A communication base station energy consumption optimization management system

Abstract

This invention relates to the field of base station energy consumption optimization technology, and in particular to a communication base station energy consumption optimization management system. The system includes analyzing historical service data of base stations, calculating service fluctuation values ​​and representative service values ​​for each local time period, merging similar time periods to divide base stations into co-frequency time periods, and then integrating multi-dimensional data to calculate a comprehensive energy efficiency coefficient. It accurately classifies base stations into two categories: transferring base stations and receiving base stations, and then calculates the service load energy consumption and new energy consumption, calculates the net transfer benefit, and outputs the optimal transfer signal. Through coordinated resource utilization between base stations, inefficient base stations can reduce their operating load or even enter an energy-saving state, while fully leveraging the resource utilization capabilities of efficient base stations, thereby reducing overall communication network energy consumption. This invention not only reduces the electricity costs of communication operators but also reduces the aging risk caused by long-term high-load operation of equipment, improving equipment lifespan and network operational stability.

Description

Technical Field

[0001] This invention relates to the field of base station energy consumption optimization technology, and in particular to a communication base station energy consumption optimization management system. Background Technology

[0002] With the rapid development of 5G networks, the Internet of Things, and edge computing technologies, the deployment scale of communication base stations continues to expand, and the number of base stations is showing a rapid growth trend. Because communication base stations need to operate continuously around the clock, their wireless equipment, transmission equipment, power supply equipment, and air conditioning and refrigeration equipment all continuously consume a large amount of electrical energy, making communication base stations one of the most important energy-consuming units in communication networks.

[0003] However, wireless communication equipment, transmission equipment, and equipment room cooling equipment need to operate continuously for a long time, which leads to a continuous increase in operating costs. In order to reduce base station energy consumption, existing technologies usually adopt energy-saving measures such as equipment hibernation, carrier shutdown, and air conditioning constant temperature control. However, most existing solutions are based on independent management of a single base station and implement energy-saving control only based on the equipment operating status. They lack in-depth analysis of historical service patterns and are difficult to accurately predict service change trends, resulting in a lag in energy-saving strategies.

[0004] Meanwhile, although adjacent base stations have the ability to coordinate service carrying, they cannot make full use of the energy efficiency differences between different base stations, resulting in some low-energy-efficiency base stations operating at high energy consumption. On the other hand, base station energy consumption is affected by a variety of factors such as ambient temperature, service load and equipment power consumption. Existing evaluation methods mostly use a single indicator for analysis, which makes it difficult to accurately reflect the actual operating efficiency of base stations and thus reduce the overall energy consumption of communication base stations. Summary of the Invention

[0005] The purpose of this invention is to solve the problems in the background art by proposing a communication base station energy consumption optimization management system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A communication base station energy consumption optimization management system, comprising:

[0008] The information acquisition module is used to collect basic information about the communication base station;

[0009] The service analysis module is used to analyze the historical service volume of the target base station based on the basic information of the communication base station, determine the service fluctuation value of each local time period, and determine the service representative value of each local time period based on the service fluctuation value. Then, according to the adjacent service representative values, the corresponding local time periods are merged to determine the co-frequency time period of the target base station.

[0010] The energy efficiency analysis module is used to calculate the comprehensive energy efficiency coefficient based on the current ambient temperature, real-time traffic volume and equipment power consumption, and to determine the compensation base station based on the comprehensive energy efficiency coefficient. The compensation base station includes the transfer base station and the receiving base station.

[0011] The transfer decision module is used to analyze the load operating energy consumption and increased operating energy consumption in the compensation base station, calculate the net transfer benefit, and determine the transfer signal based on the net transfer benefit.

[0012] The temperature control module is used to analyze the service volume of the receiving base station and the base station with normal energy efficiency during the same frequency period and determine the target pre-cooling temperature.

[0013] The action execution module is used to receive the transfer signal, obtain the compensation base station corresponding to the transfer signal, transfer the traffic of the transfer base station in the compensation base station to the receiving base station, and at the same time obtain the target pre-cooling temperature of the corresponding receiving base station or the energy-efficient base station, and issue pre-cooling instructions in real time.

[0014] As a further aspect of the present invention, the method for calculating the business fluctuation value includes:

[0015] Select any communication base station in the base station group and mark this communication base station as the target base station. First, based on the basic information of the communication base station, obtain the service coverage range of the target base station under normal conditions and obtain the historical service volume of the target base station.

[0016] Set the cycle time and unit time, and divide the cycle time into several local time periods based on the unit time. The cycle time is 24 hours and the unit time is set to 1 hour.

[0017] Historical traffic volume is divided into local time periods to obtain local traffic volume. Then, an arbitrary local time period is selected within the periodic time period and marked as the target analysis period. At the same time, all local traffic volumes of the target analysis period are obtained and calculated using the formula. The business fluctuation value Bw is obtained, where Li represents different local business volumes in the target analysis period, and i∈[1,n] indicates that there are n data points in the target analysis period, and La is the mean of the local business volume.

[0018] As a further aspect of the present invention, the method for determining the business representative value includes:

[0019] The business fluctuation value Bw is compared with the fluctuation threshold By1. If Bw≤By1, the local business volume of this target analysis period is averaged and the average calculation result is marked as the business representative value of the target analysis period. If Bw>By1, the business representative value of this target period is divided into normal business data and abnormal business data.

[0020] Obtain normal business data and perform mean processing on the normal business data. Mark the obtained numerical results as the business representative values ​​for the target analysis period. Normal business data refers to data whose business representative values ​​belong to the region [La-2×Bw, La+2×Bw], and abnormal business data refers to data whose business representative values ​​do not belong to the region [La-2×Bw, La+2×Bw].

[0021] As a further aspect of the present invention, the method for determining the same frequency time period includes:

[0022] Starting from the first business representative value in the data sequence, adjacent business representative values ​​are selected sequentially and labeled L1 and L2 respectively. If L1 ≤ By2, then merge the local time periods belonging to L1 and L2 into the same frequency time period, and continue to judge L3; if If >By2, then the connection is broken after L1, and L2 becomes the starting point of the next new same-frequency period; and so on, until the entire data sequence is traversed, eventually forming several continuous same-frequency periods with gentle internal fluctuations.

[0023] As a further aspect of the present invention, the method for calculating the comprehensive energy efficiency coefficient includes:

[0024] Select any target base station in the base station group, collect the ambient temperature of the current target base station, then obtain the current real-time traffic volume Lsy of the target base station, and at the same time collect the current main equipment power consumption Ws and temperature control equipment power consumption Wk of the target base station.

[0025] Using calculation formula The overall energy efficiency coefficient Ec is obtained, where Tk is the temperature coefficient corresponding to the ambient temperature and c is a constant coefficient.

[0026] As a further aspect of the present invention, the method for determining the compensation base station includes:

[0027] Calculate the comprehensive energy efficiency coefficient Ec of other base stations in the base station group in turn, and compare the comprehensive energy efficiency coefficient Ec with the energy efficiency threshold Ey. When Ec≥Ey, the corresponding base station is marked as a normal energy efficiency base station, and when Ec<Ey, the corresponding base station is marked as an abnormal energy efficiency base station.

[0028] All base stations with abnormal energy efficiency are obtained, and their corresponding comprehensive energy efficiency coefficients are arranged in descending order to obtain a base station sequence. Then, the last base station with abnormal energy efficiency in the base station sequence and the first base station with abnormal energy efficiency are set as a pair of compensation base stations, the second to last base station with abnormal energy efficiency and the second base station with abnormal energy efficiency are set as a pair of compensation base stations, and so on, to obtain multiple compensation base stations.

[0029] Two energy-efficient base stations, G1 and G2, are identified among the compensation base stations. The comprehensive energy efficiency coefficients of the two energy-efficient base stations are compared. If the comprehensive energy efficiency coefficient of G1 is greater than that of G2, then G1 is used as the receiving base station and G2 is used as the transfer base station. If the comprehensive energy efficiency coefficient of G1 is less than that of G2, then G1 is used as the transfer base station and G2 is used as the receiving base station.

[0030] As a further aspect of the present invention, the method for determining the transfer signal includes:

[0031] Select a pair of compensation base stations, obtain the co-frequency time periods corresponding to the transferring base station and the receiving base station based on the current time, take the intersection of the co-frequency time periods, and mark the time period corresponding to the intersection as the common time period;

[0032] Obtain the service representative value of the transferred base station during the public period, and obtain the corresponding load operating energy consumption Ff based on this service representative value. At the same time, obtain the service representative value of the receiving base station, add the service representative value of the receiving base station to the service representative value of the transferred base station to obtain the comprehensive service value, obtain the operating energy consumption under the original service representative value of the receiving base station and the operating energy consumption corresponding to the comprehensive service value, and then subtract the operating energy consumption corresponding to the original service representative value from the operating energy consumption corresponding to the comprehensive service value to obtain the operating energy consumption increase Fz.

[0033] Among them, load operation energy consumption and increased operation energy consumption include equipment energy consumption and temperature control energy consumption, respectively;

[0034] Using calculation formula The net transfer benefit Ys is obtained, where Fs is the additional energy consumption caused during the transfer of the communication base station;

[0035] The net transfer income Ys is compared with the estimated income threshold Y1. If Ys ≥ Y1, a transfer signal is triggered; if Ys < Y1, a reset signal is generated.

[0036] As a further aspect of the present invention, when a transfer signal is detected, a one-way communication connection is established between the transfer decision module and the energy efficiency analysis module. According to the comprehensive energy efficiency coefficient calculation method in the energy efficiency analysis module, the comprehensive energy efficiency coefficient of the receiving base station after receiving the service representative value of the transfer base station is calculated. If the comprehensive energy efficiency coefficient is greater than or equal to the energy efficiency threshold Ey, the receiving base station is marked as a normal energy efficiency base station. If the comprehensive energy efficiency coefficient is less than the energy efficiency threshold Ey, the receiving base station is marked as an abnormal energy efficiency base station again. The abnormal energy efficiency base stations are then rearranged according to the above method to obtain a new base station sequence.

[0037] When a reset signal is generated, the corresponding energy-efficient base station is directly put back into the base station sequence, and the transfer signal is obtained again in the same way.

[0038] As a further aspect of the present invention, the method for determining the target precooling temperature includes:

[0039] Obtain the current real-time temperature Tems of a base station with normal energy efficiency. Simultaneously, based on the service representative volume Ldsz of the current co-frequency period or the comprehensive service value Ldsz of the common period, use the calculation formula... The target pre-cooling temperature Tbw is obtained, where Qws represents the heat generation coefficient per unit of traffic, Area represents the base station area, and R represents the building's insulation coefficient.

[0040] As a further aspect of the present invention, during the calculation of the target pre-cooling temperature, the receiving base station corresponds to the comprehensive service value of the public period, and the energy efficiency normal base station corresponds to the service representative value of the same frequency period. If a base station has both the receiving base station and the energy efficiency normal base station tags, the priority of the receiving base station is greater than that of the energy efficiency normal base station.

[0041] Compared with existing technologies, the advantages of this invention are:

[0042] This invention analyzes historical service data from base stations, calculates service fluctuation values ​​and representative service values ​​for each local time period, merges similar time periods to divide base stations into co-frequency time periods, and then integrates multi-dimensional data to calculate a comprehensive energy efficiency coefficient. It accurately classifies base stations into two categories: transferring base stations and receiving base stations. Subsequently, it calculates service load energy consumption and additional energy consumption, calculates the net transfer benefit, and outputs the optimal transfer signal. Through coordinated resource utilization between base stations, inefficient base stations can reduce their operating load or even enter an energy-saving state, while fully leveraging the resource utilization capabilities of efficient base stations, thereby reducing overall communication network energy consumption. Furthermore, by combining co-frequency time periods and base station service representative volume, the optimal target pre-cooling temperature is determined. The action execution module completes the cross-base station migration of services and issues air conditioning pre-cooling commands. Compared to the passive response method of traditional temperature control systems, this invention can complete temperature adjustment in advance before the arrival of service peaks, reducing the instantaneous heat dissipation pressure during equipment operation. Moreover, while ensuring the continuity of communication services, this invention achieves dynamic balanced distribution of service load and optimized utilization of energy resources. This not only reduces the electricity costs of communication operators but also reduces the aging risk caused by long-term high-load operation of equipment, improving equipment lifespan and network operational stability. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0044] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0045] Reference Figure 1 A communication base station energy consumption optimization management system includes an information acquisition module, a service analysis module, an energy efficiency analysis module, a transfer decision module, a temperature control module, and an action execution module.

[0046] The information acquisition module is used to collect basic information about the communication base station. This basic information includes the internal structure information and the external distribution information of the communication base station. Specifically, the internal structure information refers to the physical composition, parameters, and operating status of the base station equipment room, tower, main equipment, and supporting systems. The external distribution information refers to the geographical location of the base station, the surrounding environment, the coverage area, the relationship with neighboring stations, and the electromagnetic and geographical distribution. Then, the information acquisition module establishes a one-way communication connection with the service analysis module and the energy efficiency analysis module, respectively, and transmits the basic information of the communication base station to the service analysis module and the energy efficiency analysis module.

[0047] The service analysis module is used to analyze the inertial services of the target base station and determine the service representative value of the target base station. The specific methods for determining the service representative value include:

[0048] Select any communication base station in the base station group, take this communication base station as an example, and mark this communication base station as the target base station. First, based on the basic information of the communication base station, obtain the service coverage of the target base station under normal conditions, and obtain the historical service volume of the target base station.

[0049] The cycle time is set, wherein in this embodiment, the cycle time is 24 hours, and further, the time range is set to 8:00 AM to 8:00 AM the next day. At the same time, a unit time is set, and based on the unit time, the cycle time is divided into several local time periods, wherein the unit time in this embodiment is set to 1 hour.

[0050] Historical traffic volume is divided into local time periods to obtain local traffic volume. Then, an arbitrary local time period is selected within the periodic time period. Taking this local time period as an example, it is marked as the target analysis period. At the same time, all local traffic volumes of the target analysis period are obtained, and the calculation formula is used. The business fluctuation value Bw is obtained, where Li represents different local business volumes in the target analysis period, and i∈[1,n] indicates that there are n data in the target analysis period, and La is the mean of the local business volume;

[0051] The business fluctuation value Bw is compared with the fluctuation threshold By1. If Bw≤By1, the local business volume of this target analysis period is averaged and the average calculation result is marked as the business representative value of the target analysis period. If Bw>By1, the business representative value of this target period is divided into normal business data and abnormal business data.

[0052] Obtain normal business data and perform mean processing on it. Mark the resulting numerical values ​​as representative business values ​​for the target analysis period. Normal business data refers to representative business values ​​belonging to the region [La-2×Bw, La+2×Bw], while abnormal business data refers to representative business values ​​not belonging to the region [La-2×Bw, La+2×Bw]. Furthermore, By1 is not a pre-specified fixed value, but a statistical threshold determined based on the fluctuation distribution of historical normal operation data; specifically, the fluctuation value corresponding to the corresponding quantile position can be selected as By1 based on the distribution characteristics of historical data.

[0053] The business representative values ​​for all local time periods are obtained using the method described above. Then, the business representative values ​​are arranged in chronological order to obtain a data sequence.

[0054] Based on adjacent business representative values ​​in the data sequence, corresponding local time periods are merged to obtain time periods with the same frequency. Further, the methods for determining time periods with the same frequency include:

[0055] Starting from the first business representative value in the data sequence, adjacent business representative values ​​are selected sequentially and labeled L1 and L2 respectively. If L1 ≤ By2, then merge the local time periods belonging to L1 and L2 into the same frequency time period, and continue to judge L3; if If the value is greater than By2, the connection is broken after L1, and L2 serves as the starting point for the next new synchronous frequency period. This process continues until the entire data sequence is traversed, ultimately forming several continuous synchronous frequency periods with relatively smooth internal fluctuations. Here, By2 is a threshold value, and the specific value of By2 is set by those skilled in the art based on big data experience. Furthermore, By2 is not a fixed value pre-specified, but a statistical threshold determined based on the fluctuation distribution of historical normal operation data. Specifically, the fluctuation value corresponding to the corresponding quantile position can be selected as By2 based on the distribution characteristics of historical data.

[0056] Then, a one-way communication connection is established between the business analysis module and the transfer decision module, and the business representative value and the same frequency time period are transmitted to the transfer decision module;

[0057] The energy efficiency analysis module is used to analyze the energy efficiency status of base stations and determine the transfer direction of the base stations. The specific methods for determining the transfer direction include:

[0058] Select any target base station in the base station group, collect the ambient temperature of the current target base station, then obtain the current real-time traffic volume Lsy of the target base station, and at the same time collect the current main equipment power consumption Ws and temperature control equipment power consumption Wk of the target base station.

[0059] Then use the calculation formula The overall energy efficiency coefficient Ec is obtained, where Tk is the temperature coefficient corresponding to the ambient temperature and c is a constant coefficient.

[0060] Furthermore, there is a rule table corresponding to the ambient temperature and the temperature coefficient, and the specific correspondence method is obtained by those skilled in the art after big data calculation. In this embodiment, the specific establishment method is based on the historical operation data of the target base station: by dividing the historical ambient temperature into multiple temperature ranges, the service volume, main equipment power consumption and temperature control equipment power consumption in each temperature range are statistically analyzed, and the comprehensive energy efficiency level corresponding to each temperature range is calculated accordingly. Then, the comprehensive energy efficiency level of each temperature range is compared with the benchmark temperature range to obtain the corresponding temperature coefficient, thereby forming the correspondence between ambient temperature and temperature coefficient.

[0061] Following the same method, the comprehensive energy efficiency coefficient Ec of other base stations in the base station group is calculated sequentially. The comprehensive energy efficiency coefficient Ec is compared with the energy efficiency threshold Ey. When Ec≥Ey, the corresponding base station is marked as a normal energy efficiency base station. When Ec<Ey, the corresponding base station is marked as an abnormal energy efficiency base station. In this embodiment, the method for determining the value of Ey is as follows: sort the comprehensive energy efficiency coefficient Ec of all base stations in the base station group from largest to smallest, select the base station ranked in the bottom K1% (e.g., the bottom 20%) and mark it as an abnormal energy efficiency base station. At this time, the comprehensive energy efficiency coefficient ranked in the (1-K1)% position is the current energy efficiency threshold Ey.

[0062] Furthermore, the larger the overall energy efficiency coefficient, the higher the energy efficiency conversion of the corresponding base station and the lower the energy cost of effective communication; the smaller the overall energy efficiency coefficient, the lower the energy efficiency conversion of the corresponding base station and the higher the energy cost of effective communication.

[0063] In one embodiment of the present invention, for example in a specific implementation scenario, a target base station A is selected. The system collects the current ambient temperature of the base station in real time, which is 25 degrees Celsius. According to the preset rule table, the corresponding temperature coefficient Tk=1.2 is obtained. At the same time, the current real-time traffic volume of the target base station A is obtained as Lsy=5000Mbps, the power consumption of the main equipment is Ws=1500W, and the power consumption of the temperature control equipment (air conditioner) is Wk=500W. Assuming the constant coefficient c=1 (to prevent the denominator from being zero), the physical quantities are substituted into the formula for calculation, resulting in Ec=2.99. As a comparative test, during the high-temperature period, the real-time traffic volume Lsy of the same base station drops to 2000Mbps, but due to exposure to sunlight, the ambient temperature reaches 35 degrees Celsius, corresponding to Tk=0.8. With the backup power consumption Ws=1500W remaining constant and the temperature control equipment operating at full load Wk=1500W, substituting the physical quantities into the formula yields Ec=0.53. Through the actual calculation of the above physical quantities, it can be seen that when the energy cost of converting the target base station into effective communication is low (as in the first scenario), the Ec value is relatively large (2.99); when the base station consumes a large amount of ineffective energy for heat dissipation (as in the second scenario), the Ec value is significantly reduced (0.53). Through this quantitative formula that divides the service volume by the thermodynamic power consumption, the system can accurately identify abnormal base stations in a "high-consumption, low-efficiency" state, thus providing absolutely reliable data support for subsequent load transfer or hibernation commands, effectively achieving the technical effect of reducing overall energy consumption.

[0064] All base stations with abnormal energy efficiency are obtained, and their corresponding comprehensive energy efficiency coefficients are arranged in descending order to obtain a base station sequence. Then, the last base station with abnormal energy efficiency in the base station sequence and the first base station with abnormal energy efficiency are set as a pair of compensation base stations, the second to last base station with abnormal energy efficiency and the second base station with abnormal energy efficiency are set as a pair of compensation base stations, and so on, to obtain multiple compensation base stations.

[0065] Two energy-efficient base stations, G1 and G2, are identified among the compensation base stations. The comprehensive energy efficiency coefficients of the two energy-efficient base stations are compared. If the comprehensive energy efficiency coefficient of G1 is greater than that of G2, then G1 is used as the receiving base station and G2 is used as the transfer base station. If the comprehensive energy efficiency coefficient of G1 is less than that of G2, then G1 is used as the transfer base station and G2 is used as the receiving base station.

[0066] Then, a one-way communication connection is established between the energy efficiency analysis module and the transfer decision module, and the compensation base station is transmitted to the transfer decision module;

[0067] The handover decision module is used to analyze the energy consumption in the compensation base station. Specific processing methods include:

[0068] Choose any pair of compensation base stations, taking this compensation base station as an example, based on the current time, obtain the same frequency time period corresponding to the transfer base station and the receiving base station, take the intersection of the same frequency time period, and mark the time period corresponding to the intersection as the common time period;

[0069] Obtain the service representative value of the transferred base station during the public period, and obtain the corresponding load operating energy consumption Ff based on this service representative value. At the same time, obtain the service representative value of the receiving base station, add the service representative value of the receiving base station to the service representative value of the transferred base station to obtain the comprehensive service value, obtain the operating energy consumption under the original service representative value of the receiving base station and the operating energy consumption corresponding to the comprehensive service value, and then subtract the operating energy consumption corresponding to the original service representative value from the operating energy consumption corresponding to the comprehensive service value to obtain the operating energy consumption increase Fz.

[0070] Among them, load operation energy consumption and increased operation energy consumption include equipment energy consumption and temperature control energy consumption, respectively;

[0071] Then use the calculation formula The net transfer benefit Ys is obtained, where Fs is the additional energy consumption caused during the transfer of the communication base station;

[0072] The net transfer income Ys is compared with the estimated income threshold Y1. If Ys ≥ Y1, a transfer signal is triggered. If Ys < Y1, a reset signal is generated. Furthermore, the specific value of the estimated income threshold Y1 is set by those skilled in the art based on big data experience. In this embodiment, the specific value of the estimated income threshold Y1 is set to 100.

[0073] For example, during a certain public period, base station A plans to transfer the services (representative service value) of its edge sector to receiving base station B. At this time, the following data is collected and calculated: if base station A unloads this part of the service, the total energy consumption of its corresponding sleepable radio frequency equipment and the corresponding temperature control energy consumption will decrease, i.e., the load operation energy consumption Ff = 800W. After receiving base station B takes over the service, the total increase in its equipment transmission power and temperature control energy consumption will increase, i.e., the increased operation energy consumption Fz = 300W. The additional energy consumption Fs = 50W caused by signaling interaction during this inter-site transfer of communication services is assessed. Substituting the above physical quantities into the calculation formula: Ys = Ff - Fz - Fs = 800W - 300W - 50W = 450W. At this time, the calculated net transfer benefit Ys (450W) is greater than the estimated benefit threshold Y1. The system determines that this transfer can effectively reduce energy consumption at the global level, and therefore triggers the transfer signal.

[0074] When a transfer signal is detected, a one-way communication connection is established between the transfer decision module and the energy efficiency analysis module. According to the comprehensive energy efficiency coefficient calculation method in the energy efficiency analysis module, the comprehensive energy efficiency coefficient of the receiving base station after receiving the service representative value of the transfer base station is calculated. If the comprehensive energy efficiency coefficient is greater than or equal to the energy efficiency threshold Ey, the receiving base station is marked as a normal energy efficiency base station. If the comprehensive energy efficiency coefficient is less than the energy efficiency threshold Ey, the receiving base station is marked as an abnormal energy efficiency base station again. The abnormal energy efficiency base stations are then rearranged according to the above method to obtain a new base station sequence.

[0075] When a reset signal is generated, the corresponding energy efficiency abnormal base station is directly put back into the base station sequence, and the transfer signal is obtained again in the same way.

[0076] Repeat the above steps until all energy-inefficient base stations are paired. Then, establish one-way communication connections between the transfer decision module and the temperature control module and the action execution module, respectively, and transmit the transfer signal to the temperature control module and the action execution module.

[0077] The temperature control module is used to analyze the service volume of the receiving base station and the base station with normal energy efficiency, and determine the target pre-cooling temperature. The specific methods for determining the target pre-cooling temperature include:

[0078] Obtain the current real-time temperature Tems of a base station with normal energy efficiency. Simultaneously, based on the service representative volume Ldsz of the current co-frequency period or the comprehensive service value Ldsz of the common period, use the calculation formula... The target pre-cooling temperature Tbw is obtained, where Qws represents the heat generation coefficient per unit of traffic, Area represents the base station area, and R represents the building insulation coefficient.

[0079] For example, at a certain time, the system obtains the current real-time internal temperature of a base station with normal energy efficiency, Tems = 26 degrees Celsius. The system predicts or obtains the expected traffic volume (e.g., data burst traffic during the evening rush hour) Ldsz = 5000 Mbps for the base station during the same frequency period. According to the hardware specifications of the base station, the heat generation coefficient per unit traffic volume is known to be Qws = 0.02 (unit: watts / Mbps, i.e., the additional heat power generated per 1 Mbps of traffic volume processed). The area of ​​the base station's equipment room is Area = 20 square meters, and the comprehensive thermal insulation coefficient of the equipment room building is R = 2.5. Substituting the above specific physical quantities into the calculation formula, we get Tbw = 24 degrees Celsius. That is, in order to cope with the heat impact generated by the upcoming 5000 Mbps traffic volume, the system needs to set the pre-cooling temperature target of the equipment room to 24 degrees Celsius. This avoids the high power peak energy consumption of the temperature control equipment and also ensures the thermal stability of the main communication equipment during peak traffic periods, effectively achieving significant energy saving and consumption reduction as well as network robustness.

[0080] Furthermore, in the process of calculating the target pre-cooling temperature, the receiving base station corresponds to the comprehensive service value of the public period, while the energy efficiency normal base station corresponds to the service representative value of the same frequency period. If a base station has both the receiving base station and energy efficiency normal base station labels at the same time, the priority of the receiving base station is greater than that of the energy efficiency normal base station.

[0081] Then, a one-way communication connection is established between the temperature control module and the action execution module, and the target pre-cooling temperature is transmitted to the action execution module;

[0082] The action execution module is used to receive the transfer signal and obtain the corresponding compensation base station. It transfers the traffic of the transfer base station in the compensation base station to the receiving base station. At the same time, it obtains the target pre-cooling temperature of the corresponding receiving base station or the base station with normal energy efficiency, and issues a pre-cooling command in real time to make the temperature control equipment start working at the lowest frequency conversion level.

[0083] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A communication base station energy consumption optimization management system, characterized in that, include: The information acquisition module is used to collect basic information about the communication base station; The service analysis module is used to analyze the historical service volume of the target base station based on the basic information of the communication base station, determine the service fluctuation value of each local time period, and determine the service representative value of each local time period based on the service fluctuation value. Then, according to the adjacent service representative values, the corresponding local time periods are merged to determine the co-frequency time period of the target base station. The energy efficiency analysis module is used to calculate the comprehensive energy efficiency coefficient based on the current ambient temperature, real-time traffic volume and equipment power consumption, and to determine the compensation base station based on the comprehensive energy efficiency coefficient. The compensation base station includes the transfer base station and the receiving base station. The transfer decision module is used to analyze the load operating energy consumption and increased operating energy consumption in the compensation base station, calculate the net transfer benefit, and determine the transfer signal based on the net transfer benefit. The temperature control module is used to analyze the service volume of the receiving base station and the base station with normal energy efficiency during the same frequency period and determine the target pre-cooling temperature. The action execution module is used to receive the transfer signal, obtain the compensation base station corresponding to the transfer signal, transfer the traffic of the transfer base station in the compensation base station to the receiving base station, and at the same time obtain the target pre-cooling temperature of the corresponding receiving base station or the energy-efficient base station, and issue pre-cooling instructions in real time.

2. The communication base station energy consumption optimization management system according to claim 1, characterized in that, The methods for calculating business volatility include: Select any communication base station in the base station group and mark this communication base station as the target base station. First, based on the basic information of the communication base station, obtain the service coverage range of the target base station under normal conditions and obtain the historical service volume of the target base station. Set the cycle time and unit time, and divide the cycle time into several local time periods based on the unit time. The cycle time is 24 hours and the unit time is set to 1 hour. Historical traffic volume is divided into local time periods to obtain local traffic volume. Then, an arbitrary local time period is selected within the periodic time period and marked as the target analysis period. At the same time, all local traffic volumes of the target analysis period are obtained and calculated using the formula. The business fluctuation value Bw is obtained, where Li represents different local business volumes in the target analysis period, and i∈[1,n] indicates that there are n data points in the target analysis period, and La is the mean of the local business volume.

3. The communication base station energy consumption optimization management system according to claim 2, characterized in that, Methods for determining the value of a business representative include: The business fluctuation value Bw is compared with the fluctuation threshold By1. If Bw≤By1, the local business volume of this target analysis period is averaged and the average calculation result is marked as the business representative value of the target analysis period. If Bw>By1, the business representative value of this target period is divided into normal business data and abnormal business data. Obtain normal business data and perform mean processing on the normal business data. Mark the obtained numerical results as the business representative values ​​for the target analysis period. Normal business data refers to data whose business representative values ​​belong to the region [La-2×Bw, La+2×Bw], and abnormal business data refers to data whose business representative values ​​do not belong to the region [La-2×Bw, La+2×Bw].

4. The communication base station energy consumption optimization management system according to claim 3, characterized in that, Methods for determining the same frequency time period include: Starting from the first business representative value in the data sequence, adjacent business representative values ​​are selected sequentially and labeled L1 and L2 respectively. If L1 ≤ By2, then merge the local time periods belonging to L1 and L2 into the same frequency time period, and continue to judge L3; if If the value is greater than By2, the connection is broken after L1, and L2 becomes the starting point of the next new synchronous frequency period. This process continues until the entire data sequence is traversed, eventually forming several continuous synchronous frequency periods with smooth internal fluctuations, where By2 is the threshold.

5. The communication base station energy consumption optimization management system according to claim 1, characterized in that, The methods for calculating the overall energy efficiency coefficient include: Select any target base station in the base station group, collect the ambient temperature of the current target base station, then obtain the current real-time traffic volume Lsy of the target base station, and at the same time collect the current main equipment power consumption Ws and temperature control equipment power consumption Wk of the target base station. Using calculation formula The overall energy efficiency coefficient Ec is obtained, where Tk is the temperature coefficient corresponding to the ambient temperature and c is a constant coefficient.

6. The communication base station energy consumption optimization management system according to claim 5, characterized in that, The methods for determining compensation base stations include: Calculate the comprehensive energy efficiency coefficient Ec of other base stations in the base station group in turn, and compare the comprehensive energy efficiency coefficient Ec with the energy efficiency threshold Ey. When Ec≥Ey, the corresponding base station is marked as a normal energy efficiency base station, and when Ec<Ey, the corresponding base station is marked as an abnormal energy efficiency base station. All base stations with abnormal energy efficiency are obtained, and their corresponding comprehensive energy efficiency coefficients are arranged in descending order to obtain a base station sequence. Then, the last base station with abnormal energy efficiency in the base station sequence and the first base station with abnormal energy efficiency are set as a pair of compensation base stations, the second to last base station with abnormal energy efficiency and the second base station with abnormal energy efficiency are set as a pair of compensation base stations, and so on, to obtain multiple compensation base stations. Two energy-efficient base stations, G1 and G2, are identified among the compensation base stations. The comprehensive energy efficiency coefficients of the two energy-efficient base stations are compared. If the comprehensive energy efficiency coefficient of G1 is greater than that of G2, then G1 is used as the receiving base station and G2 is used as the transfer base station. If the comprehensive energy efficiency coefficient of G1 is less than that of G2, then G1 is used as the transfer base station and G2 is used as the receiving base station.

7. The communication base station energy consumption optimization management system according to claim 1, characterized in that, Methods for determining the transfer signal include: Select a pair of compensation base stations, obtain the co-frequency time periods corresponding to the transferring base station and the receiving base station based on the current time, take the intersection of the co-frequency time periods, and mark the time period corresponding to the intersection as the common time period; Obtain the service representative value of the transferred base station during the public period, and obtain the corresponding load operating energy consumption Ff based on this service representative value. At the same time, obtain the service representative value of the receiving base station, add the service representative value of the receiving base station to the service representative value of the transferred base station to obtain the comprehensive service value, obtain the operating energy consumption under the original service representative value of the receiving base station and the operating energy consumption corresponding to the comprehensive service value, and then subtract the operating energy consumption corresponding to the original service representative value from the operating energy consumption corresponding to the comprehensive service value to obtain the operating energy consumption increase Fz. Among them, load operation energy consumption and increased operation energy consumption include equipment energy consumption and temperature control energy consumption, respectively; Using calculation formula The net transfer benefit Ys is obtained, where Fs is the additional energy consumption caused during the transfer of the communication base station; The net transfer income Ys is compared with the estimated income threshold Y1. If Ys ≥ Y1, a transfer signal is triggered. If Ys < Y1, a reset signal is generated. The estimated income threshold Y1 is set to 100.

8. The communication base station energy consumption optimization management system according to claim 7, characterized in that, When a transfer signal is detected, a one-way communication connection is established between the transfer decision module and the energy efficiency analysis module. According to the comprehensive energy efficiency coefficient calculation method in the energy efficiency analysis module, the comprehensive energy efficiency coefficient of the receiving base station after receiving the service representative value of the transfer base station is calculated. If the comprehensive energy efficiency coefficient is greater than or equal to the energy efficiency threshold Ey, the receiving base station is marked as a normal energy efficiency base station. If the comprehensive energy efficiency coefficient is less than the energy efficiency threshold Ey, the receiving base station is marked as an abnormal energy efficiency base station again. The abnormal energy efficiency base stations are then rearranged according to the above method to obtain a new base station sequence. When a reset signal is generated, the corresponding energy-efficient base station is directly put back into the base station sequence, and the transfer signal is obtained again in the same way.

9. The communication base station energy consumption optimization management system according to claim 1, characterized in that, Methods for determining the target precooling temperature include: Obtain the current real-time temperature Tems of a base station with normal energy efficiency. Simultaneously, based on the service representative volume Ldsz of the current co-frequency period or the comprehensive service value Ldsz of the common period, use the calculation formula... The target pre-cooling temperature Tbw is obtained, where Qws represents the heat generation coefficient per unit of traffic, Area represents the base station area, and R represents the building's insulation coefficient.

10. A communication base station energy consumption optimization management system according to claim 9, characterized in that, During the calculation of the target pre-cooling temperature, the receiving base station corresponds to the comprehensive service value of the public period, while the energy efficiency normal base station corresponds to the service representative value of the same frequency period. If a base station has both the receiving base station and energy efficiency normal base station labels, the receiving base station has a higher priority than the energy efficiency normal base station.

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