A power flow calculation method and system based on voltage sensitivity of root nodes of a power distribution network

Abstract

This invention discloses a power flow calculation method and system based on the voltage sensitivity of the root nodes in a distribution network. The method represents the integrated transmission and distribution power flow calculation problem as a voltage fixed-point iterative problem, establishing a power flow calculation model. The substation voltage is iteratively solved within the model, and the iteration results and real-time operational data are obtained after each iteration. Based on the real-time operational data, the transmission network sensitivity matrix and the distribution network root node sensitivity matrix are calculated using the least squares method. The convergence of the iteration results is determined based on these matrices. When the iteration results converge, the iteration is stopped, and the integrated transmission and distribution power flow value is obtained. This invention eliminates the dependence on complete network topology and parameter information during power flow calculation and enables rapid and accurate determination of power flow convergence, thereby further improving the convergence of integrated transmission and distribution power flow calculation.

Description

Technical Field

[0001] This invention relates to the field of power system analysis technology, and in particular to a power flow calculation method and system based on the voltage sensitivity of the root node of a distribution network. Background Technology

[0002] In integrated transmission and distribution power systems, the transmission and distribution networks are coupled through substation nodes. Power flow calculations are the basis for verifying the rationality of power system operation and play an extremely important role in the design and adjustment of power systems.

[0003] Traditional power flow calculation methods rely primarily on the power grid topology and line parameters, but this information is often incomplete or unavailable in practical applications. This leads to inaccurate models, large calculation errors, and even convergence failures in power flow calculations.

[0004] Existing technologies have proposed various improvement methods to enhance the convergence of power flow calculations. For example, the master-slave split method updates the power flow solution through alternating iterations, but its convergence performance is insufficient in complex distribution network scenarios. Other methods, such as the ring distribution network equivalent method and the Thevenin theorem equivalent method, while improving the accuracy of calculations to some extent, still suffer from computational errors and limitations in applicability, making it difficult to meet the reliability requirements of power system operation modes or planned power supply schemes. Summary of the Invention

[0005] The technical problem to be solved by this invention is how to improve the convergence of power flow calculation in integrated transmission and distribution systems. It provides a power flow calculation method and system based on voltage sensitivity, which can get rid of the dependence on complete network topology and parameter information in the power flow calculation process, and can quickly and accurately determine the convergence of power flow calculation, so as to further improve the convergence of power flow calculation in integrated transmission and distribution systems and improve the reliability and stability of power systems.

[0006] To address the above technical problems, embodiments of the present invention provide a power flow calculation method based on the root node voltage sensitivity of a distribution network, comprising:

[0007] The power flow calculation problem of integrated transmission and distribution is expressed as a voltage fixed-point iterative problem, and a power flow calculation model with the substation voltage as the iteration vector is established.

[0008] The power flow calculation model is solved using an iterative solution method to obtain the substation voltage. After each iteration, the iteration results and real-time operation data of the integrated power transmission and distribution system are obtained.

[0009] Based on the real-time operating data obtained after the current iteration, the least squares method is used to calculate the transmission network sensitivity matrix and the distribution network root node sensitivity matrix.

[0010] Based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix, determine the convergence of the iterative result obtained after the current iteration.

[0011] When the iterative result obtained after the current iteration converges, the iterative solution of the power flow calculation model is stopped, and the power flow value of the integrated transmission and distribution system is obtained based on the iterative result obtained after stopping the iterative solution.

[0012] As an improvement to the above scheme, the method of representing the power flow calculation problem of integrated transmission and distribution as a voltage fixed-point iterative problem and establishing a power flow calculation model with the substation voltage as the iteration vector includes:

[0013] The first power flow function of the distribution network is obtained based on the substation voltage and the distribution network node voltage.

[0014] The second power flow function of the substation is obtained based on the substation voltage, the distribution network node voltage, and the power injection of the substation.

[0015] The third power flow function of the transmission network is obtained based on the substation voltage and the substation power injection.

[0016] Based on the first power flow function, the second power flow function, and the third power flow function, the power flow calculation problem of the integrated transmission and distribution system is expressed as a voltage fixed-point iterative problem, and a power flow calculation model with the substation voltage as the iteration vector is established.

[0017] As an improvement to the above scheme, the real-time operation data includes real-time operation data of the distribution network and real-time operation data of the transmission network.

[0018] As an improvement to the above scheme, the iterative solution method is used to solve the power flow calculation model to obtain the substation voltage. After each iteration, the iteration results and real-time operating data of the integrated transmission and distribution power grid system are obtained, including:

[0019] The power flow calculation model is solved using an iterative solution method to obtain the substation voltage. After each iteration, the iteration result is obtained.

[0020] The injected active power, injected reactive power, and node voltage of each node in the distribution network are obtained as real-time operation data of the distribution network.

[0021] The active power, reactive power, voltage amplitude, and phase angle of the substation are acquired as real-time operation data of the power transmission network.

[0022] Based on the real-time operation data of the distribution network and the real-time operation data of the transmission network, the real-time operation data of the integrated transmission and distribution power grid system is obtained.

[0023] As an improvement to the above solution, the

[0024] Based on the real-time operating data obtained after the current iteration, the least squares method is used to calculate the transmission network sensitivity matrix and the distribution network root node sensitivity matrix, including:

[0025] Calculate the power transmission network sensitivity matrix based on the real-time operation data of the power transmission network obtained after the current iteration.

[0026] Based on the real-time operating data of the distribution network obtained after the current iteration, the Monte Carlo method is used to calculate the power change and voltage change between different operating states of the distribution network.

[0027] Based on the power change and the voltage change, establish an overdetermined system of equations;

[0028] The overdetermined equations are solved using the least squares method to obtain the root node sensitivity matrix of the distribution network.

[0029] As an improvement to the above scheme, the step of calculating the power change and voltage change between different operating states of the distribution network using the Monte Carlo method based on the real-time operating data of the distribution network obtained after the current iteration includes:

[0030] Cluster the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state;

[0031] Based on the first voltage distribution, a small change in power is generated using the Monte Carlo method, and the second voltage distribution corresponding to the small change in power under the operating state is calculated.

[0032] The power change is obtained based on the power distribution near the current operating state;

[0033] Calculate the voltage change based on the first voltage distribution and the second voltage distribution.

[0034] As an improvement to the above scheme, the step of clustering the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution near the current operating state includes:

[0035] The two real-time operation data of the power distribution network with the largest distance are selected as cluster centers;

[0036] The K-means clustering method is used to perform at least two levels of clustering on the real-time operating data of the power distribution network obtained after the current iteration of the solution based on the cluster centers, and the clustering measure is calculated based on the clustering results.

[0037] The clustering error rate is obtained based on the clustering metric.

[0038] When the clustering error rate is greater than a preset threshold, the two real-time operation data of the power distribution network with the largest distance are reselected as cluster centers in the next level.

[0039] When the clustering error rate is not greater than a preset threshold, the number of cluster centers and the clustering result are obtained;

[0040] Based on the number of cluster centers and the clustering results, the power distribution and its corresponding first voltage distribution near the current operating state are obtained.

[0041] As an improvement to the above scheme, the step of solving the overdetermined equations using the least squares method to obtain the root node sensitivity matrix of the distribution network includes:

[0042] By introducing a residual sum of squares function into the overdetermined system of equations, a modified overdetermined system of equations is obtained.

[0043] The least squares method is used to differentiate the parameters to be determined in the modified overdetermined equation system and solve for the maximum and minimum values ​​to obtain the root node sensitivity matrix of the distribution network.

[0044] As an improvement to the above scheme, the step of determining the convergence of the iterative result obtained after the current iteration based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix includes:

[0045] The spectral radius of the comprehensive sensitivity matrix is ​​obtained based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix.

[0046] When the spectral radius of the integrated sensitivity matrix is ​​less than a preset spectral radius threshold, the iteration result is determined to be converged; otherwise, the iteration result is determined to be non-converged.

[0047] As an improvement to the above scheme, when the iterative result obtained after the current iteration converges, the iterative solution of the power flow calculation model is stopped, and the integrated power flow value is obtained based on the iterative result obtained after stopping the iterative solution, including:

[0048] When the iterative result obtained after the current iteration converges, the iterative solution of the power flow calculation model is stopped;

[0049] Based on the iterative results obtained after stopping the iterative solution, the power flow values ​​of the distribution network, substation, and transmission network are calculated.

[0050] The power flow value of the integrated transmission and distribution network is obtained based on the power flow value of the distribution network, the power flow value of the substation, and the power flow value of the transmission network.

[0051] This invention also provides a power flow calculation system based on the root node voltage sensitivity of a distribution network, comprising:

[0052] The model building module is used to represent the power flow calculation problem of integrated transmission and distribution as a voltage fixed-point iterative problem and to build a power flow calculation model with the substation voltage as the iteration vector.

[0053] The data acquisition module is used to solve the power flow calculation model using an iterative solution method to obtain the substation voltage. After each iteration, the module acquires the iteration results and the real-time operation data of the integrated power transmission and distribution system.

[0054] The sensitivity matrix calculation module is used to calculate the transmission network sensitivity matrix and the distribution network root node sensitivity matrix using the least squares method based on the real-time operating data obtained after the current iteration.

[0055] The convergence determination module is used to determine the convergence of the iterative result obtained after the current iteration based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix.

[0056] The power flow calculation module is used to stop the iterative solution of the power flow calculation model when the iterative result obtained after the current iteration converges, and to obtain the integrated power flow value of transmission and distribution based on the iterative result obtained after stopping the iterative solution.

[0057] As an improvement to the above solution, the model building module includes:

[0058] The first power flow function acquisition unit is used to obtain the first power flow function of the distribution network based on the substation voltage and the distribution network node voltage.

[0059] The second power flow function acquisition unit is used to obtain the second power flow function of the substation based on the substation voltage, the distribution network node voltage and the substation power injection.

[0060] The third power flow function acquisition unit is used to obtain the third power flow function of the transmission network based on the substation voltage and the substation power injection.

[0061] The model building unit is used to express the power flow calculation problem of the integrated transmission and distribution system as a voltage fixed-point iterative problem based on the first power flow function, the second power flow function and the third power flow function, and to establish a power flow calculation model with the substation voltage as the iteration vector.

[0062] As an improvement to the above scheme, the real-time operation data includes real-time operation data of the distribution network and real-time operation data of the transmission network.

[0063] As an improvement to the above solution, the data acquisition module includes:

[0064] The unit for obtaining the result of an iteration is used to solve the power flow calculation model using an iterative solution method to obtain the substation voltage. After each iteration is completed, the iteration result is obtained.

[0065] The real-time operation data acquisition unit of the distribution network is used to acquire the injected active power, injected reactive power and node voltage of each node of the distribution network as real-time operation data of the distribution network.

[0066] The real-time operation data acquisition unit of the power transmission network is used to acquire the active power, reactive power, voltage amplitude and phase angle of the substation as real-time operation data of the power transmission network.

[0067] The real-time operation data acquisition unit is used to obtain the real-time operation data of the integrated power transmission and distribution system based on the real-time operation data of the distribution network and the real-time operation data of the transmission network.

[0068] As an improvement to the above scheme, the sensitivity matrix calculation module includes:

[0069] The power transmission network sensitivity matrix calculation unit is used to calculate the power transmission network sensitivity matrix based on the real-time operation data of the power transmission network obtained after the current iteration.

[0070] The electrical parameter change calculation unit is used to calculate the power change and voltage change between different operating states of the distribution network based on the real-time operating data of the distribution network obtained after the current iteration, using the Monte Carlo method.

[0071] An overdetermined equation set establishment unit is used to establish an overdetermined equation set based on the power change and the voltage change.

[0072] The equation solving unit is used to solve the overdetermined equation system using the least squares method to obtain the root node sensitivity matrix of the distribution network.

[0073] As an improvement to the above scheme, the electrical parameter change calculation unit is specifically used for:

[0074] Cluster the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state;

[0075] Based on the first voltage distribution, a small change in power is generated using the Monte Carlo method, and the second voltage distribution corresponding to the small change in power under the operating state is calculated.

[0076] The power change is obtained based on the power distribution near the current operating state;

[0077] Calculate the voltage change based on the first voltage distribution and the second voltage distribution.

[0078] As an improvement to the above scheme, the step of clustering the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution near the current operating state includes:

[0079] The two real-time operation data of the power distribution network with the largest distance are selected as cluster centers;

[0080] The K-means clustering method is used to perform at least two levels of clustering on the real-time operating data of the power distribution network obtained after the current iteration of the solution based on the cluster centers, and the clustering measure is calculated based on the clustering results.

[0081] The clustering error rate is obtained based on the clustering metric.

[0082] When the clustering error rate is greater than a preset threshold, the two real-time operation data of the power distribution network with the largest distance are reselected as cluster centers in the next level.

[0083] When the clustering error rate is not greater than a preset threshold, the number of cluster centers and the clustering result are obtained;

[0084] Based on the number of cluster centers and the clustering results, the power distribution and its corresponding first voltage distribution near the current operating state are obtained.

[0085] As an improvement to the above scheme, the equation solving unit is specifically used for:

[0086] By introducing a residual sum of squares function into the overdetermined system of equations, a modified overdetermined system of equations is obtained.

[0087] The least squares method is used to differentiate the parameters to be determined in the modified overdetermined equation system and solve for the maximum and minimum values ​​to obtain the root node sensitivity matrix of the distribution network.

[0088] As an improvement to the above scheme, the convergence determination module includes:

[0089] The spectral radius calculation unit is used to obtain the spectral radius of the comprehensive sensitivity matrix based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix.

[0090] The convergence determination unit is used to determine that the iteration result is converged when the spectral radius of the integrated sensitivity matrix is ​​less than a preset spectral radius threshold; otherwise, it determines that the iteration result is not converged.

[0091] As an improvement to the above solution, the power flow value calculation module includes:

[0092] An iteration stopping unit is used to stop the iterative solution of the power flow calculation model when the iterative result obtained after the current iteration converges.

[0093] A separate power flow calculation unit is used to calculate the power flow values ​​of the distribution network, substation, and transmission network based on the iteration results obtained after stopping the iterative solution.

[0094] An integrated power flow calculation unit is used to obtain an integrated power flow value for transmission and distribution based on the power flow value of the distribution network, the power flow value of the substation, and the power flow value of the transmission network.

[0095] Compared with existing technologies, this invention discloses a power flow calculation method and system based on the voltage sensitivity of the root node of a distribution network. It represents the integrated transmission and distribution power flow calculation problem as a voltage fixed-point iterative problem, establishing a power flow calculation model with substation voltage as the iteration vector. An iterative solution method is used to solve the power flow calculation model to obtain the substation voltage. After each iteration, the iteration result and real-time operating data of the integrated transmission and distribution power grid system are obtained. Based on the real-time operating data obtained after the current iteration, the least squares method is used to calculate the transmission network sensitivity matrix and the distribution network root node sensitivity matrix. The convergence of the iteration result obtained after the current iteration is determined based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix. When the iteration result obtained after the current iteration converges, the iterative solution of the power flow calculation model is stopped, and the integrated transmission and distribution power flow value is obtained based on the iteration result obtained after stopping the iteration. By employing the embodiments of the present invention, the dependence on complete network topology and parameter information in the power flow calculation process can be eliminated, and the convergence of power flow calculation can be quickly and accurately determined, thereby further improving the convergence of power flow calculation in the integrated transmission and distribution system and enhancing the reliability and stability of the power system. Attached Figure Description

[0096] Figure 1 This is a flowchart illustrating the steps of a power flow calculation method based on the root node voltage sensitivity of a distribution network, provided in an embodiment of the present invention.

[0097] Figure 2 This is a schematic diagram of the structure of an integrated power transmission and distribution grid system provided in an embodiment of the present invention;

[0098] Figure 3This is a schematic diagram showing the results of the calculation time and the radius of the integrated sensitivity matrix spectrum as a function of load rate in a power flow calculation according to an embodiment of the present invention.

[0099] Figure 4 This is a schematic diagram of the structure of a power flow calculation system based on the voltage sensitivity of the root node of a distribution network, provided in an embodiment of the present invention. Detailed Implementation

[0100] 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0101] In the description and claims, it should be understood that the terms "first," "second," etc., used in the description and claims are only for the purpose of distinguishing the description of the same technical features, and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated, nor necessarily the order of description or chronological order. The terms are interchangeable where appropriate. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature.

[0102] With the increasing penetration of new energy sources, especially distributed photovoltaic and wind power, traditional transmission and distribution separation power flow calculation methods can no longer meet the needs of modern power grids. Integrated transmission and distribution power flow calculations need to consider the coupling of the transmission network and the distribution network simultaneously, making the convergence problem of the calculation more complex.

[0103] In integrated transmission and distribution systems, the interaction between the transmission and distribution networks is coupled through substation nodes. Traditional power flow calculation methods mainly rely on the grid topology and line parameters, but this information is often incomplete or unavailable in practical applications. This leads to inaccurate models, large calculation errors, and even convergence failures in power flow calculations, ultimately resulting in the reliability of the power system derived from the power flow being difficult to meet requirements.

[0104] Based on the above considerations, this invention provides a power flow calculation method based on the root node voltage sensitivity of a distribution network. Please refer to... Figure 1 In this embodiment, the power flow calculation method based on the root node voltage sensitivity of the distribution network is specifically executed through steps S1 to S5:

[0105] S1. Represent the power flow calculation problem of integrated transmission and distribution as a voltage fixed-point iterative problem, and establish a power flow calculation model with the substation voltage as the iteration vector.

[0106] It should be noted that the fixed-point iterative form, as a mathematical tool, has been widely used in power flow calculation in integrated power transmission and distribution systems. In this embodiment of the invention, the power flow calculation problem is represented as a fixed-point iterative problem in mathematics using the fixed-point iterative form. The convergence of the power flow calculation problem is analyzed through fixed-point theory, thereby solving the problem that traditional methods rely on complete network topology and parameter information.

[0107] It should also be noted that the power flow calculation model described is applied to integrated transmission and distribution power systems; please refer to [link to relevant documentation]. Figure 2 , Figure 2 This is a schematic diagram of the structure of an integrated power transmission and distribution grid system provided in an embodiment of the present invention. It is understood that the power flow calculation model established under integrated transmission and distribution conditions needs to include the distribution network, substations, and transmission network.

[0108] S2. The power flow calculation model is solved using an iterative solution method to obtain the substation voltage. After each iteration, the iteration results and real-time operation data of the integrated power transmission and distribution system are obtained.

[0109] In this embodiment of the invention, the only iterative variable of the power flow calculation model generated by the fixed-point iteration principle, i.e., the fixed point, is the substation voltage. Therefore, in each iteration process, only the substation voltage needs to be iteratively calculated, so that the iteration result gradually approaches the power flow solution.

[0110] S3. Based on the real-time operating data obtained after the current iteration, calculate the transmission network sensitivity matrix and the distribution network root node sensitivity matrix using the least squares method.

[0111] In integrated transmission and distribution power flow calculation, power flow calculation can be decomposed into the interaction between the transmission network and the distribution network. In this embodiment of the invention, the coupling part of the transmission network and the distribution network is specifically considered, and the convergence of the iterative results is further analyzed by calculating the sensitivity matrix of the transmission network and the sensitivity matrix of the root node of the distribution network.

[0112] S4. Based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix, determine the convergence of the iterative result obtained after the current iteration.

[0113] By combining the transmission network sensitivity matrix and the distribution network root node sensitivity matrix, a comprehensive sensitivity matrix can be obtained to reflect the coupling between the transmission network and the distribution network.

[0114] In some embodiments, according to the fixed-point iteration theory, when the spectral radius of the comprehensive sensitivity matrix is ​​less than 1, the iteration result is determined to be convergent.

[0115] In other embodiments, considering the computational complexity and accuracy issues in practical applications, matrix norms are used to simplify the judgment criteria. When the norm of the comprehensive sensitivity matrix is ​​less than 1, the judgment iteration result is also convergent.

[0116] S5. When the iterative result obtained after the current iteration converges, stop the iterative solution of the power flow calculation model, and obtain the power flow value of the integrated transmission and distribution system based on the iterative result obtained after stopping the iterative solution.

[0117] When the power flow results converge, it indicates that the substation voltage obtained by iterating the power flow calculation model can meet the power flow requirements. Furthermore, the power grid can be optimized and adjusted based on the iteration results, so that the power flow of the transmission network, substations and distribution network all have good convergence performance.

[0118] In the above scheme, the power flow calculation of the integrated transmission and distribution system is modeled and analyzed by fixed-point iteration. Furthermore, convergence discrimination is achieved through sensitivity identification. This can get rid of the dependence on complete network topology and parameter information in the power flow calculation process, and can quickly and accurately determine the convergence of the power flow calculation, so as to further improve the convergence of the integrated transmission and distribution power flow calculation.

[0119] As a preferred implementation, step S1, representing the power flow calculation problem of integrated transmission and distribution as a voltage fixed-point iterative problem, and establishing a power flow calculation model with the substation voltage as the iteration vector, includes:

[0120] The first power flow function of the distribution network is obtained based on the substation voltage and the distribution network node voltage.

[0121] The second power flow function of the substation is obtained based on the substation voltage, the distribution network node voltage, and the power injection of the substation.

[0122] The third power flow function of the transmission network is obtained based on the substation voltage and the substation power injection.

[0123] Based on the first power flow function, the second power flow function, and the third power flow function, the power flow calculation problem of the integrated transmission and distribution system is expressed as a voltage fixed-point iterative problem, and a power flow calculation model with the substation voltage as the iteration vector is established.

[0124] For example, the first power flow function of the distribution network is G. D (U B )=U D The second power flow function of the substation is G. B (U B U D ) = S B The third power flow function of the transmission network is G. T (S B)=U B The power flow calculation model is Among them, U B For the substation voltage, U D S represents the voltage at the distribution network node. B Power injection for substations. Let be the substation voltage in the k-th iteration. Let be the substation voltage in the (k+1)th iteration.

[0125] It should be noted that the first power flow function, the second power flow function, the third power flow function, and the power flow calculation model mentioned above all contain other parameters. These parameters are related to the specific settings of the power transmission and distribution integrated system. Those skilled in the art can understand how to establish the functions and models. The present invention aims to provide a method for transforming the traditional power flow calculation method through fixed-point iteration, which does not rely on complete network topology and parameter information, thus simplifying the modeling process.

[0126] Preferably, the real-time operating data includes real-time operating data of the distribution network and real-time operating data of the transmission network.

[0127] It should be noted that the real-time operating data can be real-time collected or predicted node operating data, or it can be a mixture of actual data and generated data to improve the robustness of the power flow calculation model.

[0128] Furthermore, as a preferred implementation, step S2 involves using an iterative solution method to solve the power flow calculation model to obtain the substation voltage. After each iteration, the iteration results and real-time operating data of the integrated transmission and distribution power grid system are obtained, including:

[0129] The power flow calculation model is solved using an iterative solution method to obtain the substation voltage. After each iteration, the iteration result is obtained.

[0130] The injected active power, injected reactive power, and node voltage of each node in the distribution network are obtained as real-time operation data of the distribution network.

[0131] The active power, reactive power, voltage amplitude, and phase angle of the substation are acquired as real-time operation data of the power transmission network.

[0132] Based on the real-time operation data of the distribution network and the real-time operation data of the transmission network, the real-time operation data of the integrated transmission and distribution power grid system is obtained.

[0133] It should be noted that the iteration results include the substation voltage and the power flow values ​​of the integrated transmission and distribution power grid system obtained in the current iteration.

[0134] It should also be noted that, in this embodiment of the invention, when acquiring real-time operating data, active power and reactive power are acquired for power data. Similarly, when generating the sensitivity matrix later, active power sensitivity matrix and reactive power sensitivity matrix will also be generated.

[0135] As a preferred implementation, step S3, based on the real-time operating data obtained after the current iteration, calculates the transmission network sensitivity matrix and the distribution network root node sensitivity matrix using the least squares method, and is executed through steps S31 to S34:

[0136] S31. Calculate the power transmission network sensitivity matrix based on the real-time operation data of the power transmission network obtained after the current iteration.

[0137] For example, the power transmission network sensitivity matrix S T for Among them, P B Q represents the active power of the substation. B V represents the reactive power of the substation. B i represents the voltage amplitude of the substation. B This represents the voltage phase angle of the substation.

[0138] S32. Based on the real-time operating data of the distribution network obtained after the current iteration, the Monte Carlo method is used to calculate the power change and voltage change between different operating states of the distribution network.

[0139] S33. Based on the power change and the voltage change, establish an overdetermined set of equations.

[0140] S34. Solve the overdetermined system of equations using the least squares method to obtain the root node sensitivity matrix of the distribution network.

[0141] Further, preferably, step S32 includes:

[0142] Cluster the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state;

[0143] The Monte Carlo method is used to generate minute power changes, and the second voltage distribution corresponding to the minute power changes under the operating conditions is calculated.

[0144] The power change is obtained based on the power distribution near the current operating state;

[0145] Calculate the voltage change based on the first voltage distribution and the second voltage distribution.

[0146] In this embodiment of the invention, the Monte Carlo method is used to generate MN groups of small power changes (M>>2k); where M is the number of groups of real-time running data, N is the number of groups of power changes and voltage changes between different operating states obtained through step S32, and k is the number of nodes.

[0147] For example, for each voltage change node, based on the changes in power and voltage, M equations can be established, i.e., an overdetermined system of equations:

[0148]

[0149] Furthermore, the step of clustering the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state includes:

[0150] The two real-time operation data of the power distribution network with the largest distance are selected as cluster centers;

[0151] The K-means clustering method is used to perform at least two levels of clustering on the real-time operating data of the power distribution network obtained after the current iteration of the solution based on the cluster centers, and the clustering measure is calculated based on the clustering results.

[0152] The clustering error rate is obtained based on the clustering metric.

[0153] When the clustering error rate is greater than a preset threshold, the two real-time operation data of the power distribution network with the largest distance are reselected as cluster centers in the next level.

[0154] When the clustering error rate is not greater than a preset threshold, the number of cluster centers and the clustering result are obtained;

[0155] Based on the number of cluster centers and the clustering results, the power distribution and its corresponding first voltage distribution near the current operating state are obtained.

[0156] In this embodiment of the invention, in order to get rid of the dependence of traditional clustering algorithms on the number of selected cluster centers K, an improved hierarchical K-means clustering algorithm based on the maximum distance method is adopted, and the initial clustering value is selected by the maximum distance method.

[0157] In some embodiments, a total of M sets of real-time operational data are acquired, and the original set of power distribution is P = [P1, P2, ..., P...]. M ], where the power distribution vector for any scene is P i =[p i,1 ,p i,2 ,…,p i,T The initial number of clusters is set to K1.

[0158] K1 initial cluster centers are selected based on the maximum distance method. First, the two samples with the largest distance are selected as the initial cluster centers. Calculate the sample distance d, and select the sample with the largest product of distances to other samples from the remaining M-2 scenarios as the third cluster center; thus obtaining K1 initial cluster centers.

[0159] Perform K-means clustering, assigning all samples to the nearest cluster centers. Let the number of iterations be l = 1, and calculate the clustering measure function J(l) at the l-th iteration. The clustering measure function is: Among them, M i Let i be the number of scenes in the i-th class. C is the j-th data vector in the i-th class; i Let be the cluster center of the i-th class.

[0160] Next, the next level of clustering is performed: the cluster with the largest radius among all clusters is selected, and the result is determined by r. i =max‖P j -C i ||, j = 1, 2, ..., M i Calculate the cluster radius, select the two samples with the largest distance in the cluster as the new cluster centers; perform K-means clustering again based on the cluster centers, let l = l + 1, and calculate the clustering measure function value J(l + 1) for the (l + 1)th time.

[0161] Define ε = (J(l) – J(l+1)) / J(l). If ε > ε0, return to continue iterating, where ε0 is a given threshold that can be set according to the change curve of the clustering metric function value; otherwise, the algorithm ends, outputting the number of cluster centers and the clustering results. From the clustering results, obtain N sets of corresponding actual power data, then obtain the voltage distribution data under this power distribution scenario, and obtain the power distribution and the corresponding first voltage distribution of the current operating state based on the classified voltage distribution data.

[0162] Furthermore, through Establish an overdetermined system of equations; among which, Let i be the sensitivity vector of the node with active power in the distribution network. Let i be the sensitivity vector of the node with reactive power in the distribution network. Let i be the combined sensitivity vector of the distribution network node with respect to reactive power. and is the unknown quantity in the overdetermined system of equations.

[0163] In a preferred embodiment, step S34 includes:

[0164] By introducing a residual sum of squares function into the overdetermined system of equations, a modified overdetermined system of equations is obtained.

[0165] The least squares method is used to differentiate the parameters to be determined in the modified overdetermined equation system and solve for the maximum and minimum values ​​to obtain the root node sensitivity matrix of the distribution network.

[0166] It should be noted that the overdetermined system of equations generally has no solution, therefore it is necessary to find a suitable solution. To ensure that the equations hold true as much as possible, in this embodiment of the invention, the optimal solution to the overdetermined system of equations is further obtained by introducing the residual sum of squares function.

[0167] In some embodiments, by Introducing a residual sum-of-squares function into the overdetermined system of equations for the parameters to be determined Taking the derivative and solving for the maximum and minimum values ​​yields the optimal solution using least squares.

[0168] As a preferred implementation, step S4, determining the convergence of the iterative result obtained after the current iteration based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix, includes:

[0169] The spectral radius of the comprehensive sensitivity matrix is ​​obtained based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix.

[0170] When the spectral radius of the integrated sensitivity matrix is ​​less than a preset spectral radius threshold, the iteration result is determined to be converged; otherwise, the iteration result is determined to be non-converged.

[0171] In a preferred embodiment of the present invention, the preset spectral radius threshold is 1, and the spectral radius is characterized by the norm of the comprehensive sensitivity matrix. When the norm of the comprehensive sensitivity matrix is ​​less than 1, the spectral radius of the comprehensive sensitivity matrix is ​​considered to be less than 1, and the iteration result is determined to be converged.

[0172] For example, IEEE standard case 14 is used as the transmission network example, and a modified case 69 is used as the distribution network example. Based on the original distribution network example, distributed generation with a capacity of 700kW is added to nodes 14 and 32 respectively, with PV control. The distribution network example is connected to node 14 of the transmission network. A scenario where the load rate of the distribution network changes from 0.7 to 2.3 is used to simulate the gradual divergence of power flow calculations in the integrated transmission and distribution system under heavy load conditions.

[0173] The convergence calculation method provided in this embodiment of the invention is based on the least squares method, while the most traditional convergence calculation formula is based on physical principles. This embodiment of the invention will use both methods to analyze the convergence of power flow calculations.

[0174] The voltage sensitivity matrix obtained based on physical principles is as follows:

[0175]

[0176] Where S is the voltage sensitivity matrix, and J is the Jacobian matrix for power flow calculation, the Jacobian matrix can be expressed as:

[0177]

[0178] Considering that the value of θ is generally very small, we can approximate it as cosθ = 1 and sinθ = 0. Further simplification yields:

[0179]

[0180] With the voltage amplitude per unit value around 1.0 pu, Gaussian elimination is applied to the above equation to obtain an approximate expression for the voltage sensitivity:

[0181] ΔU=S U-P ΔP+S U-Q ΔQ;

[0182]

[0183] Among them, S U-P For active-voltage sensitivity, S U-Q To obtain the reactive power-voltage sensitivity, we can further obtain the voltage sensitivity of the root node of the distribution network to reactive power.

[0184] By combining the transmission network sensitivity matrix and the distribution network root node sensitivity matrix, a comprehensive sensitivity matrix can be obtained. According to the fixed-point iteration theory, when the spectral radius satisfies... When the result is 1, it indicates that the iteration result has converged.

[0185] Please see Figure 3 , Figure 3 The solid red line represents the spectral radius of the integrated sensitivity matrix calculated using physical principles, the dashed red line represents the spectral radius of the integrated sensitivity matrix calculated using the least squares method provided in this embodiment, and the blue line represents the power flow calculation time used in this embodiment. It can be seen that the values ​​obtained by the two methods are basically consistent, and the proposed criterion based on the spectral radius of the integrated sensitivity matrix can also characterize the convergence of the power flow in the integrated transmission and distribution system. This indicates that the power flow calculation method provided in this embodiment has good accuracy.

[0186] It should also be noted that the traditional method of calculating the spectral radius of the comprehensive sensitivity matrix based on physical principles is an accurate expression of the node voltage sensitivity. However, it requires multiple matrix inversion operations, which may lead to long calculation times and numerical instability for distribution networks with a large number of nodes and ill-conditioned matrices.

[0187] Further, as a preferred embodiment, step S5, when the iterative result obtained after the current iteration converges, stops the iterative solution of the power flow calculation model, and obtains the integrated power flow value based on the iterative result obtained after stopping the iterative solution, including:

[0188] When the iterative result obtained after the current iteration converges, the iterative solution of the power flow calculation model is stopped;

[0189] Based on the iterative results obtained after stopping the iterative solution, the power flow values ​​of the distribution network, substation, and transmission network are calculated.

[0190] The power flow value of the integrated transmission and distribution network is obtained based on the power flow value of the distribution network, the power flow value of the substation, and the power flow value of the transmission network.

[0191] In some embodiments, after step S5, the safety index and power supply quality of the power system are calculated based on the integrated transmission and distribution power flow value; the power system is then adjusted based on the safety index and the power supply quality. Specifically, when adjusting the power system, preset accuracy requirements are used as constraints based on the transmission network power flow value, the distribution network power flow value, and the substation power flow value to adjust the equipment parameters of the power system.

[0192] The power flow calculation method based on the voltage sensitivity of the root node of the distribution network provided by the embodiments of the present invention can get rid of the dependence on the complete network topology and parameter information in the power flow calculation process, and can quickly and accurately determine the convergence of the power flow calculation, so as to further improve the convergence of the power flow calculation of the integrated transmission and distribution, and improve the reliability and stability of the power system.

[0193] Please see Figure 4 This invention provides a power flow calculation system based on the voltage sensitivity of the root node of a distribution network, including a model building module 11, a data acquisition module 12, a sensitivity matrix calculation module 13, a convergence determination module 14, and a power flow value calculation module 15, wherein:

[0194] Model building module 11 is used to represent the power flow calculation problem of integrated transmission and distribution as a voltage fixed-point iterative problem and to establish a power flow calculation model with the substation voltage as the iteration vector.

[0195] Data acquisition module 12 is used to solve the power flow calculation model using an iterative solution method to obtain the substation voltage. After each iteration, it acquires the iteration results and real-time operation data of the integrated power transmission and distribution system.

[0196] Sensitivity matrix calculation module 13 is used to calculate the transmission network sensitivity matrix and the distribution network root node sensitivity matrix using the least squares method based on the real-time operating data obtained after the current iteration.

[0197] The convergence determination module 14 is used to determine the convergence of the iterative result obtained after the current iteration based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix.

[0198] The power flow calculation module 15 is used to stop the iterative solution of the power flow calculation model when the iterative result obtained after the current iteration converges, and to obtain the power flow value of the power transmission and distribution system based on the iterative result obtained after stopping the iterative solution.

[0199] In a preferred embodiment, the model building module 11 includes:

[0200] The first power flow function acquisition unit is used to obtain the first power flow function of the distribution network based on the substation voltage and the distribution network node voltage.

[0201] The second power flow function acquisition unit is used to obtain the second power flow function of the substation based on the substation voltage, the distribution network node voltage and the substation power injection.

[0202] The third power flow function acquisition unit is used to obtain the third power flow function of the transmission network based on the substation voltage and the substation power injection.

[0203] The model building unit is used to express the power flow calculation problem of the integrated transmission and distribution system as a voltage fixed-point iterative problem based on the first power flow function, the second power flow function and the third power flow function, and to establish a power flow calculation model with the substation voltage as the iteration vector.

[0204] In one preferred embodiment, the real-time operating data includes real-time operating data of the distribution network and real-time operating data of the transmission network.

[0205] Further, preferably, the data acquisition module 12 includes:

[0206] The unit for obtaining the result of an iteration is used to solve the power flow calculation model using an iterative solution method to obtain the substation voltage. After each iteration is completed, the iteration result is obtained.

[0207] The real-time operation data acquisition unit of the distribution network is used to acquire the injected active power, injected reactive power and node voltage of each node of the distribution network as real-time operation data of the distribution network.

[0208] The real-time operation data acquisition unit of the power transmission network is used to acquire the active power, reactive power, voltage amplitude and phase angle of the substation as real-time operation data of the power transmission network.

[0209] The real-time operation data acquisition unit is used to obtain the real-time operation data of the integrated power transmission and distribution system based on the real-time operation data of the distribution network and the real-time operation data of the transmission network.

[0210] In a preferred embodiment, the sensitivity matrix calculation module 13 includes:

[0211] The power transmission network sensitivity matrix calculation unit is used to calculate the power transmission network sensitivity matrix based on the real-time operation data of the power transmission network obtained after the current iteration.

[0212] The electrical parameter change calculation unit is used to calculate the power change and voltage change between different operating states of the distribution network based on the real-time operating data of the distribution network obtained after the current iteration, using the Monte Carlo method.

[0213] An overdetermined equation set establishment unit is used to establish an overdetermined equation set based on the power change and the voltage change.

[0214] The equation solving unit is used to solve the overdetermined equation system using the least squares method to obtain the root node sensitivity matrix of the distribution network.

[0215] Further, preferably, the electrical parameter change calculation unit is specifically used for:

[0216] Cluster the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state;

[0217] Based on the first voltage distribution, a small change in power is generated using the Monte Carlo method, and the second voltage distribution corresponding to the small change in power under the operating state is calculated.

[0218] The power change is obtained based on the power distribution near the current operating state;

[0219] Calculate the voltage change based on the first voltage distribution and the second voltage distribution.

[0220] Furthermore, as a preferred embodiment, the...

[0221] Clustering is performed on the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state, including:

[0222] The two real-time operation data of the power distribution network with the largest distance are selected as cluster centers;

[0223] The K-means clustering method is used to perform at least two levels of clustering on the real-time operating data of the power distribution network obtained after the current iteration of the solution based on the cluster centers, and the clustering measure is calculated based on the clustering results.

[0224] The clustering error rate is obtained based on the clustering metric.

[0225] When the clustering error rate is greater than a preset threshold, the two real-time operation data of the power distribution network with the largest distance are reselected as cluster centers in the next level.

[0226] When the clustering error rate is not greater than a preset threshold, the number of cluster centers and the clustering result are obtained;

[0227] Based on the number of cluster centers and the clustering results, the power distribution and its corresponding first voltage distribution near the current operating state are obtained.

[0228] In a preferred embodiment, the equation-solving unit is specifically used for:

[0229] By introducing a residual sum of squares function into the overdetermined system of equations, a modified overdetermined system of equations is obtained.

[0230] The least squares method is used to differentiate the parameters to be determined in the modified overdetermined equation system and solve for the maximum and minimum values ​​to obtain the root node sensitivity matrix of the distribution network.

[0231] In a preferred embodiment, the convergence determination module 14 includes:

[0232] The spectral radius calculation unit is used to obtain the spectral radius of the comprehensive sensitivity matrix based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix.

[0233] The convergence determination unit is used to determine that the iteration result is converged when the spectral radius of the integrated sensitivity matrix is ​​less than a preset spectral radius threshold; otherwise, it determines that the iteration result is not converged.

[0234] In a preferred embodiment, the power flow calculation module 15 includes:

[0235] An iteration stopping unit is used to stop the iterative solution of the power flow calculation model when the iterative result obtained after the current iteration converges.

[0236] A separate power flow calculation unit is used to calculate the power flow values ​​of the distribution network, substation, and transmission network based on the iteration results obtained after stopping the iterative solution.

[0237] An integrated power flow calculation unit is used to obtain an integrated power flow value for transmission and distribution based on the power flow value of the distribution network, the power flow value of the substation, and the power flow value of the transmission network.

[0238] The power flow calculation system based on the voltage sensitivity of the root node of the distribution network provided by the embodiments of the present invention can get rid of the dependence on the complete network topology and parameter information in the power flow calculation process, and can quickly and accurately determine the convergence of the power flow calculation, so as to further improve the convergence of the power flow calculation of the integrated transmission and distribution, and improve the reliability and stability of the power system.

[0239] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0240] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A power flow calculation method based on the voltage sensitivity of the root node in a distribution network, characterized in that, include: The power flow calculation problem of integrated transmission and distribution is expressed as a voltage fixed-point iterative problem, and a power flow calculation model with the substation voltage as the iteration vector is established. The power flow calculation model is solved using an iterative solution method to obtain the substation voltage. After each iteration, the iteration results and real-time operation data of the integrated power transmission and distribution system are obtained. Based on the real-time operating data obtained after the current iteration, the least squares method is used to calculate the transmission network sensitivity matrix and the distribution network root node sensitivity matrix. Based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix, determine the convergence of the iterative result obtained after the current iteration. When the iterative result obtained after the current iteration converges, the iterative solution of the power flow calculation model is stopped, and the power flow value of the integrated transmission and distribution system is obtained based on the iterative result obtained after stopping the iterative solution. The method of representing the integrated power flow calculation problem as a voltage fixed-point iterative problem and establishing a power flow calculation model with the substation voltage as the iteration vector includes: The first power flow function of the distribution network is obtained based on the substation voltage and the distribution network node voltage. The second power flow function of the substation is obtained based on the substation voltage, the distribution network node voltage, and the power injection of the substation. The third power flow function of the transmission network is obtained based on the substation voltage and the substation power injection. Based on the first power flow function, the second power flow function, and the third power flow function, the power flow calculation problem of the integrated transmission and distribution system is expressed as a voltage fixed-point iterative problem, and a power flow calculation model with the substation voltage as the iteration vector is established. The real-time operation data includes real-time operation data of the distribution network and real-time operation data of the transmission network; The step of calculating the transmission network sensitivity matrix and the distribution network root node sensitivity matrix using the least squares method based on the real-time operating data obtained after the current iteration includes: Calculate the power transmission network sensitivity matrix based on the real-time operation data of the power transmission network obtained after the current iteration. Based on the real-time operating data of the distribution network obtained after the current iteration, the Monte Carlo method is used to calculate the power change and voltage change between different operating states of the distribution network. Based on the power change and the voltage change, establish an overdetermined system of equations; The overdetermined equations are solved using the least squares method to obtain the root node sensitivity matrix of the distribution network.

2. The power flow calculation method based on the root node voltage sensitivity of a distribution network as described in claim 1, characterized in that, The iterative solution method is used to solve the power flow calculation model to obtain the substation voltage. After each iteration, the iteration results and real-time operating data of the integrated transmission and distribution power grid system are obtained, including: The power flow calculation model is solved using an iterative solution method to obtain the substation voltage. After each iteration, the iteration result is obtained. The injected active power, injected reactive power, and node voltage of each node in the distribution network are obtained as real-time operation data of the distribution network. The active power, reactive power, voltage amplitude, and phase angle of the substation are acquired as real-time operation data of the power transmission network. Based on the real-time operation data of the distribution network and the real-time operation data of the transmission network, the real-time operation data of the integrated transmission and distribution power grid system is obtained.

3. The power flow calculation method based on the root node voltage sensitivity of a distribution network as described in claim 1, characterized in that, The method of calculating the power and voltage changes between different operating states of the distribution network using the Monte Carlo method, based on the real-time operating data obtained after the current iteration, includes: Cluster the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state; Based on the first voltage distribution, a small change in power is generated using the Monte Carlo method, and the second voltage distribution corresponding to the small change in power under the operating state is calculated. The power change is obtained based on the power distribution near the current operating state; Calculate the voltage change based on the first voltage distribution and the second voltage distribution.

4. The power flow calculation method based on the root node voltage sensitivity of a distribution network as described in claim 3, characterized in that, The step of clustering the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state includes: The two real-time operation data of the power distribution network with the largest distance are selected as cluster centers; The K-means clustering method is used to perform at least two levels of clustering on the real-time operating data of the power distribution network obtained after the current iteration of the solution based on the cluster centers, and the clustering measure is calculated based on the clustering results. The clustering error rate is obtained based on the clustering metric. When the clustering error rate is greater than a preset threshold, the two real-time operation data of the power distribution network with the largest distance are reselected as cluster centers in the next level. When the clustering error rate is not greater than a preset threshold, the number of cluster centers and the clustering result are obtained; Based on the number of cluster centers and the clustering results, the power distribution and its corresponding first voltage distribution near the current operating state are obtained.

5. The power flow calculation method based on the root node voltage sensitivity of a distribution network as described in claim 1, characterized in that, The method of solving the overdetermined equations using the least squares method yields the root node sensitivity matrix of the distribution network, including: By introducing a residual sum of squares function into the overdetermined system of equations, a modified overdetermined system of equations is obtained. The least squares method is used to differentiate the parameters to be determined in the modified overdetermined equation system and solve for the maximum and minimum values ​​to obtain the root node sensitivity matrix of the distribution network.

6. The power flow calculation method based on the root node voltage sensitivity of a distribution network as described in claim 1, characterized in that, The step of determining the convergence of the iterative result obtained after the current iteration based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix includes: The spectral radius of the comprehensive sensitivity matrix is ​​obtained based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix. When the spectral radius of the integrated sensitivity matrix is ​​less than a preset spectral radius threshold, the iteration result is determined to be converged; otherwise, the iteration result is determined to be non-converged.

7. The power flow calculation method based on the root node voltage sensitivity of a distribution network as described in claim 1, characterized in that, When the iterative result obtained after the current iteration converges, the iterative solution of the power flow calculation model is stopped, and the integrated power flow value is obtained based on the iterative result obtained after stopping the iterative solution, including: When the iterative result obtained after the current iteration converges, the iterative solution of the power flow calculation model is stopped; Based on the iterative results obtained after stopping the iterative solution, the power flow values ​​of the distribution network, substation, and transmission network are calculated. The power flow value of the integrated transmission and distribution network is obtained based on the power flow value of the distribution network, the power flow value of the substation, and the power flow value of the transmission network.

8. A power flow calculation system based on the voltage sensitivity of the root node in a distribution network, characterized in that, include: The model building module is used to represent the power flow calculation problem of integrated transmission and distribution as a voltage fixed-point iterative problem and to build a power flow calculation model with the substation voltage as the iteration vector. The data acquisition module is used to solve the power flow calculation model using an iterative solution method to obtain the substation voltage. After each iteration, the module acquires the iteration results and the real-time operation data of the integrated power transmission and distribution system. The sensitivity matrix calculation module is used to calculate the transmission network sensitivity matrix and the distribution network root node sensitivity matrix using the least squares method based on the real-time operating data obtained after the current iteration. The convergence determination module is used to determine the convergence of the iterative result obtained after the current iteration based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix. The power flow value calculation module is used to stop the iterative solution of the power flow calculation model when the iterative result obtained after the current iteration solution converges, and to obtain the power flow value of the power transmission and distribution system based on the iterative result obtained after stopping the iterative solution. The model building module includes: The first power flow function acquisition unit is used to obtain the first power flow function of the distribution network based on the substation voltage and the distribution network node voltage. The second power flow function acquisition unit is used to obtain the second power flow function of the substation based on the substation voltage, the distribution network node voltage and the substation power injection. The third power flow function acquisition unit is used to obtain the third power flow function of the transmission network based on the substation voltage and the substation power injection. The model building unit is used to express the power flow calculation problem of the integrated transmission and distribution system as a voltage fixed-point iterative problem based on the first power flow function, the second power flow function and the third power flow function, and to establish a power flow calculation model with the substation voltage as the iteration vector; The real-time operation data includes real-time operation data of the distribution network and real-time operation data of the transmission network; The sensitivity matrix calculation module includes: The power transmission network sensitivity matrix calculation unit is used to calculate the power transmission network sensitivity matrix based on the real-time operation data of the power transmission network obtained after the current iteration. The electrical parameter change calculation unit is used to calculate the power change and voltage change between different operating states of the distribution network based on the real-time operating data of the distribution network obtained after the current iteration, using the Monte Carlo method. An overdetermined equation set establishment unit is used to establish an overdetermined equation set based on the power change and the voltage change. The equation solving unit is used to solve the overdetermined equation system using the least squares method to obtain the root node sensitivity matrix of the distribution network.

9. A power flow calculation system based on the root node voltage sensitivity of a distribution network as described in claim 8, characterized in that, The data acquisition module includes: The unit for obtaining the result of an iteration is used to solve the power flow calculation model using an iterative solution method to obtain the substation voltage. After each iteration is completed, the iteration result is obtained. The real-time operation data acquisition unit of the distribution network is used to acquire the injected active power, injected reactive power and node voltage of each node of the distribution network as real-time operation data of the distribution network. The real-time operation data acquisition unit of the power transmission network is used to acquire the active power, reactive power, voltage amplitude and phase angle of the substation as real-time operation data of the power transmission network. The real-time operation data acquisition unit is used to obtain the real-time operation data of the integrated power transmission and distribution system based on the real-time operation data of the distribution network and the real-time operation data of the transmission network.

10. The power flow calculation system based on the root node voltage sensitivity of a distribution network as described in claim 8, characterized in that, The electrical parameter change calculation unit is specifically used for: Cluster the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state; Based on the first voltage distribution, a small change in power is generated using the Monte Carlo method, and the second voltage distribution corresponding to the small change in power under the operating state is calculated. The power change is obtained based on the power distribution near the current operating state; Calculate the voltage change based on the first voltage distribution and the second voltage distribution.

11. The power flow calculation system based on the root node voltage sensitivity of a distribution network as described in claim 10, characterized in that, The step of clustering the real-time operating data of the distribution network obtained after the current iteration to obtain the power distribution and its corresponding first voltage distribution in the vicinity of the current operating state includes: The two real-time operation data of the power distribution network with the largest distance are selected as cluster centers; The K-means clustering method is used to perform at least two levels of clustering on the real-time operating data of the power distribution network obtained after the current iteration of the solution based on the cluster centers, and the clustering measure is calculated based on the clustering results. The clustering error rate is obtained based on the clustering metric. When the clustering error rate is greater than a preset threshold, the two real-time operation data of the power distribution network with the largest distance are reselected as cluster centers in the next level. When the clustering error rate is not greater than a preset threshold, the number of cluster centers and the clustering result are obtained; Based on the number of cluster centers and the clustering results, the power distribution and its corresponding first voltage distribution near the current operating state are obtained.

12. The power flow calculation system based on the root node voltage sensitivity of a distribution network as described in claim 8, characterized in that, The equation-solving unit is specifically used for: By introducing a residual sum of squares function into the overdetermined system of equations, a modified overdetermined system of equations is obtained. The least squares method is used to differentiate the parameters to be determined in the modified overdetermined equation system and solve for the maximum and minimum values ​​to obtain the root node sensitivity matrix of the distribution network.

13. The power flow calculation system based on the root node voltage sensitivity of a distribution network as described in claim 8, characterized in that, The convergence determination module includes: The spectral radius calculation unit is used to obtain the spectral radius of the comprehensive sensitivity matrix based on the transmission network sensitivity matrix and the distribution network root node sensitivity matrix. The convergence determination unit is used to determine that the iteration result is converged when the spectral radius of the integrated sensitivity matrix is ​​less than a preset spectral radius threshold; otherwise, it determines that the iteration result is not converged.

14. The power flow calculation system based on the root node voltage sensitivity of a distribution network as described in claim 8, characterized in that, The power flow value calculation module includes: An iteration stopping unit is used to stop the iterative solution of the power flow calculation model when the iterative result obtained after the current iteration converges. A separate power flow calculation unit is used to calculate the power flow values ​​of the distribution network, substation, and transmission network based on the iteration results obtained after stopping the iterative solution. An integrated power flow calculation unit is used to obtain an integrated power flow value for transmission and distribution based on the power flow value of the distribution network, the power flow value of the substation, and the power flow value of the transmission network.

Images