CN-121998664-A - Energy management and control platform based on carbon emission monitoring

CN121998664ACN 121998664 ACN121998664 ACN 121998664ACN-121998664-A

Abstract

The invention belongs to the technical field of energy management and information technology intersection, and particularly discloses an energy management and control platform based on carbon emission monitoring, which comprises a carbon emission monitoring module, a carbon emission calculating module, a carbon intensity analyzing module, a task scheduling module, a task allocation optimizing module and a task feedback terminal, wherein the carbon emission monitoring module is used for monitoring the carbon emission of a user; according to the invention, the indirect carbon emission, the total active power consumption and the energy carbon intensity of the data center are converted into the unit calculation power carbon intensity, so that the carbon emission efficiency of the data center in different areas becomes quantifiable, and a carbon efficiency priority sequence is generated according to the quantified carbon emission efficiency, so that tasks are intelligently and dynamically distributed to the data center with highest current carbon efficiency, and meanwhile, the distribution result is optimized by introducing the historical task execution success rate and the completion time, so that the scheduling deviation possibly caused by purely depending on the real-time carbon efficiency is effectively avoided, and the reliability and the service quality of task execution are ensured while the low carbon emission level is maintained.

Inventors

HAN SHUAI
ZHANG MEN
ZHANG ZUOLI

Assignees

青岛利伟源重工有限公司
山东科技大学

Dates

Publication Date: 20260508
Application Date: 20260121

Claims (10)

1. The energy management and control platform based on carbon emission monitoring is characterized by comprising the following components: The carbon emission monitoring module monitors the total active power consumption of each eastern data center in the current monitoring period through the deployed intelligent ammeter, and acquires the real-time carbon intensity factor of the regional power grid of the eastern data center through the data interface; the carbon emission calculation module is used for calculating the indirect carbon emission of each eastern data center in the current monitoring period based on the electric energy consumption and the real-time carbon intensity factor; the carbon intensity analysis module is used for monitoring renewable energy data of each western data center in the current monitoring period and analyzing the energy carbon intensity of each western data center in the current monitoring period; The task scheduling module monitors running state data of each data center based on resource requirements of the computing tasks to be executed, and dynamically distributes the computing tasks by combining the indirect carbon emission and the energy carbon intensity; the task allocation optimization module is used for performing task allocation optimization by combining historical task execution data based on an allocation result of the calculation task; and the task feedback terminal feeds back a task allocation optimization result to the energy management and control platform.
2. The energy management and control platform based on carbon emission monitoring as recited in claim 1, wherein the monitoring of the total active power consumption comprises: Disposing intelligent electric meters at the electric energy input total incoming line loops of all eastern data centers, and periodically collecting instantaneous active power of the electric energy input total incoming line loops through the intelligent electric meters to form active power time sequence data; and integrating the active power time sequence data in a time window of the current monitoring period to calculate the total active power consumption of each eastern data center in the current monitoring period.
3. The energy management and control platform based on carbon emission monitoring as defined in claim 1, wherein the obtaining of the real-time carbon intensity factor comprises: Acquiring active power of various generator sets at each monitoring time point in the current monitoring period from a regional power grid to which each eastern data center belongs through a data interface; matching various generator sets with carbon emission coefficients of unit generated energy divided according to the types of the generator sets to obtain the carbon emission coefficients of unit generated energy of various generator sets; The product calculation is carried out on the active power of each generator set and the carbon emission coefficient of the unit power generation amount, and the calculation results are summed to obtain the total carbon emission rate of the power grid; summing the active power of various generator sets to obtain the total active power of the power grid; taking the ratio of the total carbon emission rate of the power grid to the total active power of the power grid as a real-time carbon intensity factor of each monitoring time point; And carrying out average value calculation on the real-time carbon intensity factors of all the monitoring time points to obtain the real-time carbon intensity factors of the regional power grid of each eastern data center in the current monitoring period.
4. The energy management and control platform based on carbon emission monitoring as defined in claim 1, wherein the calculation of the indirect carbon emission amount comprises: Acquiring the total active power consumption of each eastern data center in the current monitoring period and the real-time carbon intensity factor of the area of each eastern data center in the current monitoring period; And performing scalar multiplication operation on the total active power consumption in the current monitoring period and the real-time carbon intensity factor to obtain the indirect carbon emission of each eastern data center in the current monitoring period.
5. The energy management and control platform based on carbon emission monitoring as defined in claim 1, wherein the monitoring of the renewable energy data comprises: real-time monitoring instantaneous active power data of matched renewable energy power generation facilities through monitoring systems deployed in all western data centers; performing integral operation on the instantaneous active power data in a time window of the current monitoring period to obtain the total power generation amount of renewable energy sources of each western data center in the current monitoring period; The method comprises the steps of monitoring total active power consumption of the intelligent electric meters in a current monitoring period through the intelligent electric meters deployed in the electric energy input total inlet circuit of each western data center; And taking the total power generation amount and the total active power consumption amount of the renewable energy sources as renewable energy source data of each western data center.
6. The energy management and control platform based on carbon emission monitoring as defined in claim 1, wherein analyzing the energy carbon intensity of each western data center comprises: comparing the total active power consumption of each western data center in the current monitoring period with the total power generation of renewable energy sources; When the total power generation amount of the renewable energy sources is larger than or equal to the total active power consumption amount, judging that the energy source carbon intensity of the western data center is 0; When the total power generation amount of the renewable energy sources is smaller than the total active power consumption amount, calculating the difference value between the total active power consumption amount and the total power generation amount of the renewable energy sources to obtain the electric grid supplementary electric quantity, and multiplying the electric grid supplementary electric quantity by a real-time carbon intensity factor to obtain the carbon emission amount; Dividing the carbon emissions by the total active power consumption to calculate the energy carbon intensity for each western data center.
7. The energy management and control platform based on carbon emission monitoring as defined in claim 1, wherein the dynamically assigned computing tasks comprise: q1, determining an available data center set of each computing task to be executed based on running state data of each data center and resource requirements of the computing task to be executed; Q2, calculating the unit calculation power carbon intensity of each data center in the available data center set based on the indirect carbon emission and the total active power consumption of the eastern data center and the energy carbon intensity of the western data center; Q3, based on the unit calculation force carbon intensity, sequencing all data centers in the available data center set according to the unit calculation force carbon intensity from low to high, and generating a carbon efficiency priority sequence of each calculation task to be executed; q4, acquiring task submission time of each calculation task to be executed from the resource requirement, and sequencing each calculation task to be executed in ascending order according to the task submission time from the early to the late to generate a task sequence to be scheduled; Q5, acquiring a first unassigned calculation task to be executed from a task sequence to be scheduled, assigning the calculation task to a first available data center in a corresponding carbon efficiency priority sequence, updating the available resource state of the data center according to the assignment, and synchronously updating the carbon efficiency priority sequences of all affected tasks; q6, repeatedly executing the task allocation operation until all the calculation tasks to be executed complete data center allocation.
8. The energy management platform based on carbon emission monitoring as recited in claim 7, wherein said determining a set of available data centers for each computing task to be performed comprises: Acquiring required computing resources and required memory capacity required by execution of the computing task from resource requirements of the computing task to be executed; acquiring current available computing resources and memory capacity of each data center from the running state data, and respectively comparing the current available computing resources and memory capacity with required computing resources and required memory capacity of a computing task to be executed; And screening the data centers with the current available computing resources larger than or equal to the required computing resources and the memory capacity larger than or equal to the required memory capacity as available data centers for computing tasks to be executed, and further generating available data center sets of the computing tasks to be executed.
9. The energy management and control platform based on carbon emission monitoring as defined in claim 7, wherein the calculation of the calculated carbon strength per unit of force comprises: If the data center belongs to the eastern area, dividing the indirect carbon emission by the total active power consumption of the data center in the current monitoring period to obtain the unit calculated power carbon intensity of the data center; and if the data center belongs to the western region, taking the energy carbon intensity as the unit calculation power carbon intensity.
10. The energy management and control platform based on carbon emission monitoring as defined in claim 7, wherein the performing task allocation optimization comprises: Taking the data center distributed by each calculation task to be executed as each data center to be verified, and acquiring the historical task execution success rate of each data center to be verified and the average task completion time of the same task type from the historical task execution data; Comparing the historical task execution success rate and the average task completion time with preset thresholds respectively; When the historical task execution success rate is higher than or equal to a preset task execution success rate threshold value and the average task completion time is lower than or equal to a preset task completion time threshold value, judging that the allocation of the task to be executed does not need to be optimized; When the historical task execution success rate is lower than a preset task execution success rate threshold or the average task completion time exceeds a preset task completion time threshold, judging that the calculation task to be executed needs to be subjected to task allocation optimization; And eliminating the distributed data center from the carbon efficiency priority sequence of the task to be executed, further calculating the comprehensive preference index of the task to be executed on the residual data center based on the unit calculation power carbon intensity of the residual data center, the historical task execution success rate and the average task completion time, generating an optimized scheduling sequence according to the comprehensive preference index, and extracting the data center with the first order as the distributed data center of the task to be executed.

Description

Energy management and control platform based on carbon emission monitoring Technical Field The invention belongs to the technical field of energy management and information technology intersection, and relates to an energy management and control platform based on carbon emission monitoring. Background Under the push of digital economy, the energy consumption and carbon emission problems of data centers are increasingly prominent. In order to achieve the dual carbon objective, energy management and control technology integrating carbon emission monitoring is receiving a great deal of attention. The technology generally evaluates carbon emission by collecting data center energy consumption data and combining a carbon accounting model, and provides basis for energy efficiency optimization and carbon management. At present, a part of platforms realize basic energy consumption monitoring and carbon accounting, and few systems are trying to introduce carbon factors in task scheduling so as to preliminarily realize carbon optimization in an operation and maintenance stage. The Chinese patent of publication No. CN117217497A discloses a comprehensive energy management platform and a comprehensive energy management method, wherein the platform constructs a system architecture comprising an infrastructure layer, a data transmission layer, a platform service layer and an auxiliary service layer, can collect comprehensive energy data of various energy devices, and responds to user instructions at the platform service layer to execute corresponding operations. The auxiliary service layer further provides a peak regulation auxiliary function to assist in realizing energy supply and demand balance, and uniformly controls carbon emission of related energy equipment, so that centralized monitoring and basic carbon management of multiple types of energy equipment are realized. The prior art has the following defects that 1, the prior art can not provide dynamic real-time carbon intensity factors reflecting real-time power generation structures for an eastern data center mainly powered by a power grid, and meanwhile, the actual carbon emission reduction benefits generated by the consumption of local renewable energy sources by a western data center are difficult to evaluate accurately, so that the evaluation of the carbon performance of the data center in different areas is deviated, and the resource scheduling decision guided by the accurate carbon efficiency is difficult to support. 2. The prior art mainly focuses on energy supply and demand balance, does not establish a linkage mechanism of carbon emission and task scheduling, also lacks a unified index for converting carbon intensity into unit calculation power carbon intensity, further cannot dynamically schedule tasks to western low-carbon data centers according to carbon efficiency, and lacks a closed-loop optimization mechanism based on historical task execution success rate and completion time, so that comprehensive optimization of carbon efficiency and task performance is difficult to realize. Disclosure of Invention In view of this, in order to solve the problems set forth in the background art, an energy management and control platform based on carbon emission monitoring is proposed. The invention provides an energy management and control platform based on carbon emission monitoring, which comprises a carbon emission monitoring module, wherein the carbon emission monitoring module monitors the total active power consumption of each eastern data center in the current monitoring period through a deployed intelligent ammeter, and acquires a real-time carbon intensity factor of an regional power grid through a data interface. And the carbon emission calculation module is used for calculating the indirect carbon emission of each eastern data center in the current monitoring period based on the electric energy consumption and the real-time carbon intensity factor. And the carbon intensity analysis module is used for monitoring renewable energy data of each western data center in the current monitoring period and analyzing the energy carbon intensity of each western data center in the current monitoring period. And the task scheduling module is used for monitoring the running state data of each data center based on the resource requirement of the calculation task to be executed and dynamically distributing the calculation task by combining the indirect carbon emission and the energy carbon intensity. And the task allocation optimization module is used for performing task allocation optimization by combining historical task execution data based on an allocation result of the calculation task. And the task feedback terminal feeds back a task allocation optimization result to the energy management and control platform. Compared with the prior art, the method has the beneficial effects that (1) the method calculates the indirect carbon emission by monitoring the real-time car