Evaluation device and evaluation method

Abstract

To enable effectiveness of building body cold storage to be determined without actually using the building body cold storage.SOLUTION: An acquisition unit 111 acquires first electric power amount data relating to an electric power amount required for air conditioning control per unit period for each of a plurality of rooms for which an electricity bill did not decrease even though the air conditioning control was performed to lower a room temperature during night than during the day, and second electric power amount data relating to an electric power amount for a room to be evaluated per unit period. A determination unit 112 statistically analyzes the first electric power amount data to determine first characteristic data relating to characteristics of the electric power amount in the room for which the electricity bill did not decrease even though the air conditioning control was performed, and statistically analyzes the second electric power amount data to determine second characteristic data relating to characteristics of the electric power amount in the room to be evaluated. A decision unit 113 decides whether building body cold storage is effective or ineffective for the room to be evaluated based on the first characteristic data and the second characteristic data.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an apparatus and method for evaluating the effectiveness of cold storage in a room housing information and communication devices and the like. [Background technology]

[0002] In server rooms in data centers and other locations, many of the information and communication devices, such as servers, are stored in racks. To prevent breakdowns in the information and communication devices, measures must be taken to reduce the heat generated by the devices, and air conditioners are used to cool them. However, if the temperature inside the server room is kept constant throughout the year, the air conditioner's set temperature will also be constant, resulting in high power consumption and high electricity bills for air conditioning. Therefore, as a means of reducing the electricity bills for air conditioning, for example, a cold storage technology for the building structure, as shown in Patent Document 1, is used.

[0003] With the cold storage system, the server room is cooled by using a larger amount of power at a lower electricity rate during the nighttime electricity rate period. During the daytime electricity rate period, the set temperature is adjusted when the outside temperature starts to rise, and once the adjustment is complete, the set temperature is maintained. This reduces the electricity costs for operating the air conditioner. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Publication No. 2023-43544 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the effectiveness of building structure cold storage varies depending on the machine room to which it is applied. Even if building structure cold storage is implemented, electricity charges may not decrease, and may even increase, depending on the machine room. For this reason, when introducing building structure cold storage to a machine room, it is necessary to actually operate the building structure cold storage to determine its effectiveness, which creates the problem of high implementation costs.

[0006] An object of the present invention is to provide a technical means for determining the effectiveness of cold storage in a building without actually operating the building. [Means for solving the problem]

[0007] An evaluation device according to one embodiment of the present invention includes an acquisition unit that acquires, for each of a plurality of rooms in which electricity bills are not reduced even when air-conditioning control is implemented, such that the room temperature is lower at night than during the day, first electricity amount data regarding the amount of electricity required per unit period for the air-conditioning control and second electricity amount data regarding the amount of electricity required per unit period for the room to be evaluated; a determination unit that determines, by statistically analyzing the first electricity amount data, first characteristic data regarding the characteristics of the amount of electricity for the room in which electricity bills are not reduced even when the air-conditioning control is implemented, and second characteristic data regarding the characteristics of the amount of electricity for the room to be evaluated, by statistically analyzing the second electricity amount data; and a determination unit that determines whether the air-conditioning control is effective or ineffective for the room to be evaluated based on the first characteristic data and the second characteristic data.

[0008] An evaluation method according to one aspect of the present invention acquires, for each of a plurality of rooms in which electricity bills were not reduced even when air-conditioning control was implemented, such that the room temperature was lower at night than during the day, first electricity amount data relating to the amount of electricity required per unit period for the air-conditioning control and second electricity amount data relating to the amount of electricity required per unit period for the room being evaluated; statistically analyzes the first electricity amount data to determine first characteristic data relating to the characteristics of the amount of electricity in the room in which electricity bills were not reduced even when the air-conditioning control was implemented; and statistically analyzes the second electricity amount data to determine second characteristic data relating to the characteristics of the amount of electricity in the room being evaluated; and determines whether the air-conditioning control is effective or ineffective for the room being evaluated based on the first characteristic data and the second characteristic data. [Effects of the Invention]

[0009] According to one aspect of the present invention, the effectiveness of cold energy storage in the building can be determined without actually operating the building cold energy storage. [Brief explanation of the drawings]

[0010] [Figure 1A] 1 is a block diagram showing a configuration of an evaluation system 1 according to an embodiment. [Figure 1B] FIG. 2 is a diagram showing an example of a machine room 20 in which cold storage in the building body is performed. [Figure 1C] FIG. 10 is a diagram illustrating an example of the operation of cold storage in the building body. [Figure 1D] FIG. 10 is a diagram showing the effect of cold storage in the building body in a certain machine room. [Figure 1E] FIG. 1D is a diagram showing the effect of cold storage in the building body in a machine room different from that shown in FIG. [Figure 2] 1 is a block diagram showing the configuration of an evaluation device 10 according to an embodiment. [Figure 3] 4 is a flowchart showing the operation of the evaluation device 10. [Figure 4] 4 is a flowchart showing the operation of the evaluation device 10. [Figure 5] 10 is a diagram illustrating an example of air conditioning power consumption data acquired by the evaluation device 10. FIG. [Figure 6] 1 is a diagram illustrating an example of a load duration curve generated by the evaluation device 10. FIG. [Figure 7] FIG. 10 is a diagram showing the relationship between the kurtosis of the distribution of air conditioning power consumption data and the load duration curve. [Figure 8] FIG. 10 is a diagram showing the relationship between the skewness of the distribution of air conditioning power consumption data and the load duration curve. [Figure 9] FIG. 10 is a diagram showing the relationship between kurtosis and skewness of the distribution of air-conditioning power consumption data in a machine room where cold storage in the building structure is disabled. [Figure 10] FIG. 10 is a diagram showing a method for determining the effectiveness of cold storage in the building body. [Figure 11] FIG. 10 is a diagram showing the effect of the evaluation method according to the embodiment. [Figure 12] FIG. 10 is a diagram showing the effect of the evaluation method according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] A. Embodiment A-1. System Configuration FIG. 1A is a block diagram showing the configuration of an evaluation system 1 according to an embodiment. The evaluation system 1 includes an evaluation device 10 and multiple machine rooms 20. As shown in FIG. 1B (described later), the machine room 20 includes at least an air conditioner, an air conditioner operation control unit, and a rack housing information and communication devices to be cooled. The evaluation device 10 may be connected to the air conditioner operation control units of the multiple machine rooms 2 via a network such as the Internet or a mobile communication network. Alternatively, the evaluation device 10 may be connected to the air conditioner operation control units of the multiple machine rooms 2 via cables such as USB cables. Alternatively, the evaluation device 10 may exchange information with the air conditioner operation control units of the multiple machine rooms 20 via a portable storage medium. The evaluation device 10 according to this embodiment is a device that determines the effectiveness of the building cold storage system in the machine rooms 20 for which the effectiveness has not yet been determined.

[0012] A-2. Machine room 20 1B is a diagram showing an example of a machine room 20 in which cold energy storage is performed in the building frame. As shown in FIG. 1B, one or more air conditioners 22 are arranged on a floor frame 21 of the machine room 20, and double floor panels 23 are arranged at intervals. A plurality of racks 24 accommodating information and communication devices are arranged on the double floor panels 23. The air conditioners 22 supply cool air to the space between the double floor panels 23 and the floor frame 21. This cool air is supplied into the racks 24, where it becomes warm due to heat generated by the information and communication devices, is exhausted above the racks 24, and is collected by the air conditioners 22.

[0013] An air conditioner operation control unit 27 is connected to the air conditioner 22. The air conditioner 22 adjusts the strength of the cold air supplied to the rack 24 so that the temperature inside the rack 24 becomes the set temperature. The air conditioner operation control unit 27 is a means for storing cold in the building by controlling the set temperature for the air conditioner 22 over time.

[0014] FIG. 1C is a diagram showing an example of the operation of building cold storage. In the example of operation shown in FIG. 1C, at 10:00 PM every day, the air conditioner operation control unit 27 starts the first-stage cooling. In this first-stage cooling, the air conditioner operation control unit 27 gradually lowers the set temperature of the air conditioner 22 from 30°C to 27°C by 2:00 AM the next day. At 2:00 AM, the air conditioner operation control unit 27 starts the second-stage cooling. In this second-stage cooling, the air conditioner operation control unit 27 maintains the set temperature at 27°C until 9:00 AM. At 9:00 AM, the air conditioner operation control unit 27 starts mitigation. In this mitigation, the air conditioner operation control unit 27 gradually raises the set temperature of the air conditioner 22 to 30°C by 2:00 PM. At 2:00 PM, the air conditioner operation control unit 27 starts normal operation. In this normal operation, the air conditioner operation control unit 27 maintains the set temperature at 30°C until 10:00 PM. Thereafter, the same operation is repeated.

[0015] Figure 1D shows the results of an investigation into the electricity charges incurred before and during the period when cold storage in the building structure was performed when an air conditioner was operated in a certain machine room. Figure 1E shows the results of an investigation into the electricity charges incurred before and during the period when cold storage in the building structure was performed when an air conditioner was operated in a different machine room from that shown in Figure 1D. The survey results shown in Figure 1D show that when cold storage in the building structure was performed, the electricity charges decreased compared to before cold storage in the building structure. On the other hand, the survey results shown in Figure 1E show that when cold storage in the building structure was performed, the electricity charges increased compared to before cold storage in the building structure.

[0016] As such, there are machine rooms in which cold storage in the building structure is effective, and there are also machine rooms in which cold storage in the building structure is ineffective. The evaluation device 10 determines the effectiveness of cold storage in the building body in the machine room 20.

[0017] A-2. Evaluation device 10 2 is a block diagram showing the configuration of the evaluation device 10. The evaluation device 10 includes a communication device 101, a storage device 102, a processing device 103, and a bus 109 that interconnects these devices.

[0018] The communication device 101 communicates with the air conditioner operation control unit (see FIG. 11) in the machine room 20 via a wired or wireless network, a cable, or a portable storage medium.

[0019] The storage device 102 is a recording medium readable by the processing device 103. The storage device 102 includes, for example, a nonvolatile memory and a volatile memory. The nonvolatile memory is, for example, a ROM (Read Only Memory), an EPROM (Erasable Programmable Read Only Memory), and an EEPROM (Electrically Erasable Programmable Read Only Memory). The volatile memory is, for example, a RAM (Random Access Memory). The storage device 102 stores a program PG1. The program PG1 is a program for operating the evaluation device 10.

[0020] The processing device 103 includes one or more central processing units (CPUs). The one or more CPUs are an example of one or more processors. Each of the processor and the CPU is an example of a computer.

[0021] The processing device 103 reads the program PG1 from the storage device 102. The processing device 103 functions as an acquisition unit 111, a determination unit 112, and a judgment unit 113 by executing the program PG1.

[0022] The acquisition unit 111 acquires first power amount data regarding the amount of power required for air conditioning control per unit period for each of multiple machine rooms 20 (hereinafter referred to as ineffective machine rooms) in which the electricity bill did not decrease even when air conditioning control was implemented to make the room temperature lower at night than during the day, and acquires second power amount data regarding the amount of power required per unit period for the machine room 20 to be evaluated (hereinafter referred to as the machine room to be evaluated).

[0023] Here, the distribution of the first electric energy data of each of the multiple inactive machine rooms has a common characteristic. If the distribution of the second electric energy data of a machine room to be evaluated has a characteristic similar to this common characteristic, the machine room to be evaluated is likely to be an inactive machine room in which structural cold energy storage is ineffective. Therefore, the common characteristic of the distribution of the first electric energy data of the multiple inactive machine rooms is important as a criterion for determining the effectiveness of structural cold energy storage.

[0024] Therefore, the determination unit 112 determines first characteristic data regarding the characteristics of the amount of electricity of an inactive machine room where the electricity bill does not decrease even if air conditioning control is implemented, by statistically analyzing the first electric energy data, and determines second characteristic data regarding the characteristics of the amount of electricity of the machine room to be evaluated, by statistically analyzing the second electric energy data.

[0025] Then, the determining unit 113 determines whether the cold energy storage in the building structure is effective or ineffective for the machine room to be evaluated, based on the first characteristic data and the second characteristic data.

[0026] Specifically, the first characteristic data includes a first index obtained by applying a first statistical process to the first power energy data and a second index obtained by applying a second statistical process to the first power energy data, and the second characteristic data includes a third index obtained by applying the first statistical process to the second power energy data and a fourth index obtained by applying the second statistical process to the second power energy data.

[0027] Then, the judgment unit 113 judges whether the cold storage in the building structure is effective or ineffective for the machine room to be evaluated based on the degree of deviation between the set of the first index and the second index and the set of the third index and the fourth index.

[0028] More specifically, the first statistical process is a process for determining kurtosis, which indicates the degree to which the distribution of frequencies for power amounts per unit time is peaked compared to a normal distribution, and the second statistical process is a process for determining skewness, which indicates the degree to which the distribution of frequencies for power amounts per unit time is asymmetric compared to a normal distribution. Furthermore, the first index is kurtosis corresponding to multiple inactive machine rooms, the second index is skewness corresponding to multiple inactive machine rooms, the third index is kurtosis corresponding to the machine room to be evaluated, and the fourth index is skewness corresponding to the machine room to be evaluated.

[0029] Then, the determination unit 113 determines an approximation curve showing the relationship between kurtosis and skewness based on the first index and the second index. This approximation curve is a curve showing common characteristics of the distribution of the first power amount data of each of the above-mentioned multiple inactive machine rooms.

[0030] The judgment unit 113 determines a reference skewness, which is the skewness on the approximate curve, by substituting the third index into this approximate curve, and determines the degree of deviation, based on the reference skewness and the fourth index, as the degree to which the fourth index deviates from the approximate curve (the degree to which the distribution characteristics of the second electric energy data of the room to be evaluated deviate from the common characteristics of the distribution of the first electric energy data of the inactive machine room).

[0031] The acquisition unit 111, the decision unit 112, and the judgment unit 113 may be configured by circuits such as a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array).

[0032] Next, the operation of this embodiment will be described. Fig. 3 is a flowchart of the advance preparation process P100 executed by the processing device 3 in accordance with the program PG1. Fig. 4 is a flowchart of the evaluation process P200 executed by the processing device 3 in accordance with the program PG1. The processing device 3 executes the advance preparation process P100 of Fig. 3 prior to evaluating the effectiveness of the building body cold storage for the machine rooms 20. The processing device 3 also executes the evaluation process P200 of Fig. 4 to evaluate the effectiveness of the building body cold storage for each machine room 20.

[0033] The processes of steps S101 and S102 in Fig. 3 and the process of step S201 in Fig. 4 are processes performed by the above-mentioned acquisition unit 111. The processes of steps S103 and S104 in Fig. 3 and the process of step S202 in Fig. 4 are processes performed by the above-mentioned determination unit 112. The process of step S105 in Fig. 3 and the processes of steps S203, S204, and S205 in Fig. 4 are processes performed by the above-mentioned determination unit 113.

[0034] First, the advance preparation process P100 in Fig. 3 will be described. In the initial state, normal air cooling without storing cold water in the building structure is performed in the multiple machine rooms 20. The processing device 103 causes some of the multiple machine rooms 20 (hereinafter referred to as first machine rooms) to store cold water in the building structure from winter to spring. Then, the processing device 103 selects 20 to 30 machine rooms 20 for which storing cold water in the building structure is disabled from among the first machine rooms for which the processing device 103 has instructed to store cold water in the building structure (step S101).

[0035] Next, the processing device 103 uses the communication device 101 to collect daily air-conditioning power data (first power data for each hour) from the selected inactive machine room before cold energy storage in the building structure is performed from October 1st to December 31st (step S102). Figure 5 is a diagram showing an example of the first power data collected from a certain inactive machine room. The first power data is time-series data of daily air-conditioning power data.

[0036] Next, the processing device 103 sorts the daily air-conditioning power amount data constituting the first power amount data in descending order and generates a load duration curve for each inactive machine room (step S103). Figure 6 is a diagram illustrating an example of a load duration curve obtained from the first power amount data of Figure 5.

[0037] Next, the processing device 103 calculates the kurtosis x and skewness y of the load duration curve for each inactive machine room using the following equations (1) and (2) (step S104): In the following equations (1) and (2), n is the number of samples, xi is each sample (i.e., the amount of power), s is the standard deviation, and x with a bar at the top is the mean value of the samples.

number

number

[0038] Figure 7 is a diagram showing the relationship between the kurtosis of the distribution of the first electric energy data in the inactive machine room and the load duration curve. Kurtosis x is a first index obtained by applying a first statistical process (Equation (1)) to the first electric energy data obtained from the inactive machine room. Figure 8 is a diagram showing the relationship between the skewness y of the distribution of the first electric energy data in the inactive machine room and the load duration curve. Skewness y is a second index obtained by applying a second statistical process (Equation (2)) to the first electric energy data obtained from the inactive machine room.

[0039] When the distribution of the first power consumption data is more peaked than a normal distribution (data concentrated around the mean), kurtosis takes a positive value, and when the distribution is flatter than a normal distribution (data dispersed from around the mean), kurtosis takes a negative value. In the case of a normal distribution, kurtosis is 0. When kurtosis is small, the cooling capacity is constantly fluctuating. When kurtosis is large, the peak cooling capacity is always at a high load or a low load (fan load).

[0040] When the distribution of the first electric energy data is biased to the left (toward smaller electric energy) than the normal distribution, the skewness y is a positive value. When the distribution of the first electric energy data is biased to the right (toward larger electric energy) than the normal distribution, the skewness y is a negative value. When the distribution of the first electric energy data is a normal distribution, the skewness y is 0. When the skewness is small, the cooling capacity is always in a high load state. When the skewness is large, the cooling capacity is always in a low load state (fan blowing state).

[0041] Next, the processing device 103 performs regression analysis (the least squares method) on the set of kurtosis x and skewness y obtained from each inactive machine room, and generates an approximate curve equation for the kurtosis and skewness (step S105). Figure 9 is a diagram showing an example of the regression analysis in step S105. In step S105, an approximate curve equation that relates the kurtosis x of the distribution of the first power amount data to the skewness y is generated. The above is the processing content of the advance preparation process P100.

[0042] Next, the evaluation process P200 in Fig. 4 will be described. First, the processing device 103 uses the communication device 101 to collect daily air-conditioning power consumption data (second power consumption data for each hour) from 10 / 1 to 12 / 31 before cold storage in the building structure is performed from the machine room to be evaluated (step S201).

[0043] Next, the processing device 103 calculates the kurtosis x and skewness y of the load duration curve for the machine room to be evaluated using the above formulas (1) and (2) (step S202). Here, the kurtosis x is a third index obtained by applying the first statistical processing (formula (1)) to the second electric energy data obtained from the machine room to be evaluated. The skewness y is a fourth index obtained by applying the second statistical processing (formula (2)) to the second electric energy data obtained from the machine room to be evaluated.

[0044] Next, the processing device 103 substitutes the kurtosis x obtained in step S202 into the approximation curve equation obtained in step S105 described above, and calculates the standard skewness ys (step S203).

[0045] Next, the processing device 103 calculates the deviation by dividing the reference skewness ys obtained in step S203 by the skewness y obtained in step S202 (step S204).

[0046] Next, the processing device 104 determines the effectiveness of cold energy storage in the machine room 20 to be evaluated based on the deviation degree obtained in step S204 (step S205). Specifically, if the deviation degree is 0.8 or less or 1.61 or more, the processing device 104 determines that the machine room 20 to be evaluated is suitable for cold energy storage in the machine room 20 to be evaluated.

[0047] Fig. 10 is a diagram showing an example of the determination operation of step S205. In Fig. 10, ysmax is the skewness at which the deviation is 0.8, and ysmin is the skewness at which the deviation is 1.61. If the skewness y is equal to or less than ymin or equal to or greater than ymax, the processing device 103 determines that the machine room to be evaluated is a machine room 20 suitable for storing cold energy in the building structure.

[0048] 11 and 12 are diagrams showing the effects of this embodiment. In this embodiment, the validity of 121 machine rooms was determined, consisting of 45 machine rooms 20 in which building-body cold storage was valid and 76 machine rooms in which building-body cold storage was invalid. As a result, as shown in FIG. 11, the processing device 103 determined 18 of the 45 valid machine rooms 20 as valid machine rooms 20 and 27 as invalid machine rooms 20. Furthermore, the processing device 103 determined 25 of the 76 invalid machine rooms 20 as valid machine rooms 20 and 51 as invalid machine rooms 20.

[0049] The results in Fig. 12 can be obtained from the results in Fig. 11. That is, for the machine rooms 20 where cold storage in the building structure is effective, the accuracy rate (valid match rate) of the processing device 103 was 40.0%, and for the machine rooms 20 where cold storage in the building structure is ineffective, the accuracy rate (invalid match rate) of the processing device 103 was 67.1%. Furthermore, the accuracy rate for both the effective and ineffective machine rooms 20 was 57.0%. Thus, according to this embodiment, a sufficient accuracy rate can be obtained for determining the effectiveness of cold storage in the building structure.

[0050] A-5. Summary of embodiments As described above, in this embodiment, the cold energy storage in the building structure is performed only for some of the machine rooms 20, and the effectiveness of the cold energy storage in the building structure for the remaining machine rooms is determined based on the distribution characteristics of the second electric energy data of the machine rooms without actually operating the cold energy storage in the building structure. Therefore, according to this embodiment, the effectiveness of the cold energy storage in the building structure can be determined without actually operating the cold energy storage in the building structure.

[0051] B: Modified example The following are variations of the above-described embodiment. Two or more variations arbitrarily selected from the following variations may be combined as appropriate within the scope of not mutually contradicting each other.

[0052] B1: First modified example In the above-described embodiment, one evaluation device 10 is provided with the acquisition unit 111, the determination unit 112, and the judgment unit 113, but some of the acquisition unit 111, the determination unit 112, and the judgment unit 113 may be provided in a device other than the evaluation device 10. For example, the acquisition units 111 may be provided in the air conditioner operation control units of multiple machine rooms 20, and the first power amount data and the second power amount data may be sent from these acquisition units 111 to the evaluation device 10.

[0053] B2: Second variant In the above-described embodiment, increasing the number of machine rooms 20 in which cold energy storage is performed in the building body in step S101 of Fig. 3 is undesirable because it increases the number of machine rooms 20 in which cold energy storage in the building body is performed even though cold energy storage in the building body is disabled (i.e., ineffective machine rooms), thereby increasing the amount of wasted power. It is preferable to limit the number of first machine rooms in which cold energy storage in the building body is performed in step S101 to the minimum number of rooms necessary to obtain an accurate approximation curve equation (step S105). Therefore, the advance preparation process P100 (see Fig. 3) in the above-described embodiment is modified as follows.

[0054] First, in step S101, a small number of first machine rooms are selected from the multiple machine rooms 20, and cold energy storage in the building structure is performed. Then, first power amount data is acquired from the inactive machine rooms among the small number of first machine rooms, and an approximate curve formula is obtained. Then, the accuracy rate of the judgment of the effectiveness of cold energy storage in the building structure using this approximate curve formula is calculated.

[0055] If the accuracy rate is not sufficient, a new first machine room is selected, cold storage in the building is performed, and first power amount data is obtained from the previous first machine room and the inactive machine room in the current first machine room, and an approximate curve formula is obtained.The accuracy rate of the judgment of the effectiveness of cold storage in the building using this approximate curve formula is then calculated.

[0056] By repeating this process, the accuracy rate of the effectiveness judgment using the approximate curve formula increases. When the accuracy rate reaches a sufficient value, the system switches to the operation of judging the effectiveness of the building cold storage system using the last obtained approximate curve, without actually operating the building cold storage system.

[0057] C:Other (1) In the above-described embodiment, ROM and RAM are exemplified as storage device 102, but storage device 102 may also be a flexible disk, a magneto-optical disk (e.g., a compact disk, a digital versatile disk, a Blu-ray (registered trademark) disc), a smart card, a flash memory device (e.g., a card, a stick, a key drive), a CD-ROM (Compact Disc-ROM), a register, a removable disk, a hard disk, a floppy (registered trademark) disk, a magnetic strip, a database, a server, or other suitable storage medium.

[0058] (2) In the above-described embodiments, the described information, data, etc. may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0059] (3) In the above-described embodiment, input and output information may be stored in a specific location (for example, a memory) or may be managed using a management table. Input and output information may be overwritten, updated, or added to. Output information may be deleted. Input information may be transmitted to another device.

[0060] (4) In the above-described embodiment, the determination may be made based on a value represented by one bit (0 or 1), a Boolean value (true or false), or a comparison of numerical values ​​(e.g., comparison with a predetermined value).

[0061] (5) The order of the process procedures, sequences, flowcharts, etc. illustrated in the above-described embodiments may be rearranged unless inconsistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0062] (6) Each function illustrated in FIG. 2 is realized by any combination of at least one of hardware and software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, by wire, wirelessly, etc.) and these multiple devices. A functional block may also be realized by combining software with the single device or the multiple devices.

[0063] (7) The programs exemplified in the above-described embodiments should be broadly construed to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., regardless of whether they are called software, firmware, middleware, microcode, hardware description language, or by other names.

[0064] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), then these wired and / or wireless technologies are included within the definition of transmission media.

[0065] (8) In each of the foregoing embodiments, the terms "system" and "network" are used interchangeably.

[0066] (9) The information, parameters, etc. described in this disclosure may be expressed using absolute values, relative values ​​from a predetermined value, or corresponding other information.

[0067] (10) In the above-described embodiments, the air conditioner operation control unit may be a mobile device. Examples of such a mobile device include a mobile station (MS). Those skilled in the art may refer to a mobile station as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other appropriate term. Furthermore, in this disclosure, terms such as "mobile station," "user terminal," "user equipment (UE)," and "terminal" may be used interchangeably.

[0068] (11) In the above-described embodiments, the terms "connected," "coupled," or any variation thereof refers to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access." As used in this disclosure, two elements may be considered to be "connected" or "coupled" to each other using at least one of one or more wires, cables, and printed electrical connections, as well as electromagnetic energy having wavelengths in the radio frequency range, microwave range, and optical (both visible and invisible) range, as some non-limiting and non-exhaustive examples.

[0069] (12) In the above embodiments, the phrase "based on" does not mean "based only on," unless otherwise specified. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0070] (13) As used in this disclosure, the terms "determining" and "determining" may encompass a wide variety of actions. "Determining" and "determining" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (e.g., searching in a table, database, or other data structure), ascertaining, and the like. "Determining" and "determining" may also include receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), and the like. Furthermore, "judgment" and "decision" can include regarding resolving, selecting, choosing, establishing, comparing, etc. as having been "judgment" or "decision." In other words, "judgment" and "decision" can include regarding some action as having been "judgment" or "decision." Furthermore, "judgment (decision)" can be interpreted as "assuming," "expecting," "considering," etc.

[0071] (14) In the above embodiments, when "include," "including," and variations thereof are used, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, the term "or" as used in this disclosure is not intended to be an exclusive or.

[0072] (15) In this disclosure, where articles are added by translation, such as a, an, and the in English, this disclosure may include that the nouns following these articles are plural.

[0073] (16) In this disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "combined" may also be interpreted in the same way as "different."

[0074] (17) Each aspect / embodiment described in this disclosure may be used alone, in combination, or switched depending on the implementation. Notification of predetermined information (e.g., notification that "X is true") is not limited to explicit notification, but may be implicit (e.g., not notifying the predetermined information). [Explanation of symbols]

[0075] 1...evaluation system, 10...evaluation device, 20, 20a...machine room, 21...floor structure, 22...second...air conditioner, 23...double floor panel, 24...rack, 27...air conditioner operation control unit, 101...communication device, 102...storage device, 103...processing device, PG1...program, 111...acquisition unit, 112...determination unit, 113...judgment unit.

Claims

1. an acquisition unit that acquires first power amount data relating to the amount of power required for each unit period for air conditioning control for each of a plurality of rooms for which the electricity bill has not been reduced even when air conditioning control is performed to make the room temperature lower at night than in the daytime, and acquires second power amount data relating to the amount of power required for each unit period for the room to be evaluated; a determination unit that statistically analyzes the first power amount data to determine first characteristic data relating to characteristics of the power amount of a room in which the electricity bill will not be reduced even if the air conditioning control is performed, and that statistically analyzes the second power amount data to determine second characteristic data relating to characteristics of the power amount of the room to be evaluated; a determination unit that determines whether the air conditioning control is valid or invalid for the room to be evaluated based on the first characteristic data and the second characteristic data; An evaluation device comprising:

2. the first characteristic data includes a first index obtained by performing a first statistical process on the first power amount data and a second index obtained by performing a second statistical process on the first power amount data; the second characteristic data includes a third index obtained by applying the first statistical processing to the second power amount data and a fourth index obtained by applying the second statistical processing to the second power amount data; the determination unit determines whether the air conditioning control is effective or ineffective for the room to be evaluated based on a degree of deviation between a set of the first index and the second index and a set of the third index and the fourth index. The evaluation device according to claim 1 .

3. the first statistical processing is processing for determining kurtosis, which indicates how sharp a distribution of frequencies with respect to the amount of power per unit time is compared with a normal distribution; the second statistical processing is processing for determining a skewness indicating a degree of asymmetry of a frequency distribution of the amount of power per unit time compared to a normal distribution; the first index is the kurtosis corresponding to the plurality of rooms, the second index is the skewness corresponding to the plurality of rooms; the third index is the kurtosis corresponding to the room to be evaluated, The fourth index is the skewness corresponding to the room to be evaluated. The evaluation device according to claim 2 .

4. The determination unit determining an approximation curve showing the relationship between the kurtosis and the skewness based on the first index and the second index; determining a reference skewness, which is the skewness on the approximate curve, by substituting the third index into the approximate curve; determining, based on the reference skewness and the fourth index, a degree of deviation of the fourth index from the approximate curve as the deviation degree; The evaluation device according to claim 3 .

5. For each of a plurality of rooms for which the electricity bill did not decrease even when air conditioning control was performed to make the room temperature lower at night than during the day, first power amount data relating to the amount of power required for the air conditioning control per unit period is acquired, and second power amount data relating to the amount of power required for the unit period is acquired for the room to be evaluated; determining first characteristic data relating to characteristics of the amount of power in a room in which the electricity bill will not be reduced even if the air conditioning control is performed by statistically analyzing the first electric energy data; and determining second characteristic data relating to characteristics of the amount of power in the room to be evaluated by statistically analyzing the second electric energy data; determining whether the air conditioning control is effective or ineffective for the room to be evaluated based on the first characteristic data and the second characteristic data; Evaluation method.

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