Carbon flow path tracking method and device

Abstract

The invention discloses a carbon flow path tracking method and device. The power network diagram is constructed through the real-time power data, then the carbon emission factor and the carbon flow path of each node are calculated, then the carbon emission of each node is determined, the weight of each transmission path is evaluated according to the carbon emission, and finally the line with the maximum carbon emission in the preset monitoring time period is found out. Therefore, the emission reduction strategy is implemented more effectively, the power resource configuration is optimized more effectively, and the problem that the carbon flow path cannot be tracked accurately in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the field of carbon flow path tracing, and in particular to a carbon flow path tracing method and device. Background Art

[0002] With the global concern about climate change, low-carbon economic development has become a goal pursued by all countries. As one of the main sources of carbon emissions, the carbon flow path tracking of the power industry is of great significance for achieving carbon emission reduction. However, the existing carbon flow path tracking methods often cannot accurately reflect the flow and quantification of carbon emissions in regional integrated energy systems, which highlights the importance of carbon flow path analysis and processing.

[0003] There are still some areas in the current carbon flow path analysis that need to be optimized, which are specifically reflected in the following aspects: the carbon flow path analysis data may be inaccurate due to interference from other factors. The current carbon flow path analysis still has certain drawbacks. It is impossible to effectively and timely observe changes in the carbon flow path weights, and it is impossible to effectively ensure the comprehensiveness of the carbon flow path analysis. It is impossible to effectively guarantee the scientificity and reliability of the carbon flow path analysis, and it is impossible to provide accurate data for the follow-up, and it is impossible to improve the accuracy of the carbon flow path analysis. At the same time, it is also not conducive to improving the analysis efficiency and intelligence level of the carbon flow path analysis to a certain extent, resulting in the inability of existing technologies to accurately track the carbon flow path. Summary of the invention

[0004] The present invention provides a carbon flow path tracking method and device to solve the problem that the prior art cannot accurately track the carbon flow path.

[0005] In a first aspect, the present application provides a carbon flow path tracing method, comprising:

[0006] Get real-time power data;

[0007] Constructing a target power network diagram according to the real-time power data and each power consumption unit node;

[0008] According to the target power network diagram, various carbon emission factors of each power consumption unit node within a preset monitoring time period and various transmission paths of carbon flow within the preset monitoring time period are calculated;

[0009] Calculate the carbon emissions of each power consumption unit node within a preset monitoring time period according to the carbon emission factors and the target power network diagram;

[0010] Calculating and obtaining weights of the transmission paths according to the carbon emissions;

[0011] According to the weights, the line with the largest carbon emission among the carbon emission in the target power network diagram within the preset monitoring time period is calculated.

[0012] This application can accurately map the energy flow relationship between power consumption units by acquiring real-time power data and constructing a target power network diagram. Using these data, the present application can calculate the carbon emission factor of each power consumption unit node during a specific monitoring period, thereby revealing the transmission path of the carbon flow. This mapping and calculation not only enhances the understanding of the distribution of carbon emissions in the power system, but also by quantifying the carbon emissions of each node, it is possible to evaluate the carbon emission contributions of different power flows. Furthermore, by analyzing the carbon emissions of each transmission path, the present application can determine the lines with the highest carbon emissions in the power network. This allows for more effective implementation of emission reduction strategies and optimization of power resource allocation to solve the problem that existing technologies cannot accurately track carbon flow paths.

[0013] As a preferred embodiment of the first aspect, the real-time power data is specifically:

[0014] The real-time power data includes each fuel consumption and each power generation of each power station of each power consumption unit node within a preset monitoring time period.

[0015] In this preferred embodiment, the present application can construct an accurate power network diagram by recording in detail the fuel consumption and power generation of each power consumption unit in a specific period of time, and then analyze the carbon emission factor of each node. This analysis makes it possible to calculate the carbon emissions of each node in the entire network and evaluate the carbon emission weights of different power transmission paths. Ultimately, the present application is able to identify the lines with the largest carbon emissions. The present application provides a clear framework to identify and quantify carbon emission hotspots in the power system, so that power operators and policymakers can implement emission reduction measures in a targeted manner, optimize energy distribution, improve the energy efficiency of the system, and promote the green transformation of the entire power industry.

[0016] As a preferred embodiment of the first aspect, the calculation obtains each carbon emission factor of each power consumption unit node within a preset monitoring time period, specifically:

[0017] According to the power generation of each power station of each power consumption unit node within the preset monitoring time period, the power generation proportion of each power station of each power consumption unit node within the preset monitoring time period is calculated;

[0018] According to the first formula and the proportion of each power generation, each carbon emission factor of each power consumption unit node within a preset monitoring time period is calculated;

[0019] Among them, the first formula is

[0020] Where η r represents the carbon emission coefficient of the rth node in the target power network diagram within the set monitoring time period, Represents various carbon emission factors within the preset monitoring time period.

[0021] In this preferred embodiment, the present application first calculates the proportion of each power station in the total power generation by analyzing the power generation of each power consumption unit node within a preset monitoring time period. This step is fundamental because it will show which power stations play a greater role in power production. Then, using a specific calculation formula (the first formula), combined with these power generation proportions, the carbon emission factor of each power consumption unit node can be determined. This formula usually takes into account the carbon emission coefficient in the power generation process, which reflects the carbon emissions generated per unit of electrical energy in the power generation process. The present application provides an accurate way to evaluate the carbon emission responsibility of each node in the power network. By understanding the carbon emission factor of each node, the carbon footprint of the power grid can be more effectively monitored and managed, the areas with the greatest emission reduction potential can be identified, and more precise strategies can be formulated to achieve emission reduction goals.

[0022] As a preferred embodiment of the first aspect, the calculation of each carbon emission amount of each power consumption unit node within a preset monitoring time period is specifically:

[0023] Obtaining each power consumption unit node's received power and total power consumption of each power station within a preset monitoring time period;

[0024] According to the received power amounts and the total consumed power amount, the average power value of each power consumption unit node within a preset monitoring time period is calculated;

[0025] According to the second formula, the carbon emissions of each power consumption unit node within a preset monitoring time period are calculated;

[0026] Among them, the second formula is

[0027] In the formula, T represents the duration of the preset monitoring period. Represents the average electric power of the rth power consumption unit node within the preset monitoring time period.

[0028] In this preferred embodiment, the present application can calculate the average power of these nodes by accurately obtaining the amount of power received by each power consumption unit node from each power station and its total power consumption during a specific monitoring period. Using these data, combined with the preset time period length, according to the second formula, the carbon emissions of each node during the period can be accurately calculated. The beneficial effect of this calculation method is that it provides a quantitative tool to evaluate the carbon efficiency of power consumption units, allowing energy managers to identify nodes with higher carbon emissions.

[0029] With this data, the application can further analyze the energy usage patterns and efficiency in the power grid, thereby providing decision support for optimizing power distribution and improving energy efficiency.

[0030] As a preferred embodiment of the first aspect, the weights of the transmission paths are calculated based on the carbon emissions, specifically:

[0031] Determine the carbon emissions of each transmission line within a preset monitoring period according to the carbon emissions of each power consumption unit node within a preset monitoring period;

[0032] Calculate each weight of each transmission path according to the third formula;

[0033] Wherein, the third formula is:

[0034] Where ι represents the predefined weight adjustment factor, ψ y Indicates the carbon emissions of each transmission line during the preset monitoring time period.

[0035] In this preferred embodiment, the present application can determine the carbon emissions of each transmission line in the power network by analyzing the carbon emissions of each power consumption unit node within a preset monitoring time period. Using these data, combined with a predefined weight adjustment factor, the weight of each transmission path in the power network can be calculated by a third formula. The beneficial effect of this weight calculation method is that it provides a mechanism to evaluate and compare the relative environmental impacts of different power transmission paths. By identifying transmission paths with higher weights, the present application can give priority to technical upgrades or optimizations of these paths to reduce their carbon emissions. For example, the carbon footprint of these paths can be reduced by improving the efficiency of transmission lines, increasing the supply of renewable energy along the lines, or improving power dispatch strategies.

[0036] In a second aspect, the present application provides a carbon flow path tracking device. The carbon flow path tracking device includes an acquisition module, a construction module and a calculation module;

[0037] The acquisition module is used to obtain real-time power data;

[0038] The extraction module is used to construct a target power network diagram according to the real-time power data and each power consumption unit node;

[0039] The calculation module is used to calculate each carbon emission factor of each power consumption unit node within a preset monitoring time period and each transmission path of the carbon flow within the preset monitoring time period according to the target power network diagram;

[0040] According to the carbon emission factors and the target power network diagram, the carbon emissions of the power consumption unit nodes within the preset monitoring time period are calculated;

[0041] Calculating the weights of the transmission paths according to the carbon emissions.

[0042] According to the weights, the line with the largest carbon emission among the carbon emission in the target power network diagram within the preset monitoring time period is calculated.

[0043] This device uses three modules to divide the work and coordinate work to better achieve accurate tracking of the carbon flow path. This application can accurately map the energy flow relationship between power consumption units by acquiring real-time power data and constructing a target power network diagram. Using these data, the present application can calculate the carbon emission factor of each power consumption unit node during a specific monitoring period, thereby revealing the transmission path of the carbon flow. This mapping and calculation not only enhances the understanding of the distribution of carbon emissions in the power system, but also by quantifying the carbon emissions of each node, it can evaluate the carbon emission contributions of different power flows. Furthermore, by analyzing the carbon emissions of each transmission path, the present application can determine the line with the highest carbon emissions in the power network. This can more effectively implement emission reduction strategies and optimize power resource allocation to solve the problem that existing technologies cannot accurately track carbon flow paths.

[0044] As a preferred embodiment of the second aspect, the real-time power data is specifically:

[0045] The real-time power data includes each fuel consumption and each power generation of each power station of each power consumption unit node within a preset monitoring time period.

[0046] In this preferred embodiment, the present application can construct an accurate power network diagram by recording in detail the fuel consumption and power generation of each power consumption unit in a specific period of time, and then analyze the carbon emission factor of each node. This analysis makes it possible to calculate the carbon emissions of each node in the entire network and evaluate the carbon emission weights of different power transmission paths. Ultimately, the present application is able to identify the lines with the largest carbon emissions. The present application provides a clear framework to identify and quantify carbon emission hotspots in the power system, so that power operators and policymakers can implement emission reduction measures in a targeted manner, optimize energy distribution, improve the energy efficiency of the system, and promote the green transformation of the entire power industry.

[0047] As a preferred embodiment of the second aspect, the calculation obtains each carbon emission factor of each power consumption unit node within a preset monitoring time period, specifically:

[0048] According to the power generation of each power station of each power consumption unit node within the preset monitoring time period, the power generation proportion of each power station of each power consumption unit node within the preset monitoring time period is calculated;

[0049] According to the first formula and the proportion of each power generation, each carbon emission factor of each power consumption unit node within a preset monitoring time period is calculated;

[0050] Among them, the first formula is

[0051] Where η r represents the carbon emission coefficient of the rth node in the target power network diagram within the set monitoring time period, Represents various carbon emission factors within the preset monitoring time period.

[0052] In this preferred embodiment, the present application first calculates the proportion of each power station in the total power generation by analyzing the power generation of each power consumption unit node within a preset monitoring time period. This step is fundamental because it will show which power stations play a greater role in power production. Then, using a specific calculation formula (the first formula), combined with these power generation proportions, the carbon emission factor of each power consumption unit node can be determined. This formula usually takes into account the carbon emission coefficient in the power generation process, which reflects the carbon emissions generated per unit of electrical energy in the power generation process. The present application provides an accurate way to evaluate the carbon emission responsibility of each node in the power network. By understanding the carbon emission factor of each node, the carbon footprint of the power grid can be more effectively monitored and managed, the areas with the greatest emission reduction potential can be identified, and more precise strategies can be formulated to achieve emission reduction goals.

[0053] As a preferred embodiment of the second aspect, the calculating of each carbon emission amount of each power consumption unit node within a preset monitoring time period is specifically:

[0054] Obtaining each power consumption unit node's received power and total power consumption of each power station within a preset monitoring time period;

[0055] According to the received power amounts and the total consumed power amount, the average power value of each power consumption unit node within a preset monitoring time period is calculated;

[0056] According to the second formula, the carbon emissions of each power consumption unit node within a preset monitoring time period are calculated;

[0057] Among them, the second formula is

[0058] In the formula, T represents the duration of the preset monitoring period. Represents the average electric power of the rth power consumption unit node within the preset monitoring time period.

[0059] In this preferred embodiment, the present application can calculate the average power of these nodes by accurately obtaining the amount of power received by each power consumption unit node from each power station and its total power consumption during a specific monitoring period. Using these data, combined with the preset time period length, according to the second formula, the carbon emissions of each node during the period can be accurately calculated. The beneficial effect of this calculation method is that it provides a quantitative tool to evaluate the carbon efficiency of power consumption units, allowing energy managers to identify nodes with higher carbon emissions.

[0060] With this data, the application can further analyze the energy usage patterns and efficiency in the power grid, thereby providing decision support for optimizing power distribution and improving energy efficiency.

[0061] As a preferred embodiment of the second aspect, the weights of the transmission paths are calculated based on the carbon emissions, specifically:

[0062] Determine the carbon emissions of each transmission line within a preset monitoring period according to the carbon emissions of each power consumption unit node within a preset monitoring period;

[0063] Calculate each weight of each transmission path according to the third formula;

[0064] Wherein, the third formula is:

[0065] Where ι represents the predefined weight adjustment factor, ψ yIndicates the carbon emissions of each transmission line during the preset monitoring time period.

[0066] In this preferred embodiment, the present application can determine the carbon emissions of each transmission line in the power network by analyzing the carbon emissions of each power consumption unit node within a preset monitoring time period. Using these data, combined with a predefined weight adjustment factor, the weight of each transmission path in the power network can be calculated by a third formula. The beneficial effect of this weight calculation method is that it provides a mechanism to evaluate and compare the relative environmental impacts of different power transmission paths. By identifying transmission paths with higher weights, the present application can give priority to technical upgrades or optimizations of these paths to reduce their carbon emissions. For example, the carbon footprint of these paths can be reduced by improving the efficiency of transmission lines, increasing the supply of renewable energy along the lines, or improving power dispatch strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 : A schematic diagram of a flow chart of an embodiment of a carbon flow path tracing method provided in the present application;

[0068] Figure 2 : A structural schematic diagram of an embodiment of a carbon flow path tracking device provided in the present application. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments 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.

[0070] Embodiment 1

[0071] Please refer to Figure 1 , which is a carbon flow path tracing method provided by an embodiment of the present invention.

[0072] In this embodiment, the process of the carbon flow path tracing method in the present application is described in detail through steps S01-S05.

[0073] S01: Obtain real-time power data.

[0074] As a preferred embodiment of the first embodiment, the real-time power data is obtained as follows:

[0075] Log in to the target energy carbon power grid platform to obtain real-time power data of each power consumption unit corresponding to each power station in the target area.

[0076] The Target Energy Carbon Grid Platform is an intelligent energy management system that aims to improve energy efficiency and reduce carbon emissions by real-time monitoring and optimizing the allocation of power resources. It can help users obtain real-time power data between each power consumption unit and power station in a specific area, thereby supporting the integration and sustainable development of renewable energy.

[0077] S02: Constructing a target power network diagram according to the real-time power data and each power consumption unit node.

[0078] As a preferred embodiment of the first embodiment, the target power network diagram is constructed according to the real-time power data and each power consumption unit node, specifically:

[0079] Obtain the receiving power frequency of each power consumption unit in the target area within the set monitoring time period and the corresponding load demand of each power station from the target energy carbon grid platform, and also obtain the location of each power consumption unit in the target area;

[0080] The distance between each power consumption unit and other power consumption units in the target area is obtained by using the GIS geographic information system, and the distance between each power consumption unit and other power consumption units in the target area is obtained by scaling it according to the same scale, and then the power network sketch corresponding to the target area is preliminarily drawn by using the topological simulation software;

[0081] The distances between each power consumption unit and each power station in the target area are extracted based on the GIS geographic information system, and marked as the line distance L between each power consumption unit and each power station in the target area. fd , f represents the number of each power consumption unit, f = 1, 2, ... i, d represents the number of each power station, d = 1, 2 ... b;

[0082] pass Calculate the resistance R of each power consumption unit corresponding to each power station in the target area fd , A represents the predetermined line cross-sectional area, ρ fd It represents the resistivity of the fth power consumption unit in the target area corresponding to the dth power station. The specific calculation process is:

[0083] The increased reference resistivity value ρ″ corresponding to the extended unit line length is extracted from the power database, and the resistivity ρ of each power consumption unit corresponding to each power station in the target area is obtained according to the line distance between each power consumption unit in the target area and each power station. fd =ρ′+(L fd ×ρ″), ρ′ represents the standard resistivity value corresponding to the predefined initial line length;

[0084] The receiving power frequency HZ of each power consumption unit in the target area within the set monitoring time period is obtained from the preliminary information of each power consumption unit in the target area. f ,pass The reactance X of each power consumption unit in the target area corresponding to each power station in the set monitoring time period is calculated. fd , where D represents the predefined line reference winding depth;

[0085] According to the preliminary information of each power consumption unit in the target area, the load demand I corresponding to each power station in the target area within the set monitoring time period is obtained. fd ,pass Calculate the line capacity S of each power consumption unit in the target area corresponding to each power station in the set monitoring time period f , ν f represents the received voltage value of the fth power consumption unit in the target area;

[0086] The resistivity, reactance and line capacity of each power consumption unit corresponding to each power station in the target area within the set monitoring time period are simultaneously filled into the power network sketch corresponding to the target area, thereby obtaining the power network diagram of the target area within the set monitoring time period.

[0087] In this preferred embodiment, the present application can construct an accurate power network diagram by recording in detail the fuel consumption and power generation of each power consumption unit in a specific period of time, and then analyze the carbon emission factor of each node. This analysis makes it possible to calculate the carbon emissions of each node in the entire network and evaluate the carbon emission weights of different power transmission paths. Ultimately, the present application is able to identify the lines with the largest carbon emissions. The present application provides a clear framework to identify and quantify carbon emission hotspots in the power system, so that power operators and policymakers can implement emission reduction measures in a targeted manner, optimize energy distribution, improve the energy efficiency of the system, and promote the green transformation of the entire power industry.

[0088] S03: According to the target power network diagram, various carbon emission factors of each power consumption unit node within a preset monitoring time period and various transmission paths of the carbon flow within the preset monitoring time period are calculated.

[0089] As a preferred embodiment of the first embodiment, the carbon emission factors of each power consumption unit node within a preset monitoring time period and the transmission paths of the carbon flow within the preset monitoring time period are calculated according to the target power network diagram, specifically:

[0090] Count the number of nodes in the target power network diagram and number them one by one, analyze and obtain the carbon emission coefficient of each node in the target power network diagram within the set monitoring time period, and further determine the carbon emission factor of each node in the target power network diagram within the set monitoring time period;

[0091] Furthermore, the analysis obtains the carbon emission coefficient of each node in the target power network diagram within the set monitoring time period. The specific analysis process is as follows:

[0092] Obtain the fuel consumption of each power generation fuel type corresponding to each power station in each power consumption unit in the target area within the set monitoring time period and power generation r represents the number of each node, r = 1, 2...j, p represents the number of each power generation fuel type, p = 1, 2,...a;

[0093] And according to the corresponding power generation fuel types of each node in the target area, it is compared with the predefined fuel emission factors corresponding to each power generation fuel type, and the fuel emission factors corresponding to each power generation fuel type of each node in the target area are obtained by comparison;

[0094] According to the deployed sensors, the transmission voltage values ​​of each power consumption unit in the target area corresponding to each power station in the set monitoring time period are further obtained, which are annotated as the transmission voltage value ν of each node in the target area r ;

[0095] According to the deployed sensors, the receiving terminal voltage V of each node corresponding to each power station in the target area within the set monitoring time period is further obtained. rd and the receiving end current I rd ,pass The power loss value P of each node corresponding to each power station in the target area within the set monitoring time period is calculated. rd ;

[0096] Further obtain the carbon emission coefficient of each node in the target power network diagram within the set monitoring time period

[0097]

[0098] Furthermore, the carbon emission factor of each node in the target power network diagram within a set monitoring time period is determined by:

[0099] According to the power consumption units in the target area, the corresponding power generation of each power station in each power generation fuel type within the set monitoring time period Obtain the power generation proportion of each node in the target area corresponding to each power generation fuel type within the set monitoring time period

[0100] Then according to the analytical formula Analyze and obtain the carbon emission factors of each node in the target power network diagram within the set monitoring time period Among them, η r Represents the carbon emission coefficient of the rth node in the target power network diagram within the set monitoring time period.

[0101] Furthermore, the transmission path of the carbon flow corresponding to each node in the target power network diagram within the set monitoring time period is tracked, and the specific tracking process includes the following steps:

[0102] Obtain the target power network graph, and extract the number of each node and its adjacent nodes from it, and form a node set N(r) corresponding to each node with the adjacent nodes corresponding to each node, and number each adjacent node in sequence as 1, 2, ...h, ...q;

[0103] According to the target power network diagram, the active power of each node in the target area corresponding to each adjacent node within the set monitoring time period is obtained. and reactive power Then the complex power of each node in the target area corresponding to each adjacent node in the set monitoring time period is obtained. l represents the imaginary unit;

[0104] And then through Calculate the line carbon flow of each node in the target area corresponding to each adjacent node within the set monitoring time period

[0105] According to the node set corresponding to each node, the number of adjacent nodes corresponding to each node is obtained, and the adjacent nodes are compared with each other, and the nodes with the largest number of adjacent nodes are screened out and ranked first, and the nodes are marked as first nodes, and the distances of the first nodes corresponding to the power stations are obtained, and the distances are compared with the predefined reference distances. If there is a first node corresponding to the distances of the power stations that are greater than the predefined reference distance, the first node is marked as a carbon flow sink;

[0106] According to the line carbon flow of each node corresponding to each adjacent node in the target area within the set monitoring time period, the line carbon flow of each adjacent node corresponding to the carbon flow sink point within the set monitoring time period is obtained, and the carbon flow transmission path of each adjacent node adjacent to the carbon flow sink point is marked as being transmitted from each adjacent node to the carbon flow sink point;

[0107] Then, the carbon flow sink and each adjacent node thereto are removed from the target power network diagram to obtain each remaining node in the target power network diagram, and the second carbon flow node is screened from each remaining node in the same manner as the screening method of the carbon flow sink, and the carbon flow transmission path of each adjacent node adjacent to the second carbon flow node is analyzed in the same manner as the analysis method of the carbon flow transmission path of each adjacent node adjacent to the carbon flow sink;

[0108] This analysis method is used to analyze and obtain the transmission path of the carbon flow corresponding to each node in the target power network diagram within the set monitoring time period.

[0109] In this preferred embodiment, the present application can reveal the carbon emission levels of different nodes by calculating the carbon emission factors of each power consumption unit node in the target power network diagram within a preset monitoring time period, thereby identifying the main sources of carbon emissions in the power grid. Combined with these carbon emission factors, further analysis of the transmission path of the carbon flow can provide a detailed understanding of the flow of carbon emissions in the power grid. The beneficial effect of this analysis is that it enables energy operators and policymakers to intuitively see the distribution of carbon emissions in the process of power production and distribution, and then formulate targeted emission reduction measures.

[0110] Specifically, by identifying high-carbon emission nodes and paths, this application can prioritize the implementation of energy efficiency improvement and clean energy substitution strategies at these key points, such as upgrading old power generation equipment and increasing the proportion of renewable energy such as solar and wind power. In addition, this detailed carbon flow analysis can also help optimize power dispatch and reduce dependence on high-carbon emission power resources by adjusting the way electricity is generated, transmitted and consumed. Ultimately, these measures will help reduce the carbon footprint of the entire power network, promote the development of the power industry in a low-carbon and environmentally friendly direction, and provide support for achieving long-term climate change mitigation goals.

[0111] S04: Calculate the carbon emissions of each power consumption unit node within a preset monitoring time period according to the carbon emission factors and the target power network diagram.

[0112] As a preferred embodiment of the first embodiment, the carbon emission of each power consumption unit node within a preset monitoring time period is calculated according to each carbon emission factor and the target power network diagram, specifically:

[0113] Based on the carbon emission factors of each node in the target power network diagram within the set monitoring time period, calculate the carbon emissions of each node in the target power network diagram within the set monitoring time period;

[0114] Furthermore, the carbon emissions of each node in the target power network diagram are calculated within a set monitoring time period, and the specific calculation process is as follows:

[0115] Obtain the received power volume JS of each node in the target area corresponding to each power station in the set monitoring time period from the target energy carbon grid platform rd At the same time, the total power consumption of each node in the target area during the set monitoring time period is obtained. r ;

[0116] Obtain the electric power of each node in the target area at each monitoring time point within the set monitoring time period from the target energy carbon power grid platform, sum and average them, and obtain the average electric power of each node in the target area within the set monitoring time period;

[0117] in accordance with Calculate the carbon emissions of each node in the target power network diagram within the set monitoring time period ψ r , T represents the duration of the set monitoring time period, It represents the average electric power of the rth node in the target area during the set monitoring time period.

[0118] In this preferred embodiment, the present application can accurately calculate the carbon emissions of each node during a specific monitoring period by combining the carbon emission factor of each power consumption unit node and the data of the power network diagram. The beneficial effect of this method is that it provides a quantitative tool that enables the main sources of carbon emissions in the power grid to be clearly identified. With this data, emission reduction measures can be implemented more targeted, such as optimizing the power generation structure, improving energy efficiency, or increasing the proportion of clean energy, thereby effectively reducing the overall carbon footprint of the power grid and promoting the power system to develop in a more environmentally friendly and sustainable direction.

[0119] S05: Calculate the weights of the transmission paths based on the carbon emissions, and calculate the line with the largest carbon emissions among the carbon emissions in the target power network diagram within a preset monitoring time period based on the weights.

[0120] As a preferred embodiment of the first embodiment, the weights of the transmission paths are calculated based on the carbon emissions, and the line with the largest carbon emissions among the carbon emissions in the target power network diagram within a preset monitoring time period is calculated based on the weights, specifically:

[0121] According to the carbon emissions of each node in the target power network diagram within the set monitoring time period, the weights of each carbon flow line corresponding to the target power network diagram within the set monitoring time period are analyzed.

[0122] Furthermore, the weights of the carbon flow lines corresponding to the target power network diagram within the set monitoring time period are analyzed, and the specific analysis process is as follows:

[0123] According to the carbon emissions of each node in the target power network diagram within the set monitoring time period, the carbon emissions of each carbon flow line in the target power network diagram ψ y , y represents the number of each carbon flow line, y = 1, 2, ... w;

[0124] pass Calculate the weight τ of each carbon flow line corresponding to the target power network diagram within the set monitoring time period y , where ι represents the predefined weight adjustment factor.

[0125] It should be supplemented that the weights of each carbon flow line corresponding to the target power network diagram within the set monitoring time period are compared to determine the line with the largest carbon emissions in the target power network diagram within the set monitoring time period, and then feed it back to the terminal to analyze the reasons for the high carbon emissions and how to make subsequent improvements.

[0126] In this preferred embodiment, the present application can efficiently identify the path with the highest carbon emissions during a specific monitoring period by measuring the carbon emissions of each power consumption unit node and determining the weight of the power transmission path accordingly. The advantage of this process is that it can provide a clear optimization direction for grid management, so that emission reduction efforts can be prioritized on those key transmission lines that have the greatest impact on the environment. Such a strategy not only helps to achieve more precise carbon emission control, but also promotes the rational allocation of resources, enhances the energy efficiency and environmental performance of the power grid, and thus promotes the transformation of the entire power industry towards low-carbon and green sustainable development.

[0127] Furthermore, in actual application, the present application also includes an electric power database for storing the increased reference resistivity value corresponding to the extension of the unit line length.

[0128] This application obtains the real-time power data of each power consumption unit corresponding to each power station in the target area, and constructs a power network diagram of the target area within the set monitoring time period with each power consumption unit as a node, determines the carbon emission factor of each node in the target power network diagram within the set monitoring time period, and further calculates the carbon emissions of each node in the target power network diagram within the set monitoring time period, and then tracks the transmission path of the carbon flow corresponding to each node in the target power network diagram within the set monitoring time period, and analyzes the weights of each carbon flow line corresponding to the target power network diagram within the set monitoring time period, which can provide important support for carbon emission supervision, carbon trading and low-carbon economic development, effectively solve the current problem that there are still certain drawbacks in the carbon flow path analysis, avoid the inaccuracy of carbon flow path analysis data due to interference from other factors, effectively and timely observe the changes in carbon flow path weights, effectively ensure the comprehensiveness of carbon flow path analysis, and effectively ensure the scientificity and reliability of carbon flow path analysis, and also provide accurate data for follow-up, improve the accuracy of carbon flow path analysis, and at the same time, to a certain extent, improve the analysis efficiency and intelligence level of carbon flow path analysis.

[0129] Embodiment 2

[0130] Please refer to Figure 2 , which is a carbon flow path tracking device provided in an embodiment of the present application.

[0131] In this embodiment, the carbon flow path tracking device includes an acquisition module 10 , a construction module 20 and a calculation module 30 .

[0132] The acquisition module 10 is used to acquire real-time power data.

[0133] As a preferred embodiment of the second embodiment, the real-time power data is obtained as follows:

[0134] Log in to the target energy carbon power grid platform to obtain real-time power data of each power consumption unit corresponding to each power station in the target area.

[0135] The Target Energy Carbon Grid Platform is an intelligent energy management system that aims to improve energy efficiency and reduce carbon emissions by real-time monitoring and optimizing the allocation of power resources. It can help users obtain real-time power data between each power consumption unit and power station in a specific area, thereby supporting the integration and sustainable development of renewable energy.

[0136] The construction module 20 is used to construct a target power network diagram according to the real-time power data and each power consumption unit node.

[0137] As a preferred embodiment of the second embodiment, the target power network diagram is constructed according to the real-time power data and each power consumption unit node, specifically:

[0138] Obtain the receiving power frequency of each power consumption unit in the target area within the set monitoring time period and the corresponding load demand of each power station from the target energy carbon grid platform, and also obtain the location of each power consumption unit in the target area;

[0139] The distance between each power consumption unit and other power consumption units in the target area is obtained by using the GIS geographic information system, and the distance between each power consumption unit and other power consumption units in the target area is obtained by scaling it according to the same scale, and then the power network sketch corresponding to the target area is preliminarily drawn by using the topological simulation software;

[0140] The distances between each power consumption unit and each power station in the target area are extracted based on the GIS geographic information system, and marked as the line distance L between each power consumption unit and each power station in the target area. fd , f represents the number of each power consumption unit, f = 1, 2, ... i, d represents the number of each power station, d = 1, 2 ... b;

[0141] pass Calculate the resistance R of each power consumption unit corresponding to each power station in the target area fd , A represents the predetermined line cross-sectional area, ρ fdIt represents the resistivity of the fth power consumption unit in the target area corresponding to the dth power station. The specific calculation process is:

[0142] The increased reference resistivity value ρ″ corresponding to the extended unit line length is extracted from the power database, and the resistivity ρ of each power consumption unit corresponding to each power station in the target area is obtained according to the line distance between each power consumption unit in the target area and each power station. fd =ρ′+(L fd ×ρ″), ρ′ represents the standard resistivity value corresponding to the predefined initial line length;

[0143] The receiving power frequency HZ of each power consumption unit in the target area within the set monitoring time period is obtained from the preliminary information of each power consumption unit in the target area. f ,pass The reactance X of each power consumption unit in the target area corresponding to each power station in the set monitoring time period is calculated. fd , where D represents the predefined line reference winding depth;

[0144] According to the preliminary information of each power consumption unit in the target area, the load demand I corresponding to each power station in the target area within the set monitoring time period is obtained. fd ,pass Calculate the line capacity S of each power consumption unit in the target area corresponding to each power station in the set monitoring time period f , ν f represents the received voltage value of the fth power consumption unit in the target area;

[0145] The resistivity, reactance and line capacity of each power consumption unit corresponding to each power station in the target area within the set monitoring time period are simultaneously filled into the power network sketch corresponding to the target area, thereby obtaining the power network diagram of the target area within the set monitoring time period.

[0146] In this preferred embodiment, the present application can construct an accurate power network diagram by recording in detail the fuel consumption and power generation of each power consumption unit in a specific period of time, and then analyze the carbon emission factor of each node. This analysis makes it possible to calculate the carbon emissions of each node in the entire network and evaluate the carbon emission weights of different power transmission paths. Ultimately, the present application is able to identify the lines with the largest carbon emissions. The present application provides a clear framework to identify and quantify carbon emission hotspots in the power system, so that power operators and policymakers can implement emission reduction measures in a targeted manner, optimize energy distribution, improve the energy efficiency of the system, and promote the green transformation of the entire power industry.

[0147] The calculation module 30 is used to calculate, based on the target power network diagram, various carbon emission factors of each power consumption unit node within a preset monitoring time period and various transmission paths of the carbon flow within the preset monitoring time period.

[0148] As a preferred embodiment of the second embodiment, the carbon emission factors of each power consumption unit node within a preset monitoring time period and the transmission paths of the carbon flow within the preset monitoring time period are calculated according to the target power network diagram, specifically:

[0149] Count the number of nodes in the target power network diagram and number them one by one, analyze and obtain the carbon emission coefficient of each node in the target power network diagram within the set monitoring time period, and further determine the carbon emission factor of each node in the target power network diagram within the set monitoring time period;

[0150] Furthermore, the analysis obtains the carbon emission coefficient of each node in the target power network diagram within the set monitoring time period. The specific analysis process is as follows:

[0151] Obtain the fuel consumption of each power generation fuel type corresponding to each power station in each power consumption unit in the target area within the set monitoring time period and power generation r represents the number of each node, r = 1, 2...j, p represents the number of each power generation fuel type, p = 1, 2,...a;

[0152] And according to the corresponding power generation fuel types of each node in the target area, it is compared with the predefined fuel emission factors corresponding to each power generation fuel type, and the fuel emission factors corresponding to each power generation fuel type of each node in the target area are obtained by comparison;

[0153] According to the deployed sensors, the transmission voltage values ​​of each power consumption unit in the target area corresponding to each power station in the set monitoring time period are further obtained, which are annotated as the transmission voltage value ν of each node in the target area r ;

[0154] According to the deployed sensors, the receiving terminal voltage V of each node corresponding to each power station in the target area within the set monitoring time period is further obtained. rd and the receiving end current I rd ,pass The power loss value P of each node corresponding to each power station in the target area within the set monitoring time period is calculated. rd ;

[0155] Further obtain the carbon emission coefficient of each node in the target power network diagram within the set monitoring time period

[0156]

[0157] Furthermore, the carbon emission factor of each node in the target power network diagram within a set monitoring time period is determined by:

[0158] According to the power consumption units in the target area, the corresponding power generation of each power station in each power generation fuel type within the set monitoring time period Obtain the power generation proportion of each node in the target area corresponding to each power generation fuel type within the set monitoring time period

[0159] Then according to the analytical formula Analyze and obtain the carbon emission factors of each node in the target power network diagram within the set monitoring time period Among them, η r Represents the carbon emission coefficient of the rth node in the target power network diagram within the set monitoring time period.

[0160] Furthermore, the transmission path of the carbon flow corresponding to each node in the target power network diagram within the set monitoring time period is tracked, and the specific tracking process includes the following steps:

[0161] Obtain the target power network graph, and extract the number of each node and its adjacent nodes from it, and form a node set N(r) corresponding to each node with the adjacent nodes corresponding to each node, and number each adjacent node in sequence as 1, 2, ...h, ...q;

[0162] According to the target power network diagram, the active power of each node in the target area corresponding to each adjacent node within the set monitoring time period is obtained. and reactive power Then the complex power of each node in the target area corresponding to each adjacent node in the set monitoring time period is obtained. l represents the imaginary unit;

[0163] And then through Calculate the line carbon flow of each node in the target area corresponding to each adjacent node within the set monitoring time period

[0164] According to the node set corresponding to each node, the number of adjacent nodes corresponding to each node is obtained, and the adjacent nodes are compared with each other, and the nodes with the largest number of adjacent nodes are screened out and ranked first, and the nodes are marked as first nodes, and the distances of the first nodes corresponding to the power stations are obtained, and the distances are compared with the predefined reference distances. If there is a first node corresponding to the distances of the power stations that are greater than the predefined reference distance, the first node is marked as a carbon flow sink;

[0165] According to the line carbon flow of each node corresponding to each adjacent node in the target area within the set monitoring time period, the line carbon flow of each adjacent node corresponding to the carbon flow sink point within the set monitoring time period is obtained, and the carbon flow transmission path of each adjacent node adjacent to the carbon flow sink point is marked as being transmitted from each adjacent node to the carbon flow sink point;

[0166] Then, the carbon flow sink and each adjacent node thereto are removed from the target power network diagram to obtain each remaining node in the target power network diagram, and the second carbon flow node is screened from each remaining node in the same manner as the screening method of the carbon flow sink, and the carbon flow transmission path of each adjacent node adjacent to the second carbon flow node is analyzed in the same manner as the analysis method of the carbon flow transmission path of each adjacent node adjacent to the carbon flow sink;

[0167] This analysis method is used to analyze and obtain the transmission path of the carbon flow corresponding to each node in the target power network diagram within the set monitoring time period.

[0168] In this preferred embodiment, the present application can reveal the carbon emission levels of different nodes by calculating the carbon emission factors of each power consumption unit node in the target power network diagram within a preset monitoring time period, thereby identifying the main sources of carbon emissions in the power grid. Combined with these carbon emission factors, further analysis of the transmission path of the carbon flow can provide a detailed understanding of the flow of carbon emissions in the power grid. The beneficial effect of this analysis is that it enables energy operators and policymakers to intuitively see the distribution of carbon emissions in the process of power production and distribution, and then formulate targeted emission reduction measures.

[0169] Specifically, by identifying high-carbon emission nodes and paths, this application can prioritize the implementation of energy efficiency improvement and clean energy substitution strategies at these key points, such as upgrading old power generation equipment and increasing the proportion of renewable energy such as solar and wind power. In addition, this detailed carbon flow analysis can also help optimize power dispatch and reduce dependence on high-carbon emission power resources by adjusting the way electricity is generated, transmitted and consumed. Ultimately, these measures will help reduce the carbon footprint of the entire power network, promote the development of the power industry in a low-carbon and environmentally friendly direction, and provide support for achieving long-term climate change mitigation goals.

[0170] The calculation module 30 is used to calculate the carbon emissions of each power consumption unit node within a preset monitoring time period according to the carbon emission factors and the target power network diagram.

[0171] As a preferred embodiment of the second embodiment, the carbon emission of each power consumption unit node within a preset monitoring time period is calculated according to each carbon emission factor and the target power network diagram, specifically:

[0172] Based on the carbon emission factors of each node in the target power network diagram within the set monitoring time period, calculate the carbon emissions of each node in the target power network diagram within the set monitoring time period;

[0173] Furthermore, the carbon emissions of each node in the target power network diagram are calculated within a set monitoring time period, and the specific calculation process is as follows:

[0174] Obtain the received power volume JS of each node in the target area corresponding to each power station in the set monitoring time period from the target energy carbon grid platform rd At the same time, the total power consumption of each node in the target area during the set monitoring time period is obtained. r ;

[0175] Obtain the electric power of each node in the target area at each monitoring time point within the set monitoring time period from the target energy carbon power grid platform, sum and average them, and obtain the average electric power of each node in the target area within the set monitoring time period;

[0176] in accordance with Calculate the carbon emissions of each node in the target power network diagram within the set monitoring time period ψ r , T represents the duration of the set monitoring time period, It represents the average electric power of the rth node in the target area during the set monitoring time period.

[0177] In this preferred embodiment, the present application can accurately calculate the carbon emissions of each node during a specific monitoring period by combining the carbon emission factor of each power consumption unit node and the data of the power network diagram. The beneficial effect of this method is that it provides a quantitative tool that enables the main sources of carbon emissions in the power grid to be clearly identified. With this data, emission reduction measures can be implemented more targeted, such as optimizing the power generation structure, improving energy efficiency, or increasing the proportion of clean energy, thereby effectively reducing the overall carbon footprint of the power grid and promoting the power system to develop in a more environmentally friendly and sustainable direction.

[0178] The calculation module 30 is used to calculate the weights of the transmission paths according to the carbon emissions, and calculate the line with the largest carbon emissions among the carbon emissions in the target power network diagram within a preset monitoring time period according to the weights.

[0179] As a preferred embodiment of the second embodiment, the weights of the transmission paths are calculated based on the carbon emissions, and the line with the largest carbon emissions among the carbon emissions in the target power network diagram within the preset monitoring time period is calculated based on the weights, specifically:

[0180] According to the carbon emissions of each node in the target power network diagram within the set monitoring time period, the weights of each carbon flow line corresponding to the target power network diagram within the set monitoring time period are analyzed.

[0181] Furthermore, the weights of the carbon flow lines corresponding to the target power network diagram within the set monitoring time period are analyzed, and the specific analysis process is as follows:

[0182] According to the carbon emissions of each node in the target power network diagram within the set monitoring time period, the carbon emissions of each carbon flow line in the target power network diagram ψ y , y represents the number of each carbon flow line, y = 1, 2, ... w;

[0183] pass Calculate the weight τ of each carbon flow line corresponding to the target power network diagram within the set monitoring time period y , where ι represents the predefined weight adjustment factor.

[0184] It should be supplemented that the weights of each carbon flow line corresponding to the target power network diagram within the set monitoring time period are compared to determine the line with the largest carbon emissions in the target power network diagram within the set monitoring time period, and then feed it back to the terminal to analyze the reasons for the high carbon emissions and how to make subsequent improvements.

[0185] In this preferred embodiment, the present application can efficiently identify the path with the highest carbon emissions during a specific monitoring period by measuring the carbon emissions of each power consumption unit node and determining the weight of the power transmission path accordingly. The advantage of this process is that it can provide a clear optimization direction for grid management, so that emission reduction efforts can be prioritized on those key transmission lines that have the greatest impact on the environment. Such a strategy not only helps to achieve more precise carbon emission control, but also promotes the rational allocation of resources, enhances the energy efficiency and environmental performance of the power grid, and thus promotes the transformation of the entire power industry towards low-carbon and green sustainable development.

[0186] Furthermore, in actual application, the present application also includes an electric power database for storing the increased reference resistivity value corresponding to the extension of the unit line length.

[0187] The device uses three modules to divide the work and coordinate the work to better achieve accurate tracking of the carbon flow path. This application obtains the real-time power data of each power consumption unit corresponding to each power station in the target area, and constructs a power network diagram of the target area within the set monitoring time period with each power consumption unit as a node, determines the carbon emission factor of each node in the target power network diagram within the set monitoring time period, and further calculates the carbon emissions of each node in the target power network diagram within the set monitoring time period, and then tracks the transmission path of the carbon flow corresponding to each node in the target power network diagram within the set monitoring time period, and analyzes the weights of each carbon flow line corresponding to the target power network diagram within the set monitoring time period, which can provide important support for carbon emission supervision, carbon trading and low-carbon economic development, effectively solve the current problem that there are still certain drawbacks in the carbon flow path analysis, avoid the inaccuracy of carbon flow path analysis data due to interference from other factors, effectively and timely observe the changes in carbon flow path weights, effectively ensure the comprehensiveness of carbon flow path analysis, and effectively ensure the scientificity and reliability of carbon flow path analysis, and also provide accurate data for follow-up, improve the accuracy of carbon flow path analysis, and at the same time, to a certain extent, improve the analysis efficiency and intelligence level of carbon flow path analysis.

[0188] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A carbon flow path tracing method, characterized in that: include: Get real-time power data; Constructing a target power network diagram according to the real-time power data and each power consumption unit node; According to the target power network diagram, various carbon emission factors of each power consumption unit node within a preset monitoring time period and various transmission paths of carbon flow within the preset monitoring time period are calculated; Calculate the carbon emissions of each power consumption unit node within a preset monitoring time period according to the carbon emission factors and the target power network diagram; Calculating and obtaining weights of the transmission paths according to the carbon emissions; According to the weights, the line with the largest carbon emission among the carbon emission in the target power network diagram within the preset monitoring time period is calculated.

2. The carbon flow path tracing method according to claim 1, characterized in that: The real-time power data is specifically: The real-time power data includes each fuel consumption and each power generation of each power station of each power consumption unit node within a preset monitoring time period.

3. The carbon flow path tracing method according to claim 1, characterized in that: The calculation obtains each carbon emission factor of each power consumption unit node within a preset monitoring time period, specifically: According to the power generation of each power station of each power consumption unit node within the preset monitoring time period, the power generation proportion of each power station of each power consumption unit node within the preset monitoring time period is calculated; According to the first formula and the respective proportions of power generation, the respective carbon emission factors of the power consumption unit nodes within the preset monitoring time period are calculated; Among them, the first formula is Where η r represents the carbon emission coefficient of the rth node in the target power network diagram within the set monitoring time period, Represents various carbon emission factors within the preset monitoring time period.

4. The carbon flow path tracing method according to claim 1, characterized in that: The calculation of each carbon emission amount of each power consumption unit node within a preset monitoring time period is specifically as follows: Obtaining each power consumption unit node's received power and total power consumption of each power station within a preset monitoring time period; According to the received power amounts and the total consumed power amount, the average power value of each power consumption unit node within a preset monitoring time period is calculated; According to the second formula, the carbon emissions of each power consumption unit node within a preset monitoring time period are calculated; Among them, the second formula is In the formula, T represents the duration of the preset monitoring period. Represents the average electric power of the rth power consumption unit node within the preset monitoring time period.

5. The carbon flow path tracing method according to claim 1, characterized in that: The weights of the transmission paths are calculated based on the carbon emissions, specifically: Determine the carbon emissions of each transmission line within a preset monitoring period according to the carbon emissions of each power consumption unit node within a preset monitoring period; Calculate the weights of the transmission paths according to the third formula; Wherein, the third formula is: Where ι represents the predefined weight adjustment factor, ψ y Indicates the carbon emissions of each transmission line during the preset monitoring time period.

6. A carbon flow path tracking device, characterized in that: It includes acquisition module, construction module and calculation module; The acquisition module is used to obtain real-time power data; The extraction module is used to construct a target power network diagram according to the real-time power data and each power consumption unit node; The calculation module is used to calculate each carbon emission factor of each power consumption unit node within a preset monitoring time period and each transmission path of the carbon flow within the preset monitoring time period according to the target power network diagram; According to the carbon emission factors and the target power network diagram, the carbon emissions of the power consumption unit nodes within the preset monitoring time period are calculated; Calculating the weights of the transmission paths according to the carbon emissions. According to the weights, the line with the largest carbon emission among the carbon emission in the target power network diagram within the preset monitoring time period is calculated.

7. The carbon flow path tracking device according to claim 6, characterized in that: The real-time power data is specifically: The real-time power data includes each fuel consumption and each power generation of each power station of each power consumption unit node within a preset monitoring time period.

8. The carbon flow path tracking device according to claim 6, characterized in that: The calculation obtains each carbon emission factor of each power consumption unit node within a preset monitoring time period, specifically: According to the power generation of each power station of each power consumption unit node within the preset monitoring time period, the power generation proportion of each power station of each power consumption unit node within the preset monitoring time period is calculated; According to the first formula and the respective proportions of power generation, the respective carbon emission factors of the power consumption unit nodes within the preset monitoring time period are calculated; Among them, the first formula is Where η r represents the carbon emission coefficient of the rth node in the target power network diagram within the set monitoring time period, Represents various carbon emission factors within the preset monitoring time period.

9. The carbon flow path tracking device according to claim 6, characterized in that: The calculation of each carbon emission amount of each power consumption unit node within a preset monitoring time period is specifically as follows: Obtaining each power consumption unit node's received power and total power consumption of each power station within a preset monitoring time period; According to the received power amounts and the total consumed power amount, the average power value of each power consumption unit node within a preset monitoring time period is calculated; According to the second formula, the carbon emissions of each power consumption unit node within a preset monitoring time period are calculated; Among them, the second formula is In the formula, T represents the duration of the preset monitoring period. Represents the average electric power of the rth power consumption unit node within the preset monitoring time period.

10. The carbon flow path tracking device according to claim 6, characterized in that: The weights of the transmission paths are calculated based on the carbon emissions, specifically: Determine the carbon emissions of each transmission line within a preset monitoring period according to the carbon emissions of each power consumption unit node within a preset monitoring period; Calculate the weights of the transmission paths according to the third formula; Wherein, the third formula is: Where ι represents the predefined weight adjustment factor, ψ y Indicates the carbon emissions of each transmission line during the preset monitoring time period.

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