Refrigerating machine room energy-saving management system based on Internet of Things

Abstract

The invention relates to the technical field of environment monitoring, in particular to a refrigerating machine room energy-saving management system based on the internet of things, which comprises an information acquisition module, a historical data analysis module, a data processing module and a data processing module, the standard energy consumption grade analysis module is used for analyzing the standard energy consumption grade of each air conditioner, the air conditioner energy consumption analysis module is used for analyzing the energy consumption state of each air conditioner and giving an alarm to a user, and the adjustment optimization module is used for adjusting the analysis process of the energy consumption state of each air conditioner and optimizing the adjustment process of the energy consumption state of each air conditioner. The machine room analysis module is used for analyzing the operation state of the refrigerating machine room, and the energy-saving management module is used for generating an energy-saving management scheme of the next monitoring period and outputting the energy-saving management scheme to a user. The energy-saving management efficiency of the refrigerating machine room is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to an energy-saving management system for a refrigeration room based on the Internet of Things. Background Art

[0002] With the development of society, the demand for refrigeration in large buildings and data centers is increasing. Traditional refrigeration room management methods are often inefficient, energy-intensive, and difficult to remotely monitor and control. Therefore, it is particularly important to develop an energy-saving management system that can monitor, intelligently analyze, and automatically adjust the operating status of refrigeration equipment in real time.

[0003] Chinese patent publication number CN106979588A discloses an energy-saving management system for air-conditioning energy consumption in a computer room, which relates to the field of air-conditioning control technology and includes multiple air conditioners, multiple temperature sensors and a control center. The control center is used to calculate the refrigeration weight in the air-conditioning control area according to the equipment distribution in the computer room equipment space and the equipment power consumption, and calculate the actual temperature of the area of ​​the air-conditioning control area according to the refrigeration weight and the sampling temperature of each temperature sensor, and compare whether the calculated actual temperature of the area is within the preset suitable temperature range of the air-conditioning. If not, the air-conditioning set temperature is lowered or raised to finally realize whether the actual temperature of the area is within the preset suitable temperature range of the air-conditioning. The modified invention can adjust the control temperature of the air-conditioning corresponding to each area in the computer room according to the cooling demand of each area in the computer room, so as to achieve the purpose of energy saving. The invention also discloses an energy-saving management method for the energy consumption of the air-conditioning in the computer room; it can be seen that the invention does not analyze the particularity of the environment in which the computer room is located and the different refrigeration scenarios of each air-conditioning, and there is a problem of low efficiency in energy-saving management of the refrigeration room. Summary of the invention

[0004] To this end, the present invention provides a refrigeration room energy-saving management system based on the Internet of Things, so as to overcome the problem of low efficiency of energy-saving management of refrigeration rooms in the prior art.

[0005] To achieve the above purpose, the present invention provides a refrigeration room energy-saving management system based on the Internet of Things, comprising:

[0006] An information acquisition module is used to obtain the operating data and building environment data of each air conditioner during the monitoring period, and is also used to obtain the historical operating data of each air conditioner;

[0007] A historical data analysis module is used to analyze the standard energy consumption level of each air conditioner based on the historical operation data of each air conditioner during the monitoring period;

[0008] The air conditioner energy consumption analysis module is used to analyze the energy consumption status of each air conditioner according to the operating data of each air conditioner during the monitoring period, and to alarm the user according to the energy consumption status analysis results of each air conditioner and the air conditioner operating period;

[0009] An adjustment and optimization module is used to adjust the analysis process of the energy consumption state of each air conditioner according to the building environment data within the monitoring period, and is also used to optimize the adjustment process of the energy consumption state of each air conditioner according to the altitude;

[0010] The computer room analysis module is used to analyze the operating status of the refrigeration room according to the energy consumption status analysis results of each air conditioner;

[0011] The energy-saving management module is used to generate an energy-saving management plan for the next monitoring cycle based on the energy consumption status analysis results of each air conditioner and the operating status analysis results of the refrigeration room, and output the energy-saving management plan to the user.

[0012] Furthermore, the historical data analysis module is provided with a data statistics unit, which is used to collect statistics on the historical average energy consumption index d(i) of each air conditioner according to the historical operation data of each air conditioner. The statistical process of the historical average energy consumption index d(i) of each air conditioner is as follows:

[0013]

[0014] Wherein, d(i)(j) represents the energy consumption of the i-th air conditioner in the j-th historical time period, i=1,2...N, N is the number of air conditioners in the building, j=1,2...J, J is the number of historical operation data obtained, T(j) is the average ambient temperature in the j-th historical time period, and t(j) is the preset temperature of the air conditioner in the j-th historical time period.

[0015] Furthermore, the historical data analysis module is further provided with a level analysis unit, which is used to classify the standard energy consumption level of each air conditioner according to the statistical results of the historical average energy consumption index d(i), and calculate the standard power of each air conditioner, wherein:

[0016] When d(i)<D1, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 1, and sets the standard power of the air conditioner to p1(i).

[0017] When D1≤d(i)<D2, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 2, and sets the standard power of the air conditioner to p2(i).

[0018]

[0019] When d(i)≥D2, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 3, and sets the standard power of the air conditioner to p3(i).

[0020]

[0021] Furthermore, the air conditioning energy consumption analysis module is provided with an environment analysis unit, and the environment analysis unit is used to analyze the working mode of each air conditioning according to the operating data of each air conditioning within the monitoring period, wherein:

[0022] When μ(i)<U1, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is the energy-saving working mode;

[0023] When U1≤μ(i)<U2, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is the normal working mode;

[0024] When μ(i)≥U2, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is a strong working mode;

[0025] Among them, μ(i) is the environmental energy consumption coefficient of the i-th air conditioner, and μ(i) is set to [c(i)-C(i)] / C(i), c(i) is the air-conditioning ambient temperature of the i-th air conditioner during the monitoring period, C(i) is the air-conditioning set temperature of the i-th air conditioner during the monitoring period, U1 is the first preset environmental energy consumption coefficient, and U2 is the second preset environmental energy consumption coefficient.

[0026] Furthermore, the air conditioner energy consumption analysis module is further provided with an energy consumption status analysis unit, which is used to analyze the energy consumption status of each air conditioner according to the working mode analysis result and the standard energy consumption level analysis result within the monitoring period, wherein:

[0027] When the working mode is the normal working mode, if W(i) / TS<pz(i), the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i), the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal, where z=1,2,3;

[0028] When the working mode is the energy-saving working mode, if W(i) / TS<pz(i)×cos{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i)×cos{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal;

[0029] When the working mode is the strong working mode, if W(i) / TS<pz(i)×exp{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i)×exp{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal;

[0030] Where W(i) is the real-time energy consumption of the i-th air conditioner during the monitoring period, and W(i) = TS × [η × T 内 (i)+b], η is the change rate of air conditioning temperature with respect to energy consumption, set η=1-{[f(i)-hf(i)] / hf(i)+[s(i)-hs(i)] / s(i)}, f(i) is the supply air temperature of the ith air conditioner during the monitoring period, hf(i) is the return air temperature of the ith air conditioner during the monitoring period, s(i) is the supply air humidity of the ith air conditioner during the monitoring period, hs(i) is the return air humidity of the ith air conditioner during the monitoring period, b is the intercept of air conditioning temperature with respect to energy consumption, T 内 (i) is the air-conditioning environment temperature during the monitoring period, and TS is the duration of the monitoring period.

[0031] Furthermore, the air conditioner energy consumption analysis module is also provided with an alarm unit, which is used to alarm the user according to the energy consumption status analysis results and historical operating periods of each air conditioner, wherein:

[0032] When the time period in the monitoring cycle does not match the air conditioner operation time period, if P(i)>0, the alarm unit sends an alarm to the user that the air conditioner is not shut down normally; if P(i)=0, the alarm unit does not send an alarm message to the user;

[0033] When the time period within the monitoring cycle matches the air conditioner operation time period, if the energy consumption status of the air conditioner is abnormal, the alarm unit sends the air conditioner energy consumption alarm to the user; if the energy consumption status of the air conditioner is normal, the alarm unit does not send an alarm message to the user.

[0034] Furthermore, the adjustment unit adjusts the energy consumption state analysis process of each air conditioner according to the building environment data within the monitoring period;

[0035] The adjustment unit calculates the environmental impact coefficient α according to the building environment data within the monitoring period, and adjusts the energy consumption state analysis process of each air conditioner according to the calculation result of the environmental impact coefficient α, wherein:

[0036] When α<A, the adjustment unit determines that the environmental impact coefficient within the monitoring period is normal and does not make any adjustment;

[0037] When α≥A, the adjustment unit determines that the environmental impact coefficient is abnormal during the monitoring period, and adjusts the standard power of each air conditioner to pz'(i);

[0038] Among them, A is the preset environmental impact coefficient.

[0039] Furthermore, the adjustment optimization module is further provided with an optimization unit, which compares the building altitude h with the preset altitude H, and optimizes the adjustment process of the energy consumption state of each air conditioner according to the comparison result, wherein:

[0040] When h<H, the optimization unit determines that the altitude of the building is normal and does not perform optimization;

[0041] When h≥H, the optimization unit determines that the altitude of the building is abnormal, and optimizes the preset environmental impact coefficient A to A'.

[0042] Furthermore, the computer room analysis module calculates the abnormal power consumption index β of the computer room according to the energy consumption status analysis results of each air conditioner. The calculation formula of the abnormal power consumption index β of the computer room is as follows:

[0043]

[0044] The abnormal power consumption index β of the computer room is defined as the sum of the abnormal power consumption ratios of all air-conditioning equipment controlled by the refrigeration room, βk(i) is the abnormal power consumption index of the i-th air conditioner, k is the abnormal power consumption index index, and k is set to 1, 2, 3. When the working mode is the normal working mode, β1(i) is set to *[W(i) / TS-pz(i)] / pz(i); when the working mode is the energy-saving working mode, β2(i) is set to *W(i) / TS / [pz(i)×cos{[μ(i)-U] / U}]-1; when the working mode is the strong working mode, β3(i) is set to *W(i) / TS / [pz(i)×exp{[μ(i)-U] / U}]-1;

[0045] The computer room analysis module compares the abnormal power consumption index β of the computer room with the power consumption index threshold B, and analyzes the operating status of the refrigeration room during the monitoring period according to the comparison result, wherein:

[0046] When β<B, the machine room analysis module determines that the operation status of the refrigeration machine room during the monitoring period is normal;

[0047] When β≥B, the computer room analysis module determines that the operation status of the refrigeration computer room during the monitoring period is abnormal.

[0048] Furthermore, the energy-saving management module generates an energy-saving management plan for the next monitoring cycle according to the energy consumption status analysis results of each air conditioner and the operating status analysis results of the refrigeration room, wherein:

[0049] When the operating state of the refrigeration room is normal, the energy-saving management module adjusts the preset temperature of the air conditioner with abnormal energy consumption state to T 设 (i)', set T 设 (i)'=T 设(i)×ln[e+βk(i)], where e is a natural logarithm; the energy-saving management module does not adjust the preset temperature of the air conditioner whose energy consumption state is normal;

[0050] When the operating state of the refrigeration room is abnormal, the energy-saving management module adjusts the preset temperature of the air conditioner with abnormal energy consumption state to T 设 (i)”, set T 设 (i)” = T 设 (i)×exp[βk(i)]; the energy-saving management module does not adjust the preset temperature of the air conditioner whose energy consumption state is normal;

[0051] Among them, T 设 (i) is the preset temperature of the i-th air conditioner in the next monitoring period;

[0052] The energy-saving management module uses the preset temperature of each air conditioner as the energy-saving management plan for the next monitoring cycle, and outputs the energy-saving management plan for the next monitoring cycle to the user.

[0053] Compared with the prior art, the beneficial effects of the present invention lie in that the information required for the present embodiment is acquired by the information acquisition module, thereby improving the accuracy and completeness of the information acquisition; the standard energy consumption level of each air conditioner is analyzed by the historical data analysis module, thereby improving the accuracy of the analysis of the standard energy consumption level and standard power of each air conditioner; the energy consumption status of each air conditioner is analyzed by the air conditioner energy consumption analysis module, and an alarm is issued to the user based on the analysis result, thereby improving the accuracy of the analysis of the air conditioner energy consumption status; the analysis process of the energy consumption status of each air conditioner is adjusted and optimized by the adjustment and optimization module, thereby improving the accuracy of the analysis of the air conditioner energy consumption status; the operating status of the refrigeration room within the monitoring period is analyzed by the computer room analysis module, thereby improving the accuracy of the analysis of the operating status of the refrigeration room; the energy-saving management plan for the next monitoring period is generated by the energy-saving management module, thereby improving the efficiency of the energy-saving management of the refrigeration room. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a schematic diagram of the structure of the refrigeration room energy-saving management system based on the Internet of Things in this embodiment.

[0055] Figure 2 Schematic diagram of the structure of the historical data analysis module of this embodiment.

[0056] Figure 3 Schematic diagram of the structure of the air conditioning energy consumption analysis module in this embodiment.

[0057] Figure 4 This is a schematic diagram of the structure of the adjustment and optimization module in this embodiment. DETAILED DESCRIPTION

[0058] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0059] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0060] It should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0061] See also Figure 1 As shown, it is a structural diagram of the energy-saving management system of the refrigeration room based on the Internet of Things in this embodiment, including:

[0062] The information acquisition module is used to obtain the operating data and building environment data of each air conditioner within the monitoring period, and is also used to obtain the historical operating data of each air conditioner; the operating data of each air conditioner includes the air conditioning environment temperature, supply air temperature, return air temperature, supply air humidity and return air humidity; the building environment data includes the temperature variation coefficient, real-time atmospheric pressure and building altitude; the historical operating data of each air conditioner is the operating data of each air conditioner within the historical time period, including the energy consumption of each air conditioner within the historical time period, the average ambient temperature and the preset temperature of the air conditioner; the duration of the historical time period is the same as the duration of the monitoring period; the value of the monitoring period in this embodiment is 1 hour. At the same time, this embodiment does not specifically limit the value of the monitoring period, and those skilled in the art can set it freely, as long as the value of the monitoring period is satisfied The value requirement can be set, such as the monitoring period can also be set to 2 hours, 3 hours, etc.; this embodiment does not specifically limit the method for obtaining the operating data of each air conditioner and the building environment data, and those skilled in the art can set it freely, as long as the acquisition requirements of the operating data of each air conditioner and the building environment data are met, such as the operating data of each air conditioner can be obtained through sensors and the hospital BA system, and the building environment temperature can be obtained in real time through the temperature sensor, and the real-time acquisition interval of the building environment temperature is 10s. At the same time, those skilled in the art can freely set the acquisition interval of the building environment temperature, such as the acquisition interval of the building environment temperature can also be set to 5s, etc., and the temperature variation coefficient can be calculated in real time according to the building environment temperature. The calculation process of the temperature variation coefficient is a prior art, and this embodiment will not be repeated here;

[0063] A historical data analysis module, used to analyze the standard energy consumption level of each air conditioner according to the historical operation data of each air conditioner within the monitoring period, and the historical data analysis module is connected to the information acquisition module;

[0064] An air-conditioning energy consumption analysis module, used to analyze the energy consumption status of each air-conditioning according to the operating data of each air-conditioning within the monitoring period, and to warn the user according to the energy consumption status analysis result of each air-conditioning and the air-conditioning operating period, the energy consumption analysis module is connected to the information acquisition module;

[0065] An adjustment and optimization module, used for adjusting the energy consumption state analysis process of each air conditioner according to the building environment data within the monitoring period, and the adjustment and optimization module is connected to the air conditioner energy consumption analysis module;

[0066] A machine room analysis module, used to analyze the operating status of the refrigeration room according to the energy consumption status analysis results of each air conditioner, and the machine room analysis module is connected to the adjustment and optimization module;

[0067] The energy-saving management module is used to generate an energy-saving management plan for the next monitoring cycle based on the energy consumption status analysis results of each air conditioner and the operating status analysis results of the refrigeration room, and output the energy-saving management plan to the user. The energy-saving management module is connected to the room analysis module and the air conditioner energy consumption analysis module.

[0068] Specifically, the energy-saving management system for refrigeration rooms based on the Internet of Things described in this embodiment is applied to the energy-saving management of refrigeration rooms in hospitals in high-altitude areas; the energy-saving management system for refrigeration rooms based on the Internet of Things described in this embodiment acts on the hospital BA system (building automation system)

[0069] See also Figure 2 As shown, it is a schematic diagram of the structure of the historical data analysis module of this embodiment, including:

[0070] A data statistics unit is used to collect statistics on the historical average energy consumption index of each air conditioner based on the historical operation data of each air conditioner;

[0071] The energy consumption standard analysis unit is used to classify the standard energy consumption level of each air conditioner according to the statistical result of the historical average energy consumption index d(i) and calculate the standard power of each air conditioner. The energy consumption standard analysis unit is connected to the data statistics unit.

[0072] Specifically, the historical data analysis module is provided with a data statistics unit, and the data statistics unit performs statistics on the historical average energy consumption index d(i) of each air conditioner according to the historical operation data of each air conditioner. The statistical process of the historical average energy consumption index d(i) of each air conditioner is as follows:

[0073]

[0074] Wherein, d(i)(j) represents the energy consumption of the i-th air conditioner in the j-th historical time period, i=1,2...N, N is the number of air conditioners in the building, j=1,2...J, J is the number of historical operation data obtained, T(j) is the average ambient temperature in the j-th historical time period, and t(j) is the preset temperature of the air conditioner in the j-th historical time period.

[0075] It can be understood that in this embodiment, when T(j)-t(j)=0,

[0076] Specifically, the data statistics unit improves the accuracy of the statistics of the historical average energy consumption index of each air conditioner by statistics, thereby improving the accuracy of the standard energy consumption level and standard power analysis of each air conditioner, thereby improving the accuracy of the energy consumption status analysis of each air conditioner, and ultimately improving the efficiency of energy-saving management of the refrigeration room.

[0077] Specifically, the historical data analysis module is further provided with a level analysis unit, which divides the standard energy consumption level of each air conditioner according to the statistical results of the historical average energy consumption index d(i), and calculates the standard power of each air conditioner, wherein:

[0078] When d(i)<D1, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 1, and sets the standard power of the air conditioner to p1(i).

[0079] When D1≤d(i)<D2, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 2, and sets the standard power of the air conditioner to p2(i).

[0080]

[0081] When d(i)≥D2, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 3, and sets the standard power of the air conditioner to p3(i).

[0082]

[0083] Wherein, D1 is a first preset air conditioning energy consumption index, D2 is a second preset air conditioning energy consumption index, and D1<D2.

[0084] It can be understood that the first level described in this embodiment is an energy-saving air conditioner, the second level is a normal power consumption air conditioner, and the third level is an energy-consuming air conditioner; the "first level", "second level" and "third level" described in this embodiment are subdivisions based on national standards, so that the division levels are more in line with the scenarios described in this embodiment.

[0085] Specifically, the level analysis unit improves the accuracy of the analysis of the standard energy consumption level and standard power of each air conditioner by dividing the standard energy consumption level of each air conditioner and calculating the standard power of each air conditioner, thereby improving the accuracy of the energy consumption status analysis of each air conditioner, and ultimately improving the efficiency of energy-saving management of the refrigeration room; it can be understood that this embodiment does not make specific limitations on the values ​​of the first preset air conditioner energy consumption index D1 and the second preset air conditioner energy consumption index D2. Technical personnel in this field can set them freely, and only need to meet the value requirements of the first preset air conditioner energy consumption index D1 and the second preset air conditioner energy consumption index D2. For example, the first preset air conditioner energy consumption index D1 can be set to 0.1, and the second preset air conditioner energy consumption index D2 can be set to 0.2.

[0086] See also Figure 3 As shown, it is a structural schematic diagram of the air conditioning energy consumption analysis module of this embodiment, including:

[0087] An environmental analysis unit, used to analyze the working mode of each air conditioner according to the operating data of each air conditioner during the monitoring period;

[0088] An energy consumption status analysis unit, used for analyzing the energy consumption status of each air conditioner according to the working mode analysis result and the standard energy consumption level analysis result within the monitoring period, and the energy consumption status analysis unit is connected to the environment analysis unit;

[0089] The alarm unit is used to warn the user according to the energy consumption status analysis result and the historical operation time period of each air conditioner, and the alarm unit is connected to the energy consumption status analysis unit.

[0090] Specifically, the air conditioning energy consumption analysis module is provided with an environment analysis unit, and the environment analysis unit analyzes the working mode of each air conditioning according to the operating data of each air conditioning within the monitoring period, wherein:

[0091] When μ(i)<U1, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is the energy-saving working mode;

[0092] When U1≤μ(i)<U2, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is the normal working mode;

[0093] When μ(i)≥U2, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is a strong working mode;

[0094] Among them, μ(i) is the environmental energy consumption coefficient of the i-th air conditioner, and μ(i) is set to [c(i)-C(i)] / C(i), c(i) is the air-conditioning ambient temperature of the i-th air conditioner during the monitoring period, C(i) is the air-conditioning set temperature of the i-th air conditioner during the monitoring period, U1 is the first preset environmental energy consumption coefficient, and U2 is the second preset environmental energy consumption coefficient.

[0095] Specifically, the environmental analysis unit improves the accuracy of the air conditioner working status analysis by analyzing the working mode of each air conditioner, and further improves the accuracy of the air conditioner energy consumption status analysis, thereby improving the accuracy of the refrigeration room operation status analysis, and ultimately improving the efficiency of the refrigeration room energy-saving management; it can be understood that this embodiment does not make specific limitations on the values ​​of the first preset environmental energy consumption coefficient U1 and the second preset environmental energy consumption coefficient U2, and technical personnel in this field can set them freely, and only need to meet the value requirements of the first preset environmental energy consumption coefficient U1 and the second preset environmental energy consumption coefficient U2, such as the first preset environmental energy consumption coefficient U1 can be set to 0.2, and the second preset environmental energy consumption coefficient U2 can be set to 0.4.

[0096] Specifically, the air conditioner energy consumption analysis module is further provided with an energy consumption status analysis unit, which analyzes the energy consumption status of each air conditioner according to the working mode analysis results and the standard energy consumption level analysis results within the monitoring period, wherein:

[0097] When the working mode is the normal working mode, if W(i) / TS<pz(i), the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i), the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal, where z=1,2,3;

[0098] When the working mode is the energy-saving working mode, if W(i) / TS<pz(i)×cos{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i)×cos{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal;

[0099] When the working mode is the strong working mode, if W(i) / TS<pz(i)×exp{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i)×exp{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal;

[0100] Where W(i) is the real-time energy consumption of the i-th air conditioner during the monitoring period, and W(i) = TS × [η × T 内 (i)+b], η is the change rate of air conditioning temperature with respect to energy consumption, set η=1-{[f(i)-hf(i)] / hf(i)+[s(i)-hs(i)] / s(i)}, f(i) is the supply air temperature of the ith air conditioner during the monitoring period, hf(i) is the return air temperature of the ith air conditioner during the monitoring period, s(i) is the supply air humidity of the ith air conditioner during the monitoring period, hs(i) is the return air humidity of the ith air conditioner during the monitoring period, b is the intercept of air conditioning temperature with respect to energy consumption, T 内 (i) is the air-conditioning environment temperature during the monitoring period, and TS is the duration of the monitoring period.

[0101] Specifically, the energy consumption status analysis unit improves the accuracy of the air conditioner energy consumption status analysis by analyzing the energy consumption status of each air conditioner, thereby improving the accuracy of the operation status analysis of the refrigeration room, and ultimately improving the efficiency of the energy-saving management of the refrigeration room; it can be understood that this embodiment does not make a specific limitation on the value of the air-conditioning temperature related intercept b with respect to energy consumption, and technical personnel in this field can set it freely, as long as the value requirement of the air-conditioning temperature related intercept b with respect to energy consumption is met, such as the air-conditioning temperature related intercept b with respect to energy consumption can be set to 2.355.

[0102] Specifically, the air conditioner energy consumption analysis module is further provided with an alarm unit, which is used to alarm the user according to the energy consumption status analysis results and historical operating periods of each air conditioner, wherein:

[0103] When the time period in the monitoring cycle does not match the air conditioner operation time period, if P(i)>0, the alarm unit sends an alarm to the user that the air conditioner is not shut down normally; if P(i)=0, the alarm unit does not send an alarm message to the user;

[0104] When the time period within the monitoring cycle matches the air conditioner operation time period, if the energy consumption status of the air conditioner is abnormal, the alarm unit sends the air conditioner energy consumption alarm to the user; if the energy consumption status of the air conditioner is normal, the alarm unit does not send an alarm message to the user.

[0105] Specifically, the alarm unit improves the accuracy of abnormal alarms for air-conditioning energy consumption by alerting the user, thereby improving the efficiency of energy-saving management of the refrigeration room.

[0106] See also Figure 4 As shown, it is a schematic diagram of the structure of the adjustment and optimization module of this embodiment, including:

[0107] An adjustment unit, used to adjust the energy consumption state analysis process of each air conditioner according to the building environment data within the monitoring period;

[0108] The optimization module is used to optimize the adjustment process of the energy consumption state of each air conditioner according to the building altitude, and the optimization module is connected to the adjustment unit.

[0109] Specifically, the adjustment unit adjusts the energy consumption state analysis process of each air conditioner according to the building environment data within the monitoring period;

[0110] The adjustment unit calculates the environmental impact coefficient α according to the building environment data within the monitoring period, and adjusts the energy consumption state analysis process of each air conditioner according to the calculation result of the environmental impact coefficient α, wherein:

[0111] When α<A, the adjustment unit determines that the environmental impact coefficient within the monitoring period is normal and does not make any adjustment;

[0112] When α≥A, the adjustment unit determines that the environmental impact coefficient is abnormal during the monitoring period, adjusts the standard power of each air conditioner to pz'(i), and sets pz'(i)=pz(i)×{1+sin[(α-A) / A]};

[0113] The environmental impact coefficient α is defined as the uncontrollable abnormal coefficient of the energy consumption of all air-conditioning equipment in the building due to the influence of high-altitude air. α is set to exp{(py-PY) / PY} / CV, where py is the real-time atmospheric pressure, PY is the standard atmospheric pressure, CV is the temperature variation coefficient, and A is the preset environmental impact coefficient.

[0114] Specifically, the adjustment unit calculates the environmental impact coefficient according to the building environment data within the monitoring period, and adjusts the energy consumption status analysis process of each air conditioner according to the calculation result of the environmental impact coefficient, thereby improving the accuracy of the air conditioner energy consumption status analysis, thereby improving the accuracy of the operation status analysis of the refrigeration room, and ultimately improving the efficiency of energy-saving management of the refrigeration room; it can be understood that this embodiment does not make specific limitations on the value of the preset environmental impact coefficient A, and technical personnel in this field can set it freely, as long as the value requirements of the preset environmental impact coefficient A are met, such as the preset environmental impact coefficient A can be set to 1.6.

[0115] Specifically, the adjustment optimization module is further provided with an optimization unit, which compares the building altitude h with the preset altitude H, and optimizes the adjustment process of the energy consumption state of each air conditioner according to the comparison result, wherein:

[0116] When h<H, the optimization unit determines that the altitude of the building is normal and does not perform optimization;

[0117] When h≥H, the optimization unit determines that the altitude of the building is abnormal, and optimizes the preset environmental impact coefficient A to A', setting A'=A×{1-exp[(Hh) / H]}.

[0118] Specifically, the optimization unit improves the accuracy of the air conditioner energy consumption status analysis by optimizing the adjustment process of the energy consumption status of each air conditioner, thereby improving the accuracy of the operation status analysis of the refrigeration room, and ultimately improving the efficiency of the energy-saving management of the refrigeration room; it can be understood that this embodiment does not make specific limitations on the value of the preset altitude H, and technical personnel in this field can set it freely, as long as the value requirements of the preset altitude H are met, such as the preset altitude H can be set to 1500 meters.

[0119] Specifically, the computer room analysis module calculates the abnormal power consumption index β of the computer room according to the energy consumption status analysis results of each air conditioner. The calculation formula of the abnormal power consumption index β of the computer room is as follows:

[0120]

[0121] The abnormal power consumption index β of the computer room is defined as the sum of the abnormal power consumption ratios of all air-conditioning equipment controlled by the refrigeration room, βk(i) is the abnormal power consumption index of the i-th air conditioner, k is the abnormal power consumption index index, and k is set to 1, 2, 3. When the working mode is the normal working mode, β1(i) is set to *[W(i) / TS-pz(i)] / pz(i); when the working mode is the energy-saving working mode, β2(i) is set to *W(i) / TS / [pz(i)×cos{[μ(i)-U] / U}]-1; when the working mode is the strong working mode, β3(i) is set to *W(i) / TS / [pz(i)×exp{[μ(i)-U] / U}]-1;

[0122] The computer room analysis module compares the abnormal power consumption index β of the computer room with the power consumption index threshold B, and analyzes the operating status of the refrigeration room during the monitoring period according to the comparison result, wherein:

[0123] When β<B, the machine room analysis module determines that the operation status of the refrigeration machine room during the monitoring period is normal;

[0124] When β≥B, the computer room analysis module determines that the operation status of the refrigeration computer room during the monitoring period is abnormal.

[0125] It can be understood that the meaning of “*” in “*[W(i) / TS-pz(i)] / pz(i)” in this embodiment is: when [W(i) / TS-pz(i)] / pz(i)<0, *[W(i) / TS-pz(i)] / pz(i)=0; when [W(i) / TS-pz(i)] / pz(i)≥0, *[W(i) / TS-pz(i)] / pz(i)=[W(i) / TS-pz(i)] / pz(i), and the usage of “*” thereafter is consistent with that here and will not be elaborated on.

[0126] Specifically, the computer room analysis module improves the accuracy of the operation status analysis of the refrigeration room by analyzing the operation status of the refrigeration room during the monitoring period, and ultimately improves the efficiency of energy-saving management of the refrigeration room; it can be understood that this embodiment does not make specific limitations on the value of the power consumption index threshold B, and technical personnel in this field can set it freely, as long as the value requirements of the power consumption index threshold B are met, such as the power consumption index threshold B can be set to 1.

[0127] Specifically, the energy-saving management module generates an energy-saving management plan for the next monitoring cycle according to the energy consumption status analysis results of each air conditioner and the operating status analysis results of the refrigeration room, wherein:

[0128] When the operating state of the refrigeration room is normal, the energy-saving management module adjusts the preset temperature of the air conditioner with abnormal energy consumption state to T 设 (i)', set T 设 (i)'=T 设 (i)×ln[e+βk(i)], where e is a natural logarithm; the energy-saving management module does not adjust the preset temperature of the air conditioner whose energy consumption state is normal;

[0129] When the operating state of the refrigeration room is abnormal, the energy-saving management module adjusts the preset temperature of the air conditioner with abnormal energy consumption state to T 设 (i)”, set T 设 (i)” = T 设 (i)×exp[βk(i)]; the energy-saving management module does not adjust the preset temperature of the air conditioner whose energy consumption state is normal;

[0130] Among them, T 设 (i) is the preset temperature of the i-th air conditioner in the next monitoring period;

[0131] The energy-saving management module uses the preset temperature of each air conditioner as the energy-saving management plan for the next monitoring cycle, and outputs the energy-saving management plan for the next monitoring cycle to the user.

[0132] Specifically, the energy-saving management module generates an energy-saving management plan for the next monitoring cycle and outputs the energy-saving management plan to the user, thereby improving the accuracy of the management plan analysis and thus improving the efficiency of the energy-saving management of the refrigeration room.

[0133] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A refrigeration room energy-saving management system based on the Internet of Things, characterized in that: include: An information acquisition module is used to obtain the operating data and building environment data of each air conditioner during the monitoring period, and is also used to obtain the historical operating data of each air conditioner; A historical data analysis module is used to analyze the standard energy consumption level of each air conditioner based on the historical operation data of each air conditioner during the monitoring period; The air conditioner energy consumption analysis module is used to analyze the energy consumption status of each air conditioner according to the operating data of each air conditioner during the monitoring period, and to alarm the user according to the energy consumption status analysis results of each air conditioner and the air conditioner operating period; An adjustment and optimization module is used to adjust the analysis process of the energy consumption state of each air conditioner according to the building environment data within the monitoring period, and is also used to optimize the adjustment process of the energy consumption state of each air conditioner according to the altitude; The computer room analysis module is used to analyze the operating status of the refrigeration room according to the energy consumption status analysis results of each air conditioner; The energy-saving management module is used to generate an energy-saving management plan for the next monitoring cycle based on the energy consumption status analysis results of each air conditioner and the operating status analysis results of the refrigeration room, and output the energy-saving management plan to the user.

2. The refrigeration room energy-saving management system based on the Internet of Things according to claim 1 is characterized in that: The historical data analysis module is provided with a data statistics unit, which is used to collect statistics on the historical average energy consumption index d(i) of each air conditioner according to the historical operation data of each air conditioner. The statistical process of the historical average energy consumption index d(i) of each air conditioner is as follows: Wherein, d(i)(j) represents the energy consumption of the i-th air conditioner in the j-th historical time period, i=1,2...N, N is the number of air conditioners in the building, j=1,2...J, J is the number of historical operation data obtained, T(j) is the average ambient temperature in the j-th historical time period, and t(j) is the preset temperature of the air conditioner in the j-th historical time period.

3. The refrigeration room energy-saving management system based on the Internet of Things according to claim 2 is characterized in that: The historical data analysis module is further provided with a level analysis unit, which is used to classify the standard energy consumption level of each air conditioner according to the statistical results of the historical average energy consumption index d(i), and calculate the standard power of each air conditioner, wherein: When d(i)<D1, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 1, and sets the standard power of the air conditioner to p1(i). When D1≤d(i)<D2, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 2, and sets the standard power of the air conditioner to p2(i). When d(i)≥D2, the level analysis unit determines that the standard energy consumption level of the air conditioner is level 3, and sets the standard power of the air conditioner to p3(i).

4. The refrigeration room energy-saving management system based on the Internet of Things according to claim 3 is characterized in that: The air conditioner energy consumption analysis module is provided with an environment analysis unit, and the environment analysis unit is used to analyze the working mode of each air conditioner according to the operating data of each air conditioner within the monitoring period, wherein: When μ(i)<U1, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is the energy-saving working mode; When U1≤μ(i)<U2, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is the normal working mode; When μ(i)≥U2, the environmental analysis unit determines that the working mode of the air conditioner during the monitoring period is a strong working mode; Among them, μ(i) is the environmental energy consumption coefficient of the i-th air conditioner, and μ(i) is set to [c(i)-C(i)] / C(i), c(i) is the air-conditioning ambient temperature of the i-th air conditioner during the monitoring period, C(i) is the air-conditioning set temperature of the i-th air conditioner during the monitoring period, U1 is the first preset environmental energy consumption coefficient, and U2 is the second preset environmental energy consumption coefficient.

5. The refrigeration room energy-saving management system based on the Internet of Things according to claim 4 is characterized in that: The air conditioner energy consumption analysis module is further provided with an energy consumption status analysis unit, which is used to analyze the energy consumption status of each air conditioner according to the working mode analysis results and the standard energy consumption level analysis results within the monitoring period, wherein: When the working mode is the normal working mode, if W(i) / TS<pz(i), the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i), the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal, where z=1,2,3; When the working mode is the energy-saving working mode, if W(i) / TS<pz(i)×cos{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i)×cos{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal; When the working mode is the strong working mode, if W(i) / TS<pz(i)×exp{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is normal; if P(i) / TS≥pz(i)×exp{[μ(i)-U] / U}, the energy consumption state analysis unit determines that the energy consumption state of the air conditioner during the monitoring period is abnormal; Where W(i) is the real-time energy consumption of the i-th air conditioner during the monitoring period, and W(i) = TS × [η × T 内 (i)+b], η is the change rate of air conditioning temperature with respect to energy consumption, set η=1-{[f(i)-hf(i)] / hf(i)+[s(i)-hs(i)] / s(i)}, f(i) is the supply air temperature of the ith air conditioner during the monitoring period, hf(i) is the return air temperature of the ith air conditioner during the monitoring period, s(i) is the supply air humidity of the ith air conditioner during the monitoring period, hs(i) is the return air humidity of the ith air conditioner during the monitoring period, b is the intercept of air conditioning temperature with respect to energy consumption, T 内 (i) is the air-conditioning environment temperature during the monitoring period, and TS is the duration of the monitoring period.

6. The refrigeration room energy-saving management system based on the Internet of Things according to claim 5 is characterized in that: The air conditioner energy consumption analysis module is also provided with an alarm unit, which is used to alarm the user according to the energy consumption status analysis results and historical operating periods of each air conditioner, wherein: When the time period in the monitoring cycle does not match the air conditioner operation time period, if P(i)>0, the alarm unit sends an alarm to the user that the air conditioner is not shut down normally; if P(i)=0, the alarm unit does not send an alarm message to the user; When the time period within the monitoring cycle matches the air conditioner operation time period, if the energy consumption status of the air conditioner is abnormal, the alarm unit sends the air conditioner energy consumption alarm to the user; if the energy consumption status of the air conditioner is normal, the alarm unit does not send an alarm message to the user.

7. The refrigeration room energy-saving management system based on the Internet of Things according to claim 6 is characterized in that: The adjustment unit adjusts the energy consumption state analysis process of each air conditioner according to the building environment data within the monitoring period; The adjustment unit calculates the environmental impact coefficient α according to the building environment data within the monitoring period, and adjusts the energy consumption state analysis process of each air conditioner according to the calculation result of the environmental impact coefficient α, wherein: When α<A, the adjustment unit determines that the environmental impact coefficient within the monitoring period is normal and does not make any adjustment; When α≥A, the adjustment unit determines that the environmental impact coefficient is abnormal during the monitoring period, and adjusts the standard power of each air conditioner to pz'(i); Among them, A is the preset environmental impact coefficient.

8. The refrigeration room energy-saving management system based on the Internet of Things according to claim 7 is characterized in that: The adjustment and optimization module is further provided with an optimization unit, which compares the building altitude h with the preset altitude H, and optimizes the adjustment process of the energy consumption state of each air conditioner according to the comparison result, wherein: When h<H, the optimization unit determines that the altitude of the building is normal and does not perform optimization; When h≥H, the optimization unit determines that the altitude of the building is abnormal, and optimizes the preset environmental impact coefficient A to A'.

9. The refrigeration room energy-saving management system based on the Internet of Things according to claim 8 is characterized in that: The computer room analysis module calculates the abnormal power consumption index β of the computer room according to the energy consumption status analysis results of each air conditioner. The calculation formula of the abnormal power consumption index β of the computer room is as follows: The abnormal power consumption index β of the computer room is defined as the sum of the abnormal power consumption ratios of all air-conditioning equipment controlled by the refrigeration room, βk(i) is the abnormal power consumption index of the i-th air conditioner, k is the abnormal power consumption index index, and k is set to 1, 2, 3. When the working mode is the normal working mode, β1(i) is set to *[W(i) / TS-pz(i)] / pz(i); when the working mode is the energy-saving working mode, β2(i) is set to *W(i) / TS / [pz(i)×cos{[μ(i)-U] / U}]-1; when the working mode is the strong working mode, β3(i) is set to *W(i) / TS / [pz(i)×exp{[μ(i)-U] / U}]-1; The computer room analysis module compares the abnormal power consumption index β of the computer room with the power consumption index threshold B, and analyzes the operating status of the refrigeration room during the monitoring period according to the comparison result, wherein: When β<B, the machine room analysis module determines that the operation status of the refrigeration machine room during the monitoring period is normal; When β≥B, the computer room analysis module determines that the operation status of the refrigeration computer room during the monitoring period is abnormal.

10. The refrigeration room energy-saving management system based on the Internet of Things according to claim 9 is characterized in that: The energy-saving management module generates an energy-saving management plan for the next monitoring cycle according to the energy consumption status analysis results of each air conditioner and the operating status analysis results of the refrigeration room, wherein: When the operating state of the refrigeration room is normal, the energy-saving management module adjusts the preset temperature of the air conditioner with abnormal energy consumption state to T 设 (i)', set T 设 (i)'=T 设 (i)×ln[e+βk(i)], where e is a natural logarithm; the energy-saving management module does not adjust the preset temperature of the air conditioner whose energy consumption state is normal; When the operating state of the refrigeration room is abnormal, the energy-saving management module adjusts the preset temperature of the air conditioner with abnormal energy consumption state to T 设 (i)”, set T 设 (i)” = T 设 (i)×exp[βk(i)]; the energy-saving management module does not adjust the preset temperature of the air conditioner whose energy consumption state is normal; Among them, T 设 (i) is the preset temperature of the i-th air conditioner in the next monitoring period; The energy-saving management module uses the preset temperature of each air conditioner as the energy-saving management plan for the next monitoring cycle, and outputs the energy-saving management plan for the next monitoring cycle to the user.

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