A power grid regulation method and system for carbon reduction

Abstract

The application discloses a kind of carbon reduction-oriented power grid regulation methods and systems, applied to carbon reduction regulation technical field of power grid, method includes: based on the electrical connection data of all topological nodes of target power grid, the power flow directed graph of target power grid is constructed;Carbon emission reasoning is carried out to power flow directed graph according to the current operating data of target power grid, and branch carbon flux density is obtained;According to the numerical comparison result of all branch carbon flux density, the carbon over-limit line of target power grid is determined, and the target carbon reduction amount of carbon over-limit line;The impedance adjustment amount of carbon over-limit line is calculated based on target carbon reduction amount, and power grid regulation instruction is generated according to impedance adjustment amount and the associated equipment information of carbon over-limit line;The execution process of power grid regulation instruction is simulated to obtain new branch carbon flux density;Based on branch carbon flux density and new branch carbon flux density, power grid regulation instruction is executed, and the carbon reduction regulation of target power grid is realized.The application improves the accuracy of carbon reduction regulation of power grid.

Description

Technical Field

[0001] This invention relates to the field of power grid carbon reduction and control technology, and in particular to a power grid control method and system for carbon reduction. Background Technology

[0002] Existing methods for regulating and controlling the carbon emissions of power grids typically involve: first, collecting grid operating parameters (e.g., injected power at grid nodes, transmitted power on grid lines, and carbon emission records of generating units); then, determining the carbon emission data for each node and line based on these parameters; next, identifying nodes or lines with high carbon emission intensity according to preset carbon emission level limits; finally, performing qualitative or quantitative analysis on these nodes or lines to obtain adjustment information for grid operating parameters; and then disseminating this information to the corresponding grid equipment for regulation.

[0003] Current grid control processes aimed at reducing carbon emissions operate in an open-loop manner. The entire process relies on the overall operation of the grid to formulate carbon reduction control strategies, without considering the inter-grid control effects. For example, reducing carbon emissions from a single line exceeding emission limits may increase emissions from other lines. This leads to inaccurate carbon reduction control results in existing grid control methods. Summary of the Invention

[0004] This invention provides a power grid control method and system for carbon reduction, in order to solve the technical problem that the carbon reduction control results of existing power grid control methods for carbon reduction are inaccurate.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a power grid regulation method for carbon reduction, comprising: Based on the electrical connection data of all topological nodes of the target power grid, a directed power flow graph of the target power grid is constructed; Carbon emission inference is performed on the directed power flow graph based on the current operating data of the target power grid to obtain the branch carbon flux density; Based on the numerical comparison results of the carbon flux density of all the branches, the carbon-exceeding lines of the target power grid and the target carbon reduction amount of the carbon-exceeding lines are determined. Based on the target carbon reduction amount, the impedance adjustment amount of the carbon-exceeding line is calculated, and based on the impedance adjustment amount and the associated equipment information of the carbon-exceeding line, a power grid control command is generated. The execution process of the power grid control command is simulated to obtain the new carbon flux density of the branch. Based on the comparison between the branch carbon flux density and the new carbon flux density of the branch, the power grid control command is executed to achieve carbon reduction control of the target power grid.

[0006] As one preferred embodiment, constructing the directed power flow graph of the target power grid based on the electrical connection data of all topological nodes of the target power grid includes: Based on the electrical connection data of all topological nodes in the target power grid, determine all adjacent node pairs with electrical connection relationships in the target power grid, as well as the power grid branches between each adjacent node pair; Based on the power flow direction between each of the adjacent node pairs and each of the power grid branches, a directed power flow graph of the target power grid is constructed.

[0007] As one preferred embodiment, the step of performing carbon emission inference on the directed power flow graph based on the current operating data of the target power grid to obtain the branch carbon flux density includes: Based on the branch power flow data, node load active power and generation-related data of the target power grid at the same moment, the analytical results of the node carbon potential balance relationship are determined. Based on the analysis results and the historical operating data of the target power grid, the normalized residual of each topological node under the candidate carbon potential vector is determined. Based on the normalized residual of each topological node, the residual fluctuation scale of each topological node and the target ratio of each topological node are obtained; the target ratio is the ratio of the absolute value of each normalized residual to the residual fluctuation scale. The target ratio of all the topological nodes is uniformly optimized and solved to obtain the nodal carbon potential of each topological node. Based on the nodal carbon potential of each of the topological nodes, the branch carbon flux density of each of the power grid branches is determined.

[0008] As one preferred embodiment, obtaining the residual fluctuation scale of each topological node based on the normalized residual of each topological node includes: Based on the normalized residual within the historical time window of each topological node, the historical fluctuation scale of each topological node is obtained. The historical fluctuation scale of each topological node is exponentially smoothed to obtain the residual fluctuation scale of each topological node.

[0009] As one preferred embodiment, the step of uniformly optimizing the target ratio of all the topological nodes to obtain the nodal carbon potential of each topological node includes: The target ratio is adjusted based on a preset loss function to obtain an optimized ratio; Based on the optimization ratio of each topological node, the candidate carbon potential vector is uniformly optimized to obtain the nodal carbon potential of each topological node.

[0010] As one preferred embodiment, the calculation of the impedance adjustment amount for the carbon-exceeding line based on the target carbon reduction amount includes: Based on the current operating data of the target power grid and the directed power flow graph, a power grid operation model is constructed; In the power grid operation model, the relationship between the carbon flux density and the equivalent reactance of the branch of the carbon-exceeding line is simulated to obtain the virtual carbon impedance of the carbon-exceeding line. In the power grid operation model, the influence relationship between the virtual carbon impedance and the target power grid is simulated to obtain the impedance adjustment amount of the carbon-exceeding line.

[0011] As one preferred embodiment, generating power grid control commands based on the impedance adjustment amount and the associated equipment information of the carbon-exceeding line includes: Based on the associated equipment information of the carbon-exceeding circuit, a control command conversion model is constructed; In the control command conversion model, the conversion relationship between the impedance adjustment amount and the equipment control parameters is simulated to obtain the equipment parameter adjustment amount; Power grid control commands are generated based on the adjustment amounts of the equipment parameters.

[0012] As one preferred embodiment, the simulation of the execution process of the power grid control command to obtain the new carbon flux density of the branch includes: In the power grid operation model, carbon emissions are simulated for the target power grid after the execution of the power grid control command to obtain the new carbon flux density of the branch.

[0013] As one preferred embodiment, the step of executing the power grid control command based on the comparison result of the branch carbon flux density and the new carbon flux density of the branch to achieve carbon reduction control of the target power grid includes: Based on the comparison between the branch carbon flux density and the new carbon flux density of the branch, the simulated carbon reduction amount of the carbon-exceeding line is determined. Based on the difference between the target carbon reduction amount and the simulated carbon reduction amount, the power grid control command is executed to achieve carbon reduction control of the target power grid.

[0014] Another embodiment of the present invention provides a power grid control system for carbon reduction, comprising: The directed power flow graph construction module is used to construct the directed power flow graph of the target power grid based on the electrical connection data of all topological nodes of the target power grid. The branch carbon flux density determination module is used to perform carbon emission inference on the directed power flow graph based on the current operating data of the target power grid to obtain the branch carbon flux density. The target carbon reduction determination module is used to determine the carbon-exceeding lines of the target power grid and the target carbon reduction amount of the carbon-exceeding lines based on the numerical comparison results of the carbon flux density of all the branches. The power grid control command generation module is used to calculate the impedance adjustment amount of the carbon-exceeding line based on the target carbon reduction amount, and generate power grid control commands based on the impedance adjustment amount and the associated equipment information of the carbon-exceeding line. The instruction execution simulation module is used to simulate the execution process of the power grid control instructions to obtain the new carbon flux density of the branch. The power grid carbon reduction control module is used to execute the power grid control command based on the comparison result of the branch carbon flux density and the branch new carbon flux density, so as to achieve carbon reduction control of the target power grid. Attached Figure Description

[0015] Figure 1 This is one of the flowcharts of the power grid regulation method for carbon reduction provided by the present invention; Figure 2 This is the second flowchart of the power grid regulation method for carbon reduction provided by the present invention; Figure 3 This is a schematic diagram of the structure of the power grid control system for carbon reduction provided by the present invention.

[0016] Figure label: Among them, 301 is the power flow directed graph construction module; 302 is the branch carbon flux density determination module; 303 is the target carbon reduction determination module; 304 is the power grid control command generation module; 305 is the command execution simulation module; and 306 is the power grid carbon reduction control module. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] In the description of this application, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0019] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. The terms "vertical," "horizontal," "left," "right," "upper," "lower," and similar expressions used herein are for illustrative purposes only and do not indicate or imply that the device or component referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0020] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0021] See Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the power grid control method for carbon reduction provided by the present invention, as shown below. Figure 1 As shown, this embodiment includes steps 100 to 600, and the specific steps are as follows: Step 100: Based on the electrical connection data of all topology nodes of the target power grid, construct the power flow directed graph of the target power grid; In this embodiment, the directed power flow graph refers to a graph with topological nodes of the power grid as vertices and branches (between nodes with electrical connections) as edges, and the edge directions are determined based on the actual direction of the real-time active power flow on each branch. The method for constructing the directed power flow graph is as follows: First, obtain the association relationships between the topological nodes and branches of the target power grid, thereby forming an undirected topological graph; then, from the power grid state estimation or power flow calculation results at the same time, read the active power flow value of the power grid branch ij between node i and node j. If there is a positive current value Then the power flow direction of the power grid branch ij is determined to be from node i to node j; if If the direction is from node j to node i, then the direction is determined by the direction from node j to node i. For example, in a power grid, the measured active power of branch 1-4 is 165MW, so the power flow direction is determined by the direction from node j to node i, thus determining a directed edge 1→4 in the directed power flow graph. This directed graph is used for subsequent carbon emission inference.

[0022] Step 200: Perform carbon emission inference on the directed power flow graph based on the current operating data of the target power grid to obtain the branch carbon flux density; In this embodiment, the branch carbon flux density refers to the carbon emissions corresponding to a unit of electrical energy flowing through the branch per unit time. Its reasoning and acquisition process includes: first, based on the same moment... Based on the nodal load active power, unit output, and unit carbon intensity, a nodal carbon potential balance equation is constructed according to the principle of carbon flow conservation. ,in, It consists of the node outflow power base and the inflow branch power; The carbon potential at the node (to be determined). First, carbon power is injected into the nodes. Second, an endogenous scaling method is used to estimate the nodes online. residual fluctuation scale An optimization model is constructed using the Huber robust loss function, and the node values ​​are obtained through iterative reweighted least squares solution. carbon potential Finally, for a directed edge i→j, define its branch carbon flux density. For example, if the power flow direction of branch 1-4 is 1→4, then the carbon potential of node 1 is equal to the carbon flux density of branch 1-4.

[0023] Step 300: Based on the numerical comparison results of the carbon flux density of all the branches, determine the carbon-exceeding lines of the target power grid and the target carbon reduction amount of the carbon-exceeding lines. In this embodiment, a carbon-exceeding line refers to a line whose branch carbon flux density exceeds a preset threshold. This preset threshold can be derived from... since Regional green power supply assessment standards. For all controllable branches, calculate the carbon congestion index. If the carbon congestion index is greater than or equal to the trigger threshold, the branch is determined to be a carbon-exceeding line. Further, define the target carbon reduction amount. ,in, The desired target carbon flux density (usually taken as...) Or slightly below the threshold, where, branch road (The carbon flux threshold). For example, if the current carbon flux density of a branch is 440 and the threshold is 400, then the target carbon reduction is 40.

[0024] Step 400: Calculate the impedance adjustment amount of the carbon-exceeding line based on the target carbon reduction amount, and generate a power grid control command based on the impedance adjustment amount and the associated equipment information of the carbon-exceeding line. In this embodiment, the impedance adjustment amount refers to the change in the equivalent reactance of the branch required to reduce the carbon flux density of the branch to the target value. Its calculation method is as follows: In a shadow model decoupled from the actual power grid, the local sensitivity of the branch's carbon flux density to the equivalent reactance is calculated, and the result is numerically approximated using the central difference method. If the local sensitivity is <0 (i.e., increasing the reactance reduces the carbon flux), then the original impedance adjustment amount is equal to the negative of the ratio of the target carbon reduction amount to the local sensitivity. Then, based on the type of device installed on the branch, the original impedance adjustment amount is converted into a physical control command.

[0025] Step 500: Simulate the execution process of the power grid control command to obtain the new carbon flux density of the branch. In this embodiment, the simulation is conducted in a shadow model, which is decoupled from the actual power grid and is only used to simulate the effect of command control. Specifically, the proposed power grid control command is written into the network parameters of the shadow model, the node admittance matrix is ​​updated, and then the AC power flow is resolved to obtain the active power flow distribution of the branches after control. Then, the carbon emission inference method described above is called to calculate the carbon flux density of each branch based on the new power flow results, which is the new carbon flux density of the branches in this embodiment. For example, the carbon flux density of a certain line before control is 440, and the new carbon flux density after simulation adjustment becomes 395. This result is used for subsequent comparison.

[0026] Step 600: Based on the comparison between the branch carbon flux density and the new carbon flux density of the branch, execute the power grid control command to achieve carbon reduction control of the target power grid.

[0027] In this embodiment, the comparison result refers to comparing the branch carbon flux density before and after regulation to calculate the simulated carbon reduction. Then, it is determined whether the simulated carbon reduction reaches or exceeds the target carbon reduction. If it reaches the target and all grid safety constraints are met, the grid regulation command generated in step 400 above is formally issued to the grid field device for execution. If it does not reach the target but is still improving, and there are no safety limits exceeded, the current grid regulation command is accepted. If the simulation result shows that the carbon flux density has increased or caused other lines to exceed the limit, the grid regulation command is rejected and readjusted. For example, if a line has a target carbon reduction of 40, and the simulated actual carbon reduction is 38, and the voltage and thermal stability are normal, then the grid regulation command is executed.

[0028] This invention achieves precise sensing of carbon flux density in each branch of the power grid by constructing a directed power flow graph and inferring carbon emissions, providing a unified and stable data foundation for proactive carbon reduction. Based on the target carbon reduction amount for lines exceeding carbon limits, impedance adjustment is calculated and device control commands are generated, achieving a precise mapping from carbon reduction requirements to physical control quantities. Before execution, shadow model simulation of the commands allows for early prediction of control effects and safety risks, avoiding safety issues such as voltage exceeding limits and branch thermal instability. By comparing carbon flux density before and after simulation, a closed-loop verification and decision-making mechanism is formed, ensuring that control commands effectively reduce carbon emissions while strictly meeting the hard constraints of the power grid. This invention improves the stability of carbon potential sensing. It achieves dual synergy between low-carbon and safe operation of the power grid, effectively reducing the average carbon potential of the power grid and the amount of carbon exceeding limits on the load side, and improving the accuracy of power grid carbon reduction control.

[0029] In another embodiment of the power grid regulation method for carbon reduction provided by the present invention, the above steps specifically include: Step 110: Based on the electrical connection data of all topological nodes in the target power grid, determine all adjacent node pairs with electrical connection relationships in the target power grid, and the power grid branches between each adjacent node pair; Step 120: Based on the power flow direction between each of the adjacent node pairs and each of the power grid branches, construct the directed power flow graph of the target power grid.

[0030] In this embodiment, an adjacent node pair refers to two nodes directly connected by a branch. This embodiment provides a specific implementation: First, all node numbers and branch connection relationships are read from the power grid topology data to generate an adjacency table. For each branch, its two endpoints are denoted as node i and node j, forming an adjacent node pair (i, j). Then, the active power flow of the branch at the same time is obtained. ,like According to The sign of the active power flow determines the direction of the power flow. If there is an active power flow value... Then the power flow direction of the power grid branch ij is determined to be from node i to node j; if The direction is from node j to node i. In a directed power flow graph, a directed edge is created for each pair of adjacent nodes, with the edge direction consistent with the power flow direction. If the power of a branch is zero or the measurement is invalid, the edge is temporarily ignored.

[0031] This embodiment clarifies the specific elements of constructing a directed power flow graph (adjacent node pairs and power flow direction), improving the clarity and feasibility of the solution.

[0032] See Figure 2 , Figure 2 This is a flowchart illustrating another embodiment of the power grid control method for carbon reduction provided by the present invention, as shown below. Figure 2As shown, this embodiment includes steps 210 to 250, and the specific steps are as follows: Step 210: Based on the branch power flow data, node load active power and power generation related data of the target power grid at the same moment, determine the analytical results of the node carbon potential balance relationship; Step 220: Based on the analysis results and the historical operating data of the target power grid, determine the normalized residual of each topological node under the candidate carbon potential vector; Step 230: Based on the normalized residual of each topological node, obtain the residual fluctuation scale of each topological node and the target ratio of each topological node; the target ratio is the ratio of the absolute value of each normalized residual to the residual fluctuation scale. Step 240: Perform a unified optimization solution on the target ratio of all the topological nodes to obtain the nodal carbon potential of each topological node; Step 250: Determine the branch carbon flux density of each of the power grid branches based on the nodal carbon potential of each of the topological nodes.

[0033] In this embodiment, the nodal carbon potential balance relationship refers to a system of linear equations established based on the principle of carbon flow conservation. This embodiment provides one implementation method: First, for each node i, its mixed outflow power base is calculated according to the directed power flow graph, as shown in Formula 1, where... For node load; Power of the positive branch; Indicates to the node Input the set of neighboring nodes for the positive power. Then, construct the matrix. Its diagonal element The off-diagonal elements are shown in Equation 2. Simultaneously, the nodal carbon power injection is calculated, as shown in Equation 3, where... To be connected to the node A collection of generating units; For the unit's carbon strength; This provides power to the generator unit. From this, a linear equation is derived. Secondly, a historical normalized residual window is maintained for each node, and the residual fluctuation scale is obtained through exponential smoothing. The Huber optimization model is then reconstructed and solved using iterative reweighted least squares to obtain the nodal carbon potential. Finally, for each branch, if its power flow direction is i→j, then the branch carbon flux density is... .

[0034] (1) (2) (3) In another embodiment of the power grid regulation method for carbon reduction provided by the present invention, the above steps specifically include: Step 231: Based on the normalized residual within the historical time window of each topological node, obtain the historical fluctuation scale of each topological node; Step 232: Perform exponential smoothing on the historical fluctuation scale of each topological node to obtain the residual fluctuation scale of each topological node.

[0035] In this embodiment, historical fluctuation scaling and exponential smoothing are key to achieving endogenous scaling estimation. The specific steps are as follows: Let the current time be t. Maintain a sliding window Hi(t) of length W (e.g., W=10) for node i, storing the normalized residuals of the most recent W historical times. First, calculate the median of the normalized residuals within the window. Then calculate the median of the absolute deviations of each residual from the median. The short-term fluctuation scale Then, using the exponential smoothing formula... Update long-term operating scales, among which, This is the forgetting factor (configurable to 0.9). For example, if the normalized residuals of a node over the past 10 time steps are [0.1, -0.2, 0.15, 0.3, -0.1, 0.2, -0.25, 0.05, 0.12, -0.18], the calculated short-term scale is approximately 0.22. If the long-term scale of the previous time step was 0.20, then the updated scale is approximately 0.202. When the absolute value of the current normalized residual is detected to be greater than... When a reset is triggered, the median of the short-term scales of the two adjacent hop nodes is taken as the new value. .

[0036] This embodiment achieves online estimation of residual fluctuation scale through an adaptive mechanism of sliding window and exponential smoothing, without relying on external prior statistics, thus enhancing the algorithm's robustness to noise and outliers.

[0037] In another embodiment of the power grid regulation method for carbon reduction provided by the present invention, the above steps specifically include: Step 241: Adjust the target ratio based on a preset loss function to obtain an optimized ratio; Step 242: Based on the optimization ratio of each topological node, perform a unified optimization solution on the candidate carbon potential vector to obtain the nodal carbon potential of each topological node.

[0038] In this embodiment, the preset loss function can be the Huber function, and the optimized ratio refers to the value after mapping by the Huber function. The complete optimization solution process is given in this embodiment as follows: The target ratio is defined as shown in Formula 4, where, Huber function As shown in Formula 5, A value of 1.345 can be chosen. The optimization model is then shown in Equation 6. Iterative reweighted least squares is used for the solution: in the m-th iteration, the following is calculated... Set the weights as shown in Formula 7; then solve the weighted least squares problem as shown in Formula 8. Repeat until... For example, in a real power grid, the initial candidate solution uses the direct inversion result, which converges after 5 iterations. The obtained nodal carbon potentials meet the physical non-negativity constraint and are much more stable than the direct solution.

[0039] (4) (5) (6) (7) (8) This embodiment effectively suppresses the interference of bad data on carbon potential estimation by using the Huber loss function and iterative reweighted least squares, thus ensuring the stability and physical rationality of the solution results.

[0040] In another embodiment of the power grid regulation method for carbon reduction provided by the present invention, the above steps specifically include: Step 410: Construct a power grid operation model based on the current operating data of the target power grid and the directed power flow graph; Step 420: In the power grid operation model, the relationship between the carbon flux density of the branch and the equivalent reactance of the branch of the carbon-exceeding line is simulated to obtain the virtual carbon impedance of the carbon-exceeding line. Step 430: In the power grid operation model, the influence relationship between the virtual carbon impedance and the target power grid is simulated to obtain the impedance adjustment amount of the carbon-exceeding line.

[0041] The power grid operation model in this embodiment is the shadow model. The virtual carbon impedance is the branch equivalent reactance increment simulated in the shadow model to reduce carbon flux. This embodiment provides specific conversions for the following three device types: For TCSC, the branch reactance is directly modified in the shadow model to the original reactance plus the equivalent reactance change; for UPFC, it is equivalent to a series variable reactance, which is achieved by adjusting the injected voltage amplitude; for phase-shifting transformers, equivalent power flow regulation is achieved by changing the phase shift angle.

[0042] In this embodiment, taking the TCSC device installed in branch 1 as an example: First, in the shadow model, the reference reactance of branch 1 is 0.082, the carbon flux density is 520, the carbon flux density threshold is 400, and the target carbon reduction is 120. Sensitivity calculation yields S=-150, so the original impedance adjustment is 0.8, far exceeding the device capacity, and therefore saturated to 0.15. This virtual carbon impedance is then converted into the TCSC firing angle command. Through repeated simulations using the shadow model, the feasible impedance adjustment is finally determined.

[0043] By constructing an independent power grid operation model (shadow model), offline pre-simulation of control effects was achieved, and a virtual carbon impedance was defined as a unified interface to facilitate conversion between different FACTS devices.

[0044] In another embodiment of the power grid regulation method for carbon reduction provided by the present invention, the above steps specifically include: Step 440: Based on the associated equipment information of the carbon exceeding line, construct a control command conversion model; Step 450: In the control command conversion model, the conversion relationship between the impedance adjustment amount and the equipment control parameters is simulated to obtain the equipment parameter adjustment amount; Step 460: Generate power grid control instructions based on the device parameter adjustment amount.

[0045] The control command conversion model in this embodiment refers to the mapping relationship that converts virtual carbon impedance into physical parameters of a specific device. This embodiment provides conversion models for three types of devices. TCSC: Conversion model is... The control command is the series reactance setpoint; UPFC: the conversion model is ,in, For branch current amplitude, the control command is series injection voltage amplitude and quadrature phase angle; for phase-shifting transformers: first calculate the sensitivity of active power to phase shift angle. Then obtain the phase shift angle increment. ,in, Depend on It is obtained through equivalent conversion.

[0046] In this embodiment, the associated equipment information includes device type, installation branch, capacity range, reference parameters, and rate of change limit, which can be obtained from the equipment ledger or setting sheet. For example, if the TCSC is installed on branch 1, with a capacity range of -0.20 to 0.15 pu and a reference reactance of 0.082 pu, and the virtual impedance adjustment is +0.12 pu, then the converted control command is: =0.202pu, then trimmed to the capacity range, the final instruction is 0.202pu (not exceeding the upper limit). For UPFC, the voltage instruction also needs to be limited to the range specified by the device.

[0047] This embodiment establishes a unified control command conversion model to transform the abstract virtual carbon impedance into physical parameters that can be recognized by different FACTS devices, thereby achieving device independence of the control strategy and improving the versatility of the method.

[0048] In another embodiment of the power grid regulation method for carbon reduction provided by the present invention, the above steps specifically include: Step 510: In the power grid operation model, perform carbon emission simulation on the target power grid after executing the power grid control command to obtain the new carbon flux density of the branch.

[0049] This embodiment explicitly states that the simulation is performed within a power grid operation model (i.e., a shadow model). The specific steps are as follows: First, the generated power grid control commands (such as the target reactance of the TCSC and the injection voltage of the UPFC) are written into the corresponding branch parameters of the shadow model, updating the node admittance matrix. Then, the same AC power flow solver as the real power grid is invoked to calculate the node voltage and branch power after control in the shadow model. Next, the aforementioned carbon emission inference method is invoked, using the new power flow results from the shadow model as input, to recalculate the carbon potential of each node and the carbon flux density of each branch. This result is the new carbon flux density of the branch. For example, after simultaneously issuing control commands to five devices, the new carbon flux density of the branch is recalculated in the shadow model, and the carbon potential of each node decreases after control. During the simulation, if voltage or thermal stability exceeds limits, a rollback mechanism is triggered.

[0050] This embodiment clarifies the specific carrier of the simulation (power grid operation model / shadow model) and the simulation content (carbon emission simulation), ensuring the full feasibility of the simulation process.

[0051] In another embodiment of the power grid regulation method for carbon reduction provided by the present invention, the above steps specifically include: Step 610: Based on the comparison between the branch carbon flux density and the new branch carbon flux density, determine the simulated carbon reduction amount of the carbon-exceeding line. Step 620: Execute the power grid control command based on the difference between the target carbon reduction amount and the simulated carbon reduction amount to achieve carbon reduction control of the target power grid.

[0052] In this embodiment, firstly, the branch carbon flux density before regulation and the simulated new branch carbon flux density are obtained and compared to calculate the simulated carbon reduction of the carbon-exceeding line, which is the difference in carbon flux density before and after regulation. Then, the simulated carbon reduction is compared with the previously determined target carbon reduction, while simultaneously verifying the grid's safety constraints. If the simulated carbon reduction meets the target carbon reduction and all safety constraints are met, the grid regulation command is executed directly. If there is a difference between the simulated carbon reduction and the target carbon reduction, and the target carbon reduction cannot be fully met, the impedance adjustment is adjusted with minimal rollback to maximize the carbon reduction while ensuring safety constraints. Then, the adjusted regulation command is executed, thereby achieving carbon reduction regulation of the target grid.

[0053] This embodiment compares the simulated carbon reduction with the target carbon reduction and introduces a minimum backoff mechanism to ensure that the actual control commands can effectively reduce carbon emissions without exceeding the grid safety boundary, thus achieving closed-loop verification and adaptive correction of the control target.

[0054] The following describes the carbon reduction-oriented power grid control system provided by the present invention. The carbon reduction-oriented power grid control system described below can be referred to in correspondence with the carbon reduction-oriented power grid control method described above.

[0055] Please refer to Figure 3 The present invention also provides a power grid control system for carbon reduction, comprising: The power flow directed graph construction module 301 is used to construct the power flow directed graph of the target power grid based on the electrical connection data of all topology nodes of the target power grid; Branch carbon flux density determination module 302 is used to perform carbon emission inference on the power flow directed graph based on the current operating data of the target power grid to obtain the branch carbon flux density. The target carbon reduction determination module 303 is used to determine the carbon-exceeding lines of the target power grid and the target carbon reduction amount of the carbon-exceeding lines based on the numerical comparison results of the carbon flux density of all the branches. The power grid control command generation module 304 is used to calculate the impedance adjustment amount of the carbon-exceeding line based on the target carbon reduction amount, and generate a power grid control command based on the impedance adjustment amount and the associated equipment information of the carbon-exceeding line. The instruction execution simulation module 305 is used to simulate the execution process of the power grid control instruction to obtain the new carbon flux density of the branch. The power grid carbon reduction control module 306 is used to execute the power grid control command based on the comparison result of the branch carbon flux density and the branch new carbon flux density, so as to achieve carbon reduction control of the target power grid.

[0056] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A power grid control method for carbon reduction, characterized in that, include: Based on the electrical connection data of all topological nodes of the target power grid, a directed power flow graph of the target power grid is constructed; Carbon emission inference is performed on the directed power flow graph based on the current operating data of the target power grid to obtain the branch carbon flux density; Based on the numerical comparison results of the carbon flux density of all the branches, the carbon-exceeding lines of the target power grid and the target carbon reduction amount of the carbon-exceeding lines are determined. Based on the target carbon reduction amount, the impedance adjustment amount of the carbon-exceeding line is calculated, and based on the impedance adjustment amount and the associated equipment information of the carbon-exceeding line, a power grid control command is generated. The execution process of the power grid control command is simulated to obtain the new carbon flux density of the branch. Based on the comparison between the branch carbon flux density and the new carbon flux density of the branch, the power grid control command is executed to achieve carbon reduction control of the target power grid.

2. The power grid regulation method for carbon reduction as described in claim 1, characterized in that, The construction of the directed power flow graph of the target power grid based on the electrical connection data of all topology nodes of the target power grid includes: Based on the electrical connection data of all topological nodes in the target power grid, determine all adjacent node pairs with electrical connection relationships in the target power grid, as well as the power grid branches between each adjacent node pair; Based on the power flow direction between each of the adjacent node pairs and each of the power grid branches, a directed power flow graph of the target power grid is constructed.

3. The power grid regulation method for carbon reduction as described in claim 2, characterized in that, The step of performing carbon emission inference on the directed power flow graph based on the current operating data of the target power grid to obtain the branch carbon flux density includes: Based on the branch power flow data, node load active power and generation-related data of the target power grid at the same moment, the analytical results of the node carbon potential balance relationship are determined. Based on the analysis results and the historical operating data of the target power grid, the normalized residual of each topological node under the candidate carbon potential vector is determined. Based on the normalized residual of each topological node, the residual fluctuation scale of each topological node and the target ratio of each topological node are obtained; the target ratio is the ratio of the absolute value of each normalized residual to the residual fluctuation scale. The target ratio of all the topological nodes is uniformly optimized and solved to obtain the nodal carbon potential of each topological node. Based on the nodal carbon potential of each of the topological nodes, the branch carbon flux density of each of the power grid branches is determined.

4. The power grid regulation method for carbon reduction as described in claim 3, characterized in that, The process of obtaining the residual fluctuation scale of each topological node based on the normalized residual of each topological node includes: Based on the normalized residual within the historical time window of each topological node, the historical fluctuation scale of each topological node is obtained. The historical fluctuation scale of each topological node is exponentially smoothed to obtain the residual fluctuation scale of each topological node.

5. The power grid regulation method for carbon reduction as described in claim 3, characterized in that, The unified optimization solution for the target ratio of all the topological nodes, to obtain the nodal carbon potential of each topological node, includes: The target ratio is adjusted based on a preset loss function to obtain an optimized ratio; Based on the optimization ratio of each topological node, the candidate carbon potential vector is uniformly optimized to obtain the nodal carbon potential of each topological node.

6. The power grid regulation method for carbon reduction as described in claim 1, characterized in that, The impedance adjustment amount calculated based on the target carbon reduction amount for the carbon-exceeding line includes: Based on the current operating data of the target power grid and the directed power flow graph, a power grid operation model is constructed; In the power grid operation model, the relationship between the carbon flux density and the equivalent reactance of the branch of the carbon-exceeding line is simulated to obtain the virtual carbon impedance of the carbon-exceeding line. In the power grid operation model, the influence relationship between the virtual carbon impedance and the target power grid is simulated to obtain the impedance adjustment amount of the carbon-exceeding line.

7. The power grid regulation method for carbon reduction as described in claim 1, characterized in that, The step of generating power grid control commands based on the impedance adjustment amount and the associated equipment information of the carbon-exceeding line includes: Based on the associated equipment information of the carbon-exceeding circuit, a control command conversion model is constructed; In the control command conversion model, the conversion relationship between the impedance adjustment amount and the equipment control parameters is simulated to obtain the equipment parameter adjustment amount; Power grid control commands are generated based on the adjustment amounts of the equipment parameters.

8. The power grid regulation method for carbon reduction as described in claim 6, characterized in that, The simulation of the execution process of the power grid control command yields the following new carbon flux density for the branch: In the power grid operation model, carbon emissions are simulated for the target power grid after the execution of the power grid control command to obtain the new carbon flux density of the branch.

9. The power grid regulation method for carbon reduction as described in claim 1, characterized in that, The step of executing the power grid control command based on the comparison between the branch carbon flux density and the new carbon flux density of the branch to achieve carbon reduction control of the target power grid includes: Based on the comparison between the branch carbon flux density and the new carbon flux density of the branch, the simulated carbon reduction amount of the carbon-exceeding line is determined. Based on the difference between the target carbon reduction amount and the simulated carbon reduction amount, the power grid control command is executed to achieve carbon reduction control of the target power grid.

10. A power grid control system for carbon reduction, characterized in that, include: The directed power flow graph construction module is used to construct the directed power flow graph of the target power grid based on the electrical connection data of all topological nodes of the target power grid. The branch carbon flux density determination module is used to perform carbon emission inference on the directed power flow graph based on the current operating data of the target power grid to obtain the branch carbon flux density. The target carbon reduction determination module is used to determine the carbon-exceeding lines of the target power grid and the target carbon reduction amount of the carbon-exceeding lines based on the numerical comparison results of the carbon flux density of all the branches. The power grid control command generation module is used to calculate the impedance adjustment amount of the carbon-exceeding line based on the target carbon reduction amount, and generate power grid control commands based on the impedance adjustment amount and the associated equipment information of the carbon-exceeding line. The instruction execution simulation module is used to simulate the execution process of the power grid control instructions to obtain the new carbon flux density of the branch. The power grid carbon reduction control module is used to execute the power grid control command based on the comparison result of the branch carbon flux density and the branch new carbon flux density, so as to achieve carbon reduction control of the target power grid.

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