Energy efficiency evaluation method, device, equipment, storage medium and product

Abstract

The application relates to an energy efficiency evaluation method, device, equipment, storage medium and product. The energy efficiency evaluation method comprises the following steps: obtaining target device energy consumption of a target area in each statistical period; the target device energy consumption is network device energy consumption generated for processing communication services initiated by a target base station corresponding to the target area; based on the target device energy consumption of the target area in each statistical period and a power supply mode of the target area in each statistical period, target carbon emission of the target area in each statistical period is calculated, and the carbon emission calculation mode is different for different power supply modes; and based on the target carbon emission in each statistical period and a base station type of the target base station, energy efficiency of the target area is evaluated to obtain an energy efficiency evaluation result.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to an energy efficiency assessment method, apparatus, device, storage medium, and product. Background Technology

[0002] Energy efficiency assessment of communication networks is an important means to improve network resource utilization and environmental benefits. However, existing energy efficiency assessment methods usually only calculate energy consumption for a single energy system, making it difficult to comprehensively and accurately reflect the true energy utilization efficiency and environmental impact of modern communication networks. Summary of the Invention

[0003] This application provides an energy efficiency assessment method, apparatus, device, storage medium, and product, which can achieve differentiated calculation of carbon emissions under different energy structures, thereby more comprehensively and realistically reflecting the overall energy utilization efficiency of communication networks and their environmental impact. The technical solution is as follows.

[0004] On the one hand, an energy efficiency assessment method is provided, the method comprising: Obtain the target device energy consumption of the target area in each statistical period; the target device energy consumption is the network device energy consumption generated to process the communication services initiated by the target base station corresponding to the target area; Based on the energy consumption of the target equipment in each statistical period of the target area and the power supply method of the target area in each statistical period, the target carbon emissions of the target area in each statistical period are calculated. The calculation method for carbon emissions corresponding to different power supply methods is different. Based on the target carbon emissions in each statistical period and the base station type of the target base station, an energy efficiency assessment is performed on the target area to obtain the energy efficiency assessment results.

[0005] On the other hand, an energy efficiency assessment device is provided, the device comprising: The energy consumption acquisition module is used to acquire the energy consumption of target devices in the target area within each statistical period; the target device energy consumption is the network device energy consumption generated for processing the communication services initiated by the target base station corresponding to the target area. The calculation module is used to calculate the target carbon emissions of the target area in each statistical period based on the energy consumption of the target equipment in each statistical period of the target area and the power supply method of the target area in each statistical period. The calculation method for carbon emissions is different for different power supply methods. The energy efficiency assessment module is used to assess the energy efficiency of the target area based on the target carbon emissions and the base station type of the target base station in each statistical period, and obtain the energy efficiency assessment results.

[0006] In one possible implementation, the energy acquisition module includes: The first energy consumption acquisition submodule is used to acquire the total energy consumption of each type of equipment within a target statistical period; the target statistical period can be any one of the statistical periods. The second energy consumption acquisition submodule is used to calculate the energy consumption of various types of devices in the target area based on the resource occupancy ratio of the resources called by the communication services in the target area and the total energy consumption of each type of device; different types of devices are based on different resource types for evaluating the resource occupancy ratio; The energy consumption calculation submodule is used to calculate the energy consumption of the target equipment within the target statistical period based on the energy consumption of each type of equipment in the target area.

[0007] In one possible implementation, the carbon emissions include carbon emissions from power supply and carbon emissions from power generation, wherein the power supply method includes at least one of the following: power supply from the public grid, photovoltaic power supply, diesel power supply, and battery power supply; The carbon emissions from the power generation powered by the battery are the carbon emissions corresponding to the stored electricity. The calculation method for the carbon emissions from the power generation powered by the battery differs depending on the charging method.

[0008] In one possible implementation, the device further includes: The feature data acquisition module is used to acquire the base station feature data of each base station; The clustering module is used to perform clustering processing based on the base station feature data of each base station, and to divide each base station into capacity base stations and coverage base stations.

[0009] In one possible implementation, the energy efficiency assessment module includes: The traffic value acquisition submodule is used to acquire the transmission traffic value of the target base station in each statistical period when the target base station is a capacity base station. The first energy efficiency calculation submodule is used to calculate the first basic energy efficiency of the target base station in each statistical period based on the transmission traffic value in each statistical period and the target carbon emission in each statistical period. The first coefficient calculation submodule is used to calculate the time fluctuation coefficient based on the first basic energy efficiency in each statistical period, so as to obtain the time fluctuation coefficient corresponding to the target area. The time fluctuation coefficient is used to indicate the stability of network energy efficiency in the time dimension.

[0010] In one possible implementation, the energy efficiency assessment module includes: The area acquisition submodule is used to acquire the coverage area of ​​the coverage area corresponding to multiple coverage base stations when the target base station is a coverage base station; The second energy efficiency calculation submodule is used to calculate the second basic energy efficiency of each coverage base station based on the coverage area of ​​multiple coverage base stations and the target carbon emissions of each coverage base station in the same statistical period. The second coefficient calculation submodule is used to calculate the spatial fluctuation coefficient based on the second basic energy efficiency of each coverage base station to obtain the spatial fluctuation coefficient corresponding to the target area. The spatial fluctuation coefficient is used to indicate the balance of network energy efficiency in the spatial dimension.

[0011] On the other hand, a computer device is provided, the computer device including a processor and a memory, the memory storing at least one computer program, the at least one computer program being loaded and executed by the processor to implement the above-described energy efficiency assessment method.

[0012] On the other hand, a computer-readable storage medium is provided, wherein at least one computer program is stored in the computer-readable storage medium, the computer program being loaded and executed by a processor to implement the above-described energy efficiency assessment method.

[0013] On the other hand, a computer program product is provided, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions that, when executed by a computer, cause the computer to perform to implement the energy efficiency assessment method provided in the various optional implementations described above.

[0014] The energy efficiency assessment method provided in this application obtains the energy consumption of network equipment generated by processing base station communication services within a target area, and further calculates the target carbon emissions related to energy efficiency by combining the power supply methods under different statistical periods. Finally, a comprehensive energy efficiency assessment of the target area is conducted based on the carbon emissions and the base station type. Compared with the limitations of only targeting a single energy system, this solution introduces power supply methods to achieve differentiated calculation of carbon emissions under different energy structures. This allows for a more comprehensive and accurate reflection of the overall energy utilization efficiency of the communication network and its environmental impact, providing a scientific basis for formulating precise energy efficiency improvement strategies and achieving green and low-carbon development.

[0015] Furthermore, conducting energy efficiency assessments based on base station type makes these assessments more aligned with actual needs and improves their accuracy.

[0016] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] Figure 1 A flowchart of an exemplary embodiment of the present application is shown; Figure 2 A schematic diagram illustrating the grid method for estimating coverage area provided in an exemplary embodiment of this application is shown; Figure 3 A schematic diagram of an energy efficiency assessment system provided in an exemplary embodiment of this application is shown; Figure 4 A block diagram of an energy efficiency assessment device provided in an exemplary embodiment of this application is shown; Figure 5 This application shows a structural block diagram of a computer device according to an exemplary embodiment. Figure 6 A structural block diagram of a computer device is shown in another exemplary embodiment of this application. Detailed Implementation

[0019] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of methods consistent with some aspects of this application as detailed in the appended claims.

[0020] This application provides an energy efficiency assessment method that can achieve energy efficiency assessment based on different power supply methods and different base station types, thereby improving the effectiveness of energy efficiency assessment and making the energy efficiency assessment results more consistent with the actual situation. Figure 1 A flowchart of an exemplary embodiment of this application is shown. This method can be executed by a computer device, which can be implemented as a server or a terminal, such as... Figure 1 As shown, the energy efficiency assessment method may include the following steps.

[0021] Step 110: Obtain the target device energy consumption in the target area within each statistical period; the target device energy consumption is the network device energy consumption generated to process the communication services initiated by the target base station corresponding to the target area.

[0022] The target area can be the area covered by the target base station. The areas covered by different base stations may overlap geographically. For example, there may be multiple base stations on different floors of a large building or in an underground parking lot. These base stations cover areas with the same latitude and longitude but different horizontal altitudes. Each base station has its own specific target area. In other words, the target area in this application is the area covered by the target base station, and the target areas corresponding to different base stations may overlap.

[0023] The length of the statistical period can be set based on actual needs, and this application does not impose any restrictions on it.

[0024] Regarding the target device's energy consumption, in one possible implementation, different base stations are configured with their own corresponding network devices to support the communication services initiated by those base stations. In this case, the computer device can determine the target device's energy consumption by obtaining the energy consumption of the network devices corresponding to each base station. In another possible implementation, to improve equipment utilization and save costs, some network devices can be shared across multiple areas. The total energy consumption of the same network device may correspond to multiple areas. In this case, the computer device can use the energy consumption segmentation method provided in this application to divide the total energy consumption of the network devices by area to achieve energy efficiency assessment for each area. This energy efficiency segmentation method can be implemented as follows: Obtain the total energy consumption of each type of equipment within the target statistical period; the target statistical period can be any one of the statistical periods. Based on the resource occupancy ratio of communication services in the target area across various types of devices and the total energy consumption of each type of device, calculate the energy consumption of each type of device in the target area; different types of devices are based on different resource types for evaluating resource occupancy ratios. Based on the energy consumption of various types of equipment in the target area, calculate the target equipment energy consumption within the target statistical period.

[0025] Indicatively, device types can include computing devices, storage devices, management devices, switching devices, and cooling devices. Computing devices are responsible for running applications and processing data, such as high-performance, multi-core servers; storage devices are responsible for storing information, such as hard drives and disks; management devices are responsible for monitoring the stable operation of the system, such as various sensors (including temperature sensors, humidity sensors, etc.) and image acquisition devices (cameras, etc.); switching devices are responsible for temporarily storing incoming data packets, finding the next hop, and forwarding them, such as routers and switches; cooling devices are used to cool indoor spaces or equipment to ensure that the equipment operates at a suitable temperature, such as air conditioners, fans, and chillers.

[0026] As an illustration, the calculation method for the total energy consumption of each piece of equipment can be expressed as follows:

[0027] in, This represents the equipment power, and T represents the statistical period. This represents the total energy consumption of the equipment. Different network devices can use corresponding values ​​to calculate their total energy consumption using the formula above.

[0028] The resource occupancy ratio of communication services in the target area refers to the proportion of the total resources used by various types of devices within the statistical period to meet the communication service needs initiated by the target base station corresponding to the target area. Different types of devices use different resource types to evaluate the resource occupancy ratio.

[0029] For example, for computing devices, the resource usage ratio of computer equipment can be assessed based on the CPU (Central Processing Unit) utilization rate.

[0030] In one possible implementation, the computer device can obtain the CPU utilization rate of programs in each region during the statistical period, and break down the device energy consumption of computing devices during the statistical period based on the ratio between the CPU utilization rates of programs in each region.

[0031] In another possible implementation, the computer device can divide the statistical period into multiple time intervals, sample the CPU utilization of programs in each region within each time interval, and determine the average CPU utilization of programs in the same region within each time interval as the CPU utilization of that region. Then, based on the ratio between the CPU utilization of programs in different regions, the device energy consumption of computing devices within the statistical period is broken down. For example, if a computing device runs computing programs in regions 1 and 2, with average CPU utilization of 20% and 30% respectively (ratio 2:3), then 40% of the total device energy consumption of this computing device within the statistical period T is included in the device energy consumption of region 1, and 60% is included in the device energy consumption of region 2.

[0032] Among them, computer equipment can use computer monitoring software to monitor the CPU usage of programs in each area.

[0033] For storage devices, computer equipment can assess resource usage based on the frequency of disk I / O (Input / Output) operations.

[0034] Similar to the statistical methods used for computing devices, one possible implementation is to record the disk I / O operation frequency of programs belonging to different regions within the statistical period, and then break down the device energy consumption of storage devices within the statistical period based on the ratio between disk read and write operation frequencies. Another possible implementation is to divide the statistical period into time intervals when performing disk I / O operation frequency statistics, and calculate the average of the disk I / O operation frequencies of programs in each time interval to obtain the disk I / O operation frequency of programs in each region.

[0035] For the energy consumption of management equipment, computer equipment can be divided equally among the energy consumption of management equipment within the statistical period based on the number of regions.

[0036] For switching equipment, computer equipment can assess resource usage ratios based on the forwarding traffic corresponding to the region.

[0037] In one possible implementation, the computer device can obtain the source region of the traffic forwarded by the switching device within a statistical period, and break down the device energy consumption of the switching device within the statistical period based on the ratio between the forwarded traffic corresponding to each region.

[0038] In determining the source region of traffic, computer devices can read the source IP (Internet Protocol) address, source MAC (Media Access Control) address, and VLAN ID (Virtual Local Area Network Identifier) ​​of IP packets or Ethernet frames. Combined with the specific network protocol, traffic path tracing technology is used to determine the source region of the traffic, avoiding the confusion of source IP addresses caused by technologies such as VPNs (Virtual Private Networks). Furthermore, computer devices can multiply the packet length by a correction factor based on the number of forwarding rules and forwarding complexity to include the traffic in the corresponding region. Within the statistical period, the energy consumption allocation ratio is determined based on the traffic proportions of different regions. For example, if a router forwards 2GB of traffic from region 1 and 3GB of traffic from region 2 within the statistical period, then 40% of the router's total device energy consumption is included in the device energy consumption of region 1, and 60% of the router's total device energy consumption is included in the device energy consumption of region 2.

[0039] For cooling devices, computer equipment can perform a secondary breakdown of the total energy consumption of these devices to allocate it to different regions. In the first breakdown, the computer equipment can allocate energy consumption based on the proportion of the total energy consumption of the network devices served by the cooling device. For example, if an air conditioner cools multiple network devices in a room, its total energy consumption is allocated to each network device according to the ratio of their respective energy consumption. In the second breakdown, each network device is further allocated to its corresponding region based on its energy consumption allocation method. For instance, if a room contains one computing device, one storage device, and one air conditioner cooling both devices, and within a statistical period T, the total energy consumption ratio between the computing device and the storage device is 2:3, then 40% of the air conditioner's total energy consumption within the statistical period is included in the computing device's energy consumption, and 60% is included in the storage device's energy consumption. Then, the energy consumption of the corresponding network devices is further allocated to different regions based on the energy consumption allocation method for each type of network device.

[0040] Among them, computer equipment can obtain the energy consumption of management equipment and cooling equipment through the building energy management system, and can obtain the energy consumption of computing equipment, storage equipment and switching equipment through network protocols such as SNMP (Simple Network Management Protocol) and SDN (Software-Defined Networking).

[0041] It should be noted that the number and type of network devices in different regions may be the same or different. When calculating the energy consumption of various devices in a region, the calculation should be based on the actual situation of each region. This application does not impose any restrictions on this.

[0042] Taking the target area as an example, after obtaining the energy consumption of various types of devices in the target area, the computer device can obtain the sum of the energy consumption of various types of devices as the target device energy consumption within the target statistical period.

[0043] Step 120: Based on the target equipment energy consumption and the power supply method of the target area in each statistical period, calculate the target carbon emissions of the target area in each statistical period. The calculation method for carbon emissions is different for different power supply methods.

[0044] The target carbon emissions for the target area in each statistical period refer to the carbon emissions generated by the energy consumption of the target equipment produced and / or supplied by the power supply method in that statistical period.

[0045] In this embodiment of the application, carbon emissions include carbon emissions from power supply and carbon emissions from power generation. Carbon emissions from power supply refer to the carbon emissions generated during the power application phase, that is, the carbon emissions generated when power is applied to network equipment to support communication services initiated by base stations. Carbon emissions from power generation refer to the carbon emissions generated during the power production phase, that is, the carbon emissions generated when other energy sources are converted into electrical energy.

[0046] Power supply methods can include at least one of the following: public grid power supply, photovoltaic power supply, diesel power supply, and battery power supply. Public grid power supply refers to the method of obtaining electricity from the public power grid, whose power sources can include thermal power, wind power, hydropower, and nuclear power, etc. Photovoltaic power supply refers to the method of generating electricity using photovoltaic power generation equipment deployed within the target area of ​​the base station or equipment room. Photovoltaic power supply utilizes solar energy to generate electricity, and all the electricity generated by photovoltaic power supply is used by the base station or equipment room. Diesel power supply utilizes diesel generators and diesel fuel to generate electricity and can be used as a power supply method in emergencies. Battery power supply refers to storing electricity from the public grid or photovoltaic power generation in advance using batteries as a supplement to other power supply methods. To maintain the stable operation of the communication network, the communication network typically has one or more of the above power supply methods. When there are two or more power supply methods, the power supply method is determined to be a hybrid power supply. In this case, the carbon emissions are the sum of the carbon emissions of the multiple power supply methods.

[0047] The calculation methods for carbon emissions differ depending on the power supply method. For example, for public grid power (hereinafter referred to as municipal power), the carbon emission calculation method can be expressed as follows:

[0048] Where E represents the mains power consumption (unit: kWh), and in this embodiment, the energy consumption of the target equipment can be substituted. τ1 is the mains power carbon emission factor (unit: kgCO2 / kWh), T is the statistical period (unit: hour), and b1 is the carbon emission averaging coefficient of the mains power equipment manufacturing process (unit: kgCO2 / h). The mains power τ1 is related to the proportion of thermal power, wind power, nuclear power, hydropower, etc. in the public power grid, and can be queried and dynamically updated by relevant departments.

[0049] For diesel-powered electricity (hereinafter referred to as diesel-powered electricity), its carbon emissions can be calculated as follows:

[0050] Where V is diesel consumption (unit: L), τ2 is diesel carbon emission factor (unit: kgCO2 / L), T is the statistical period (unit: hour), and b2 is the carbon emission amortization coefficient of the diesel generator equipment manufacturing process (unit: kgCO2 / h). The τ2 of the diesel generator is related to the type of diesel fuel and the model of the diesel engine, and can be obtained by consulting relevant manuals.

[0051] For photovoltaic power generation, since the carbon emissions during photovoltaic power generation are zero, the carbon emissions are generated during the application stage, and their calculation method can be expressed as follows:

[0052] Where T is the statistical period (unit: hour), and b3 is the carbon emission averaging factor of the photovoltaic equipment manufacturing process (unit: kgCO2 / h).

[0053] Since batteries do not have the ability to generate electricity, the carbon emissions from battery-powered power generation are the carbon emissions corresponding to the stored electricity. The calculation method for the carbon emissions from battery-powered power generation differs depending on the charging method. For example, if we define S as the dynamic carbon stock of the battery, that is, the carbon emissions corresponding to the stored electricity, S=0 when the stored electricity in the battery is 0. When charging the battery using other power supply methods, S can be updated using different calculation methods depending on the charging method.

[0054] As an illustration, when the charging method is public grid power supply, the formula for calculating the carbon emissions of battery-powered power generation can be expressed as follows:

[0055] Where Ein is the mains power consumption (unit: kWh), τ1 is the mains carbon emission factor (unit: kgCO2 / kWh), and alpha is the battery coulombic efficiency (also called charge-discharge efficiency), which is provided by the battery manufacturer.

[0056] When the charging method is diesel power, the formula for calculating the carbon emissions of battery-powered power generation can be expressed as:

[0057] Where V is the diesel consumption (unit: L), and τ2 is the diesel carbon emission factor (unit: kgCO2 / L).

[0058] When the charging method is photovoltaic power supply, since photovoltaic power generation is a clean energy source, its carbon emissions are 0, therefore, S remains unchanged.

[0059] The formula for calculating the carbon emissions from power supply during battery discharge can be expressed as follows:

[0060]

[0061]

[0062] Where Emission represents carbon dioxide emissions, Econ represents the amount of electricity used (this refers to the amount of electricity reduced from the battery; the actual amount of electricity output to the device needs to be multiplied by the discharge efficiency coefficient), Estore represents the current battery capacity, T represents the statistical period, and b4 represents the carbon emission amortization coefficient of the battery manufacturing process (unit: kgCO2 / h). Since batteries age with use, their coulombic efficiency gradually decreases with each use. Therefore, a timed update mechanism for the battery's coulombic efficiency can be established, adjusting alpha periodically.

[0063] The calculation method for b (including b1 to b4) is to divide the carbon emissions generated during the manufacturing process of the power supply equipment by the expected lifespan of the equipment.

[0064] In one possible implementation, if a communication system is connected to a certain power supply method but does not use that power supply method in the current statistical period, the computer equipment can include the carbon emissions generated during the manufacturing process of the power supply equipment corresponding to that power supply method in the carbon emissions of the current statistical period.

[0065] When the target area uses a hybrid power supply, the target carbon emissions within the statistical period are a linear sum of the carbon emissions generated by each power supply method. The carbon emissions generated by each power supply method are related to its contribution to the energy consumption of the target equipment. For example, if the target equipment consumes 100 kWh of energy within the statistical period, with the public power grid contributing 50%, photovoltaic power contributing 30%, and diesel power contributing 20%, then the carbon emissions for each power supply method are calculated separately based on its corresponding formula, and then summed to obtain the target carbon emissions.

[0066] In one possible implementation, computer equipment can perform energy consumption statistics based on the communication network infrastructure to which each network device belongs in the target area, with each communication network infrastructure serving as a unit. Then, when calculating carbon emissions, carbon emissions are calculated based on the energy consumption of the equipment corresponding to each communication network infrastructure to obtain the target carbon emissions. The communication network infrastructure can include wireless access networks, core networks, and data centers.

[0067] Step 130: Based on the target carbon emissions and the base station type of the target base station in each statistical period, conduct an energy efficiency assessment of the target area to obtain the energy efficiency assessment results.

[0068] In this embodiment of the application, when the computer device performs energy efficiency assessment, it can perform the corresponding energy efficiency assessment based on the base station type. Different base station types have different energy efficiency assessment methods. Therefore, before performing energy efficiency assessment, it is necessary to determine the base station type of the target base station.

[0069] In this embodiment, based on the task type of the communication tasks undertaken by the base station, the base station can be divided into coverage base stations and capacity base stations. Coverage base stations are used to provide wide-area signal coverage to ensure stable communication signals in a wide area. Coverage base stations are characterized by large coverage area, high transmission power, large geographical coverage area, and low user density. Coverage base stations are usually used in rural areas, suburbs, and other areas. Capacity base stations are used to provide sufficient network capacity in densely populated user areas to ensure communication quality when a large number of users access the network at the same time. Capacity base stations are characterized by small coverage area, high concurrency connection capability, and high user density. Capacity base stations are usually used in city centers, commercial areas, stadiums, or large-scale events.

[0070] In one possible implementation, the computer device can determine the base station type of each base station (including the target base station) through clustering. This process can be implemented as follows: Obtain base station characteristic data for each base station; Clustering is performed on the base station characteristic data of each base station to classify them into capacity base stations and coverage base stations.

[0071] The base station characteristic data may include, but is not limited to, the number of users, user density, traffic load, transmit power, antenna height, base station type (macro, micro), deployment environment, etc. After obtaining the base station characteristic data of each base station, the computer equipment can perform standardization processing on the continuous data to facilitate subsequent clustering processing. An illustrative example, the standardization processing formula can be expressed as:

[0072] Where x represents continuous data, mu represents the data mean, and sigma represents the standard deviation.

[0073] During the clustering process, the computer device can first initialize the cluster centers: randomly select two base station data points as initial cluster centers; allocate base station data points: calculate the distance from each base station data point to the cluster center and assign it to the cluster cluster of the nearest cluster center; update the cluster centers: calculate the center point of each cluster cluster and update the center point to the corresponding cluster center, which can be the average value of all base station data points in the cluster cluster; repeat the above steps until the cluster centers are stable or a specified number of rounds is reached.

[0074] After clustering is completed, the base station type of each base station is determined based on the cluster it belongs to.

[0075] For capacity-type base stations, the corresponding energy efficiency assessment process can be implemented as follows: When the target base station is a capacity-type base station, obtain the transmission traffic value of the target base station in each statistical period; Based on the transmission traffic value and the target carbon emission in each statistical period, the first basic energy efficiency of the target base station in each statistical period is calculated. The time fluctuation coefficient is calculated based on the first basic energy efficiency in each statistical period to obtain the time fluctuation coefficient corresponding to the target area. The time fluctuation coefficient is used to indicate the stability of network energy efficiency in the time dimension.

[0076] The transmission traffic value of capacity-type base stations can be obtained through statistics from base station control software.

[0077] The primary energy efficiency can be the ratio of the transmission flow rate to the corresponding target carbon emissions within a statistical period, expressed in Gbit / kgCO2. Its calculation formula can be expressed as follows: First basic energy efficiency = Transmission flow rate / Target carbon emissions For capacity-type base stations, when calculating the time fluctuation coefficient, the computer equipment performs a first basic energy efficiency calculation for multiple statistical periods. Based on the first basic energy efficiency of multiple statistical periods, the standard deviation and mean are calculated. Then, the time fluctuation coefficient is calculated based on the standard deviation and mean. This time fluctuation coefficient can be the ratio of the standard deviation to the mean. Schematic, the formula for calculating the time fluctuation coefficient can be expressed as: Time fluctuation coefficient = sigma1 / mu1 Where sigma1 represents the standard deviation of the first basic energy efficiency over multiple statistical periods, and mu1 represents the mean of the first basic energy efficiency over multiple statistical periods.

[0078] For coverage base stations, the corresponding energy efficiency assessment process can be implemented as follows: When the target base station is a coverage base station, obtain the coverage area of ​​the coverage area corresponding to multiple coverage base stations; The second basic energy efficiency of each coverage base station is calculated based on the coverage area of ​​multiple coverage base stations and the target carbon emissions of each coverage base station in the same statistical period. The spatial fluctuation coefficient is calculated based on the second basic energy efficiency of each coverage base station to obtain the spatial fluctuation coefficient corresponding to the target area. The spatial fluctuation coefficient is used to indicate the balance of network energy efficiency in the spatial dimension.

[0079] The coverage area of ​​a coverage base station can be obtained by either circular estimation or grid estimation. Circular estimation assumes the base station coverage area is circular, estimates the maximum distance r from the base station to the user, and then estimates the coverage area based on the circle area calculation formula S=Π*r*r.

[0080] Among them, different estimation methods can be used when estimating the maximum distance based on the different duplex modes of the base station.

[0081] For TDD (Time Division Duplex) base stations, computer equipment can estimate the distance using either the TA (Time Advance) measurement method or the path loss measurement method. The TA measurement method estimates the distance by testing the propagation time of the signal from the user equipment to the base station. Illustratively, the maximum distance can be the product of the one-way propagation time and the electromagnetic wave transmission speed, where the one-way propagation time is TA / 2. The path loss measurement method estimates the maximum distance by measuring the strength of the signal received by the base station and the strength of the signal sent by the user equipment, based on an empirical formula for path loss. Alternatively, in another scenario, the computer equipment can obtain the historical maximum distance as the maximum distance.

[0082] For FDD (Frequency Division Duplex) base stations, computer equipment can estimate distances using path loss measurement.

[0083] In another possible implementation, for a TDD base station, the computer equipment can also estimate the maximum distance and coverage area based on the two methods mentioned above, and then perform a weighted sum of the coverage areas obtained by the two methods to obtain the coverage area of ​​the TDD base station. If the coverage area obtained by the TA measurement method is defined as Sta, and the area obtained by the path loss measurement method is defined as Sloss, if the difference between Sta and Sloss is greater than a threshold, the coverage area is calculated using a weighted estimation method. For example, if |Sta-Sloss| / Sta>30%, then S=k*Sta+(1-k)*Sloss, where k is an adjustable parameter, taking values ​​from 0 to 1, and can be adaptively adjusted according to the base station deployment environment (e.g., urban or suburban). If the difference between Sta and Sloss is less than the threshold, the coverage area obtained by the TA measurement method can be determined as the coverage area of ​​the TDD base station; alternatively, the coverage area obtained by the path loss measurement method can also be determined as the coverage area of ​​the TDD base station, based on a pre-set value priority. This application does not impose any restrictions on this.

[0084] Grid-based estimation assumes the base station coverage area is a polygon. Based on this, computer equipment can divide the map into a grid of equally sized squares, with each square having the same area. The coverage area is then calculated based on the grid pattern of the base station coverage. Figure 2 A schematic diagram illustrating the grid method for estimating coverage area provided in an exemplary embodiment of this application is shown, such as... Figure 2 As shown, grid 210 represents the base station, and grid 220 represents the user or geographical boundary. Based on drive test information, user-reported data, and other data, combined with user geographical location data and signal strength heatmap, a coverage boundary is fitted. The sum of the grid areas within the boundary line is the base station coverage area. If the grid is completely surrounded by the boundary line, the grid area is included in the coverage area. If the grid is crossed by the boundary line, half of the grid area is included in the coverage area. By statistically analyzing the grid areas within the boundary line, the coverage area of ​​the corresponding base station is obtained.

[0085] The second basic energy efficiency can be the ratio of coverage area to the corresponding target carbon emissions, expressed in km² / kgCO2. Its calculation formula can be expressed as: Second basic energy efficiency = Coverage area / Target carbon emissions For coverage base stations, when calculating the spatial fluctuation coefficient, the computer equipment performs a second basic energy efficiency calculation on multiple regions within the same statistical period. Based on the second basic energy efficiency of multiple regions, the standard deviation and mean are calculated, and then the spatial fluctuation coefficient is calculated based on the standard deviation and mean. This spatial fluctuation coefficient can be the ratio of the standard deviation to the mean. Schematic, the formula for calculating the spatial fluctuation coefficient can be expressed as: Spatial fluctuation coefficient = sigma2 / mu2 Where sigma2 represents the standard deviation of the second basic energy efficiency of multiple regions in the same statistical period, and mu2 represents the mean of the second basic energy efficiency of multiple regions in the same statistical period.

[0086] Since the time fluctuation coefficient reflects the stability of network energy efficiency over time, a higher time fluctuation coefficient indicates reduced network energy efficiency during certain periods. Therefore, when the time fluctuation coefficient exceeds the first threshold, the computer equipment can send a first alarm message to the relevant users or operators to instruct them to use load balancing strategies during peak network periods. The spatial fluctuation coefficient measures the spatial balance of network energy efficiency. A higher spatial fluctuation coefficient indicates resource waste in some areas. Therefore, when the spatial fluctuation coefficient exceeds the second threshold, the computer equipment can send a second alarm message to the relevant users or operators to instruct them to conduct regional investigations to resolve the anomaly. In one possible scenario, for coverage base stations or capacity base stations, if the average value is less than the average threshold during the calculation of the corresponding fluctuation coefficient, it is determined that there is a data anomaly, and the corresponding alarm message is sent directly, thereby reducing the resource loss caused by subsequent fluctuation coefficient calculations.

[0087] When a region exhibits both a time fluctuation coefficient exceeding the first threshold and a spatial fluctuation coefficient exceeding the second threshold, it is determined that the region has extremely low energy efficiency during peak hours, requiring inspection and adjustment of its communication strategy and equipment heat dissipation. Conversely, when a region exhibits both a time fluctuation coefficient below the first threshold and a spatial fluctuation coefficient below the second threshold, it is determined that the current region has high network energy efficiency, and its communication strategy and equipment heat dissipation can be used as a reference group for adjustments in other regions.

[0088] In summary, the energy efficiency assessment method provided in this application obtains the energy consumption of network equipment generated by processing base station communication services within a target area, and further calculates the target carbon emissions related to energy efficiency by combining the power supply methods under different statistical periods. Finally, a comprehensive energy efficiency assessment of the target area is conducted based on the carbon emissions and the base station type. Compared to the limitations of targeting only a single energy system, this solution, by introducing power supply methods, achieves differentiated calculation of carbon emissions under different energy structures. This allows for a more comprehensive and accurate reflection of the overall energy utilization efficiency of the communication network and its environmental impact, providing a scientific basis for formulating precise energy efficiency improvement strategies and achieving green and low-carbon development.

[0089] Furthermore, conducting energy efficiency assessments based on base station type makes these assessments more aligned with actual needs and improves their accuracy.

[0090] Figure 3 This application illustrates a schematic diagram of an energy efficiency assessment system provided in an exemplary embodiment. This energy efficiency assessment system can be applied in a computer device to perform tasks such as... Figure 1 The energy efficiency assessment method of the illustrated embodiment, such as Figure 3As shown, the energy efficiency assessment system includes an energy consumption statistics component 310, a carbon emission calculation component 320, a base station classification component 330, and an energy efficiency calculation component 340.

[0091] Among them, the energy consumption statistics component 310 is used to calculate the energy consumption of various types of equipment, corresponding to the energy consumption breakdown of each region, and to determine the target equipment energy consumption of each region within the statistical period.

[0092] The carbon emission calculation component 320 is used to calculate carbon emissions based on the power supply method of each region within the statistical period and the target equipment energy consumption obtained by the energy consumption statistics component, so as to obtain the target carbon emission amount of each region within the statistical period.

[0093] The base station classification component 330 is used to classify base stations into coverage base stations and capacity base stations based on base station feature data.

[0094] The energy efficiency calculation component 340 is used to perform energy efficiency assessment on a region based on the region's target carbon emissions in each statistical period and the base station type, and obtain the energy efficiency assessment results.

[0095] The operational details of each of the above components during the energy efficiency assessment process can be found in the following references: Figure 1 The relevant content of the illustrated embodiment will not be repeated here.

[0096] Figure 4 This invention illustrates a block diagram of an energy efficiency assessment apparatus provided in an exemplary embodiment of this application. This apparatus can be applied in a computer device for performing tasks such as... Figure 1 All or part of the steps in the illustrated embodiments, such as Figure 4 As shown, the device may include the following modules.

[0097] The energy consumption acquisition module 410 is used to acquire the target device energy consumption in the target area within each statistical period; the target device energy consumption is the network device energy consumption generated for processing the communication services initiated by the target base station corresponding to the target area. The calculation module 420 is used to calculate the target carbon emissions of the target area in each statistical period based on the energy consumption of the target equipment in each statistical period of the target area and the power supply method of the target area in each statistical period. The calculation method of carbon emissions is different for different power supply methods. The energy efficiency assessment module 430 is used to assess the energy efficiency of the target area based on the target carbon emissions and the base station type of the target base station in each statistical period, and obtain the energy efficiency assessment results.

[0098] In one possible implementation, the energy acquisition module 410 includes: The first energy consumption acquisition submodule is used to acquire the total energy consumption of each type of equipment within a target statistical period; the target statistical period can be any one of the statistical periods. The second energy consumption acquisition submodule is used to calculate the energy consumption of various types of devices in the target area based on the resource occupancy ratio of the resources called by the communication services in the target area and the total energy consumption of each type of device; different types of devices are based on different resource types for evaluating the resource occupancy ratio; The energy consumption calculation submodule is used to calculate the energy consumption of the target equipment within the target statistical period based on the energy consumption of each type of equipment in the target area.

[0099] In one possible implementation, the carbon emissions include carbon emissions from power supply and carbon emissions from power generation, wherein the power supply method includes at least one of the following: power supply from the public grid, photovoltaic power supply, diesel power supply, and battery power supply; The carbon emissions from the power generation powered by the battery are the carbon emissions corresponding to the stored electricity. The calculation method for the carbon emissions from the power generation powered by the battery differs depending on the charging method.

[0100] In one possible implementation, the device further includes: The feature data acquisition module is used to acquire the base station feature data of each base station; The clustering module is used to perform clustering processing based on the base station feature data of each base station, and to divide each base station into capacity base stations and coverage base stations.

[0101] In one possible implementation, the energy efficiency assessment module 430 includes: The traffic value acquisition submodule is used to acquire the transmission traffic value of the target base station in each statistical period when the target base station is a capacity base station. The first energy efficiency calculation submodule is used to calculate the first basic energy efficiency of the target base station in each statistical period based on the transmission traffic value in each statistical period and the target carbon emission in each statistical period. The first coefficient calculation submodule is used to calculate the time fluctuation coefficient based on the first basic energy efficiency in each statistical period, so as to obtain the time fluctuation coefficient corresponding to the target area. The time fluctuation coefficient is used to indicate the stability of network energy efficiency in the time dimension.

[0102] In one possible implementation, the energy efficiency assessment module 430 includes: The area acquisition submodule is used to acquire the coverage area of ​​the coverage area corresponding to multiple coverage base stations when the target base station is a coverage base station; The second energy efficiency calculation submodule is used to calculate the second basic energy efficiency of each coverage base station based on the coverage area of ​​multiple coverage base stations and the target carbon emissions of each coverage base station in the same statistical period. The second coefficient calculation submodule is used to calculate the spatial fluctuation coefficient based on the second basic energy efficiency of each coverage base station to obtain the spatial fluctuation coefficient corresponding to the target area. The spatial fluctuation coefficient is used to indicate the balance of network energy efficiency in the spatial dimension.

[0103] In summary, the energy efficiency assessment device provided in this application obtains the energy consumption of network equipment generated by processing base station communication services within a target area, and further calculates the target carbon emissions related to energy efficiency by combining the power supply methods under different statistical periods. Finally, it conducts a comprehensive energy efficiency assessment of the target area based on the carbon emissions and the base station type. Compared to the limitations of targeting only a single energy system, this solution, by introducing power supply methods, achieves differentiated calculation of carbon emissions under different energy structures. This allows for a more comprehensive and accurate reflection of the overall energy utilization efficiency of the communication network and its environmental impact, providing a scientific basis for formulating precise energy efficiency improvement strategies and achieving green and low-carbon development.

[0104] Furthermore, conducting energy efficiency assessments based on base station type makes these assessments more aligned with actual needs and improves their accuracy.

[0105] Figure 5 This diagram illustrates a structural block diagram of a computer device 500 according to an exemplary embodiment of this application. This computer device can be implemented as a server as described in the above-described scheme of this application. The computer device 500 includes a Central Processing Unit (CPU) 501, a system memory 504 including Random Access Memory (RAM) 502 and Read-Only Memory (ROM) 503, and a system bus 505 connecting the system memory 504 and the CPU 501. The computer device 500 also includes a mass storage device 506 for storing an operating system 509, application programs 510, and other program modules 511. The system memory 504 and the mass storage device 506 can be collectively referred to as memory.

[0106] According to various embodiments of this application, the computer device 500 can also be connected to a remote computer on a network, such as the Internet. That is, the computer device 500 can be connected to a network 508 via a network interface unit 507 connected to the system bus 505, or the network interface unit 507 can be used to connect to other types of networks or remote computer systems (not shown).

[0107] The memory also includes at least one instruction, at least one program, code set, or instruction set, which are stored in the memory. The central processing unit 501 executes the at least one instruction, at least one program, code set, or instruction set to implement all or part of the steps in the energy efficiency assessment methods shown in the above embodiments.

[0108] Figure 6 A structural block diagram of a computer device 600 illustrating another exemplary embodiment of this application is shown. This computer device 600 can be implemented as the aforementioned terminal. For example, the computer device can be an Android terminal device; typically, the computer device 600 includes a processor 601 and a memory 602. The memory 602 may include one or more computer-readable storage media for storing at least one instruction, which is executed by the processor 601 to implement all or part of the steps in the energy efficiency assessment method shown in the method embodiments of this application.

[0109] In some embodiments, the computer device 600 may optionally include a peripheral device interface 603 and at least one peripheral device. The processor 601, memory 602, and peripheral device interface 603 can be connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 603 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of the following: a radio frequency circuit 604, a display screen 605, a camera assembly 606, an audio circuit 607, and a power supply 608. In some embodiments, the computer device 600 also includes one or more sensors 609. These sensors 609 include, but are not limited to, an accelerometer 610, a gyroscope 611, a pressure sensor 612, an optical sensor 613, and a proximity sensor 614. Those skilled in the art will understand that... Figure 6 The structure shown does not constitute a limitation on the computer device 600, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0110] In one exemplary embodiment, a computer-readable storage medium is also provided, which stores at least one computer program that is loaded and executed by a processor to implement all or part of the steps in the energy efficiency assessment method described above. For example, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, or optical data storage device, etc.

[0111] In one exemplary embodiment, a computer program product is also provided, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions that, when executed by a computer, cause the computer to perform the above-described actions. Figure 1 All or part of the steps of the embodiments shown in the examples.

[0112] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0113] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. An energy efficiency assessment method, characterized in that, The method includes: Obtain the target device energy consumption of the target area in each statistical period; the target device energy consumption is the network device energy consumption generated to process the communication services initiated by the target base station corresponding to the target area; Based on the energy consumption of the target equipment in each statistical period of the target area and the power supply method of the target area in each statistical period, the target carbon emissions of the target area in each statistical period are calculated. The calculation method for carbon emissions corresponding to different power supply methods is different. Based on the target carbon emissions in each statistical period and the base station type of the target base station, an energy efficiency assessment is performed on the target area to obtain the energy efficiency assessment results. The acquisition of target device energy consumption in the target area within each statistical period includes: Obtain the total energy consumption of each type of equipment within the target statistical period; the target statistical period can be any one of the various statistical periods. Based on the resource occupancy ratio of communication services in the target area across various types of devices and the total energy consumption of each type of device, the energy consumption of each type of device in the target area is calculated; different types of devices are based on different resource types for evaluating resource occupancy ratios. Based on the energy consumption of each type of equipment in the target area, calculate the energy consumption of the target equipment within the target statistical period.

2. The method according to claim 1, characterized in that, The carbon emissions include carbon emissions from power supply and carbon emissions from power generation, and the power supply methods include at least one of the following: power supply from the public power grid, photovoltaic power supply, diesel power supply, and battery power supply; The carbon emissions from the power generation powered by the battery are the carbon emissions corresponding to the stored electricity. The calculation method for the carbon emissions from the power generation powered by the battery differs depending on the charging method.

3. The method according to claim 1, characterized in that, The method further includes: Obtain base station characteristic data for each base station; Clustering is performed on the base station feature data of each base station to classify each base station into capacity base stations and coverage base stations.

4. The method according to claim 3, characterized in that, The energy efficiency assessment of the target area is performed based on the target carbon emissions and the base station type of the target base station within each statistical period, resulting in energy efficiency assessment results, including: When the target base station is a capacity-type base station, the transmission traffic value of the target base station in each statistical period is obtained; Based on the transmission traffic value and the target carbon emission in each statistical period, the first basic energy efficiency of the target base station in each statistical period is calculated. The time fluctuation coefficient is calculated based on the first basic energy efficiency in each statistical period to obtain the time fluctuation coefficient corresponding to the target area. The time fluctuation coefficient is used to indicate the stability of network energy efficiency in the time dimension.

5. The method according to claim 3, characterized in that, The energy efficiency assessment of the target area is performed based on the target carbon emissions and the base station type of the target base station within each statistical period to obtain the assessment results of the target area, including: When the target base station is a coverage base station, the coverage area of ​​the coverage area corresponding to multiple coverage base stations is obtained; The second basic energy efficiency of each coverage base station is calculated based on the coverage area of ​​multiple coverage base stations and the target carbon emissions of each coverage base station in the same statistical period. The spatial fluctuation coefficient is calculated based on the second basic energy efficiency of each coverage base station to obtain the spatial fluctuation coefficient corresponding to the target area. The spatial fluctuation coefficient is used to indicate the balance of network energy efficiency in the spatial dimension.

6. An energy efficiency assessment device, characterized in that, The device includes: The energy consumption acquisition module is used to acquire the energy consumption of target devices in the target area within each statistical period; the target device energy consumption is the network device energy consumption generated for processing the communication services initiated by the target base station corresponding to the target area. The calculation module is used to calculate the target carbon emissions of the target area in each statistical period based on the energy consumption of the target equipment in each statistical period of the target area and the power supply method of the target area in each statistical period. The calculation method for carbon emissions is different for different power supply methods. The energy efficiency assessment module is used to assess the energy efficiency of the target area based on the target carbon emissions and the base station type of the target base station in each statistical period, and obtain the energy efficiency assessment results. The energy consumption acquisition module includes: The first energy consumption acquisition submodule is used to acquire the total energy consumption of each type of equipment within a target statistical period; the target statistical period can be any one of the statistical periods. The second energy consumption acquisition submodule is used to calculate the energy consumption of various types of devices in the target area based on the resource occupancy ratio of the resources called by the communication services in the target area and the total energy consumption of each type of device; different types of devices are based on different resource types for evaluating the resource occupancy ratio; The energy consumption calculation submodule is used to calculate the energy consumption of the target equipment within the target statistical period based on the energy consumption of various types of equipment in the target area.

7. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one computer program, which is loaded and executed by the processor to implement the energy efficiency assessment method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one computer program, which is loaded and executed by a processor to implement the energy efficiency assessment method as described in any one of claims 1 to 5.

9. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions that, when executed by a computer, cause the computer to perform an energy efficiency assessment method as described in any one of claims 1 to 5.

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