Distribution network configuration optimization method and device based on harmonic compensation and network loss suppression

Abstract

The application relates to a power distribution network configuration optimization method and device based on harmonic compensation and network loss suppression, a computer device, a storage medium and a computer program product. The method comprises the following steps: obtaining each harmonic impedance of each branch of a power distribution network, each harmonic mutual impedance between nodes, an association matrix formed between all nodes and all branches, each harmonic current of each node and each harmonic voltage of each node when no shunt active power filter is configured; determining a target function and a target condition of shunt active power filter configuration of the power distribution network, solving the target function through a multi-objective particle swarm optimization algorithm, obtaining a global platonic optimal solution set of the target function, and determining a final total configuration capacity scheme of the shunt active power filter from the global platonic optimal solution set under the target condition. The method can improve the power quality of the power distribution network.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power electronics, in particular to a power distribution network configuration optimization method and device based on harmonic compensation and network loss suppression. BACKGROUND

[0002] In recent years, the number of nonlinear loads dispersedly connected to the power distribution network is growing, making the harmonic distortion problem more and more serious. Harmonic voltage distortion not only affects the normal operation of electrical equipment, but also causes additional harmonic network loss. For such problems, a shunt active power filter (SAPF) can compensate for the harmonic current generated by nonlinear loads, thereby eliminating the harmonic distortion caused by harmonic sources.

[0003] In related technologies, the traditional SAPF point-to-point configuration scheme is to install it at the user side near the nonlinear load for harmonic compensation. However, with the distributed access of nonlinear loads in the power distribution network, the point-to-point configuration method has higher requirements for the number and capacity of SAPF configuration, thereby causing the problem of high installation and operation and maintenance cost. Therefore, there is an urgent need for a power distribution network configuration optimization method based on harmonic compensation and network loss suppression. SUMMARY

[0004] Therefore, it is necessary to provide a power distribution network configuration optimization method and device based on harmonic compensation and network loss suppression, a computer device, a computer readable storage medium, and a computer program product in view of the above technical problems.

[0005] In a first aspect, the present application provides a power distribution network configuration optimization method based on harmonic compensation and network loss suppression. The method comprises:

[0006] obtaining the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node of the power distribution network when no shunt active power filter is configured;

[0007] determining the target function and the target condition of the shunt active power filter configuration of the power distribution network, wherein the target function includes the harmonic network loss function of the power distribution network and the total configuration capacity function of the shunt active power filter, and the target condition is set based on whether the harmonic voltage content rate of each node meets the preset harmonic voltage content rate and whether the total voltage distortion rate of each node meets the preset voltage distortion rate;

[0008] According to the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node when no shunt active power filter is configured and the harmonic voltage of each node, a global Platonic optimal solution set is obtained by solving the objective function through a multi-objective particle swarm optimization algorithm, and the final total configuration capacity scheme of the shunt active power filter is determined from the global Platonic optimal solution set under the target condition, wherein the global Platonic optimal solution set includes the alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0009] In one of the embodiments, the objective function for determining the configuration of the shunt active power filter in the power distribution network comprises:

[0010] The harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured is obtained.

[0011] The harmonic network loss function of the power distribution network is determined according to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches and the harmonic current of each node when no shunt active power filter is configured.

[0012] The total configuration capacity function of the shunt active power filter is determined according to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured.

[0013] In one of the embodiments, the harmonic network loss function of the power distribution network comprises:

[0014] The residual harmonic voltage function of each node is determined according to the harmonic current injected at each node when no shunt active power filter is configured, the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured and the harmonic mutual impedance between each node.

[0015] The harmonic network loss function of the power distribution network is determined according to the residual harmonic voltage function of each node, the correlation matrix formed between all nodes and all branches and the harmonic impedance of all branches.

[0016] In one of the embodiments, the total configuration capacity function of the shunt active power filter is determined according to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, comprising:

[0017]

[0018] In formula (1), I SAPF represents the total configuration capacity of the SAPF, I SAPF,m represents the configuration capacity of the SAPF to the node m, represents the hth harmonic current injected by the parallel active power filter to the node m, H represents the highest order of the harmonic current, and N represents the total number of nodes of the power distribution network.

[0019] In one embodiment, the process of determining the harmonic voltage content rate of each node comprises:

[0020] obtaining the fundamental voltage of each node;

[0021] determining the harmonic voltage content rate of each node based on a preset formula;

[0022] The preset formula comprises:

[0023]

[0024] In formula (2), V represents the hth harmonic voltage content rate of the node n, represents the hth residual harmonic voltage of the node n, represents the fundamental voltage of the node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes of the power distribution network.

[0025] In one embodiment, the process of determining the total voltage distortion rate of each node comprises:

[0026]

[0027] In formula (3), THD n represents the total voltage distortion rate of the node n, represents the hth residual harmonic voltage of the node n, represents the fundamental voltage of the node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes of the power distribution network.

[0028] In a second aspect, the application further provides a power distribution network configuration optimization device based on harmonic compensation and network loss suppression. The device comprises:

[0029] An acquisition module is configured to acquire the harmonic impedance of each branch of a power distribution network, the harmonic mutual impedance between nodes, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no parallel active power filter is configured.

[0030] The first determining module is configured to determine a target function and a target condition for the shunt active power filter configuration of the power distribution network, wherein the target function comprises a harmonic network loss function of the power distribution network and a total configuration capacity function of the shunt active power filter, and the target condition is set based on whether the harmonic voltage content of each node meets a preset harmonic voltage content and whether the total voltage distortion rate of each node meets a preset voltage distortion rate.

[0031] The second determining module is configured to solve the target function by using a multi-objective particle swarm optimization algorithm according to the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no shunt active power filter is configured, to obtain a global Plat optimal solution set of the target function, and to determine a final total configuration capacity scheme of the shunt active power filter from the global Plat optimal solution set under the target condition, wherein the global Plat optimal solution set comprises an alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0032] In a third aspect, the present application further provides a computer device. The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0033] The harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no shunt active power filter is configured are obtained.

[0034] The target function and the target condition for the shunt active power filter configuration of the power distribution network are determined, wherein the target function comprises a harmonic network loss function of the power distribution network and a total configuration capacity function of the shunt active power filter, and the target condition is set based on whether the harmonic voltage content of each node meets a preset harmonic voltage content and whether the total voltage distortion rate of each node meets a preset voltage distortion rate.

[0035] The target function is solved by using a multi-objective particle swarm optimization algorithm according to the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no shunt active power filter is configured, to obtain a global Plat optimal solution set of the target function, and a final total configuration capacity scheme of the shunt active power filter is determined from the global Plat optimal solution set under the target condition, wherein the global Plat optimal solution set comprises an alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0036] In a fourth aspect, the present application also provides a computer readable storage medium. The computer readable storage medium has a computer program stored thereon, and the computer program, when executed by a processor, implements the following steps:

[0037] obtaining each harmonic impedance of each branch of the power distribution network, each harmonic mutual impedance between each node, an association matrix formed between all nodes and all branches, each harmonic current of each node and each harmonic voltage of each node when no shunt active power filter is configured;

[0038] determining a target function and a target condition for the shunt active power filter configuration of the power distribution network, wherein the target function includes a harmonic network loss function of the power distribution network and a total configuration capacity function of the shunt active power filter, and the target condition is set based on whether each harmonic voltage content rate of each node meets a preset harmonic voltage content rate and whether a total voltage distortion rate of each node meets a preset voltage distortion rate;

[0039] solving the target function by a multi-objective particle swarm optimization algorithm according to each harmonic impedance of each branch of the power distribution network, each harmonic mutual impedance between each node, the association matrix formed between all nodes and all branches, each harmonic current of each node and each harmonic voltage of each node when no shunt active power filter is configured, to obtain a global platonic optimal solution set of the target function, and determining a final total configuration capacity scheme of the shunt active power filter from the global platonic optimal solution set under the target condition, wherein the global platonic optimal solution set includes an alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0040] In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program, and the computer program, when executed by a processor, implements the following steps:

[0041] obtaining each harmonic impedance of each branch of the power distribution network, each harmonic mutual impedance between each node, an association matrix formed between all nodes and all branches, each harmonic current of each node and each harmonic voltage of each node when no shunt active power filter is configured;

[0042] determining a target function and a target condition for the shunt active power filter configuration of the power distribution network, wherein the target function includes a harmonic network loss function of the power distribution network and a total configuration capacity function of the shunt active power filter, and the target condition is set based on whether each harmonic voltage content rate of each node meets a preset harmonic voltage content rate and whether a total voltage distortion rate of each node meets a preset voltage distortion rate;

[0043] According to the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no shunt active power filter is configured, the global platonic optimal solution set of the target function is obtained by solving the target function through the multi-objective particle swarm optimization algorithm, and the final total configuration capacity scheme of the shunt active power filter is determined from the global platonic optimal solution set under the target condition, wherein the global platonic optimal solution set includes the alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0044] The power distribution network configuration optimization method, device, computer equipment, storage medium and computer program product based on harmonic compensation and network loss suppression described above obtain the harmonic impedance of each branch of the power distribution network, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no shunt active power filter is configured; determine the target function and target condition of the shunt active power filter configuration of the power distribution network, solve the target function through the multi-objective particle swarm optimization algorithm, obtain the global platonic optimal solution set of the target function, and determine the final total configuration capacity scheme of the shunt active power filter from the global platonic optimal solution set under the target condition. The method can reduce the harmonic content of the power distribution network, thereby improving the power quality of the power distribution network and optimizing the configuration capacity of the SAPF. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 It is an application environment diagram of the power distribution network configuration optimization method based on harmonic compensation and network loss suppression in one embodiment;

[0046] Figure 2 It is a flowchart of the power distribution network configuration optimization method based on harmonic compensation and network loss suppression in one embodiment;

[0047] Figure 3 It is a schematic diagram of the IEEE 18-node power distribution network system topology in one embodiment;

[0048] Figure 4 It is a schematic diagram of the capacity of the nonlinear load in one embodiment;

[0049] Figure 5 It is a schematic diagram of the SAPF capacity to be configured at each node in one embodiment;

[0050] Figure 6 It is a structural block diagram of the power distribution network configuration optimization device based on harmonic compensation and network loss suppression in one embodiment;

[0051] Figure 7An internal structure diagram of a computer device in an embodiment. DETAILED DESCRIPTION

[0052] For the purpose, technical solutions and advantages of the present application to be clearer, the present application is further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.

[0053] The power distribution network configuration optimization method based on harmonic compensation and network loss suppression provided by the embodiments of the present application can be applied to the application environment as shown in the figure. Figure 1 The terminal 101 communicates with the server 102 through the network. The data storage system can store the data required to be processed by the server 102. The data storage system can be integrated on the server 102, or placed on the cloud or other network servers.

[0054] The terminal obtains the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current injected at each node and the harmonic voltage injected at each node when no shunt active power filter is configured in the power distribution network; determines the target function and the target condition of the shunt active power filter configuration of the power distribution network, wherein the target function includes the harmonic network loss function of the power distribution network and the total configuration capacity function of the shunt active power filter, and the target condition is set based on whether the harmonic voltage content rate of each node meets the preset harmonic voltage content rate and whether the total voltage distortion rate of each node meets the preset voltage distortion rate; the target function is solved by a multi-objective particle swarm optimization algorithm to obtain a global platonic optimal solution set of the target function, and the final total configuration capacity scheme of the shunt active power filter is determined from the global platonic optimal solution set under the target condition, and the global platonic optimal solution set includes the alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0055] The terminal 101 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things device can be a smart speaker, a smart television, a smart air conditioner, a smart vehicle device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server 102 can be implemented by an independent server or a server cluster composed of multiple servers.

[0056] In one embodiment, as shown in the figure, Figure 2As shown, a power distribution network configuration optimization method based on harmonic compensation and network loss suppression is provided. In this embodiment, the method is applied to a terminal. It should be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and can be realized through the interaction of the terminal and the server. In this embodiment, the method includes the following steps:

[0057] 201. Obtain the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node of the power distribution network.

[0058] 202. Determine the objective function and objective condition of the shunt active power filter configuration of the power distribution network, wherein the objective function includes the harmonic network loss function of the power distribution network and the total configuration capacity function of the shunt active power filter, and the objective condition is set based on whether the harmonic voltage content rate of each node meets the preset harmonic voltage content rate and whether the total voltage distortion rate of each node meets the preset voltage distortion rate.

[0059] 203. According to the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when the shunt active power filter is not configured, the global Plat optimal solution set of the objective function is obtained by solving the objective function through a multi-objective particle swarm optimization algorithm, and the final total configuration capacity scheme of the shunt active power filter is determined from the global Plat optimal solution set under the objective condition, wherein the global Plat optimal solution set includes the candidate total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0060] Wherein, the power distribution network configuration optimization includes the configuration optimization of the shunt active power filter in the power distribution network. Harmonic refers to a distortion of a normal current waveform. In general, harmonic sources are mainly divided into three categories, namely semiconductor converters, nonlinear impedances and saturated reactances. In the above step 201, the harmonic impedance of each branch, the harmonic mutual impedance between each node and the correlation matrix formed between all nodes and all branches are obtained according to the power distribution network line planning data manual, wherein the harmonic impedance of each branch refers to the harmonic impedance between nodes in the power distribution network.

[0061] In addition, when the shunt active power filter is not configured, the complex vector expression of the harmonic voltage of each node in the power distribution network is as follows:

[0062]

[0063] Vn,h,befrepresents the hth harmonic voltage of node n when no SAPF is configured, subscript bef represents the state of the node when no SAPF is configured, subscript n = 1, 2, …, N is the node number, and subscript h = 1, 2, …, H is the harmonic number.

[0064] In step 202, the objective function can also be referred to as a fitness function, and the objective function can be composed of multiple functions. In the embodiment of the present application, the objective function mainly includes a harmonic network loss function of the power distribution network and a total configuration capacity function of the SAPF. The harmonic network loss of the power distribution network refers to the total harmonic power loss in the power distribution network, and the total configuration capacity of the SAPF refers to the total current injected by all SAPFs into the power distribution network. The objective of the objective function in the embodiment of the present application is to minimize the harmonic network loss of the power distribution network and the total configuration capacity of the SAPF.

[0065] In addition, in step 202, the preset harmonic voltage content rate and the preset total voltage distortion rate refer to the harmonic voltage content rate and the total voltage distortion rate specified in the national standard. In general, the harmonic voltage content rate in the power distribution network should be lower than the harmonic voltage content rate specified in the national standard, and the total voltage distortion rate should be lower than the total voltage distortion rate specified in the national standard.

[0066] The harmonic network loss function of the power distribution network includes the harmonic impedance of each branch of the power distribution network, the harmonic mutual impedance between nodes, the correlation matrix formed between all nodes and all branches, and the harmonic current of each branch when no SAPF is configured.

[0067] In step 203, the multi-objective particle swarm optimization (MOPSO) algorithm is a particle swarm optimization (PSO) algorithm that can only be used in single objective and applied to multi-objective. The steps of the MOPSO algorithm include:

[0068] (1) Initialization, set the number of particles P of the particle swarm, the upper and lower limits of the position and speed of each particle, and then randomly select the initial position and initial speed of each particle within the limit range;

[0069] (2) Calculate the fitness function of each particle;

[0070] ​(3) Determine the current particle swarm and individual's set of platonic optimal solution, if there is a particle, all of its fitness function is greater than the target particle, then the target particle does not belong to the platonic optimal solution, replace the original target particle with the particle as a new target particle; otherwise, the target particle belongs to the platonic optimal solution set;

[0071] (4) Update the particle position and speed, randomly select a particle position in the individual platonic optimal solution set and the global platonic optimal solution set of the particle, as the "individual platonic optimal solution" and "global platonic optimal solution" of the current particle, based on the iteration process of the multi-objective particle swarm optimization algorithm, update the position X and speed V of all particles according to formula (5) and formula (6):

[0072]

[0073]

[0074] In formula (5) and formula (6), r represents the iteration number, p represents the particle number; ω represents the inertia coefficient of inheriting the last particle speed, ω=0.5 when the iteration number is less than 50% of the iteration upper limit, and ω=0.8 when the iteration number is greater than 50% of the iteration upper limit; c1 and c2 represent the learning factors of the individual platonic optimal solution and the global platonic optimal solution respectively, both equal to 2; rand() represents a random number between 0 and 1; Archivep and Archiveg are the dominated particles of the current particle, which are the individual platonic optimal solution and the global platonic optimal solution randomly selected from the individual platonic optimal solution set of particle p and the global platonic optimal solution set of the particle swarm respectively.

[0075] (5) Iteration termination condition, when the iteration number reaches the specified upper limit or the global platonic optimal solution no longer changes, the iteration is terminated; otherwise, return to the above step (2).

[0076] Specifically, first, according to the problem to be solved in the power distribution network, that is, to realize the configuration optimization of the parallel active power filter of the power distribution network, the target is determined, that is, to reduce the total configuration capacity of the parallel active power filter under the condition of small harmonic network loss, and then two objective functions can be determined, which are the harmonic network loss function of the power distribution network and the total configuration capacity function of the parallel active power filter. Then, based on the multi-objective particle swarm optimization algorithm, the two objective functions are solved, and the global platonic optimal solution set is obtained, and the objective function of the solution set is the platonic optimal front (Pareto set) of "harmonic network loss of power distribution network after configuration SAPF-SAPF configuration total capacity". Finally, under the limitation of the target condition, the final total configuration capacity scheme of the parallel active power filter is determined from the global platonic optimal solution set.

[0077] The method provided by the embodiment of the application can obtain the global platonic optimal solution set of the target function by determining the target function of the configuration of the shunt active power filter of the power distribution network and solving the target function based on the multi-objective particle swarm optimization algorithm, and can reduce the power loss caused by harmonics in the power distribution network when reducing the total configuration capacity of the shunt active power filter, thereby improving the use value and efficiency of the shunt active power filter.

[0078] In combination with the above embodiment, in one embodiment, the target function of the configuration of the shunt active power filter of the power distribution network comprises:

[0079] 301, obtaining the harmonic currents of each order injected by the shunt active power filter into each node when the shunt active power filter is configured;

[0080] 302, determining a harmonic network loss function of the power distribution network according to the harmonic currents of each order injected by the shunt active power filter into each node when the shunt active power filter is configured, the harmonic impedances of each order of each branch, the harmonic mutual impedances of each order between nodes, the association matrix formed between all nodes and all branches, the harmonic currents of each order of each node and the harmonic voltages of each order of each node when the shunt active power filter is not configured;

[0081] 303, determining a total configuration capacity function of the shunt active power filter according to the harmonic currents of each order injected by the shunt active power filter into each node when the shunt active power filter is configured.

[0082] In the above step 301, the harmonic currents of each order injected by the shunt active power filter into each node are the particle positions in the multi-objective particle swarm optimization algorithm in the above step 203, and the harmonic currents of each order injected by the shunt active power filter into each node can be expressed in the form of a complex vector:

[0083]

[0084] In formula (7), indicates the harmonic current of each order injected by the shunt active power filter into node n, the subscript SAPF indicates that the node is in the state of being configured with the SAPF, the subscript n=1, 2, …, N is the node number, and the subscript h=1, 2, …, H is the harmonic order.

[0085] The speed of the particle is defined by a complex matrix V, which has the same dimension as the position matrix X of the particle. The speed of the particle determines the iteration speed of the particle position, and is updated together with the particle position. The position and speed update formulas of the particle are shown in formulas (5) and (6) respectively.

[0086] The total configuration capacity function of the parallel active power filter in the objective function needs to be solved, wherein the SAPF capacity to be configured at the node m can be expressed as:

[0087]

[0088] In formula (8), I SAPF,m represents the SAPF capacity configured at the node m, The hth harmonic current injected by the SAPF to the node m, and H represents the highest order of the harmonic current.

[0089] It is worth mentioning that when the objective function is solved for the first time in the preset solution range by the multi-objective particle swarm optimization algorithm, it is assumed that each node in the power distribution network is configured with the SAPF, and in the solution process, the harmonic currents injected by the parallel active power filter to the corresponding node at any node in the power distribution network can change, that is, the position of the particle changes in the iteration process.

[0090] Specifically, after the harmonic currents injected by the parallel active power filter to all nodes are updated once, that is, after the position of each particle is updated once, the speed of the corresponding particle is also updated, and at the same time, the position of the particle is updated, and the two objective values of the particle at the new position are determined based on the objective function. After all particles determine their respective two objective values, the individual platonic optimal solution set and the global platonic optimal solution set are determined based on the two objective values corresponding to all particles.

[0091] The method provided by the embodiment of the application can determine the harmonic network loss function of the power distribution network and the total configuration capacity function of the parallel active power filter, and solve the two objective functions by the multi-objective particle swarm optimization algorithm, so that the global platonic optimal solution set of the two objective functions can be obtained, and then the global platonic optimal solution of the two objective functions can be obtained.

[0092] In combination with the content of the above embodiment, in one embodiment, the harmonic network loss function of the power distribution network is determined, including:

[0093] 401. Determine the residual harmonic voltage function of each node according to the harmonic currents injected at each node when no parallel active power filter is configured, the harmonic currents injected by the parallel active power filter to each node when the parallel active power filter is configured, and the harmonic mutual impedance between nodes;

[0094] 402. Determine the harmonic network loss function of the power distribution network according to the residual harmonic voltage function of each node, the association matrix formed between all nodes and all branches, and the harmonic impedance of all branches.

[0095] Specifically, according to the harmonic currents of each node when the shunt active power filter is not configured, the harmonic currents injected by the shunt active power filter into each node when the shunt active power filter is configured, and the harmonic mutual impedances between the nodes, a residual harmonic voltage function of each node is determined, comprising:

[0096]

[0097] In formula (9), represents the hth residual harmonic voltage of node n after the SAPF is configured, represents the hth harmonic voltage at each node when the SAPF is not configured, represents the hth harmonic voltage injected by the SAPF into node m when the SAPF is configured, represents the hth harmonic current injected by the SAPF into node m when the SAPF is configured, represents the hth harmonic impedance between nodes m and n, and N is the total number of nodes in the power distribution network.

[0098] According to the residual harmonic voltage function of each node, the associated matrix formed between all nodes and all branches, and the harmonic impedances of all branches, a harmonic network loss function of the power distribution network is determined, comprising:

[0099]

[0100]

[0101] In formula (10), P R harmonic network loss of the power distribution network, represents the hth harmonic voltage of branch l, represents the hth harmonic impedance of branch l, H represents the highest order of the harmonic voltage (impedance), and L represents the total number of branches of the power distribution network; in formula (11), represents the hth harmonic voltage of branch l, A n,l represents the element of the nth row and the lth column of the associated matrix A between all nodes and all branches in the power distribution network, wherein the associated matrix A is uniquely determined by the network topology of the power distribution network.

[0102] The method provided by the embodiment of the application can obtain the total harmonic network loss of the power distribution network by determining the residual harmonic voltage of each node, so that the multi-objective particle swarm optimization algorithm can be used to solve the target function to obtain a smaller harmonic network loss, and thus the harmonic network loss of the power distribution network can be reduced.

[0103] In combination with the above embodiment, in one embodiment, according to the harmonic currents injected by the shunt active power filter into each node when the shunt active power filter is configured, a total configuration capacity function of the shunt active power filter is determined, comprising:

[0104]

[0105] In formula (12), I SAPF represents the total configuration capacity of the SAPF, I SAPF,m represents the configuration capacity of the SAPF to the node m, represents the hth harmonic current injected by the SAPF to the node m, H represents the highest order of the harmonic current, and N represents the total quantity of nodes of the power distribution network.

[0106] Specifically, in the process of solving the objective function by the multi-objective particle swarm optimization algorithm, the position of the particle in the particle swarm (i.e., the harmonic current injected by the SAPF to each node) is updated, and thus the total configuration capacity of the SAPF is also updated after the position of the particle in the particle swarm is updated each time.

[0107] In addition, before the objective function is solved by the multi-objective particle swarm optimization algorithm, it is assumed that each node in the power distribution network is configured with the SAPF at the beginning. Most of the harmonic currents injected by the SAPF are optimized in the iterative solving process, and if the harmonic current injected by the SAPF of a certain node becomes 0 in the iterative solving process, it indicates that the SAPF does not need to be configured for the node.

[0108] The method provided by the embodiment of the application can obtain the total configuration capacity of the SAPF by configuring the SAPF and the harmonic current injected by the SAPF to each node.

[0109] In combination with the above embodiment, in one embodiment, the determination process of the harmonic voltage content rate of each node includes the following steps.

[0110] 501. Obtain the fundamental voltage of each node.

[0111] 502. Determine the harmonic voltage content rate of each node based on a preset formula.

[0112] The preset formula includes the following formula (13).

[0113]

[0114] In formula (13), V represents the hth harmonic voltage content rate of the node n, represents the hth residual harmonic voltage of the node n, represents the fundamental voltage of the node n, H represents the highest order of the harmonic voltage, and N represents the total quantity of nodes of the power distribution network.

[0115] Specifically, after determining the harmonic voltage content rate of each node, it is judged whether the harmonic content rate of the node meets the standard according to the preset harmonic voltage content rate.

[0116] The method provided by the embodiment of the application can determine the harmonic voltage content rate of each node through the fundamental voltage and the harmonic voltage of each node, thereby judging whether the harmonic content rate of the node meets the standard according to the preset harmonic voltage content rate, and finally determining the final SAPF configuration scheme, and reducing the harmonic voltage of the power distribution network.

[0117] In combination with the above embodiment, in one embodiment, the determination process of the voltage total distortion rate of each node comprises:

[0118]

[0119] In formula (14), THD n represents the voltage total distortion rate of node n, represents the h-order residual harmonic voltage of node n, represents the fundamental voltage of node n, H represents the highest order of the harmonic voltage, and N represents the total amount of nodes of the power distribution network.

[0120] Specifically, before determining the voltage total distortion rate of each node, the harmonic voltage of each node and the fundamental voltage of each node need to be determined. In actual application, the fundamental voltage and the harmonic voltage are obtained by decomposing the voltage waveform through Fourier analysis, wherein the voltage waveform with the lowest frequency is the fundamental voltage, and the voltage waveforms with other frequencies are the harmonic voltages.

[0121] The method provided by the embodiment of the application can obtain the voltage total distortion rate of the corresponding node through the fundamental voltage and the harmonic voltage of each node, thereby judging whether the voltage total distortion rate of the node meets the standard according to the preset voltage total distortion rate, and finally determining the final SAPF configuration scheme, and reducing the distortion rate of the harmonic voltage of the power distribution network.

[0122] In combination with the above embodiment, in one embodiment, the final total configuration capacity scheme of the parallel active power filter is determined from the global Plato optimal solution set under a target condition, wherein the target condition comprises:

[0123]

[0124]

[0125] In formula (15), α represents the preset harmonic voltage content rate, and in formula (16), β represents the preset voltage distortion rate.

[0126] Specifically, a solution set in which the harmonic voltage of each node meets the preset harmonic voltage content and the preset voltage distortion rate is selected from the global Plato optimal solution set as a first optimal solution set, then a solution set in which the number of SAPFs to be configured is the least is selected from the first optimal solution set as a second solution set, and finally a solution with the lowest harmonic network loss in the second solution set is selected as an optimal solution, which is the final total configuration capacity scheme of the distribution network SAPF.

[0127] The method provided by the embodiment of the application can determine the final total configuration capacity scheme of the distribution network SAPF from the global Plato optimal solution set by the target condition and the limitation of the number of SAPFs to be configured, so that the optimization of the configuration of the distribution network parallel active power filter is realized, and the power quality of the distribution network is improved.

[0128] To verify the feasibility and effectiveness of the above SAPF configuration optimization method, in an embodiment, an IEEE-18 node small distribution network containing 8 nonlinear loads is designed in MATLAB, the SAPF is configured according to the above steps, and the harmonic states of the distribution network before and after the configuration are compared.

[0129] Figure 3 For the topology of the built IEEE 18 node distribution network system, nonlinear loads are configured at buses 2, 4, 6, 8, 12, 13, 15 and 16. In the simulation, the 5th and 7th harmonic currents generated by each nonlinear load have the same proportion of fundamental capacity (5th harmonic current content is 37.60%, 7th harmonic current content is 16.77%), and the capacities of all nonlinear loads are as shown in Figure 4 .

[0130] Under the target condition, the final total configuration capacity scheme of the small distribution network SAPF includes: 3 SAPFs are configured and installed at nodes 8, 12 and 16, and the SAPF capacity to be configured at each node is as shown in Figure 5 .

[0131] The method provided by the embodiment of the application can reduce the harmonic network loss generated by the nonlinear load in the distribution network system by reasonable configuration of the SAPF, so that the efficiency of the SAPF can be improved, and the method has strong engineering application value.

[0132] It should be understood that although the steps in the flowcharts involved in the embodiments described above are shown in sequence according to the arrows, the steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of the steps is not strictly limited in sequence, and the steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the embodiments described above can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of the steps or stages is not necessarily sequential, but can be alternately or alternately executed with at least part of other steps or steps or stages in other steps.

[0133] Based on the same inventive concept, the embodiments of the present application also provide a harmonic compensation and network loss suppression based power distribution network configuration optimization device for implementing the harmonic compensation and network loss suppression based power distribution network configuration optimization method described above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more harmonic compensation and network loss suppression based power distribution network configuration optimization device embodiments provided below can be referred to the limitations of the harmonic compensation and network loss suppression based power distribution network configuration optimization method described above, which will not be repeated here.

[0134] In one embodiment, as shown in Figure 6 A harmonic compensation and network loss suppression based power distribution network configuration optimization device is provided, comprising: an acquisition module 601, a first determination module 602, and a second determination module 603, wherein:

[0135] The acquisition module 601 is configured to acquire the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node, and the harmonic voltage of each node of the power distribution network when no shunt active power filter is configured.

[0136] The first determination module 602 is configured to determine the target function and the target condition of the shunt active power filter configuration of the power distribution network, wherein the target function includes the harmonic network loss function of the power distribution network and the total configuration capacity function of the shunt active power filter, and the target condition is set based on whether the harmonic voltage content rate of each node meets the preset harmonic voltage content rate and whether the total voltage distortion rate of each node meets the preset voltage distortion rate.

[0137] The second determining module 603 is configured to: according to the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node when no shunt active power filter is configured, and the harmonic voltage of each node, solve a target function by using a multi-objective particle swarm optimization algorithm to obtain a global Plat optimal solution set of the target function, and determine a final total configuration capacity scheme of the shunt active power filter from the global Plat optimal solution set under a target condition, wherein the global Plat optimal solution set comprises an alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0138] In one embodiment, the first determining module 602 comprises:

[0139] The first obtaining sub-module is configured to: obtain the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured;

[0140] The first determining sub-module is configured to: obtain the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, and the harmonic current of each node when no shunt active power filter is configured, and determine a harmonic network loss function of the power distribution network.

[0141] The second determining sub-module is configured to: determine a total configuration capacity function of the shunt active power filter according to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured.

[0142] In one embodiment, the first determining sub-module comprises:

[0143] The first determining unit is configured to: determine a residual harmonic voltage function of each node according to the harmonic current injected at each node when no shunt active power filter is configured, the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, and the harmonic mutual impedance between each node.

[0144] The second determining unit is configured to: determine a harmonic network loss function of the power distribution network according to the residual harmonic voltage function of each node, the correlation matrix formed between all nodes and all branches, and the harmonic impedance of all branches.

[0145] In one embodiment, the second determining sub-module comprises: a total configuration capacity function.

[0146]

[0147] In formula (17), ISAPF represents the total configuration capacity of the SAPF, I SAPF,m represents the configuration capacity of the SAPF to the node m, represents the hth harmonic current injected by the parallel active power filter to the node m, H represents the highest order of the harmonic current, and N represents the total number of nodes of the power distribution network.

[0148] In one embodiment, the first determining module 602 further comprises:

[0149] The second obtaining sub-module is configured to obtain the fundamental voltage of each node.

[0150] The third determining sub-module is configured to determine the harmonic voltage content rate of each node based on a preset formula.

[0151] The preset formula comprises:

[0152]

[0153] In formula (18), Vn represents the hth harmonic voltage of the node n, represents the hth harmonic voltage content rate of the node n, represents the hth residual harmonic voltage of the node n, represents the fundamental voltage of the node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes of the power distribution network.

[0154] In one embodiment, the first determining module 602 further comprises a voltage total distortion rate function.

[0155]

[0156] In formula (19), THD represents the voltage total distortion rate of the node n, n represents the voltage total distortion rate of the node n, represents the hth residual harmonic voltage of the node n, represents the fundamental voltage of the node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes of the power distribution network.

[0157] The above various modules in the power distribution network configuration optimization device based on harmonic compensation and loss suppression can be realized by software, hardware, and combinations thereof, in whole or in part. The above various modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to the above various modules.

[0158] In one embodiment, a computer device is provided, which can be a server, and the internal structure diagram thereof can be as shown in Figure 7As shown in the figure. The computer device includes a processor, a memory and a network interface connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with the external terminal through the network connection. The computer program is executed by the processor to implement a power distribution network configuration optimization method based on harmonic compensation and network loss suppression.

[0159] Those skilled in the art can understand that, Figure 7 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0160] In one embodiment, a computer device is provided, comprising a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the following steps:

[0161] Obtaining the harmonic impedance of each branch of the power distribution network, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no shunt active power filter is configured;

[0162] Determine the objective function and the target condition of the shunt active power filter configuration of the power distribution network, wherein the objective function includes the harmonic network loss function of the power distribution network and the total configuration capacity function of the shunt active power filter, and the target condition is set based on whether the harmonic voltage content rate of each node meets the preset harmonic voltage content rate and whether the total voltage distortion rate of each node meets the preset voltage distortion rate;

[0163] According to the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no shunt active power filter is configured, the objective function is solved by a multi-objective particle swarm optimization algorithm to obtain a global platonic optimal solution set of the objective function. Under the target condition, the final total configuration capacity scheme of the shunt active power filter is determined from the global platonic optimal solution set, wherein the global platonic optimal solution set includes the alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0164] In one embodiment, the processor, when executing the computer program, also implements the following steps:

[0165] Obtaining the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured;

[0166] According to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, the harmonic impedance of each branch, the harmonic mutual impedance between nodes, the association matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when the shunt active power filter is not configured, determining the harmonic network loss function of the power distribution network;

[0167] According to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, determining the total configuration capacity function of the shunt active power filter.

[0168] In one embodiment, the processor, when executing the computer program, also implements the following steps:

[0169] According to the harmonic current injected by each node when the shunt active power filter is not configured, the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, and the harmonic mutual impedance between nodes, determining the residual harmonic voltage function of each node;

[0170] According to the residual harmonic voltage function of each node, the association matrix formed between all nodes and all branches, and the harmonic impedance of all branches, determining the harmonic network loss function of the power distribution network.

[0171] In one embodiment, the processor, when executing the computer program, also implements the following steps:

[0172] Determining the harmonic voltage content rate of each node, comprising:

[0173]

[0174] In formula (20), I SAPF represents the total configuration capacity of the SAPF, I SAPF,m represents the configuration capacity of the SAPF to node m, represents the h-th harmonic current injected by the shunt active power filter to node m, H represents the highest order of the harmonic current, and N represents the total number of nodes of the power distribution network.

[0175] In one embodiment, the processor, when executing the computer program, also implements the following steps:

[0176] Obtaining the fundamental voltage of each node;

[0177] determining a harmonic voltage content rate of each node based on a preset formula;

[0178] The preset formula includes:

[0179]

[0180] In formula (21), Vn(h) represents the hth harmonic voltage of node n, Vn(h) = Vn(h) - Vn(h-1), Vn(h-1) represents the (h-1)th harmonic voltage of node n, Vn(1) represents the fundamental voltage of node n, and H represents the highest order of harmonic voltage. Vn(h) represents the hth harmonic voltage content rate of node n, Vn(h) represents the hth residual harmonic voltage of node n, Vn(1) represents the fundamental voltage of node n, and H represents the highest order of harmonic voltage.

[0181] In one embodiment, the processor further implements the following steps when executing the computer program:

[0182] determining a total voltage distortion rate of each node, including:

[0183]

[0184] In formula (22), THDn represents the total voltage distortion rate of node n, and Vn(h) represents the hth harmonic voltage of node n. n Vn(h) represents the hth harmonic voltage content rate of node n, Vn(h) represents the hth residual harmonic voltage of node n, Vn(1) represents the fundamental voltage of node n, and H represents the highest order of harmonic voltage.

[0185] In one embodiment, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program. The computer program is executed by a processor to implement the following steps:

[0186] obtaining the harmonic impedance of each branch of the power distribution network, the harmonic mutual impedance between each node, the association matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no shunt active power filter is configured;

[0187] determining a target function and a target condition of the shunt active power filter of the power distribution network, wherein the target function includes a harmonic network loss function of the power distribution network and a total configuration capacity function of the shunt active power filter, and the target condition is set based on whether the harmonic voltage content rate of each node meets a preset harmonic voltage content rate and whether the total voltage distortion rate of each node meets a preset voltage distortion rate;

[0188] According to the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node when no shunt active power filter is configured and the harmonic voltage of each node, a global Plat optimal solution set of the target function is obtained by solving the target function through a multi-objective particle swarm optimization algorithm, and the final total configuration capacity scheme of the shunt active power filter is determined from the global Plat optimal solution set under the target condition, wherein the global Plat optimal solution set includes the alternative total configuration capacity scheme of the shunt active power filter in the power distribution network.

[0189] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0190] The harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured is obtained.

[0191] The harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, and the harmonic current of each node when no shunt active power filter is configured and the harmonic voltage of each node are determined.

[0192] The total configuration capacity function of the shunt active power filter is determined according to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured.

[0193] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0194] The residual harmonic voltage function of each node is determined according to the harmonic current injected at each node when no shunt active power filter is configured, the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, and the harmonic mutual impedance between nodes.

[0195] The harmonic network loss function of the power distribution network is determined according to the residual harmonic voltage function of each node, the correlation matrix formed between all nodes and all branches, and the harmonic impedance of all branches.

[0196] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0197] The total configuration capacity function of the shunt active power filter includes:

[0198]

[0199] In formula (23), I SAPF represents the total configuration capacity of the SAPF, I SAPF,m represents the configuration capacity of the SAPF to the node m, represents the hth harmonic current injected by the shunt active power filter to the node m, H represents the highest order of the harmonic current, and N represents the total number of nodes of the power distribution network.

[0200] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0201] determining the respective harmonic voltage content of each node, comprising:

[0202] obtaining the fundamental voltage of each node;

[0203] determining the harmonic voltage content of each node based on a preset formula;

[0204] The preset formula comprises:

[0205]

[0206] In formula (24), I represents the hth harmonic voltage content of the node n, represents the hth residual harmonic voltage of the node n, represents the fundamental voltage of the node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes of the power distribution network.

[0207] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0208] determining the total voltage distortion rate of each node, comprising:

[0209]

[0210] In formula (25), THD n represents the total voltage distortion rate of the node n, represents the hth residual harmonic voltage of the node n, represents the fundamental voltage of the node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes of the power distribution network.

[0211] In one embodiment, a computer program product is provided, comprising a computer program which, when executed by the processor, implements the following steps:

[0212] obtaining the harmonic impedance of each node, the harmonic mutual impedance between nodes, the association matrix formed between all nodes and all branches, the harmonic current of each node, and the harmonic voltage of each node when no shunt active power filter is configured.

[0213] determining a target function and a target condition of the shunt active power filter configuration of the distribution network, wherein the target function comprises a harmonic network loss function of the distribution network and a total configuration capacity function of the shunt active power filter, and the target condition is set based on whether each node's harmonic voltage content of each order meets a preset harmonic voltage content and whether each node's voltage total distortion rate meets a preset voltage distortion rate;

[0214] solving the target function by a multi-objective particle swarm optimization algorithm according to the harmonic impedance of each branch, the harmonic mutual impedance between nodes, the correlation matrix formed between all nodes and all branches, the harmonic current of each node when the shunt active power filter is not configured, and the harmonic voltage of each node, obtaining a global platonic optimal solution set of the target function, and determining a final total configuration capacity scheme of the shunt active power filter from the global platonic optimal solution set under the target condition, wherein the global platonic optimal solution set comprises an alternative total configuration capacity scheme of the shunt active power filter in the distribution network.

[0215] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0216] obtaining the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured;

[0217] determining the harmonic network loss function of the distribution network according to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, the harmonic impedance of each branch, the harmonic mutual impedance between nodes, the correlation matrix formed between all nodes and all branches, and the harmonic current of each node when the shunt active power filter is not configured.

[0218] determining the total configuration capacity function of the shunt active power filter according to the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured.

[0219] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0220] determining the residual harmonic voltage function of each node according to the harmonic current injected at each node when the shunt active power filter is not configured, the harmonic current injected by the shunt active power filter to each node when the shunt active power filter is configured, and the harmonic mutual impedance between nodes;

[0221] According to the harmonic voltage function of each node, the correlation matrix formed between all nodes and all branches, and the harmonic impedance of all branches, a harmonic network loss function of the distribution network is determined.

[0222] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0223] A total configuration capacity function of the shunt active power filter is determined, including:

[0224]

[0225] In formula (26), I SAPF represents the total configuration capacity of the SAPF, I SAPF,m represents the configuration capacity of the SAPF to node m, represents the hth harmonic current injected by the shunt active power filter to node m, H represents the highest order of the harmonic current, and N represents the total number of nodes of the distribution network.

[0226] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0227] A respective harmonic voltage content rate of each node is determined, including:

[0228] The fundamental wave voltage of each node is obtained;

[0229] Based on a preset formula, the harmonic voltage content rate of each node is determined;

[0230] The preset formula includes:

[0231]

[0232] In formula (27), V represents the hth harmonic voltage content rate of node n, represents the hth residual harmonic voltage of node n, represents the fundamental wave voltage of node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes of the distribution network.

[0233] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0234] A total voltage distortion rate of each node is determined, including:

[0235]

[0236] In formula (28), THD n represents the total voltage distortion rate of node n, represents the hth residual harmonic voltage of node n, The fundamental wave voltage of a node n, H represents the highest order of harmonic voltage, and N represents the total number of nodes of the power distribution network.

[0237] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties.

[0238] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. Any reference to memory, database or other medium used in the embodiments provided by the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetic variable memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (Phase Change Memory, PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided by the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided by the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0239] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the present disclosure.

[0240] The above-described embodiments are merely illustrative of several embodiments of the present application, which are described in more detail and in a specific manner, but should not be construed as limiting the scope of the patent of the present application. It should be noted that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A distribution network configuration optimization method based on harmonic compensation and network loss suppression, characterized in that, The method includes: Obtain the harmonic impedance of each branch of the distribution network, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no parallel active power filter is configured. The objective function and objective conditions for configuring parallel active power filters in the distribution network are determined. The objective function includes the harmonic network loss function of the distribution network and the total configuration capacity function of the parallel active power filters. The objective conditions are set based on whether the harmonic voltage content rate of each node meets the preset harmonic voltage content rate and whether the total voltage distortion rate of each node meets the preset voltage distortion rate. Based on the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current and harmonic voltage of each node when no parallel active power filter is configured, the objective function is solved by a multi-objective particle swarm optimization algorithm to obtain the global Pareto optimal solution set of the objective function. Under the objective condition, the final total configuration capacity scheme of the parallel active power filter is determined from the global Pareto optimal solution set. The global Pareto optimal solution set includes the alternative total configuration capacity schemes of the parallel active power filter in the distribution network. The objective function for determining the configuration of parallel active power filters in the distribution network includes: Obtain the harmonic currents injected into each node by the parallel active power filter when configuring it. The harmonic network loss function of the distribution network is determined based on the harmonic currents injected into each node by the parallel active power filter when the parallel active power filter is configured, the harmonic impedances of each branch, the harmonic mutual impedances between each node, the correlation matrix formed between all nodes and all branches, the harmonic currents and harmonic voltages of each node when the parallel active power filter is not configured. The total configuration capacity function of the parallel active power filter is determined based on the harmonic currents injected into each node by the parallel active power filter when it is configured. Determining the harmonic network loss function of the distribution network includes: The residual harmonic voltage function of each node is determined based on the harmonic currents injected at each node when no parallel active power filter is configured, the harmonic currents injected into each node by the parallel active power filter when the parallel active power filter is configured, and the harmonic mutual impedance between the nodes. The harmonic network loss function of the distribution network is determined based on the remaining harmonic voltage function of each node, the correlation matrix formed between all nodes and all branches, and the harmonic impedance of all branches.

2. The method according to claim 1, characterized in that, The step of determining the total configuration capacity function of the parallel active power filter based on the harmonic currents injected into each node by the parallel active power filter when configuring it includes: Among them, I SAPF Indicates the total configuration capacity of SAPF, I SAPF,m This indicates the configured capacity of node m in SAPF. This represents the h-th harmonic current injected into node m by the parallel active power filter, where H represents the highest harmonic current and N represents the total number of nodes in the distribution network.

3. The method according to claim 1, characterized in that, The process of determining the harmonic voltage content of each node includes: Obtain the fundamental voltage of each node; Based on a preset formula, the harmonic voltage content of each node is determined. The preset formula includes: in, This represents the h-th harmonic voltage content at node n. This represents the h-th residual harmonic voltage at node n. H represents the fundamental voltage of node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes in the distribution network.

4. The method according to claim 1, characterized in that, The process of determining the total voltage distortion rate of each node includes: Among them, THD n This represents the total voltage distortion rate at node n. This represents the h-th residual harmonic voltage at node n. H represents the fundamental voltage of node n, H represents the highest order of the harmonic voltage, and N represents the total number of nodes in the distribution network.

5. A distribution network configuration optimization device based on harmonic compensation and network loss suppression, characterized in that, The device includes: The acquisition module is used to acquire the harmonic impedance of each branch of the distribution network, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when no parallel active power filter is configured. The first determining module is used to determine the objective function and objective conditions for the configuration of the parallel active power filter in the distribution network. The objective function includes the harmonic network loss function of the distribution network and the total configuration capacity function of the parallel active power filter. The objective conditions are set based on whether the harmonic voltage content rate of each node meets the preset harmonic voltage content rate and whether the total voltage distortion rate of each node meets the preset voltage distortion rate. The second determining module is used to solve the objective function using a multi-objective particle swarm optimization algorithm based on the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current and harmonic voltage of each node when no parallel active power filter is configured, to obtain the global Pareto optimal solution set of the objective function. Under the objective condition, the final total configuration capacity scheme of the parallel active power filter is determined from the global Pareto optimal solution set. The global Pareto optimal solution set includes the alternative total configuration capacity schemes of the parallel active power filter in the distribution network. The first determining module includes: The first acquisition submodule is used to acquire the harmonic currents injected into each node by the parallel active power filter when configuring the parallel active power filter. The first determining submodule is used to determine the harmonic network loss function of the distribution network based on the harmonic current injected into each node by the parallel active power filter when the parallel active power filter is configured, the harmonic impedance of each branch, the harmonic mutual impedance between each node, the correlation matrix formed between all nodes and all branches, the harmonic current of each node and the harmonic voltage of each node when the parallel active power filter is not configured. The second determining submodule is used to determine the total configuration capacity function of the parallel active power filter based on the harmonic currents injected into each node by the parallel active power filter when configuring the parallel active power filter. The first determined submodule includes: The first determining unit is used to determine the residual harmonic voltage function of each node based on the harmonic current injected at each node when no parallel active power filter is configured, the harmonic current injected into each node by the parallel active power filter when the parallel active power filter is configured, and the harmonic mutual impedance between the nodes. The second determining unit is used to determine the harmonic network loss function of the distribution network based on the remaining harmonic voltage function of each node, the correlation matrix formed between all nodes and all branches, and the harmonic impedance of all branches.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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