CN-121981361-A - Carbon emission tracking method, system, equipment and medium for electric power system

CN121981361ACN 121981361 ACN121981361 ACN 121981361ACN-121981361-A

Abstract

The invention discloses a carbon emission tracking method, a system, equipment and a medium of an electric power system, which comprise the steps of combining a current power supply structure and carbon emission intensity of each generator set, calculating a carbon emission response value of a corresponding period to generate a carbon emission fluctuation influence data set, comparing the carbon emission fluctuation influence data set with actual carbon emission monitoring data, analyzing time lag characteristics of carbon emission response caused by load fluctuation to generate a carbon emission timeliness influence result, identifying abnormal fluctuation events in actual carbon emission, correcting parameters of a carbon emission response model according to the identification result to generate a carbon emission fluctuation monitoring feedback result, analyzing carbon emission trend to generate a carbon emission fluctuation trend data set, and combining abnormal fluctuation event information and corrected model parameters to generate a carbon emission state tracking report. The invention realizes high-precision, real-time, self-adaptive and prospective monitoring of the carbon emission state of the power system.

Inventors

CHEN ZHIQI
LU XIN
CHEN LONG
LIN CHAO
WANG ZHIPENG
YANG YUNYI
ZHANG HONGLUE
CHEN SHENG
XIA TIAN
JIAN YAJUN
TAN WENHUI
LI KANG
RAO HONGYU
GUO MING

Assignees

贵州电网有限责任公司

Dates

Publication Date: 20260505
Application Date: 20251201

Claims (10)

1. A method for tracking carbon emissions in an electrical power system, comprising: Acquiring real-time load data of a power system, extracting multi-dimensional characteristics of load fluctuation, and generating a load fluctuation characteristic data set; based on the load fluctuation characteristic data set, combining the current power supply structure and the carbon emission intensity of each generator set, calculating a carbon emission response value of a corresponding period, and generating a carbon emission fluctuation influence data set; Comparing the carbon emission fluctuation influence data set with actual carbon emission monitoring data, analyzing the time lag characteristic of carbon emission response caused by load fluctuation, and generating a carbon emission timeliness influence result; Based on the carbon emission timeliness influence result, identifying an abnormal fluctuation event in actual carbon emission, and correcting parameters of a carbon emission response model according to the identification result to generate a carbon emission fluctuation monitoring feedback result; And carrying out carbon emission trend analysis based on the carbon emission fluctuation monitoring feedback result to generate a carbon emission fluctuation trend data set, and combining the abnormal fluctuation event information and the corrected model parameters to generate a carbon emission state tracking report.
2. The method for tracking carbon emission of an electric power system according to claim 1, wherein the extracting the multidimensional feature of the load fluctuation comprises: Carrying out sliding window segmentation on the real-time load data to obtain a plurality of continuous time window subsequences; calculating the load change amplitude and the load change rate in each window based on the time window subsequence, and generating a window level fluctuation feature vector; Based on the window level fluctuation feature vector, load fluctuation is divided into periodic fluctuation and aperiodic fluctuation.
3. The method for tracking carbon emissions in an electrical power system of claim 1 or 2, wherein generating the carbon emissions fluctuation influencing dataset comprises: Distributing the load fluctuation characteristics to corresponding power supply nodes according to the power areas; Based on the dispatching output proportion of the current running unit of each power supply node, carrying out weighted aggregation on the carbon emission intensity of the unit to obtain regional carbon emission intensity; according to the regional carbon emission intensity, respectively analyzing the carbon emission influence of periodic fluctuation and aperiodic fluctuation to obtain a periodic carbon emission response value and an aperiodic carbon emission response value; and summarizing the periodic carbon emission response values and the aperiodic carbon emission response values according to regions to generate a carbon emission fluctuation influence data set.
4. The method for tracking carbon emissions in an electrical power system of claim 3 wherein said analyzing a time-lag characteristic of a load fluctuation induced carbon emission response comprises: Dividing an instantaneous response interval, a short-term hysteresis interval and a long-term hysteresis interval according to the time delay of the carbon emission response by taking the load fluctuation occurrence moment as a starting point; calculating the carbon emission variation amplitude according to the carbon emission monitoring data in the transient response interval, the short-term hysteresis interval and the long-term hysteresis interval respectively, and counting the corresponding variance of each interval to obtain the corresponding stability index of each interval; And screening a hysteresis interval with variance lower than a preset stability threshold as an effective response mode based on the stability index, and generating a carbon emission timeliness influence result.
5. The method for tracking carbon emissions in an electrical power system of claim 4 wherein identifying an abnormal surge event comprises: Calculating a standard deviation based on the historical prediction error sequence, and setting an abnormality determination threshold to be twice the standard deviation; calculating the absolute value of the deviation between the current actual carbon emission monitoring value and the expected response value, and generating an abnormal fluctuation event identifier when the absolute value of the deviation exceeds the abnormal judgment threshold value; And responding to the abnormal fluctuation event identification, and recording the abnormal occurrence time, the area and the corresponding load fluctuation characteristics.
6. The method for tracking carbon emissions in an electrical power system of claim 5 wherein said modifying parameters of a carbon emission response model comprises: Based on the deviation direction and the magnitude of the abnormal fluctuation event, updating the response coefficient of the corresponding region to obtain a corrected response coefficient; Applying the corrected response coefficient to a carbon emission response value prediction for a subsequent period of time; And the carbon emission monitoring frequency of the next period is adjusted while updating the response coefficient.
7. The method for tracking carbon emissions in an electrical power system of claim 6, wherein said performing carbon emission trend analysis comprises: Smoothing the carbon emission sequence in the carbon emission fluctuation monitoring feedback result by adopting a moving average method to obtain a smoothed carbon emission trend sequence; based on the smoothed carbon emission trend sequence, detecting trend change key points by using an accumulation and algorithm, and determining trend directions of the key points; And generating a carbon emission fluctuation trend data set containing trend lifting marks and descending marks according to the trend change key points and trend directions corresponding to the trend change key points.
8. A power system carbon emission tracking system employing the method of any one of claims 1-7, comprising: the load fluctuation feature extraction module is used for acquiring real-time load data of the power system, extracting multi-dimensional features of load fluctuation and generating a load fluctuation feature data set; The electric-carbon coupling response modeling module is used for calculating a carbon emission response value of a corresponding period based on the load fluctuation characteristic data set and combining the current power supply structure and the carbon emission intensity of each generator set to generate a carbon emission fluctuation influence data set; The carbon emission response hysteresis analysis module is used for comparing the carbon emission fluctuation influence data set with actual carbon emission monitoring data, analyzing the time hysteresis characteristic of carbon emission response caused by load fluctuation, and generating a carbon emission timeliness influence result; the abnormal recognition and model feedback correction module is used for recognizing abnormal fluctuation events in actual carbon emission based on the carbon emission timeliness influence result, correcting parameters of a carbon emission response model according to the recognition result and generating a carbon emission fluctuation monitoring feedback result; and the carbon emission state comprehensive evaluation module is used for carrying out carbon emission trend analysis based on the carbon emission fluctuation monitoring feedback result to generate a carbon emission fluctuation trend data set, and combining the abnormal fluctuation event information and the corrected model parameters to generate a carbon emission state tracking report.
9. An electronic device, comprising: a memory for storing a program; a processor for loading the program to perform the steps of the method according to any one of claims 1-7.
10. A computer readable storage medium storing a program, which when executed by a processor, implements the steps of the method according to any one of claims 1-7.

Description

Carbon emission tracking method, system, equipment and medium for electric power system Technical Field The invention relates to the technical field of power systems, in particular to a method, a system, equipment and a medium for tracking carbon emission of a power system. Background The current carbon emission monitoring of the power system mainly extends around the running state of equipment, such as voltage, current and power variation, and the core aim is to ensure the safety and stability of a power grid. However, the dynamic and complex association relation between load fluctuation and carbon emission is often insufficient, and the modeling capability of depth is not established. In fact, load fluctuations contain multi-dimensional characteristics of amplitude, period, frequency, etc., which directly affect how different types of power sources are called by scheduling, and the carbon intensity of power sources such as coal power, gas power, wind power, photovoltaic, etc. are greatly different. However, the prior art does not effectively couple the load characteristics with the power structure and the carbon intensity variation, so that it is difficult to capture the carbon emission nonlinear response process caused by the load disturbance, and the monitoring result is seriously disjointed with the actual carbon emission behavior. Under such periodic scenes as the early and late peaks or sudden disturbance such as sudden start and stop of a large user, sudden drop of new energy output and the like, the response of carbon emission usually has time delay and trend evolution, but the system often ignores the hysteresis effect, so that an evaluation result is obviously delayed and real emission dynamics cannot be reflected timely. Short plates exist in the aspect of abnormality identification, the judgment is mostly carried out by depending on a fixed threshold value, an adaptive judging mechanism based on time sequence data is lacked, and the situation of misjudgment or missed judgment exists in the face of complex rules of different areas and different time periods. More importantly, the current monitoring mainly comprises post-event data summarization, a closed loop mechanism of 'monitoring-analysis-feedback-adjustment' is not formed, and accurate and timely decisions required by real-time regulation strategies such as low-carbon scheduling, demand response and the like are difficult to support. Disclosure of Invention The present invention has been made in view of the above-described problems occurring in the prior art. Therefore, the invention provides a carbon emission tracking method, a system, equipment and a medium for an electric power system, which solve the problems that the existing carbon emission monitoring method for the electric power system lacks modeling capability of dynamic and nonlinear association and time-dependent response between load fluctuation and carbon emission, so that evaluation is delayed, abnormal identification is not timely, and accurate regulation and control are difficult to support. In order to solve the technical problems, the invention provides the following technical scheme: in a first aspect, the present invention provides a method for tracking carbon emissions in an electrical power system, comprising: Acquiring real-time load data of a power system, extracting multi-dimensional characteristics of load fluctuation, and generating a load fluctuation characteristic data set; based on the load fluctuation characteristic data set, combining the current power supply structure and the carbon emission intensity of each generator set, calculating a carbon emission response value of a corresponding period, and generating a carbon emission fluctuation influence data set; Comparing the carbon emission fluctuation influence data set with actual carbon emission monitoring data, analyzing the time lag characteristic of carbon emission response caused by load fluctuation, and generating a carbon emission timeliness influence result; Based on the carbon emission timeliness influence result, identifying an abnormal fluctuation event in actual carbon emission, and correcting parameters of a carbon emission response model according to the identification result to generate a carbon emission fluctuation monitoring feedback result; And carrying out carbon emission trend analysis based on the carbon emission fluctuation monitoring feedback result to generate a carbon emission fluctuation trend data set, and combining the abnormal fluctuation event information and the corrected model parameters to generate a carbon emission state tracking report. As a preferable mode of the electric power system carbon emission tracking method of the present invention, the extracting the multidimensional feature of the load fluctuation includes: Carrying out sliding window segmentation on the real-time load data to obtain a plurality of continuous time window subsequences; calculating the load change