CN-121981362-A - Method, system, equipment and medium for calculating electric carbon coupling carbon flow

CN121981362ACN 121981362 ACN121981362 ACN 121981362ACN-121981362-A

Abstract

The invention discloses an electric carbon coupling carbon flow calculation method, system, equipment and medium, which comprise the steps of obtaining a real-time power curve of a power transmission line and corresponding current, resistance and power factor multisource operation data, segmenting the real-time power curve according to time windows, extracting a power dynamic characteristic set in each time period based on current change trend, calculating energy loss of the power transmission line in each time period according to the multisource operation data, generating a carbon emission factor calibration result by combining a reference carbon emission factor and the difference of the energy loss, determining a carbon flow attribution result of each power generation node in each time period based on the carbon emission factor calibration result and a power factor curve of each power generation node, calculating a comprehensive carbon flow value of each power generation node, and summarizing to obtain a carbon flow calculation result of the power system. The invention obviously improves the real-time performance, accuracy and physical consistency of the carbon flow calculation.

Inventors

CHEN SHENG
LI JUNLIN
QIN HAI
LIANG LING
JIAN YAJUN
LI KANG
Dai Qican
LIU JUN
WANG KUNLUN
Ren Tinghao
CHEN ZHIQI
ZHANG HONGLUE
XIA TIAN
MA JIANWEI
ZHOU ZHONGQIANG
WAN HUIJIANG
LIU XIAOFANG
LI YINGJIE

Assignees

贵州电网有限责任公司

Dates

Publication Date: 20260505
Application Date: 20251201

Claims (10)

1. An electrical carbon-coupled carbon flow calculation method, comprising: Acquiring a real-time power curve of a power transmission line and corresponding current, resistance and power factor multisource operation data; Dividing the real-time power curve according to a time window, and extracting a power dynamic feature set in each time period based on a current change trend; calculating the energy loss of the power transmission line in each time period according to the multi-source operation data, and generating a carbon emission factor calibration result by combining the difference between a reference carbon emission factor and the energy loss; determining the attribution result of the carbon flow of each power generation node in each time period based on the carbon emission factor calibration result and the power factor curve of the power generation node; And calculating the comprehensive carbon flow value of each power generation node by combining the carbon flow attribution result, the power dynamic characteristic set and the carbon emission factor calibration result, and summarizing to obtain a carbon flow calculation result of the power system.
2. The method for calculating the electric carbon coupling carbon flow according to claim 1, wherein the calculating the energy loss of the power transmission line in each time period according to the multi-source operation data comprises the following steps: Calculating the base joule heat loss based on the current effective value and the line resistance; correcting the basic joule heat loss according to the power factor to obtain an intermediate loss value accounting for the influence of reactive current; and calculating an unbalance loss correction term based on the unbalance degree of the three-phase current, and adding the unbalance loss correction term to the intermediate loss value to obtain the final energy loss.
3. The method for calculating the carbon flow of the electric carbon coupling of claim 1 or 2, wherein generating the carbon emission factor calibration result comprises: calculating the relative deviation of the reference carbon emission factor and the carbon emission corresponding to the actual loss; When the relative deviation exceeds a preset threshold, marking the current period as an abnormal calibration period; Generating a period-specific carbon emission factor offset based on the loss characteristics of the abnormal calibration period; and adding the carbon emission factor offset to the reference carbon emission factor to obtain a calibrated carbon emission factor corresponding to each time period, and taking the calibrated carbon emission factor as a carbon emission factor calibration result.
4. The method for calculating the carbon flow of the electric carbon coupling of claim 3, wherein determining the result of the attribution of the carbon flow of each power generating node in each time period comprises: Invoking a time period exclusive offset in a carbon emission factor calibration result, and performing dimensionless treatment on the offset; obtaining a power factor curve value of each power generation node under the same time index, and calculating a point-by-point difference value of a dimensionless offset and a power factor to obtain the power factor offset value; Multiplying the power factor offset value by the active power generation amount of the corresponding power generation node in the corresponding period of time to generate a node carbon flow mapping value; and collecting the carbon flow mapping values of each period according to the node numbers, calculating the accumulated sum and the time average change rate, and generating a carbon flow attribution result comprising the node allocation label, the carbon flow direction number and the attribution mapping matrix according to the relative proportion among the nodes.
5. The method for calculating the carbon flow of the electric carbon coupling of claim 4, wherein calculating the integrated carbon flow value of each power generation node comprises: Aligning each characteristic quantity in the carbon flow attribution result, the power dynamic characteristic set and the offset in the carbon emission factor calibration result point by point according to the original sampling time stamp, and complementing the data at the missing moment by adopting an interpolation mode and a forward filling mode; multiplying the aligned carbon flow attribution result by the power fluctuation frequency at the corresponding moment to obtain a fluctuation weighted carbon flow; linearly superposing the fluctuation weighted carbon flow and the aligned carbon emission factor offset; And carrying out normalized integration on the superposition result according to the duration time of the time window to obtain the comprehensive carbon flow value.
6. The method for calculating the electrical carbon coupling carbon flow of claim 5, wherein the slicing the real-time power curve according to the time window comprises: Setting the self-adaptive time window length according to the power change rate; Forcibly dividing a time window boundary at the power abrupt change point; Smoothing and filtering the power data in each time window; And respectively storing the power data after the smoothing filtering processing as a segmented power sequence according to a corresponding time window.
7. The method for calculating the carbon flow of the electric carbon coupling of claim 6, wherein the power dynamic characteristic set comprises a power fluctuation range, a power fluctuation frequency and a power change slope; the power fluctuation range is obtained by calculating the difference between the maximum value and the minimum value of the power sequence in each time window; The power fluctuation frequency is obtained by counting the continuous times of the power fluctuation amplitude exceeding a preset reference value in each time window; The power change slope is obtained by calculating the absolute value of the difference value of the adjacent power sampling points in each time window and calculating the average value.
8. An electrical carbon-coupled carbon flow computing system employing the method of any one of claims 1-7, comprising: the data acquisition module is used for acquiring a real-time power curve of the power transmission line and corresponding current, resistance and power factor multisource operation data; The dynamic characteristic extraction module is used for segmenting the real-time power curve according to a time window and extracting a power dynamic characteristic set in each time period based on a current change trend; the factor calibration module is used for calculating the energy loss of the power transmission line in each time period according to the multi-source operation data and generating a carbon emission factor calibration result by combining the difference between the reference carbon emission factor and the energy loss; The carbon flow attribution module is used for determining the carbon flow attribution result of each power generation node in each time period based on the carbon emission factor calibration result and the power factor curve of the power generation node; and the carbon flow summarizing module is used for calculating the comprehensive carbon flow value of each power generation node by combining the carbon flow attribution result, the power dynamic characteristic set and the carbon emission factor calibration result, and summarizing to obtain a carbon flow calculation result of the power system.
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

Method, system, equipment and medium for calculating electric carbon coupling carbon flow Technical Field The invention relates to the technical field of carbon flow calculation, in particular to an electric carbon coupling carbon flow calculation method, an electric carbon coupling carbon flow calculation system, electric carbon coupling carbon flow calculation equipment and an electric carbon coupling carbon flow calculation medium. Background In current power system carbon emission management, a fixed, static carbon emission factor is often employed to calculate the carbon flow. This does not make good use of timing information such as power data, current data, etc. generated in real time within the transmission line. In practice, these data are subject to constant changes over time, and the manner of the changes is complex, such as sometimes fluctuating particularly, and sometimes relatively smooth. However, the existing method does not perform segmentation processing on the time series data, and does not extract fluctuation features, such as the amplitude and the frequency of fluctuation. Thus, there is no way to accurately capture the true operating state of the power system during different periods of time. The resulting relationship between carbon emission factor and actual power consumption is reduced to a "static map" as if carbon emissions were the same whenever electricity was used. The treatment mode obviously ignores the real-time influence of power fluctuation and line energy loss on carbon emission, so that the evaluation result of the carbon emission is always half beat slowly, the actual operation condition of the system is not kept up, and the refined carbon management requirement is very difficult to support naturally. In addition, the existing model has a relatively obvious short plate in two aspects of data fusion and dynamic calibration. On the one hand, they often rely on only a single reference carbon emission factor when calculating, without effectively integrating the power, current, resistance, power factor, and other multi-source operating parameters. In fact, each of these parameters is important—for example, the energy loss of the line is different in different time periods, the power factor of the power generation node is also shifted, and these directly affect how the carbon flows are distributed. However, the existing method ignores the key factors, so that the calculated deviation of the carbon flow result is often larger. On the other hand, these models also lack a calibration mechanism that can dynamically adjust the carbon emission factor based on actual operating data. Particularly when the power demand fluctuates very much, such as during the morning and evening peaks or extreme weather, the energy loss changes very drastically, but the model has no way to update the carbon emission factor in time based on these actual loss differences across the time period. Thus, the predicted carbon emission value is not accurate enough, and it is difficult to meet the scientific and real-time requirements for carbon emission control decision in the energy management work. 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 an electric carbon coupling carbon flow calculation method, an electric carbon coupling carbon flow calculation system, electric carbon coupling carbon flow calculation equipment and an electric carbon coupling carbon flow calculation medium, which solve the problems that the existing electric carbon coupling carbon flow calculation method often depends on static carbon emission factors, real-time power, current and other time sequence data are not segmented and fluctuation feature extracted, multisource operation parameters are not fused and carbon emission factors are dynamically calibrated, so that carbon flow calculation is lag and deviation is large, and scientific and real-time carbon emission control decision is 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 calculating an electrical carbon-coupled carbon flow, comprising: Acquiring a real-time power curve of a power transmission line and corresponding current, resistance and power factor multisource operation data; Dividing the real-time power curve according to a time window, and extracting a power dynamic feature set in each time period based on a current change trend; calculating the energy loss of the power transmission line in each time period according to the multi-source operation data, and generating a carbon emission factor calibration result by combining the difference between a reference carbon emission factor and the energy loss; determining the attribution result of the carbon flow of each power generation node in each time period based on the carbon