Computing power network energy consumption management system and method, electronic device and storage medium

Abstract

The application provides a computing power network energy consumption management system, method, electronic equipment and storage medium, and belongs to the technical field of computing power network. The system comprises an energy consumption analysis module, a computing network operation emission reduction module and a computing network operation and maintenance carbon reduction module. The computing power network energy consumption management system provided by the application analyzes the energy consumption results of the data center through the energy consumption analysis module; generates a computing power resource scheduling scheme through the computing network operation emission reduction module, and schedules the computing power resources according to the computing power resource scheduling scheme after the business deployment, so that the utilization of the computing power resources can be optimized; generates an energy consumption optimization scheme through the computing network operation and maintenance carbon reduction module, and optimizes the system energy consumption according to the energy consumption optimization scheme, so that the overall energy consumption can be effectively optimized. The combination of the three modules can provide integrated computing network services with low carbon and low cost, realize the conversion of system energy consumption level benefits into cost advantages, promote green development by using innovative information technology means, and improve the performance of the system in the low carbon capacity.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computing power network, and in particular to a computing power network energy consumption management system and method, electronic equipment and storage medium. BACKGROUND

[0002] In the current industrial industry, data centers, network systems and edge nodes have become major energy consumers, with electricity costs accounting for 60-70% of total costs. There is an urgent need for related platforms to provide energy consumption optimization strategies in the dimensions of infrastructure construction, software and hardware collaboration, operation and maintenance, etc. There are many challenges in the current green and low-carbon software and hardware services for the industry: (1) In terms of hardware infrastructure construction and operation and maintenance, current energy-saving design is usually carried out through pre-evaluation during the construction phase, including dynamic environment, computing, storage, network architecture, etc. For data centers that have been built, there is a lack of energy efficiency optimization at the later operation and maintenance level, especially in scenarios where business load and demand are dynamically changing; (2) In terms of software operation and service, industrial platforms usually access a large number of applications for different devices and different scenarios. The current lack of related capabilities and specifications for energy consumption evaluation of software from the perspective of energy consumption and resource optimization leads to a lack of software optimization in the energy consumption dimension, as well as a lack of related capabilities to combine software energy consumption with resource scheduling of hardware, network and other infrastructure, and continuously optimize and evolve, resulting in insufficient application energy consumption management; (3) From the macroscopic scheduling and optimization aspect, it involves the collaboration of cloud, edge, end, network and other infrastructure, as well as the deployment and migration of distributed applications and data. Existing scheduling strategies mostly use delay, accuracy, resource utilization, etc. as scheduling indicators, and there is a relative lack of consideration of energy consumption. In general, the existing computing power network operating system has problems such as insufficient energy consumption evaluation of data centers in the industrial field, high overall energy consumption, low cloud-edge-end collaboration efficiency, and insufficient software and hardware collaboration capabilities. Therefore, the existing computing power network operating system performs poorly in low-carbon capability. SUMMARY

[0003] The present application provides a computing power network energy consumption management system, method, electronic equipment and storage medium to solve the problem of poor low-carbon capability of the existing computing power network operating system.

[0004] In a first aspect, the present application provides a computing power network energy consumption management system, comprising an energy consumption analysis module, a computing network operation emission reduction module and a computing network operation and maintenance carbon reduction module.

[0005] The energy consumption analysis module is configured to analyze the energy consumption results of the data center.

[0006] The computing network operation emission reduction module is configured to generate a computing power resource scheduling scheme based on the energy consumption results, and to perform computing power resource scheduling according to the computing power resource scheduling scheme after business deployment.

[0007] The algorithm network operation carbon reduction module is configured to generate an energy consumption optimization scheme based on the energy consumption results and the computing power resource scheduling scheme, and perform system energy consumption optimization according to the energy consumption optimization scheme.

[0008] In one embodiment, the energy consumption analysis module includes a green power analysis unit, an information technology load analysis unit, an application analysis unit, and a dynamic environment data analysis unit.

[0009] The green power analysis unit is configured to perceive green power of the data center and perform energy consumption analysis on the green power to obtain energy consumption results of the green power.

[0010] The information technology load analysis unit is configured to monitor load of an information technology system and perform energy consumption analysis on the load to obtain energy consumption results of the monitored information technology system.

[0011] The application analysis unit is configured to monitor running data of application software and perform energy consumption analysis on the running data to obtain energy consumption results of the application software.

[0012] The dynamic environment data analysis unit is configured to monitor dynamic environment monitoring data of a dynamic environment monitoring system and perform energy consumption analysis on the dynamic environment monitoring data to obtain energy consumption results of the dynamic environment monitoring system.

[0013] In one embodiment, the algorithm network operation emission reduction module includes a resource display unit.

[0014] The resource display unit is configured to determine a green power access amount of the green power of the data center based on the energy consumption results of the green power, evaluate green power computing power supply capacity based on the green power access amount, and visually display the green power access amount and the green power computing power supply capacity.

[0015] In one embodiment, the algorithm network operation emission reduction module further includes an energy consumption optimization evaluation unit and a computing power scheduling unit.

[0016] The energy consumption optimization evaluation unit is configured to generate an energy consumption optimization management scheme based on the energy consumption results.

[0017] The computing power scheduling unit is configured to obtain available computing power resource capacity, generate a business deployment scheme based on the computing power resource capacity and the energy consumption optimization management scheme, generate a computing power resource scheduling scheme based on the business deployment scheme, deploy businesses according to the business deployment scheme, and schedule computing power resources according to the computing power resource scheduling scheme after the business deployment.

[0018] In one embodiment, the algorithm network operation carbon reduction module includes a dynamic environment evaluation unit and an energy efficiency monitoring unit.

[0019] The dynamic ring evaluation unit is configured to obtain historical operation data of the power environment monitoring system in different working intervals, and determine an energy consumption optimal working interval according to the historical operation data;

[0020] The energy efficiency monitoring unit is configured to monitor a load of the information technology system and a load of the power environment monitoring system after scheduling of the computing power resources according to the computing power resource scheduling scheme, and determine whether there is an optimization space for the energy consumption result according to the load of the information technology system, the load of the power environment monitoring system, and the energy consumption optimal working interval.

[0021] In an embodiment, the algorithm network operation and carbon reduction module further comprises an energy consumption optimization unit.

[0022] The energy consumption optimization unit is configured to generate an energy consumption optimization scheme according to the computing power resource scheduling scheme and the energy consumption optimal working interval after determining that there is an optimization space for the energy consumption result, and perform system energy consumption optimization according to the energy consumption optimization scheme.

[0023] In a second aspect, the present application further provides an algorithm power network energy consumption management method, comprising:

[0024] analyzing an energy consumption result of a data center;

[0025] generating a computing power resource scheduling scheme based on the energy consumption result, and scheduling computing power resources according to the computing power resource scheduling scheme after business deployment;

[0026] generating an energy consumption optimization scheme based on the energy consumption result and the computing power resource scheduling scheme, and performing system energy consumption optimization according to the energy consumption optimization scheme.

[0027] In an embodiment, the generating a computing power resource scheduling scheme based on the energy consumption result, and scheduling computing power resources according to the computing power resource scheduling scheme after business deployment, comprises:

[0028] generating an energy consumption optimization management scheme according to the energy consumption result;

[0029] obtaining available computing power resource capacity, generating a business deployment scheme according to the computing power resource capacity and the energy consumption optimization management scheme;

[0030] generating a computing power resource scheduling scheme according to the business deployment scheme;

[0031] performing business deployment according to the business deployment scheme, and scheduling computing power resources according to the computing power resource scheduling scheme after business deployment.

[0032] In a third aspect, the present application provides an electronic device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the computing power network energy consumption management method when executing the program.

[0033] In a fourth aspect, the present application further provides a storage medium, which comprises a non-transitory computer readable storage medium, and a computer program is stored on the storage medium, and the computer program implements the steps of the computing power network energy consumption management method when executed by a processor.

[0034] The computing power network energy consumption management system, method, electronic device and storage medium provided by the present application can provide accurate and effective energy consumption data by analyzing the energy consumption results of the data center through the energy consumption analysis module; can optimize the utilization of computing power resources, reduce unnecessary energy waste and reduce carbon emissions by generating a computing power resource scheduling scheme through the computing network operation emission reduction module and scheduling computing power resources according to the computing power resource scheduling scheme after business deployment; and can effectively optimize the overall energy consumption and reduce carbon emissions by generating an energy consumption optimization scheme through the computing network operation carbon reduction module and optimizing the system energy consumption according to the energy consumption optimization scheme. Therefore, by combining the energy consumption analysis module, the computing network operation emission reduction module and the computing network operation carbon reduction module, an integrated computing network service with low carbon and low cost can be provided, the system energy consumption level benefit can be converted into a cost advantage, green development can be promoted by innovative information technology means, and the performance of the system in low-carbon capability can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0036] Figure 1 is a structural schematic diagram of the computing power network energy consumption management system provided by the present application;

[0037] Figure 2 is a flowchart of the computing power network energy consumption management method provided by the present application;

[0038] Figure 3 is a structural schematic diagram of the electronic device provided by the present application. DETAILED DESCRIPTION

[0039] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0040] The terms "first", "second" and the like in the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein.

[0041] The following will be described in combination with Figures 1-3 The computing power network energy consumption management system, method, electronic device and storage medium provided by the present application are described.

[0042] It should be noted that the computing power network energy consumption management system provided by the present application is mainly applied in the industrial field. Based on the multi-source data of the data center accessed from the industrial bottom layer and the application data of the upper layer, the related technologies of the computing power network are fused, the goal of improving the energy utilization efficiency and renewable energy utilization rate of the data center in the industrial field is gathered, and the energy consumption optimization under the full-chain computing power network covering "perception-analysis-operation-maintenance" is carried out. On the one hand, a perfect industrial computing network energy efficiency evaluation, low-carbon scheduling and intelligent optimization system is constructed by fusing wide-area multi-source data such as green power supply, dynamic environment data, system load and application software energy consumption; on the other hand, in the process of data transmission and analysis, based on the ability of reinforcement learning and deep learning, the container platform is supported to sink to the edge node and the end node, and at the same time, the data compression and data preprocessing algorithm can be combined to realize the cloud-edge-end collaborative ability of data, improve the resource and network utilization rate, reduce the network load and data transmission amount, so as to realize the optimization of the global task offloading strategy facing the green and low-carbon.

[0043] Figure 1 FIG. 1 is a structural schematic diagram of the computing power network energy consumption management system provided by the present application. As shown in FIG. 1, the computing power network energy consumption management system provided by the present application includes an energy consumption analysis module, a computing network operation emission reduction module and a computing network maintenance carbon reduction module. Figure 1

[0044] The energy consumption analysis module is used for analyzing the energy consumption result of the data center.

[0045] The computing network operation emission reduction module is used for generating a computing power resource scheduling scheme based on the energy consumption result, and scheduling the computing power resources according to the computing power resource scheduling scheme after the business deployment.

[0046] ​The algorithm network operation carbon reduction module is configured to generate an energy consumption optimization scheme based on the energy consumption result and the computing resource scheduling scheme, and to perform system energy consumption optimization according to the energy consumption optimization scheme.

[0047] Specifically, the energy consumption analysis module can periodically or in real time collect multi-source data of the data center, and perform energy consumption analysis on the multi-source data to obtain an energy consumption result of the data center. The multi-source data stored by the data center can include power supply data, load of information technology systems or devices, application software running data, and power environment monitoring data, etc. By using perception data fusion technologies such as deep learning, correlation analysis, and cluster analysis, a full-site integrated energy consumption analysis base is constructed for green power (i.e., electrical energy converted from renewable energy) analysis, information technology load analysis, application software analysis, and power environment data analysis, to provide accurate and effective data support for energy consumption improvement operation and operation decision-making, and to realize analysis and mining of wide-area multi-source function, energy consumption, and computing power load data, to ensure energy consumption intelligent optimization.

[0048] The algorithm network operation carbon reduction module is configured to generate an energy consumption optimization scheme based on the energy consumption result and the computing resource scheduling scheme, and to perform system energy consumption optimization according to the energy consumption optimization scheme.

[0049] The algorithm network operation carbon reduction module can also visualize data such as access amount, usage, and energy consumption of green power, to intuitively display data and information, and to help managers quickly and conveniently obtain green power related data.

[0050] The algorithm network operation carbon reduction module can analyze an energy consumption optimal working interval of information technology equipment and power environment monitoring data based on historical operation data, monitor load conditions of the information technology equipment and the power environment monitoring system after business deployment, determine whether there is an optimization space for the energy consumption result of the energy consumption analysis module according to the load conditions, generate an energy consumption optimization scheme according to the computing resource scheduling scheme and the energy consumption optimal working interval if there is an optimization space, and perform system energy consumption optimization according to the energy consumption optimization scheme, to reduce energy consumption of the information technology equipment and the power environment monitoring system to the optimal working interval.

[0051] Further, the energy consumption analysis module comprises a green power analysis unit, an information technology load analysis unit, an application analysis unit, and an environmental data analysis unit.

[0052] The green power analysis unit is configured to perceive green power of the data center and perform energy consumption analysis on the green power to obtain energy consumption results of the green power.

[0053] The information technology load analysis unit is configured to monitor load of the information technology system and perform energy consumption analysis on the load to obtain energy consumption results of the monitored information technology system.

[0054] The application analysis unit is configured to monitor running data of the application software and perform energy consumption analysis on the running data to obtain energy consumption results of the application software.

[0055] The environmental data analysis unit is configured to monitor environmental monitoring data of the environmental monitoring system and perform energy consumption analysis on the environmental monitoring data to obtain energy consumption results of the environmental monitoring system.

[0056] Specifically, the green power analysis unit can perceive the green nature of power supply of the data center through data analysis and mining technology to identify green power of the data center. Further, the green power analysis unit performs energy consumption analysis on the green power to obtain energy consumption results of the green power.

[0057] The green power analysis unit can also form a green power evaluation level of the data center through power source identification, carbon emission analysis, renewable energy contribution evaluation, and the like.

[0058] Further, the information technology load analysis unit can monitor load of the information technology system, and the load monitoring of the information technology system includes, but is not limited to, performance monitoring, fault monitoring, resource utilization monitoring, and early warning monitoring, and the like, to understand performance, resource utilization, and efficiency of the information technology system. Further, the information technology load analysis unit performs energy consumption analysis on the load of the information technology system to obtain energy consumption results of the monitored information technology system. Through monitoring and analyzing load data, information technology equipment with high energy consumption can be identified, and corresponding energy consumption improvement strategies can be specified.

[0059] Further, the application analysis unit can monitor running data of the application software to realize real-time or periodic monitoring of application data, performance parameters, and the like during running of the application software. Further, the application analysis unit performs energy consumption analysis on the running data of the application software to obtain energy consumption results of the application software.

[0060] The application software analysis unit can further obtain different categories of application software by classifying the application software, and match different categories of application software with energy consumption evaluation methods respectively. Further, the application software analysis unit generates one or more energy consumption evaluation standards based on one or more energy consumption evaluation methods, and obtains energy consumption test data of each application software based on one or more energy consumption evaluation methods. Further, the application software analysis unit compares the energy consumption test data of each application software with the energy consumption evaluation standards to obtain an energy consumption test model of the category of application software, and generates software deployment optimization suggestions according to the energy consumption test model.

[0061] Further, the dynamic environment data analysis unit can monitor the dynamic environment monitoring data of the power environment monitoring system to realize the process of monitoring and analyzing and interpreting the industrial data center infrastructure management data. Further, the dynamic environment data analysis unit performs energy consumption analysis on the dynamic environment monitoring data to obtain the energy consumption result of the power environment monitoring system. The dynamic environment monitoring data analysis includes but is not limited to energy management, environment monitoring, capacity management, and fault early warning and maintenance, etc. Through dynamic environment monitoring data analysis, effective measures for energy saving and consumption reduction are mined for computing power operation and operation, and the performance and reliability of computing power use are improved.

[0062] Further, the computing network operation emission reduction module includes a resource display unit.

[0063] The resource display unit is configured to determine a green power access amount of green power of the data center according to the energy consumption result of the green power, evaluate a green power computing power supply capacity according to the green power access amount, and visually display the green power access amount and the green power computing power supply capacity.

[0064] Specifically, the resource display unit can determine a green power access amount of green power and an amount of power resources expected to be consumed per unit computing power resource according to the energy consumption result of the green power of the data center, analyze and evaluate the capacity of the computing power center to provide green power computing power, i.e., the green power computing power supply capacity, according to the green power access amount and the amount of power resources expected to be consumed. Further, the resource display unit visually displays the green power access amount and the green power computing power supply capacity.

[0065] The resource display unit can further determine the proportion and capacity of solar power, hydropower, wind power and other green power sources used according to the energy consumption result of the data center, and visually display the proportion and capacity of the multiple green power sources.

[0066] The resource display unit can further evaluate the green power computing power of the computing power center based on data such as the stability of historical business deployment and operation of the user, and the historical stability of green power resources, obtain a green power computing power evaluation grade, and visually display the green power computing power evaluation grade.

[0067] Further, the algorithm network operation emission reduction module further comprises an energy consumption optimization evaluation unit and an algorithm scheduling unit.

[0068] The energy consumption optimization evaluation unit is configured to generate an energy consumption optimization management scheme according to the energy consumption result.

[0069] The algorithm scheduling unit is configured to obtain an available algorithm resource capacity, generate a business deployment scheme according to the algorithm resource capacity and the energy consumption optimization management scheme, generate an algorithm resource scheduling scheme according to the business deployment scheme, deploy the business according to the business deployment scheme, and schedule the algorithm resource according to the algorithm resource scheduling scheme after the business deployment.

[0070] Specifically, the energy consumption optimization evaluation unit can generate an energy consumption optimization management scheme according to the energy consumption result. In the periodic running or after the completion of the application software, the energy consumption optimization scheme can optimize the software energy consumption evaluation method, standard and algorithm resource energy consumption evaluation model.

[0071] Further, the algorithm scheduling unit can obtain the algorithm resource capacity and the storage resource capacity that the algorithm center can provide services, and generate a business deployment scheme for the centralized deployment demand of part of the user full-amount business, in order to optimize part of the business (migratable business) in the existing algorithm center, to meet the centralized deployment demand of the user. Further, the algorithm scheduling unit generates an algorithm resource scheduling scheme according to the business deployment scheme, to fully utilize the existing algorithm resources.

[0072] Further, the algorithm unit can deploy the business according to the business deployment scheme, and after the business deployment, the algorithm resource can be scheduled according to the algorithm resource scheduling scheme by connecting the algorithm workstations or cloud management platforms in each algorithm center, to realize the opening of the business.

[0073] Further, the algorithm network operation emission reduction module further comprises an energy consumption optimization evaluation unit and an algorithm scheduling unit;

[0074] The dynamic environment evaluation unit is configured to obtain historical running data of the dynamic environment monitoring system in different working intervals, and determine an energy consumption optimal working interval according to the historical running data.

[0075] The energy efficiency monitoring unit is configured to monitor the load of the information technology system and the load of the dynamic environment monitoring system after the algorithm resource is scheduled according to the algorithm resource scheduling scheme, and determine whether there is an optimization space for the energy consumption result according to the load of the information technology system, the load of the dynamic environment monitoring system and the energy consumption optimal working interval.

[0076] Specifically, the dynamic environment evaluation unit can obtain historical operation data of the power environment monitoring system in different working intervals, analyze the energy consumption of the power environment monitoring system in different working intervals, such as high-voltage power distribution, low-voltage power distribution, super-power generator set, power distribution cabinet, uninterruptible power supply system, direct current power supply system, and storage battery, per unit of electricity, to evaluate the optimal working interval of energy consumption.

[0077] The dynamic environment evaluation unit can also analyze the energy consumption of the cooling tower per unit of temperature and humidity, and the energy consumption of the air conditioner, based on the historical operation data of the power environment monitoring system, to evaluate the optimal working environment of energy consumption.

[0078] The dynamic environment evaluation unit can also evaluate the optimal control scheme of the power switch, air conditioner, air supply, chilled water, cooling tower, and other control systems based on the historical operation data of the power environment monitoring system.

[0079] Further, the energy efficiency monitoring unit can monitor the load of the information technology system and the load of the power environment monitoring system after the computing resource scheduling scheme is implemented, that is, by monitoring the business deployment, capacity demand, and performance requirements of the information technology system, the load of the computing resource, network resource, storage resource, and other information technology system devices in the computing center are monitored. Further, the energy efficiency monitoring unit evaluates whether there is an optimization space for the energy consumption result of the energy consumption analysis module based on the load of the information technology system, the load of the power environment monitoring system, and the optimal working interval of energy consumption, combined with the machine learning algorithm. If there is an optimization space for the energy consumption result, further energy consumption optimization can be achieved.

[0080] Further, the computing network operation and carbon reduction module further includes an energy consumption optimization unit.

[0081] The energy consumption optimization unit is used to generate an energy consumption optimization scheme based on the computing resource scheduling scheme and the optimal working interval of energy consumption after determining that there is an optimization space for the energy consumption result, and to perform system energy consumption optimization based on the energy consumption optimization scheme.

[0082] Specifically, the energy consumption optimization unit can generate an energy consumption optimization scheme based on the computing resource scheduling scheme and the optimal working interval of energy consumption after determining that there is an optimization space for the energy consumption result, and perform system energy consumption optimization based on the energy consumption optimization scheme, to reduce the energy consumption of the information technology equipment and the power environment monitoring system to the optimal working interval, while also satisfying the allocation of the information technology equipment and the power environment monitoring system to the optimal working environment, and satisfying the energy consumption control of the information technology equipment and the power environment monitoring system in the optimal control scheme.

[0083] Therefore, the computing power network energy consumption management system can realize energy consumption optimization of various industrial scenes, help users further realize the goal of "reducing cost, improving quality, and increasing efficiency", meet the same business demand, ensure the service quality and energy efficiency of the business, reduce the power consumption, reduce the overall cost (including electricity bill, resource investment, operation and maintenance cost, labor cost, etc.), reduce carbon emissions, realize the operation system based on the fusion of computing power network, green and low carbon, realize the analysis of industrial data, optimization of data center, digital carbon management of application equipment, and realize the operation system based on the fusion of computing power network, green and low carbon.

[0084] The computing power network energy consumption management system provided by the application can analyze the energy consumption results of the data center through the energy consumption analysis module, can provide accurate and effective energy consumption data, can generate a computing power resource scheduling scheme through the computing power network operation emission reduction module, and can optimize the utilization of computing power resources, reduce unnecessary energy waste, and reduce carbon emissions by scheduling computing power resources according to the computing power resource scheduling scheme after business deployment. The energy consumption optimization scheme can be generated through the computing power network operation and maintenance carbon reduction module, and the overall energy consumption can be effectively optimized and the carbon emissions can be reduced by optimizing the system energy consumption according to the energy consumption optimization scheme. Therefore, the energy consumption analysis module, the computing power network operation emission reduction module and the computing power network operation and maintenance carbon reduction module can provide integrated computing power network services with low carbon and low cost, realize the conversion of system energy consumption level benefits into cost advantages, promote green development by innovative information technology means, and improve the performance of the system in the low carbon capacity.

[0085] Figure 2 The application provides a computing power network energy consumption management method. Referring to Figure 2 The computing power network energy consumption management method provided by the application can include the following steps:

[0086] Step 100: analyzing the energy consumption results of a data center;

[0087] Step 200: based on the energy consumption results, generating a computing power resource scheduling scheme, and scheduling computing power resources according to the computing power resource scheduling scheme after business deployment;

[0088] Step 300: based on the energy consumption results and the computing power resource scheduling scheme, generating an energy consumption optimization scheme, and optimizing the system energy consumption according to the energy consumption optimization scheme.

[0089] The computing power resource scheduling scheme is generated based on the energy consumption results, and the computing power resource scheduling scheme is used to schedule the computing power resources after the business deployment, which includes the following steps:

[0090] According to the energy consumption result, an energy consumption optimization management scheme is generated;

[0091] An available computing resource capacity is acquired, and according to the computing resource capacity and the energy consumption optimization management scheme, a business deployment scheme is generated;

[0092] According to the business deployment scheme, a computing resource scheduling scheme is generated;

[0093] According to the business deployment scheme, business deployment is performed, and after the business deployment, computing resource scheduling is performed according to the computing resource scheduling scheme.

[0094] Specifically, the energy consumption analysis module can periodically or in real time collect multi-source data of the data center, and perform energy consumption analysis on the multi-source data to obtain the energy consumption result of the data center. The multi-source data stored by the data center can include power supply data, load of information technology systems or devices, application software running data, and power environment monitoring data, etc. By using perception data fusion technologies such as deep learning, correlation analysis, and clustering analysis, a full-site integrated energy consumption analysis base for green power analysis, information technology load analysis, application software analysis, and dynamic environment data analysis is constructed, which provides accurate and effective data support for energy consumption improvement operation and operation decision-making, and realizes analysis and mining of wide-area multi-source function, energy consumption, and computing load data, etc. to ensure energy consumption intelligent optimization.

[0095] The algorithm network operation emission reduction module mainly faces industrial industry users, and can generate a business deployment scheme meeting user requirements based on the energy consumption result of the energy consumption analysis module, further generate a computing resource scheduling scheme based on the business deployment scheme, further perform business deployment according to the business deployment scheme, and after the business deployment, perform computing resource scheduling according to the computing resource scheduling scheme. In the business deployment, the enterprise needs to consider how to effectively organize resources and allocate tasks according to user requirements, etc. to realize business strategic planning. After the business deployment, computing scheduling is a process of reasonably allocating and managing computing resources according to business requirements and resource conditions, and through effective computing scheduling, the implementation of business deployment can be better supported, and the utilization rate and efficiency of resources can be improved.

[0096] The algorithm network operation emission reduction module can also visually display data such as the access amount, use condition, and energy consumption condition of green power, which can directly display data and information to help managers quickly and conveniently obtain green power related data.

[0097] The carbon reduction module of the algorithm network operation and maintenance can analyze the energy consumption optimal working interval of the information technology equipment and the power environment monitoring data based on historical operation data, monitor the load status of the information technology equipment and the power environment monitoring system after business deployment, determine whether there is an optimization space for the energy consumption analysis module according to the load status, if there is an optimization space, generate an energy consumption optimization scheme according to the computing resource scheduling scheme and the energy consumption optimal working interval, and perform system energy consumption optimization according to the energy consumption optimization scheme, so as to reduce the energy consumption of the information technology equipment and the power environment monitoring system to the optimal working interval.

[0098] Further, the energy consumption analysis module includes a green power analysis unit, an information technology load analysis unit, an application analysis unit, and a dynamic environment data analysis unit.

[0099] The green power analysis unit is used to perceive the green power of the data center and perform energy consumption analysis on the green power to obtain the energy consumption result of the green power.

[0100] The information technology load analysis unit is used to monitor the load of the information technology system and perform energy consumption analysis on the load to obtain the energy consumption result of the monitored information technology system.

[0101] The application software analysis unit is used to monitor the running data of the application software and perform energy consumption analysis on the running data to obtain the energy consumption result of the application software.

[0102] The dynamic environment data analysis unit is used to monitor the dynamic environment monitoring data of the power environment monitoring system and perform energy consumption analysis on the dynamic environment monitoring data to obtain the energy consumption result of the power environment monitoring system.

[0103] Specifically, the green power analysis unit can perceive the green nature of the power supply of the data center through data analysis and mining technology to identify the green power of the data center. Further, the green power analysis unit performs energy consumption analysis on the green power to obtain the energy consumption result of the green power.

[0104] The green power analysis unit can also form a green power evaluation level of the data center through power source identification, carbon emission analysis, renewable energy contribution evaluation, and other methods.

[0105] Further, the information technology load analysis unit can monitor the load of the information technology system, and the load monitoring of the information technology system includes but is not limited to performance monitoring, fault monitoring, resource utilization monitoring, and early warning monitoring, etc., to understand the performance, resource utilization, and efficiency of the information technology system. Further, the information technology load analysis unit can analyze the energy consumption of the load of the information technology system to obtain the energy consumption result of the monitored information technology system. Through monitoring and analyzing the load data, the information technology equipment with high energy consumption can be identified, and the corresponding energy consumption improvement strategy can be specified.

[0106] Further, the application software analysis unit can monitor the running data of the application software to realize real-time or periodic monitoring of the application data, performance parameters, etc. during the running of the application software. Further, the application software analysis unit can analyze the energy consumption of the running data of the application software to obtain the energy consumption result of the application software.

[0107] The application software analysis unit can also classify the application software to obtain different categories of application software, and match the energy consumption evaluation method for different categories of application software. Further, the application software analysis unit can generate one or more energy consumption evaluation standards based on one or more energy consumption evaluation methods, and obtain the energy consumption test data of each application software based on one or more energy consumption evaluation methods. Further, the application software analysis unit can compare the energy consumption test data of each application software with the energy consumption evaluation standard to obtain the energy consumption test model of the application software of this category, and can generate software deployment optimization suggestions according to the energy consumption test model.

[0108] Further, the dynamic environment data analysis unit can monitor the dynamic environment monitoring data of the power environment monitoring system to realize the process of analyzing and interpreting the monitoring and management data of the industrial data center infrastructure. Further, the dynamic environment data analysis unit can analyze the energy consumption of the dynamic environment monitoring data to obtain the energy consumption result of the power environment monitoring system. The dynamic environment monitoring data analysis includes but is not limited to energy management, environment monitoring, capacity management, and fault early warning and maintenance, etc. Through the dynamic environment monitoring data analysis, effective measures for energy saving and consumption reduction of the computing power operation and operation can be mined to improve the performance and reliability of the computing power use.

[0109] Further, the computing network operation emission reduction module includes a resource display unit;

[0110] The resource display unit is configured to determine the green power access amount of the green power according to the energy consumption result of the green power of the data center, evaluate the green power computing power supply capacity according to the green power access amount, and visually display the green power access amount and the green power computing power supply capacity.

[0111] Specifically, the resource display unit can determine, according to the energy consumption result of the data center, a green electricity access amount of the green electricity and an expected power resource consumption amount of a unit computing power resource, analyze and evaluate, according to the green electricity access amount and the expected power resource consumption amount, a capacity of the computing power center capable of providing green electricity computing power, that is, a green electricity computing power supply capacity. Further, the resource display unit visually displays the green electricity access amount and the green electricity computing power supply capacity.

[0112] The resource display unit can also determine, according to the energy consumption result of the data center, a proportion and capacity of the used green power sources such as solar energy, hydropower, and wind power, and visually display the proportions and capacities of the multiple green power sources.

[0113] The resource display unit can also evaluate the green electricity computing power of the computing power center based on historical business deployment stability of the user, historical stability of the green electricity resource, and other data, obtain a green electricity computing power evaluation grade, and visually display the green electricity computing power evaluation grade.

[0114] Further, the computing network operation emission reduction module further includes an energy consumption optimization evaluation unit and a computing power scheduling unit.

[0115] The energy consumption optimization evaluation unit is configured to generate an energy consumption optimization management scheme according to the energy consumption result.

[0116] The computing power scheduling unit is configured to obtain an available computing power resource capacity, generate a business deployment scheme according to the computing power resource capacity and the energy consumption optimization management scheme, generate a computing power resource scheduling scheme according to the business deployment scheme, deploy the business according to the business deployment scheme, and schedule the computing power resource according to the computing power resource scheduling scheme after the business deployment.

[0117] Specifically, the energy consumption optimization evaluation unit can generate an energy consumption optimization management scheme according to the energy consumption result. In the periodic running of the application software or after completion, the energy consumption optimization scheme can optimize the software energy consumption evaluation method, standard, and computing power resource energy consumption evaluation model.

[0118] Further, the computing power scheduling unit can obtain the computing power resource capacity and the storage resource capacity that the computing power center can provide services, generate a business deployment scheme for part of the user's full-amount business centralized deployment demand, in order to optimize part of the business (migratable business) in the existing computing power center, to meet the user's centralized deployment demand. Further, the computing power scheduling unit generates a computing power resource scheduling scheme according to the business deployment scheme, to fully utilize the existing computing power resources.

[0119] Further, the computing power unit can deploy services according to a service deployment scheme, and after service deployment, the computing power resources can be scheduled according to a computing power resource scheduling scheme by connecting the computing power workstations or cloud management platforms in each computing power center, so as to realize the opening of services.

[0120] Further, the algorithm network operation and carbon reduction module comprises a dynamic environment evaluation unit and an energy efficiency monitoring unit.

[0121] The dynamic environment evaluation unit is configured to obtain historical operation data of the power environment monitoring system in different working intervals, and determine an energy consumption optimal working interval according to the historical operation data.

[0122] The energy efficiency monitoring unit is configured to monitor the load of the information technology system and the load of the power environment monitoring system after the computing power resources are scheduled according to the computing power resource scheduling scheme, and determine whether there is an optimization space for the energy consumption result according to the load of the information technology system, the load of the power environment monitoring system and the energy consumption optimal working interval.

[0123] Specifically, the dynamic environment evaluation unit can obtain historical operation data of the power environment monitoring system in different working intervals, analyze the energy consumption of the power environment monitoring system in different working intervals, such as high-voltage power distribution, low-voltage power distribution, super-power generator set, power distribution cabinet, uninterruptible power supply system, direct current power supply system, and battery, per unit of electricity, so as to evaluate the energy consumption optimal working interval.

[0124] The dynamic environment evaluation unit can also analyze the cooling tower energy consumption and the energy consumption of air conditioners per unit of temperature and humidity based on the historical operation data of the power environment monitoring system under different temperature and humidity, so as to evaluate the energy consumption optimal working environment.

[0125] The dynamic environment evaluation unit can also evaluate the energy consumption optimal control scheme of the control system of power switches, air conditioners, air supply, chilled water, cooling towers, etc. based on the historical operation data of the power environment monitoring system.

[0126] Further, the energy efficiency monitoring unit can monitor the load of the information technology system and the load of the power environment monitoring system after the computing power resources are scheduled according to the computing power resource scheduling scheme, that is, by monitoring the service deployment situation, capacity demand and performance requirements of the information technology system, etc. The load of various information technology system devices such as computing resources, network resources and storage resources in the computing power center is monitored. Further, the energy efficiency monitoring unit determines whether there is an optimization space for the energy consumption result of the energy consumption analysis module according to the load of the information technology system, the load of the power environment monitoring system and the energy consumption optimal working interval, and combines the machine learning algorithm to evaluate the energy consumption result. If there is an optimization space for the energy consumption result, energy consumption optimization can be further realized.

[0127] Further, the algorithm network operation and maintenance carbon reduction module further comprises an energy consumption optimization unit.

[0128] The energy consumption optimization unit is configured to generate an energy consumption optimization scheme according to the computing resource scheduling scheme and the optimal energy consumption interval after determining that there is an optimization space for the energy consumption result, and to perform system energy consumption optimization according to the energy consumption optimization scheme.

[0129] Specifically, the energy consumption optimization unit can generate an energy consumption optimization scheme according to the computing resource scheduling scheme and the optimal energy consumption interval after determining that there is an optimization space for the energy consumption result, and perform system energy consumption optimization according to the energy consumption optimization scheme, so as to reduce the energy consumption of the information technology equipment and the power environment monitoring system to the optimal working interval, and also satisfy the allocation of the information technology equipment and the power environment monitoring system to the optimal working environment, and satisfy the energy consumption control of the information technology equipment and the power environment monitoring system in the optimal control scheme.

[0130] Therefore, the computing power network energy consumption management system can realize energy consumption optimization of various industrial scenarios, help users to further realize the goal of "reducing cost, improving quality and increasing efficiency", and reduce the overall cost (including electricity bill, resource investment, operation and maintenance cost, labor cost, etc.) while meeting the same business demand, ensuring the service quality and energy efficiency of the business, reducing the carbon emission, and realizing the surplus carbon quota obtained by reducing the emission in the carbon trading market to obtain the emission reduction income, and continuously promoting the intensive, efficient and green development of the industrial computing power network.

[0131] The computing power network energy consumption management method provided by the present application can analyze the energy consumption result of the data center through the energy consumption analysis module, can provide accurate and effective energy consumption data, can generate a computing resource scheduling scheme through the algorithm network operation and maintenance carbon reduction module, and can optimize the utilization of computing resources, reduce unnecessary energy waste and reduce carbon emissions by scheduling computing resources according to the computing resource scheduling scheme after the business deployment. Through the algorithm network operation and maintenance carbon reduction module, an energy consumption optimization scheme can be generated, and system energy consumption optimization can be performed according to the energy consumption optimization scheme, which can effectively optimize the overall energy consumption and reduce carbon emissions. Therefore, by combining the energy consumption analysis module, the algorithm network operation and maintenance carbon reduction module and the algorithm network operation and maintenance carbon reduction module, low-carbon and low-cost integrated computing power network services can be provided, the system energy consumption level income can be converted into cost advantage, and innovative information technology means can be used to promote green development, so as to improve the performance of the system in the low-carbon ability.

[0132] Figure 3 is a structural schematic diagram of an electronic device provided by the present application, as Figure 3As shown, the electronic device can include a processor 310, a communications interface 320, a memory 330, and a communications bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other through the communications bus 340. The processor 310 can invoke the logical instructions in the memory 330 to execute the computing power network energy consumption management method, which includes analyzing the energy consumption results of a data center; based on the energy consumption results, generating a computing power resource scheduling scheme, and after business deployment, performing computing power resource scheduling according to the computing power resource scheduling scheme; based on the energy consumption results and the computing power resource scheduling scheme, generating an energy consumption optimization scheme, and performing system energy consumption optimization according to the energy consumption optimization scheme.

[0133] In addition, the logical instructions in the memory 330 described above can be implemented in the form of a software functional unit and sold or used as an independent product, which can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0134] On the other hand, the present application also provides a computer program product, which includes a computer program stored on a non-transitory computer readable storage medium, and the computer program includes program instructions, when the program instructions are executed by a computer, the computer can execute the computing power network energy consumption management method provided by the above-mentioned embodiments, which includes: analyzing the energy consumption results of a data center; based on the energy consumption results, generating a computing power resource scheduling scheme, and after business deployment, performing computing power resource scheduling according to the computing power resource scheduling scheme; based on the energy consumption results and the computing power resource scheduling scheme, generating an energy consumption optimization scheme, and performing system energy consumption optimization according to the energy consumption optimization scheme.

[0135] In yet another aspect, the present application also provides a non-transitory computer readable storage medium having stored thereon a computer program, which, when executed by a processor, implements a computing power network energy consumption management method provided by any of the above embodiments. The method includes: analyzing energy consumption results of a data center; generating a computing power resource scheduling scheme based on the energy consumption results, and performing computing power resource scheduling according to the computing power resource scheduling scheme after service deployment; generating an energy consumption optimization scheme based on the energy consumption results and the computing power resource scheduling scheme, and performing system energy consumption optimization according to the energy consumption optimization scheme.

[0136] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the present embodiment scheme according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0137] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software plus necessary universal hardware platforms, and of course, can also be realized by hardware. Based on such understanding, the above technical solutions, essentially or in terms of contribution to the prior art, can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0138] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to some technical features thereof; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A computing power network energy consumption management system, characterized in that, It includes an energy consumption analysis module, a computing network operation and emission reduction module, and a computing network operation and maintenance carbon reduction module; The energy consumption analysis module is used to analyze the energy consumption results of the data center; The computing network operation emission reduction module is used to generate a computing power resource scheduling scheme based on the energy consumption results, and to perform computing power resource scheduling according to the computing power resource scheduling scheme after the business is deployed. The computing network operation and maintenance carbon reduction module is used to generate an energy consumption optimization plan based on the energy consumption results and the computing power resource scheduling plan, and to optimize the system energy consumption according to the energy consumption optimization plan. The network operation emission reduction module also includes an energy consumption optimization and evaluation unit and a computing power scheduling unit; The energy consumption optimization assessment unit is used to generate an energy consumption optimization management plan based on the energy consumption results; The computing power scheduling unit is used to obtain the available computing power resource capacity, generate a business deployment plan based on the computing power resource capacity and the energy consumption optimization management plan, generate a computing power resource scheduling plan based on the business deployment plan, deploy the business according to the business deployment plan, and schedule computing power resources according to the computing power resource scheduling plan after the business deployment. The carbon reduction module for network operation and maintenance includes an environmental assessment unit and an energy efficiency monitoring unit. The dynamic environment assessment unit is used to acquire historical operating data of the power environment monitoring system in different working ranges, and to determine the optimal energy consumption working range based on the historical operating data. The energy efficiency monitoring unit is used to monitor the load of the information technology system and the load of the power and environment monitoring system after scheduling computing resources according to the computing resource scheduling scheme, and to determine whether there is room for optimization of the energy consumption results based on the load of the information technology system, the load of the power and environment monitoring system and the optimal energy consumption working range. The carbon reduction module for network operation and maintenance also includes an energy consumption optimization unit; The energy consumption optimization unit is used to generate an energy consumption optimization scheme based on the computing power resource scheduling scheme and the optimal energy consumption working interval after determining that there is room for optimization in the energy consumption result, and to perform system energy consumption optimization based on the energy consumption optimization scheme.

2. The computing power network energy consumption management system according to claim 1, characterized in that, The energy consumption analysis module includes a green electricity analysis unit, an information technology load analysis unit, an application software analysis unit, and an environmental data analysis unit. The green power analysis unit is used to sense the green power of the data center and perform energy consumption analysis on the green power to obtain the energy consumption results of the green power. The information technology load analysis unit is used to monitor the load of the information technology system and perform energy consumption analysis on the load to obtain the energy consumption results of the monitored information technology system. The application software analysis unit is used to monitor the operating data of the application software and perform energy consumption analysis on the operating data to obtain the energy consumption results of the application software. The dynamic environment data analysis unit is used to monitor the dynamic environment monitoring data of the power environment monitoring system and perform energy consumption analysis on the dynamic environment monitoring data to obtain the energy consumption results of the power environment monitoring system.

3. The computing power network energy consumption management system according to claim 2, characterized in that, The network operation emission reduction module includes a resource display unit; The resource display unit is used to determine the amount of green electricity accessed based on the energy consumption results of green electricity in the data center, evaluate the green electricity computing power supply capacity based on the amount of green electricity accessed, and visualize the amount of green electricity accessed and the green electricity computing power supply capacity.

4. A method for managing the energy consumption of a computing network, characterized in that, include: Analyze the energy consumption results of the data center; Based on the energy consumption results, a computing resource scheduling scheme is generated, and computing resources are scheduled according to the computing resource scheduling scheme after the service is deployed. Based on the energy consumption results and the computing resource scheduling scheme, an energy consumption optimization scheme is generated, and the system energy consumption is optimized according to the energy consumption optimization scheme. The process of generating a computing resource scheduling scheme based on the energy consumption results, and then scheduling computing resources according to the scheme after service deployment, includes: Based on the energy consumption results, an energy consumption optimization management plan is generated; Obtain available computing power resources capacity, and generate a business deployment plan based on the computing power resources capacity and the energy consumption optimization management scheme; Based on the aforementioned business deployment plan, a computing resource scheduling plan is generated; Deploy services according to the aforementioned service deployment plan, and then schedule computing resources according to the aforementioned computing resource scheduling plan after service deployment. The step of generating an energy consumption optimization scheme based on the energy consumption results and the computing resource scheduling scheme, and optimizing system energy consumption according to the energy consumption optimization scheme, includes: Acquire historical operating data of the power and environment monitoring system in different working zones, and determine the optimal energy consumption working zone based on the historical operating data; After scheduling computing resources according to the computing resource scheduling scheme, the load of the information technology system and the load of the power and environment monitoring system are monitored. Based on the load of the information technology system, the load of the power and environment monitoring system and the optimal energy consumption working range, it is determined whether there is room for optimization of the energy consumption results. After determining that there is room for optimization in the energy consumption results, an energy consumption optimization scheme is generated based on the computing power resource scheduling scheme and the optimal energy consumption working interval, and the system energy consumption is optimized according to the energy consumption optimization scheme.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the computing power network energy consumption management method as described in claim 4.

6. A storage medium comprising a non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the computing power network energy consumption management method as described in claim 4.

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