Power distribution network carbon footprint estimation method based on electric quantity data and related equipment

Abstract

The invention provides a power distribution network carbon footprint estimation method based on electric quantity data and related equipment, and the method comprises the steps: obtaining the power supply quantity, a head node carbon potential curve and a load power curve of a typical day of a power distribution network, and enabling the power supply quantity to comprise the power consumption of a user, the fixed line loss electric quantity and the variable line loss electric quantity; based on the head node carbon potential curve, obtaining an average carbon potential corresponding to the fixed line loss electric quantity; based on the head node carbon potential curve and the load power curve, respectively obtaining a weighted average carbon potential corresponding to the electricity consumption of the user and a square weighted average carbon potential corresponding to the variable line loss electricity quantity; and based on the average carbon potential and the corresponding fixed line loss electric quantity, the weighted average carbon potential and the corresponding user electricity consumption, and the square weighted average carbon potential and the corresponding variable line loss electric quantity, obtaining a carbon footprint estimation value corresponding to the power supply quantity. The method is suitable for the power distribution network of which the real-time measurement data is difficult to obtain or incomplete to obtain, and the accurate estimation of the carbon footprint of the power distribution network can be realized.

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 the foundation for maintaining a peaceful and stable social development. With the strategic goals of "carbon neutrality" and "carbon peak", clean and low-carbon has become the core goal of the new power system. In order to evaluate the effectiveness of regional low-carbon emission reduction work, the carbon footprint analysis of the distribution network is urgent.

[0003] However, accurate carbon footprint analysis of distribution networks is still difficult at this stage. On the one hand, medium and low voltage distribution networks have long had problems such as incomplete measurements and low data quality, making it difficult to obtain accurate and comprehensive network status; on the other hand, with the access of low-carbon power sources such as photovoltaics and wind turbines, the temporal and spatial distribution of the carbon footprint of the distribution network has become more complex, bringing new challenges to carbon footprint analysis, making traditional methods of accurate calculation of carbon emission flows unsuitable for actual analysis of the carbon footprint of distribution networks.

[0004] Existing research on the carbon footprint of distribution networks is mainly based on the improvement of carbon emission flow theory, and still requires power flow calculation of the network. Existing methods are not suitable for distribution networks with incomplete measurements and difficult to perform multi-time section time series power flow calculation. Therefore, the present invention proposes a distribution network carbon footprint estimation method based on electricity data for distribution networks with incomplete measurements. Summary of the invention

[0005] The present invention provides a distribution network carbon footprint estimation method based on electricity data and related equipment. The estimation method is applicable to 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 distribution network measurement is high and problems such as incomplete measurement will exist for a long time, the present invention is feasible to estimate the carbon footprint under the condition of incomplete distribution network measurement, and has guiding significance for the effect evaluation and direction of regional power carbon emission reduction work.

[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 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;

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

[0009] Based on the first node carbon potential curve and the load power curve, respectively obtaining 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;

[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 comprises:

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

[0015] The steps of respectively obtaining 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 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 power consumption and a first square weighted average carbon potential corresponding to the first variable line loss power;

[0017] The step of obtaining a carbon footprint estimation value 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 comprises:

[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 the photovoltaic-powered line during the photovoltaic output period includes:

[0020] Obtain 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 distribution network carbon footprint estimation method based on electricity data provided by the present invention, the steps of obtaining a carbon footprint estimation value 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 carbon footprint estimation 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 acquire 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 used 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 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 respectively based on the first node carbon potential curve and the load power curve;

[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, wherein when the processor executes the program, a 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 in any one of the 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 the electricity are analyzed from the perspective of carbon footprint analysis. According to the characteristics of each part of the 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 distribution network carbon footprint estimation method 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 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 carbon footprint estimation under the condition of incomplete measurement of the distribution network, and has guiding significance for the effect evaluation and 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

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

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

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

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

[0051] Figure 5A network topology diagram of an 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 an 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 an 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 purpose, technical scheme and advantages of the present invention clearer, the present invention will be described clearly and completely in combination with the specific embodiments and drawings of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] It should be noted that it is explicitly and implicitly understood by those of ordinary skill 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 be 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 quantitative limitation and may represent the singular or plural. The terms "including", "comprising", "having" and any of their variations involved in the present invention are intended to cover non-exclusive inclusions; the terms "first", "second", "third", etc. involved in the present invention are merely to distinguish similar objects and do not represent a specific ordering of 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 flows. The definition of the carbon emission flow of the power system is a virtual network flow formed by the carbon emissions that exist depending on the power flow and are used to characterize the carbon emissions that maintain the flow of any branch 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, in combination with the accompanying drawings and in combination with specific application scenarios, describes in detail the method for estimating the carbon footprint of a distribution network based on electricity data provided by an embodiment of the present invention.

[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 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;

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

[0064] Step A3: Based on the first node carbon potential curve and the 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;

[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, the carbon potential of each node in 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 the 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 have considerable stability. 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] For non-PV output periods, it is equivalent to the distribution network not containing distributed power sources. At the same time, the carbon potential of each node in the distribution network is equal and is only affected by the carbon potential of the first node. First, the basic scenario of non-PV output periods is estimated.

[0069] The power supply of the distribution network is decomposed into the sum of user power consumption and line loss. Line loss includes fixed line loss and variable line loss. Fixed line loss refers to the loss generated on the equivalent parallel conductance of the power line and transformer. For the distribution network, it mainly includes the iron loss of the power transformer, the insulation dielectric loss of the power cable and the capacitor, etc.; variable line loss refers to the power consumed on the resistance of the power line and the power transformer. This part of the loss is proportional to the square of the transmission power or current. Both circuit losses can be calculated according to theory. For the distribution network, it is generally easier to obtain the power supply and user power consumption of the distribution network (that is, the sum of the meter readings of the user meters within the power supply range of the distribution network). The line loss is obtained by subtracting the user power consumption from the power supply, and the fixed line loss can be estimated according to the no-load condition of the line. The variable line loss is obtained by subtracting the fixed line loss from the line loss. 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 estimation corresponding to each part of the power supply is defined as the following carbon potentials.

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

[0071] The first node carbon potential curve is sampled according to a preset sampling interval to obtain a plurality of carbon potential sampling values, and the 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 first node carbon potential curve 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 taken as the average carbon potential e corresponding to the fixed line loss avg , as shown in formula (1):

[0073]

[0074] In the formula, 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, take the normalized load power value and the typical carbon potential value at different times;

[0078] Step A3B3: Based on the normalized load power value and the typical carbon potential value, a weighted average carbon potential is obtained.

[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 the normalized load power value P t nor , and the weighted average carbon potential corresponding to the user's electricity consumption is obtained The unit is tCO2 / MWh, as shown in formula (3):

[0083]

[0084] In the formula, is the normalized load power value at h; e h is the typical carbon potential value at h, in units of 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, take the normalized load power square value and the typical carbon potential value at different times;

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

[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 is obtained The unit is tCO2 / MWh, as shown in formula (5):

[0093]

[0094] In the formula, is the normalized square value of load power at time 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 for continuous and stable loss of electricity, 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 estimated 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 the user carbon footprint, variable line loss carbon footprint and fixed line loss carbon footprint generated in the T period, all in tCO2; They are user electricity consumption, variable line loss electricity and fixed line loss electricity in time period T, and the unit is 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 carbon footprint of the distribution network 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] Obtain 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 last node, and the second total load average power from the previous node to the last 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 photovoltaic access position on line loss. The present invention approximately divides photovoltaic access modes into two types: concentrated distribution and uniform distribution.

[0114] For a distribution line, when distributed photovoltaics are concentrated, the node 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 users 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 the convenience of estimation, the conditions for determining the power supply area L corresponding to photovoltaic PV on a certain line are shown in formula (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 T period of photovoltaic power supply, 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 of this line, and is greater than or equal to the average power of the total load from node i to node n, it is considered that node i to node n is the power supply area L of the photovoltaic power source PV. For the convenience of estimation, the carbon emission intensity of distributed photovoltaic 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 is:

[0118]

[0119] In the formula, during the T period of photovoltaic power supply, is the power 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] In the formula, is the estimated carbon footprint of the area outside the photovoltaic power supply area L during the period T, It 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 concentrated 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 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;

[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 quantity is obtained;

[0127] Step A3 specifically includes:

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

[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 of the carbon footprint of the distribution network during the non-PV output period is still used for estimation; for the PV power supply area L, the carbon potential of each node in the area at the same time point is equal, and 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 of the photovoltaic power supply area L calculated by formula (11)) is taken. t,L) is taken as the average carbon potential corresponding to the first fixed line loss in the photovoltaic power supply area. avg,L , unit is tCO2 / MWh. 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 The weighted average carbon potential corresponding to the electricity consumption of the first user in the photovoltaic power supply area is obtained The unit is tCO2 / MWh. The expression of is shown in formula (14):

[0135]

[0136] In the formula, 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 The square weighted average carbon potential corresponding to the first variable line loss in the photovoltaic power supply area is obtained 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, and 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, the carbon footprint estimation method of the distribution network during the distributed photovoltaic output period is obtained.

[0146] The present invention takes the IEEE-33 node distribution network as an example for analysis to 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, load data

[0148]

[0149] In order 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 According to the typical daily carbon potential curve and load curve, the 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 the present invention, according to the typical daily photovoltaic output curve, the photovoltaic output period is set to 8:00 to 16:00, and 17:00 to 7:00 the next morning is the non-photovoltaic output period. 13 nodes are connected to photovoltaics for centralized access, and the nodes marked as 27, 30, and 32 are connected to photovoltaics for uniform access, which is simplified to centralized access at 30 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 in different regions at 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 data of different regions at different time periods, we substituted them into formulas (6) to (9) and (16) to (19) to calculate the estimated value of 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, during the period when photovoltaic power is not in use, the error between the estimated total carbon emissions and the precise calculated value is 1.75%. 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 7.21%. However, in general, the total carbon footprint error for the whole day is only 0.05%, which verifies the effectiveness of this method.

[0162] Example 2: Each node marked as 4, 9, 12, 14, 20, 23, 24, 27, 30 and 32 is connected to a photovoltaic power plant with a capacity of 100 kW. The network topology of the distribution network is as follows: Figure 6 According to the typical day carbon potential curve and load curve, the flow calculation and carbon flow calculation are performed every hour, and the exact value of the typical day 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 large-scale 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-scale photovoltaic access as uniform access, simplifying the network topology, 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 the 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 in different regions at 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 data of different regions at different time periods, we substituted them into formulas (6) to (9) and (16) to (19) to calculate the estimated value of 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, during the period when photovoltaic power is not in use, the error between the estimated total carbon emissions and the precise calculated value is 1.75%. 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 total carbon footprint error 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, the present 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, an average carbon potential, a weighted average carbon potential based on a load curve and a weighted average carbon potential calculation method based on the square of the load are proposed, and then a basic estimation method for 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 carbon footprint estimation under the condition of incomplete measurement of the distribution network, and has guiding significance for the effect evaluation 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] The acquisition module 21 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;

[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 used for: sampling the first node carbon potential curve according to a preset sampling interval time to obtain a plurality of carbon potential sampling values, and averaging 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 used for: normalizing the load power curve to obtain a normalized load power curve; taking the normalized load power value and the typical carbon potential value at different times on the normalized load power curve and the first node carbon potential curve; and obtaining the weighted average carbon potential based on the normalized load power value and the typical carbon potential value;

[0181] The second calculation module 23 is also specifically used for: performing a square operation on the load power curve and obtaining a normalized load power square curve after normalization; taking 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 obtaining 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 used 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 for: multiplying the fixed line loss electricity with the corresponding average carbon potential to obtain the fixed line loss carbon footprint; multiplying the user's electricity consumption with the corresponding weighted average carbon to obtain the user's carbon footprint; multiplying the variable line loss electricity with the corresponding square weighted average carbon potential to obtain the variable line loss carbon footprint; adding the fixed line loss carbon footprint, the user carbon footprint and the variable line loss carbon footprint to obtain the carbon footprint estimate.

[0184] The third calculation module 24 is also specifically used for: 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;

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

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

[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 method for estimating the carbon footprint of a distribution network based on electricity data provided by the method embodiment of the present invention may 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 method for estimating the carbon footprint of a distribution network 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. 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 the embodiments may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0191] Embodiment 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 through 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 the power data provided by the above method embodiment, and the method includes:

[0193] 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;

[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 it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, 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, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a 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: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0198] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute the distribution network carbon footprint estimation method based on electricity data provided by 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, where 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] Embodiment 4

[0204] This embodiment provides a non-transitory computer-readable storage medium, on which a computer program is stored. 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, where 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, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0210] The devices and media provided in the embodiments of the present invention correspond one-to-one to the methods, and therefore, the devices and media also have similar beneficial technical effects as the 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 "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or method. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or method including the elements.

[0212] The above are only embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail above with general descriptions and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made on the basis of the present invention. Therefore, these modifications or improvements made on the basis of not departing from the spirit of the present invention all belong to 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 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; Based on the first-node carbon potential curve, an average carbon potential corresponding to the fixed line loss electricity is obtained; Based on the first node carbon potential curve and the load power curve, respectively obtaining 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 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.

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 comprises: Based on the first first node carbon potential curve, obtaining a first average carbon potential corresponding to the first fixed line loss quantity; The steps of respectively obtaining 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 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 power consumption and a first square weighted average carbon potential corresponding to the first variable line loss power; The step of obtaining a carbon footprint estimation value 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 comprises: 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 is 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: Obtain 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 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 comprises: 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 quantity based on the first node carbon potential curve and the load power curve comprises: 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 a carbon footprint estimation value 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 comprises: 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 carbon footprint estimation value.

7. 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 comprises: 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.

8. A distribution network carbon footprint estimation device based on electricity data, characterized in that: include: An acquisition module is used to acquire 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 used 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 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 respectively based on the first node carbon potential curve and the load power curve; 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.

9. 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 7 is implemented.

10. 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 7 is implemented.

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