Thermoelectric conversion cooling control system and method based on 5g base station machine room

Abstract

The application discloses a thermoelectric conversion cooling control system based on a 5G base station machine room and a method thereof, wherein the cooling control system comprises a comprehensive complex signal acquisition module, which is used for acquiring data affecting temperature change; a signal conversion module, which is used for converting the data into 5G base station machine room temperature signals; a 5G transmission module, which is used for transmitting the temperature signals to a temperature precise control module; an adaptive cooling conditioning module, which is used for automatically adjusting the lowest temperature and the highest temperature interval and the refrigeration duration; the temperature precise control module, which is used for analyzing and processing the signals to generate temperature control instructions; and a thermoelectric conversion module, which is used for performing closed-loop feedback control on the environment according to the instructions. The application obtains various signals through an internet of things sensing network and sensors, simultaneously realizes signal modulation, realizes wireless transmission based on 5G communication technology, accelerates the data transmission speed and stability, and simultaneously realizes prediction of 5G machine room environment temperature values and precise control of target temperature.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of intelligent energy saving, in particular relates to a heat and electricity conversion cooling control system based on 5G base station machine room and a method thereof. BACKGROUND

[0002] Nowadays, fossil energy shortage and environmental pollution problems are highlighted, and energy diversification and efficient multi-stage utilization have become an important way to solve energy and environmental problems. As a green energy technology and environmentally friendly refrigeration technology, thermoelectric conversion technology has attracted widespread attention from academia and industry. Thermoelectric conversion technology is a technology that uses the Seebeck effect and Peltier effect of materials to directly convert heat and electricity, including thermoelectric power generation and thermoelectric refrigeration. This technology has the characteristics of small system size, high reliability, no emission of pollutants, and wide application temperature range. Thermoelectric devices can realize the direct conversion of heat and electricity, and have important research value in the fields of waste heat recovery and solid-state refrigeration.

[0003] 5G base station machine room has high energy consumption and large heat generation. Traditional room-level precision air conditioners are difficult to ensure safe and efficient operation of equipment. However, in traditional thermoelectric refrigeration technology solutions, temperature data acquisition often relies on wired temperature sensors, and temperature data is usually transmitted in a wired form, which increases labor costs and causes unstable data transmission. At the same time, the traditional refrigeration scheme usually only sets a threshold for the ambient temperature, resulting in poor refrigeration effect and the inability to achieve dynamic cooling. SUMMARY

[0004] The purpose of the present application is to provide a heat and electricity conversion cooling control system based on 5G base station machine room and a method thereof to solve the problems existing in the prior art.

[0005] In order to achieve the above-mentioned purpose, the present application provides a heat and electricity conversion cooling control system based on 5G base station machine room, which comprises a comprehensive complex signal acquisition module, a signal conversion module, a 5G transmission module, an adaptive cooling conditioning module, a temperature precision control module and a thermoelectric conversion module connected in sequence.

[0006] The comprehensive complex signal acquisition module is used to acquire the environmental temperature data, humidity, illumination, radiation and personnel access data of the 5G machine room. The comprehensive complex signal acquisition module comprises a plurality of wireless temperature sensors, and the environmental temperature data is an analog signal comprising the temperature value of the environment per unit time.

[0007] The signal conversion module is used to convert the environmental temperature data into 5G base station machine room temperature signals.

[0008] The 5G transmission module is used to transmit the 5G base station machine room temperature signals to the temperature precision control module.

[0009] The adaptive cooling conditioning module is used for automatically adjusting the set minimum temperature and maximum temperature interval and the refrigeration time length;

[0010] The temperature precise control module is used for analyzing and processing the 5G base station machine room temperature signal to generate a temperature control instruction;

[0011] The thermoelectric conversion module is used for performing closed-loop feedback control on the environment according to the temperature control instruction.

[0012] Optionally, the signal conversion module performs OFDM modulation on the environment temperature data to generate an OFDM signal, performs digital-analog conversion on the OFDM signal to generate a digital temperature signal, and decodes the digital temperature signal to generate the 5G base station machine room temperature signal in digital form.

[0013] Optionally, the 5G transmission module includes a 5G base station machine room, a 5G signal sending end and a 5G signal receiving end; the 5G signal sending end is arranged in the signal conversion module, the 5G signal receiving end is arranged in the temperature precise control module, and the signal sending end is used for sending the converted 5G base station machine room temperature signal to the 5G base station machine room, which is transmitted to the 5G signal receiving end through the 5G base station machine room.

[0014] Optionally, the temperature precise control module receives the 5G base station machine room temperature signal, simultaneously obtains the maximum environment temperature and the refrigeration time length through the temperature setting module, constructs a temperature change curve graph with time according to the 5G base station machine room temperature signal, constructs a temperature prediction model based on a convolutional neural network, inputs the change curve graph into the temperature prediction model, predicts the time for the current temperature to reach the maximum environment temperature, and obtains the cooling value at the current time according to the refrigeration time length and the time for the current temperature to reach the maximum environment temperature, and generates the temperature control instruction according to the cooling value.

[0015] Optionally, the thermoelectric conversion module includes a thermoelectric refrigerator, the thermoelectric refrigerator performs heat absorption refrigeration through Peltier effect, and the thermoelectric conversion module controls the power-on time length of the thermoelectric refrigerator according to the temperature control instruction.

[0016] In another aspect to achieve the above object, the present application provides a thermoelectric conversion cooling control method based on a 5G base station machine room, including the following steps:

[0017] Obtain various data influencing temperature change such as 5G machine room environment temperature, humidity, illumination, radiation and personnel access based on a wireless temperature sensor; the environment temperature data is an analog signal, including the temperature value of the environment per unit time;

[0018] Converting the ambient temperature data into a 5G base station room temperature signal based on OFDM modulation and transmitting the 5G base station room temperature signal based on 5G communication technology;

[0019] Setting a minimum temperature and a maximum temperature interval and a refrigeration duration;

[0020] Obtaining a cooling value at the current time based on the 5G base station room temperature signal, the maximum ambient temperature and the refrigeration duration;

[0021] Performing thermoelectric refrigeration based on the cooling value.

[0022] Optionally, the process of converting the ambient temperature data into a 5G base station room temperature signal comprises:

[0023] OFDM modulating the ambient temperature data to generate an OFDM signal, digitally-analog converting the OFDM signal to generate a digital temperature signal, and decoding the digital temperature signal to generate the 5G base station room temperature signal in digital form.

[0024] Optionally, the process of transmitting the 5G base station room temperature signal based on 5G communication technology comprises:

[0025] Setting a signal sending end in the wireless temperature sensor, sending the 5G base station room temperature signal to a 5G base station room based on the signal sending end, and transmitting based on the 5G base station room.

[0026] Optionally, the process of obtaining a cooling value at the current time based on the 5G base station room temperature signal, the maximum ambient temperature and the refrigeration duration comprises:

[0027] Constructing a temperature change curve graph over time based on the 5G base station room temperature signal, constructing a temperature prediction model based on a convolutional neural network, inputting the change curve graph into the temperature prediction model, predicting the time for the current temperature to reach the maximum ambient temperature, and obtaining a cooling value at the current time according to the refrigeration duration and the time for the current temperature to reach the maximum ambient temperature.

[0028] Optionally, the process of performing thermoelectric refrigeration based on the cooling value comprises:

[0029] Performing heat absorption refrigeration based on a thermoelectric refrigerator, and controlling the power-on duration of the thermoelectric refrigerator based on the cooling value at the current time.

[0030] The technical effects of the present application are:

[0031] This invention acquires various signals related to the influence of 5G data center ambient temperature through IoT sensing networks and their wireless sensors, modulates the simulated temperature signals, and realizes wireless data transmission based on 5G communication technology, thereby accelerating the data transmission speed and improving the stability of data acquisition. At the same time, by constructing temperature change curves and applying convolutional neural networks, it realizes the prediction of 5G data center ambient temperature values ​​and the precise control of target temperature. Attached Figure Description

[0032] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0033] Figure 1 This is a structural diagram of the thermoelectric conversion cooling control system based on a 5G base station equipment room in an embodiment of the present invention;

[0034] Figure 2 This is a flowchart of a thermoelectric conversion cooling control method for 5G base station equipment rooms according to an embodiment of the present invention. Detailed Implementation

[0035] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0036] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0037] Example 1

[0038] like Figure 1 As shown, this embodiment provides a thermoelectric conversion cooling control system based on a 5G base station equipment room. It includes a comprehensive complex signal acquisition module for acquiring various data affecting temperature changes, such as ambient temperature, humidity, light intensity, radiation, and personnel entry and exit within the 5G equipment room; a signal conversion module for converting the ambient temperature data into a 5G base station equipment room temperature signal; a 5G transmission module for transmitting the 5G base station equipment room temperature signal to a precise temperature control module; an adaptive cooling conditioning module for automatically adjusting the minimum and maximum temperature ranges and cooling duration; a precise temperature control module for analyzing and processing the 5G base station equipment room temperature signal to generate temperature control commands; and a thermoelectric conversion module for performing closed-loop feedback control of the environment based on the temperature control commands. The modules within the system are connected sequentially, specifically:

[0039] The complex comprehensive signal acquisition module includes a plurality of wireless temperature sensors, the wireless sensor has the advantages of small size, rich interface and convenient installation, can effectively obtain 5G machine room environment temperature, humidity, illumination, radiation and personnel access and other data affecting temperature change, therefore, the example realizes data monitoring and transmission through the Internet of Things sensing network and its sensor wireless sensor; the obtained environment temperature data is an analog signal, including the environment temperature value in a unit of time.

[0040] In the signal conversion module, the specific conversion process of the signal includes: after obtaining the various data affecting temperature change of the 5G machine room environment temperature, humidity, illumination, radiation and personnel access, the module modulates the environment temperature data by OFDM, generates an OFDM signal, converts the OFDM signal to a digital temperature signal, and decodes the digital temperature signal to generate a digital form of the 5G base station machine room temperature signal.

[0041] The system staff can input the highest temperature allowed to be reached by the monitored environment and the duration of continuous refrigeration in the adaptive cooling conditioning module according to the actual cooling target as the target of the system processing module.

[0042] The 5G transmission module includes a 5G base station machine room, a 5G signal sending end and a 5G signal receiving end; wherein the 5G signal sending end is arranged in the signal conversion module, the 5G signal receiving end is arranged in the temperature precise control module, the temperature data converted by the 5G signal sending end is transmitted to the 5G base station machine room, and then transmitted to the signal receiving end in the processing module for analysis and processing, the system applies the advantages of 5G communication technology to thermoelectric refrigeration technology, and improves the transmission speed and stability of data.

[0043] The data processing and analysis process of the temperature precise control module includes: after receiving the 5G base station machine room temperature signal, the lowest temperature and the highest temperature interval set by a person and the refrigeration duration are obtained through the temperature setting module at the same time, and the temperature value in unit time in the 5G base station machine room temperature signal is used to construct an environment temperature change curve diagram, and a temperature prediction model is constructed based on a convolutional neural network, the change curve diagram is input into the temperature prediction model, the model can obtain the temperature change trend in the curve time according to the curve diagram, the time for the current temperature to reach the set highest environment temperature can be predicted according to the change trend, and a time difference is obtained according to the time for the current temperature to reach the highest environment temperature and the refrigeration duration, the time difference represents the difference between the current temperature change to reach the highest temperature and the preset refrigeration duration, according to the time difference, the target temperature value at the current time can be obtained combined with the curve diagram of the temperature change with time, and the cooling value of the system can be obtained according to the target temperature value at the current time and the current temperature in the curve diagram, and finally the temperature control instruction for controlling the working duration of the thermoelectric conversion module is generated according to the cooling value.

[0044] The thermoelectric conversion module includes a thermoelectric refrigerator, the thermoelectric refrigerator realizes heat absorption refrigeration of the current environment according to the Peltier effect through two groups of semiconductors made of different metal materials, after the closed circuit of the thermoelectric refrigerator is powered on, a potential difference is formed between the two groups of semiconductor materials, and a temperature difference is formed through the potential difference, so that one of the two groups of materials becomes cold, so as to achieve the purpose of cooling and refrigeration.

[0045] Finally, the thermoelectric conversion module obtains the power-on duration of the thermoelectric refrigerator according to the temperature control instruction, and controls the thermoelectric refrigerator.

[0046] As shown in Figure 2 The embodiment provides a thermoelectric conversion cooling control method based on a 5G base station machine room, which includes the following steps:

[0047] Various data affecting temperature change such as 5G machine room environment temperature, humidity, illumination, radiation and personnel access are obtained based on a wireless temperature sensor; the environment temperature data is an analog signal, including the temperature value of the environment in unit time;

[0048] Based on OFDM modulation, the environment temperature data is converted into a 5G base station machine room temperature signal, and the 5G base station machine room temperature signal is transmitted based on 5G communication technology;

[0049] The lowest temperature and the highest temperature interval and the refrigeration duration are set;

[0050] The cooling value at the current time is obtained based on the 5G base station machine room temperature signal, the highest environment temperature and the refrigeration duration;

[0051] Based on the cooling value, thermoelectric refrigeration is performed.

[0052] As a preferred embodiment of the present application, the process of converting the ambient temperature data into a 5G base station room temperature signal includes:

[0053] The ambient temperature data is OFDM modulated to generate an OFDM signal, the OFDM signal is digital-analog converted to generate a digital temperature signal, and the digital temperature signal is decoded to generate the 5G base station room temperature signal in digital form.

[0054] As a preferred embodiment of the present application, the process of transmitting the 5G base station room temperature signal based on 5G communication technology includes:

[0055] A signal sending end is arranged in the wireless temperature sensor, the 5G base station room temperature signal is sent to the 5G base station room based on the signal sending end, and transmission is performed based on the 5G base station room.

[0056] As a preferred embodiment of the present application, the process of obtaining the cooling value at the current time based on the 5G base station room temperature signal, the highest ambient temperature and the refrigeration duration includes:

[0057] A temperature change curve graph is constructed based on the 5G base station room temperature signal, a temperature prediction model is constructed based on a convolutional neural network, the change curve graph is input into the temperature prediction model, the time for the current temperature to reach the highest ambient temperature is predicted, and the cooling value at the current time is obtained according to the refrigeration duration and the time for the current temperature to reach the highest ambient temperature.

[0058] As a preferred embodiment of the present application, the process of performing thermoelectric refrigeration based on the cooling value includes:

[0059] Based on the cooling value at the current time, the power-on duration of the thermoelectric refrigerator is controlled.

[0060] In the specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts between each embodiment can be referred to each other. For the method disclosed in the embodiment, since it corresponds to the system disclosed in the embodiment, the description is relatively simple, and the related part can be referred to the system part.

[0061] The above description is only the preferred embodiment of the present application, but the protection scope of the present application is not limited to this, any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A thermoelectric conversion cooling control system for 5G base station equipment rooms, characterized in that, It includes a comprehensive complex signal acquisition module, a signal conversion module, a 5G transmission module, an adaptive cooling and conditioning module, a precise temperature control module, and a thermoelectric conversion module, which are connected in sequence. The integrated complex signal acquisition module is used to acquire ambient temperature data, humidity, light intensity, radiation, and personnel entry and exit data of the 5G equipment room; the integrated complex signal acquisition module includes several wireless temperature sensors, and the ambient temperature data is an analog signal, including the ambient temperature value per unit time. The signal conversion module is used to convert the ambient temperature data into a 5G base station room temperature signal. The 5G transmission module is used to transmit the temperature signal of the 5G base station equipment room to the temperature precision control module; The adaptive cooling conditioning module is used to automatically adjust the range between the set minimum and maximum ambient temperatures and the cooling duration. The precise temperature control module is used to analyze and process the temperature signal of the 5G base station equipment room and generate temperature control commands. The thermoelectric conversion module is used to perform closed-loop feedback control of the environment according to the temperature control command; The precise temperature control module receives the temperature signal from the 5G base station equipment room, obtains the range between the lowest and highest ambient temperatures and the cooling duration through the temperature setting module, and constructs an ambient temperature change curve over time based on the temperature values ​​per unit time in the 5G base station equipment room temperature signal. A temperature prediction model is then built based on a convolutional neural network. The change curve is input into the temperature prediction model, which obtains the temperature change trend over the curve's time frame. Based on this trend, the model predicts the time it will take for the current temperature to reach the highest ambient temperature. A time difference is obtained based on the difference between the time it takes for the current temperature to reach the highest ambient temperature and the preset cooling duration. This time difference, combined with the temperature change curve over time, allows the acquisition of the target temperature value at the current moment. Based on the target temperature value and the current temperature in the curve, the cooling value at the current moment is obtained, and the temperature control command is generated based on this cooling value.

2. The thermoelectric conversion cooling control system based on 5G base station equipment room according to claim 1, characterized in that, The signal conversion module performs OFDM modulation on the ambient temperature data to generate an OFDM signal, performs digital-to-analog conversion on the OFDM signal to generate a digital temperature signal, and decodes the digital temperature signal to generate the digital form of the 5G base station room temperature signal.

3. The thermoelectric conversion cooling control system based on 5G base station equipment room according to claim 1, characterized in that, The 5G transmission module includes a 5G base station equipment room, a 5G signal transmitter, and a 5G signal receiver. The 5G signal transmitter is located within the signal conversion module, and the 5G signal receiver is located within the temperature precision control module. The signal transmitter is used to send the converted 5G base station equipment room temperature signal to the 5G base station equipment room, which then transmits the signal to the 5G signal receiver.

4. The thermoelectric conversion cooling control system based on 5G base station equipment room according to claim 1, characterized in that, The thermoelectric conversion module includes a thermoelectric cooler, which absorbs heat and cools through the Peltier effect. The thermoelectric conversion module controls the energizing time of the thermoelectric cooler according to the temperature control command.

5. A control method based on the thermoelectric conversion cooling control system for a 5G base station equipment room according to any one of claims 1-4, characterized in that, Includes the following steps: Data on ambient temperature, humidity, light intensity, radiation, and personnel entry and exit in the 5G data center are acquired using wireless temperature sensors; the ambient temperature data is an analog signal, including the ambient temperature value per unit time. Based on OFDM modulation, the ambient temperature data is converted into a 5G base station room temperature signal and transmitted based on 5G communication technology. Set the minimum and maximum ambient temperature ranges and the cooling time; The cooling value at the current moment is obtained based on the 5G base station equipment room temperature signal, the highest ambient temperature, and the cooling duration. Thermoelectric cooling is performed based on the aforementioned cooling value; The process of obtaining the current cooling value based on the 5G base station equipment room temperature signal, the highest ambient temperature, and the cooling duration includes: A temperature change curve over time is constructed based on the temperature signal of the 5G base station equipment room, and a temperature prediction model is constructed based on a convolutional neural network. The change curve is input into the temperature prediction model to predict the time when the current temperature will reach the highest ambient temperature, and the cooling value at the current moment is obtained based on the cooling duration and the time when the current temperature will reach the highest ambient temperature.

6. The control method for the thermoelectric conversion cooling control system based on a 5G base station equipment room according to claim 5, characterized in that, The process of converting the ambient temperature data into a 5G base station equipment room temperature signal includes: The ambient temperature data is OFDM modulated to generate an OFDM signal. The OFDM signal is then converted from digital to analog to generate a digital temperature signal. Finally, the digital temperature signal is decoded to generate the digital form of the 5G base station room temperature signal.

7. The control method for the thermoelectric conversion cooling control system based on a 5G base station equipment room according to claim 5, characterized in that, The process of transmitting the 5G base station room temperature signal based on 5G communication technology includes: A signal transmitting end is set in the wireless temperature sensor, and the temperature signal of the 5G base station equipment room is sent to the 5G base station equipment room based on the signal transmitting end, and the signal is transmitted based on the 5G base station equipment room.

8. The control method for the thermoelectric conversion cooling control system based on a 5G base station equipment room according to claim 5, characterized in that, The process of thermoelectric cooling based on the aforementioned cooling value includes: Thermoelectric coolers are used for heat absorption and cooling, and the energization time of the thermoelectric coolers is controlled based on the current temperature drop value.

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