Digital twinning-based central air-conditioning high-efficiency refrigerating machine room analogue simulation system and method

Abstract

The invention relates to the technical field of refrigerating machine room energy efficiency, and discloses a central air-conditioning efficient refrigerating machine room analogue simulation system and method based on digital twinning, and a real-time data acquisition module, a data online analysis module, a system behavior prediction module and a dynamic adjustment control module are established. The real-time data acquisition module is divided into a power supply data unit, a refrigeration data unit, an environment data unit, a ventilation pipeline data unit and an IT load data unit, the data online analysis module calculates the electric energy utilization efficiency # imgabs0 #, the average cold load # imgabs1 # and the total energy consumption # imgabs2 #, and the system behavior prediction module predicts the real-time data according to the electric energy utilization efficiency # imgabs3 #, the average cold load # imgabs4 # and the total energy consumption # imgabs5 #. The system behavior prediction module predicts future energy demand and load change conditions, and the dynamic adjustment control module performs unit parameter adjustment on the power supply data unit, the refrigeration data unit, the environment data unit, the ventilation pipeline data unit and the IT load data unit according to the energy demand and load change predicted by the system behavior prediction module.

Description

Technical Field

[0001] The present invention relates to the field of refrigeration room energy efficiency technology, and specifically to a central air-conditioning high-efficiency refrigeration room simulation system and method based on digital twins. Background Art

[0002] In the application of simulation systems and methods for high-efficiency refrigeration rooms of central air conditioners, technological development has gradually evolved from relying on basic computing platforms and static control strategies to using advanced digital twin technology and intelligent control. Traditional simulation systems and methods, such as the M-DHECS Midea high-efficiency refrigeration room system simulation optimization design platform, significantly improve the energy efficiency of the room system through functions such as load calculation, system equipment selection, operation logic and economic analysis. This traditional method focuses on the optimization of refrigeration room hardware and energy consumption analysis, and improves efficiency by adjusting actual physical parameters.

[0003] However, the existing technology has some defects, mainly in the static nature of its control strategy, which requires manual adjustment according to the actual operating conditions or automatic adjustment based on preset programs. This method cannot fully adapt to the real-time changes in system operation, which may lead to inflexible and timely energy efficiency management. In order to solve these problems, simulation systems and methods based on digital twins have been proposed and begun to be applied. This technology not only includes all the functions of traditional methods, but also adds the ability of real-time data processing, system behavior prediction, and dynamic adjustment of control strategies. The digital twin model can adjust itself according to the changing working conditions, predict future states, and optimize control strategies in a timely manner, thereby efficiently managing and optimizing energy efficiency.

[0004] In short, the simulation system and method of the central air-conditioning high-efficiency refrigeration room based on digital twins have significant advantages in achieving real-time data monitoring, intelligent optimization and full life cycle management. This integration of technologies not only improves the design accuracy and operation efficiency of the system, but also plays an important role in reducing operation and maintenance costs, improving system reliability and sustainability. Summary of the invention

[0005] 1. Technical issues to be resolved In view of the shortcomings of the prior art, the present invention provides a central air-conditioning high-efficiency refrigeration room simulation system and method based on digital twins, which has the advantages of real-time data processing, system behavior prediction, and dynamic adjustment of control strategies, solving the problem in the prior art that manual adjustments are required according to actual operating conditions or automatic adjustments rely on preset programs.

[0006] (II) Technical solution To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a central air-conditioning high-efficiency refrigeration room simulation system based on digital twin, comprising a real-time data acquisition module, a data online analysis module, a system behavior prediction module, and a dynamic adjustment control module; The real-time data acquisition module includes a power supply data unit, a cooling data unit, an environmental data unit, a ventilation pipeline data unit and an IT load data unit; The power supply data unit collects power supply data through sensors, measuring devices and online smart meters, the power supply data unit collects power supply data through online monitoring equipment and sensors, the cooling data unit collects cooling data through sensors, the environment data unit collects environment data through sensors and data acquisition equipment, the ventilation duct data unit collects ventilation duct data through air volume meters and sensors, the IT load data unit collects IT load data through sensors and data acquisition equipment, and the power supply data unit, cooling data unit, environment data unit, ventilation duct data unit and IT load data unit are connected to the data online analysis module through a network; The data online analysis module includes an energy utilization unit, an average cooling load unit and an energy consumption unit. The energy utilization unit calculates the energy utilization efficiency based on the power supply data and IT load data. The average cooling load unit calculates the average cooling load based on the cooling data, environmental data and ventilation pipeline data. The energy consumption unit calculates the total energy consumption based on the refrigeration data, environmental data and ventilation pipeline data. , the electric energy utilization unit, the average cooling load unit and the energy consumption unit are connected to the system behavior prediction module through a network; The system behavior prediction module is based on the power utilization efficiency , average cooling load and total energy consumption , predicting future energy demand and load changes, the system behavior prediction module is connected to the dynamic adjustment control module through a network; The dynamic adjustment control module adjusts the unit parameters of the power supply data unit, the cooling data unit, the environment data unit, the ventilation pipeline data unit and the IT load data unit respectively according to the energy demand and load change predicted by the system behavior prediction module.

[0007] Preferably, the power supply data unit numbers the power consumption of all devices when the central air conditioner is running according to the power supply data characteristics, and the power supply data number is , , ,… The cooling data unit numbers the power consumption energy of the cooling system according to the cooling data characteristics, and monitors the power consumption energy of the cooling system and the flow rate of the coolant in real time. The power consumption energy of the cooling system is numbered as , , ,… , the flow rate of the coolant in the cooling system is numbered as , , ,… .

[0008] Preferably, the environmental data unit numbers the environmental equipment power consumption energy and the coolant temperature at the inlet and outlet of the cooling system according to the environmental data characteristics, and the environmental equipment power consumption energy is numbered as follows: , , ,… , the coolant temperature at the inlet of the cooling system is numbered , , ,… , the coolant temperature at the outlet is numbered as , , ,… .

[0009] Preferably, the ventilation pipeline data unit numbers the ventilation pipeline electricity consumption energy according to the ventilation pipeline data characteristics, and the ventilation pipeline electricity consumption energy number is , , ,… .

[0010] Preferably, the IT load data unit numbers the power consumed by all IT devices when the central air conditioner is running according to the IT load data characteristics, and the IT load data number is , , ,… .

[0011] Preferably, the power utilization unit calculates the power utilization efficiency according to the power supply data and IT load data , and its calculation formula is:

[0012] In the formula, It represents the efficiency of electric energy utilization. , , ,… Indicates power supply data. Indicates the statistical The power supply data corresponding to each device, , , ,… Indicates IT load data, Indicates the statistical IT load data corresponding to each device, Indicates the total number of power supply devices counted.

[0013] Preferably, the average cooling load unit calculates the average cooling load according to the refrigeration data, the environmental data and the ventilation pipeline data. , and its calculation formula is:

[0014] In the formula, represents the average cooling load, , , ,… Indicates the coolant temperature at the inlet of the cooling system, Indicates the cooling system statistics. The coolant temperature at the inlet of each cooling device, , , ,… represents the coolant temperature at the outlet, Indicates the cooling system statistics. The coolant temperature at the outlet of each cooling device, , , ,… Indicates the flow rate of coolant in the cooling system. Indicates the cooling system statistics. The flow rate of the coolant corresponding to each cooling device, Indicates the total number of cooling devices counted.

[0015] Preferably, the energy consumption unit calculates the total energy consumption based on the refrigeration data, environmental data and ventilation pipeline data. , and its calculation formula is:

[0016] In the formula, represents the total energy consumption, , , ,… Indicates the energy consumed by electricity in the cooling system. , , ,… Indicates the energy consumption of ventilation pipes. , , ,… Indicates the energy consumed by environmental equipment.

[0017] Preferably, the system behavior prediction module and the dynamic adjustment control module are based on the power utilization efficiency , average cooling load and total energy consumption The forecasting and adjustment process is: The power supply data unit optimizes the load distribution of the distribution line according to the prediction data and adjusts the power supply frequency and voltage; The refrigeration data unit adjusts the operating state of the refrigeration equipment or adjusts the cooling temperature and flow rate according to the predicted average cooling load demand; The environmental data unit adjusts the operation mode of the air conditioning system according to the predicted environmental parameters to adjust the fresh air system and the exhaust system; The ventilation pipeline data unit adjusts the air volume of the ventilation system and the opening and closing state of the air outlet according to the predicted air quality and temperature changes; The IT load data unit adjusts the server operating status of the data center according to the predicted computing demand.

[0018] Preferably, a simulation method for a central air-conditioning high-efficiency refrigeration room based on digital twins comprises the following steps: Step 1: Establish a real-time data acquisition module, an online data analysis module, a system behavior prediction module, and a dynamic adjustment control module; Step 2: The real-time data acquisition module is divided into a power supply data unit, a cooling data unit, an environmental data unit, a ventilation pipeline data unit, and an IT load data unit; Step 3: The data online analysis module is divided into power utilization unit, average cooling load unit and energy consumption unit, and the power utilization efficiency is calculated. , average cooling load and total energy consumption ; Step 4: System behavior prediction module based on power utilization efficiency , average cooling load and total energy consumption , predict future energy demand and load changes; Step 5: The dynamic adjustment control module adjusts the unit parameters of the power supply data unit, the cooling data unit, the environmental data unit, the ventilation pipeline data unit and the IT load data unit according to the energy demand and load changes predicted by the system behavior prediction module.

[0019] Compared with the prior art, the present invention provides a central air-conditioning high-efficiency refrigeration room simulation system and method based on digital twins, which has the following beneficial effects: 1. The present invention calculates the efficiency of electric energy utilization , average cooling load and total energy consumption , adjusting the parameters of the power supply data unit, cooling data unit, environmental data unit, ventilation pipe data unit and IT load data unit respectively, will help improve the efficiency and response speed of the entire system, thereby achieving effective energy management while increasing the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the structure of the present invention; Figure 2 It is a step diagram of the method of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] See also Figure 1 - Figure 2 , a simulation system for high-efficiency central air-conditioning refrigeration room based on digital twin, including real-time data acquisition module, online data analysis module, system behavior prediction module, and dynamic adjustment control module; The real-time data acquisition module includes power supply data unit, cooling data unit, environmental data unit, ventilation pipeline data unit and IT load data unit; The power supply data unit collects power supply data through sensors, measuring devices and online smart meters. The power supply data unit collects power supply data through online monitoring equipment and sensors. The refrigeration data unit collects refrigeration data through sensors. The environment data unit collects environment data through sensors and data acquisition equipment. The ventilation duct data unit collects ventilation duct data through air volume meters and sensors. The IT load data unit collects IT load data through sensors and data acquisition equipment. The power supply data unit, the refrigeration data unit, the environment data unit, the ventilation duct data unit and the IT load data unit are connected to the data online analysis module through a network. The data online analysis module includes power utilization unit, average cooling load unit and energy consumption unit. The power utilization unit calculates the power utilization efficiency based on the power supply data and IT load data. The average cooling load unit calculates the average cooling load based on the cooling data, environmental data and ventilation pipeline data. The energy consumption unit calculates the total energy consumption based on the refrigeration data, environmental data and ventilation pipeline data. ,The power utilization unit, the average cooling load unit and the energy consumption unit are connected with the system behavior prediction module through a network; The system behavior prediction module is based on the power utilization efficiency , average cooling load and total energy consumption ,To predict future energy demand and load changes, the system behavior prediction module is connected with the ,dynamic adjustment control module through the network; The dynamic adjustment control module adjusts the unit parameters of the power supply data unit, the cooling data unit, the environmental data unit, the ventilation pipeline data unit and the IT load data unit respectively according to the energy demand and load changes predicted by the system behavior prediction module.

[0023] The power supply data unit numbers the power consumption of all devices when the central air conditioner is running according to the power supply data characteristics. The power supply data number is , , ,… The cooling data unit numbers the power consumption energy of the cooling system according to the cooling data characteristics, and monitors the power consumption energy of the cooling system and the flow rate of the coolant in real time. The power consumption energy of the cooling system is numbered as , , ,… , the flow rate of the coolant in the cooling system is numbered , , ,… .

[0024] The environmental data unit numbers the power consumption energy of the environmental equipment and the coolant temperature at the inlet and outlet of the cooling system according to the environmental data characteristics. The power consumption energy of the environmental equipment is numbered as , , ,… , the coolant temperature at the inlet of the cooling system is numbered , , ,… , the coolant temperature at the outlet is numbered , , ,… .

[0025] The ventilation pipeline data unit numbers the ventilation pipeline electricity consumption energy according to the ventilation pipeline data characteristics. The ventilation pipeline electricity consumption energy number is , , ,… .

[0026] The IT load data unit numbers the power consumed by all IT equipment when the central air conditioner is running according to the IT load data characteristics. The IT load data number is , , ,… .

[0027] The power utilization unit calculates power utilization efficiency based on power supply data and IT load data , and its calculation formula is:

[0028] In the formula, It represents the efficiency of electric energy utilization. , , ,… Indicates power supply data. Indicates the statistical The power supply data corresponding to each device, , , ,… Indicates IT load data, Indicates the statistical IT load data corresponding to each device, Indicates the total number of power supply devices counted.

[0029] Advantages: By calculating the efficiency of electric energy utilization ,The power supply data unit optimizes the load distribution of the distribution lines according to the ,prediction data of the system behavior prediction module to adjust the power supply frequency and ,voltage to ensure the stability and efficiency of the power supply.

[0030] The average cooling load unit calculates the average cooling load based on the cooling data, environmental data and ventilation pipe data , and its calculation formula is:

[0031] In the formula, represents the average cooling load, , , ,… Indicates the coolant temperature at the inlet of the cooling system, Indicates the cooling system statistics. The coolant temperature at the inlet of each cooling device, , , ,… represents the coolant temperature at the outlet, Indicates the cooling system statistics. The coolant temperature at the outlet of each cooling device, , , ,… Indicates the flow rate of coolant in the cooling system. Indicates the cooling system statistics. The flow rate of the coolant corresponding to each cooling device, Indicates the total number of cooling devices counted.

[0032] Advantages: By calculating the average cooling load ,The refrigeration data unit adjusts the operating status of the refrigeration equipment (such as turning on or off the refrigeration equipment) or adjusts the cooling temperature and flow rate according to the average cooling load demand predicted by the system behavior prediction module to meet the actual demand in the future time period, optimize the startup and shutdown time of the refrigeration system, and improve energy efficiency.

[0033] The energy consumption unit calculates the total energy consumption based on the cooling data, environmental data and ventilation pipeline data , and its calculation formula is:

[0034] In the formula, represents the total energy consumption, , , ,… Indicates the energy consumed by electricity in the cooling system. , , ,… Indicates the energy consumption of ventilation pipes. , , ,… Indicates the energy consumed by environmental equipment.

[0035] Advantages: By calculating the total energy consumption ,The ventilation duct data unit adjusts the air volume of the ventilation system according to the air quality and temperature changes predicted by the system behavior prediction module, automatically adjusts the opening and closing state of the air vents, optimizes the air circulation path, controls the noise level of the ventilation system, and improves the user experience.

[0036] The system behavior prediction module and the dynamic adjustment control module are based on the power utilization efficiency , average cooling load and total energy consumption The forecasting and adjustment process is: The power supply data unit optimizes the load distribution of the distribution lines based on the forecast data, adjusts the power supply frequency and voltage, and ensures the stability and efficiency of the power supply; The cooling data unit adjusts the operating status of the cooling equipment (such as turning on or off the cooling equipment) or adjusts the cooling temperature and flow rate according to the predicted average cooling load demand to meet the actual demand in the future time period, optimize the startup and shutdown time of the cooling system, and improve energy efficiency; The environmental data unit adjusts the operation mode of the air conditioning system according to the predicted environmental parameters (such as temperature and humidity) to adjust the fresh air system and exhaust system, maintain the indoor air quality, realize the intelligent adjustment of the environmental control system, and improve the comfort of users; The ventilation duct data unit adjusts the air volume of the ventilation system according to the predicted air quality and temperature changes, adjusts the opening and closing status of the air vents, optimizes the air circulation path, controls the noise level of the ventilation system, and improves the user experience; The IT load data unit adjusts the server operation status of the data center according to the predicted computing demand, optimizes the power consumption mode of the storage system, reduces the energy consumption of IT equipment, implements virtualization technology, and dynamically allocates computing resources to adapt to different workloads; Advantages: By calculating the efficiency of electric energy utilization , average cooling load and total energy consumption , adjusting the parameters of the power supply data unit, cooling data unit, environmental data unit, ventilation pipe data unit and IT load data unit respectively, will help improve the efficiency and response speed of the entire system, thereby achieving effective energy management while increasing the user experience.

[0037] The simulation method of a central air-conditioning high-efficiency refrigeration room based on digital twin includes the following steps: Step 1: Establish a real-time data acquisition module, an online data analysis module, a system behavior prediction module, and a dynamic adjustment control module; Step 2: The real-time data acquisition module is divided into a power supply data unit, a cooling data unit, an environmental data unit, a ventilation pipeline data unit, and an IT load data unit; Step 3: The data online analysis module is divided into power utilization unit, average cooling load unit and energy consumption unit, and the power utilization efficiency is calculated. , average cooling load and total energy consumption ; Step 4: System behavior prediction module based on power utilization efficiency , average cooling load and total energy consumption , predict future energy demand and load changes; Step 5: The dynamic adjustment control module adjusts the unit parameters of the power supply data unit, the cooling data unit, the environmental data unit, the ventilation pipeline data unit and the IT load data unit according to the energy demand and load changes predicted by the system behavior prediction module.

[0038] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital twin-based central air-conditioning high-efficiency refrigeration room simulation system, characterized by: It includes real-time data acquisition module, online data analysis module, system behavior prediction module, and dynamic adjustment control module; The real-time data acquisition module includes a power supply data unit, a cooling data unit, an environmental data unit, a ventilation pipeline data unit and an IT load data unit; The power supply data unit collects power supply data through sensors, measuring devices and online smart meters, the power supply data unit collects power supply data through online monitoring equipment and sensors, the cooling data unit collects cooling data through sensors, the environment data unit collects environment data through sensors and data acquisition equipment, the ventilation pipeline data unit collects ventilation pipeline data through air volume meters and sensors, the IT load data unit collects IT load data through sensors and data acquisition equipment, and the power supply data unit, cooling data unit, environment data unit, ventilation pipeline data unit and IT load data unit are connected to the data online analysis module through a network; The data online analysis module includes an energy utilization unit, an average cooling load unit and an energy consumption unit. The energy utilization unit calculates the energy utilization efficiency based on the power supply data and IT load data. The average cooling load unit calculates the average cooling load based on the cooling data, environmental data and ventilation pipeline data. The energy consumption unit calculates the total energy consumption based on the refrigeration data, environmental data and ventilation pipeline data. , the electric energy utilization unit, the average cooling load unit and the energy consumption unit are connected to the system behavior prediction module through a network; The system behavior prediction module is based on the power utilization efficiency , average cooling load and total energy consumption , predicting future energy demand and load changes, the system behavior prediction module is connected to the dynamic adjustment control module through a network; The dynamic adjustment control module adjusts the unit parameters of the power supply data unit, the cooling data unit, the environment data unit, the ventilation pipeline data unit and the IT load data unit respectively according to the energy demand and load change predicted by the system behavior prediction module.

2. The digital twin-based central air-conditioning high-efficiency refrigeration room simulation system according to claim 1 is characterized in that: The power supply data unit numbers the power consumption of all devices when the central air conditioner is running according to the power supply data characteristics. The power supply data number is , , ,… The cooling data unit numbers the power consumption energy of the cooling system according to the cooling data characteristics, and monitors the power consumption energy of the cooling system and the flow rate of the coolant in real time. The power consumption energy of the cooling system is numbered as , , ,… , the flow rate of the coolant in the cooling system is numbered as , , ,… .

3. The central air-conditioning high-efficiency refrigeration room simulation system based on digital twin according to claim 1 is characterized in that: The environmental data unit numbers the environmental equipment power consumption energy and the coolant temperature at the inlet and outlet of the cooling system according to the environmental data characteristics. The environmental equipment power consumption energy number is , , ,… , the coolant temperature at the inlet of the cooling system is numbered , , ,… , the coolant temperature at the outlet is numbered as , , ,… .

4. The central air-conditioning high-efficiency refrigeration room simulation system based on digital twin according to claim 1 is characterized in that: The ventilation pipeline data unit numbers the ventilation pipeline electricity consumption energy according to the ventilation pipeline data characteristics, and the ventilation pipeline electricity consumption energy number is , , ,… .

5. The digital twin-based central air-conditioning high-efficiency refrigeration room simulation system according to claim 1 is characterized in that: The IT load data unit numbers the power consumed by all IT devices when the central air conditioner is running according to the IT load data characteristics. The IT load data number is , , ,… .

6. The digital twin-based central air-conditioning high-efficiency refrigeration room simulation system according to claim 5 is characterized by: The power utilization unit calculates the power utilization efficiency according to the power supply data and IT load data , and its calculation formula is: In the formula, It represents the efficiency of electric energy utilization. , , ,… Indicates power supply data. Indicates the statistical The power supply data corresponding to each device, , , ,… Indicates IT load data, Indicates the statistical IT load data corresponding to each device, Indicates the total number of power supply devices counted.

7. The digital twin-based central air-conditioning high-efficiency refrigeration room simulation system according to claim 4 is characterized in that: The average cooling load unit calculates the average cooling load based on the cooling data, the environmental data and the ventilation pipeline data. , and its calculation formula is: In the formula, represents the average cooling load, , , ,… Indicates the coolant temperature at the inlet of the cooling system, Indicates the cooling system statistics. The coolant temperature at the inlet of each cooling device, , , ,… represents the coolant temperature at the outlet, Indicates the cooling system statistics. The coolant temperature at the outlet of each cooling device, , , ,… Indicates the flow rate of coolant in the cooling system. Indicates the cooling system statistics. The flow rate of the coolant corresponding to each cooling device, Indicates the total number of cooling devices counted.

8. The digital twin-based central air-conditioning high-efficiency refrigeration room simulation system according to claim 5 is characterized by: The energy consumption unit calculates the total energy consumption based on the refrigeration data, environmental data and ventilation pipeline data , and its calculation formula is: In the formula, represents the total energy consumption, , , ,… Indicates the energy consumed by electricity in the cooling system. , , ,… Indicates the energy consumption of ventilation pipes. , , ,… Indicates the energy consumed by environmental equipment.

9. The digital twin-based central air-conditioning high-efficiency refrigeration room simulation system according to claim 8 is characterized in that: The system behavior prediction module and the dynamic adjustment control module are based on the power utilization efficiency , average cooling load and total energy consumption The forecasting and adjustment process is: The power supply data unit optimizes the load distribution of the distribution line according to the prediction data and adjusts the power supply frequency and voltage; The refrigeration data unit adjusts the operating state of the refrigeration equipment or adjusts the cooling temperature and flow rate according to the predicted average cooling load demand; The environmental data unit adjusts the operation mode of the air conditioning system according to the predicted environmental parameters to adjust the fresh air system and the exhaust system; The ventilation pipeline data unit adjusts the air volume of the ventilation system and the opening and closing state of the air outlet according to the predicted air quality and temperature changes; The IT load data unit adjusts the server operating status of the data center according to the predicted computing demand.

10. A simulation method for a central air-conditioning high-efficiency refrigeration room based on digital twins, characterized in that: The following steps are involved: Step 1: Establish a real-time data acquisition module, an online data analysis module, a system behavior prediction module, and a dynamic adjustment control module; Step 2: The real-time data acquisition module is divided into a power supply data unit, a cooling data unit, an environmental data unit, a ventilation pipeline data unit, and an IT load data unit; Step 3: The data online analysis module is divided into power utilization unit, average cooling load unit and energy consumption unit, and the power utilization efficiency is calculated. , average cooling load and total energy consumption ; Step 4: System behavior prediction module based on power utilization efficiency , average cooling load and total energy consumption , predict future energy demand and load changes; Step 5: The dynamic adjustment control module adjusts the unit parameters of the power supply data unit, the cooling data unit, the environmental data unit, the ventilation pipeline data unit and the IT load data unit according to the energy demand and load changes predicted by the system behavior prediction module.

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