CN213454122U - Central air conditioning energy efficiency optimization system based on big data analysis - Google Patents
Central air conditioning energy efficiency optimization system based on big data analysis Download PDFInfo
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- CN213454122U CN213454122U CN202022686424.1U CN202022686424U CN213454122U CN 213454122 U CN213454122 U CN 213454122U CN 202022686424 U CN202022686424 U CN 202022686424U CN 213454122 U CN213454122 U CN 213454122U
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Abstract
The utility model discloses a central air conditioning efficiency optimization system based on big data analysis of energy-conserving technical field of control management, the system includes central air conditioning machine room equipment, information acquisition equipment, big data processing center, artificial intelligence cloud platform, instrument controlgear and end equipment, information acquisition equipment is used for gathering the temperature information that the air conditioner set for, outdoor temperature information and air conditioning regional temperature information, big data processing center can receive the temperature information that the air conditioner set for, outdoor temperature information and air conditioning regional temperature information, reference person uses the habitual data of air conditioner, obtain individualized air conditioning regional ambient temperature demand through big data operation, artificial intelligence cloud platform is the intelligent device of control and management central air conditioning machine room equipment, can with the demand according to the cold volume of different conditions, and different seasons external environment condition changes and adopts self-learning, The self-adaptive optimization technology actively adjusts, and ensures safe, reliable and efficient operation of central air-conditioning room equipment.
Description
Technical Field
The utility model relates to a central air conditioning efficiency optimization system based on big data analysis adopts the application of artificial intelligence technique cooperation big data to come integrated control in order to reduce air conditioner room energy consumption, improves the efficiency ratio of system.
Background
The central air conditioner is one of the indispensable important equipment of modern buildings, and according to survey statistics, most of buildings are in the maximum load only for dozens of days in a year. The cold load of the central air conditioner is always in dynamic change. At present, the energy consumption of many central air conditioners accounts for almost 50% or more of the total energy consumption of buildings. With the development of science and technology, the artificial intelligence technology is showing more and more important functions as a new science and technology force, and the application of the technology in the field of energy efficiency optimization of the central air conditioner room brings a great leap for the energy efficiency optimization and energy saving effects of the central air conditioner.
At present, the energy efficiency optimization modes of the central air-conditioning system are many: firstly, adjust cold water circulation and cooling water circulation system's flow through the variable flow technique, guarantee the stability of temperature difference to reduce the energy consumption, promote the system of the operation effect of air conditioner. The cooling water system has the characteristic of adjusting the flow rate along with the change of the load of the air conditioner, and can also ensure that the temperature difference of the cooling water and the cold water is kept the same during circulation. The sensor transmits the information to the information processing device after the information is collected, and finally the adjustment effect on the cold water circulating system and the cooling water circulating system is achieved through the adjustment of the condenser, so that the purpose of reducing energy consumption is achieved. The second is heat recovery technology and energy storage technology. The cold accumulation technology is to avoid the peak period of power consumption, store certain cold energy in a certain time, and release the cold energy in the peak period of power consumption, thereby reducing the pressure of power supply. The peak shifting and valley filling are utilized, and the peak shifting and the peak power utilization are realized. Efficient equipment is also adopted, and comprises a host, a water pump, a fan and the like; the system design is optimized to reduce the system resistance and reduce the wind and water conveying energy consumption; regularly maintain, wash the scale removal and improve heat exchange efficiency of heat transfer parts. However, the currently adopted energy saving technology only performs energy saving control on one part of the refrigeration system, and cannot perform energy saving control according to the overall change of the system, and the mismatch between each part generates extra power consumption.
Based on this, the utility model designs a central air conditioning efficiency optimization system based on big data analysis to solve the above-mentioned problem.
SUMMERY OF THE UTILITY MODEL
An object of the utility model is to provide a central air conditioning efficiency optimization system based on big data analysis to solve the above-mentioned problem of mentioning.
Central air conditioning efficiency optimization system not the equipment of a design, but one set of economizer system device of "tailor-made" according to air conditioner room equipment's operating condition institute. The information acquisition equipment acquires real-time equipment and environment information. The big data processing center comprises a data receiving unit and a database. The big data processing center receives the temperature information set by the air conditioner, the outdoor temperature information and the air conditioning area temperature information, and can obtain the personalized air conditioning area environment temperature requirement by big data calculation by referring to the habit data of the personnel using the air conditioner. The artificial intelligence cloud platform (AI) integrates various information, self-learning and self-adaptive optimization technologies are adopted according to the requirement of cold capacity in a building and the change of external climate, the outlet water temperature and the outlet water flow of chilled water and cooling water are actively adjusted, the integrated energy consumption of a water chilling unit, a chilled water pump and a cooling water pump is reduced, and the Energy Efficiency (EER) of a refrigerating machine system is stabilized at the highest energy efficiency section. According to the change of the load at the tail end of the air conditioner and the operation condition of the air conditioner host, the parameters (temperature, pressure, flow and the like) of a water system of the central air conditioner are automatically and completely acquired, the air conditioner is regulated and controlled at any time, and the flow of a system refrigerant is enabled to synchronously change along with the change of the load, so that the energy efficiency ratio (COP value) of the air conditioning system is ensured to be always in the maximum energy-saving operation state on the premise that the central air conditioning system can meet the requirement of a human body on the comfort level, and the energy consumption of the system is greatly.
Central air conditioning computer lab efficiency optimizing system can solve the energy-conserving each part of system and be non-unified, can not reach the problem of best energy-conserving effect.
In order to achieve the above object, the utility model provides a following technical scheme: a central air conditioner energy efficiency optimization system based on big data analysis comprises a central air conditioner room device, an information collection device, a big data processing center, an artificial intelligence cloud platform, an instrument control device and a terminal device, wherein the information collection device is used for collecting temperature information set by an air conditioner, outdoor temperature information and air conditioner area temperature information, the big data processing center is used for receiving the information collected by the information collection device and then carrying out big data operation, the artificial intelligence cloud platform integrates the information collected by the information collection device and the operation result of the big data processing center and is in butt joint with the instrument control device, and the instrument control device controls the terminal device to work through the central air conditioner room device.
Preferably, the information acquisition equipment comprises a water temperature sensor, a temperature and humidity sensor, a flow sensor and a pressure sensor.
Preferably, the terminal equipment comprises a fresh air handling unit, a fan coil and a plate heat exchanger.
Preferably, the central air-conditioning room equipment comprises a water chilling unit, a freezing pump and a cooling pump.
Preferably, the freezing pump and the cooling pump both adopt variable frequency water pumps.
Compared with the prior art, the beneficial effects of the utility model are that:
the utility model discloses a real-time equipment of information acquisition equipment collection, environmental information, temperature information, outdoor temperature information and the regional temperature information of air conditioner that the air conditioner set for are received to big data processing center, can refer to personnel's habitual data that use the air conditioner, obtain individualized regional ambient temperature demand of air conditioner through big data operation. The artificial intelligence cloud platform (AI) integrates various information, self-learning and self-adaptive optimization technologies are adopted according to the requirement of cold capacity in a building and the change of external climate, the outlet water temperature and the outlet water flow of chilled water and cooling water are actively adjusted, the integrated energy consumption of a water chilling unit, a chilled water pump and a cooling water pump is reduced, and the Energy Efficiency (EER) of a refrigerating machine system is stabilized at the highest energy efficiency section. According to the change of the load at the tail end of the air conditioner and the operation condition of the air conditioner host, the parameters (temperature, pressure, flow and the like) of a water system of the central air conditioner are automatically and completely acquired, the air conditioner is regulated and controlled at any time, and the flow of a system refrigerant is enabled to synchronously change along with the change of the load, so that the energy efficiency ratio (COP value) of the air conditioning system is ensured to be always in the maximum energy-saving operation state on the premise that the central air conditioning system can meet the requirement of a human body on the comfort level, and the energy consumption of the system is greatly.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of the system of the present invention;
fig. 2 is a system logic control diagram of the present invention.
In the drawings, the components represented by the respective reference numerals are listed below:
1. an artificial intelligence cloud platform; 2. an instrument control device; 3. a terminal device; 4. a central air-conditioning room device; 5. an information acquisition device; 6. a water temperature sensor; 7. a temperature and humidity sensor; 8. a flow sensor; 9. a pressure sensor; 10. a fresh air handling unit; 11. a fan coil; 12. a plate heat exchanger; 13. a water chilling unit; 14. a freeze pump; 15. a cooling pump; 16. big data processing center.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution: a central air-conditioning energy efficiency optimization system based on big data analysis comprises a central air-conditioning machine room device 4, an information acquisition device 5, a big data processing center 16, an artificial intelligent cloud platform 1, an instrument control device 2 and a terminal device 3, wherein the information acquisition device 5 is used for acquiring temperature information set by an air conditioner, outdoor temperature information and air-conditioning area temperature information, the big data processing center 16 can receive the temperature information set by the air conditioner, the outdoor temperature information and the air-conditioning area temperature information, reference personnel use habit data of the air conditioner to obtain individualized air-conditioning area environment temperature requirements through big data operation, the artificial intelligent cloud platform 1 integrates the information acquired by the information acquisition device 5 and the operation result of the big data processing center 16 and is in butt joint with the instrument control device 2, and the artificial intelligent cloud platform is an intelligent device for controlling and managing the central air-conditioning machine room device, the self-learning and self-adaptive optimization technology can be adopted according to the requirements of cooling capacity under different conditions and the change of external environmental conditions in different seasons, active adjustment is carried out, and safe, reliable and efficient operation of central air-conditioning room equipment is ensured. The computer software control system controls the starting, linkage, stopping, resetting, alarming and the like of peripheral related equipment of the central air conditioner, thereby realizing unattended operation, saving operation management personnel and reducing operation and maintenance cost. The system is added with settings such as gain compensation, zero position compensation and full-range compensation through the artificial intelligence cloud platform 1, so that the system is more suitable for the design of a central air-conditioning system, and the instrument control equipment 2 controls the tail end equipment 3 to work through the central air-conditioning room equipment 4.
Wherein, information acquisition equipment 5 includes temperature sensor 6, temperature and humidity sensor 7, flow sensor 8 and pressure sensor 9, and information acquisition equipment 5 can realize that dynamic load follows, has optimized air conditioner host computer operational environment, satisfies the requirement of central air conditioning system nonlinearity and time variation nature, makes air conditioner host computer operate at the optimum operating mode all the time to keep the highest heat conversion efficiency, thereby reduce the energy consumption of host computer.
The terminal device 3 comprises a fresh air handling unit 10, a fan coil 11 and a plate heat exchanger 12.
The central air-conditioning room equipment 4 comprises a water chilling unit 13, a freezing pump 14 and a cooling pump 15.
The refrigeration pump 14 and the cooling pump 15 both adopt variable frequency water pumps, and the requirements of the air conditioning system on use under various load conditions are met through flow control, so that the comfort of a terminal user is ensured, and the energy consumption of the system is saved to the maximum extent; the flow of the cooling water is dynamically adjusted, and the inlet and outlet temperatures of the cooling water are controlled at the same time, so that the central air-conditioning host machine is ensured to operate at the highest efficiency state at any time.
The energy-saving control method is based on the principle of optimal system benefit, and reduces comprehensive energy consumption of the water chilling unit, the freezing water pump and the cooling water pump. According to the requirement of cold quantity in the building and the change of external climate, a self-learning and self-adaptive optimization technology is adopted to actively adjust the temperature and the flow of the outlet water of the chilled water, and the frequency of the chilled water pump/cooling water pump is automatically adjusted according to the change of load, so that the Energy Efficiency Ratio (EER) is stabilized at the highest energy efficiency section. To achieve energy saving.
EER: the energy efficiency ratio of the system; w: electrical energy consumed by the device; c: the specific heat capacity of the medium;
m: the mass of the medium is obtained through flow calculation;
delta T: the temperature difference is that the freezing water pump is the temperature difference of inlet and outlet water, and the cooling water pump is the temperature difference of outlet water and return water.
The information acquisition equipment 5 can acquire real-time working state information of each part of the system, including inflow flow, inflow pressure and inflow temperature of cooling water; the inlet flow, inlet pressure and inlet temperature of the chilled water, and the temperature and humidity in the air-conditioning room. The real-time energy efficiency ratio of the freezing water pump and the cooling water pump can be calculated according to the real-time power of the system and the acquired information and by substituting the real-time power and the acquired information into a formula. The artificial intelligence cloud platform 1 adopts self-learning and self-adaptive optimization technology according to the change of the load at the tail end of the air conditioner, the operation condition of the air conditioner host and the complete sampling data of the parameters (temperature, pressure, flow and the like) of the central air conditioner water system, and simultaneously combines the habitual data of a reference person of the big data processing center 16 using the air conditioner to obtain individualized environment temperature demand data of the air conditioner area through big data operation, and regulates and controls the air conditioner in real time, so that the flow of the system refrigerant changes synchronously along with the change of the load, thereby ensuring that the energy efficiency ratio (COP value) of the air conditioner system is always in the optimal energy-saving operation state on the premise of ensuring that the central air conditioner system can meet the requirement of human body on comfort, and greatly reducing. Meanwhile, automatic control can be realized, a computer software control system controls starting, linkage, stopping, resetting, alarming and the like of peripheral related equipment of the central air conditioner, and unattended operation can be realized.
In the description herein, references to the description of "one embodiment," "an example," "a specific example," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and its practical applications, to thereby enable others skilled in the art to best understand the invention for and utilize the invention. The present invention is limited only by the claims and their full scope and equivalents.
Claims (5)
1. The utility model provides a central air conditioning efficiency optimizing system based on big data analysis which characterized in that: the system comprises a central air conditioner room device (4), an information acquisition device (5), a big data processing center (16), an artificial intelligence cloud platform (1), an instrument control device (2) and a terminal device (3), wherein the information acquisition device (5) is used for acquiring temperature information set by an air conditioner, outdoor temperature information and air conditioner area temperature information, the big data processing center (16) is used for receiving information acquired by the information acquisition device (5) and then carrying out big data operation, the artificial intelligence cloud platform (1) integrates the information acquired by the information acquisition device (5) and the operation result of the big data processing center (16) and is in butt joint with the instrument control device (2), and the instrument control device (2) controls the terminal device (3) to work through the central air conditioner room device (4).
2. The central air-conditioning energy efficiency optimization system based on big data analysis according to claim 1, characterized in that: the information acquisition equipment (5) comprises a water temperature sensor (6), a temperature and humidity sensor (7), a flow sensor (8) and a pressure sensor (9).
3. The central air-conditioning energy efficiency optimization system based on big data analysis according to claim 1, characterized in that: the terminal equipment (3) comprises a fresh air handling unit (10), a fan coil (11) and a plate heat exchanger (12).
4. The central air-conditioning energy efficiency optimization system based on big data analysis according to claim 1, characterized in that: the central air-conditioning room equipment (4) comprises a water chilling unit (13), a freezing pump (14) and a cooling pump (15).
5. The central air-conditioning energy efficiency optimization system based on big data analysis according to claim 4, characterized in that: the freezing pump (14) and the cooling pump (15) both adopt variable frequency water pumps.
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Cited By (8)
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| CN113685971A (en) * | 2021-08-02 | 2021-11-23 | 吉林建筑大学 | Constant-temperature heat supply automatic control circulation dynamic balance control system and method and data processing terminal |
| CN113883692A (en) * | 2021-10-28 | 2022-01-04 | 湖北合合能源科技发展有限公司 | Intelligent energy management system for energy conservation of air conditioner |
| CN114279053A (en) * | 2021-12-24 | 2022-04-05 | 湖北华工能源股份有限公司 | Central air-conditioning system based on COP band theory and control method |
| CN114527810A (en) * | 2022-02-17 | 2022-05-24 | 江苏锐天智能科技股份有限公司 | Temperature control data acquisition, mining and analysis system based on big data |
| CN114704922A (en) * | 2022-04-01 | 2022-07-05 | 南京亚派软件技术有限公司 | Energy efficiency analysis system of machine room air conditioner |
| CN114909781A (en) * | 2022-05-23 | 2022-08-16 | 浙江鑫帆暖通智控股份有限公司 | Building equipment intelligent group control system based on windows |
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| CN116951672A (en) * | 2023-09-20 | 2023-10-27 | 深圳中正信息科技有限公司 | Central air conditioner energy efficiency analysis method, device and readable storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113685971A (en) * | 2021-08-02 | 2021-11-23 | 吉林建筑大学 | Constant-temperature heat supply automatic control circulation dynamic balance control system and method and data processing terminal |
| CN113883692A (en) * | 2021-10-28 | 2022-01-04 | 湖北合合能源科技发展有限公司 | Intelligent energy management system for energy conservation of air conditioner |
| CN114279053A (en) * | 2021-12-24 | 2022-04-05 | 湖北华工能源股份有限公司 | Central air-conditioning system based on COP band theory and control method |
| CN115013943A (en) * | 2022-01-12 | 2022-09-06 | 武汉舒适易佰科技有限公司 | Intelligent air conditioner control system |
| CN114527810A (en) * | 2022-02-17 | 2022-05-24 | 江苏锐天智能科技股份有限公司 | Temperature control data acquisition, mining and analysis system based on big data |
| CN114527810B (en) * | 2022-02-17 | 2022-12-27 | 江苏锐天智能科技股份有限公司 | Temperature control data acquisition, mining and analysis system based on big data |
| CN114704922A (en) * | 2022-04-01 | 2022-07-05 | 南京亚派软件技术有限公司 | Energy efficiency analysis system of machine room air conditioner |
| CN114909781A (en) * | 2022-05-23 | 2022-08-16 | 浙江鑫帆暖通智控股份有限公司 | Building equipment intelligent group control system based on windows |
| CN116951672A (en) * | 2023-09-20 | 2023-10-27 | 深圳中正信息科技有限公司 | Central air conditioner energy efficiency analysis method, device and readable storage medium |
| CN116951672B (en) * | 2023-09-20 | 2024-02-23 | 深圳中正信息科技有限公司 | Central air conditioner energy efficiency analysis method, device and readable storage medium |
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