Power grid dynamic carbon emission factor calculation method and system considering bidirectional traceability correction

Abstract

The application discloses a kind of power grid dynamic carbon emission factor calculation method and system considering two-way tracing correction, first, carbon flow calculation is carried out based on power grid flow result, carbon emission source is traced from network layer to node from top to bottom, and carbon emission factor is obtained;Then, carbon emission reduction intensity factor is obtained by tracing from park to node from bottom to top against flow;Finally, carbon emission factor is corrected based on the carbon emission reduction intensity factor, and dynamic carbon emission factor is obtained.The dynamic carbon emission factor obtained by the application can better adapt to the change of regional multi-agent carbon emission and carbon emission reduction behavior by two-way tracing from top to bottom and from bottom to top, and realizes the dynamic update of carbon emission factor.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of power systems, and particularly relates to a power grid dynamic carbon emission factor calculation method and system considering bidirectional traceability correction. BACKGROUND

[0002] With the increasing severity of global climate change, effective management and accurate accounting of carbon emissions have become the focus of attention of governments and the power industry. In the power system, the traditional carbon emission factor is usually calculated from the generator node or the transformer bus node to the user node. Although this method can reflect the overall carbon emission of the power grid, it often cannot accurately capture the influence of user-side emission reduction interaction behavior on the carbon emission distribution of the power grid. This makes it difficult for existing power grid carbon emission models to support user-side interaction regulation mechanisms aimed at reducing carbon emissions.

[0003] In a regional multi-agent environment, user electricity consumption and transaction behavior are highly coupled with physical processes of power distribution and carbon flow distribution. The carbon emission and emission reduction behavior of each user is interrelated, and these behaviors have a significant impact on the carbon emission distribution of the power grid. However, current calculation methods do not effectively consider these dynamic interactions, leading to potential inaccuracies when developing emission reduction policies or optimizing power dispatch.

[0004] Therefore, in order to more accurately evaluate the comprehensive influence of the carbon emission and emission reduction behavior of regional multi-agents on the carbon emission distribution of the power grid, it is urgent to propose a power grid dynamic carbon emission factor calculation method and system considering bidirectional traceability correction. SUMMARY

[0005] The purpose of the present application is to provide a power grid dynamic carbon emission factor calculation method and system considering bidirectional traceability correction. The node carbon emission factor is traced from top to bottom and from bottom to top, which can better adapt to the changes in regional multi-agent carbon emission and carbon emission reduction behavior, and realize dynamic updating of the carbon emission factor. The evidence storage method based on blockchain technology stores the dynamic carbon emission factor in multiple space-time dimensions, ensuring that the dynamic carbon emission factor data cannot be tampered with and the emission process is traceable.

[0006] To achieve the above purpose, the solution of the present application is:

[0007] A power grid dynamic carbon emission factor calculation method considering bidirectional traceability correction, comprising,

[0008] Based on the power flow results, carbon flow calculation is performed, and the carbon emission source is traced from the network layer to the node from top to bottom to obtain the carbon emission factor;

[0009] From the park to the node, the inverse flow is traced from bottom to top to obtain the carbon emission reduction intensity factor;

[0010] The carbon emission factor is corrected based on the carbon emission reduction intensity factor to obtain a dynamic carbon emission factor.

[0011] The carbon emission factor is obtained by tracing the carbon emission source from the network layer to the node from top to bottom based on the power grid flow result, and includes,

[0012] Obtain real-time data of power grid parameters;

[0013] Perform AC power flow calculation to obtain power flow and network loss of each branch of the power grid;

[0014] According to the AC power flow calculation result, the generated power is divided into power drawn by each node load from the generator, power drawn by each branch from the generator, and network loss power borne by the generator;

[0015] Based on the foregoing generated power decomposition result, the generated carbon emission is divided into total carbon flow rate borne by each node load, each branch, and network loss;

[0016] According to the total carbon flow rate of the inflow of each node branch and the total outflow power, the carbon emission factor of the node is calculated.

[0017] According to the AC power flow calculation result, the generated power is divided into power drawn by each node load from the generator, power drawn by each branch from the generator, and network loss power borne by the generator, including,

[0018] Construct the downstream power flow distribution matrix T u :

[0019] T u P=P G

[0020]

[0021] In the formula, P G is an active power output matrix of each node generator, P=[P1 P2...P n ] T is a power outflow matrix of each node, T u,ki is the element in the kth row and the ith column of the matrix T u , P ki is the power of branch k-i, U k is the upstream node set of node k, that is, the node set directly connected to node k and having active power flowing to node k, P i is the active power flowing through node i, and n is the number of nodes of the power system.

[0022] The power drawn by the node load from the generator is calculated by the following method:

[0023] The power component P drawn by the load at node k from the generator at node i Lk,Gi Represented as:

[0024]

[0025] In the formula, P Lk For the load of node k, P Gi For the generator output at node i, P k Let be the power flowing through node k;

[0026] The method for calculating the power drawn from the generator by the branch is as follows:

[0027] The generator at node i supplies power P to branch kj. kj Contribution share P kj,Gi for:

[0028]

[0029] The method for calculating the grid loss power borne by the generator is as follows:

[0030] Similarly, the generator at access node i causes network loss in branch kj. Contribution share Represented as:

[0031]

[0032] Based on the aforementioned power generation decomposition results, the carbon emissions from power generation are decomposed into the total carbon flow rate borne by each node load, each branch, and network losses, including...

[0033] The load at node k carries the carbon flow rate component C of the unit connected to node i. Lk,Gi for:

[0034]

[0035] In the formula, e Gi The carbon emission intensity of the generator set connected to node i;

[0036]

[0037] In the formula, C Lk The total carbon flux at node k;

[0038] Branch kj carries the carbon flow rate component C of the generator set connected to node i. kj,Gi for:

[0039]

[0040] In the formula, C kj The total carbon flow rate of branch kj;

[0041] The branch k-j network loss bearing access node i's generator set carbon flow rate component is:

[0042]

[0043] In the formula, The total carbon flow rate of the branch k-j network loss.

[0044] Wherein, the node carbon emission factor is calculated, including, for node j, its carbon emission factor is expressed as:

[0045]

[0046] In the formula, E Nj The carbon emission factor of node j; C kj The total carbon flow rate of branch k-j; The total carbon flow rate of the branch k-j network loss; U j The upstream node set of node j; P j The active power flowing through node j.

[0047] Wherein, the carbon emission reduction intensity factor is obtained by tracing back from the park to the node from bottom to top, including,

[0048] The low-carbon behavior fusion aggregation power is obtained by fusing and aggregating the low-carbon behavior power changes of the park multi-agent users;

[0049] The low-carbon behavior fusion aggregation power is equivalent to the virtual generator injection power;

[0050] The equivalent generator injection power is decomposed into the contributions to each node load, each branch and network loss by constructing the counter-flow power flow distribution matrix;

[0051] Based on the foregoing injection power decomposition result, the equivalent generator injection carbon emission is decomposed into the total carbon flow rate respectively borne by each node load, each branch and network loss;

[0052] According to the total carbon flow rate and total outflow power of the branch where each node is located, the carbon emission reduction intensity factor of the node is calculated.

[0053] Wherein, the park multi-agent users include residential users, small and medium-sized industrial and commercial users and distributed clean energy;

[0054] The low-carbon behavior power change fusion aggregation expression of the park layer multi-agent users is:

[0055]

[0056] In the formula, P sum(t) is the power of low-carbon behavior fusion and aggregation, ΔP r,i (t) is the power reduction of residential users, ΔP b,i is the power reduction of small and medium-sized industrial and commercial users, ΔP d,i (t) is the power change of distributed clean energy; N1 is the number of residential users, N2 is the number of small and medium-sized industrial and commercial users, and N3 is the number of distributed clean energy;

[0057] From the park to the node, the power of low-carbon behavior fusion and aggregation of multi-agent users in the park is equivalent to the injection power of a virtual generator in a reverse flow tracing from bottom to top:

[0058] P F (t) = -P sum (t)

[0059] In the formula, P F (t) is the injection power of the equivalent generator;

[0060] The equivalent generator injection power is decomposed:

[0061] B d P = P F

[0062]

[0063] In the formula, B d is the reverse flow distribution matrix, B d,ki is the element in the kth row and the ith column of the matrix B d , P = [P1 P2...P n ] T is the outflow power matrix of each node; P F is the injection power matrix of the equivalent generator of each node, P Fi is the equivalent generator power of access node i; P Lk,Fi is the contribution of the equivalent generator power of access node i to the load of node k, P kj,Fi is the contribution of the equivalent generator power of access node i to the power of branch k-j, is the contribution of the equivalent generator power of access node i to the power loss of branch k-j;

[0064] The equivalent generator injection carbon emission is decomposed:

[0065]

[0066] In the formula, C Lk,Fi is the contribution of the equivalent generator carbon flow rate of access node i to the load of node k, e Fi is the carbon emission factor of node i, C Lk is the total carbon flow rate of node k load;

[0067]

[0068] wherein C kj,Fi is the contribution of the equivalent generator carbon flow rate of node i to branch k-j, C kj is the total carbon flow rate of branch k-j;

[0069]

[0070] wherein, is the contribution of the equivalent generator carbon flow rate of node i to branch k-j network loss, is the total carbon flow rate of branch k-j network loss;

[0071] The carbon emission reduction intensity factor is calculated according to the following formula:

[0072]

[0073] wherein ΔE Nj is the carbon emission reduction intensity factor of node j.

[0074] The carbon emission factor is corrected based on the carbon emission reduction intensity factor to obtain a dynamic carbon emission factor, including,

[0075] The carbon emission factor is corrected according to the following formula:

[0076] E' Nj = E Nj + ΔE Nj

[0077] wherein E' Nj is the dynamic carbon emission factor; E Nj is the carbon emission factor of node j, ΔE Nj is the carbon emission reduction intensity factor of node j.

[0078] The method further includes a block chain technology-based storage method for realizing multi-time and space storage of the dynamic carbon emission factor, including,

[0079] Step a, determining the type and architecture of the block chain platform, selecting a block chain platform that meets the requirements; designing a smart contract for data storage, including defining storage structure, access authority and data verification rules;

[0080] Step b, determining the source of network carbon emission intensity and carbon emission reduction data, including user subjects, electricity consumption, electricity saving, and electricity types; storing the collected data on the block chain and updating the relevant data records in real time;

[0081] Step c, deploying the designed smart contract to the selected block chain platform and ensuring correct execution of the contract;

[0082] Step d, when a specific event occurs, the smart contract generates a corresponding record; the record contains the relevant timestamp, dynamic carbon emission factor and emission reduction amount;

[0083] Step e, design a user interface and data visualization tool for viewing and analyzing record data.

[0084] A power grid dynamic carbon emission factor calculation system considering bidirectional traceability correction, comprising,

[0085] A carbon emission factor calculation module configured to calculate carbon flow based on power grid flow results, trace carbon emission sources from the network layer to the node from top to bottom, and obtain carbon emission factors;

[0086] A carbon emission reduction intensity factor calculation module configured to trace carbon emission reduction intensity factors from the park to the node from bottom to top;

[0087] A correction module configured to correct the carbon emission factor based on the carbon emission reduction intensity factor to obtain a dynamic carbon emission factor.

[0088] After adopting the above scheme, the beneficial effects of the present application are that, compared with the prior art, the power grid dynamic carbon emission factor calculation method and system considering bidirectional traceability correction in the present application considers the influence of the emission reduction interaction behavior of park users on the power grid carbon emission distribution, the node carbon emission factor is traced from top to bottom and from bottom to top, which can better adapt to the changes of regional multi-agent carbon emission and carbon emission reduction behavior, and realize dynamic updating of the carbon emission factor; the record method based on the blockchain technology realizes multi-time and space record of the dynamic carbon emission factor, ensures that the dynamic carbon emission factor data cannot be tampered with, and the emission process is traceable. BRIEF DESCRIPTION OF DRAWINGS

[0089] Figure 1 The flowchart of the present application is shown in the figure;

[0090] Figure 2 The IEEE33 node power grid system topology diagram is shown in the figure;

[0091] Figure 3 The node load distribution diagram is shown in the figure;

[0092] Figure 4 The top-down carbon emission traceability and carbon emission factor calculation result schematic diagram is shown in the figure;

[0093] Figure 5 The bottom-up carbon emission reduction traceability and carbon emission factor calculation result schematic diagram is shown in the figure. DETAILED DESCRIPTION

[0094] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described below clearly and completely with reference to the drawings in the embodiments of the present application. The described embodiments of the present application are only a part of the embodiments of the present application, rather than all the embodiments. Based on the spirit of the present application, all the other embodiments of the present application not described in the present application obtained by those skilled in the art without creative work according to the embodiments described in the present application should belong to the protection scope of the present application.

[0095] Figure 1 The flowchart of the power grid dynamic carbon emission factor calculation method considering bidirectional traceability correction is shown. The first aspect of the present application relates to a power grid dynamic carbon emission factor calculation method considering bidirectional traceability correction, which comprises steps (1), (2) and (3).

[0096] Step (1), carbon flow calculation based on power grid flow results, tracing carbon emission sources from network layer to nodes from top to bottom to obtain node carbon emission factors.

[0097] Further, step (1) specifically comprises:

[0098] (11) Based on the power grid flow results, carbon flow calculation is performed to trace the carbon emission sources from the network layer to the nodes from top to bottom to obtain the node carbon emission factors, comprising:

[0099] Obtain real-time data such as node load, generator output and network topology parameters, etc.

[0100] AC power flow calculation to obtain branch power flow and network loss;

[0101] Power decomposition, allocating power to each branch, each node load and network loss; wherein, according to the AC power flow calculation results, a downstream power flow distribution matrix is constructed, and according to the downstream power flow distribution matrix, the power is decomposed into the power drawn by each node load from the generator, the power drawn by each branch from the generator and the network loss power borne by the generator;

[0102] Generation carbon emission allocation, based on the power decomposition results, allocating generation carbon emission to each branch, each node load and network loss;

[0103] Node carbon emission factor calculation, calculating node carbon intensity.

[0104] (12) Power decomposition includes power drawn by load from generator, power drawn by branch from generator and network loss power borne by generator. Taking a power system containing n nodes as an example, a downstream power flow distribution matrix is defined, which represents the relationship between generator power and node power:

[0105] Tu P = P G

[0106]

[0107] where P G is the active power generation matrix of all nodes, P = [P1 P2... P n ] T is the outflow power matrix of all nodes, T u is the downstream power flow distribution matrix, T u,ki is the kth row and ith column element in matrix T u , P ki is the power of branch k-i; U k is the upstream node set of node k, i.e., the node set directly connected to node k and having active power flowing to node k; P i is the active power flowing through node i.

[0108] wherein the power calculation method of the load drawn from the generator is:

[0109] The power component P Lk,Gi drawn by the load of node k from the generator of access node i is represented as:

[0110]

[0111] wherein P Lk is the load of node k, P Gi is the generator output of node i, and P k is the power flowing through node k.

[0112] wherein the power calculation method of the branch drawn from the generator is:

[0113] The contribution P kj of the generator of access node i to the power P kj,Gi of branch k-j is:

[0114]

[0115] wherein the power calculation method of the network loss borne by the generator is:

[0116] Similarly, the contribution P of the generator of access node i to the network loss of branch k-j can be represented as:

[0117]

[0118] ​(13) The power generation carbon emission allocation includes allocating the power generation carbon emission to each node load, each branch power and network loss. Based on the aforementioned power generation power allocation result, the power allocation result of each branch, each node load and generator is multiplied by the carbon emission intensity of the corresponding generator set, so as to obtain the power generation carbon emission allocation result of each branch, each node load and generator.

[0119] The expression for allocating the power generation carbon emission to each node load is:

[0120]

[0121] In the formula, C Lk,Gi is the carbon flow rate component of the node k load to be borne by the unit of the access node i, e Gi is the carbon emission intensity of the generator set of the access node i.

[0122]

[0123] In the formula, C Lk is the total carbon flow rate of the node k, and n is the number of nodes of the power system.

[0124] The expression for allocating the power generation carbon emission to each branch power is:

[0125]

[0126] In the formula, C kj,Gi is the carbon flow rate component of the branch k-j to be borne by the generator set of the access node i.

[0127]

[0128] In the formula, C kj is the total carbon flow rate of the branch k-j.

[0129] The expression for allocating the power generation carbon emission to network loss is:

[0130] The carbon flow rate corresponding to the active loss of the branch k-j is:

[0131]

[0132] In the formula, is the carbon flow rate component of the branch k-j network loss to be borne by the generator set of the access node i.

[0133]

[0134] In the formula, is the total carbon flow rate of the branch k-j network loss.

[0135] (14) The node carbon emission factor calculation method is:

[0136] The node carbon emission factor is the ratio of the sum of the branch carbon flow rate flowing into the node to the total outgoing power of the node, which describes the equivalent carbon dioxide reduced to the power generation side per unit of electricity used by the node, with the unit of tCO2 / (MW·h). For node j, the node carbon emission factor can be expressed as:

[0137]

[0138] In the formula, E Nj is the carbon emission factor of node j, U j is the set of upstream nodes of node j.

[0139] Step (2), considering the influence of the emission reduction interactive behavior of the park users on the carbon emission distribution of the power grid, the node carbon emission factor is corrected from the park to the node from bottom to top, and the dynamic updating of the carbon emission factor is realized;

[0140] Further, step (2) specifically includes:

[0141] (21) Considering the influence of the emission reduction interactive behavior of the park users on the carbon emission distribution of the power grid, the node carbon emission factor is corrected from the park to the node from bottom to top, including:

[0142] Fusing and aggregating the low-carbon behavior power changes of the park multi-agent users;

[0143] From the park to the node from bottom to top, the dynamic carbon emission factor is calculated.

[0144] (22) The park multi-agent users mainly include residential users, small and medium-sized industrial and commercial users, and distributed clean energy. The emission reduction interactive behavior of the park users mainly includes demand response, power saving and green power trading behaviors.

[0145] The fusing and aggregating expression of the low-carbon behavior power changes of the park multi-agent users is:

[0146]

[0147] In the formula, P sum (t) is the fusing and aggregating power of the low-carbon behavior, ΔP r,i (t) is the power reduction amount of the residential users, ΔP b,i is the power reduction amount of the small and medium-sized industrial and commercial users, ΔP d,i (t) is the power generation change amount of the distributed clean energy; N1 is the number of residential users, N2 is the number of small and medium-sized industrial and commercial users, and N3 is the number of distributed clean energy.

[0148] (23) From the park to the node, the low-carbon behavior of the multi-agent user in the park is aggregated and equivalent to the virtual generator injection power from bottom to top.

[0149] P F (t)=-P sum (t)

[0150] P F (t) is the injection power of the equivalent generator.

[0151] (24) The equivalent generator injection power is proportionally allocated:

[0152] B d P=P F

[0153]

[0154] P d is the inverse flow distribution matrix, B d,ki is the element in the kth row and the ith column of the matrix B d , P=[P1 P2...P n ] T is the outflow power matrix of each node, P F is the injection power matrix of the equivalent generator of each node, P Fi is the equivalent generator power of access node i, P Lk,Fi is the contribution of the equivalent generator power of access node i to the load of node k, P kj,Fi is the contribution of the equivalent generator power of access node i to the power of branch k-j, is the contribution of the equivalent generator power of access node i to the loss of branch k-j.

[0155] (25) The equivalent generator injection carbon is proportionally allocated:

[0156]

[0157]

[0158] P Lk,Fi is the contribution of the equivalent generator carbon flow rate of access node i to the load of node k, e Fi is the carbon emission factor of node i calculated according to the top-down tracing, C Lk is the total carbon flow rate of node k load.

[0159]

[0160] P kj,FiC kj C is the total carbon flow rate of branch k-j.

[0161]

[0162] wherein, C is the contribution of the equivalent generator carbon flow rate of node i to the branch k-j network loss, C is the total carbon flow rate of branch k-j network loss.

[0163] (26) Similar to the top-down hierarchical tracing method, a carbon emission reduction intensity factor calculation method considering the low-carbon interaction behavior of park users can be obtained, and the updating and correction of dynamic carbon emission factors can be realized.

[0164]

[0165] E' Nj = E Nj + ΔE Nj

[0166] wherein ΔE Nj is the carbon emission reduction intensity factor of node j, E' Nj is the carbon emission factor of node j after correction.

[0167] Step (3), based on the evidence storage method of the blockchain technology, the multi-time and space storage of dynamic carbon emission factors is realized, which ensures that the dynamic carbon emission factor data cannot be tampered with, and the emission process can be traced.

[0168] Further, step (3) specifically includes:

[0169] (31) Use blockchain technology to store evidence and trace the carbon emission intensity factor and time stamp of multiple time sections and other electronic data information. Combined with abstract algorithms, digital signatures, digital certificates and other technical means, the authenticity, integrity and effectiveness of electronic data are guaranteed. The use of blockchain technology makes the data tamper-proof, and the data or information stored therein forms a linear, time-ordered "event chain" with characteristics of unforgeability, full trace, traceability, openness, transparency, collective maintenance, etc.

[0170]

[0171] (32) The multi-time and space storage method of dynamic carbon emission factors specifically includes:

[0172] 1) Design a blockchain evidence storage system architecture

[0173] a) Determine the type and architecture of the blockchain platform, and select a suitable blockchain platform.

[0174] b) Designing a smart contract for data storage, including defining storage structure, access rights, and data verification rules.

[0175] 2) Data collection and storage

[0176] a) Determine the sources of data related to network carbon intensity and carbon reduction, including user entities, electricity consumption, electricity saving, and electricity types.

[0177] b) Design a secure and reliable data collection system to ensure the authenticity and credibility of data sources.

[0178] c) Store the collected data on the blockchain and update the relevant data records in real time.

[0179] 3) Smart contract operation and data verification

[0180] a) Deploy the designed smart contract to the selected blockchain platform and ensure the correct execution of the contract.

[0181] b) Implement relevant data verification logic in the smart contract, including rule checking and confirmation of carbon intensity and carbon reduction data.

[0182] 4) Generate storage records

[0183] a) When certain events occur (such as the start of a new carbon reduction project or the achievement of carbon reduction targets), the smart contract will generate corresponding storage records.

[0184] b) Storage data will include relevant timestamps, dynamic carbon emission factors, and reduction amounts to ensure data tamper resistance and integrity.

[0185] 5) Data visualization and traceability

[0186] a) Design user interfaces and data visualization tools to allow stakeholders to easily access and analyze storage data.

[0187] b) Support carbon intensity and carbon reduction data traceability and flow analysis to fully understand the sources and changes of relevant data.

[0188] In the second aspect of the invention, a power grid dynamic carbon emission factor calculation system considering bidirectional traceability correction is provided, which includes a calculation module and a storage module; wherein,

[0189] The calculation module is used for top-down and bottom-up traceability, considers the interactive behavior of park users for emission reduction, and updates the dynamic carbon emission factor; specifically including:

[0190] The carbon emission factor calculation module is configured to calculate carbon flow based on the power grid flow result, trace carbon emission sources from the network layer to the nodes from top to bottom, and obtain carbon emission factors.

[0191] The carbon emission reduction intensity factor calculation module is configured to trace carbon emission reduction intensity factors from the park to the nodes from bottom to top, and obtain carbon emission reduction intensity factors.

[0192] The correction module is configured to correct the carbon emission factors based on the carbon emission reduction intensity factors to obtain dynamic carbon emission factors.

[0193] The storage module is configured to store the dynamic carbon emission factors obtained by the calculation module in multiple space-time to ensure that the carbon emission intensity data is tamper-proof and the emission process is traceable.

[0194] The system provided by the embodiment of the application can be implemented in software and / or hardware, and can be configured in a terminal device.

[0195] It should be noted that in the above-described embodiments of the determination system, each unit and module included is only divided according to functional logic, but is not limited to the above-described division, as long as the corresponding functions can be implemented; in addition, the specific names of each functional unit are only for easy mutual differentiation, and do not limit the protection scope of the application. The modules described as separate components can or can not be physically separated, and the components shown as modules can or can not be physical modules, i.e., they can be located in one place or distributed on multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment. Those skilled in the art can clearly understand that each embodiment can be realized by means of software and necessary general hardware platform, and of course, it can also be realized by hardware only, as long as the function or action can be realized.

[0196] The simulation verification of the application is described below.

[0197] In this paper, the IEEE 33-node distribution network system is taken as an example, and the topological structure diagram is as shown in Figure 2 The 1st node, the 21st node and the 30th node are assumed to be the upper power supply, and the carbon emission intensity of different nodes is different, and the carbon emission intensity factors of the upper power supply are set to 0.5703tCO2 / MWh, 0.525tCO2 / MWh and 0.875tCO2 / MWh respectively.

[0198] The load distribution diagram of the 33 nodes is as shown in Figure 3As shown, each node exhibits different electricity consumption and carbon emission behaviors at different times. It can be observed that nodes 24 and 25 have higher load demands, while node 11 has lower load demands.

[0199] A top-down calculation of carbon emission sources and carbon emission factors was performed on this network topology, and the results are as follows: Figure 4 As shown in the figure, the branch power flow, branch carbon flow density distribution, and node carbon emission factor calculation results are reflected in the figure. Different environmental attributes of various upstream power sources will lead to differences in node carbon emission factors. Simulation results show that nodes closer to high-carbon-emission power sources have higher carbon emission factors, while nodes closer to low-carbon-emission power sources have lower carbon emission factors. Among the three upstream power sources, node 30 has the highest carbon emission factor, and node 21 has the lowest. The node carbon emission factor is related to the carbon emission intensity of the injected power. Near node 30, the node carbon emission factor is mostly 0.875. For nodes 2-7, 18-20, 23-24, 26-28, and 31-33, the power flow into these nodes originates from only one upstream power source or one adjacent node. Therefore, the node carbon emission factor of these nodes should be consistent with the carbon emission intensity of the upstream node providing active power flow or the upstream power source.

[0200] Similarly, taking the IEEE 33-node distribution network system as an example, considering users' carbon emission reduction behavior for bottom-up carbon emission tracing, assuming that users at nodes 8 and 24 have reduced their electricity consumption by 0.1 MWh and 0.2 MWh respectively, this reduction can be equated to the injected power of a virtual generator, with its injected carbon emission intensity set to a negative value. Based on the calculation results of node carbon emission intensity in the top-down hierarchical tracing method, the initial carbon emission intensity factors for nodes 8 and 24 are set to 0.5506 tCO2 / MWh and 0.5703 tCO2 / MWh respectively.

[0201] The calculation results of bottom-up carbon reduction source tracing and carbon reduction intensity factor are as follows: Figure 5 As shown in the figure, the branch power flow changes, branch carbon flow density distribution, and node carbon reduction intensity factor calculation results are illustrated by the user's carbon reduction behavior. When negative carbon emission intensity is injected into the grid, each node has a corresponding carbon reduction intensity factor. The node's carbon reduction intensity factor is determined by the injected carbon emission factor of the reducing node. It can be observed that the node carbon reduction intensity factor injected by virtual generator No. 24 is -0.0119, and the node carbon reduction intensity factor injected by virtual generator No. 8 is -0.0058. The injected power of some nodes is jointly provided by nodes No. 8 and No. 24, and the node carbon reduction intensity factor is a linear combination of the two.

[0202] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application but not to limit it, and although the present application has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that the specific embodiments of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and any modification or equivalent replacement without departing from the spirit and scope of the present application should be covered in the protection scope of the claims of the present application.

Claims

1. A method for calculating the dynamic carbon emission factor of a power grid considering bidirectional source tracing correction, characterized in that: include, Carbon flow is calculated based on power grid flow results, and carbon emission sources are traced from the network layer to the nodes from top to bottom to obtain carbon emission factors; By tracing the carbon emission reduction intensity factor from the bottom up from the park to the node, the carbon emission reduction intensity factor can be obtained. The carbon emission factor is modified based on the carbon emission reduction intensity factor to obtain the dynamic carbon emission factor; Among them, the carbon emission reduction intensity factor is obtained by tracing the source from the park to the node from the bottom up, including, The changes in the low-carbon behavior power of multiple users in the park are aggregated to obtain the aggregated power of low-carbon behavior. The combined power of the aforementioned low-carbon behavior is equivalent to the power injected by a virtual generator; Construct a countercurrent power flow distribution matrix and decompose the equivalent generator injected power into contributions to the load of each node, each branch, and network losses respectively; Based on the aforementioned injected power decomposition results, the equivalent generator injected carbon emissions are decomposed into the total carbon flow rate borne by each node load, each branch, and network loss respectively. Calculate the carbon emission reduction intensity factor of each node based on the total inflow carbon flow rate and total outflow power of the branch where each node is located. Among them, the park's multiple users include residential users, small and medium-sized industrial and commercial users, and distributed clean energy; The convergent expression for the low-carbon behavior power changes of multiple users at the park level: In the formula, P sum (t) represents the fusion power of low-carbon behavior, ΔP r,i (t) represents the reduction in electricity consumption for residential users, ΔP b,i For the reduction in electricity consumption by small and medium-sized industrial and commercial users, ΔP d,i (t) represents the change in power generation from distributed clean energy; N1 represents the number of residential users, N2 represents the number of small and medium-sized industrial and commercial users, and N3 represents the number of distributed clean energy sources. Tracing back from the bottom up from the park to the nodes, the low-carbon behaviors of multiple users in the park are integrated and their combined power is equivalent to the power injected by a virtual generator: P F (t)=-P sum (t) In the formula, P F (t) represents the injected power of the equivalent generator; Decompose the equivalent generator injected power: B d P=P F In the formula, B d For the countercurrent power flow distribution matrix, B d,ki For matrix B d The element in the k-th row and i-th column is P = [P1 P2 ... P]. n ] T P represents the power outflow matrix for each node. F Let P be the injected power matrix of the equivalent generator at each node. Fi P represents the equivalent generator power of node i. Lk,Fi P represents the contribution of the equivalent generator power of node i to the load of node k. kj,Fi Let the equivalent generator power of node i contribute to the power of branch kj. The contribution of the equivalent generator power of access node i to the network loss of branch kj; P ki For branch ki power; U k Let P be the set of upstream nodes of node k, that is, the set of nodes directly connected to node k and whose active power flows to k; i Let be the active power flowing through node i, and n be the number of nodes in the power system; P Lk For the load of node k, P kj For the generator at node i, the power of branch kj is... The generator at access node i causes network loss on branch kj. The equivalent generator is injected into the carbon emissions for decomposition: In the formula, C Lk,Fi e represents the contribution of the equivalent generator carbon flow rate of node i to the load of node k. Fi Let C be the carbon emission factor of node i. Lk P represents the total carbon flow rate at node k load; k Let be the power flowing through node k; In the formula, C kj,Fi Let C be the contribution of the equivalent generator carbon flow rate at node i to branch kj. kj The total carbon flow rate of branch kj; In the formula, Let be the contribution of the equivalent generator carbon flow rate at node i to the network loss in branch kj. The total carbon flow rate of the branch kj network loss; The carbon emission reduction intensity factor is calculated using the following formula: In the formula, ΔE Nj Let be the carbon emission reduction intensity factor for node j.

2. The method as described in claim 1, characterized in that: Carbon flow calculations are performed based on power grid flow results. Carbon emission sources are traced from the network layer down to the nodes to obtain carbon emission factors, including... Obtain real-time data of power grid parameters; Perform AC power flow calculations to obtain the power flow and network losses of each branch of the power grid; Based on the AC power flow calculation results, the power generation is decomposed into the power drawn by each node load from the generator, the power drawn by each branch from the generator, and the power loss borne by the generator. Based on the aforementioned power generation decomposition results, the carbon emissions from power generation are decomposed into the total carbon flow rate borne by each node load, each branch, and network loss. The carbon emission factor of each node is calculated based on the total inflow carbon flow rate and total outflow power of the branch to which each node is located.

3. The method as described in claim 2, characterized in that: Based on the AC power flow calculation results, the generating power is decomposed into the power drawn by each node load from the generator, the power drawn by each branch from the generator, and the power loss borne by the generator, including... Constructing the downstream power flow distribution matrix T u : T u P=P G In the formula, P G Let P be the active power output matrix of the generators at each node, where P = [P1 P2 ... P2 ... P3 ... P4 ... P5 ... P6 ... P7 ... P8 ... P9 ... n ] T Let T be the outflow power matrix for each node. u,ki For matrix T u The element in the k-th row and i-th column of P; ki For branch ki power; U k Let P be the set of upstream nodes of node k, that is, the set of nodes directly connected to node k and whose active power flows to k; i Let be the active power flowing through node i, and n be the number of nodes in the power system; The method for calculating the power drawn by the node load from the generator is as follows: The power component P drawn by the load at node k from the generator at node i Lk,Gi Represented as: In the formula, P Lk For the load of node k, P Gi For the generator output at node i, P k Let be the power flowing through node k; The method for calculating the power drawn from the generator by the branch is as follows: The generator at node i supplies power P to branch kj. kj Contribution share P kj,Gi for: The method for calculating the grid loss power borne by the generator is as follows: Similarly, the generator at access node i causes network loss in branch kj. Contribution share Represented as:

4. The method as described in claim 3, characterized in that: Based on the aforementioned power generation decomposition results, the carbon emissions from power generation are decomposed into the total carbon flow rate borne by each node load, each branch, and network losses, including... The load at node k carries the carbon flow rate component C of the unit connected to node i. Lk,Gi for: In the formula, e Gi The carbon emission intensity of the generator set connected to node i; In the formula, C Lk The total carbon flux at node k; Branch kj carries the carbon flow rate component C of the generator set connected to node i. kj,Gi for: In the formula, C kj The total carbon flow rate of branch kj; The branch network loss carries the carbon flow rate component of the generator set connected to node i. for: In the formula, The total carbon flow rate is the loss rate of the branch kj network.

5. The method as described in claim 1, characterized in that: Calculate the node carbon emission factor, including, for node j, its carbon emission factor is expressed as: In the formula, E Nj C is the carbon emission factor of node j; kj The total carbon flow rate of branch kj; The total carbon flow rate of the branch kj network loss; U j Let P be the set of upstream nodes of node j; j Let be the active power flowing through node j.

6. The method as described in claim 1, characterized in that: Based on the aforementioned carbon emission reduction intensity factor, the carbon emission factor is modified to obtain a dynamic carbon emission factor, including: The carbon emission factor is corrected according to the following formula: E' Nj =E Nj +ΔE Nj In the formula, E' Nj E is a dynamic carbon emission factor. Nj Let E be the carbon emission factor at node j. Nj Let be the carbon emission reduction intensity factor for node j.

7. The method as described in claim 1, characterized in that: It also includes blockchain-based evidence storage methods to achieve multi-temporal and spatiotemporal evidence storage of dynamic carbon emission factors, including... Step a: Determine the type and architecture of the blockchain platform, and select a blockchain platform that meets the requirements; Design smart contracts for data notarization, including defining storage structure, access permissions, and data verification rules; Step b, determine the sources of data related to network carbon emission intensity and carbon emission reduction, including user entities, electricity consumption, electricity savings, and electricity consumption type; The collected data is stored on the blockchain and the relevant data records are updated in real time; Step c: Deploy the designed smart contract to the selected blockchain platform and ensure the contract is executed correctly; Step d: When a specific event occurs, the smart contract generates a corresponding evidence record; the evidence data includes relevant timestamps, dynamic carbon emission factors, and emission reduction amounts. Step e involves designing a user interface and data visualization tools for viewing and analyzing evidence data.

8. A power grid dynamic carbon emission factor calculation system considering bidirectional source tracing correction, characterized in that: include, The carbon emission factor calculation module is configured to perform carbon flow calculation based on the power grid flow results, and trace the carbon emission sources from the network layer to the nodes from top to bottom to obtain the carbon emission factor; The carbon emission reduction intensity factor calculation module is configured to trace back the source from the park to the node from bottom to top to obtain the carbon emission reduction intensity factor; as well as, The correction module is configured to correct the carbon emission factor based on the carbon emission reduction intensity factor to obtain a dynamic carbon emission factor. Among them, the carbon emission reduction intensity factor is obtained by tracing the source from the park to the node from the bottom up, including, The changes in the low-carbon behavior power of multiple users in the park are aggregated to obtain the aggregated power of low-carbon behavior. The combined power of the aforementioned low-carbon behavior is equivalent to the power injected by a virtual generator; Construct a countercurrent power flow distribution matrix and decompose the equivalent generator injected power into contributions to the load of each node, each branch, and network losses respectively; Based on the aforementioned injected power decomposition results, the equivalent generator injected carbon emissions are decomposed into the total carbon flow rate borne by each node load, each branch, and network loss respectively. Calculate the carbon emission reduction intensity factor of each node based on the total inflow carbon flow rate and total outflow power of the branch where each node is located. Among them, the park's multiple users include residential users, small and medium-sized industrial and commercial users, and distributed clean energy; The convergent expression for the low-carbon behavior power changes of multiple users at the park level: In the formula, P sum (t) represents the fusion power of low-carbon behavior, ΔP r,i (t) represents the reduction in electricity consumption for residential users, ΔP b,i For the reduction in electricity consumption by small and medium-sized industrial and commercial users, ΔP d,i (t) represents the change in power generation from distributed clean energy; N1 represents the number of residential users, N2 represents the number of small and medium-sized industrial and commercial users, and N3 represents the number of distributed clean energy sources. Tracing back from the bottom up from the park to the nodes, the low-carbon behaviors of multiple users in the park are integrated and their combined power is equivalent to the power injected by a virtual generator: P F (t)=-P sum (t) In the formula, P F (t) represents the injected power of the equivalent generator; Decompose the equivalent generator injected power: B d P=P F In the formula, B d For the countercurrent power flow distribution matrix, B d,ki For matrix B d The element in the k-th row and i-th column is P = [P1 P2 ... P]. n ] T P represents the power outflow matrix for each node. F Let P be the injected power matrix of the equivalent generator at each node. Fi P represents the equivalent generator power of node i. Lk,Fi P represents the contribution of the equivalent generator power of node i to the load of node k. kj,Fi Let the equivalent generator power of node i contribute to the power of branch kj. The contribution of the equivalent generator power of access node i to the network loss of branch kj; P ki For branch ki power; U k Let P be the set of upstream nodes of node k, that is, the set of nodes directly connected to node k and whose active power flows to k; i Let be the active power flowing through node i, and n be the number of nodes in the power system; P Lk For the load of node k, P kj For the generator at node i, the power of branch kj is... The generator at access node i causes network loss on branch kj. The equivalent generator is injected into the carbon emissions for decomposition: In the formula, C Lk,Fi e represents the contribution of the equivalent generator carbon flow rate of node i to the load of node k. Fi Let C be the carbon emission factor of node i. Lk P represents the total carbon flow rate at node k load; k Let be the power flowing through node k; In the formula, C kj,Fi Let C be the contribution of the equivalent generator carbon flow rate at node i to branch kj. kj The total carbon flow rate of branch kj; In the formula, Let be the contribution of the equivalent generator carbon flow rate at node i to the network loss in branch kj. The total carbon flow rate of the branch kj network loss; The carbon emission reduction intensity factor is calculated using the following formula: In the formula, ΔE Nj Let be the carbon emission reduction intensity factor for node j.

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