Indoor temperature regulation and control method based on hybrid cooling system

Abstract

The invention discloses an indoor temperature regulation and control method based on a hybrid cooling system, and relates to an industrial equipment temperature control method. According to the method, an air conditioner cooling unit, a natural cold air introduction unit, an environment sensing system and a control system are integrated. The air-conditioning cooling unit adopts an efficient variable-frequency air-conditioning unit, so that the refrigeration power can be adjusted in real time; the natural cold air introduction unit realizes introduction and flow control of cold air through a pipeline system, an axial flow fan and an electric valve; according to the system, hybrid energy is utilized, multi-channel accurate adjustment and intelligent control are achieved, energy is saved, consumption is reduced (energy consumption is reduced by 30%-50% compared with that of a traditional system), temperature control precision is high (the temperature fluctuation range is reduced from + / -3 DEG C to + / -0.5 DEG C), and expansibility is high (modular design facilitates upgrading and reconstruction); the problems of the existing temperature control technology in the aspects of energy consumption, control accuracy and intelligent level are effectively solved, and wide application prospects and remarkable economic benefits are achieved.

Description

Technical Field

[0001] The present invention relates to a temperature control method for industrial equipment, specifically a method for regulating indoor temperature based on a hybrid cooling system. Background Art

[0002] In the field of industrial equipment temperature control technology, the temperature regulation of large indoor equipment is of crucial importance. Large equipment in places such as data centers and factory workshops generates a large amount of heat during operation. If the temperature cannot be controlled in a timely and effective manner, the performance of the equipment will be severely affected, and even failures may occur, leading to serious consequences such as production interruption and data loss.

[0003] Currently, there are many problems with traditional temperature regulation methods. In terms of cooling methods, single air-conditioning cooling exposes significant limitations. In the high-temperature season, traditional air-conditioning systems need to operate at a high load continuously to maintain the normal operating temperature of large indoor equipment, which results in a sharp increase in energy consumption. According to relevant data statistics, in some data centers, the energy consumption of the air-conditioning system in summer even accounts for more than 60% of the total energy consumption. In the low-temperature environment in winter, even though there is a large amount of available natural cold source outdoors, traditional air-conditioning systems still rely on their own refrigeration mechanisms and fail to effectively utilize this free cold energy, causing a great waste of energy.

[0004] Natural ventilation, as another common cooling method, also has deficiencies. Existing natural cold air introduction systems lack precision in control and cannot dynamically adjust the air flow according to the real-time changes in the indoor and outdoor temperature differences. In practical applications, when the indoor and outdoor temperature difference is small, it may not be able to introduce enough cold air to meet the heat dissipation requirements of the equipment; when the temperature difference is large, it may introduce too much cold air, resulting in excessive fluctuations in the indoor temperature or even overcooling, which not only affects the stable operation of the equipment but also may damage the service life of the equipment.

[0005] In terms of the degree of intelligence, most existing systems rely on manual operation and are difficult to respond in real time to complex and changeable environmental changes. When factors such as environmental temperature and equipment load change rapidly, manual operation often has delays and cannot adjust the operating parameters of the cooling system in a timely manner, resulting in low control efficiency. For example, in a data center, when the server load suddenly increases and generates a large amount of additional heat, the manually operated cooling system may not be able to react quickly, causing the equipment to be in a high-temperature environment for a long time and increasing the risk of equipment damage.

[0006] In summary, the existing temperature regulation technologies for large indoor equipment have many defects in terms of energy consumption, control precision, and intelligence level, and there is an urgent need for an innovative hybrid cooling system to solve these problems. Summary of the Invention

[0007] The object of the present invention is to provide an indoor temperature regulation method based on a hybrid cooling system. This method combines an air-conditioning refrigeration and natural cold air utilization hybrid cooling system, which can adjust the refrigeration power in real time. The natural cold air introduction unit realizes the introduction and flow control of cold air through a pipeline system, an axial flow fan, and an electric valve. The present invention utilizes hybrid energy, multi-channel precise regulation, and intelligent control, and is applicable to the temperature regulation of large indoor equipment such as data centers and factory workshops.

[0008] The object of the present invention is achieved through the following technical solutions:

[0009] An indoor temperature regulation method based on a hybrid cooling system, the method is a temperature regulation method for large indoor equipment that integrates multiple control strategies, including an air-conditioning cooling unit, a natural cold air introduction unit, an environmental perception system, and a control system;

[0010] The specific regulation process is as follows:

[0011] In the manual control mode, the operator manually sets the target temperature and the operating parameters of each device through the upper computer interface;

[0012] In the automatic control mode, historical meteorological data is collected, including temperature T, humidity H, air pressure P, wind speed V, and indoor equipment load data L, and the data is normalized. The normalization formula for temperature data is The normalization methods for humidity, air pressure, wind speed data, and indoor equipment load data L are similar;

[0013] The long short-term memory network (LSTM) model is used for training. The input gate calculation formula of the LSTM model is i t =σ(W ii x t +W hi h t-1 +b i );

[0014] The forgetting gate calculation formula:

[0015] The memory cell update formula:

[0016] The output gate calculation formula: o t =σ(W io x t +W ho h t-1 +b o );

[0017] The hidden state at the current moment: h t =o t *tanh(C t );

[0018] Input the normalized meteorological data and equipment load data monitored in real time into the trained LSTM model to predict the future change trend of meteorological data, and combine with the indoor set temperature T set , and adopt a fuzzy control algorithm to formulate a temperature control strategy. First, fuzzy the temperature deviation e = T set -T pred and the rate of change of temperature deviation Δe into fuzzy variables, then formulate fuzzy rules according to expert experience, obtain the fuzzy control quantity through the fuzzy inference synthesis algorithm, and finally use defuzzification methods such as the centroid method to convert the fuzzy control quantity into the air-conditioning power adjustment value ΔP, the fan speed adjustment value Δn, and the valve opening adjustment value Δα;

[0019] The environmental perception system uses a PT100 temperature sensor with an accuracy of ±0.1°C and a fast response speed to monitor the outdoor air temperature in real time, and obtains humidity, air pressure, and wind speed meteorological information through the meteorological data interface.

[0020] For the indoor temperature control method based on a hybrid cooling system, the upper computer control unit of the control system is composed of an industrial computer and a data acquisition card, and has a manual control mode and an automatic control mode.

[0021] For the indoor temperature control method based on a hybrid cooling system, the air-conditioning cooling unit selects a variable-frequency air-conditioning unit, and the unit adjusts the refrigeration power in real time according to the indoor load.

[0022] For the indoor temperature control method based on a hybrid cooling system, the natural cold air introduction unit includes:

[0023] A pipeline system that connects the indoor equipment area and the outdoor environment. The diameter of the main pipeline is in the range of 500mm - 1000mm, and the diameter of the branch channel is in the range of 200mm - 500mm. It uses polyurethane foam insulation pipe material, and the pipeline layout is designed according to the indoor equipment layout;

[0024] Axial fans are installed at the inlet and outlet of the pipeline. They use motors with adjustable speeds, and each fan can be independently controlled to start or stop, and the fan speed is regulated according to the indoor-outdoor temperature difference and temperature adjustment requirements;

[0025] Electric valves are set on the branch channels and are connected to the upper computer control system. By opening and closing and adjusting the opening degree, the cold air flow in each area is controlled.

[0026] For the indoor temperature control method based on a hybrid cooling system, in the high-temperature period in summer, air-conditioning cooling is the main method; in winter, natural cold air is preferentially used for cooling.

[0027] The advantages and positive effects of the present invention are:

[0028] 1. The hybrid energy utilization mode of the present invention: During the high-temperature period in summer, the system mainly focuses on air-conditioning cooling to effectively control the indoor temperature; in winter in suitable areas, natural cold air is preferentially utilized for cooling, significantly reducing the energy consumption of air conditioners. Compared with the traditional single air-conditioning refrigeration system, it can reduce energy consumption by 30%-50%, achieving efficient energy utilization.

[0029] 2. The multi-channel precise temperature regulation of the present invention: By increasing the number of branch channels and valve control, independent temperature regulation of different indoor areas can be achieved. Taking a data center as an example, the heat generation situations of different cabinets are different. By precisely controlling the cold air flow rate of each branch channel, it can ensure that each cabinet is at the optimal working temperature, improving the stability and service life of the equipment.

[0030] 3. The intelligent control strategy of the present invention: Combining manual control with automatic control by AI algorithms, it not only meets the manual intervention requirements under special working conditions but also realizes the automated and intelligent operation of the system using AI algorithms. Through real-time data analysis and intelligent decision-making, the system can quickly respond to environmental changes, control the temperature fluctuation range within ±0.5°C, and achieve precise control of the indoor temperature.

[0031] 4. The present invention has remarkable energy conservation and consumption reduction: Through the effective utilization of natural cold air in winter and intelligent control strategies, the comprehensive annual energy consumption is reduced by 30%-50% compared with the traditional system, greatly reducing the operating cost.

[0032] 5. The present invention has high temperature control accuracy: Multi-channel regulation and intelligent control make the indoor temperature more uniform and stable. The temperature fluctuation range is reduced from ±3°C in the traditional system to ±0.5°C, providing a better operating environment for indoor equipment.

[0033] 6. The present invention has strong scalability: The system adopts a modular design, and the number of branch channels and equipment configuration can be flexibly increased or decreased according to actual needs, facilitating system upgrade and transformation to adapt to indoor places of different scales and requirements. It achieves the goals of high-efficiency energy conservation and precise temperature control, and has broad application prospects and significant economic benefits. Description of the Drawings

[0034] Figure 1 It is the overall architecture diagram of the system of the present invention;

[0035] Figure 2 It is the working principle diagram of the air-conditioning cooling unit of the present invention;

[0036] Figure 3 It is the pipeline layout diagram of the natural cold air introduction unit of the present invention;

[0037] Figure 4 It is the automatic control flow chart of the present invention. Detailed Implementation Modes

[0038] The composition of the present invention includes:

[0039] 1) An air-conditioning cooling unit;

[0040] 2) A natural cold air introduction unit;

[0041] 3) An environmental perception system;

[0042] 4) A control system;

[0043] 5) Based on the hybrid cooling system, the temperature of large indoor equipment is regulated.

[0044] The implementation steps of the present invention:

[0045] Step 1: Select a high-efficiency variable-frequency air-conditioning unit. With advanced variable-frequency technology, this unit can adjust the refrigeration power in real time according to the indoor load. When the load of indoor equipment is low, it automatically reduces the refrigeration power to reduce energy consumption; during the peak load period, it quickly increases the refrigeration capacity to maintain a stable indoor temperature.

[0046] Step 2

[0047] Pipeline system: Specifically design a pipeline network connecting the indoor equipment area and the outdoor environment. The main pipeline is designed with a large diameter to ensure sufficient air flow. The branch channels are reasonably distributed according to the layout of indoor equipment to meet the temperature regulation needs of different areas. Select high-quality thermal insulation materials such as polyurethane foam insulation pipes as the pipeline material to effectively reduce heat loss during transmission. The diameter of the main pipeline can be set within the range of 500mm - 1000mm according to actual needs, and the diameter of the branch channels is 200mm - 500mm.

[0048] Airflow regulation components:

[0049] Axial flow fans: Install high-performance axial flow fans at the inlet and outlet of the pipeline. The fans are equipped with motors with adjustable speeds, and each fan can be independently controlled to start or stop. According to the temperature difference between indoor and outdoor and the temperature regulation needs, the fan speed is accurately regulated to achieve precise adjustment of the air flow. For example, when there is sufficient outdoor cold air, the fan speed is increased to introduce more cold air; when the indoor temperature approaches the set value, the fan speed is reduced to maintain a stable temperature.

[0050] Electric valves: Set electric valves on each branch channel. Through the opening and closing and opening degree adjustment of the valves, precise control of the cold air flow in each area is achieved. Each electric valve is connected to the upper computer control system and can quickly respond according to real-time temperature data and control instructions to ensure uniform distribution of indoor temperature.

[0051] Step 3 Outdoor temperature detector: A PT100 temperature sensor with an accuracy of up to ±0.1°C and a fast response speed is used to monitor the outdoor temperature in real time and transmit the data to the host computer in real time. At the same time, combined with the meteorological data interface, more comprehensive meteorological information such as humidity, air pressure, and wind speed is obtained.

[0052] Step 4 Host computer control unit:

[0053] Hardware composition: It is composed of a high-performance industrial computer and a data acquisition card, with powerful data processing and control capabilities.

[0054] Manual control mode: Operators can manually set the target temperature and the operating parameters of each device through the host computer interface. For example, under specific production process requirements, operators adjust the air conditioner power, fan speed, and valve opening according to experience and actual conditions to ensure that the indoor temperature meets the process requirements.

[0055] Automatic control mode: Collect historical meteorological data (including temperature T, humidity H, air pressure P, wind speed V, etc.) and indoor equipment load data L, and perform normalization processing on the data.

[0056] Temperature data normalization formula:

[0057]

[0058] Where T min and T max are the minimum and maximum values in the historical temperature data respectively. Similar normalization methods are also used for data such as humidity, air pressure, wind speed, and indoor equipment load data L.

[0059]

[0060] Machine learning model training: The long short-term memory network (LSTM), a time series prediction model, is used. The core structure of LSTM includes the input gate i t forget gate f t , output gate o t and memory cell C t .

[0061] Input gate calculation formula: i t =σ(W ii x t +W hi h t-1 +b i )

[0062] Where σ is the sigmoid activation function, W ii and W hi are weight matrices, x t is the input at the current moment, ht-1 is the hidden state at the previous moment, b i is the bias.

[0063] Forget gate calculation formula:

[0064] Memory cell update formula:

[0065]

[0066] where tanh is the hyperbolic tangent activation function.

[0067] Output gate calculation formula: o t = σ(W io x t + W ho h t-1 + b o )

[0068] Hidden state at the current moment: h t = o t * tanh(C t )

[0069] Train the LSTM model with a large amount of historical data so that it learns the variation laws of meteorological data and equipment load data over time.

[0070] Weather prediction and strategy formulation: Input the normalized meteorological data and equipment load data monitored in real time into the trained LSTM model to predict the meteorological data within the next day, such as the variation trends of temperature T pred and humidity H pred etc. According to the prediction results, combined with the indoor set temperature T set , adopt a fuzzy control algorithm to formulate a temperature control strategy.

[0071] First, the temperature deviation e = T set - T predThe temperature deviation and its change rate Δe are fuzzified into fuzzy variables. For example, the temperature deviation is divided into fuzzy subsets such as negative big (NB), negative medium (NM), negative small (NS), zero (ZE), positive small (PS), positive medium (PM), and positive big (PB). The membership degree in each fuzzy subset is determined through the membership function. Then, fuzzy rules are formulated based on expert experience, such as "if the temperature deviation is positive big and the change rate of temperature deviation is positive small, then increase the air-conditioning cooling power and decrease the fan speed". Finally, the fuzzy control quantity is obtained through the fuzzy inference synthesis algorithm, and then the fuzzy control quantity is converted into an accurate control quantity by using defuzzification methods such as the centroid method, such as the air-conditioning power adjustment value ΔP, the fan speed adjustment value Δn, and the valve opening adjustment value Δα, to achieve precise control of the indoor temperature. For example, when it is predicted that the outdoor temperature will continue to drop in the next few hours and the indoor equipment load is low, according to the fuzzy control calculation results, automatically control the opening of an appropriate number of fans and reduce the fan speed to introduce an appropriate amount of natural cold air for cooling; when it is predicted that the temperature will rise rapidly, adjust the air-conditioning power in advance and reduce the introduction amount of natural cold air at the same time to ensure that the indoor temperature is always stable within the set range.

[0072] Step 5 is based on the hybrid cooling system to control the temperature of large indoor equipment.

[0073] As shown in the figure, the specific embodiment of the present invention includes the following steps:

[0074] Step 1: Select a high-efficiency variable-frequency air-conditioning unit. With advanced variable-frequency technology, this unit can adjust the cooling power in real time according to the indoor load. When the indoor equipment load is low, it automatically reduces the cooling power to reduce energy consumption; during the peak load period, it quickly increases the cooling capacity to maintain the indoor temperature stable;

[0075] Step 2:

[0076] Pipeline system: Specifically design a pipeline network connecting the indoor equipment area and the outdoor environment. The main pipeline is designed with a large diameter to ensure sufficient air flow, and the branch channels are reasonably distributed according to the layout of indoor equipment to meet the temperature adjustment requirements of different areas. Select high-quality thermal insulation materials such as polyurethane foam insulation pipes as the pipeline material to effectively reduce the heat loss during transmission.

[0077] Axial flow fans: Install high-performance axial flow fans at the inlet and outlet of the pipeline. The fans use motors with adjustable speeds, and each fan can be independently controlled to turn on or off. According to the indoor-outdoor temperature difference and temperature adjustment requirements, accurately control the fan speed to achieve precise adjustment of the air flow. For example, when there is sufficient outdoor cold air, increase the fan speed to introduce more cold air; when the indoor temperature is close to the set value, reduce the fan speed to maintain a stable temperature.

[0078] Electric valves: Electric valves are installed on each branch channel. By adjusting the opening and closing of the valves and their degrees of opening, precise control over the cold air flow in each area is achieved. Each electric valve is connected to the upper computer control system and can quickly respond according to real-time temperature data and control instructions to ensure uniform distribution of indoor temperature;

[0079] Step 3: Outdoor air temperature detector: A PT100 temperature sensor with an accuracy of up to ±0.1°C and a fast response speed is used to monitor the outdoor air temperature in real time and transmit the data to the upper computer in real time. At the same time, combined with the meteorological data interface, more comprehensive meteorological information such as humidity, air pressure, and wind speed is obtained.;

[0080] Step 4:

[0081] Manual control mode: Operators can manually set the target temperature and the operating parameters of each device through the upper computer interface.

[0082] Automatic control mode: Historical meteorological data (including temperature T, humidity H, air pressure P, wind speed V, etc.) and indoor equipment load data L are collected, and the data is normalized.

[0083] Machine learning model training: The long short-term memory network (LSTM), a time series prediction model, is used. The core structure of LSTM includes the input gate i t forget gate f t 、output gate o t and memory cell C t .

[0084] The LSTM model is trained with a large amount of historical data to enable it to learn the variation laws of meteorological data and equipment load data over time.

[0085] Weather prediction and strategy formulation: The normalized meteorological data and equipment load data monitored in real time are input into the trained LSTM model to predict the meteorological data within the next day, such as the variation trends of temperature T pred 、humidity H pred , etc. According to the prediction results, combined with the indoor set temperature T set , a temperature control strategy is formulated using the fuzzy control algorithm.

[0086] First, the temperature deviation e = T set -T predThe temperature deviation and its change rate Δe are fuzzified into fuzzy variables. For example, the temperature deviation is divided into fuzzy subsets such as negative big (NB), negative medium (NM), negative small (NS), zero (ZE), positive small (PS), positive medium (PM), and positive big (PB). The membership degree in each fuzzy subset is determined through the membership function. Then, fuzzy rules are formulated based on expert experience, such as "if the temperature deviation is positive big and the change rate of temperature deviation is positive small, then increase the air-conditioning cooling power and decrease the fan speed". Finally, the fuzzy control quantity is obtained through the fuzzy inference synthesis algorithm, and then the fuzzy control quantity is converted into an accurate control quantity by using defuzzification methods such as the centroid method, such as the air-conditioning power adjustment value ΔP, the fan speed adjustment value Δn, and the valve opening adjustment value Δα, to achieve precise control of the indoor temperature. For example, when it is predicted that the outdoor temperature will continue to drop in the next few hours and the indoor equipment load is low, according to the fuzzy control calculation results, an appropriate number of fans are automatically controlled to be turned on and the fan speed is reduced to introduce an appropriate amount of natural cold air for cooling; when it is predicted that the temperature will rise rapidly, the air-conditioning power is adjusted in advance and the introduction amount of natural cold air is reduced at the same time to ensure that the indoor temperature is always stable within the set range;

[0087] Step 5: Hybrid energy utilization mode: During the high-temperature period in summer, the system mainly uses air-conditioning cooling to effectively control the indoor temperature; in winter in suitable areas, natural cold air is preferentially used for cooling, greatly reducing the air-conditioning energy consumption. Compared with the traditional single air-conditioning refrigeration system, the energy consumption can be reduced by 30%-50%, realizing the efficient utilization of energy.

[0088] Multi-channel precise temperature adjustment: By increasing the number of branch channels and valve control, independent temperature adjustment of different indoor areas can be achieved. Taking a data center as an example, the heat generation situations of different cabinets are different. By precisely controlling the cold air flow of each branch channel, it can be ensured that each cabinet is at the optimal working temperature, improving the stability and service life of the equipment.

[0089] Intelligent control strategy: Combining manual control and automatic control by AI algorithms not only meets the manual intervention requirements under special working conditions but also realizes the automatic and intelligent operation of the system by using AI algorithms. Through real-time data analysis and intelligent decision-making, the system can quickly respond to environmental changes, control the temperature fluctuation range within ±0.5°C, and achieve precise control of the indoor temperature.

[0090] The above specific implementation manners are used to explain and illustrate the present invention, rather than limiting the present invention. Any modification and change made to the present invention within the scope of the purpose and claims of the present invention fall within the protection scope of the present invention.

Claims

1. A method for controlling indoor temperature based on a hybrid cooling system, characterized in that: The method is a temperature control method for large indoor equipment that integrates multiple control strategies, including an air conditioning cooling unit, a natural cold air introduction unit, an environmental sensing system, and a control system; The specific control process is: In manual control mode, the operator manually sets the target temperature and operating parameters of each device through the host computer interface; In the automatic control mode, historical meteorological data are collected, including temperature T, humidity H, air pressure P, wind speed V and indoor equipment load data L, and the data are normalized. The temperature data normalization formula is: The normalization method of humidity, air pressure, wind speed data and indoor equipment load data L is similar; The long short-term memory network (LSTM) model is used for training. The input gate calculation formula of the LSTM model is i t =σ(W ii x t +W hi h t-1 +b i ); Forget gate calculation formula: Memory unit update formula: Output gate calculation formula: t =σ(W io x t +W ho h t-1 +b o ); Current hidden state: h t =o t *tanh(C t ); The normalized meteorological data and equipment load data monitored in real time are input into the trained LSTM model to predict the future trend of meteorological data changes, combined with the indoor set temperature T set , the fuzzy control algorithm is used to formulate the temperature control strategy. First, the temperature deviation e = T set -T pred The temperature deviation change rate Δe is fuzzified into fuzzy variables, and then fuzzy rules are formulated based on expert experience. The fuzzy control quantity is obtained through the fuzzy reasoning synthesis algorithm. Finally, the fuzzy control quantity is converted into the air conditioning power adjustment value ΔP, the fan speed adjustment value Δn and the valve opening adjustment value Δα by using the defuzzification method such as the center of gravity method. The environmental sensing system uses a PT100 temperature sensor with an accuracy of ±0.1°C and a fast response speed to monitor the outdoor temperature in real time, and combines it with the meteorological data interface to obtain meteorological information such as humidity, air pressure, and wind speed.

2. The indoor temperature control method based on the hybrid cooling system according to claim 1 is characterized in that: The host computer control unit of the control system is composed of an industrial computer and a data acquisition card, and has a manual control mode and an automatic control mode.

3. The indoor temperature control method based on a hybrid cooling system according to claim 1, characterized in that: The air conditioning cooling unit uses a variable frequency air conditioning unit, which adjusts the cooling power in real time according to the indoor load.

4. The indoor temperature control method based on a hybrid cooling system according to claim 1, characterized in that: The natural cold air introduction unit comprises: The pipeline system connects the indoor equipment area with the outdoor environment. The diameter of the main pipeline is in the range of 500mm-1000mm, and the diameter of the branch channel is in the range of 200mm-500mm. It uses polyurethane foam insulation pipe material, and the pipeline layout is designed according to the indoor equipment layout; Axial flow fans are installed at the inlet and outlet of the duct and use motors with adjustable speed. Each fan can be independently controlled to turn on or off, and the fan speed can be adjusted according to the indoor and outdoor temperature difference and temperature regulation requirements; The electric valve is installed on the branch channel and connected to the host control system. It controls the cold air flow in each area by opening and closing and adjusting the opening degree.

5. The indoor temperature control method based on a hybrid cooling system according to claim 1, characterized in that: The method mainly uses air conditioning for cooling during the high temperature period in summer; in winter, natural cold air is preferentially used for cooling.

Images