Traceability and quantification method and device of electrical carbon footprint, computer equipment, readable storage medium and program product

Abstract

The invention relates to an electrical carbon footprint tracing and quantifying method, device and equipment, a readable storage medium and a program product, and relates to the technical field of carbon footprint accounting. By adopting the method, the carbon emission can be quantitatively shared based on the traceability relationship and the tracking effect. The method comprises the steps of quantifying marginal contribution of a load to new energy consumption based on a time sequence similarity and a space coupling degree in a power consumption curve of the load in unit time, and obtaining a contribution evaluation value; according to the contribution evaluation value, establishing an electrical carbon footprint traceability relationship between the source side direct carbon emission and the charge side indirect carbon emission; processing the power consumption curve by using a load flexibility characterization method based on a curve tracking mechanism to obtain a load flexibility characterization result; on the basis of an electric carbon footprint quantitative allocation mechanism, according to a load flexibility characterization result, quantifying load electric carbon footprint spatial-temporal characteristics under a curve tracking mechanism; and according to the electricity-carbon footprint traceability relation and the load electricity-carbon footprint spatial-temporal characteristics, carrying out quantitative allocation on the carbon emission of the load.

Description

Technical Field

[0001] The present application relates to the technical field of carbon footprint accounting, and in particular to a method, device, computer equipment, computer-readable storage medium and computer program product for tracing and quantifying electricity carbon footprint. Background Art

[0002] In the safe operation balance of the power grid, the demand for new energy consumption conflicts with the electricity demand of users. Different electricity consumption behaviors will produce different carbon emissions. Therefore, electricity users should be the main responsible persons for carbon emissions.

[0003] In traditional technology, the main method for measuring carbon emissions is the emission factor method, which is calculated as follows: carbon emissions are equal to the sum of the products of electricity consumption data of various activities and the emission coefficient. The carbon emission factor is calculated based on historical data and is a pre-analysis. This method is relatively practical, but due to the large uncertainty in using historical data and the large spatial scale of calculating emission factors to divide the power grid area, there are certain lags and limitations. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for tracing and quantifying electricity carbon footprint in response to the above-mentioned technical problems.

[0005] In the first aspect, the present application provides a method for tracing and quantifying the carbon footprint of electricity, including:

[0006] Obtaining a power consumption curve of the load in unit time, in the power consumption curve, quantifying the marginal contribution of the load to the consumption of new energy based on time series similarity and spatial coupling, and obtaining a contribution evaluation value;

[0007] According to the contribution evaluation value, the electric carbon footprint traceability relationship of the direct carbon emissions on the source side and the indirect carbon emissions on the load side is established;

[0008] The power consumption curve is processed by using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the power consumption curve;

[0009] Based on the preset electricity carbon footprint quantitative allocation mechanism, according to the load flexibility characterization result, quantify the spatiotemporal characteristics of the load electricity carbon footprint under the curve tracking mechanism;

[0010] The carbon emissions of the load are quantified and apportioned according to the traceability relationship of the electricity carbon footprint and the spatiotemporal characteristics of the load electricity carbon footprint.

[0011] In one embodiment, in the power consumption curve, the marginal contribution of the load to the consumption of new energy is quantified based on the time series similarity and the spatial coupling to obtain a contribution evaluation value, including:

[0012] According to the power consumption curve, the average power increase of the load in the target time period is calculated; based on the time series similarity and the spatial coupling, a marginal contribution calculation model is constructed; the power generation of the target unit and the average power increase are input into the marginal contribution calculation model to obtain the contribution evaluation value output by the marginal contribution calculation model.

[0013] In one embodiment, establishing the electric carbon footprint traceability relationship between the source-side direct carbon emissions and the load-side indirect carbon emissions according to the contribution evaluation value includes:

[0014] The contribution evaluation value is input into the direct carbon emission calculation model on the source side to obtain the direct carbon emissions, and the contribution evaluation value is input into the indirect carbon emission calculation model on the load side to obtain the indirect carbon emissions; the direct carbon emissions and the indirect carbon emissions are subjected to source tracing analysis to obtain source tracing analysis results; based on the source tracing analysis results, the electric carbon footprint traceability relationship of the direct carbon emissions on the source side and the indirect carbon emissions on the load side is established.

[0015] In one embodiment, the method for characterizing load flexibility based on a curve tracing mechanism is used to process the power consumption curve to obtain a load flexibility characterization result of the power consumption curve, including:

[0016] According to the power consumption curve, a target curve and an actual curve are obtained, the target curve is traced, and the actual curve is adjusted to obtain a target curve sequence and an actual curve sequence; according to a preset reliability index and the target curve sequence, the tracking effect of the actual curve sequence is evaluated to obtain an evaluation score; according to the evaluation score, the load flexibility characterization result of the power consumption curve is obtained.

[0017] In one embodiment, quantifying the spatiotemporal characteristics of the load electric carbon footprint under the curve tracing mechanism according to the load flexibility characterization result includes:

[0018] According to the load flexibility characterization results, the carbon emission traceability coefficient is weighted, and the data is merged through the spatial coupling matrix to obtain the carbon emission traceability matrix; according to the preset sharing ratio and power balance constraints, the carbon emission traceability matrix is ​​quantitatively calculated to obtain the equivalent carbon emissions of the load; based on the equivalent carbon emissions, the spatiotemporal characteristics of the load's electric carbon footprint are obtained.

[0019] In one embodiment, the method further comprises:

[0020] Obtain identification information of the load, and match the corresponding target information entry in the electric carbon footprint information library according to the identification information; enter the carbon emission allocation result of the load into the target information entry in the electric carbon footprint information library.

[0021] In a second aspect, the present application also provides a device for tracing and quantifying the carbon footprint of electricity, including:

[0022] A contribution evaluation module is used to obtain a power consumption curve of a load in a unit time, and in the power consumption curve, the marginal contribution of the load to the consumption of new energy is quantified based on the time series similarity and the spatial coupling to obtain a contribution evaluation value;

[0023] A relationship establishment module, used to establish an electric carbon footprint traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side according to the contribution evaluation value;

[0024] A curve processing module, used to process the power consumption curve using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the power consumption curve;

[0025] A characteristic quantification module, for quantifying the spatiotemporal characteristics of the load electric carbon footprint under the curve tracing mechanism based on a preset electric carbon footprint quantitative allocation mechanism and according to the load flexibility characterization result;

[0026] The quantitative allocation module is used to quantitatively allocate the carbon emissions of the load according to the traceability relationship of the electricity carbon footprint and the spatiotemporal characteristics of the load electricity carbon footprint.

[0027] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0028] Obtain the electricity consumption curve of the load in unit time, and in the electricity consumption curve, quantify the marginal contribution of the load to the consumption of new energy based on time series similarity and spatial coupling to obtain a contribution evaluation value; establish an electricity carbon footprint traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side according to the contribution evaluation value; process the electricity consumption curve using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the electricity consumption curve; based on a preset electricity carbon footprint quantitative allocation mechanism, quantify the spatiotemporal characteristics of the load electricity carbon footprint under the curve tracing mechanism according to the load flexibility characterization result; and quantitatively allocate the carbon emissions of the load according to the electricity carbon footprint traceability relationship and the spatiotemporal characteristics of the load electricity carbon footprint.

[0029] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0030] Obtain the electricity consumption curve of the load in unit time, and in the electricity consumption curve, quantify the marginal contribution of the load to the consumption of new energy based on time series similarity and spatial coupling to obtain a contribution evaluation value; establish an electricity carbon footprint traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side according to the contribution evaluation value; process the electricity consumption curve using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the electricity consumption curve; based on a preset electricity carbon footprint quantitative allocation mechanism, quantify the spatiotemporal characteristics of the load electricity carbon footprint under the curve tracing mechanism according to the load flexibility characterization result; and quantitatively allocate the carbon emissions of the load according to the electricity carbon footprint traceability relationship and the spatiotemporal characteristics of the load electricity carbon footprint.

[0031] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0032] Obtain the electricity consumption curve of the load in unit time, and in the electricity consumption curve, quantify the marginal contribution of the load to the consumption of new energy based on time series similarity and spatial coupling to obtain a contribution evaluation value; establish an electricity carbon footprint traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side according to the contribution evaluation value; process the electricity consumption curve using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the electricity consumption curve; based on a preset electricity carbon footprint quantitative allocation mechanism, quantify the spatiotemporal characteristics of the load electricity carbon footprint under the curve tracing mechanism according to the load flexibility characterization result; and quantitatively allocate the carbon emissions of the load according to the electricity carbon footprint traceability relationship and the spatiotemporal characteristics of the load electricity carbon footprint.

[0033] The above-mentioned traceability and quantification methods, devices, computer equipment, computer-readable storage media and computer program products of the electric carbon footprint are studied from two aspects, namely, the traceability method and the quantification mechanism, based on the spatiotemporal characteristics of electric-carbon coupling. First, a traceability method of electric carbon footprint involving the contribution of new energy consumption is proposed. The marginal contribution of load to new energy consumption is quantified based on time series similarity and spatial coupling, and the traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side is established through the contribution evaluation value; then, considering the adjustable capacity of the load, a quantitative allocation mechanism of electric carbon footprint for new energy consumption is proposed, and the system's new energy consumption capacity is improved by tracking the load to the ideal target curve, and the carbon emissions are quantitatively allocated based on the traceability relationship and tracking effect. In this application, it is proposed that the load participates in the dispatch in the form of curve tracking, and a reliability evaluation index is proposed to establish a load carbon emission traceability allocation method based on the contribution of new energy consumption, which effectively solves the problem of lag and limitations in the measurement method of carbon emissions in the current technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0035] FIG1 is an application environment diagram of a method for tracing and quantifying an electric carbon footprint in one embodiment;

[0036] Figure 2 A schematic diagram of a flow chart of a method for tracing and quantifying an electricity carbon footprint in one embodiment;

[0037] Figure 3 A schematic diagram of a process for quantifying marginal contribution in one embodiment;

[0038] Figure 4 is a schematic diagram of a curve similarity evaluation method based on Mahalanobis distance in one embodiment;

[0039] Figure 5 A schematic diagram of a flow chart of a method for tracing and quantifying the carbon footprint of electricity in a specific embodiment;

[0040] Figure 6 It is a structural block diagram of a device for tracing and quantifying the electric carbon footprint in one embodiment;

[0041] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0043] The traceability and quantification method of the electric carbon footprint provided in the embodiment of the present application can be applied in the application environment shown in FIG1 . The terminal communicates with the server through the network. The data storage system can store the data that the server needs to process. The data storage system can be integrated on the server, or placed on the cloud or other network servers.

[0044] Specifically, the method for tracing and quantifying the electricity carbon footprint provided in the embodiment of the present application can be executed by a server.

[0045] Exemplarily, the server obtains the electricity consumption curve of the load in unit time, and quantifies the marginal contribution of the load to the consumption of new energy in the electricity consumption curve based on time series similarity and spatial coupling to obtain a contribution evaluation value; the server establishes an electricity carbon footprint traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side based on the contribution evaluation value; the server processes the electricity consumption curve using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the electricity consumption curve; the server quantifies the temporal and spatial characteristics of the load electricity carbon footprint under the curve tracing mechanism based on a preset electricity carbon footprint quantitative allocation mechanism and the load flexibility characterization result; the server quantitatively allocates the carbon emissions of the load based on the electricity carbon footprint traceability relationship and the temporal and spatial characteristics of the load electricity carbon footprint.

[0046] In the application environment shown in FIG1 , the terminal may be, but is not limited to, various personal computers, notebook computers, smart phones, and tablet computers. The server may be implemented as an independent server or a server cluster consisting of multiple servers.

[0047] In one embodiment, Figure 2 As shown, a method for tracing and quantifying the carbon footprint of electricity is provided, and the method is applied to the server in FIG1 as an example for explanation, including the following steps:

[0048] Step S201, obtaining the power consumption curve of the load in unit time, and quantifying the marginal contribution of the load to the new energy consumption in the power consumption curve based on the time series similarity and spatial coupling to obtain a contribution evaluation value.

[0049] The unit time can be adjusted according to actual needs, such as one day or one week.

[0050] Among them, new energy consumption refers to the process of converting renewable energy (such as wind energy, solar energy, etc.) into electricity so that it can be effectively absorbed and utilized by power grids, users or other purposes.

[0051] Specifically, the server obtains the power consumption curve of the load in unit time. When the average power of the load increases by ΔP (constant) within a certain period of time t, the marginal contribution of the load to the consumption of new energy is quantified in the power consumption curve based on the time series similarity and spatial coupling, and the contribution evaluation value corresponding to the marginal contribution is obtained.

[0052] Step S202: establishing an electricity carbon footprint traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side according to the contribution evaluation value.

[0053] Among them, electricity carbon footprint refers to the emission of greenhouse gases such as carbon dioxide generated during the production and use of electricity. It is an important indicator for assessing the impact of electricity production, transmission and consumption on climate change.

[0054] Specifically, the server obtains direct carbon emissions and indirect carbon emissions according to the contribution evaluation value, and establishes the electricity carbon footprint traceability relationship of direct carbon emissions on the source side and indirect carbon emissions on the load side based on the direct carbon emissions and indirect carbon emissions.

[0055] Step S203: Process the power consumption curve using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the power consumption curve.

[0056] Specifically, if the fluctuation of load power consumption within a certain time scale is regarded as a normal distribution, the time series converted from the load curve can be regarded as a set of distributions, which can be regarded as a multidimensional distribution in the multidimensional space. The target curve of load tracking and the time series converted from the actual curve can be regarded as two points in the space. The distance between these two points can be used to evaluate the degree of completeness of the actual curve to the target curve, thereby obtaining the load flexibility characterization result of the power consumption curve.

[0057] Step S204, based on the preset electricity carbon footprint quantitative allocation mechanism and according to the load flexibility characterization result, the temporal and spatial characteristics of the load electricity carbon footprint under the curve tracking mechanism are quantified.

[0058] Specifically, based on the preset quantitative allocation mechanism of electricity carbon footprint and the load flexibility characterization results, the server obtains the carbon emission traceability matrix; according to the preset allocation ratio and power balance constraints, the carbon emission traceability matrix is ​​quantitatively calculated to obtain the equivalent carbon emissions of the load; based on the equivalent carbon emissions, the spatiotemporal characteristics of the load electricity carbon footprint are obtained.

[0059] Step S205: quantify and apportion the carbon emissions of the load according to the traceability relationship of the electricity carbon footprint and the spatiotemporal characteristics of the load electricity carbon footprint.

[0060] Specifically, to address the shortcomings of the existing envelope-based flexibility characterization method, a load flexibility characterization method for curve tracking is proposed. The server establishes a quantitative allocation mechanism for the electric carbon footprint for the ideal load curve. According to the traceability relationship of the electric carbon footprint and the spatiotemporal characteristics of the load electric carbon footprint, the spatiotemporal characteristics of the load electric carbon footprint under the ideal curve tracking mechanism are quantified.

[0061] The above-mentioned traceability and quantification methods of electricity carbon footprint are based on the spatiotemporal characteristics of electricity-carbon coupling, and are studied from two aspects: traceability methods and quantification mechanisms. First, a traceability method of electricity carbon footprint involving the contribution of new energy consumption is proposed. The marginal contribution of load to new energy consumption is quantified based on time series similarity and spatial coupling, and the traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side is established through the contribution evaluation value; then, considering the adjustable capacity of the load, a quantitative allocation mechanism of electricity carbon footprint for new energy consumption is proposed, and the system's new energy consumption capacity is improved by tracking the load to the ideal target curve, and carbon emissions are quantitatively allocated based on the traceability relationship and tracking effect. In this application, it is proposed that the load participates in scheduling in the form of curve tracking, and a reliability evaluation index is proposed to establish a load carbon emission tracing and allocation method based on the contribution of new energy consumption, which effectively solves the problem of lag and limitations in the current technology of carbon emission measurement methods.

[0062] In one embodiment, if Figure 3 As shown, in the above step S201, in the electricity consumption curve, the marginal contribution of the load to the consumption of new energy is quantified based on the time series similarity and the spatial coupling to obtain the contribution evaluation value, which specifically includes the following steps:

[0063] Step S301, calculating the average power increase of the load within the target time period according to the power consumption curve.

[0064] Step S302: construct a marginal contribution calculation model based on temporal similarity and spatial coupling.

[0065] Step S303: input the power generation and average power increase of the target unit into the marginal contribution calculation model to obtain the contribution evaluation value output by the marginal contribution calculation model.

[0066] Specifically, the server calculates the average power increase of the load during the target time period based on the power consumption curve; constructs a marginal contribution calculation model based on time series similarity and spatial coupling; inputs the power generation of the target unit and the average power increase into the marginal contribution calculation model to obtain the contribution evaluation value output by the marginal contribution calculation model.

[0067] It should be noted that the power system bears enormous pressure to reduce carbon emissions. When evaluating the carbon emission reduction benefits on the demand side from the perspective of new energy consumption, on the time scale, if the load can be improved through planned electricity consumption to be consistent with the timing of new energy power generation in the large power grid, it will be conducive to the consumption of new energy and reduce carbon emissions; on the spatial scale, the higher the degree of coupling between the load and the new energy power station in the power grid topology, the more new energy is consumed and the greater the contribution to emission reduction.

[0068] For example, the marginal contribution of load to renewable energy consumption can be defined as: when the load's power consumption curve in a day is known, when the average power of the load increases by ΔP (constant) within a certain period of time t, the total increase in the output of all renewable energy in the area where the power grid system to which the load is connected is , which is expressed as follows:

[0069] (1)

[0070] In the above formula, and The load increment The new energy consumption of the whole system before and after the increase, is the power generation of the i-th unit.

[0071] In one embodiment, in the above step S202, based on the contribution evaluation value, the electric carbon footprint traceability relationship between the source-side direct carbon emissions and the load-side indirect carbon emissions is established, which specifically includes the following steps:

[0072] The contribution evaluation value is input into the direct carbon emission calculation model on the source side to obtain the direct carbon emissions, and the contribution evaluation value is input into the indirect carbon emission calculation model on the load side to obtain the indirect carbon emissions; the direct carbon emissions and indirect carbon emissions are traced back to obtain the traceability analysis results; based on the traceability analysis results, the electric carbon footprint traceability relationship of the direct carbon emissions on the source side and the indirect carbon emissions on the load side is established.

[0073] Specifically, the server inputs the contribution evaluation value into the source-side direct carbon emission calculation model to obtain the direct carbon emissions output by the source-side direct carbon emission calculation model, and inputs the contribution evaluation value into the load-side indirect carbon emission calculation model to obtain the indirect carbon emissions output by the load-side indirect carbon emission calculation model; performs a traceability analysis on the direct carbon emissions and the indirect carbon emissions to obtain the traceability analysis results; and establishes a traceability relationship between the electric carbon footprint of the source-side direct carbon emissions and the load-side indirect carbon emissions based on the traceability analysis results.

[0074] For example, the carbon emission traceability of the entire network can be expressed as follows:

[0075] (2)

[0076] In the above formula, The power of the first unit G1 shared by the first load node L1, there are m load nodes and n units. Given the shared power, the carbon emissions of each load node can be obtained as:

[0077] (3)

[0078] In the above formula, is the carbon emission factor of the nth unit in the unit.

[0079] In one embodiment, in the above step S203, the load flexibility characterization method based on the curve tracing mechanism is used to process the power consumption curve to obtain the load flexibility characterization result of the power consumption curve, which specifically includes the following steps:

[0080] According to the power consumption curve, the target curve and the actual curve are obtained, the target curve is traced, and the actual curve is adjusted to obtain the target curve sequence and the actual curve sequence; according to the preset reliability index and the target curve sequence, the tracking effect of the actual curve sequence is evaluated to obtain the evaluation score; according to the evaluation score, the load flexibility characterization result of the power consumption curve is obtained.

[0081] Specifically, if the fluctuation of load power consumption within a certain time scale is regarded as a normal distribution, the time series converted from the load curve can be regarded as a set of distributions, which can be regarded as a multidimensional distribution in the multidimensional space, and the target curve of load tracking and the time series converted from the actual curve can be regarded as two points in the space. The distance between these two points can be used to evaluate the degree of completion of the actual curve to the target curve. Figure 4 As shown, in the definition of Mahalanobis distance, we can measure the distance from a point to a distribution. The calculation formula for calculating the distance from a point x to a sample distribution with a mean of μ and a covariance of S is as follows. In fact, it is equivalent to centering the multivariate variable first and then calculating the Euclidean distance:

[0082] (4)

[0083] In the above formula, x is the data point, is the sample mean.

[0084] The target curve sequence for curve tracking with known load and the adjusted load curve sequence are used as evaluation indicators to evaluate the reliability of the load in completing a target curve during curve tracking. It can be expressed as the following formula:

[0085] (5)

[0086] (6)

[0087] (7)

[0088] In the above formula, is the sequence of target load curves, is the sequence of actual load curves, k=24, is the variance of electricity consumption in the i-th hour of a day in the load history data, is a vector composed of the variance of load power consumption data within k=24 hours, The tracking deviation of the load curve tracking this time. When the actual load curve is closer to the trajectory of the target curve, the distance between the two points after centering is smaller, and the tracking deviation is The smaller the reliability index The larger it is, the more complete the load tracking target curve is during the curve tracking process, and the better the effect of load curve tracking is.

[0089] In one embodiment, in the above step S204, according to the load flexibility characterization result, the temporal and spatial characteristics of the load electricity carbon footprint under the curve tracking mechanism are quantified, which specifically includes the following steps:

[0090] According to the load flexibility characterization results, the carbon emission traceability coefficient is weighted, and the data is merged through the spatial coupling matrix to obtain the carbon emission traceability matrix; according to the preset apportionment ratio and power balance constraints, the carbon emission traceability matrix is ​​quantitatively calculated to obtain the equivalent carbon emissions of the load; based on the equivalent carbon emissions, the spatiotemporal characteristics of the load's electric carbon footprint are obtained.

[0091] Specifically, the server performs weighted calculation of the carbon emission traceability coefficient based on the load flexibility characterization results, and merges the data through the spatial coupling matrix to obtain the carbon emission traceability matrix; according to the preset sharing ratio and power balance constraints, the carbon emission traceability matrix is ​​quantitatively calculated to obtain the equivalent carbon emissions of the load; based on the equivalent carbon emissions, the spatiotemporal characteristics of the load's electric carbon footprint are obtained.

[0092] For example, the amount of electricity to be shared by each load for carbon emissions can be expressed as:

[0093] (8)

[0094] The cumulative power output of each thermal generator within T can be expressed as:

[0095] (9)

[0096] The vector of the electricity carbon footprint traceability coefficient can be expressed as follows:

[0097] (10)

[0098] In the above formula, is the carbon emission traceability coefficient, which represents the competitiveness of the load in allocating carbon emissions from thermal power units. The carbon emission traceability coefficient is weighted in all coupled loads, and the data is combined through the spatial coupling matrix to obtain the carbon emission traceability matrix, which can be expressed as follows:

[0099] (11)

[0100] (12)

[0101] In the above formula, represents the kth row of the coupling matrix, that is, the unit The power supply relationship with each load is selected from the vector Data of loads with coupling relationships, To represent the load in the coupling relationship matrix With load The coupling factor.

[0102] On load When tracing back and allocating the indirect carbon emissions generated in the electricity consumption, the following allocation ratio is limited:

[0103] (13)

[0104] (14)

[0105] In the above formula, For and load Thermal power units with coupling relationship, For load The corresponding constant, provided that the load With load There is a coupling relationship, and according to the power balance constraint conditions, it can be derived as follows:

[0106] (15)

[0107] (16)

[0108] (17)

[0109] (18)

[0110] Finally, we can substitute the original quantitative relationship and get the result:

[0111] (19)

[0112] (20)

[0113] In the above formula, represents the i-th row of the carbon emission allocation matrix, represents the i-th column of the coupling matrix, that is, the load The power supply relationship with each thermal power generating unit is selected from the vector to be allocated to the load Thermal power units with electricity output.

[0114] Substituting into equations (16) and (18), we get the load The equivalent carbon emissions of the load in T time is:

[0115] (twenty one)

[0116] In one embodiment, after the carbon emissions of the load are quantified and allocated according to the traceability relationship of the electricity carbon footprint and the temporal and spatial characteristics of the load electricity carbon footprint, the method of the present application further includes the following steps:

[0117] Obtain the identification information of the load, and match the corresponding target information entry in the electric carbon footprint information library according to the identification information; enter the carbon emission allocation result of the load into the target information entry of the electric carbon footprint information library.

[0118] Among them, an information entry generally refers to a short information unit arranged according to certain rules in a book, document, database or encyclopedia, similar to a title or a section.

[0119] Specifically, the server obtains the identification information of the load, and matches the corresponding target information entry in the electric carbon footprint information library according to the identification information; after obtaining the carbon emission allocation result of the load, the carbon emission allocation result of the load is entered into the target information entry of the electric carbon footprint information library.

[0120] In this embodiment, by matching the corresponding target information entry in the electric carbon footprint information library according to the identification information, and then entering the carbon emission allocation result of the load into the target information entry of the electric carbon footprint information library, different loads are used as the division criteria, and the carbon emission allocation result is entered into the work ticket database in a regular and orderly manner, which is conducive to the efficient storage and subsequent reference of the carbon emission allocation results.

[0121] In one embodiment, Figure 5 As shown, a method for tracing and quantifying the carbon footprint of electricity in a specific embodiment is provided, which specifically includes the following steps:

[0122] Step S501, obtain the power consumption curve of the load in unit time, and calculate the average power increase of the load in the target time period according to the power consumption curve; construct a marginal contribution calculation model based on time series similarity and spatial coupling; input the power generation of the target unit and the average power increase into the marginal contribution calculation model to obtain the contribution evaluation value output by the marginal contribution calculation model.

[0123] Step S502, input the contribution evaluation value into the source-side direct carbon emission calculation model to obtain direct carbon emissions, and input the contribution evaluation value into the load-side indirect carbon emission calculation model to obtain indirect carbon emissions; perform source tracing analysis on the direct carbon emissions and the indirect carbon emissions to obtain source tracing analysis; and establish an electric carbon footprint traceability relationship between the source-side direct carbon emissions and the load-side indirect carbon emissions based on the source tracing analysis.

[0124] Step S503, according to the power consumption curve, obtain the target curve and the actual curve, track the target curve, and adjust the actual curve to obtain the target curve sequence and the actual curve sequence; according to the preset reliability index and the target curve sequence, evaluate the tracking effect of the actual curve sequence to obtain an evaluation score; according to the evaluation score, obtain the load flexibility characterization result of the power consumption curve.

[0125] Step S504: Based on the preset electricity carbon footprint quantitative allocation mechanism, the carbon emission traceability coefficient is weighted according to the load flexibility characterization result, and the data is merged through the spatial coupling matrix to obtain the carbon emission traceability matrix; according to the preset allocation ratio relationship and power balance constraints, the carbon emission traceability matrix is ​​quantitatively calculated to obtain the equivalent carbon emissions of the load; based on the equivalent carbon emissions, the spatiotemporal characteristics of the load electricity carbon footprint are obtained.

[0126] Step S505: quantify and apportion the carbon emissions of the load according to the traceability relationship of the electricity carbon footprint and the spatiotemporal characteristics of the load electricity carbon footprint.

[0127] Step S506, obtaining identification information of the load, and matching the corresponding target information entry in the electric carbon footprint information library according to the identification information; and entering the carbon emission allocation result of the load into the target information entry of the electric carbon footprint information library.

[0128] The beneficial effects brought by the above embodiments are as follows:

[0129] First, this application proposes a carbon footprint tracing method involving the contribution of load to the consumption of new energy, reveals the principle of how load achieves carbon emission reduction, and quantifies the emission reduction effect of a load within a certain time scale from the perspective of marginal effect. It proposes an evaluation method that measures the contribution of load to the consumption of new energy through the temporal consistency of source and load, and establishes a carbon footprint tracing method for new energy consumption based on the emission reduction effect and evaluation indicators.

[0130] Second, this application establishes a carbon footprint quantitative allocation mechanism that takes into account load flexibility. In view of the shortcomings of the current load-side flexibility representation being inaccurate, unclear and difficult to evaluate, it is proposed that the load participate in scheduling in the form of curve tracing, and reliability evaluation indicators are proposed. A load carbon emission tracing and allocation method based on the contribution of new energy consumption is established, the electric carbon footprint of the target curve is quantified, and the changing characteristics of the load electric carbon footprint caused by the actual fluctuations of curve tracing are discussed.

[0131] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0132] Based on the same inventive concept, the embodiment of the present application also provides a device for tracing and quantifying the electric carbon footprint for realizing the electric carbon footprint tracing and quantification method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more electric carbon footprint tracing and quantification devices provided below can refer to the limitations of the electric carbon footprint tracing and quantification method above, and will not be repeated here.

[0133] In an exemplary embodiment, Figure 6 As shown, a device for tracing and quantifying the carbon footprint of electricity is provided, comprising:

[0134] The contribution evaluation module 601 is used to obtain the power consumption curve of the load in unit time, and in the power consumption curve, quantify the marginal contribution of the load to the consumption of new energy based on the time series similarity and spatial coupling to obtain the contribution evaluation value;

[0135] A relationship establishment module 602 is used to establish an electric carbon footprint traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side according to the contribution evaluation value;

[0136] The curve processing module 603 is used to process the power consumption curve using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the power consumption curve;

[0137] The characteristic quantification module 604 is used to quantify the temporal and spatial characteristics of the load electric carbon footprint under the curve tracking mechanism based on the preset electric carbon footprint quantitative allocation mechanism and the load flexibility characterization result;

[0138] The quantitative allocation module 605 is used to quantitatively allocate the carbon emissions of the load according to the traceability relationship of the electricity carbon footprint and the temporal and spatial characteristics of the load electricity carbon footprint.

[0139] In one embodiment, the contribution evaluation module 601 is also used to calculate the average power increase of the load within the target time period based on the power consumption curve; construct a marginal contribution calculation model based on time series similarity and spatial coupling; input the power generation of the target unit and the average power increase into the marginal contribution calculation model to obtain the contribution evaluation value output by the marginal contribution calculation model.

[0140] In one embodiment, the relationship establishment module 602 is also used to input the contribution evaluation value into the source-side direct carbon emission calculation model to obtain direct carbon emissions, and input the contribution evaluation value into the load-side indirect carbon emission calculation model to obtain indirect carbon emissions; perform a traceability analysis on the direct carbon emissions and the indirect carbon emissions to obtain the traceability analysis results; and establish an electric carbon footprint traceability relationship between the source-side direct carbon emissions and the load-side indirect carbon emissions based on the traceability analysis results.

[0141] In one embodiment, the curve processing module 603 is also used to obtain a target curve and an actual curve based on the power consumption curve, perform curve tracking on the target curve, and adjust the actual curve to obtain a target curve sequence and an actual curve sequence; evaluate the tracking effect of the actual curve sequence based on preset reliability indicators and the target curve sequence to obtain an evaluation score; and obtain a load flexibility characterization result of the power consumption curve based on the evaluation score.

[0142] In one embodiment, the feature quantification module 604 is also used to weight the carbon emission traceability coefficient according to the load flexibility characterization result, and merge the data through the spatial coupling matrix to obtain the carbon emission traceability matrix; according to the preset sharing ratio relationship and power balance constraint conditions, the carbon emission traceability matrix is ​​quantitatively calculated to obtain the equivalent carbon emissions of the load; based on the equivalent carbon emissions, the spatiotemporal characteristics of the load electric carbon footprint are obtained.

[0143] In one embodiment, the traceability and quantification device of the electric carbon footprint also includes a data storage module, which is used to obtain the identification information of the load, and match the corresponding target information entry in the electric carbon footprint information library according to the identification information; and enter the carbon emission allocation result of the load into the target information entry of the electric carbon footprint information library.

[0144] Each module in the above-mentioned electric carbon footprint traceability and quantification device can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0145] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store carbon emission allocation result data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for tracing and quantifying an electric carbon footprint is implemented.

[0146] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0147] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0148] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0149] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0150] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0151] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0152] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0153] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for tracing and quantifying the carbon footprint of electricity, characterized in that: The method comprises: Obtaining a power consumption curve of the load in unit time, in the power consumption curve, quantifying the marginal contribution of the load to the consumption of new energy based on time series similarity and spatial coupling, and obtaining a contribution evaluation value; According to the contribution evaluation value, the electric carbon footprint traceability relationship of the direct carbon emissions on the source side and the indirect carbon emissions on the load side is established; The power consumption curve is processed by using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the power consumption curve; Based on the preset electricity carbon footprint quantitative allocation mechanism, according to the load flexibility characterization result, quantify the spatiotemporal characteristics of the load electricity carbon footprint under the curve tracking mechanism; The carbon emissions of the load are quantified and apportioned according to the traceability relationship of the electricity carbon footprint and the spatiotemporal characteristics of the load electricity carbon footprint.

2. The method according to claim 1, characterized in that: In the power consumption curve, the marginal contribution of the load to the consumption of new energy is quantified based on the time series similarity and spatial coupling to obtain a contribution evaluation value, including: Calculating the average power increase of the load within the target time period according to the power consumption curve; Based on the temporal similarity and the spatial coupling degree, constructing a marginal contribution calculation model; The power generation of the target unit and the average power increase are input into the marginal contribution calculation model to obtain the contribution evaluation value output by the marginal contribution calculation model.

3. The method according to claim 1, characterized in that The electric carbon footprint traceability relationship of direct carbon emissions on the source side and indirect carbon emissions on the load side is established according to the contribution evaluation value, including: Input the contribution evaluation value into the source-side direct carbon emission calculation model to obtain direct carbon emissions, and input the contribution evaluation value into the load-side indirect carbon emission calculation model to obtain indirect carbon emissions; Performing source tracing analysis on the direct carbon emissions and the indirect carbon emissions to obtain source tracing analysis results; According to the traceability analysis results, the electricity carbon footprint traceability relationship of direct carbon emissions on the source side and indirect carbon emissions on the load side is established.

4. The method according to claim 1, characterized in that: The method for characterizing load flexibility based on a curve tracing mechanism is used to process the power consumption curve to obtain a load flexibility characterization result of the power consumption curve, including: According to the power consumption curve, a target curve and an actual curve are obtained, the target curve is traced, and the actual curve is adjusted to obtain a target curve sequence and an actual curve sequence; According to the preset reliability index and the target curve sequence, the tracking effect of the actual curve sequence is evaluated to obtain an evaluation score; According to the evaluation score, the load flexibility characterization result of the electricity consumption curve is obtained.

5. The method according to claim 4, characterized in that The step of quantifying the spatiotemporal characteristics of the load electric carbon footprint under the curve tracing mechanism according to the load flexibility characterization result includes: According to the load flexibility characterization results, the carbon emission traceability coefficient is weighted, and the data is merged through a spatial coupling matrix to obtain a carbon emission traceability matrix; According to the preset apportionment ratio and power balance constraint conditions, the carbon emission traceability matrix is ​​quantitatively calculated to obtain the equivalent carbon emissions of the load; Based on the equivalent carbon emissions, the spatiotemporal characteristics of the load electrical carbon footprint are obtained.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Obtaining identification information of the load, and matching corresponding target information entries in an electric carbon footprint information library according to the identification information; The carbon emission allocation result of the load is entered into the target information entry of the electric carbon footprint information library.

7. A device for tracing and quantifying the carbon footprint of electricity, characterized in that: The device comprises: A contribution evaluation module is used to obtain a power consumption curve of a load in a unit time, and in the power consumption curve, the marginal contribution of the load to the consumption of new energy is quantified based on the time series similarity and the spatial coupling to obtain a contribution evaluation value; A relationship establishment module, used to establish an electric carbon footprint traceability relationship between direct carbon emissions on the source side and indirect carbon emissions on the load side according to the contribution evaluation value; A curve processing module, used to process the power consumption curve using a load flexibility characterization method based on a curve tracing mechanism to obtain a load flexibility characterization result of the power consumption curve; A characteristic quantification module, for quantifying the temporal and spatial characteristics of the load electric carbon footprint under the curve tracing mechanism based on a preset electric carbon footprint quantitative allocation mechanism and according to the load flexibility characterization result; The quantitative allocation module is used to quantitatively allocate the carbon emissions of the load according to the traceability relationship of the electricity carbon footprint and the spatiotemporal characteristics of the load electricity carbon footprint.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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