon dioxide) emission amount is minimized by reflecting the actual gas consumption amount during the elapsed period of the current month. In addition, when a consumer to which the air conditioning system 1 is applied is provided with gas appliances such as a hot water supply system or a kitchen appliance other than the air conditioning system 1, the predicted value and actual value of the gas consumption may include the gas consumption of these appliances such as the hot water supply system or the kitchen appliance.

[0088] Second embodiment Incidentally, in a conventional air conditioning system, a target power demand set value is set as an upper limit of allowable power consumption in the entire building of a customer to which the air conditioning system is applied. The target power demand set value is set to, for example, the contracted power of the customer. In an air conditioning system having an EHP and a GHP, the operation ratio of the EHP and the GHP is controlled so that the power consumption in the entire building of the customer does not exceed the target power demand set value, in other words, the contracted power.

[0089] As described above, the basic electricity charge in the electricity rate table is set according to the contracted power. Therefore, if the contracted power can be reduced, the electricity charge can be reduced, and the economic merit for the consumer can be improved.

[0090] Fig. 6 is a schematic block diagram showing an example of the configuration of an air conditioning system 200 according to the second embodiment. In the air conditioning system 200 of the second embodiment, the operation of the server control device 64 of the management server 16 and the data stored in the storage device 62 of the management server 16 are different from those of the air conditioning system 1 of the first embodiment, but the system configuration is the same as that of the first embodiment shown in Fig. 1. Therefore, in the second embodiment, the points different from the first embodiment will be described, and the points in common with the first embodiment will not be described for the sake of convenience.

[0091] Hereinafter, the power consumption of the entire building of the customer to which the air conditioning system 200 is applied may be referred to as the total power consumption. The total power consumption includes the power consumption of various electrical loads in the building of the customer, such as home appliances and lighting. The total power consumption also includes the power consumption of the EHP 10 and the power consumption of the GHP 12 in the air conditioning system 200 applied to the building of the customer.

[0092] The power consumption of the GHP 12 is, for example, about the power consumption required to ignite the gas engine 40, and is therefore extremely small compared to the total power consumption, regardless of the load factor of the GHP 12. In addition, even if the load factor of the GHP 12 changes, the amount of change in the power consumption of the GHP 12 is small.

[0093] In contrast, the power consumption of the EHP 10 includes the power to operate the electric motor 30, so it increases as the load factor of the EHP 10 increases and has a large contribution to the overall power consumption. Therefore, if the power consumption of the EHP 10 increases significantly, the overall power consumption also increases significantly in accordance with the increase in the power consumption of the EHP 10. Conversely, by suppressing the power consumption of the EHP 10, the overall power consumption can also be suppressed.

[0094] The storage device 62 stores total power consumption data 210. The total power consumption data 210 is data in which past actual values ​​of total power consumption in the entire building in which the EHP 10 and the GHP 12 are installed are associated with date and time. In other words, the total power consumption data 210 includes a history of changes in total power consumption in the past.

[0095] The server control device 64 periodically acquires the total power consumption from, for example, a meter installed at the power receiving point where the building is connected to the power grid, and associates the acquired total power consumption with the date and time of acquisition and stores it in the storage device 62 as total power consumption data 210.

[0096] The server control device 64 also functions as a set value derivation unit 220 by the processor executing a program. The set value derivation unit 220 derives a target power demand set value. The derivation of the target power demand set value will be described in detail later.

[0097] The operation ratio derivation unit 80 derives an operation ratio between the EHP 10 and the GHP 12 such that the total power consumption does not exceed the target power demand set value derived by the set value derivation unit 220. The operation map generation unit 82 generates an operation map based on the derived operation ratio, and transmits the generated operation map to the EHP 10 and the GHP 12. As a result, the EHP 10 and the GHP 12 are operated at an operation ratio such that the total power consumption does not exceed the target power demand set value.

[0098] Fig. 7 is a diagram for explaining an outline of a method for determining a target power demand setting value. Fig. 7 shows an example of a transition of the actual value of the total power consumption in a predetermined period of the past, which is included in the total power consumption data 210. The predetermined period of the past is, for example, the most recent one year from the present time to one year ago, but is not limited to this example and may be any period of the past.

[0099] Hereinafter, for convenience of explanation, the time point at which the actual value of the total power consumption becomes maximum in a predetermined period of time in the past may be referred to as the peak time. In the example of Fig. 7, time point T10 is the peak time in the predetermined period of time in the past.

[0100] A solid line A10 in Fig. 7 indicates a current target power demand set value before a new target power demand set value is derived. As shown in Fig. 7, the actual value of the total power consumption at the peak time is equal to or less than the current target power demand set value.

[0101] Here, it can be assumed that the total power consumption from the present time to the future will change in the same way as the change in the actual value of the total power consumption in a predetermined period in the past. In this case, if the total power consumption can be reduced at a future time point corresponding to a past peak time, it is possible to reduce the future target power demand setting value. Hereinafter, for convenience of explanation, the future time point corresponding to the past peak time may be referred to as a future peak time.

[0102] For example, if the power consumption of the EHP 10, which is included in the actual value of the overall power consumption during the peak time, can be suppressed during the future peak time, it is possible to suppress the overall power consumption during the future peak time. However, since there is a risk that the air conditioning load during the future peak time cannot be handled simply by suppressing the power consumption of the EHP 10, the load factor of the GHP 12 is increased by an amount equivalent to the load factor of the EHP 10 that is reduced by suppressing the power consumption. Even if the load factor of the GHP 12 is increased, it can be considered that the overall power consumption does not substantially increase.

[0103] That is, the set value derivation unit 220 prorates the actual value of the air conditioning load during the past peak hours, which can be regarded as an estimated value of the air conditioning load during the future peak hours, so that the load factor of the GHP 12 is maximized and the load factor of the EHP 10 is minimized. The set value derivation unit 220 derives the total power consumption after suppression based on such proration. This makes it possible to suppress the total power consumption during the future peak hours while responding to the air conditioning load during the future peak hours.

[0104] The total power consumption after the suppression during the future peak can be assumed to be the maximum estimated value of the total power consumption in the future. Therefore, the set value derivation unit 220 determines the total power consumption after the suppression during the future peak as a new target power demand set value in the future. Then, the operation ratio is controlled so that the total power consumption does not exceed the new target power demand set value in the future.

[0105] In addition, depending on the overall power consumption after suppression derived based on the actual air conditioning load value during peak hours, the overall power consumption at other times during a specified period in the past, excluding peak hours, may exceed the overall power consumption after suppression.

[0106] Hereinafter, for convenience of explanation, the peak time when the total power consumption in a given period of the past is the maximum value may be referred to as the first peak time. Also, the time when the actual value of the total power consumption in a given period of the past is the maximum value excluding the first peak time, that is, the peak time next to the first peak time, may be referred to as the second peak time. In the example of FIG. 7, time T10 is the first peak time, and time T20 is the second peak time. Also, the future time corresponding to the first peak time in the past may be referred to as the first future peak time, and the future time corresponding to the second peak time in the past may be referred to as the second future peak time.

[0107] A solid line A20 in Fig. 7 shows an example of the total power consumption after first suppression, which is the total power consumption after suppression derived for the first peak time. In the example of Fig. 7, the actual value of the total power consumption at time T20, which is the second peak time, exceeds the total power consumption after first suppression. In such a case, there is a risk that the total power consumption at the second future peak time corresponding to the second peak time will exceed the total power consumption after first suppression.

[0108] Therefore, similarly to the first future peak time, the load factor of the GHP 12 is increased for the second future peak time to suppress the power consumption of the EHP 10. That is, the set value derivation unit 220 prorates the actual value of the air conditioning load during the past second peak time, which can be regarded as an estimated value of the air conditioning load during the second future peak time, so that the load factor of the GHP 12 is maximized and the load factor of the EHP 10 is minimized. The set value derivation unit 220 derives the overall power consumption after suppression during the second future peak time based on such proration.

[0109] The dashed-dotted line A30 in Fig. 7 shows a first example of the second post-suppression total power consumption, which is the post-suppression total power consumption derived for the second peak time. As shown by the dashed-dotted line A30 in Fig. 7, when the second post-suppression total power consumption is equal to or less than the first post-suppression total power consumption, even if the first post-suppression total power consumption is determined as a new future target power demand setting value, if the total power consumption is actually suppressed at the second future peak time, the total power consumption can be prevented from exceeding the target power demand setting value even at the second future peak time. In such a case, the setting value derivation unit 220 determines the first post-suppression total power consumption as the new future target power demand setting value.

[0110] A dashed line A32 in Fig. 7 shows a second example of the total power consumption after the second suppression. As shown by the dashed line A32 in Fig. 7, when the total power consumption after the second suppression exceeds the total power consumption after the first suppression, even if the total power consumption is actually suppressed at the first future peak, the total power consumption at the second future peak will exceed the total power consumption after the first suppression. In that case, if the total power consumption after the first suppression is determined as a new target power demand setting value, it is estimated that the total power consumption will exceed the new target power demand setting value at the second future peak.

[0111] Therefore, when the second post-restriction total power consumption exceeds the first post-restriction total power consumption, the set value derivation unit 220 determines the second post-restriction total power consumption, which is the larger total power consumption, as a new target power demand set value. This makes it possible to appropriately control the total power consumption so that it does not exceed the new target power demand set value in the future.

[0112] Here, an example up to the second peak has been described. However, if it is estimated that the power consumption will exceed the total power consumption after the suppression even after the next peak after the second peak, the derivation of the total power consumption after the suppression may be repeated in the same manner as for the first peak and the second peak.

[0113] That is, the set value derivation unit 220 may identify peak times at which the actual value of the overall power consumption in a predetermined period in the past is maximum, in descending order of the overall power consumption. The set value derivation unit 220 may derive the overall power consumption after suppression for each peak time, and identify the maximum value of each of the overall power consumption after suppression. The set value derivation unit 220 may determine whether there is an actual value of the overall power consumption that exceeds the maximum value of the overall power consumption after suppression, excluding the identified peak times in the predetermined period in the past. When it is determined that there is no actual value of the overall power consumption that exceeds the maximum value of the overall power consumption after suppression, the set value derivation unit 220 may determine the maximum value of the overall power consumption after suppression as the target power demand set value.

[0114] 8 is a flowchart explaining the flow of the operation of the set value derivation unit 220. The set value derivation unit 220 starts a series of processes for deriving a target power demand set value when a specific timing arrives. The specific timing may be any preset timing such as the first day of a month or the first day of a year, or may be a timing when a specific input operation is input by a user of the air conditioning system 200, for example.

[0115] When a specific timing arrives, the setting value derivation unit 220 identifies a specific past period based on the current date and time, and obtains the actual value of the total power consumption for the specific past period from the total power consumption data 210 in the storage device 62 (S50).

[0116] The set value derivation unit 220 identifies the peak time based on the acquired actual values ​​of the total power consumption (S51). For example, the set value derivation unit 220 determines the date and time associated with the maximum value of the acquired actual values ​​of the total power consumption as the peak time.

[0117] As will be described later, the peak time identification in step S51 may be repeatedly executed under predetermined conditions, which will be described later. In the first peak time identification, a first peak time is identified, and in the second peak time identification, a second peak time is identified, and so on. Each time step S51 is repeated, the next peak time is identified in descending order of total power consumption.

[0118] The set value derivation unit 220 acquires the actual value of the air conditioning load and the actual value of the operation ratio during the peak time identified in step S51 from the actual value data 70 in the storage device 62 (S52).

[0119] The set value derivation unit 220 derives the actual value of the power consumption of the EHP 10 from the actual value of the EHP load factor included in the acquired actual value of the operation ratio during peak hours (S53).

[0120] The set value derivation unit 220 apportions the acquired actual value of the air conditioning load at the peak so that the load factor of the GHP 12 is maximized and the load factor of the EHP 10 is minimized (S54). For example, when the actual value of the air conditioning load is equal to or less than the maximum output of the GHP 12 when the load factor of the GHP 12 is at its maximum value, the set value derivation unit 220 sets the load factor of the GHP 12 to a value such that the output of the GHP 12 is substantially the same as the actual value of the air conditioning load, and sets the load factor of the EHP 10 to zero. Also, when the actual value of the air conditioning load exceeds the maximum output of the GHP 12 when the load factor of the GHP 12 is at its maximum value, the set value derivation unit 220 sets the load factor of the GHP 12 to its maximum value, and sets the load factor of the EHP 10 to a value equivalent to the value obtained by subtracting the maximum output of the GHP 12 from the actual value of the air conditioning load.

[0121] By apportioning in this manner, an operation ratio at which the load factor of the EHP 10 is suppressed is derived, which is an estimate of the operation ratio at a future peak hour corresponding to the peak hour identified in step S51.

[0122] The set value derivation unit 220 derives the post-restriction power consumption of the EHP 10 from the post-restriction load factor of the EHP 10 included in the operation ratio derived by proportional division in step S54 (S55).

[0123] The set value derivation unit 220 subtracts the suppressed power consumption of the EHP 10 derived in step S55 from the actual value of the power consumption of the EHP 10 derived in step S53 to derive a difference value of the power consumption of the EHP 10 (S56).

[0124] The set value derivation unit 220 subtracts the difference value of the power consumption of the EHP 10 derived in step S56 from the actual value of the total power consumption at the peak time identified in step S51 to derive the post-suppression total power consumption at a future peak time corresponding to the peak time identified in step S51 (S57). For example, if a first peak time is identified in step S51, a first post-suppression total power consumption for the first peak time is derived, and if a second peak time is identified in step S51, a second post-suppression total power consumption for the second peak time is derived.

[0125] The set value derivation unit 220 stores the total power consumption after suppression derived in step S57 in the storage device 62 or memory.

[0126] The set value derivation unit 220 identifies the maximum value of the post-suppression total power consumption from the derived post-suppression total power consumption (S59). For example, when a first peak time is identified in step S51, since there is only one derived post-suppression total power consumption, the first post-suppression total power consumption related to the first peak time is identified as the maximum value. Also, for example, when a second peak time is identified in step S51, the larger of the first post-suppression total power consumption and the second post-suppression total power consumption is identified as the maximum value. In this manner, the maximum value of the post-suppression total power consumption is updated.

[0127] The set value derivation unit 220 determines whether or not there is an actual value of the overall power consumption that exceeds the maximum value identified in step S59 during a predetermined past period, excluding the actual value of the overall power consumption at the peak identified in step S51 (S60). For example, when the first peak is identified in step S51, the set value derivation unit 220 determines in step S60 whether or not there is an actual value of the overall power consumption that exceeds the first post-suppression overall power consumption, excluding the overall power consumption at the first peak.

[0128] If it is determined that there is an actual value of the total power consumption that exceeds the maximum value (YES in S60), the set value derivation unit 220 excludes the peak time identified in step S51 from the predetermined past period (S61). Then, the set value derivation unit 220 identifies a peak time from within the predetermined past period other than the excluded peak time (S51). For example, if the first peak time is excluded, the date and time associated with the actual value of the total power consumption that is the next maximum value after the actual value of the total power consumption at the first peak time is identified as the peak time (i.e., the second peak time).

[0129] In addition, since an identified peak time (e.g., the first peak time) is excluded in step S61, if a second peak time (i.e., the second peak time) is identified in step S51, the first peak time is excluded from the comparison target in the second step S60, and the comparison process of step S60 can be performed appropriately.

[0130] If it is determined that there is no actual value of the total power consumption that exceeds the maximum value (NO in S60), the setting value derivation unit 220 determines the maximum value of the total power consumption after suppression identified in step S59 as the target power demand setting value (S62), and ends the series of processes.

[0131] In this way, the set value derivation unit 220 repeats the identification of the peak time and the derivation of the post-suppression overall power consumption until there is no actual value of the overall power consumption that exceeds the maximum value of the post-suppression overall power consumption, and updates the maximum value of the post-suppression overall power consumption. The set value derivation unit 220 determines the maximum value of the post-suppression overall power consumption when there is no actual value of the overall power consumption that exceeds the maximum value of the post-suppression overall power consumption as a new target power demand set value.

[0132] Generally, the contracted power can be renewed every year, and is renewed according to the maximum value of the actual total power consumption during the most recent year based on the renewal time.

[0133] For example, assume that the target power demand set value can be changed from 350kW to 300kW by determining a new target power demand set value. Then, after changing the target power demand set value, the operation ratio is controlled so as not to exceed the changed target power demand set value, thereby suppressing the maximum value of the overall power consumption to 300kW until the next renewal of the contract power. Then, when the time comes to renew the contract power, the contract power is renewed from 350kW to 300kW. Reducing the contract power in this way allows the power fee to be reduced.

[0134] As described above, in the air conditioning system 200 of the second embodiment, the peak time when the actual value of the total power consumption in a predetermined past period is maximum is specified, and the actual value of the power consumption of the EHP at the peak time is derived. In the air conditioning system 200 of the second embodiment, the actual value of the air conditioning load at the peak time is apportioned so that the load rate of the GHP is maximized and the load rate of the EHP is minimized, and the power consumption of the EHP after suppression is derived. In the air conditioning system 200 of the second embodiment, the power consumption of the EHP after suppression is subtracted from the actual value of the power consumption of the EHP at the peak time to derive the difference value of the power consumption of the EHP, and the total power consumption after suppression is derived by subtracting the difference value of the power consumption of the EHP from the actual value of the total power consumption at the peak time. In the air conditioning system 200 of the second embodiment, the total power consumption after suppression is determined as the target power demand setting value.

[0135] As a result, in the air conditioning system 200 of the second embodiment, the target power demand setting value can be set to a more appropriate value. As a result, in the air conditioning system 200 of the second embodiment, it is possible to reduce the contracted power, and the power fee can be suppressed. Therefore, according to the air conditioning system 200 of the second embodiment, it is possible to improve the economic merit of the user.

[0136] In the air conditioning system 200 of the second embodiment, the operation ratio after the target power demand set value is determined may be derived in the same manner as in the first embodiment and the modified example of the first embodiment described above.

[0137] Third embodiment Incidentally, since GHPs have a gas engine, they have many mechanical moving parts, and maintenance such as part replacement is periodically performed. For example, the first maintenance of a GHP is performed when the accumulated value of the GHP's operating time since the start of its introduction reaches 10,000 hours, and maintenance is performed every time the accumulated value of the GHP's operating time increases by 10,000 hours. Hereinafter, for ease of explanation, the accumulated time of the GHP's operating time over a predetermined period of time may be referred to as the accumulated operating time. Also, the number of maintenances may be referred to as the number of maintenances.

[0138] On the other hand, since the EHP 10 does not have a gas engine 40 and has few mechanical moving parts, maintenance such as periodic part replacement is not required.

[0139] Furthermore, the contract period for an air conditioning system between a provider and a user is the period during which the performance of the air conditioning system is guaranteed, for example, 15 years from the start of installation of the air conditioning system. The period during which the performance of an air conditioning system having an EHP and a GHP is guaranteed may be set based on the period during which the performance of a GHP that requires maintenance, among the devices that make up the air conditioning system, is guaranteed. Hereinafter, for ease of explanation, the period during which performance is guaranteed may be referred to as the performance guarantee period.

[0140] During the performance guarantee period of the GHP (in other words, the performance guarantee period of the air conditioning system), when the timing for GHP maintenance arrives according to the accumulated operation time of the GHP, the GHP maintenance is performed. When the GHP maintenance is performed, the user is forced to pay the cost of the GHP maintenance.

[0141] In light of this, if the number of GHP maintenance operations during the GHP's performance guarantee period can be reduced, no fees will be charged for the reduced maintenance operations, thereby improving the economic benefits for users.

[0142] Fig. 9 is a schematic block diagram showing an example of the configuration of an air conditioning system 300 according to the third embodiment. In the air conditioning system 300 of the third embodiment, the operation of the server control device 64 of the management server 16 and the data stored in the storage device 62 of the management server 16 are different from those of the air conditioning system 1 of the first embodiment, but the system configuration is the same as that of the first embodiment shown in Fig. 1. Therefore, in the third embodiment, differences from the first embodiment will be described, and descriptions of commonalities with the first embodiment will be omitted for convenience.

[0143] The storage device 62 stores driving time data 310. The driving time data 310 is at least a past actual value of the driving time of the GHP 12 associated with a date and time. That is, the driving time data 310 includes a history of changes in the driving time of the GHP 12 in the past.

[0144] The server control device 64 measures, for example, the operation time of the GHP 12 during the operation of the GHP 12. At the end of a day, the server control device 64 associates the operation time of the GHP 12 measured on that day with the day and stores it in the storage device 62 as operation time data 310.

[0145] The server control device 64 also functions as an operation time control unit 320 by the processor executing a program. The operation time control unit 320 controls the operation time of the GHP 12 so as to reduce the number of maintenance operations of the GHP 12. The operation time control unit 320 will be described in detail later.

[0146] 10 is a flowchart explaining the flow of processing related to the control of the operation time of the GHP 12. When a specific timing arrives, the operation time control unit 320 starts a series of processing related to the control of the operation time of the GHP 12. The specific timing may be, for example, any timing set in advance, such as the first day of a month or the first day of a year, or may be a timing when a specific input operation is input by the user of the air conditioning system 300 or the like.

[0147] As mentioned above, the performance guarantee period of the GHP 12 is the period from the start of the introduction of the GHP 12 to the end of the performance guarantee period. Hereinafter, the period from the start of the introduction of the GHP 12 to the present time within the performance guarantee period of the GHP 12 may be referred to as the elapsed period (elapsed guarantee period). The period from the present time to the end of the performance guarantee period of the GHP 12 may be referred to as the unexpired period (unexpired guarantee period).

[0148] When a specific timing arrives, the operation time control unit 320 acquires the actual value of the past operation time of the GHP 12 during the period that has elapsed since the start of the introduction of the GHP 12 to the present time from the operation time data 310 in the storage device 62 (S70).

[0149] The operation time control unit 320 derives a performance value of the cumulative operation time of the GHP 12 during the elapsed period by adding up the acquired past operation time performance values ​​over the elapsed period (S71).

[0150] The operation time control unit 320 derives an estimate of the cumulative operation time of the GHP 12 in the unexpired period from the present time to the end of the performance guarantee period of the GHP 12 based on the actual value of the past operation time of the GHP 12 (S72). For example, the operation time control unit 320 adds the actual value of the operation time of the GHP 12 in the most recent predetermined period (e.g., the most recent one year) based on the present time over the most recent predetermined period to derive the actual value of the cumulative operation time of the GHP 12 in the most recent predetermined period. The operation time control unit 320 adds the actual value of the cumulative operation time of the GHP 12 in the most recent predetermined period for the unexpired period to derive an estimate of the cumulative operation time of the GHP 12 in the unexpired period.

[0151] The operating time control unit 320 adds the actual value of the cumulative operating time of GHP 12 for the elapsed period derived in step S71 and the estimated value of the cumulative operating time of GHP 12 for the unelapsed period derived in step S72 to derive an estimated value of the cumulative operating time of GHP 12 for the performance guarantee period of GHP 12 (S73).

[0152] The operation time control unit 320 derives an estimate of the number of maintenances of the GHP 12 during the performance guarantee period of the GHP 12 based on the estimate of the cumulative operation time of the GHP 12 during the performance guarantee period of the GHP 12 (S74). For example, the operation time control unit 320 derives an estimate of the number of maintenances by dividing the estimate of the cumulative operation time of the GHP 12 during the performance guarantee period of the GHP 12 by the cumulative operation time of the GHP 12 required until one maintenance occurs.

[0153] In the illustrated method of deriving the estimated value of the number of maintenances by division, the decimal points are discarded and the estimated value of the number of maintenances is derived as an integer. For example, assume that the cumulative operating time of the GHP 12 required until one maintenance occurs is 10,000 hours. In an example where the estimated cumulative operating time of the GHP 12 during the performance guarantee period of the GHP 12 is 31,000 hours, the estimated value of the number of maintenances is 3 times, and in an example where the estimated cumulative operating time of the GHP 12 during the performance guarantee period of the GHP 12 is 29,000 hours, the estimated value of the number of maintenances is 2 times.

[0154] The operation time control unit 320 derives a threshold value of the accumulated operation time that allows the number of maintenance operations to be reduced by one from the derived estimated value of the number of maintenance operations (S75).

[0155] As described above, the cumulative operating time of the GHP 12 required until one maintenance is required is assumed to be 10,000 hours. If the estimated number of maintenances is three, the estimated cumulative operating time during the performance guarantee period can be reduced by one to two, if the estimated cumulative operating time during the performance guarantee period is set to less than 30,000 hours. Therefore, the operating time control unit 320 sets the threshold value of the cumulative operating time to a time obtained by subtracting a predetermined margin from 30,000 hours. The predetermined margin is, for example, 1,000 hours, but may be set to any time that takes into account the error of the future cumulative operating time in the unexpired period. In this example, the operating time control unit 320 sets the threshold value of the cumulative operating time to 29,000 hours, obtained by subtracting 1,000 hours from 30,000 hours.

[0156] The operating time control unit 320 subtracts the threshold value of the cumulative operating time derived in step S75 from the estimated value of the cumulative operating time for the performance guarantee period derived in step S73, to derive the reduction time, which is the cumulative operating time of the GHP 12 that needs to be reduced in order to reduce the number of maintenance visits by one (S76).

[0157] The operation time control unit 320 derives a boundary value of the air conditioning load rate indicating the air conditioning load rate at which switching between the sole operation of the EHP 10 and the sole operation of the GHP 12 is performed, based on the reduction time derived in step S76 and the length of the unexpired period (S77).

[0158] Fig. 11 is a diagram for explaining the derivation of boundary values ​​of the air conditioning load factor. In Fig. 11, the horizontal axis indicates the air conditioning load factor, and the vertical axis indicates the efficiency of each device, the EHP 10 and the GHP 12. More specifically, in Fig. 11, solid line B10 and dashed line B12 indicate the efficiency of the EHP 10 with respect to the air conditioning load factor, solid line B20, dashed line B22 and dashed line B24 indicate the efficiency of the GHP 12 with respect to the air conditioning load factor, and solid line B30 indicates the total efficiency of the EHP 10 and the GHP 12 with respect to the air conditioning load factor.

[0159] 11, the air conditioning load factor "L10" corresponds to the intersection of the curve showing the efficiency of the EHP 10 and the curve showing the efficiency of the GHP 12. Moreover, the air conditioning load factor "L20" corresponds to the intersection of the curve showing the efficiency of the GHP 12 and the curve showing the combined efficiency of the EHP 10 and the GHP 12.

[0160] When the air conditioning load factor is "L10" or less, the system is set to an EHP solo operation state in which the GHP 12 is stopped and only the EHP 10 is operating. On the other hand, when the air conditioning load factor is greater than "L10" and is "L20" or less, the system is set to a GHP solo operation state in which the EHP 10 is stopped and only the GHP 12 is operating. Also, when the air conditioning load factor is "L20" or more, the system is set to a mixed operation state in which both the EHP 10 and the GHP 12 are operating.

[0161] In this case, switching between EHP independent operation and GHP independent operation will occur at the air conditioning load factor "L10." In other words, the air conditioning load factor "L10" indicates the boundary value.

[0162] Now, let us assume that the boundary value of the "L10" position is shifted to the "L30" position, which has a higher air conditioning load factor than "L10". This will expand the range of air conditioning load factors that will result in the EHP being in solo operation, and as a result, the range of air conditioning load factors that will result in the GHP being in solo operation will be narrowed. If the range of air conditioning load factors that will result in the GHP being in solo operation is narrowed, the frequency with which the GHP 12 is operated will decrease, and the operating time of the GHP 12 will be reduced.

[0163] Therefore, in step S77 of FIG. 10, the driving time control unit 320 derives a boundary value so that the boundary value is greater than the current value.

[0164] For example, the driving time control unit 320 may derive the boundary value such that the shift amount from the current boundary value increases as the reduced time derived in step S76 increases.

[0165] Also, for example, the driving time control unit 320 may derive the boundary value such that the shift amount from the current boundary value increases as the length of the unelapsed time increases.

[0166] More specifically, for example, a boundary value derivation map in which the reduction time, the length of the remaining time, and the boundary value of the air conditioning load factor are associated with each other may be stored in advance in the storage device 62. The operation time control unit 320 may derive the boundary value from the derived reduction time, the length of the actual remaining time, and the boundary value derivation map.

[0167] In the above embodiment, the boundary value is derived based on both the reduced time and the length of the remaining time. However, the operation time control unit 320 may derive the boundary value based on at least the reduced time, regardless of the length of the remaining time.

[0168] After deriving the boundary value, the operation time control unit 320 determines whether the derived boundary value is equal to or less than a predetermined value set in advance (S78). The predetermined value here may be set to an air conditioning load factor at which the efficiency of the EHP 10 is at an allowable lower limit, such as 30%. In other words, step S78 corresponds to determining whether the range of air conditioning load factors that will result in an EHP solo operation state when the derived boundary value is used is within a range in which the efficiency of the EHP is allowable.

[0169] If it is determined that the boundary value is equal to or less than the predetermined value (YES in S78), the operation time control unit 320 determines that the efficiency of the EHP 10 in an EHP-only operation state will be within the allowable range even if the boundary value is updated, and therefore determines that the number of maintenance operations can be reduced by one (S79).Then, the operation time control unit 320 updates the boundary value of the air conditioning load factor to the value derived in step S77 (S80), and proceeds to the processing of step S83.

[0170] On the other hand, if it is determined that the boundary value exceeds the predetermined value (NO in S78), the operation time control unit 320 determines that it is impossible to reduce the number of maintenance operations because updating the boundary value would drastically reduce the efficiency of the EHP 10 in an EHP-only operation state (S81).Then, the operation time control unit 320 does not update the boundary value derived in step S77, but maintains the boundary value of the air conditioning load factor at the current value (S82), and proceeds to the processing of step S82.

[0171] In step S83, the operation ratio derivation unit 80 derives the operation ratio between the EHP 10 and the GHP 12 based on the boundary value of the air conditioning load factor (S83). Then, the operation map generation unit 82 generates an operation map based on the derived operation ratio (S84), and ends the series of processes. The generated operation map is transmitted to the EHP 10 and the GHP 12. As a result, the EHP 10 and the GHP 12 are operated according to the received operation map.

[0172] For example, if the boundary value is updated in step S80, an operation ratio is derived in step S83 based on the updated boundary value. As a result, an operation ratio at which the load rate of the GHP 12 is zero in a range where the air conditioning load rate is equal to or less than the updated boundary value is derived and reflected in the operation map. In such an operation map, the range of the air conditioning load rate at which the load rate of the GHP 12 is zero is wide. Therefore, by operating the GHP 12 according to such an operation map, the operation time of the GHP can be reduced.

[0173] Also, if the boundary value is maintained in step S82, an operation load factor is derived based on the maintained boundary value in step S83. As a result, an operation ratio at which the load factor of the GHP 12 is zero in a range where the air conditioning load factor is equal to or less than the maintained boundary value is derived and reflected in the operation map. In such an operation map, the range of the air conditioning load factor at which the load factor of the GHP 12 is zero is narrower than in the mode in which the boundary value is updated. In this case, the operation time of the GHP 12 is not reduced compared to the mode in which the boundary value is updated. However, in this case, the advantage of preventing the adverse effects caused by the extreme decrease in efficiency of the EHP 10 due to the boundary value being forcibly updated is greater.

[0174] If it is determined that the maintenance count cannot be reduced, the boundary value is maintained at the current value in step S82. However, if it is determined that the maintenance count cannot be reduced, the operation time control unit 320 may change the boundary value of the air conditioning load factor to the initial value.

[0175] As described above, in the air conditioning system 300 of the third embodiment, an estimated value of the cumulative operation time of the performance guarantee period, which is the period during which the performance of the GHP 12 is guaranteed, is derived based on the actual value of the past operation time of the GHP 12. In the air conditioning system 300 of the third embodiment, an estimated value of the number of maintenances of the GHP 12 during the performance guarantee period is derived based on the estimated value of the cumulative operation time of the performance guarantee period. In the air conditioning system 300 of the third embodiment, a reduction time, which is the cumulative operation time of the GHP 12 that needs to be reduced in order to reduce the number of maintenances, is derived based on the estimated value of the number of maintenances. In the air conditioning system 300 of the third embodiment, a boundary value indicating the air conditioning load rate at which switching is performed between the independent operation of the EHP 10 and the independent operation of the GHP 12, is derived so as to be a value larger than the current value based on the reduction time. In the air conditioning system 300 of the third embodiment, an operation ratio is derived based on the boundary value.

[0176] As a result, in the air conditioning system 300 of the third embodiment, the operation time of the GHP from the present time onward is reduced, and the number of maintenance operations for the GHP 12 during the performance guarantee period can be reduced. As a result, in the air conditioning system 300 of the third embodiment, the costs of the air conditioning system 300 can be reduced by the amount of the reduced maintenance fees. Therefore, according to the air conditioning system 300 of the third embodiment, it is possible to improve the economic merit for the user.

[0177] In the air conditioning system 300 of the third embodiment, the operation ratio after updating the boundary value of the air conditioning load factor or after maintaining the boundary value of the air conditioning load factor may be derived in the same manner as in the first embodiment and the modified example of the first embodiment described above.

[0178] (Fourth embodiment) As described above, in the first embodiment and the modified example of the first embodiment, the operation ratio that minimizes the energy fee is determined and the operation map is generated with a focus on the energy fee for one month. Therefore, for convenience of explanation, the process of identifying the minimum energy fee based on the predicted value of the energy fee for one month and generating the operation map in at least either the first embodiment or the modified example of the first embodiment (i.e., the process in Figs. 4 and 5) may be referred to as the energy fee minimization process. In addition, the energy fee minimization process in the first embodiment may be referred to as the first energy fee minimization process, and the energy fee minimization process in the modified example of the first embodiment may be referred to as the second energy fee minimization process.

[0179] In the second embodiment, the target power demand set value is reduced, and an operation ratio is determined and an operation map is generated so as to suppress the contract power. For this reason, the process of deriving the target power demand set value in the second embodiment (i.e., the process in FIG. 8) may be referred to as a target power demand set value derivation process for convenience of explanation.

[0180] In the third embodiment, it is determined whether the number of maintenance times of the GHP 12 can be reduced, and if it is determined that the number of maintenance times can be reduced, an operation ratio is determined and an operation map is generated so as to reduce the operation time of the GHP 12. For this reason, for convenience of explanation, the process in the third embodiment of determining whether the number of maintenance times of the GHP 12 can be reduced and generating an operation map for reducing the operation time of the GHP 12 if it is determined that the number of maintenance times can be reduced (i.e., the process in FIG. 10) may be referred to as a maintenance count process.

[0181] In each of the above-described embodiments, it is possible to suppress the charges from the individual viewpoints that each embodiment focuses on. However, rather than limiting itself to optimizing the charges for individual conditions as in each of these embodiments, it is desirable to more realistically maximize the economic benefits of users by taking multiple conditions into consideration.

[0182] Therefore, in the fourth embodiment, a process that integrates the energy fee minimization process, the target power demand setting value derivation process, and the maintenance count process in each of the above-mentioned embodiments is performed, and an operation map that minimizes the energy fee is specified.

[0183] Fig. 12 is a schematic block diagram showing an example of the configuration of an air conditioning system 400 according to the fourth embodiment. In the air conditioning system 400 of the fourth embodiment, the operation of the server control device 64 of the management server 16 and the data stored in the storage device 62 of the management server 16 are different from those of the air conditioning system 1 of the first embodiment, but the system configuration is the same as that of the first embodiment shown in Fig. 1. Therefore, in the fourth embodiment, the points different from the first embodiment will be described, and the points in common with the first embodiment will not be described for the sake of convenience.

[0184] The storage device 62 stores total power consumption data 210 and driving time data 310. The total power consumption data 210 is the same as the total power consumption data 210 described in the second embodiment. The driving time data 310 is the same as the driving time data 310 described in the third embodiment.

[0185] The server control device 64 also functions as a set value derivation unit 220, an operation time control unit 320, and an integrated processing unit 420 as a result of the processor executing a program. The set value derivation unit 220 basically derives a target power demand set value, similar to the set value derivation unit 220 of the second embodiment. The operation time control unit 320 basically controls the operation time of the GHP 12 so as to reduce the number of maintenance operations for the GHP 12, similar to the operation time control unit 320 of the third embodiment.

[0186] The integration processing unit 420 performs processing for integrating the energy fee minimization processing, the target power demand setting value derivation processing, and the maintenance frequency processing.

[0187] Fig. 13 is a flowchart explaining the flow of the process executed in the fourth embodiment. The series of processes in Fig. 13 is started when a specific timing arrives. The specific timing may be any timing set in advance, such as the first day of the month, the first day of the year, or a day in the middle of the month, or may be a timing when a specific input operation is input by the user of the air conditioning system 300, for example.

[0188] When a specific timing arrives, the set value derivation unit executes a target power demand set value derivation process (S100) for deriving a target power demand set value. In the target power demand set value derivation process (S100), the process shown in FIG. 8 is performed.

[0189] The target power demand set value derived by the target power demand set value derivation process (S100) means a lower limit value to which the target power demand set value can be reduced. In this case, the target power demand set value is not limited to being reduced to the target power demand set value derived by the target power demand set value derivation process (S100), and can be set to any value equal to or greater than the target power demand set value derived by the target power demand set value derivation process (S100), for example.

[0190] For example, assume that the current target power demand set value before the target power demand set value derivation process (S100) is performed is "100 kW" and that the target power demand set value "90 kW" is derived as a result of the target power demand set value derivation process (S100). In this example, the target power demand set value can be lowered to "90 kW", but it is also possible to set the target power demand set value to, for example, "91 kW" or "92 kW".

[0191] In consideration of this, the integrated processing unit 420 determines a plurality of change values ​​of the target power demand set value, with the target power demand set value obtained by executing the target power demand set value derivation process (S100) set as the lower limit (S101). For example, in an example in which the target power demand set value "90 kW" is derived, "90 kW", "91 kW", "92 kW", etc. are determined as the change values ​​of the target power demand set value.

[0192] The integration processing unit 420 extracts any one of the change values ​​of the multiple target power demand set values ​​(S102).

[0193] The operation ratio derivation unit 80 executes an energy fee minimization process (S103) based on the change in the target power demand setting value extracted in step S102. In the energy fee minimization process (S103), basically, at least one of a first energy fee minimization process shown in Fig. 4 and a second energy fee minimization process shown in Fig. 5 is performed.

[0194] More specifically, in an example of performing the first energy fee minimization process in the energy fee minimization process (S103), in the process of deriving a predicted value of one month's gas consumption and a predicted value of one month's power consumption by apportioning the past actual values ​​of the air conditioning load, the apportionment ratio is corrected by the target power demand set value extracted in step S102. Then, the predicted value of one month's gas consumption and one month's power consumption are derived by apportioning the past actual values ​​of the air conditioning load by the corrected ratio. In this way, in the first energy fee minimization process, a predicted value of one month's energy fee reflecting the target power demand set value extracted in step S102 is derived. As a result, an operation ratio at which the predicted value of the energy fee is minimized in a state where the target power demand set value extracted in step S102 is reflected is determined, and an operation map reflecting this is generated.

[0195] In addition, in an example of performing the second energy fee minimization process in the energy fee minimization process (S103), in the process of deriving the predicted value of the gas consumption for the unexpired period and the predicted value of the power consumption for the unexpired period by apportioning the actual value of the air conditioning load for the specific period in the past, the apportionment ratio for the unexpired period is corrected by the target power demand set value extracted in step S102. Then, the predicted value of the gas consumption for the unexpired period and the power consumption for the unexpired period are derived by apportioning the actual value of the air conditioning load for the specific period in the past by the corrected ratio. In this way, in the second energy fee minimization process, the predicted value of the energy fee for one month reflecting the target power demand set value extracted in step S102 is derived. As a result, the operation ratio at which the predicted value of the energy fee is minimized in a state where the target power demand set value extracted in step S102 is reflected is determined, and an operation map reflecting this is generated.

[0196] The integrated processing unit 420 stores the minimum energy fee, the operation ratio, and the operation map derived by the energy fee minimization process (S103) in the storage device 62 in association with the target power demand setting value extracted in step S102 (S104).

[0197] Next, the operation time control unit 320 executes a maintenance count process (S105) based on the operation map derived by the energy fee minimization process (S103). In the maintenance count process (S105), the process shown in FIG. 10 is basically performed.

[0198] More specifically, in the process of deriving an estimate of the cumulative operation time of the GHP 12 for the unexpired period, an estimate of the daily operation time of the GHP 12 is derived based on the operation map derived by the energy fee minimization process (S103). The estimate of the daily operation time of the GHP derived in this way is added over the unexpired period to derive an estimate of the cumulative time of the GHP 12 for the unexpired period. In this way, a boundary value of the air conditioning load factor is derived with the operation map derived by the energy fee minimization process (S103) reflected, and it is determined whether the number of maintenance times for the GHP 12 can be reduced.

[0199] If it is determined that the number of maintenance operations can be reduced, the operation ratio is derived in a state where the operation map derived by the energy fee minimization process (S103) is reflected and the updated boundary value of the air conditioning load factor is reflected, and an operation map reflecting this is generated. If it is determined that the number of maintenance operations cannot be reduced, the boundary value of the air conditioning load factor is not updated, and therefore an operation map that is substantially the same as the operation map derived by the energy fee minimization process (S103) is generated.

[0200] The integrated processing unit 420 stores in the storage device 62 (S106) the result of determining whether or not the maintenance count can be reduced, the boundary value of the air conditioning load factor, the operation ratio, and the operation map derived by the maintenance count processing (S105), in association with the target power demand setting value extracted in step S102.

[0201] Next, the integrated processing unit 420 determines whether it is determined in the maintenance count process (S105) that the maintenance count can be reduced (S107).

[0202] When it is determined that the number of maintenance operations can be reduced (YES in S107), the operation ratio derivation unit 80 executes an energy fee minimization process (S108). In the energy fee minimization process (S108), basically, at least one of a first energy fee minimization process shown in FIG. 4 and a second energy fee minimization process shown in FIG. 5 is performed.

[0203] More specifically, in an example of performing the first energy fee minimization process in the energy fee minimization process (S108), in the process of deriving a one-month predicted gas consumption value and a one-month predicted power consumption value by apportioning the past actual values ​​of the air conditioning load, the apportionment ratio is corrected by the operation ratio in the operation map derived in the maintenance count process (S105). Then, the one-month predicted gas consumption value and the one-month predicted power consumption value are derived by apportioning the past actual values ​​of the air conditioning load by the corrected ratio. In this way, in the first energy fee minimization process, a one-month predicted energy fee value reflecting the operation map derived in the maintenance count process (S105) is derived. As a result, an operation ratio that minimizes the predicted energy fee value in a state where the operation map derived in the maintenance count process (S105) is reflected is determined, and an operation map reflecting this is generated.

[0204] In addition, in an example of performing the second energy fee minimization process in the energy fee minimization process (S108), in the process of deriving the predicted value of the gas consumption for the unexpired period and the predicted value of the power consumption for the unexpired period by apportioning the actual value of the air conditioning load for the specific period in the past, the apportionment ratio for the unexpired period is corrected by the operation ratio in the operation map derived in the maintenance count process (S105). Then, the predicted value of the gas consumption for the unexpired period and the power consumption for the unexpired period are derived by apportioning the actual value of the air conditioning load for the specific period in the past by the corrected ratio. In this way, in the second energy fee minimization process, a predicted value of the energy fee for one month reflecting the operation map derived in the maintenance count process (S105) is derived. As a result, the operation ratio at which the predicted value of the energy fee is minimized in a state where the operation map derived in the maintenance count process (S105) is reflected is determined, and an operation map reflecting this is generated.

[0205] The integrated processing unit 420 associates the minimum energy fee, operation ratio, and operation map derived by the energy fee minimization process (S108) with the target power demand setting value extracted in step S102 and stores them in the storage device 62 (S109), and proceeds to processing of step S110.

[0206] Furthermore, in step S107, if it is determined that the number of maintenance operations cannot be reduced (NO in S107), the integration processing unit 420 proceeds to the process of step S110.

[0207] In step S110, integration processing unit 420 determines whether or not there are any remaining change values ​​that have not yet been extracted among the multiple change values ​​of the target power demand setting value (S110).

[0208] If it is determined that there are remaining change values ​​(YES in S110), the integration processing unit 420 extracts one change value from the remaining change values ​​that have not yet been extracted (S102). Then, based on the change value of the target power demand setting value extracted in step S102, the energy fee minimization process (S103) and subsequent processes are performed.

[0209] In this way, in the air conditioning system 400 of the fourth embodiment, the target power demand set value is changed in a plurality of patterns, and the energy fee minimization process (S13) and the maintenance count process (S105) are performed for each of the plurality of patterns of the target power demand set value. As a result, for each pattern of the target power demand set value, an operation ratio and an operation map that minimize the predicted value of the energy fee in a state where the target power demand set value is reflected are derived.

[0210] Furthermore, in the air conditioning system 400 of the fourth embodiment, when it is determined that the maintenance frequency of the GHP 12 can be reduced in the maintenance frequency process (S105) performed for each of a plurality of patterns of target power demand set values, the energy fee minimization process (S108) is executed again in the pattern of the target power demand set value that is determined to be reduceable. This allows the operation ratio and operation map that reflect the target power demand set value and minimizes the predicted value of the energy fee in a state that reflects the condition that allows the maintenance frequency to be reduced.

[0211] If it is determined in step S110 that there are no remaining change values ​​(NO in S110), the integrated processing unit 420 identifies the operation map that provides the smallest predicted energy fee value among the predicted energy fee values ​​for each pattern of the target power demand setting value stored in step S104 and the predicted energy fee values ​​for each pattern of the target power setting value stored in step S109 that are determined to enable a reduction in the number of maintenance operations (S111).

[0212] In this way, in the air conditioning system 400 of the fourth embodiment, an operation map that minimizes the predicted value of the energy fee for the current month overall is specified while taking into account the conditions of the target power demand set value of multiple patterns and the condition of whether the maintenance frequency can be reduced. The specified operation map is transmitted to the EHP 10 and the GHP 12.

[0213] In addition, in Fig. 13, the target power demand setting value derivation process, the energy fee minimization process, and the maintenance count process are integrated. However, the maintenance count process may be omitted, and the target power demand setting value derivation process and the energy fee minimization process may be integrated. In this case, steps S105 to S109 in Fig. 13 are omitted. Also, the target power demand setting value derivation process may be omitted, and the energy fee minimization process and the maintenance count process may be integrated, or the energy fee minimization process may be omitted, and the target power demand setting value derivation process and the maintenance count process may be integrated.

[0214] As described above, the server control device 64 of the air conditioning system 400 of the fourth embodiment executes an energy fee minimization process based on the target power demand set value for each of a plurality of target power demand set value patterns equal to or greater than the target power demand set value derived by the target power demand set value derivation process, and generates an operation map in which the predicted value of the energy fee is minimized for each pattern of the target power demand set value. The server control device 64 of the air conditioning system 400 of the fourth embodiment identifies an operation map in which the predicted value of the energy fee is minimized among the predicted values ​​of the energy fee for each pattern of the target power demand set value.

[0215] As a result, in the air conditioning system 400 of the fourth embodiment, a better overall operation pattern can be obtained that takes into account not only the condition of the predicted energy fee for the current month, but also the conditions of the target power demand setting values ​​of multiple patterns. Therefore, the air conditioning system 400 of the fourth embodiment can improve the economic merits of the user.

[0216] Furthermore, the server control device 64 of the air conditioning system 400 of the fourth embodiment executes the maintenance count process based on the operation map generated based on the energy fee minimization process for each pattern of the target power demand setting value. When it is determined in the maintenance count process that the number of maintenance events can be reduced, the server control device 64 of the air conditioning system 400 of the fourth embodiment executes the energy fee minimization process based on the operation map generated based on the derived boundary value, and generates an operation map in which the predicted value of the energy fee in a state in which the number of maintenance events can be reduced is minimized. The server control device 64 of the air conditioning system 400 of the fourth embodiment identifies the operation map in which the predicted value of the energy fee is minimized among the predicted values ​​of the energy fee for each pattern of the target power demand setting value and for whether or not the number of maintenance events can be reduced.

[0217] As a result, in the air conditioning system 400 of the fourth embodiment, it is possible to obtain a better overall operation pattern that takes into account not only the condition of the predicted value of the energy fee for the current month, but also the condition of the target power demand setting value of a plurality of patterns and the condition of whether or not the number of maintenance operations can be reduced. Therefore, the air conditioning system 400 of the fourth embodiment can improve the economic merits of the user.

[0218] Although the preferred embodiment of the present invention has been described above with reference to the accompanying drawings, it goes without saying that the present invention is not limited to such an embodiment. It is clear that a person skilled in the art can think of various modifications or alterations within the scope of the claims, and it is understood that these also naturally belong to the technical scope of the present invention.

[0219] For example, a program that causes a computer to function as the server control device 64 and a storage medium, such as a computer-readable flexible disk, a magneto-optical disk, a ROM, a CD, a DVD, or a BD, on which the program is recorded, are also provided. Here, the program refers to a data processing means written in any language or description method.

[0220] It should be noted that each process shown in this specification does not necessarily have to be performed in chronological order according to the order shown in the flowchart, and may include parallel or subroutine processes. [Explanation of symbols]

[0221] 1, 200, 300, 400 Air Conditioning System 10 EHP 12 GHP 30 Electric motor 40 Gas Engine 62 Storage device 64 Server control device

Claims

1. An EHP having at least an electrically driven compressor that compresses a heat medium using an electric motor as a drive source; A GHP having at least an engine-driven compressor that compresses a heat medium using a gas engine as a driving source; a storage device that stores an actual value of an air conditioning load in association with a date and time, and stores an actual value of an overall power consumption, which is the power consumption of an entire building of a consumer, in association with a date and time; a server control device that derives a target power demand setting value, which is an upper limit of allowable power consumption in an entire building of a consumer, derives an operation ratio between the EHP and the GHP based on the target power demand setting value, and instructs the EHP and the GHP of the derived operation ratio; Equipped with The server control device includes: Identifying a peak time when the actual value of the total power consumption during a predetermined period in the past is a maximum value; Derive a performance value of the power consumption of the EHP during the peak period; The actual value of the peak air conditioning load is prorated so that the load rate of the GHP is maximized and the load rate of the EHP is minimized, thereby deriving the power consumption of the EHP after suppression; deriving a difference value of the power consumption of the EHP by subtracting the power consumption of the EHP after the suppression from an actual value of the power consumption of the EHP at the peak; Deriving the overall power consumption after suppression by subtracting a difference value of the power consumption of the EHP from an actual value of the overall power consumption at the peak time; The air conditioning system determines the total power consumption after the reduction as the target power demand setting value.

2. The server control device includes: identifying a first peak time at which the actual value of the total power consumption in a predetermined past period is a maximum value; Deriving an actual value of power consumption of the EHP during the first peak time; The actual value of the air conditioning load during the first peak time is prorated so that the load rate of the GHP is maximized and the load rate of the EHP is minimized, thereby deriving the power consumption of the EHP after suppression regarding the first peak time; subtracting the power consumption of the EHP after the suppression during the first peak time from an actual value of the power consumption of the EHP during the first peak time to derive a difference value of the power consumption of the EHP during the first peak time; deriving a first post-suppression overall power consumption, which is the overall power consumption after suppression for the first peak time, by subtracting a difference value of the power consumption of the EHP for the first peak time from an actual value of the overall power consumption for the first peak time; determining whether there is a result value of the total power consumption that exceeds the first suppression total power consumption in a predetermined past period excluding the first peak time; when it is determined that there is a result value of the overall power consumption that exceeds the first suppression overall power consumption, a second peak time at which the result value of the overall power consumption is a maximum value is identified, excluding the first peak time in a predetermined past period; Deriving an actual value of the power consumption of the EHP during the second peak time; The actual value of the air conditioning load during the second peak time is prorated so that the load rate of the GHP is maximized and the load rate of the EHP is minimized, thereby deriving the power consumption of the EHP after suppression regarding the second peak time; subtracting the power consumption of the EHP after the suppression during the second peak time from an actual value of the power consumption of the EHP during the second peak time to derive a difference value of the power consumption of the EHP during the second peak time; deriving a second post-suppression overall power consumption, which is the overall power consumption after suppression for the second peak time, by subtracting a difference value of the power consumption of the EHP for the second peak time from an actual value of the overall power consumption for the second peak time; The air conditioning system according to claim 1 , wherein the target power demand setting value is determined based on the first post-restriction total power consumption and the second post-restriction total power consumption.

3. The server control device includes: If the second post-reduction total power consumption is equal to or less than the first post-reduction total power consumption, the first post-reduction total power consumption is determined as the target power demand setting value; The air conditioning system according to claim 2 , wherein if the second post-restriction total power consumption exceeds the first post-restriction total power consumption, the second post-restriction total power consumption is determined as the target power demand setting value.

4. The server control device includes: identifying peak times at which the actual value of the total power consumption during a predetermined period in the past is a maximum value in order of the total power consumption; deriving the overall power consumption after the suppression for each of the peak times; Identifying a maximum value of the overall power consumption after each of the suppressions; 2. The air conditioning system according to claim 1, wherein when it is determined that there is no actual value of the overall power consumption that exceeds the maximum value of the overall power consumption after the suppression, excluding the identified peak times in a specified period in the past, the maximum value of the overall power consumption after the suppression is determined as the target power demand setting value.

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