Distribution network carbon footprint estimation method and related equipment based on electricity data

Abstract

The present invention provides a method and related equipment for estimating the carbon footprint of a distribution network based on electricity data. The method comprises: obtaining the power supply of the distribution network on a typical day, a first-node carbon potential curve, and a load power curve, wherein the power supply includes user power consumption, fixed line loss power, and variable line loss power; obtaining the average carbon potential corresponding to the fixed line loss power based on the first-node carbon potential curve; obtaining the weighted average carbon potential corresponding to the user power consumption and the square-weighted average carbon potential corresponding to the variable line loss power based on the first-node carbon potential curve and the load power curve; and obtaining an estimated carbon footprint corresponding to the power supply based on the average carbon potential and the corresponding fixed line loss power, the weighted average carbon potential and the corresponding user power consumption, and the square-weighted average carbon potential and the corresponding variable line loss power. The present invention is applicable to distribution networks where real-time measurement data is difficult to obtain or incomplete, and can achieve accurate estimation of the carbon footprint of the distribution network.

Description

Technical Field

[0001] The present invention relates to the field of carbon emission technology, and in particular to a method for estimating the carbon footprint of a distribution network based on electricity data and related equipment. Background Art

[0002] Energy is fundamental to maintaining a peaceful and stable society. With the strategic goals of achieving carbon neutrality and peak carbon emissions, clean, low-carbon energy has become a core objective of the new power system. To assess the effectiveness of regional low-carbon emission reduction efforts, carbon footprint analysis of distribution networks is imperative.

[0003] However, accurate distribution network carbon footprint analysis is still relatively difficult at this stage. On the one hand, medium and low voltage distribution networks have long suffered from problems such as incomplete measurement and low data quality, making it difficult to obtain an accurate and comprehensive network status. On the other hand, with the access of low-carbon power sources such as photovoltaics and wind turbines, the spatiotemporal distribution of the distribution network's carbon footprint has become more complex, bringing new challenges to carbon footprint analysis, making traditional methods for accurately calculating carbon emission flows unsuitable for actual analysis of the distribution network's carbon footprint.

[0004] Existing research on the carbon footprint of distribution networks primarily relies on improvements to carbon emission flow theory, but still requires network power flow calculations. These methods are not suitable for distribution networks with incomplete measurements and where multi-time-section time-series power flow calculations are difficult. Therefore, this paper proposes a method for estimating the carbon footprint of distribution networks based on electricity data for these incompletely measured networks. Summary of the Invention

[0005] This invention provides a method and related equipment for estimating the carbon footprint of a distribution network based on electricity data. This method is applicable to distribution networks where real-time measurement data is difficult or incomplete, enabling accurate estimation of the distribution network's carbon footprint. Given the high cost of improving distribution network measurement and the persistent problems of incomplete measurement, this invention demonstrates the feasibility of carbon footprint estimation even under incomplete distribution network measurement conditions, providing guidance for evaluating the effectiveness and direction of regional power carbon emission reduction efforts.

[0006] The present invention provides a method for estimating the carbon footprint of a distribution network based on electricity data, comprising:

[0007] Obtain the power supply, first-node carbon potential curve, and load power curve of the distribution network on a typical day, wherein the power supply includes user power consumption, fixed line loss power, and variable line loss power;

[0008] Based on the first-node carbon potential curve, obtaining an average carbon potential corresponding to the fixed line loss electricity;

[0009] Based on the first node carbon potential curve and the load power curve, respectively obtaining a weighted average carbon potential corresponding to the user's electricity consumption and a square weighted average carbon potential corresponding to the variable line loss electricity;

[0010] Based on the fixed line loss electricity and the corresponding average carbon potential, the user electricity consumption and the corresponding weighted average carbon potential, and the variable line loss electricity and the corresponding square weighted average carbon potential, an estimated carbon footprint corresponding to the power supply is obtained.

[0011] According to a method for estimating the carbon footprint of a distribution network based on electricity data provided by the present invention, the typical day is divided into a photovoltaic output period and a non-photovoltaic output period. For the photovoltaic output period, a photovoltaic power supply area is determined on a photovoltaic-powered line;

[0012] The first-node carbon potential curve includes the first first-node carbon potential curve of the photovoltaic power supply area, the user power consumption includes the first user power consumption of the photovoltaic power supply area, the fixed line loss power includes the first fixed line loss power of the photovoltaic power supply area, and the variable line loss power includes the first variable line loss power of the photovoltaic power supply area;

[0013] The step of obtaining the average carbon potential corresponding to the fixed line loss electricity based on the first-node carbon potential curve includes:

[0014] Based on the first first-node carbon potential curve, obtaining a first average carbon potential corresponding to the first fixed line loss electricity;

[0015] The steps of respectively obtaining the weighted average carbon potential corresponding to the user's electricity consumption and the square weighted average carbon potential corresponding to the variable line loss electricity based on the first-node carbon potential curve and the load power curve include:

[0016] Based on the first first-node carbon potential curve and the load power curve, respectively obtaining a first weighted average carbon potential corresponding to the first user's electricity consumption and a first square weighted average carbon potential corresponding to the first variable line loss electricity;

[0017] The step of obtaining an estimated carbon footprint corresponding to the power supply based on the fixed line loss power and the corresponding average carbon potential, the user power consumption and the corresponding weighted average carbon potential, and the variable line loss power and the corresponding square weighted average carbon potential includes:

[0018] Based on the first fixed line loss electricity and the corresponding first average carbon potential, the first user electricity consumption and the corresponding first weighted average carbon potential, and the first variable line loss electricity and the corresponding first square weighted average carbon potential, an estimated carbon footprint corresponding to the photovoltaic power supply area is obtained.

[0019] According to a method for estimating the carbon footprint of a distribution network based on electricity data provided by the present invention, the step of determining the photovoltaic power supply area on a photovoltaic-powered line during a photovoltaic output period includes:

[0020] Get the average photovoltaic output during the photovoltaic output period;

[0021] During the photovoltaic output period, for any node on the distribution line, obtaining a first total load average power from the node to the last node, and a second total load average power from the node before the node to the last node;

[0022] When the photovoltaic average output is greater than or equal to the first total load average power and less than the second total load average power, it is determined that the current node to the end node is the photovoltaic power supply area.

[0023] According to a method for estimating the carbon footprint of a distribution network based on electricity data provided by the present invention, the step of obtaining the weighted average carbon potential corresponding to the user's electricity consumption based on the first-node carbon potential curve and the load power curve includes:

[0024] Normalizing the load power curve to obtain a normalized load power curve;

[0025] On the normalized load power curve and the first-node carbon potential curve, taking normalized load power values ​​and typical carbon potential values ​​at different times;

[0026] The weighted average carbon potential is obtained based on the normalized load power value and the typical carbon potential value.

[0027] According to a method for estimating the carbon footprint of a distribution network based on electricity data provided by the present invention, the step of obtaining the square-weighted average carbon potential corresponding to the variable line loss electricity based on the first-node carbon potential curve and the load power curve includes:

[0028] Performing a square operation on the load power curve and performing a normalization process to obtain a normalized load power square curve;

[0029] On the normalized load power square curve and the first node carbon potential curve, taking the normalized load power square value and the typical carbon potential value at different times;

[0030] The square weighted average carbon potential is obtained based on the normalized load power square value and the typical carbon potential value.

[0031] According to a method for estimating the carbon footprint of a distribution network based on electricity data provided by the present invention, the steps of obtaining an estimated carbon footprint corresponding to the power supply based on the fixed line loss electricity and the corresponding average carbon potential, the user electricity consumption and the corresponding weighted average carbon potential, and the variable line loss electricity and the corresponding square weighted average carbon potential include:

[0032] Multiplying the fixed line loss electricity by the corresponding average carbon potential to obtain a fixed line loss carbon footprint;

[0033] Multiplying the weighted average carbon potential corresponding to the user's electricity consumption to obtain the user's carbon footprint;

[0034] Multiplying the variable line loss electricity by the corresponding square weighted average carbon potential to obtain a variable line loss carbon footprint;

[0035] The fixed line loss carbon footprint, the user carbon footprint, and the variable line loss carbon footprint are added together to obtain the estimated carbon footprint value.

[0036] According to a method for estimating the carbon footprint of a distribution network based on electricity data provided by the present invention, the step of obtaining the average carbon potential corresponding to the fixed line loss electricity based on the first-node carbon potential curve includes:

[0037] The first-node carbon potential curve is sampled according to a preset sampling interval to obtain a plurality of carbon potential sampling values, and an average of the plurality of carbon potential sampling values ​​is taken to obtain the average carbon potential.

[0038] The present invention also provides a distribution network carbon footprint estimation device based on electricity data, comprising:

[0039] An acquisition module is used to obtain the power supply of the distribution network on a typical day, the first node carbon potential curve and the load power curve, wherein the power supply includes user power consumption, fixed line loss power and variable line loss power;

[0040] A first calculation module is configured to obtain an average carbon potential corresponding to the fixed line loss electricity based on the first-node carbon potential curve;

[0041] A second calculation module is configured to obtain, based on the first-node carbon potential curve and the load power curve, a weighted average carbon potential corresponding to the user's electricity consumption and a square weighted average carbon potential corresponding to the variable line loss electricity;

[0042] The third calculation module is used to obtain an estimated carbon footprint corresponding to the power supply based on the fixed line loss electricity and the corresponding average carbon potential, the user electricity consumption and the corresponding weighted average carbon potential, and the variable line loss electricity and the corresponding square weighted average carbon potential.

[0043] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for estimating the carbon footprint of a distribution network based on electricity data as described above is implemented.

[0044] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for estimating the carbon footprint of a distribution network based on electricity data as described above is implemented.

[0045] The present invention provides a distribution network carbon footprint estimation method based on electricity data and related equipment. First, the power supply of the distribution network is decomposed into user electricity consumption, fixed line loss electricity and variable line loss electricity. The characteristics of each part of electricity are analyzed from the perspective of carbon footprint analysis. According to the characteristics of each part of electricity, average carbon potential, weighted average carbon potential based on load curve and weighted average carbon potential calculation method based on load square are proposed, and then a basic estimation method of the distribution network carbon footprint based on weighted average carbon potential is obtained. This estimation method is suitable for distribution networks where real-time measurement data is difficult to obtain or incomplete, and can achieve accurate estimation of the distribution network carbon footprint. Since the cost of improving the measurement of the distribution network is high and problems such as incomplete measurement will exist for a long time, the present invention is feasible for carbon footprint estimation under the condition of incomplete measurement of the distribution network, and has guiding significance for the effect evaluation and forward direction of regional power carbon emission reduction work. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 One of the flow charts of a method for estimating the carbon footprint of a distribution network based on electricity data provided by an embodiment of the present invention;

[0048] Figure 2 A typical day photovoltaic output curve diagram provided by an embodiment of the present invention;

[0049] Figure 3 A graph showing the carbon potential of the first node on a typical day provided by an embodiment of the present invention;

[0050] Figure 4 A load power curve diagram for a typical day provided by an embodiment of the present invention;

[0051] Figure 5A network topology diagram of the IEEE-33 node distribution network used in Example 1 provided in an embodiment of the present invention;

[0052] Figure 6 A network topology diagram of the IEEE-33 node distribution network used in Example 2 provided in an embodiment of the present invention;

[0053] Figure 7 A schematic diagram of the structure of a distribution network carbon footprint estimation device based on electricity data provided by an embodiment of the present invention;

[0054] Figure 8 This is a schematic structural diagram of the electronic device provided by the present invention.

[0055] Reference numerals:

[0056] 21: Acquisition module; 22: First calculation module; 23: Second calculation module; 24: Third calculation module. DETAILED DESCRIPTION

[0057] In order to make the objectives, technical solutions, and advantages of the present invention more clear, the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0058] It should be noted that, it is explicitly and implicitly understood by those skilled in the art that the embodiments described in the present invention can be combined with other embodiments without conflict. Unless otherwise defined, the technical terms or scientific terms involved in the present invention should have the usual meanings understood by people with ordinary skills in the technical field to which the present invention belongs. The words "one", "a", "a", "the" and the like involved in the present invention do not indicate a quantity limitation and can represent the singular or plural. The terms "include", "comprise", "have" and any variations thereof involved in the present invention are intended to cover non-exclusive inclusions; the terms "first", "second", "third" and the like involved in the present invention are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0059] In order to distinguish it from the direct carbon emissions generated by carbon-based energy power generation, the present invention defines the indirect carbon emissions generated by electricity consumption and transmission as carbon footprint. The analysis and calculation of the carbon footprint of the distribution network has a certain research basis, mainly based on the calculation of carbon emission flow. The definition of the carbon emission flow of the power system is a virtual network flow formed by the carbon emissions that exist and are used to characterize the maintenance of any branch flow in the power system. The existing research on the carbon footprint of the distribution network is mainly based on the improvement of the carbon emission flow theory, and it is still necessary to calculate the flow of the network. The existing method is not suitable for distribution networks with incomplete measurements and difficult to perform multi-time section time series flow calculations. Therefore, the present invention proposes a distribution network carbon footprint estimation method based on electricity data for distribution networks with incomplete measurements.

[0060] This embodiment describes in detail the method for estimating the carbon footprint of a distribution network based on electricity data provided by the embodiment of the present invention in combination with the accompanying drawings and specific application scenarios.

[0061] Reference Figure 1 As shown, this embodiment provides a method for estimating the carbon footprint of a distribution network based on electricity data, including:

[0062] Step A1: Obtain the power supply, first-node carbon potential curve, and load power curve of the distribution network on a typical day, where the power supply includes user power consumption, fixed line loss power, and variable line loss power;

[0063] Step A2: Based on the first node carbon potential curve, obtain the average carbon potential corresponding to the fixed line loss electricity;

[0064] Step A3: Based on the first-node carbon potential curve and the load power curve, obtain the weighted average carbon potential corresponding to the user's electricity consumption and the square weighted average carbon potential corresponding to the variable line loss electricity;

[0065] Step A4: Based on the fixed line loss electricity and the corresponding average carbon potential, the user electricity consumption and the corresponding weighted average carbon potential, and the variable line loss electricity and the corresponding square weighted average carbon potential, obtain an estimated carbon footprint corresponding to the power supply.

[0066] It should be noted that steps A2 and A3 do not represent a sequential order.

[0067] Specifically, the traditional precise calculation method of carbon emission flow is not suitable for the actual analysis of the carbon footprint of the distribution network. In comparison, the various data of the first node of the distribution network, the output characteristics of distributed photovoltaics, and the user's electricity consumption data are easier to obtain. For the distribution network, the distribution network has the characteristics of open-loop operation, and the network structure is usually radial. During the period when photovoltaics are not producing power, the carbon potential of each node inside the distribution network is equal to the carbon potential of the first node, and the change pattern or law of the carbon potential of the first node is affected by the various power supply structures and output characteristics of the upper power grid; in the distribution network scenario, the distribution network is affected by photovoltaic output, and the current and carbon flow are more complicated. However, for the area where the distribution network is located, the lighting conditions are affected by local climate changes. In the long run, the photovoltaic output characteristics are quite stable. The present invention takes into account the characteristics of photovoltaic output and divides typical days into photovoltaic output periods and non-photovoltaic output periods.

[0068] During periods without PV output, the distribution network is equivalent to having no distributed generation (DGs). At the same moment, the carbon potential of each node in the distribution network is equal, and is affected only by the carbon potential of the first node. First, we estimate the basic scenario of periods without PV output.

[0069] The power supply of a distribution network can be decomposed into the sum of user electricity consumption and line losses. Line losses include fixed line losses and variable line losses. Fixed line losses refer to losses incurred by the equivalent parallel conductance of power lines and transformers. For distribution networks, these losses primarily include iron losses in power transformers, insulation losses in power cables, and capacitors. Variable line losses refer to losses incurred by the resistance of power lines and transformers. These losses are proportional to the square of the transmitted power or current. Both circuit losses can be calculated theoretically. For distribution networks, it is generally easy to obtain the power supply and user electricity consumption (i.e., the sum of the meter readings of users within the distribution network's supply range). Line losses are calculated by subtracting user electricity consumption from the power supply. Fixed line losses can be estimated based on the no-load condition of the lines. Variable line losses are calculated by subtracting fixed line losses from line losses. Based on the power supply of the distribution network on a typical day, the carbon potential curve of the first node, and the load power curve, the carbon footprint corresponding to each component of the power supply is estimated using the following carbon potentials.

[0070] In this embodiment, step A2 specifically includes:

[0071] The carbon potential curve of the first node is sampled according to a preset sampling interval to obtain a plurality of carbon potential sampling values, and an average of the plurality of carbon potential sampling values ​​is taken to obtain an average carbon potential.

[0072] Specifically, the preset sampling interval t is 1h (hour), and the carbon potential curve of the first node is sampled to obtain multiple carbon potential sampling values ​​e t , calculate multiple carbon potential sampling values ​​e tThe average value of the fixed line loss is used as the average carbon potential e avg , as shown in formula (1):

[0073]

[0074] Where, e avg With e t The unit is tCO2 / MWh.

[0075] In this embodiment, in step A3, the step of obtaining the weighted average carbon potential corresponding to the user's electricity consumption based on the first-node carbon potential curve and the load power curve includes:

[0076] Step A3B1: normalizing the load power curve to obtain a normalized load power curve;

[0077] Step A3B2: On the normalized load power curve and the first-node carbon potential curve, obtain the normalized load power value and the typical carbon potential value at different times;

[0078] Step A3B3: Obtain a weighted average carbon potential based on the normalized load power value and the typical carbon potential value.

[0079] Specifically, when the load power curve of the distribution network is known, the load power curve of a typical day is normalized, as shown in formula (2):

[0080]

[0081] Where, P t is the load power value at time t; P t nor is the load power value at time t after normalization; P max is the maximum load, in MW.

[0082] Based on the normalized load power curve and the first node carbon potential curve, the typical carbon potential value e per hour during the non-PV output period is taken. h and normalized load power value P t nor , and obtain the weighted average carbon potential corresponding to the user's electricity consumption The unit is tCO2 / MWh, as shown in formula (3):

[0083]

[0084] Where, is the normalized load power value at h; e h The typical carbon potential value is in h, and the unit is tCO2 / MWh.

[0085] In this embodiment, in step A3, the step of obtaining the square weighted average carbon potential corresponding to the variable line loss electricity based on the first node carbon potential curve and the load power curve includes:

[0086] Step A3C1: performing a square operation on the load power curve and performing normalization processing to obtain a normalized load power square curve;

[0087] Step A3C2: On the normalized load power square curve and the first node carbon potential curve, obtain the normalized load power square value and the typical carbon potential value at different times;

[0088] Step A3C3: Obtain the square weighted average carbon potential based on the normalized load power square value and the typical carbon potential value.

[0089] Specifically, the load power curve is squared and normalized to obtain a normalized load power square curve, as shown in formula (4):

[0090]

[0091] Where, P t squ is the square value of the load power at time t after normalization.

[0092] Based on the normalized load power square curve and the first node carbon potential curve, the typical carbon potential value e per hour during the non-PV output period is taken. h and normalized load power square value P t squ , and the weighted average carbon potential corresponding to the variable line loss electricity is obtained The unit is tCO2 / MWh, as shown in formula (5):

[0093]

[0094] Where, is the normalized square value of the load power at h.

[0095] In this embodiment, step A4 specifically includes:

[0096] Step A41: Multiply the fixed line loss electricity by the corresponding average carbon potential to obtain the fixed line loss carbon footprint;

[0097] Step A42: Multiply the user's electricity consumption by the corresponding weighted average carbon potential to obtain the user's carbon footprint;

[0098] Step A43: Multiply the variable line loss electricity by the corresponding square weighted average carbon potential to obtain the variable line loss carbon footprint;

[0099] Step A44: Add the fixed line loss carbon footprint, the user carbon footprint, and the variable line loss carbon footprint to obtain an estimated carbon footprint value.

[0100] It should be noted that steps A41-A43 do not represent a sequential order.

[0101] Specifically, in terms of carbon footprint analysis, user electricity consumption has a time series characteristic, that is, a typical daily load curve, so the carbon footprint estimation corresponding to user electricity consumption conforms to the characteristics of the weighted average carbon potential estimation method; fixed losses are not affected by load power and are continuous and stable loss electricity, so the average carbon potential can be used for estimation; variable losses are proportional to the square of the transmission power or current. In order to improve the estimation accuracy, the weighted average carbon potential based on the square of the load should be used to estimate the carbon footprint of variable losses.

[0102] Therefore, during the non-PV output period, the carbon footprint of the distribution network can be estimated according to the following equations (6)-(9):

[0103]

[0104]

[0105]

[0106]

[0107] In formulas (6)-(9), They are user carbon footprint, variable line loss carbon footprint and fixed line loss carbon footprint generated in period T, all in tCO2; They are user electricity consumption, variable line loss electricity and fixed line loss electricity in time period T, all in MWh.

[0108] Therefore, for non-photovoltaic output periods, the power supply of the distribution network is first decomposed into user power consumption, fixed line loss power and variable line loss power. The characteristics of each part of the power are analyzed from the perspective of carbon footprint analysis. According to the characteristics of each part of the power, the average carbon potential, the weighted average carbon potential based on the load power curve, and the weighted average carbon potential based on the square of the load power are proposed to calculate the basic estimation method of the distribution network carbon footprint based on the weighted average carbon potential.

[0109] During the photovoltaic output period, the photovoltaic power supply area is determined on the photovoltaic power supply line, including:

[0110] Get the average photovoltaic output during the photovoltaic output period;

[0111] During the photovoltaic output period, for any node on the distribution line, obtain the first total load average power from the node to the end node, and the second total load average power from the node before the node to the end node;

[0112] When the average photovoltaic output is greater than or equal to the first total load average power and less than the second total load average power, it is determined that the current node to the end node is a photovoltaic power supply area.

[0113] Specifically, for lines powered by photovoltaic power, it is necessary to consider the impact of the photovoltaic access location on line loss. The present invention approximately divides the photovoltaic access mode into two types: centralized distribution and uniform distribution.

[0114] For a distribution line, when distributed photovoltaics are concentrated, the carbon potential and carbon flow density of the nodes and lines after the access point are reduced by the influence of photovoltaics. The carbon potential corresponding to the load and line loss is similar. The actual carbon potential curve corresponding to the power consumption and line loss of this part of the user should be the weighted average of the carbon potential of the first node and the carbon emission intensity of distributed photovoltaics based on power. For ease of estimation, the conditions for determining the power supply area L corresponding to photovoltaic PV on a certain line are shown in Equation (10):

[0115]

[0116] In the formula, the end node number of this line is n, P avg,PV is the average PV output in MW. During the PV output period, the PV output is taken once every hour, and then the average value is taken to get P avg,PV .

[0117] During the photovoltaic power supply period T, for any node on this line, when the average photovoltaic output is less than the average power of the total load from node i-1 to node n on this line, and is greater than or equal to the average power of the total load from node i to node n, then nodes i to node n are considered to be the photovoltaic power supply area L. For ease of estimation, the distributed photovoltaic carbon emission intensity is regarded as 0, and the first node carbon potential curve and electricity data are used to perform the following transformation to obtain the first node carbon potential e of the photovoltaic power supply area L. t,L The expression:

[0118]

[0119] In the formula, during the T period of photovoltaic power supply, is the electricity consumption of users with access nodes n in the photovoltaic power supply area L, and They are the variable line loss electricity and fixed line loss electricity generated in the photovoltaic power supply area L, and the unit of electricity for each part is MWh.

[0120] Calculate the carbon footprint of the photovoltaic network during the photovoltaic output period T As shown in formula (12):

[0121]

[0122] Where, is the estimated carbon footprint of the area outside the photovoltaic power supply area L during the period T, is the estimated carbon footprint of the photovoltaic power supply area L during the period T, and the unit is tCO2.

[0123] In this embodiment, when the photovoltaic access mode is uniformly distributed, it can be approximately regarded as concentrated access at the midpoint of the line, and then the carbon footprint is estimated using the centralized distribution judgment method.

[0124] In this embodiment, the first-node carbon potential curve includes the first first-node carbon potential curve of the photovoltaic power supply area, the user power consumption includes the first user power consumption in the photovoltaic power supply area, the fixed line loss power includes the first fixed line loss power in the photovoltaic power supply area, and the variable line loss power includes the first variable line loss power in the photovoltaic power supply area;

[0125] Step A2 specifically includes:

[0126] Based on the first node carbon potential curve, a first average carbon potential corresponding to the first fixed line loss electricity is obtained;

[0127] Step A3 specifically includes:

[0128] Based on the first node carbon potential curve and the load power curve, respectively obtaining a first weighted average carbon potential corresponding to the first user's electricity consumption and a first square weighted average carbon potential corresponding to the first variable line loss electricity;

[0129] Step A4 specifically includes:

[0130] Based on the first fixed line loss electricity and the corresponding first average carbon potential, the first user electricity consumption and the corresponding first weighted average carbon potential, and the first variable line loss electricity and the corresponding first square weighted average carbon potential, an estimated carbon footprint corresponding to the photovoltaic power supply area is obtained.

[0131] Specifically, for areas outside the photovoltaic power supply area L, the carbon footprint The above basic estimation method for the distribution network carbon footprint during non-PV output periods is still used for estimation. For the PV power supply area L, the carbon potential of each node in the area is equal at the same time point. The average carbon potential or weighted average carbon potential corresponding to each part of the electricity is as follows:

[0132] In the photovoltaic power supply period T, the first node carbon potential curve of the photovoltaic power supply area L (i.e. the first node carbon potential e calculated by formula (11) in the photovoltaic power supply area L) is taken. t,L) is used as the average carbon potential corresponding to the first fixed line loss in the photovoltaic power supply area. avg,L , unit is tCO2 / MWh. e avg,L The expression of is shown in formula (13):

[0133]

[0134] Based on the normalized typical daily load power curve and the first node carbon potential curve of the photovoltaic power supply area, the first node carbon potential value e of the photovoltaic power supply area is taken every hour in the photovoltaic output period T. h,L , Normalized load power value Obtain the weighted average carbon potential corresponding to the first user's electricity consumption in the photovoltaic power supply area The unit is tCO2 / MWh. The expression of is shown in formula (14):

[0135]

[0136] Where, e h,L The unit is tCO2 / MWh.

[0137] Based on the normalized typical daily load power square curve and the first node carbon potential curve of the photovoltaic power supply area, the first node carbon potential value e of the photovoltaic power supply area is taken every hour in the photovoltaic output period T. h,L , normalized load power square value Obtain the square weighted average carbon potential corresponding to the first variable line loss in the photovoltaic power supply area The unit is tCO2 / MWh. The expression of is shown in formula (15):

[0138]

[0139] Therefore, the estimated carbon footprint corresponding to each part of the electricity in the photovoltaic power supply area is For example, according to the following formulas (16)-(19):

[0140]

[0141]

[0142]

[0143]

[0144] In formulas (16)-(19), They are the user carbon footprint, variable line loss carbon footprint and fixed line loss carbon footprint generated during the photovoltaic power supply period T, and the unit is tCO2.

[0145] Therefore, for the distributed photovoltaic output period, we first analyze the impact of the photovoltaic access method on the carbon potential of the distribution line. According to the carbon potential characteristics after photovoltaic access, the network is simplified by time period and region. The average carbon potential applicable to the photovoltaic power supply area during the photovoltaic output period, the weighted average carbon potential based on the load curve, and the weighted average carbon potential based on the square of the load are given. Finally, a method for estimating the carbon footprint of the distribution network during the distributed photovoltaic output period is obtained.

[0146] The present invention uses the IEEE-33 node distribution network as an example to analyze and verify the effectiveness of the method provided by this embodiment. Figure 2 The upper grid has photovoltaic access, and the first node carbon potential curve and load power curve of the system on a typical day are as follows. Figure 3 and Figure 4 As shown, the hourly data in the first-node carbon potential curve and load curve of a typical day are shown in Table 1. The typical daily power supply (including line loss) is 53.67MWh.

[0147] Table 1 Typical day 24 hours first node carbon potential value and load data

[0148]

[0149] To verify the effectiveness of this method and consider the reality of large-scale photovoltaic access, the following two examples are calculated:

[0150] Example 1: 13 nodes of the distribution network are connected to photovoltaic power plants with a capacity of 200kW, and nodes marked 27, 30, and 32 are connected to photovoltaic power plants with a capacity of 100kW respectively. The network topology of the distribution network is as follows: Figure 5 Based on the typical daily carbon potential curve and load curve, the power flow calculation and carbon flow calculation are performed every hour, and the exact value of the typical daily total carbon emissions is 41.43 tons.

[0151] In order to verify the carbon footprint estimation method proposed in this invention, according to the typical daily photovoltaic output curve, the photovoltaic output period is set to 8:00 to 16:00, and the non-photovoltaic output period is set to 17:00 to 7:00 the next morning. The 13 nodes are connected to the photovoltaic for centralized access, and the nodes marked as 27, 30, and 32 are connected to the photovoltaic for uniform access, which is simplified to centralized access at 30 nodes. According to the carbon potential curve of the first node, the load power curve and various power data of the typical day, based on formulas (1), (3), (5) and (13) to (15), the average carbon potential, weighted average carbon potential and square weighted average carbon potential of different regions in different time periods can be obtained as shown in Table 2:

[0152] Table 2 Average carbon potential and weighted average carbon potential in different regions at different times

[0153]

[0154] Based on the electricity consumption data of different regions at different time periods, we substituted them into formulas (6) to (9) and (16) to (19) to calculate the estimated carbon footprint. The results are shown in Table 3 (all units are tCO2):

[0155] Table 3 Estimated carbon footprint values ​​for different regions at different times

[0156]

[0157]

[0158] Comparing the estimated carbon footprint with the accurately calculated carbon footprint, the results are shown in Table 4:

[0159] Table 4 Comparison of estimated and accurate carbon footprint values

[0160]

[0161] From the data in the table, we can see that when using this method, the error between the estimated total carbon emissions and the precise calculated value is 1.75% during the period when photovoltaic power is not output. During the period when photovoltaic power is output, the carbon flow in the distribution network is more complicated, the estimation difficulty increases, and the estimation error increases to 7.21%. However, in general, the error of the total carbon footprint for the whole day is only 0.05%, which verifies the effectiveness of this method.

[0162] Example 2: Nodes marked as 4, 9, 12, 14, 20, 23, 24, 27, 30, and 32 are connected to photovoltaic power plants with a capacity of 100kW. The network topology of the distribution network is as follows: Figure 6 Based on the typical daily carbon potential curve and load curve, the power flow calculation and carbon flow calculation are performed every hour, and the exact value of the typical daily total carbon emissions is 39.16 tons.

[0163] In order to verify the effectiveness of the carbon footprint estimation method proposed in the present invention in the scenario of a large number of photovoltaic access, the photovoltaic output period is still set to 8:00 to 16:00, and the non-photovoltaic output period is from 17:00 to 7:00 the next morning. Considering the large number of photovoltaic access as a uniform access situation, the network topology is simplified, and the loads of the 2-node to 22-node branch, the 3-node to 25-node branch, and the 6-node to 33-node branch are equivalent to point loads connected to the nodes marked 2, 3, and 6, then the photovoltaic equivalent is concentrated at 6 nodes. According to the first-node carbon potential curve, load power curve, and various power data of a typical day, based on formulas (1), (3), (5), and (13) to (15), the average carbon potential, weighted average carbon potential, and square weighted average carbon potential of different regions in different time periods are obtained as shown in Table 5:

[0164] Table 5 Average carbon potential and weighted average carbon potential in different regions at different times

[0165]

[0166] Based on the electricity consumption data of different regions at different time periods, we substituted them into formulas (6) to (9) and (16) to (19) to calculate the estimated carbon footprint. The results are shown in Table 6 (all units are tCO2):

[0167] Table 6 Estimated carbon footprint values ​​for different regions at different times

[0168]

[0169] Comparing the estimated carbon footprint with the accurately calculated carbon footprint, the results are shown in Table 7:

[0170] Table 7 Comparison of estimated and accurate carbon footprint values

[0171]

[0172]

[0173] From the data in the table, we can see that when using this method, the error between the estimated total carbon emissions and the precise calculated value is 1.75% during the period when photovoltaic power is not in use. During the period when photovoltaic power is in use, the carbon flow in the distribution network is more complicated, the estimation difficulty increases, and the estimation error increases to 4.38%. However, in general, the error of the total carbon footprint for the whole day is only 0.005%, which verifies the effectiveness of this method in scenarios with a large number of photovoltaic connections.

[0174] In summary, this embodiment provides a method for estimating the carbon footprint of a distribution network based on electricity data. First, the power supply of the distribution network is decomposed into user electricity consumption, fixed line loss electricity and variable line loss electricity. The characteristics of each part of the electricity are analyzed from the perspective of carbon footprint analysis. According to the characteristics of each part of the electricity, the average carbon potential, the weighted average carbon potential based on the load curve and the weighted average carbon potential calculation method based on the load square are proposed, and then a basic method for estimating the carbon footprint of the distribution network based on the weighted average carbon potential is obtained. This estimation method is suitable for distribution networks where real-time measurement data is difficult to obtain or incomplete, and can achieve accurate estimation of the carbon footprint of the distribution network. Since the cost of improving the measurement of the distribution network is high and problems such as incomplete measurement will exist for a long time, the present invention is feasible for estimating the carbon footprint under the condition of incomplete measurement of the distribution network, and has guiding significance for the evaluation of the effect and direction of regional power carbon emission reduction work.

[0175] Based on the same inventive idea as the above method, Figure 7 As shown, this embodiment provides a distribution network carbon footprint estimation device based on electricity data, including:

[0176] An acquisition module 21 is configured to acquire the power supply, the first node carbon potential curve, and the load power curve of the distribution network on a typical day, wherein the power supply includes user power consumption, fixed line loss power, and variable line loss power;

[0177] The first calculation module 22 is used to obtain the average carbon potential corresponding to the fixed line loss electricity based on the first node carbon potential curve;

[0178] The first calculation module 22 is specifically configured to: sample the first node carbon potential curve according to a preset sampling interval to obtain a plurality of carbon potential sampling values, and average the plurality of carbon potential sampling values ​​to obtain an average carbon potential.

[0179] The second calculation module 23 is used to obtain the weighted average carbon potential corresponding to the user's power consumption and the square weighted average carbon potential corresponding to the variable line loss power based on the first node carbon potential curve and the load power curve;

[0180] The second calculation module 23 is specifically configured to: normalize the load power curve to obtain a normalized load power curve; obtain normalized load power values ​​and typical carbon potential values ​​at different times on the normalized load power curve and the first-node carbon potential curve; and obtain a weighted average carbon potential based on the normalized load power value and the typical carbon potential value.

[0181] The second calculation module 23 is further specifically used to: perform a square operation on the load power curve and obtain a normalized load power square curve after normalization; take the normalized load power square value and the typical carbon potential value at different times on the normalized load power square curve and the first-node carbon potential curve; and obtain the square weighted average carbon potential based on the normalized load power square value and the typical carbon potential value.

[0182] The third calculation module 24 is configured to obtain an estimated carbon footprint corresponding to the power supply based on the fixed line loss power and the corresponding average carbon potential, the user power consumption and the corresponding weighted average carbon potential, and the variable line loss power and the corresponding square weighted average carbon potential;

[0183] The third calculation module 24 is specifically used to: multiply the fixed line loss electricity by the corresponding average carbon potential to obtain the fixed line loss carbon footprint; multiply the user's electricity consumption by the corresponding weighted average carbon to obtain the user's carbon footprint; multiply the variable line loss electricity by the corresponding square weighted average carbon potential to obtain the variable line loss carbon footprint; add the fixed line loss carbon footprint, the user carbon footprint and the variable line loss carbon footprint to obtain an estimated carbon footprint value.

[0184] The third calculation module 24 is further specifically configured to: the first-node carbon potential curve includes a first-node carbon potential curve in the photovoltaic power supply area, the user power consumption includes a first user power consumption in the photovoltaic power supply area, the fixed line loss power includes a first fixed line loss power in the photovoltaic power supply area, and the variable line loss power includes a first variable line loss power in the photovoltaic power supply area;

[0185] Based on the first node carbon potential curve, a first average carbon potential corresponding to the first fixed line loss electricity is obtained;

[0186] Based on the first node carbon potential curve and the load power curve, respectively obtaining a first weighted average carbon potential corresponding to the first user's electricity consumption and a first square weighted average carbon potential corresponding to the first variable line loss electricity;

[0187] Based on the first fixed line loss electricity and the corresponding first average carbon potential, the first user electricity consumption and the corresponding first weighted average carbon potential, and the first variable line loss electricity and the corresponding first square weighted average carbon potential, an estimated carbon footprint corresponding to the photovoltaic power supply area is obtained.

[0188] It should be noted that the distribution network carbon footprint estimation method based on electricity data provided by the method embodiment of the present invention can be executed by a distribution network carbon footprint estimation device based on electricity data, or by a control module in the distribution network carbon footprint estimation device based on electricity data for executing the distribution network carbon footprint estimation method based on electricity data.

[0189] The implementation process of the functions and effects of each module in the above-mentioned device is specifically detailed in the implementation process of the corresponding steps in the above-mentioned method, so the relevant parts can be referred to the partial description of the method embodiment, which will not be repeated here.

[0190] The device embodiments described above are merely illustrative. For example, the division of the modules is merely a logical function division, and there may be other division methods in actual implementation. The functional modules in the embodiments may all be integrated into one processor, or each module may be a separate device, or two or more modules may be integrated into one device; the functional modules in each embodiment may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0191] Example 3

[0192] Reference Figure 8As shown, this embodiment provides an electronic device, which includes: a processor (processor) 310, a communication interface (Communications Interface) 320, a memory (memory) 330 and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call the logic instructions in the memory 330, and the processor 310 executes the distribution network carbon footprint estimation method based on electricity data provided by the above method embodiment, which includes:

[0193] Obtain the power supply, first-node carbon potential curve, and load power curve of the distribution network on a typical day. The power supply includes user power consumption, fixed line loss power, and variable line loss power.

[0194] Based on the first node carbon potential curve, the average carbon potential corresponding to the fixed line loss electricity is obtained;

[0195] Based on the first node carbon potential curve and load power curve, the weighted average carbon potential corresponding to the user's electricity consumption and the square weighted average carbon potential corresponding to the variable line loss electricity are obtained respectively;

[0196] Based on the fixed line loss electricity and the corresponding average carbon potential, the user electricity consumption and the corresponding weighted average carbon potential, and the variable line loss electricity and the corresponding square weighted average carbon potential, the estimated carbon footprint corresponding to the power supply is obtained.

[0197] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0198] On the other hand, the present invention further provides a computer program product, comprising a computer program, which may be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the method for estimating the carbon footprint of a distribution network based on electricity data provided in the above method embodiment, the method comprising:

[0199] Obtain the power supply, first-node carbon potential curve, and load power curve of the distribution network on a typical day. The power supply includes user power consumption, fixed line loss power, and variable line loss power.

[0200] Based on the first node carbon potential curve, the average carbon potential corresponding to the fixed line loss electricity is obtained;

[0201] Based on the first node carbon potential curve and load power curve, the weighted average carbon potential corresponding to the user's electricity consumption and the square weighted average carbon potential corresponding to the variable line loss electricity are obtained respectively;

[0202] Based on the fixed line loss electricity and the corresponding average carbon potential, the user electricity consumption and the corresponding weighted average carbon potential, and the variable line loss electricity and the corresponding square weighted average carbon potential, the estimated carbon footprint corresponding to the power supply is obtained.

[0203] Example 4

[0204] This embodiment provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for estimating the carbon footprint of a distribution network based on electricity data provided in the above method embodiment is implemented. The method includes:

[0205] Obtain the power supply, first-node carbon potential curve, and load power curve of the distribution network on a typical day. The power supply includes user power consumption, fixed line loss power, and variable line loss power.

[0206] Based on the first node carbon potential curve, the average carbon potential corresponding to the fixed line loss electricity is obtained;

[0207] Based on the first node carbon potential curve and load power curve, the weighted average carbon potential corresponding to the user's electricity consumption and the square weighted average carbon potential corresponding to the variable line loss electricity are obtained respectively;

[0208] Based on the fixed line loss electricity and the corresponding average carbon potential, the user electricity consumption and the corresponding weighted average carbon potential, and the variable line loss electricity and the corresponding square weighted average carbon potential, the estimated carbon footprint corresponding to the power supply is obtained.

[0209] The various embodiments of the present invention are described in a progressive manner. Similar portions between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device and medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant portions, refer to the descriptions of the method embodiments.

[0210] The devices and media provided in the embodiments of the present invention correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0211] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, commodity, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, commodity, or method comprising the element.

[0212] The foregoing is merely an embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail above using general descriptions and specific embodiments, it will be apparent to those skilled in the art that modifications or improvements may be made based on the present invention. Therefore, such modifications or improvements made without departing from the spirit of the present invention are intended to fall within the scope of protection claimed in the present invention.

Claims

1. A method for estimating the carbon footprint of a distribution network based on electricity data, characterized in that: include: Obtain the power supply, first-node carbon potential curve, and load power curve of the distribution network on a typical day, wherein the power supply includes user power consumption, fixed line loss power, and variable line loss power; Based on the first-node carbon potential curve, obtaining an average carbon potential corresponding to the fixed line loss electricity; Based on the first node carbon potential curve and the load power curve, respectively obtaining a weighted average carbon potential corresponding to the user's electricity consumption and a square weighted average carbon potential corresponding to the variable line loss electricity; Obtaining an estimated carbon footprint corresponding to the power supply based on the fixed line loss power and the corresponding average carbon potential, the user power consumption and the corresponding weighted average carbon potential, and the variable line loss power and the corresponding square weighted average carbon potential, the steps include: Multiplying the fixed line loss electricity by the corresponding average carbon potential to obtain a fixed line loss carbon footprint; Multiplying the user's electricity consumption by the corresponding weighted average carbon potential to obtain the user's carbon footprint; Multiplying the variable line loss electricity by the corresponding square weighted average carbon potential to obtain a variable line loss carbon footprint; The fixed line loss carbon footprint, the user carbon footprint, and the variable line loss carbon footprint are added together to obtain the estimated carbon footprint value.

2. The method for estimating the carbon footprint of a distribution network based on electricity data according to claim 1, characterized in that: The typical day is divided into a photovoltaic output period and a non-photovoltaic output period. For the photovoltaic output period, a photovoltaic power supply area is determined on the photovoltaic-powered line; The first-node carbon potential curve includes the first first-node carbon potential curve of the photovoltaic power supply area, the user power consumption includes the first user power consumption of the photovoltaic power supply area, the fixed line loss power includes the first fixed line loss power of the photovoltaic power supply area, and the variable line loss power includes the first variable line loss power of the photovoltaic power supply area; The step of obtaining the average carbon potential corresponding to the fixed line loss electricity based on the first-node carbon potential curve includes: Based on the first first-node carbon potential curve, obtaining a first average carbon potential corresponding to the first fixed line loss electricity; The steps of respectively obtaining the weighted average carbon potential corresponding to the user's electricity consumption and the square weighted average carbon potential corresponding to the variable line loss electricity based on the first-node carbon potential curve and the load power curve include: Based on the first first-node carbon potential curve and the load power curve, respectively obtaining a first weighted average carbon potential corresponding to the first user's electricity consumption and a first square weighted average carbon potential corresponding to the first variable line loss electricity; The step of obtaining an estimated carbon footprint corresponding to the power supply based on the fixed line loss power and the corresponding average carbon potential, the user power consumption and the corresponding weighted average carbon potential, and the variable line loss power and the corresponding square weighted average carbon potential includes: Based on the first fixed line loss electricity and the corresponding first average carbon potential, the first user electricity consumption and the corresponding first weighted average carbon potential, and the first variable line loss electricity and the corresponding first square weighted average carbon potential, an estimated carbon footprint corresponding to the photovoltaic power supply area is obtained.

3. The method for estimating the carbon footprint of a distribution network based on electricity data according to claim 2, characterized in that: The step of determining the photovoltaic power supply area on the photovoltaic power supply line during the photovoltaic power output period includes: Get the average photovoltaic output during the photovoltaic output period; During the photovoltaic output period, for any node on the distribution line, obtaining a first total load average power from the node to the last node, and a second total load average power from the node before the node to the last node; When the photovoltaic average output is greater than or equal to the first total load average power and less than the second total load average power, it is determined that the current node to the end node is the photovoltaic power supply area.

4. The method for estimating the carbon footprint of a distribution network based on electricity data according to claim 1, characterized in that: The step of obtaining a weighted average carbon potential corresponding to the user's electricity consumption based on the first-node carbon potential curve and the load power curve includes: Normalizing the load power curve to obtain a normalized load power curve; On the normalized load power curve and the first-node carbon potential curve, taking normalized load power values ​​and typical carbon potential values ​​at different times; The weighted average carbon potential is obtained based on the normalized load power value and the typical carbon potential value.

5. The method for estimating the carbon footprint of a distribution network based on electricity data according to claim 1, characterized in that: The step of obtaining the square weighted average carbon potential corresponding to the variable line loss electricity based on the first node carbon potential curve and the load power curve includes: Performing a square operation on the load power curve and performing a normalization process to obtain a normalized load power square curve; On the normalized load power square curve and the first node carbon potential curve, taking the normalized load power square value and the typical carbon potential value at different times; The square weighted average carbon potential is obtained based on the normalized load power square value and the typical carbon potential value.

6. The method for estimating the carbon footprint of a distribution network based on electricity data according to claim 1, characterized in that: The step of obtaining the average carbon potential corresponding to the fixed line loss electricity based on the first-node carbon potential curve includes: The first-node carbon potential curve is sampled according to a preset sampling interval to obtain a plurality of carbon potential sampling values, and an average of the plurality of carbon potential sampling values ​​is taken to obtain the average carbon potential.

7. A distribution network carbon footprint estimation device based on electricity data, characterized in that: include: An acquisition module is used to obtain the power supply of the distribution network on a typical day, the first node carbon potential curve and the load power curve, wherein the power supply includes user power consumption, fixed line loss power and variable line loss power; A first calculation module is configured to obtain an average carbon potential corresponding to the fixed line loss electricity based on the first-node carbon potential curve; A second calculation module is configured to obtain, based on the first-node carbon potential curve and the load power curve, a weighted average carbon potential corresponding to the user's electricity consumption and a square weighted average carbon potential corresponding to the variable line loss electricity; A third calculation module is configured to obtain an estimated carbon footprint corresponding to the power supply based on the fixed line loss power and the corresponding average carbon potential, the user power consumption and the corresponding weighted average carbon potential, and the variable line loss power and the corresponding square weighted average carbon potential. The third calculation module is specifically configured to: Multiplying the fixed line loss electricity by the corresponding average carbon potential to obtain a fixed line loss carbon footprint; Multiplying the user's electricity consumption by the corresponding weighted average carbon potential to obtain the user's carbon footprint; Multiplying the variable line loss electricity by the corresponding square weighted average carbon potential to obtain a variable line loss carbon footprint; The fixed line loss carbon footprint, the user carbon footprint, and the variable line loss carbon footprint are added together to obtain the estimated carbon footprint value.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for estimating the carbon footprint of a distribution network based on electricity data according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for estimating the carbon footprint of a distribution network based on electricity data according to any one of claims 1 to 6 is implemented.

Images