A method and device for distributed carbon emission flow resolution considering privacy protection

Abstract

The application discloses a distributed carbon emission flow analysis method and equipment considering privacy protection, and relates to the technical field of carbon tracking of energy internet. According to the scheme, the to-be-accounted power grid is divided into multiple sub-regions, and internal nodes and boundary nodes are distinguished, so that each sub-region only calculates a desensitization boundary equivalent matrix representing the boundary equivalent characteristics of the sub-region based on the information of the internal nodes of the sub-region, and thus the internal operation of the region is completed locally. Secondly, only according to the desensitization boundary equivalent matrix of each sub-region and the information of the boundary nodes, the equivalent coupling matrix between the boundary nodes and the carbon emission flow rate of the boundary nodes are calculated, and then the carbon emission flow rate of the internal nodes is solved by back substitution in combination with the information of the internal nodes of each sub-region, and the carbon factor of each node is determined. Since the original topology and parameters of the internal nodes of each sub-region are not required in the whole network accounting process, the sensitive information in the internal nodes of each sub-region can be obtained locally, and the leakage risk caused by the requirement of disclosing internal information in the centralized accounting architecture is avoided.

Description

Technical Field

[0001] This application relates to the field of carbon tracking technology in the energy internet, and in particular to a distributed carbon emission stream analysis method and device that takes privacy protection into account. Background Technology

[0002] The theory of carbon emission flows in power systems is a core technology for carbon tracking. It combines carbon emission attributes with the physical power flow of the power grid to calculate the carbon responsibility shared by the load side. Currently, it is usually based on unified modeling of the entire network, collecting global topology and power flow distribution, and using node admittance matrices for centralized carbon flow calculation.

[0003] However, in distribution networks involving multiple stakeholders, parameters such as line impedance and load characteristics in localized areas like industrial parks and local microgrids often involve trade secrets and operational safety. Centralized accounting architectures, on the other hand, mandate that each regional entity report detailed internal topology and operational parameters to eliminate information barriers. Due to privacy concerns, each region is often unwilling or unable to provide complete data. Furthermore, any topology change in any sub-region requires updating the global model to the central system, further increasing the risk of sensitive information leakage and making it difficult to implement collaborative carbon flow accounting in multi-stakeholder scenarios.

[0004] In view of the above, how to solve the problem that centralized accounting architecture cannot guarantee the confidentiality of information within each region due to the requirement that each region disclose its internal topology and operating parameters is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] The purpose of this application is to provide a distributed carbon emission stream analysis method and device that takes privacy protection into account, in order to solve the problem that centralized accounting architecture cannot guarantee the confidentiality of information within each region because it requires each region to disclose its internal topology and operating parameters.

[0006] To address the aforementioned technical problems, this application provides a distributed carbon emission stream analysis method that takes privacy protection into account, comprising: The power grid to be calculated is divided into multiple sub-regions, and the nodes in each sub-region are divided into internal nodes and boundary nodes; wherein, the internal nodes are only connected to other nodes within the sub-region, and the boundary nodes are used to connect the nodes within the sub-region with external nodes; Based on the information of the internal nodes of each sub-region, the corresponding desensitization boundary equivalence matrix is ​​calculated respectively; wherein, the desensitization boundary equivalence matrix represents the boundary equivalence characteristics of the corresponding sub-region. Based on the desensitized boundary equivalent matrix of each sub-region and the information of the boundary nodes, calculate the equivalent coupling matrix between the corresponding boundary nodes and the carbon emission flow rate of the boundary nodes; Based on the carbon emission flow rate of each boundary node and the information of the internal nodes of the corresponding sub-region, the carbon emission flow rate of the internal nodes of the corresponding sub-region is solved, and the carbon factor of each node is determined.

[0007] On the one hand, based on the information of the internal nodes of each sub-region, the corresponding desensitization boundary equivalent matrix is ​​calculated, including: The first desensitization component is determined based on the admittance information of the internal nodes of each sub-region and the mutual admittance information between the internal nodes and the boundary nodes. The second desensitization component is determined based on the admittance information of the internal nodes of each sub-region, the mutual admittance information between the internal nodes and the boundary nodes, and the unit carbon emission information of the corresponding sub-region. The first desensitized component and the second desensitized component are used as the equivalent matrix of the desensitized boundary of the corresponding sub-region.

[0008] On the other hand, based on the desensitized boundary equivalent matrix of each sub-region and the information of the boundary nodes, the equivalent coupling matrix between the corresponding boundary nodes and the carbon emission flow rate of the boundary nodes are calculated, including: Based on the first desensitization component of each sub-region and the admittance information between the boundary nodes, the Schul complement matrix of the boundary node is determined, and the Schul complement matrix is ​​used as the equivalent coupling matrix. The carbon emission flow rate of the boundary node is determined based on the second desensitized component of each sub-region, the equivalent coupling matrix, and the information of the boundary node.

[0009] On the other hand, based on the carbon emission flow rate of each of the boundary nodes and the information of the internal nodes of the corresponding sub-region, the carbon emission flow rate of the internal nodes of the corresponding sub-region is calculated, including: The carbon emission flow rate of the internal node of the corresponding sub-region is determined based on the carbon emission flow rate of the boundary node of each sub-region, the admittance information of the internal node of the corresponding sub-region, the mutual admittance information between the internal node and the boundary node, and the unit carbon emission information of the corresponding sub-region.

[0010] On the other hand, determining the carbon factor of each node includes: The carbon factor for each node is determined based on the carbon emission flow rate and the corresponding load power of each node.

[0011] On the other hand, the determination of the carbon emission flow rate of the boundary node and the carbon emission flow rate of the internal node includes: The carbon emission rate vector of each unit is determined based on the carbon emission coefficient and the injected power of each unit. Based on the source-load power mapping matrix and the unit carbon emission rate vector, the carbon emission rate of the boundary node and the carbon emission rate of the internal node are determined. The source-load power mapping matrix is ​​used to characterize the power contribution weight of each unit node to each load node.

[0012] On the other hand, including: Obtain the node admittance matrix, load equivalent admittance matrix, and node voltage of each node in the power grid to be calculated; Based on the node admittance matrix and the load equivalent admittance matrix, the source-load current mapping matrix is ​​determined; wherein, the source-load current mapping matrix characterizes the current contribution weight of each unit node to each load node; The source-load power mapping matrix is ​​determined based on the source-load current mapping matrix and the voltage of each node.

[0013] On the other hand, obtaining the node admittance matrix, load equivalent admittance matrix, and node voltage of each node of the power grid to be calculated includes: Obtain the topology data and operating parameters of the power grid to be calculated; wherein, the topology data and operating parameters include at least branch impedance, branch-to-ground susceptance, transformer ratio, number of nodes, number of branches, unit injected power and load power of each node; Based on the topology data and operating parameters, construct the node admittance matrix of the power grid to be calculated; Power flow calculations are performed based on the node admittance matrix and power balance equations to determine the node voltage of each node; wherein, the node voltage includes amplitude and phase angle; Based on the load power and the node voltage, determine the load current phasor corresponding to the node; Based on the load current phasors and the node voltages, the equivalent load admittance of the corresponding node is determined, and the equivalent load admittance matrix is ​​constructed.

[0014] On the other hand, it also includes: Upload the desensitization boundary equivalent matrix of each sub-region to the central node; The desensitization boundary equivalent matrix of each sub-region is summarized based on the central node; wherein, the admittance information of the internal nodes of each sub-region and the mutual admittance information between the internal nodes and the boundary nodes are not uploaded to the central node; The equivalent coupling matrix and the carbon emission flow rate of the boundary nodes are obtained from the central node.

[0015] To address the aforementioned technical problems, this application also provides a distributed carbon emission stream analysis device that takes privacy protection into account, comprising: Memory, used to store computer programs; A processor is used to implement the steps of the above-described distributed carbon emission stream parsing method that takes privacy protection into account when executing the computer program.

[0016] This application provides a privacy-preserving distributed carbon emission flow analysis method. By dividing the power grid to be analyzed into multiple sub-regions and distinguishing between internal and boundary nodes, each sub-region calculates its desensitized boundary equivalence matrix, representing its boundary equivalence characteristics, based solely on information from its internal nodes. This limits the calculation of topology and operating parameters within each region to local computation. Secondly, based solely on the desensitized boundary equivalence matrix of each sub-region and the information of the boundary nodes, the equivalent coupling matrix between boundary nodes and the carbon emission flow rate of the boundary nodes are calculated. Then, by combining the information of the internal nodes of each sub-region, the carbon emission flow rate of the internal nodes is solved back-substituted to determine the carbon factor of each node. Since the original topology and parameters of the internal nodes of each sub-region are not required during the overall network calculation, sensitive information within each sub-region can form a closed loop locally, avoiding the risk of leakage caused by the requirement to disclose internal information in a centralized calculation architecture. This achieves consistent calculation of the entire network's carbon emission flow while ensuring the confidentiality of information within the region.

[0017] In addition, this application also provides a distributed carbon emission stream analysis device that takes privacy protection into account, with the same effect as above. Attached Figure Description

[0018] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram of the distributed carbon emission stream parsing architecture provided in an embodiment of this application; Figure 2 A flowchart illustrating a privacy-preserving distributed carbon emission stream parsing method provided in this application embodiment; Figure 3 A schematic diagram of the topology and power flow of a 9-node system provided in an embodiment of this application; Figure 4 A schematic diagram of the 9-node carbon factor distribution provided in an embodiment of this application; Figure 5 This is a structural diagram of a distributed carbon emission stream analysis device that takes privacy protection into account, provided as an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0021] The core of this application is to provide a distributed carbon emission stream analysis method and device that takes privacy protection into account, in order to solve the problem that centralized accounting architecture cannot guarantee the confidentiality of information within each region because it requires each region to disclose its internal topology and operating parameters.

[0022] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] Figure 1 A schematic diagram of the distributed carbon emission stream parsing architecture provided in the embodiments of this application is shown below. Figure 1 As shown, the architecture includes multiple sub-regions and a central node that interacts with each sub-region. Each sub-region completes its internal calculations locally and only uploads encrypted information to the central node. The central node then aggregates the calculations and sends the boundary results back to each sub-region. The following section details the privacy-preserving distributed carbon emission stream parsing method proposed in this application: Figure 2 A flowchart illustrating a privacy-preserving distributed carbon emission stream parsing method provided in this application embodiment. Figure 2 As shown, the method includes: S10: Divide the power grid to be calculated into multiple sub-regions, and divide the nodes of each sub-region into internal nodes and boundary nodes.

[0024] Internal nodes are connected only to other nodes within their own sub-region, while boundary nodes are used to connect nodes within their own sub-region with external nodes.

[0025] In the distributed collaborative accounting framework, the power grid to be accounted for is first divided into multiple sub-regions, and the nodes in each sub-region are classified into internal nodes and boundary nodes. It is important to note that internal nodes are only connected to other nodes within their own sub-region, while boundary nodes connect nodes within their own sub-region to external nodes. In this embodiment, the sub-region can be an industrial park, a local power supply area, or a local microgrid. The number and method of sub-region division are not limited and depend on the specific implementation. Node classification is based on their connection characteristics: nodes connected to nodes outside their own sub-region are classified as boundary nodes, and the rest are classified as internal nodes.

[0026] S11: Based on the information of the internal nodes of each sub-region, calculate the corresponding desensitization boundary equivalent matrix.

[0027] Among them, the desensitization boundary equivalence matrix represents the equivalent characteristics of the corresponding sub-region boundary.

[0028] Subsequently, based on the information of the internal nodes of each sub-region, the corresponding de-identified boundary equivalence matrix is ​​calculated. It is worth noting that the de-identified boundary equivalence matrix characterizes the boundary equivalence properties of the corresponding sub-region. Furthermore, in this specific embodiment, the calculation process is completed locally within each sub-region. The sub-region only uses its own obtainable internal node information to participate in the calculation, and the resulting de-identified boundary equivalence matrix has been encrypted with key information such as the internal equivalent topology. It should be noted that the de-identified boundary equivalence matrix can consist of one or more encrypted components; this is not limited in this embodiment and depends on the specific implementation.

[0029] S12: Based on the desensitized boundary equivalent matrix and boundary node information of each sub-region, calculate the equivalent coupling matrix between corresponding boundary nodes and the carbon emission flow rate of the boundary nodes.

[0030] Furthermore, based on the desensitized boundary equivalent matrix and boundary node information of each sub-region, the equivalent coupling matrix between corresponding boundary nodes and the carbon emission flow rate of the boundary nodes are calculated. It should be noted that the equivalent coupling matrix is ​​used to characterize the coupling relationship between boundary nodes after considering the equivalent characteristics of each sub-region boundary. It can be obtained by summing the desensitized boundary equivalent matrices uploaded by each sub-region based on the principle of block matrix inversion. The specific calculation process is not limited in this embodiment and depends on the specific implementation.

[0031] S13: Based on the carbon emission flow rate of each boundary node and the information of the internal nodes of the corresponding sub-region, solve for the carbon emission flow rate of the internal nodes of the corresponding sub-region and determine the carbon factor of each node.

[0032] Finally, based on the carbon emission flow rate of each boundary node and the information of the internal nodes of the corresponding sub-region, the carbon emission flow rate of the internal nodes of the corresponding sub-region is solved, and the carbon factor of each node is determined. It should be noted that each sub-region uses the returned boundary node carbon emission flow rate combined with the local internal node information to solve the carbon emission flow rate of its internal nodes; the carbon factor can be determined based on the node's carbon emission flow rate and node load power, and the specific determination method is not limited in this embodiment.

[0033] In this embodiment, by dividing the power grid to be calculated into multiple sub-regions and distinguishing between internal nodes and boundary nodes, each sub-region calculates its desensitized boundary equivalence matrix, representing its boundary equivalence characteristics, based solely on information from its own internal nodes. This limits the calculation of topology and operating parameters within the region to be completed locally. Secondly, the equivalent coupling matrix between boundary nodes and the carbon emission flow rate of the boundary nodes are calculated based solely on the desensitized boundary equivalence matrix of each sub-region and the information of the boundary nodes. Then, the carbon emission flow rate of the internal nodes is solved by back-substituting information from each sub-region, and the carbon factor of each node is determined. Since the original topology and parameters of the internal nodes of each sub-region do not need to be obtained during the full-network calculation, sensitive information within each sub-region can form a closed loop locally. This avoids the risk of leakage caused by the centralized calculation architecture requiring the disclosure of internal information, achieving consistent calculation of the entire network's carbon emission flow while ensuring the confidentiality requirements of information within the region.

[0034] Based on the above embodiments, in some embodiments, the corresponding desensitization boundary equivalent matrix is ​​calculated based on the information of the internal nodes of each sub-region, including: S101: Determine the first desensitization component based on the admittance information of the internal nodes of each sub-region and the mutual admittance information between the internal nodes and the boundary nodes.

[0035] S102: Determine the second desensitization component based on the admittance information of the internal nodes of each sub-region, the mutual admittance information between the internal nodes and the boundary nodes, and the unit carbon emission information of the corresponding sub-region.

[0036] S103: Use the first desensitization component and the second desensitization component as the equivalent matrix of the desensitization boundary of the corresponding sub-region.

[0037] First, the global matrix is ​​rearranged in blocks according to internal nodes and boundary nodes. Then, the node admittance matrix Y... bus By dividing into blocks, we get: ; in, It is a block diagonal matrix containing the topological parameters within each sub-region. and This refers to the mutual admittance between internal nodes and boundary nodes. The mutual admittance between boundary nodes.

[0038] Similarly, the equivalent admittance matrix of the nodal load By dividing into blocks, we get: ; in, A diagonal matrix consisting of the loads of the internal nodes. This is a diagonal matrix formed by the loads of the boundary nodes. Because... As a diagonal matrix, it only affects the relationships within each region and not the coupling relationships between regions. Let The nodal admittance matrix, taking into account load grounding admittance, is obtained as follows: ; in, For the blocks corresponding to internal nodes, For the block corresponding to the boundary node, and It represents the mutual admittance between internal nodes and boundary nodes.

[0039] Secondly, a block-wise inverse is performed based on the carbon emission rate mapping relationship. The load-side carbon emission rate can be expressed as: ; in, The node voltage column vector, Carbon emission flow rate of load, This is the column vector of carbon flow rate of the unit. To obtain the conjugate function, This is a diagonal matrix with the vectors within the parentheses as its diagonal elements. Also, for... When inverting the conjugate matrix, the lemma of inverting a block matrix (i.e., the Schul complement principle) is used: For matrix When the submatrix When reversible, about Shul supplemented: ; in, For matrix The four sub-blocks.

[0040] The inverse matrix of M can be represented in block form: .

[0041] Since, physically, as long as the sub-region is topologically connected and has a grounding branch, the sub-blocks corresponding to the internal nodes... That is, it is invertible. According to the lemma of inverting a block matrix mentioned above, for... Inverting the conjugate matrix yields: ; Among them, the superscript asterisk ( () indicates taking the conjugate. They are respectively , , conjugate, This is the Schul complement matrix corresponding to the boundary nodes.

[0042] Furthermore, let the above expression for load-side carbon emission flow rate... , And based on the above The formula for inverting the conjugate matrix, and simplifying the formula for calculating the source-load carbon flux mapping matrix, yields: ; in, They are respectively The internal node part and the boundary node part of the matrix, These represent the carbon emission flow rates of internal nodes and boundary nodes, respectively. They are respectively The internal nodes and boundary nodes of the matrix. Expanding the second line of the matrix equation above, we find that... and In the product of the two terms, all elements are of the same form and are only related to the data information within each sub-region; similarly, In the expression Each element is also decoupled from its sub-region.

[0043] Finally, based on the admittance information of the internal nodes of each sub-region and the mutual admittance information between the internal nodes and the boundary nodes, the first desensitization component is determined, as shown in the following formula: ; Based on the admittance information of the internal nodes of each sub-region, the mutual admittance information between the internal nodes and the boundary nodes, and the unit carbon emission information of the corresponding sub-region, the second desensitization component is determined, as follows: ; in, This is the first desensitization component. This is the second desensitization component. for The portion of the matrix corresponding to the internal nodes represents the carbon emission information of the internal node units after node voltage normalization. The first and second desensitized components are used as the equivalent desensitization boundary matrices for the corresponding sub-regions.

[0044] In this embodiment, the specific method of acquiring data within each sub-region is not limited and depends on the specific implementation. Thus, each sub-region calculates two encryption matrices—the first de-identified component and the second de-identified component—using only its own known data, protecting the privacy of key information such as the equivalent topology within the region and eliminating the risk of privacy leakage through reverse analysis of uploaded data to derive the internal topology.

[0045] Based on the above embodiments, in some embodiments, based on the desensitized boundary equivalent matrix of each sub-region and the information of the boundary nodes, the equivalent coupling matrix between corresponding boundary nodes and the carbon emission flow rate of the boundary nodes are calculated, including: S111: Based on the first desensitization component of each sub-region and the admittance information between the boundary nodes, determine the Schul complement matrix of the boundary nodes and use the Schul complement matrix as the equivalent coupling matrix.

[0046] S112: Determine the carbon emission flow rate of the boundary nodes based on the second desensitized component of each sub-region, the equivalent coupling matrix, and the information of the boundary nodes.

[0047] To determine the carbon emission flow rate of the boundary nodes, this embodiment specifically determines the Schul complement matrix of the boundary nodes based on the first desensitized component of each sub-region and the admittance information between the boundary nodes, and uses this Schul complement matrix as the equivalent coupling matrix. Specifically, the Schul complement matrix is: ; in, The equivalent coupling matrix is The conjugate of admittance between boundary nodes. That is, the first desensitized component uploaded from each sub-region. The central node utilizes the admittance information it holds between boundary nodes. By combining the first desensitized component of each sub-region, the following can be calculated: .

[0048] Based on the second desensitized component, equivalent coupling matrix, and boundary node information of each sub-region, the carbon emission flow rate of the boundary nodes is determined. Specifically, the central node utilizes the boundary node information it holds in the boundary node portion of the formula calculated from the rearranged source-load carbon flux mapping matrix. , Combining the second desensitized component uploaded from each sub-region with the equivalent coupling matrix The carbon emission flow rate at the boundary nodes was calculated. and the equivalent coupling matrix and boundary node carbon emission flow rate The data is then transmitted back to each sub-region. Thus, the central node can complete the collaborative calculation of boundary nodes solely based on the encrypted components uploaded by each sub-region, without obtaining the original topology and operating parameters of any nodes within the sub-region, achieving equivalent boundary collaboration between regions.

[0049] Based on the above embodiments, in some embodiments, the carbon emission flow rate of the internal nodes of the corresponding sub-region is solved based on the carbon emission flow rate of each boundary node and the information of the internal nodes of the corresponding sub-region, including: S121: Determine the carbon emission flow rate of the internal nodes of the corresponding sub-region based on the carbon emission flow rate of the boundary nodes of each sub-region, the admittance information of the internal nodes of the corresponding sub-region, the mutual admittance information between the internal nodes and the boundary nodes, and the unit carbon emission information of the corresponding sub-region.

[0050] To determine the carbon emission flow rate of internal nodes, in practice, each sub-region obtains the carbon emission flow rate of the boundary nodes that are transmitted back. Then, the carbon emission flow rate of the internal nodes is calculated using the following formula: ; in, The conjugate of the admittance sub-block of the internal node. This refers to the conjugate of the mutually admittance sub-blocks between internal nodes and boundary nodes. for The inverse of the internal node portion of the matrix, for The inverse of the boundary nodes of the matrix. Let the internal node carbon emission flow rate be the solution. For the back-transmitted boundary node carbon emission flow rate, for The portion of the matrix corresponding to the internal nodes. Each sub-region is known. , , , Given the boundary node data related to this sub-region, the carbon emission flow rate of the internal nodes can be solved. In this way, the carbon emission flow rate of internal nodes is solved locally in each sub-region, and the sensitive internal computation is closed within the sub-region, thus decomposing the large-scale global computation into small-scale parallel computations in each sub-region while ensuring privacy.

[0051] Based on the above embodiments, in some embodiments, the carbon factor of each node is determined, including: S122: Determine the carbon factor of each node based on the carbon emission flow rate and corresponding load power.

[0052] Specifically, the carbon factor of a node is obtained by averaging the carbon emission flow rate, as shown in the following formula: ; in, The carbon factor of the node. The carbon emission flow rate of the node. Let be the load power of the node, and Re() be the function to take the real part. This refers to the active power of the node's load. Therefore, based on the distributed accounting results, the average carbon factor of each node can be obtained, providing a usable node carbon measurement indicator for electricity market carbon trading and real-time dispatch.

[0053] Based on the above embodiments, in some embodiments, the determination of the carbon emission flow rate of the boundary node and the carbon emission flow rate of the internal node includes: S131: Determine the carbon emission rate vector of each unit based on the carbon emission coefficient and the injected power of each unit.

[0054] S132: Determine the carbon emission rate of the boundary nodes and the carbon emission rate of the internal nodes based on the source-load power mapping matrix and the unit carbon emission rate vector.

[0055] The source-load power mapping matrix is ​​used to characterize the power contribution weight of each unit node to each load node.

[0056] In this embodiment, given the generator output and the carbon coefficient of each generator unit, the initial carbon emission rate vector at each source end can be calculated based on the net injected power of the generator. Specifically, the carbon emission rate vector of each unit is determined based on its carbon emission coefficient and injected power, using the following formula: ; in, Let the carbon emission flow rate column vector be for each unit. This is a node-generator association matrix, used to represent nodes with the number of generators as the dimension. The column vectors are increased to N dimensions to avoid the problem of matrices of different dimensions being unable to be computed. This is a column vector of the unit's carbon emission coefficients. To inject power into the unit, diag(Crate) is a diagonal matrix with carbon emission coefficients as diagonal elements.

[0057] Based on the source-load power mapping matrix and the unit carbon emission rate vector, the carbon emission rates of the boundary nodes and the internal nodes are determined using the following formulas: ; in, Carbon emission flow rate borne by the load side This is the source-load power mapping matrix, used to characterize the power contribution weight of each unit node to each load node. Since the unit carbon emission coefficient itself is a real number, in the calculation... When the carbon emission coefficient is taken as a constant coefficient outside the real part function Re(), the final result only includes the product of the carbon emission coefficient and the active power output of the unit, excluding reactive power-related components. It should be noted that in this embodiment, the value of the unit's carbon emission coefficient is not restricted and depends on the specific implementation. In this embodiment, the allocation of carbon emission flow rate is directly traced back to each unit, and the power contribution of each unit to each load node is characterized by the source-load power mapping matrix, giving carbon responsibility accounting a clear physical source.

[0058] Based on the above embodiments, in some embodiments, the process of determining the source-load power mapping matrix includes: S141: Obtain the node admittance matrix, load equivalent admittance matrix, and node voltage of each node of the power grid to be calculated.

[0059] S142: Determine the source-load current mapping matrix based on the node admittance matrix and the load equivalent admittance matrix; wherein, the source-load current mapping matrix represents the current contribution weight of each unit node to each load node.

[0060] S143: Determine the source-load power mapping matrix based on the source-load current mapping matrix and the voltage of each node.

[0061] To determine the source-load power mapping matrix, this embodiment first obtains the node admittance matrix, load equivalent admittance matrix, and node voltage of the power grid to be calculated. Combining Kirchhoff's voltage and current laws, the node injection current, node voltage, and node admittance matrix of the entire system satisfy the following relationships: ; in, Inject current into the node, Inject current into the generator, For the current flowing out of the node load, Here is the nodal admittance matrix. These are the voltage phasors for each node. This is due to the current flowing out of the node loads. This can be expressed as the product of the load equivalent admittance matrix and the node voltage column vector, thus establishing the mapping relationship between the source load currents, as shown in the following formula: ; ; in, The node voltage column vector, This is the load equivalent admittance matrix.

[0062] Subsequently, based on the nodal admittance matrix and the load equivalent admittance matrix, the source-load current mapping matrix is ​​determined, as shown in the following formula: ; in, This is the source-load current mapping matrix, used to characterize the current contribution weight of each unit node to each load node, and its elements... The physical meaning of is the weight of the current contribution of the generator at node i to the load at node j.

[0063] Based on this, the load complex power of node j is analytically decomposed into the entire network. The sum of the contributions of each generator node is as follows: ; in, Let J be the load complex power of node j. This represents the share of load power at node j originating from generator node i, where N is the number of nodes. Based on the source-load current mapping matrix. , The parsing expression is: ; in, Let be the element in the j-th row and i-th column of the source-load current mapping matrix. Let J be the node voltage phasor at load j. Let be the node voltage phasor at generator i. Inject power into the generator at the i-th node, where conj() is the conjugate function.

[0064] Finally, based on the source-load current mapping matrix and the voltages at each node, the source-load power mapping matrix is ​​determined as follows: ; in, The source-load power mapping matrix, Let V be the voltage phasor of each node, diag(V) be a diagonal matrix with the node voltages as diagonal elements, and conj() be the conjugate function.

[0065] In this way, the construction of the source-load power mapping matrix is ​​strictly coupled with the branch complex admittance and the node voltage vector, so that the distribution ratio of carbon emission flow is related to the physical topology of the power grid, accurately characterizing the real coupling strength between the source, grid and load based on electrical distance, and ensuring that the calculation results conform to Kirchhoff's laws.

[0066] Based on the above embodiments, in some embodiments, obtaining the node admittance matrix, load equivalent admittance matrix, and node voltage of the power grid to be calculated includes: S151: Obtain the topology data and operating parameters of the power grid to be calculated; wherein, the topology data and operating parameters shall include at least the branch impedance, branch susceptance to ground, transformer ratio, number of nodes, number of branches, unit injected power and load power of each node.

[0067] S152: Construct the node admittance matrix of the power grid to be calculated based on the topology data and operating parameters.

[0068] S153: Perform power flow calculations based on the node admittance matrix and power balance equations to determine the node voltage of each node; where the node voltage includes the magnitude and phase angle.

[0069] S154: Determine the load current phasor of the corresponding node based on the power of each load and the voltage of each node.

[0070] S155: Based on the load current phasors and the voltage of each node, determine the equivalent load admittance of the corresponding node and construct the equivalent load admittance matrix.

[0071] In this embodiment, the topology data and operating parameters of the power grid to be calculated are specifically obtained. The topology data and operating parameters include at least branch impedance, branch-to-ground susceptance, transformer turns ratio, number of nodes, number of branches, generator injection power at each node, and load power. Branch impedance includes resistance. and reactance The branch line to ground is The transformer turns ratio is The number of nodes is The number of branches is .

[0072] Subsequently, based on the topology data and operating parameters, the node admittance matrix of the power grid to be calculated is constructed. Specifically, all branches are traversed, and the equivalent admittance and ground admittance of each branch are calculated according to the node numbers of its first and last nodes. An N-dimensional standard node admittance matrix is ​​then constructed according to Kirchhoff's current law. Power flow calculations are further performed based on the node admittance matrix and the power balance equations to determine the node voltages, which include both magnitude and phase angle. In this embodiment, the specific algorithm used for power flow calculation is not limited and depends on the specific implementation. For example, the Newton-Raphson method can be used to solve the nonlinear power balance equations.

[0073] Then, based on the load power and the voltage of each node, the load current phasor of the corresponding node is determined, as shown in the following formula: ; in, Let be the load current phasor of each node. For load power, Here, is the node voltage (per unit value), and conj() is the function to take the conjugate.

[0074] Finally, based on the load current phasors and node voltages, the equivalent load admittance for each node is determined, and the equivalent load admittance matrix is ​​constructed. The load is modeled as the equivalent admittance to ground, as shown in the following formula: ; in, Let be the load equivalent admittance matrix, which is an N-dimensional diagonal matrix; This represents the ground admittance of node i. Let be the load current phasor of node i. Let be the voltage at node i. Therefore, through power flow calculations and load-to-ground equivalent admittance modeling, an accurate electrical quantity basis is provided for constructing the source-load current mapping matrix and the source-load power mapping matrix.

[0075] Based on the above embodiments, in some embodiments, the method further includes: S161: Upload the desensitization boundary equivalent matrix of each sub-region to the central node.

[0076] S162: Based on the central node, summarize the desensitized boundary equivalent matrix of each sub-region; wherein, the admittance information of the internal nodes of each sub-region and the mutual admittance information between the internal nodes and the boundary nodes are not uploaded to the central node.

[0077] S163: Obtain the equivalent coupling matrix and carbon emission flow rate of the boundary nodes from the central node.

[0078] like Figure 1 As shown, the desensitized boundary equivalent matrix of each sub-region is uploaded to the central node; the desensitized boundary equivalent matrix of each sub-region is aggregated at the central node. However, the admittance information of internal nodes within each sub-region and the mutual admittance information between internal nodes and boundary nodes are not uploaded to the central node. The equivalent coupling matrix and the carbon emission flow rate of the boundary nodes are obtained from the central node. In this embodiment, the central node is a logical node responsible for boundary aggregation and collaborative calculation; its specific deployment is not limited and depends on the specific implementation. Thus, a distributed architecture of 1 master and N slaves is formed between each sub-region and the central node. Each sub-region only uploads desensitized encrypted information; internal sensitive parameters never leave the sub-region. This achieves consistent calculation of the carbon emission flow across the entire network while ensuring the confidentiality of information within the region. Simultaneously, when the local topology of a sub-region changes, only the boundary parameters of that sub-region and the central node need to be updated, without restarting the entire network calculation, improving the timeliness and scalability of large-scale power grid calculation.

[0079] To facilitate understanding of this solution by those skilled in the art, a specific example is provided below for illustration. Figure 3 This is a schematic diagram of the 9-node system topology and power flow direction provided in the embodiments of this application, as shown below. Figure 3As shown, the system has 9 nodes, including 1 node as the point of common coupling (PCC) node with a carbon emission factor of 0.6, and 4 and 8 nodes connected to a distributed generation unit with carbon emission factors of 0.2 and 0.3, respectively. Voltage information for each node is obtained through power flow calculations, and the system simulation is divided into multiple sub-regions for distributed solution to obtain the carbon factor for each node. Figure 4 This is a schematic diagram of the 9-node carbon factor distribution provided in an embodiment of this application, as shown below. Figure 4 As shown, since each generating unit contributes to the load power of other nodes, the carbon factor of all nodes in the network fluctuates around 0.45. Nodes 4 and 8 have lower carbon factors than other nodes because they are connected to new energy generating units. Nodes 3, 5, and 9 also have relatively low carbon factors because they receive some power from new energy generating units. Nodes 2, 6, and 7 have relatively high carbon factors because their power is supplied more by PCC nodes.

[0080] Figure 5 A structural diagram of a distributed carbon emission stream analysis device that takes privacy protection into account, provided as an embodiment of this application, is shown below. Figure 5 As shown, the device includes: Memory 20 is used to store computer programs; The processor 21 is configured to implement the steps of the privacy-preserving distributed carbon emission stream parsing method mentioned in the above embodiments when executing a computer program.

[0081] The distributed carbon emission stream analysis device provided in this embodiment, which takes into account privacy protection, may include, but is not limited to, smartphones, tablets, laptops, or desktop computers.

[0082] The processor 21 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 21 may be implemented using at least one of the following hardware forms: Digital Signal Processor (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor, also known as the Central Processing Unit (CPU), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 21 may integrate a Graphics Processing Unit (GPU), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 21 may also include an Artificial Intelligence (AI) processor, which handles computational operations related to machine learning.

[0083] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In this embodiment, the memory 20 is used to store at least the following computer program 201, which, after being loaded and executed by the processor 21, is capable of implementing the relevant steps of the privacy-preserving distributed carbon emission stream parsing method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, and the storage method may be temporary or permanent storage. The operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include, but is not limited to, the data involved in the privacy-preserving distributed carbon emission stream parsing method.

[0084] In some embodiments, the distributed carbon emission stream analysis device with privacy protection considerations may further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.

[0085] Those skilled in the art will understand that Figure 5 The structure shown does not constitute a limitation on a distributed carbon emission stream analysis device that takes privacy protection into account, and may include more or fewer components than shown.

[0086] Finally, this application also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps described in the above method embodiments.

[0087] It is understood that if the methods in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and executes all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0088] The foregoing has provided a detailed description of a distributed carbon emission stream analysis method and apparatus that takes privacy protection into account, as provided in this application. The various embodiments in the specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of this application.

[0089] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A distributed carbon emission stream analysis method that takes privacy protection into account, characterized in that, include: The power grid to be calculated is divided into multiple sub-regions, and the nodes in each sub-region are divided into internal nodes and boundary nodes; wherein, the internal nodes are only connected to other nodes within the sub-region, and the boundary nodes are used to connect the nodes within the sub-region with external nodes; Each sub-region calculates its corresponding desensitization boundary equivalence matrix locally based on the information of its internal nodes; wherein the desensitization boundary equivalence matrix represents the boundary equivalence characteristics of the corresponding sub-region. The central node calculates the equivalent coupling matrix between the boundary nodes and the carbon emission flow rate of the boundary nodes based on the desensitized boundary equivalent matrix of each sub-region and the information of the boundary nodes. The carbon emission flow rate of the internal nodes of the corresponding sub-region is calculated locally based on the carbon emission flow rate of each boundary node and the information of the internal nodes of the corresponding sub-region, and the carbon factor of each node is determined. Based on the information of the internal nodes of each sub-region, the corresponding desensitization boundary equivalence matrix is ​​calculated locally, including: The first desensitization component is determined based on the admittance information of the internal nodes of each sub-region and the mutual admittance information between the internal nodes and the boundary nodes. The second desensitization component is determined based on the admittance information of the internal nodes of each sub-region, the mutual admittance information between the internal nodes and the boundary nodes, and the unit carbon emission information of the corresponding sub-region. The first desensitized component and the second desensitized component are used as the equivalent matrix of the desensitized boundary of the corresponding sub-region; The central node calculates the equivalent coupling matrix between the corresponding boundary nodes and the carbon emission flow rate of the boundary nodes based on the desensitized boundary equivalent matrix of each sub-region and the information of the boundary nodes, including: Based on the first desensitization component of each sub-region and the admittance information between the boundary nodes, the Schul complement matrix of the boundary node is determined, and the Schul complement matrix is ​​used as the equivalent coupling matrix. The carbon emission flow rate of the boundary node is determined based on the second desensitized component of each sub-region, the equivalent coupling matrix, and the information of the boundary node.

2. The distributed carbon emission stream analysis method considering privacy protection according to claim 1, characterized in that, The carbon emission flow rate of the internal nodes of the corresponding sub-region is calculated locally based on the carbon emission flow rate of each boundary node and the information of the internal nodes of the corresponding sub-region, including: The carbon emission flow rate of the internal node of the corresponding sub-region is determined based on the carbon emission flow rate of the boundary node of each sub-region, the admittance information of the internal node of the corresponding sub-region, the mutual admittance information between the internal node and the boundary node, and the unit carbon emission information of the corresponding sub-region.

3. The distributed carbon emission stream analysis method considering privacy protection according to claim 1, characterized in that, Determining the carbon factor of each node includes: The carbon factor corresponding to each node is determined based on the carbon emission flow rate and the corresponding load power of each node.

4. The distributed carbon emission stream analysis method considering privacy protection according to claim 1, characterized in that, The determination of the carbon emission flow rate of the boundary node and the carbon emission flow rate of the internal node includes: The carbon emission rate vector of each unit is determined based on the carbon emission coefficient and the injected power of each unit. Based on the source-load power mapping matrix and the unit carbon emission rate vector, the carbon emission rate of the boundary node and the carbon emission rate of the internal node are determined. The source-load power mapping matrix is ​​used to characterize the power contribution weight of each unit node to each load node.

5. The distributed carbon emission stream analysis method considering privacy protection according to claim 4, characterized in that, The process of determining the source-load power mapping matrix includes: Obtain the node admittance matrix, load equivalent admittance matrix, and node voltage of each node in the power grid to be calculated; Based on the node admittance matrix and the load equivalent admittance matrix, the source-load current mapping matrix is ​​determined; wherein, the source-load current mapping matrix characterizes the current contribution weight of each unit node to each load node; The source-load power mapping matrix is ​​determined based on the source-load current mapping matrix and the voltage of each node.

6. The distributed carbon emission stream analysis method considering privacy protection according to claim 5, characterized in that, Obtaining the node admittance matrix, load equivalent admittance matrix, and node voltage of the power grid to be calculated includes: Obtain the topology data and operating parameters of the power grid to be calculated; wherein, the topology data and operating parameters include at least branch impedance, branch-to-ground susceptance, transformer ratio, number of nodes, number of branches, unit injected power and load power of each node; Based on the topology data and operating parameters, construct the node admittance matrix of the power grid to be calculated; Power flow calculations are performed based on the node admittance matrix and power balance equations to determine the node voltage of each node; wherein, the node voltage includes amplitude and phase angle; Based on the load power and the node voltage, determine the load current phasor corresponding to the node; Based on the load current phasors and the node voltages, the equivalent load admittance of the corresponding node is determined, and the equivalent load admittance matrix is ​​constructed.

7. The distributed carbon emission stream analysis method considering privacy protection according to claim 1, characterized in that, Also includes: Upload the desensitization boundary equivalent matrix of each sub-region to the central node; The desensitization boundary equivalent matrix of each sub-region is summarized based on the central node; wherein, the admittance information of the internal nodes of each sub-region and the mutual admittance information between the internal nodes and the boundary nodes are not uploaded to the central node; The equivalent coupling matrix and the carbon emission flow rate of the boundary nodes are obtained from the central node.

8. A distributed carbon emission stream analysis device that takes privacy protection into account, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the privacy-preserving distributed carbon emission stream parsing method as described in any one of claims 1 to 7 when executing the computer program.

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