A method and system for tracking multiple carbon emission flows taking into account carbon responsibility allocation of network loss

Abstract

This invention belongs to the field of electrical engineering technology and discloses a complex carbon emission flow tracking method and system that considers the allocation of carbon responsibility for network losses. The method includes: solving an AC power flow calculation model to obtain a basic active power state transition matrix, an active power loss state transition matrix, and a reactive power loss state transition matrix; utilizing the Markov flow network concept, and combining the solution of the basic active power state iteration equation, iterating the initial carbon emission flow until a steady state is reached to obtain a basic carbon potential; combining and solving the state iteration equation separately, iterating the virtual carbon source of network losses until a steady state is reached to obtain the additional carbon potential caused by active power loss and the additional carbon potential caused by reactive power loss, and thus obtaining the complex carbon potential of each node in the power system. This invention effectively solves the problem that carbon emissions caused by line network losses cannot be reasonably allocated in the indirect carbon emission accounting process of the power system, ensuring the accuracy and fairness of demand-side carbon emission accounting.

Description

Technical Field

[0001] This invention belongs to the field of electrical engineering technology, and more specifically, relates to a method and system for tracking multiple carbon emission streams that takes into account the carbon liability sharing of grid losses. Background Technology

[0002] With the deep integration of the electricity market and the carbon market, accurately tracing the carbon footprint of micro-users in the active distribution network is crucial for achieving fair carbon responsibility sharing.

[0003] However, existing carbon flow tracing technologies mostly employ scalar models, relying solely on active power topology for source tracing. In active distribution networks where source-load roles shift rapidly and power flow characteristics change frequently, this classic carbon emission flow model (scalar model) based on one-dimensional real-domain theory ignores the enormous carbon emissions from network losses caused by long-distance reactive power transmission, leading to severe "pseudo-greening" and unfair carbon accounting. Therefore, achieving accurate carbon flow tracing within the distribution network and ensuring fairness in carbon responsibility allocation is the most pressing and critical challenge in the current electricity-carbon coupling market. Summary of the Invention

[0004] In view of the above-mentioned defects or improvement needs of the existing technology, the present invention provides a method and system for tracking multiple carbon emission flows that take into account the carbon responsibility allocation of grid losses. Its purpose is to solve the blind spot in carbon emission accounting caused by reactive power, improve the accuracy of carbon flow tracking within the power grid system, and ensure the fairness of carbon responsibility allocation.

[0005] To achieve the above objectives, the present invention provides a method for tracking multiple carbon emission streams that takes into account the carbon liability sharing of grid losses, comprising: Under the boundary conditions of the power system, the AC power flow calculation model is solved to obtain the basic active power state transition matrix. Active power loss state transition matrix and reactive power loss state transition matrix ;in, This is the active power state transition matrix with no line loss. This is the state transition matrix corresponding to line losses caused by active power. This is the state transition matrix corresponding to line losses caused by reactive power; right Carbon emission flow vectors initially injected into each node of the power system by the generator The Markov state iteration equations satisfied between nodes are solved, and the carbon emission flow vectors of each node are obtained when the iteration reaches a steady state. ,use Calculate the fundamental carbon potential at each node ; right The active power loss carbon emission flow vector initially injected into each node of the power system by the virtual generator The Markov state iteration equations satisfied between nodes are solved, and the active power loss carbon emission flow vectors of each node are obtained when the iteration reaches steady state. ,use Calculate the active power loss-induced additional carbon potential at each node. ; right The reactive power loss carbon emission flow vector initially injected into each node of the power system by the virtual generator The Markov state iteration equations satisfied between nodes are solved, and the reactive power loss carbon emission flow vectors of each node are obtained when the iteration reaches steady state. ,use Calculate the additional carbon potential caused by reactive power loss at each node. ; Calculate the complex carbon potential at each node of the power system. , It represents an imaginary unit, enabling carbon emission flow tracking at various nodes in the power system.

[0006] Furthermore, Carbon emission flow vectors initially injected into each node of the power system by the generator The Markov state iteration equation satisfied between them is: ; In the formula, This represents the carbon emission flow vector of each node in the power system during the k-th iteration. In the initial iteration, k is the current iteration number; Correspondingly, the condition for iterating to a steady state is: and The difference between them is less than the preset empirical error threshold, and at this time... As the carbon emission flow vector of each node .

[0007] Furthermore, The active power loss carbon emission flow vector initially injected into each node of the power system by the virtual generator The Markov state iteration equation satisfied between them is: ; In the formula, This represents the active power loss carbon emission flow vector at each node of the power system in the k-th iteration. In the initial iteration, k is the current iteration number; Correspondingly, the condition for iterating to a steady state is: and The difference between them is less than the preset empirical error threshold, and at this time... As the active power loss carbon emission flow vector .

[0008] Furthermore, The reactive power loss carbon emission flow vector initially injected into each node of the power system by the virtual generator The Markov state iteration equation satisfied between them is: ; In the formula, This represents the reactive power loss carbon emission flow vector at each node of the power system in the k-th iteration. In the initial iteration, k is the current iteration number; Correspondingly, the condition for iterating to a steady state is: and The difference between them is less than the preset empirical error threshold, and at this time... As the reactive power loss carbon emission flow vector .

[0009] Furthermore, the AC power flow calculation model is solved to obtain the basic active power state transition matrix. Active power loss state transition matrix and reactive power loss state transition matrix ,include: Solve the AC power flow calculation model to obtain the active power flow topology and reactive power flow topology of the power system; Calculate the basic active state transition matrix. The active power loss state transition matrix The reactive power loss state transition matrix Middle element: ; ; ; in, , and They are respectively , , In characterizing power system nodes and nodes The line formed The corresponding basic active power state transition probabilities, active power-induced loss state transition probabilities, and reactive power-induced loss state transition probabilities; node basic active power flux. For nodes All upstream line injection nodes Active power and nodes The sum of active power injected by local generators; lossless transfer of active power flux at nodes. For nodes Active power flowing out of all downstream lines and nodes The sum of local active loads; lossless transfer of reactive power at nodes For nodes Reactive power flowing out of all downstream lines and nodes The sum of local reactive loads; For the node Flow to Node active power, For the node Flow to Node reactive power; , , The active power flow topology path is determined based on the aforementioned path. and The reactive power flow topology path is determined based on the aforementioned reactive power flow topology path.

[0010] Furthermore, the underlying carbon potential for: ; In the formula, For nodes The fundamental carbon potential, and the vector formed by the fundamental carbon potentials of each node, is the fundamental carbon potential. , for The middle represents the node carbon emission streams, The solution time interval for the AC power flow calculation model; The active power loss additional carbon potential for: ; in, Represents a node The active-induced carbon loss additional carbon potential is the vector formed by the active-induced carbon loss emission flows at each node. , for The middle represents the node The carbon emission stream that causes damage to the usefulness of the carbon emission stream; The reactive power loss additional carbon potential for: ; in, Represents a node The reactive power loss-induced additional carbon potential, and the vector formed by the reactive power loss-induced additional carbon potential of each node is the reactive power loss-induced additional carbon potential. , for The middle represents the node The reactive carbon emission stream.

[0011] Furthermore, the active power loss carbon emission flow vector initially injected by the virtual generator into each node of the power system is... for: ; In the formula, Initialize the power system node for the virtual generator The active power loss carbon emission flow, the vector formed by the active power loss carbon emission flows initially injected by the virtual generator into each node of the power system is: ; Lines caused by active power Line loss; The initial reactive power loss carbon emission flow vector injected by the virtual generator into each node of the power system for: : In the formula, Initialize the power system node for the virtual generator The reactive power loss carbon emission flow, the vector formed by the reactive power loss carbon emission flows initially injected by the virtual generator into each node of the power system is: ; Lines caused by reactive power Line loss.

[0012] The present invention also provides a multiple carbon emission stream tracking system that takes into account the carbon liability sharing of grid loss, including a computer-readable storage medium and a processor; The computer-readable storage medium is used to store executable instructions; The processor is used to read executable instructions stored in the computer-readable storage medium and execute the complex carbon emission stream tracking method that takes into account the carbon liability sharing of grid loss as described above.

[0013] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the complex carbon emission stream tracking method taking into account grid loss carbon liability allocation as described in any of the preceding claims.

[0014] The present invention also provides a computer program product, including a computer program that, when run on a computer, causes the computer to perform the complex carbon emission stream tracking method that takes into account grid loss carbon liability allocation as described above.

[0015] In summary, the above-described technical solutions conceived in this invention can achieve the following beneficial effects: (1) To address the problem that classical carbon emission flow models neglect the huge carbon emissions caused by reactive long-distance transmission due to network losses (line losses), resulting in non-negligible relative carbon accounting errors, this invention proposes a three-dimensional model comprising two stages (basic carbon potential solution stage and network loss-added carbon potential solution stage). , , The complex carbon flow tracing model can accurately trace and allocate the responsibility for carbon emissions caused by power transmission line losses. Specifically, this invention calculates the basic carbon potential of each node in the power network system by comprehensively considering the carbon flow characteristics inherent in active and reactive power. And the additional carbon potential caused by active power loss due to network losses. and reactive power loss due to additional carbon potential This leads to the obtaining of the node complex carbon potential, which is identical to the node complex power structure. In addition to the basic carbon potential, the node complex carbon potential also includes the active power loss-induced additional carbon potential and the reactive power loss-induced additional carbon potential caused by network losses (line losses), which can ensure the accuracy and fairness of load-side carbon emission accounting.

[0016] In summary, this invention applies Markov chains to carbon flow tracking and constructs a specific state transition matrix for iterative solution to obtain the basic carbon potential, the active power loss-induced additional carbon potential, and the reactive power loss-induced additional carbon potential. These are then synthesized into a node complex carbon potential. These features work together to form a complete new paradigm for complex carbon flow tracking based on Markov flow networks and state transition matrix iteration. This paradigm can accurately quantify the independent impact of active and reactive power losses in AC power grids on carbon emission flows and achieve accurate tracking of complex domain carbon emission flows that takes into account network loss responsibility, thus breaking through the theoretical limitations of traditional algorithms in the one-dimensional real domain. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the calculation process of the complex carbon emission flow model in this embodiment of the invention.

[0018] Figure 2 This is a topology diagram of the simulation test system of the present invention.

[0019] Figure 3 This is the power boundary diagram of the numerical test system of the present invention.

[0020] Figure 4 This is a graph verifying the performance of the model proposed in the example of this invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0022] Example 1 This invention provides a method for tracking multiple carbon emission streams that takes into account the carbon liability sharing of grid losses, comprising the following steps: S1. Determine the boundary conditions of the power network system, including the power network system topology, load conditions, power injection, and carbon source information. Based on the power network system topology, load conditions, and power injection, solve the AC power flow calculation model to obtain the active power flow topology path and reactive power flow topology path of the power network system. Based on the active power flow topology path, construct the basic active power state transition matrix using the Markov flow network concept. and active power loss state transition matrix Based on the reactive power flow topology, and utilizing the Markov flow network concept, a reactive power loss state transition matrix is ​​constructed. The carbon source information includes the carbon emission factor of the power source (generator). Basic active power state transition matrix. The active power state transition matrix does not include network (line) losses; the active power loss state transition matrix. Here are the state transition matrices corresponding to network losses caused by active power; and the state transition matrices corresponding to losses caused by reactive power. This is the state transition matrix corresponding to network losses caused by reactive power.

[0023] S2. Utilizing the concept of Markov flow networks, combined with the basic active state transition matrix. Solving the fundamental active state iterative equations, and iterating the initial carbon emission flow until steady state, yields the fundamental carbon potential of each node in the power grid system. ; S3. Based on the fundamental carbon potential obtained in step S2, combine it with the active power loss state transition matrix. and reactive power loss state transition matrix The state iteration equations (including the active power loss state iteration equation and the reactive power loss state iteration equation) are solved separately, and the virtual carbon source of network loss is iterated continuously until steady state is reached, so as to obtain the additional carbon potential of active power loss at each node of the power network system. and reactive power loss due to additional carbon potential ; S4. Based on the results of S2 and S3, the complex carbon potential of each node in the power network system is obtained. , It represents an imaginary unit, enabling carbon emission stream tracking.

[0024] As a specific implementation method, in step S1, the basic active power state transition matrix Active power loss state transition matrix and reactive power loss state transition matrix The formulas for calculating the elements are as follows: ; ; ; in, , and They are respectively , , The Middle Line number The elements of the column represent nodes in the power network system. and nodes The line formed The corresponding basic active state transition probability, active state transition probability caused by loss, and reactive state transition probability caused by loss. These represent the lines in the power network system. The two endpoints (nodes) are numbered. The value is determined based on the topology of the electronic network system; node basic active flux For nodes All upstream line injection nodes Active power and nodes The sum of active power injected by local generators; lossless transfer of active power flux at nodes. For nodes Active power flowing out of all downstream lines and nodes The sum of local active loads of nodes The local active load is the node Local generator-injected active power minus active power line losses; lossless transfer of reactive power at nodes. For nodes Reactive power flowing out of all downstream lines and nodes The sum of local reactive loads; For the node Flow to Node active power, For the node Flow to Node reactive power; , , Determining the active power flow topology path based on the power network system. and Determining the topology path based on reactive power flow.

[0025] As a specific implementation method, in step S2, based on the idea of ​​Markov flow networks, the basic active state iteration equation is: ; in, The vector represents the initial carbon emission flow of the generator injected into each node of the power network system. Each element in the vector represents the initial carbon emission flow of the generator injected into the corresponding node of the power network system. The power output of each node multiplied by its carbon emission factor is the initial carbon emission flow of the generator injected into the corresponding node of the power network system. The vector formed by the results of each node is the initial carbon injection vector. Let represent the intermediate variable in the k-th iteration, and represent the carbon emission flow vector of each node in the power grid system in the k-th iteration, where k is the k-th iteration. Initially, When the system reaches steady state ( and The difference between them is less than the preset empirical error threshold), so at this time , Let be the carbon emission flow vector of each node in the network when the system reaches stability. Then the basic carbon potential of each node can be calculated as: ; in, For nodes The basic carbon potential. for The middle represents the node The carbon emission flow, the vector formed by the basic carbon potential of each node is: , The time interval for solving the AC power flow calculation model.

[0026] As a specific implementation method, in step S3, the active power loss state iteration equation is: ; in, This represents the active power loss carbon emission flow vector initially injected into each node of the power network system by the virtual generator (a virtual carbon source for network losses, i.e., network losses). The initial injection node of the virtual generator... The positive impact of carbon emission streams , For the line Line losses caused by active power. This represents the active power loss carbon emission flow vector at each node of the power system in the k-th iteration. In the initial iteration, When the system reaches steady state ( and The difference between them is less than the preset empirical error threshold), so at this time , This represents the active power loss carbon emission flow vector of each node in the network when the system reaches stability.

[0027] The additional carbon potential caused by active power loss at the node can then be calculated as follows: ; in, Represents a node The added carbon potential that causes active damage for The middle represents the node The active-induced carbon emission flow is the vector formed by the active-induced carbon emission flows at each node, which represents the active-induced carbon potential. .

[0028] Similarly, the reactive power loss state iteration equation is: ; in, This represents the reactive power loss carbon emission flow vector initially injected into each node of the power network system by the virtual generator, where the virtual generator is initially injected into the node. Unproductive carbon emissions , For the line Line losses caused by reactive power; This represents the reactive power loss carbon emission flow vector at each node of the power system in the k-th iteration. In the initial iteration, When the system reaches steady state ( and The difference between them is less than the preset empirical error threshold), so at this time , This represents the reactive power loss carbon emission flow vector of each node in the network when the system reaches stability.

[0029] The additional carbon potential caused by reactive power loss at the node can then be calculated as follows: ; in, Represents a node The additional carbon potential caused by reactive power loss for The middle represents the node The reactive power loss carbon emission flow, the vector formed by the reactive power loss additional carbon potential at each node is the reactive power loss additional carbon potential. .

[0030] As a specific implementation method, in step S4, the real part of the complex carbon potential of each node consists of the basic carbon potential and the additional carbon potential caused by active power loss, and the imaginary part of the complex carbon potential of each node consists of the additional carbon potential caused by reactive power loss. The calculation formula for the complex carbon potential of each node is as follows: ; Among them, nodes Complex carbon potential It can be represented as: .

[0031] Complex carbon potential It can be applied in subsequent carbon metering or low-carbon scheduling.

[0032] Using an improved IEEE 33-node active distribution network operation simulation, a numerical example analysis is conducted to demonstrate the complex carbon flow tracing model and two-stage three-dimensional carbon flow tracing method proposed in this embodiment of the invention. The two stages include step S2, the solution stage for the basic carbon potential, and step S3, the solution stage for the additional carbon potential due to network losses. The three dimensions include the node basic carbon potential. Additional carbon potential caused by active power loss at nodes Node reactive power loss and additional carbon potential .

[0033] like Figure 2 As shown, the 24-hour baseload curve of the improved IEEE 33-bus system is scaled using the standard fluctuation multiplier curve from the IEEE RTS-96 reliability test system, and the normalized photovoltaic (PV) predicted output curve is synthesized using clear-sky irradiance data from NREL NSRDB. The carbon intensity of the external grid is fixed at 850 kg CO2 / MWh to highlight the impact of distributed generation in the active distribution network on the system's carbon potential. Furthermore, the carbon emission intensity of the micro gas turbine is set at 450 kg CO2 / MWh, with a maximum active and reactive power output of 0.3 MW; the distributed PV units are configured to have no reactive power support capability, with a maximum active power output of 0.5 MW.

[0034] Figure 3 The macroscopic power boundary of the test system is shown, illustrating the relationship between the combination of multiple power sources and total load demand. From Figure 3 The active power flow dispatching data shows that around noon, the output of distributed photovoltaic units significantly reduces the active power drawn from the main grid. However, from... Figure 3 The reactive power flow scheduling reveals that, since distributed photovoltaic (PV) units lack reactive power support capabilities, the increased reactive power demand during peak hours can only be provided by the remote main grid. This macro-level PQ supply mismatch determines that the active and reactive power flows in the test system will follow completely different topological paths, severely impacting the allocation logic of grid loss and carbon liability.

[0035] To demonstrate the effectiveness and necessity of the two-stage three-dimensional carbon flow tracing method (M3) in this invention, Figure 4 Two scenarios were set up at node 29: pure active load (Scenario A: P=0.1MW, Q=0) and heavy reactive load (Scenario B: P=0.1MW, Q=0.2MVar). Using the traditional scalar method M1 and the single-stage Markov method M2 (also a scalar model) as a comparison, the carbon flow algorithms M1 and M2, which only track active power flow, yielded the same calculation results, but both ignored the allocation of carbon responsibility for network losses. At t=12, the carbon penalty for network losses at node 29 was nearly a quarter of the carbon responsibility allocation result of the traditional algorithm, which strongly demonstrates the shortcomings of the classical carbon flow model in active distribution networks. In contrast, the method of this invention (M3), through the active power loss carbon penalty and reactive power loss carbon penalty of this invention, can accurately calculate the network loss carbon emission responsibility that node 29 needs to bear.

[0036] In summary, this invention reveals that the classical carbon emission flow model ignores the huge network loss carbon emissions caused by long-distance transmission of active and reactive power, leading to serious "pseudo-greening" and unfair carbon accounting. This is particularly evident during periods when local active load is completely covered by clean energy. Active load and heavy reactive load will still transfer grid loss and carbon penalties to the main grid. and (Not zero), especially heavy reactive loads will transfer significant grid loss carbon penalties to the main grid ( (Relatively large) If the traditional scalar carbon flow model continues to be used, it will generate a non-negligible relative carbon accounting error, allowing these pollution sources to systematically evade carbon taxes. The method of this invention can accurately trace and allocate the responsibility for carbon emissions caused by power transmission line losses. At the same time, the method of this invention shows good computational scalability on large-scale node testing systems and has the potential to support the real-time clearing efficiency of a large-scale electricity-carbon coupling market.

[0037] Example 2 This invention provides a complex carbon emission stream tracing system that takes into account the carbon responsibility allocation for grid loss, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the complex carbon emission stream tracing method that takes into account the carbon responsibility allocation for grid loss in Embodiment 1 above.

[0038] The relevant technical solutions are the same as above, and will not be repeated here.

[0039] Example 3 This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the complex carbon emission stream tracking method that takes into account grid loss carbon liability allocation in Embodiment 1 above.

[0040] Specifically, the memory may include high-speed random access memory, as well as non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital (SD) cards, flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0041] The relevant technical solutions are the same as above, and will not be repeated here.

[0042] Example 4 This invention provides a computer program product, including a computer program that, when run on a computer, causes the computer to perform the steps of the complex carbon emission stream tracking method that takes into account grid loss carbon liability allocation in Embodiment 1 above.

[0043] The relevant technical solutions are the same as above, and will not be repeated here.

[0044] Those skilled in the art will readily understand that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for tracking multiple carbon emission streams that takes into account the carbon liability sharing of network losses, characterized in that, include: Under the boundary conditions of the power system, the AC power flow calculation model is solved to obtain the basic active power state transition matrix. Active power loss state transition matrix and reactive power loss state transition matrix ;in, This is the active power state transition matrix with no line loss. This is the state transition matrix corresponding to line losses caused by active power. This is the state transition matrix corresponding to line losses caused by reactive power; right Carbon emission flow vectors initially injected into each node of the power system by the generator The Markov state iteration equations satisfied between nodes are solved, and the carbon emission flow vectors of each node are obtained when the iteration reaches a steady state. ,use Calculate the fundamental carbon potential at each node ; right The active power loss carbon emission flow vector initially injected into each node of the power system by the virtual generator The Markov state iteration equations satisfied between nodes are solved, and the active power loss carbon emission flow vectors of each node are obtained when the iteration reaches steady state. ,use Calculate the active power loss-induced additional carbon potential at each node. ; right The reactive power loss carbon emission flow vector initially injected into each node of the power system by the virtual generator The Markov state iteration equations satisfied between nodes are solved, and the reactive power loss carbon emission flow vectors of each node are obtained when the iteration reaches steady state. ,use Calculate the additional carbon potential caused by reactive power loss at each node. ; Calculate the complex carbon potential at each node of the power system. , It represents an imaginary unit, enabling carbon emission flow tracking at various nodes in the power system.

2. The method for tracking multiple carbon emission streams that takes into account grid loss carbon liability sharing as described in claim 1, characterized in that, Carbon emission flow vectors initially injected into each node of the power system by the generator The Markov state iteration equation satisfied between them is: ； In the formula, This represents the carbon emission flow vector of each node in the power system during the k-th iteration. In the initial iteration, k is the current iteration number; Correspondingly, the condition for iterating to a steady state is: and The difference between them is less than the preset empirical error threshold, and at this time... As the carbon emission flow vector of each node .

3. The method for tracking multiple carbon emission streams that takes into account grid loss carbon liability allocation as described in claim 1, characterized in that, The active power loss carbon emission flow vector initially injected into each node of the power system by the virtual generator The Markov state iteration equation satisfied between them is: ; In the formula, This represents the active power loss carbon emission flow vector at each node of the power system in the k-th iteration. In the initial iteration, k is the current iteration number; Correspondingly, the condition for iterating to a steady state is: and The difference between them is less than the preset empirical error threshold, and at this time... As the active power loss carbon emission flow vector .

4. The method for tracking multiple carbon emission streams that takes into account grid loss carbon liability sharing as described in claim 1, characterized in that, The reactive power loss carbon emission flow vector initially injected into each node of the power system by the virtual generator The Markov state iteration equation satisfied between them is: ； In the formula, This represents the reactive power loss carbon emission flow vector at each node of the power system in the k-th iteration. In the initial iteration, k is the current iteration number; Correspondingly, the condition for iterating to a steady state is: and The difference between them is less than the preset empirical error threshold, and at this time... As the reactive power loss carbon emission flow vector .

5. The method for tracking multiple carbon emission streams that takes into account the carbon liability sharing of network losses according to any one of claims 2-4, characterized in that, Solve the AC power flow calculation model to obtain the basic active power state transition matrix. Active power loss state transition matrix and reactive power loss state transition matrix ,include: Solve the AC power flow calculation model to obtain the active power flow topology and reactive power flow topology of the power system; Calculate the basic active state transition matrix. The active power loss state transition matrix The reactive power loss state transition matrix Middle element: ； ； ； In the formula, , and They are respectively , , In characterizing power system nodes and nodes The line formed The corresponding basic active power state transition probabilities, active power-induced loss state transition probabilities, and reactive power-induced loss state transition probabilities; node basic active power flux. For nodes All upstream line injection nodes Active power and nodes The sum of active power injected by local generators; lossless transfer of active power flux at nodes. For nodes Active power flowing out of all downstream lines and nodes The sum of local active loads; lossless transfer of reactive power at nodes For nodes Reactive power flowing out of all downstream lines and nodes The sum of local reactive loads; For the node Flow to Node active power, For the node Flow to Node reactive power; in, , , The active power flow topology path is determined based on the aforementioned path. and The reactive power flow topology path is determined based on the aforementioned reactive power flow topology path.

6. The method for tracing multiple carbon emission streams taking into account grid loss carbon liability allocation as described in claim 5, characterized in that, The basic carbon potential for: ； In the formula, For nodes The fundamental carbon potential, and the vector formed by the fundamental carbon potentials of each node, is the fundamental carbon potential. , for The middle represents the node carbon emission streams, The solution time interval for the AC power flow calculation model; The active power loss additional carbon potential for: ； in, Represents a node The active-induced carbon loss additional carbon potential is the vector formed by the active-induced carbon loss emission flows at each node. , for The middle represents the node The carbon emission stream that causes damage to the usefulness of the carbon emission stream; The reactive power loss additional carbon potential for: ； in, Represents a node The reactive power loss-induced additional carbon potential, and the vector formed by the reactive power loss-induced additional carbon potential of each node is the reactive power loss-induced additional carbon potential. , for The middle represents the node The reactive carbon emission stream.

7. The method for tracking multiple carbon emission streams that takes into account grid loss carbon liability sharing as described in claim 6, characterized in that, The initial active power loss carbon emission flow vector injected by the virtual generator into each node of the power system for: ； In the formula, Initialize the power system node for the virtual generator The active power loss carbon emission flow, the vector formed by the active power loss carbon emission flows initially injected by the virtual generator into each node of the power system is: ; Lines caused by active power Line loss; The initial reactive power loss carbon emission flow vector injected by the virtual generator into each node of the power system for: ： In the formula, Initialize the power system node for the virtual generator The reactive power loss carbon emission flow, the vector formed by the reactive power loss carbon emission flows initially injected by the virtual generator into each node of the power system is: ; Lines caused by reactive power Line loss.

8. A complex carbon emission stream tracing system that takes into account the carbon liability sharing of network losses, characterized in that, Includes computer-readable storage media and processors; The computer-readable storage medium is used to store executable instructions; The processor is used to read executable instructions stored in the computer-readable storage medium and execute the complex carbon emission stream tracking method according to any one of claims 1-7, which takes into account the carbon liability sharing of network losses.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the complex carbon emission stream tracking method as described in any one of claims 1-7, which takes into account the carbon liability sharing of network losses.

10. A computer program product, characterized in that, Includes a computer program that, when run on a computer, causes the computer to perform the complex carbon emission stream tracking method according to any one of claims 1-7, taking into account the carbon liability sharing of grid losses.

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