CEF tracking indirect carbon emission calculation method based on circuit theory analysis

Abstract

The invention provides a CEF tracking calculation indirect carbon emission method based on circuit theory analysis, which comprises the following steps of: 1, acquiring thermal power generator parameters and wind driven generator parameters, and performing Newton interpolation method interpolation on output power data containing missing values in the thermal power generator parameters and the wind driven generator parameters; 2, constructing a CEF tracking framework according to the additive performance of the CEF; 3, analyzing the power system by using a directed graph, and researching power transmission between a source and a load; step 4, establishing a CEF tracking method based on a circuit theory through network topology parameters; and 5, carrying out CEF tracking, comparing CEF tracking results, and analyzing the indirect carbon emission intensity of consumers. According to the method, indirect carbon emission of a user side is calculated by using a node inductive reactance matrix and real-time power generation carbon emission; the spatial-temporal characteristics of different power consumption behaviors can be better reflected; the method is suitable for the condition that a looped network topology structure exists, and the calculation result is more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of indirect carbon emissions of consumers, and in particular to a CEF tracking and calculation method for indirect carbon emissions based on circuit theory analysis. Background Art

[0002] Against the backdrop of increasingly severe global climate change and environmental problems, reducing greenhouse gas emissions and promoting low-carbon development has become a global consensus. As one of the main sources of greenhouse gas emissions, indirect carbon emissions from consumers cannot be ignored. Indirect carbon emissions from consumers refer to greenhouse gas emissions generated by the supply chain and production process when consumers purchase and use goods and services. These emissions are often hidden behind goods and services and are not easily perceived and calculated directly by consumers. However, with the diversification and complexity of consumption patterns, the proportion of indirect carbon emissions from consumers has gradually increased, becoming one of the important sources of greenhouse gas emissions. Therefore, accurately calculating and managing indirect carbon emissions from consumers is of great significance to achieving low-carbon development goals.

[0003] Carbon flow tracking technology is a method used to quantify and evaluate the greenhouse gas emissions generated by a specific activity, product or organization during its life cycle. This method calculates the carbon emissions of a product or service by analyzing its entire life cycle from raw material collection, production, transportation, use to waste disposal. With the continuous development of big data and Internet of Things technologies, carbon flow tracking technology has gradually matured and applied to many fields. In industries such as electricity, transportation, and construction, carbon flow tracking technology has become an important means to assess carbon emissions and formulate emission reduction strategies. However, considering the spatiotemporal characteristics of electricity consumption behaviors of different users and the complex network constraints of the power system, indirect carbon emissions from electricity consumption are difficult to measure accurately. Therefore, it is necessary to conduct research based on carbon emission flow (CEF). However, the existing technology does not have a CEF tracking method to calculate indirect carbon emissions that reflects the spatiotemporal characteristics of different electricity consumption behaviors, and the results of carbon flow tracking are not accurate. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a CEF tracking and calculation method for indirect carbon emissions based on circuit theory analysis, which uses the node inductance matrix and real-time power generation carbon emissions to calculate the indirect carbon emissions on the user side, laying a research foundation for evaluating carbon emissions and formulating emission reduction strategies; it can better reflect the temporal and spatial characteristics of different electricity consumption behaviors; it is suitable for situations where there is a ring network topology, and the calculation results are more accurate.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] The present invention is a CEF tracking and calculating indirect carbon emission method based on circuit theory analysis, comprising the following steps:

[0007] Step 1: Obtain thermal power generator parameters and wind power generator parameters, and perform Newton interpolation on output power data containing missing values ​​in the thermal power generator parameters and wind power generator parameters;

[0008] Step 2: Based on the additivity of CEF, construct the CEF tracking framework;

[0009] Step 3: Use directed graphs to analyze the power system and study the power transfer between sources and loads;

[0010] Step 4: Establish a CEF tracking method based on circuit theory through network topology parameters;

[0011] Step 5: Conduct CEF tracking and compare CEF tracking results, and analyze consumer indirect carbon emission intensity.

[0012] Furthermore, the step 1 specifically includes the following steps:

[0013] Establish a power system, connect the thermal power generators and wind power generators in the system to the inflow node, and connect the consumer users to the outflow node. For a relatively small and local power system, the voltage level is selected as 10kV; find the parameters of thermal power and wind power generators from relevant data, and obtain their output power data; since the output power data of the generator is missing, use Newton interpolation method to fill the vacant value. The basic form of Newton interpolation polynomial is shown as follows:

[0014] N n (x) = f(x0) + f[x0,x1]·(x-x0)

[0015] +f[x0,x1,x2]·(x-x0)(x-x1)

[0016] +f[x0,x1,x2,x3]·(x-x0)(x-x1)(x-x2)…;

[0017] Where x i represents time, f(x0) represents the output power of the generator at time x0, f[x0,x1,…,x k ] is the k-order difference quotient corresponding to the output power data, and the specific form is shown in the following formula:

[0018]

[0019] Data interpolation is used to fill in the missing values ​​of the generator power data, thereby obtaining relatively complete generator output power data.

[0020] Furthermore, the step 2 specifically includes the following steps:

[0021] The indirect carbon emissions from energy consumption in each period are equal to the total CEF injected into the load during this period; the corresponding relationship between the CEF on the power generation side and the demand side is obtained to measure the indirect carbon emissions of the load; according to the additivity of CEF, the CEF on the demand side can be regarded as the sum of different parts, each of which comes from a carbon emission source on the power generation side;

[0022] Suppose there are M inflow nodes connected to generators and N outflow nodes connected to loads; the dynamic carbon emission factor is calculated, which is a linear function based on unit power output, reflecting the dynamic change of the generator power generation; the carbon emission factors of various types of generator sets at the same node need to be normalized according to the power generation weight ratio of each type of generator set, and then calculated; CEF is related to the active power output P injected by the generator M The relationship between can be expressed as:

[0023] CEF in =E M ·P M ;

[0024] Where P M is the active power injection vector flowing into the node, CEF in is the CEF injection vector of the incoming node, E M is the diagonal matrix of dynamic carbon emission factors corresponding to the generator;

[0025] CEF is connected to the power flow. CEF has the same distribution as the power flow. The CEF vector of the outflow node is CEF. out Calculated as:

[0026] CEF out =α M ·CEF in ;

[0027] α M is the contribution matrix of the inflow node to the outflow node.

[0028] Furthermore, the step three specifically includes the following steps:

[0029] In the directed graph of the power system, points represent power system nodes, arcs represent lines, transformers or branches in the power system, and the direction of the arcs represents the flow direction on the branches. To find a branch chain between two branches in a power grid is to find a directed path between two specified directed arcs in a directed graph. For a directed graph with L nodes, the adjacency relationship between nodes is described by the adjacency matrix D; D = d ij is an N-order square matrix whose rows and columns correspond to nodes, where node i is the upstream node of node j, and each element is defined as follows:

[0030]

[0031] Search for branch chains between source loads according to a search method.

[0032] Furthermore, the search method adopts a breadth-first search algorithm, including the following steps: radiating search from a starting node to an outer layer, accessing all nodes adjacent to the starting node, and searching outward layer by layer until a target node is found.

[0033] Furthermore, the step 4 is specifically as follows:

[0034] The relationship between node active power injection and node phase angle can be expressed as follows:

[0035]

[0036] Among them, P M is the active power injection vector flowing into the node, P N is the active power extraction vector of the outflow node, B MM , B MN , B NM , B NN is the decomposition of the node inductance matrix, which represents the inductance of the branch corresponding to the inflow node M and the outflow node N. The node inductance matrix is ​​based on the DC power flow model, ignoring the parallel admittance and conductance of the transmission line. M and θ N Represent the phase angle vectors of the inflow node and outflow node respectively;

[0037] The key goal of the CEF tracking method is to represent P M With P N The relationship between them is:

[0038] P N =φ N θ N ;

[0039] where φ N It can be calculated by the following formula:

[0040]

[0041] in, and YesP N and θ N The i-th element of flows out of the node in the negative direction, so φ N All elements in are negative;

[0042] In the definition of φ NAfter that, the CEF formula can be derived by variable substitution, and the indirect carbon emissions corresponding to electricity consumption can be expressed as:

[0043] CEF N =(B NM +B NN (-(B NN -φ N ) -1 B NM ))(B MM +B MN (-(B NN -φ N ) -1 B NM )) -1 E M P M Among them, EM

[0044] Table 1 is a diagonal matrix of carbon emission factors corresponding to the generators.

[0045] Furthermore, the step five is specifically as follows:

[0046] Furthermore, the CEF tracking method is used to track the power system and compare the indirect carbon emissions corresponding to the electricity consumption of different consumers. The first is the method based on circuit theory, the second is the traditional CEF tracking method based on the proportional sharing principle, and the third is the widely used fixed emission factor method, verifying the superiority of the circuit-based method. For the indirect carbon emission intensity of consumers, it is related to the location and consumption cycle of consumers. The closer the consumer is to the wind turbine, the lower the indirect carbon emission intensity. The green electricity generated by wind turbines accounts for a large part of the total electricity consumption of consumers. The CEF on this part of green electricity is approximately zero, so the consumption behavior of consumers closest to wind turbines contributes little to the total carbon emissions. In addition, wind power generation changes over time, resulting in fluctuations in the indirect carbon emission intensity of different consumers in different periods. This shows that this method can show the spatiotemporal characteristics of indirect carbon emissions.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The present invention proposes a CEF tracking method based on circuit theory analysis, which uses node inductance matrix and real-time power generation carbon emissions to calculate indirect carbon emissions on the user side, laying a research foundation for evaluating carbon emissions and formulating emission reduction strategies. This method can better reveal the relationship between user electricity consumption and carbon emissions on the power generation side. The proposed method is compared with the proportional allocation method and the average carbon emission coefficient method. The proposed method has great advantages. The proposed CEF tracking method can better reflect the spatiotemporal characteristics of different electricity consumption behaviors. In addition, the proposed method is applicable to the case of a ring network topology, and the calculation results are more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in 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 only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0050] Figure 1 It is a directed graph of an embodiment of the present invention.

[0051] Figure 2 is a flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0053] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0054] like Figure 2 As shown, a CEF tracking and calculation method for indirect carbon emissions based on circuit theory analysis includes the following steps:

[0055] Step 1: Obtain thermal power generator parameters and wind power generator parameters, and perform Newton interpolation on output power data containing missing values ​​in the thermal power generator parameters and wind power generator parameters; Step 1 specifically includes the following steps:

[0056] Establish a power system, connect the thermal power generators and wind power generators in the system to the inflow node, and connect the consumer users to the outflow node. For a relatively small and local power system, the voltage level is selected as 10kV; find the parameters of thermal power and wind power generators from relevant data, and obtain their output power data; since the output power data of the generator is missing, use Newton interpolation method to fill the vacant value. The basic form of Newton interpolation polynomial is shown as follows:

[0057] Nn (x) = f(x0) + f[x0,x1]·(x-x0)

[0058] +f[x0,x1,x2]·(x-x0)(x-x1)

[0059] +f[x0,x1,x2,x3]·(x-x0)(x-x1)(x-x2)…;

[0060] Where x i represents time, f(x0) represents the output power of the generator at time x0, f[x0,x1,…,x k ] is the k-order difference quotient corresponding to the output power data, and the specific form is shown in the following formula:

[0061]

[0062] Data interpolation is used to fill in the missing values ​​of the generator power data, thereby obtaining relatively complete generator output power data.

[0063] Step 2: Based on the additivity of CEF, construct a CEF tracking framework. Step 2 specifically includes the following steps:

[0064] The indirect carbon emissions from energy consumption in each period are equal to the total CEF injected into the load during this period; the corresponding relationship between the CEF on the power generation side and the demand side is obtained to measure the indirect carbon emissions of the load; according to the additivity of CEF, the CEF on the demand side can be regarded as the sum of different parts, each of which comes from a carbon emission source on the power generation side;

[0065] Suppose there are M inflow nodes connected to generators and N outflow nodes connected to loads; the dynamic carbon emission factor is calculated, which is a linear function based on unit power output, reflecting the dynamic change of the generator power generation; the carbon emission factors of various types of generator sets at the same node need to be normalized according to the power generation weight ratio of each type of generator set, and then calculated; CEF is related to the active power output P injected by the generator M The relationship between can be expressed as:

[0066] CEF in =E M ·P M ;

[0067] Where P M is the active power injection vector flowing into the node, CEF in is the CEF injection vector of the incoming node, E M is the diagonal matrix of dynamic carbon emission factors corresponding to the generator;

[0068] CEF is connected to the power flow. CEF has the same distribution as the power flow. The CEF vector of the outflow node is CEF. out Calculated as:

[0069] CEF out =α M ·CEF in ;

[0070] α M is the contribution matrix of the inflow node to the outflow node.

[0071] Step three, using a directed graph to analyze the power system and study the power transfer between the source and the load; Step three specifically includes the following steps:

[0072] like Figure 1 As shown in the figure, in the directed graph of the power system, points represent power system nodes, arcs represent lines, transformers or branches in the power system, and the direction of the arcs represents the flow direction on the branches; finding a branch chain between two branches in a power grid is to find a directed path between two specified directed arcs in a directed graph; for a directed graph with L nodes, the adjacency relationship between nodes is described by the adjacency matrix D; D = d ij is an N-order square matrix whose rows and columns correspond to nodes, where node i is the upstream node of node j, and each element is defined as follows:

[0073]

[0074] Search for branch chains between source loads according to a search method.

[0075] The search method adopts a breadth-first search algorithm, which includes the following steps: radiate search from the starting node to the outer layer, visit all nodes adjacent to the starting node, and search outward layer by layer until the target node is found.

[0076] Step 4: Establish a CEF tracking method based on circuit theory through network topology parameters; Step 4 is as follows:

[0077] The relationship between node active power injection and node phase angle can be expressed as follows:

[0078]

[0079] Among them, P M is the active power injection vector flowing into the node, P N is the active power extraction vector of the outflow node, B MM , B MN , B NM , B NNis the decomposition of the node inductance matrix, which represents the inductance of the branch corresponding to the inflow node M and the outflow node N. The node inductance matrix is ​​based on the DC power flow model, ignoring the parallel admittance and conductance of the transmission line. M and θ N Represent the phase angle vectors of the inflow node and outflow node respectively;

[0080] The key goal of the CEF tracking method is to represent P M With P N The relationship between them is:

[0081] P N =φ N θ N ;

[0082] where φ N It can be calculated by the following formula:

[0083]

[0084] in, and YesP N and θ N The i-th element of flows out of the node in the negative direction, so φ N All elements in are negative;

[0085] In the definition of φ N After that, the CEF formula can be derived by variable substitution, and the indirect carbon emissions corresponding to electricity consumption can be expressed as:

[0086] CEF N =(B NM +B NN (-(B NN -φ N ) -1 B NM ))(B MM +B MN (-(B NN -φ N ) -1 B NM )) -1 E M P M Among them, EM

[0087] Table 1 is a diagonal matrix of carbon emission factors corresponding to the generators.

[0088] Step 5: Conduct CEF tracking and compare CEF tracking results, and analyze consumer indirect carbon emission intensity. Step 5 is as follows:

[0089] The CEF tracking method is used to track the power system and compare the indirect carbon emissions corresponding to the electricity consumption of different consumers. The first is the method based on circuit theory, the second is the traditional CEF tracking method based on the proportional sharing principle, and the third is the widely used fixed emission factor method to verify the superiority of the circuit-based method. For the indirect carbon emission intensity of consumers, it is related to the location and consumption cycle of the consumer. The closer the consumer is to the wind turbine, the lower the indirect carbon emission intensity. The green electricity generated by wind turbines accounts for a large part of the total electricity consumption of consumers. The CEF on this part of green electricity is approximately zero, so the consumption behavior of consumers closest to wind turbines contributes little to the total carbon emissions. In addition, wind power generation changes over time, resulting in fluctuations in the indirect carbon emission intensity of different consumers in different periods. This shows that this method can show the spatiotemporal characteristics of indirect carbon emissions.

[0090] The above is a detailed introduction to the CEF tracking and calculation method for indirect carbon emissions based on circuit theory analysis provided by the present invention. This article uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A CEF tracking and calculation method for indirect carbon emissions based on circuit theory analysis, It is characterized in that The following steps are involved: Step 1: Obtain thermal power generator parameters and wind power generator parameters, and perform Newton interpolation on output power data containing missing values ​​in the thermal power generator parameters and wind power generator parameters; Step 2: Based on the additivity of CEF, construct the CEF tracking framework; Step 3: Use directed graphs to analyze the power system and study the power transfer between sources and loads; Step 4: Establish a CEF tracking method based on circuit theory through network topology parameters; Step 5: Conduct CEF tracking and compare CEF tracking results, and analyze consumer indirect carbon emission intensity.

2. According to claim 1, a CEF tracking and calculating indirect carbon emission method based on circuit theory analysis, It is characterized in that The step 1 specifically includes the following steps: Establish a power system, connect the thermal power generators and wind power generators in the system to the inflow node, and connect the consumer users to the outflow node. For a relatively small and local power system, the voltage level is selected as 10kV; find the parameters of thermal power and wind power generators from relevant data, and obtain their output power data; since the output power data of the generator is missing, use Newton interpolation method to fill the vacant value. The basic form of Newton interpolation polynomial is shown as follows: N n (x)=f(x 0 )+f[x 0 ,x 1 ]·(x-x 0 ) +f[x 0 ,x 1 ,x 2 ]·(x-x 0 )(x-x 1 ) +f[x 0 ,x 1 ,x 2 ,x 3 ]·(x-x 0 )(x-x 1 )(x-x 2 )…; Where x i represents time, f(x 0 ) means that in x 0 The output power of the generator at the moment, f[x 0 ,x 1 ,…,x k ] is the k-order difference quotient corresponding to the output power data, and the specific form is shown in the following formula: Data interpolation is used to fill in the missing values ​​of the generator power data, thereby obtaining relatively complete generator output power data.

3. According to the CEF tracking and calculation method for indirect carbon emissions based on circuit theory analysis described in claim 1, It is characterized in that The step 2 specifically includes the following steps: The indirect carbon emissions from energy consumption in each period are equal to the total CEF injected into the load during this period; the corresponding relationship between the CEF on the power generation side and the demand side is obtained to measure the indirect carbon emissions of the load; according to the additivity of CEF, the CEF on the demand side can be regarded as the sum of different parts, each of which comes from a carbon emission source on the power generation side; Suppose there are M inflow nodes connected to generators and N outflow nodes connected to loads; the dynamic carbon emission factor is calculated, which is a linear function based on unit power output, reflecting the dynamic change of the generator power generation; the carbon emission factors of various types of generator sets at the same node need to be normalized according to the power generation weight ratio of each type of generator set, and then calculated; CEF is related to the active power output P injected by the generator M The relationship between can be expressed as: CEF in =E M ·P M ; Where P M is the active power injection vector flowing into the node, CEF in is the CEF injection vector of the incoming node, E M is the diagonal matrix of dynamic carbon emission factors corresponding to the generator; CEF is connected to the power flow. CEF has the same distribution as the power flow. The CEF vector of the outflow node is CEF. out is calculated as: CEF out =α M ·CEF in ; α M is the contribution matrix of the inflow node to the outflow node.

4. According to the method of CEF tracking and calculating indirect carbon emissions based on circuit theory analysis as described in claim 1, It is characterized in that The step three specifically includes the following steps: In the directed graph of the power system, points represent power system nodes, arcs represent lines, transformers or branches in the power system, and the direction of the arcs represents the flow direction on the branches. To find a branch chain between two branches in a power grid is to find a directed path between two specified directed arcs in a directed graph. For a directed graph with L nodes, the adjacency relationship between nodes is described by the adjacency matrix D; D = d ij is an N-order square matrix whose rows and columns correspond to nodes, where node i is the upstream node of node j, and each element is defined as follows: Search for branch chains between source loads according to a search method.

5. According to claim 4, a CEF tracking and calculating indirect carbon emission method based on circuit theory analysis, It is characterized in that The search method adopts a breadth-first search algorithm, and includes the following steps: radiating search from a starting node to an outer layer, visiting all nodes adjacent to the starting node, and searching outward layer by layer until a target node is found.

6. According to claim 1, a CEF tracking and calculating indirect carbon emission method based on circuit theory analysis, It is characterized in that The step 4 is as follows: The relationship between node active power injection and node phase angle can be expressed as follows: Among them, P M is the active power injection vector flowing into the node, P N is the active power extraction vector of the outflow node, B MM , B MN , B NM , B NN is the decomposition of the node inductance matrix, which represents the inductance of the branch corresponding to the inflow node M and the outflow node N. The node inductance matrix is ​​based on the DC power flow model, ignoring the parallel admittance and conductance of the transmission line. M and θ N Represent the phase angle vectors of the inflow node and outflow node respectively; The key goal of the CEF tracking method is to represent P M With P N The relationship between them is: P N =φ N i N ; where φ N It can be calculated by the following formula: in, and YesP N and θ N The i-th element of flows out of the node in the negative direction, so φ N All elements in are negative; In the definition of φ N After that, the CEF formula can be derived by variable substitution, and the indirect carbon emissions corresponding to electricity consumption can be expressed as: CEF N =(B NM +B NN (-(B NN -φ N ) -1 B NM ))(B MM +B MN (-(B NN -φ N ) -1 B NM )) -1 E M P M Among them, EM Table 1 is a diagonal matrix of carbon emission factors corresponding to the generators.

7. According to claim 1, a CEF tracking and calculating indirect carbon emission method based on circuit theory analysis, It is characterized in that The specific details of step five are as follows: Use the CEF tracking method to track the power system and compare the indirect carbon emissions corresponding to the electricity consumption of different consumers.

8. According to claim 6, a CEF tracking and calculating indirect carbon emission method based on circuit theory analysis, It is characterized in that The comparison of indirect carbon emissions corresponding to electricity consumption of different consumers is carried out based on the circuit theory method.

9. According to claim 6, a CEF tracking and calculating indirect carbon emission method based on circuit theory analysis, It is characterized in that The comparison of indirect carbon emissions corresponding to electricity consumption of different consumers is carried out using the CEF tracking method based on the proportional sharing principle.

10. The CEF tracking and calculation method for indirect carbon emissions based on circuit theory analysis according to claim 6, It is characterized in that The comparison of indirect carbon emissions corresponding to electricity consumption of different consumers is carried out using the fixed emission factor method.

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