Harmonic optimization method and device of power distribution network, computer equipment and readable storage medium

Abstract

The invention relates to a harmonic optimization method and device of a power distribution network, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a historical harmonic data set corresponding to each monitoring node in the power distribution network; determining a plurality of filtering node combinations of the power distribution network under the target optimized harmonic voltage based on the historical harmonic data set; for any filtering node combination, acquiring simulation filtering parameters corresponding to each filtering node in the filtering node combination, and calculating target harmonic compensation current corresponding to each filtering node based on the historical harmonic data set and the simulation filtering parameters; determining the total power capacity corresponding to each filtering node combination based on the target harmonic compensation current, and determining a target filtering node combination based on the total power capacity; the target filtering node combination is used for deploying harmonic filters on corresponding network nodes in the power distribution network, and harmonic optimization is carried out on the power distribution network through the harmonic filters. By adopting the method, the harmonic optimization efficiency of the power distribution network can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of power system optimization, and in particular to a method, device, computer equipment, computer-readable storage medium and computer program product for harmonic optimization of a distribution network. Background Art

[0002] In the new context of the increasing popularity of power electronic devices and the widespread access to distributed renewable energy in modern power distribution systems, the harmonic distortion problem of distribution networks has increased significantly. Harmonic distortion refers to the fact that there are a large number of power supply and consumption devices with nonlinear impedance characteristics in the power system, which inject harmonic currents into the public power grid or generate harmonic voltages in the public power grid, causing the actual voltage waveform to deviate from the sine wave. Therefore, it is necessary to control harmonic distortion to optimize the harmonics generated in the distribution network.

[0003] Harmonic pollution in modern distribution networks is decentralized and network-wide. With limited governance resources, it is difficult to achieve harmonic governance of the entire distribution network. In traditional governance methods, large nonlinear loads are usually configured with APFs (Active Power Filters) to prevent their harmonic currents from being injected into the system. However, due to the increasing types and numbers of harmonic sources in the distribution network, the harmonic flow of the distribution network presents a complex multi-source feature. The method of using APF for harmonic governance is still mainly based on injecting harmonic currents into a single node for current compensation, but it cannot accurately grasp the harmonic status of each node in the entire network, resulting in low accuracy of harmonic optimization of the distribution network, which in turn leads to problems with the power supply security of the distribution network. Summary of the invention

[0004] Based on this, it is necessary to provide a harmonic optimization method, device, computer equipment, computer-readable storage medium and computer program product that can improve the accuracy of harmonic optimization of the distribution network and thereby ensure the power supply security of the distribution network in response to the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a harmonic optimization method for a distribution network, comprising:

[0006] Obtain the historical harmonic data set corresponding to each monitoring node in the distribution network in the historical time period;

[0007] Based on the historical harmonic data set, multiple filter node combinations of the distribution network under the target optimized harmonic voltage are determined;

[0008] For any filter node combination, the analog filter parameters corresponding to each filter node in the filter node combination are obtained, and based on the historical harmonic data set and the analog filter parameters corresponding to each filter node in the filter node combination, the target harmonic compensation current corresponding to each filter node in the filter node combination is calculated;

[0009] Based on the target harmonic compensation current, the total power capacity corresponding to each filter node combination is determined, and based on the total power capacity, the target filter node combination is determined in each filter node combination; the target filter node combination is used to deploy harmonic filters on corresponding network nodes in the distribution network, and the distribution network is harmonically optimized through the harmonic filters.

[0010] In a second aspect, the present application also provides a harmonic optimization device for a distribution network, comprising:

[0011] A data acquisition module is used to obtain historical harmonic data sets corresponding to each monitoring node in the distribution network in a historical time period;

[0012] A node combination determination module is used to determine multiple filter node combinations of the distribution network under a target optimized harmonic voltage based on a historical harmonic data set;

[0013] A compensation current calculation module is used to obtain the analog filtering parameters corresponding to each filter node in the filter node combination for any filter node combination, and calculate the target harmonic compensation current corresponding to each filter node in the filter node combination based on the historical harmonic data set and analog filtering parameters corresponding to each filter node in the filter node combination;

[0014] The harmonic optimization module is used to determine the total power capacity corresponding to each filter node combination based on the target harmonic compensation current, and determine the target filter node combination in each filter node combination based on the total power capacity; the target filter node combination is used to deploy harmonic filters on the corresponding network nodes in the distribution network, and perform harmonic optimization on the distribution network through the harmonic filters.

[0015] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0016] Obtain the historical harmonic data set corresponding to each monitoring node in the distribution network in the historical time period;

[0017] Based on the historical harmonic data set, multiple filter node combinations of the distribution network under the target optimized harmonic voltage are determined;

[0018] For any filter node combination, the analog filter parameters corresponding to each filter node in the filter node combination are obtained, and based on the historical harmonic data set and the analog filter parameters corresponding to each filter node in the filter node combination, the target harmonic compensation current corresponding to each filter node in the filter node combination is calculated;

[0019] Based on the target harmonic compensation current, the total power capacity corresponding to each filter node combination is determined, and based on the total power capacity, the target filter node combination is determined in each filter node combination; the target filter node combination is used to deploy harmonic filters on corresponding network nodes in the distribution network, and the distribution network is harmonically optimized through the harmonic filters.

[0020] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0021] Obtain the historical harmonic data set corresponding to each monitoring node in the distribution network in the historical time period;

[0022] Based on the historical harmonic data set, multiple filter node combinations of the distribution network under the target optimized harmonic voltage are determined;

[0023] For any filter node combination, the analog filter parameters corresponding to each filter node in the filter node combination are obtained, and based on the historical harmonic data set and the analog filter parameters corresponding to each filter node in the filter node combination, the target harmonic compensation current corresponding to each filter node in the filter node combination is calculated;

[0024] Based on the target harmonic compensation current, the total power capacity corresponding to each filter node combination is determined, and based on the total power capacity, the target filter node combination is determined in each filter node combination; the target filter node combination is used to deploy harmonic filters on corresponding network nodes in the distribution network, and the distribution network is harmonically optimized through the harmonic filters.

[0025] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0026] Obtain the historical harmonic data set corresponding to each monitoring node in the distribution network in the historical time period;

[0027] Based on the historical harmonic data set, multiple filter node combinations of the distribution network under the target optimized harmonic voltage are determined;

[0028] For any filter node combination, the analog filter parameters corresponding to each filter node in the filter node combination are obtained, and based on the historical harmonic data set and the analog filter parameters corresponding to each filter node in the filter node combination, the target harmonic compensation current corresponding to each filter node in the filter node combination is calculated;

[0029] Based on the target harmonic compensation current, the total power capacity corresponding to each filter node combination is determined, and based on the total power capacity, the target filter node combination is determined in each filter node combination; the target filter node combination is used to deploy harmonic filters on corresponding network nodes in the distribution network, and the distribution network is harmonically optimized through the harmonic filters.

[0030] The harmonic optimization method, device, computer equipment, computer-readable storage medium and computer program product of the above-mentioned distribution network determine multiple filter node combinations of the distribution network under the target optimized harmonic voltage according to the historical harmonic data set; then calculate the target harmonic compensation current corresponding to each filter node in each filter node combination, calculate the total power capacity of each filter node combination according to the target harmonic compensation current, and determine the target filter node combination according to the total power capacity. The target optimized harmonic voltage can be used as the governance target of the distribution network, and the total power capacity can be used as the filter capacity screening target of the distribution network, thereby realizing the global governance of the distribution network, improving the harmonic optimization accuracy of the distribution network and minimizing the governance cost, thereby ensuring the power supply security of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 An application environment diagram of a harmonic optimization method for a power distribution network in one embodiment;

[0033] Figure 2 A schematic diagram of a flow chart of a harmonic optimization method for a power distribution network in one embodiment;

[0034] Figure 3 A schematic diagram of a flow chart of harmonic optimization steps of a power distribution network in one embodiment;

[0035] Figure 4 It is a schematic diagram of a process of harmonic control of a power distribution network in one embodiment;

[0036] Figure 5 is a structural block diagram of a harmonic optimization device for a power distribution network in one embodiment;

[0037] Figure 6 is an internal structure diagram of a computer device in another embodiment;

[0038] Figure 7 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0040] The harmonic optimization method for the distribution network provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, etc. The server 104 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0041] In one embodiment, Figure 2 As shown, a harmonic optimization method for a distribution network is provided. This embodiment uses the method applied to a server as an example for illustration. It can be understood that the method can also be applied to a terminal, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0042] Step 202: Obtain a historical harmonic data set corresponding to each monitoring node in the distribution network in a historical time period.

[0043] Step 204 : determining a plurality of filter node combinations of the distribution network under the target optimized harmonic voltage based on the historical harmonic data set.

[0044] Among them, the monitoring node refers to the network node in the distribution network where the monitoring equipment is pre-deployed, which is used to monitor the harmonic data generated by the network node where the monitoring equipment is deployed during operation. Harmonic data may refer to the harmonic voltage generated in the network node where the monitoring equipment is deployed. The target optimized harmonic voltage refers to the target value that the harmonic voltage generated by the distribution network is expected to reach after optimization, such as the residual harmonic voltage of the distribution network after optimization. The filtering node refers to the network node in the distribution network used to deploy harmonic filters, and the harmonic filter may be an active filter. The filter node combination refers to a group of filter nodes that can achieve the target optimized harmonic voltage, which can be understood as a deployment scheme that selects certain network nodes from each network node of the distribution network to deploy harmonic filters and can achieve the target optimized harmonic voltage.

[0045] Specifically, the server obtains the historical harmonic data set corresponding to each monitoring node in the distribution network in the historical time period. The historical harmonic data set can be a matrix data generated by the historical harmonic data corresponding to each monitoring node at each historical moment in the historical time period. Then the server takes the target optimized harmonic voltage as the optimization target, and performs node screening on the historical harmonic data set according to the preset harmonic voltage optimization logic, and screens out multiple filter node combinations that can meet the target optimized harmonic voltage. The harmonic voltage optimization logic can refer to the operation logic for optimizing the harmonic voltage.

[0046] In one embodiment, the server can obtain multiple candidate filter node combinations, and use each candidate filter node combination to perform harmonic voltage optimization on the historical harmonic data set according to the preset harmonic voltage optimization logic to obtain the optimized harmonic voltage corresponding to each candidate filter node. Then the server determines the candidate filter node combination whose optimized harmonic voltage meets the target optimized harmonic voltage as the filter node combination corresponding to the distribution network.

[0047] In one embodiment, the server obtains the historical harmonic data corresponding to the same historical moment from the historical harmonic data sets corresponding to each monitoring node in the historical time period, and obtains the sub-harmonic data sets corresponding to each historical moment. Then the server obtains the filter deployment factor according to the preset harmonic voltage optimization logic, and the server determines the compensation harmonic voltage according to the filter deployment factor, and obtains the optimized harmonic voltage according to the compensation harmonic voltage and the sub-harmonic data set. The server obtains multiple filter node combinations of the distribution network under the target optimized harmonic voltage according to the filter deployment factor that makes the optimized harmonic voltage the target optimized harmonic voltage.

[0048] Step 206, for any filter node combination, obtain the analog filter parameters corresponding to each filter node in the filter node combination, and calculate the target harmonic compensation current corresponding to each filter node in the filter node combination based on the historical harmonic data set and the analog filter parameters corresponding to each filter node in the filter node combination.

[0049] Among them, the simulated filter parameters refer to the parameters generated by simulating the operation of harmonic filters for the corresponding network nodes in the distribution network according to the filter node combination, and can refer to the impedance coefficient generated by the harmonic filter during the simulated operation. The harmonic compensation current refers to the harmonic current with the opposite magnitude and frequency of the harmonic components generated by the harmonic filter to eliminate the harmonics in the distribution network. The target harmonic compensation current is the harmonic compensation current used to calculate the total power capacity of the filter node combination.

[0050] Specifically, for any filter node combination, the server simulates the deployment and operation of the harmonic filter according to the corresponding network node of the filter node combination in the distribution network, and then obtains the simulated filtering parameters of the harmonic filter simulated by each filter node in the filter node combination, and obtains the simulated filtering parameters corresponding to each filter node. The server calculates the target harmonic compensation current corresponding to each filter node in the filter node combination based on the historical harmonic data set and simulated filtering parameters corresponding to each filter node in the filter node combination, indicating the target harmonic compensation current output by the harmonic filter simulated by the filter node. The server calculates each filter node combination in this way to obtain the target harmonic compensation current corresponding to each filter node in each filter node combination.

[0051] Step 208, based on the target harmonic compensation current, determine the total power capacity corresponding to each filter node combination, and determine the target filter node combination in each filter node combination based on the total power capacity; the target filter node combination is used to deploy harmonic filters on corresponding network nodes in the distribution network, and perform harmonic optimization on the distribution network through the harmonic filters.

[0052] Among them, the total power capacity refers to the power capacity required by each harmonic filter during operation after the harmonic filter is deployed at the corresponding network node in the distribution network.

[0053] Specifically, the server calculates the node power corresponding to each filter node according to the target harmonic compensation current and analog filter parameters corresponding to each filter node in each filter node combination, and then merges the node power of each filter node in the same filter node combination to obtain the total power capacity corresponding to each filter node combination. The server then compares the total power capacity of each filter node combination to determine the target filter node combination, and sends the target filter node combination and the corresponding total power capacity to the management terminal, so that the management personnel can actually deploy the harmonic filter at the corresponding network node of the distribution network according to the target filter node combination and the total power capacity, and perform harmonic optimization on the distribution network through the harmonic filter.

[0054] In the harmonic optimization method of the above-mentioned distribution network, multiple filter node combinations of the distribution network under the target optimized harmonic voltage are determined according to the historical harmonic data set; then the target harmonic compensation current corresponding to each filter node in each filter node combination is calculated, the total power capacity of each filter node combination is calculated according to the target harmonic compensation current, and the target filter node combination is determined according to the total power capacity. The target optimized harmonic voltage can be used as the governance target of the distribution network, and the total power capacity can be used as the filter capacity screening target of the distribution network, thereby realizing the global governance of the distribution network, improving the accuracy of harmonic optimization of the distribution network and minimizing the governance cost, thereby ensuring the power supply security of the distribution network.

[0055] In one embodiment, Figure 3 As shown, step 204, based on the historical harmonic data set, determines a plurality of filter node combinations of the distribution network under the target optimized harmonic voltage, including:

[0056] Step 302 : acquiring historical harmonic data corresponding to the same historical moment from the historical harmonic data sets corresponding to each monitoring node in the historical time period, and obtaining sub-harmonic data sets corresponding to each historical moment.

[0057] Step 304: Obtain a filter deployment factor, and determine a compensated harmonic voltage based on the filter deployment factor.

[0058] Step 306 : obtaining an optimized harmonic voltage based on the compensated harmonic voltage and the sub-harmonic data set.

[0059] Step 308: Based on the filter deployment factor that makes the optimized harmonic voltage equal to the target optimized harmonic voltage, a plurality of filter node combinations of the distribution network under the target optimized harmonic voltage are obtained.

[0060] Among them, the filter deployment factor refers to the calculation factor involved in the harmonic voltage optimization of the distribution network, which can be specifically the node location of the network node in the distribution network where the harmonic filter is deployed. The compensated harmonic voltage refers to the voltage change value for the harmonic voltage optimization of the distribution network, which can be understood as the compensation voltage output by the harmonic filter to eliminate the harmonic voltage. The optimized harmonic voltage refers to the optimized voltage value.

[0061] Specifically, the server obtains the historical harmonic data set of each monitoring node in the historical time period through the management terminal corresponding to the distribution network, as shown in formula (1).

[0062]

[0063] in, N m There are N monitoring nodes in t Historical harmonic data at each moment; Represents the historical harmonic data of the i-th monitoring node at the j-th moment.

[0064] Then the server obtains the historical harmonic data corresponding to the same historical moment from the historical harmonic data set corresponding to each monitoring node in the historical time period, obtains the sub-harmonic data set corresponding to each historical moment, and obtains the filter deployment factor, such as Indicates the N installed in the distribution network p The network node where the harmonic filter is located, p i The serial number of is consistent with the node number of the distribution network, and the number is less than the number of network nodes of the distribution network, as shown in formula (2).

[0065] 1≤pi ≤N B (2)

[0066] The server calculates the harmonic compensation current and filter parameters corresponding to each filter node at each historical moment according to the preset harmonic voltage optimization logic and the filter deployment factor, and then calculates the compensated harmonic voltage corresponding to each filter node at each historical moment according to the harmonic compensation current and the filter parameters, and obtains the compensated harmonic voltage corresponding to the distribution network at each historical moment, and then merges the sub-harmonic data set and the compensated harmonic voltage at the same historical moment to obtain the optimized harmonic voltage. At this time, since the position of each network node of the harmonic filter to be deployed in the filter deployment factor is unknown, the optimized harmonic voltage is a mathematical expression containing the unknown filter deployment factor, as shown in formula (3).

[0067]

[0068] Among them, f1 represents the residual harmonic voltage that can be achieved by each monitoring node after the harmonic filter is deployed. The objective function is obtained by selecting the square sum of the optimized harmonic voltages of each monitoring node. Indicates based on The obtained compensation current output by the harmonic filter is obtained, for example, by the least square method according to the compensation current of the harmonic filter installed at each position, and varies due to the different installation positions P of the harmonic filter; Represents the sub-harmonic data set corresponding to time t (column t) in the historical harmonic data set; Represents the compensation current output by each harmonic filter at time t; represents the impedance coefficient, i.e., the filtering parameter, which can be calculated by formula (4).

[0069]

[0070] in, is the hth harmonic impedance matrix of the distribution network, N B is the number of network nodes; Indicates the network node where the Nm monitoring devices installed in the distribution network are located; Indicates the N installed in the distribution network p The network node where the harmonic filter is located.

[0071] Then the server calculates the filter deployment factor when the optimized harmonic voltage reaches the target optimized harmonic voltage, and obtains multiple filter node combinations of the distribution network under the target optimized harmonic voltage. The filter node combination can be obtained by The target optimized harmonic voltage is, for example, the minimum optimized harmonic voltage.

[0072] In this embodiment, the objective function is obtained by selecting the sum of the squares of the optimized harmonic voltages of each monitoring node, and the filter deployment factor is calculated when the optimized harmonic voltage reaches the target optimized harmonic voltage. Multiple filter node combinations of the distribution network under the target optimized harmonic voltage are obtained, thereby ensuring the harmonic optimization effect of each filter node combination after the harmonic filter is deployed in the distribution network.

[0073] In one embodiment, step 308, based on the filter deployment factor that makes the optimized harmonic voltage the target optimized harmonic voltage, obtains a plurality of filter node combinations of the distribution network under the target optimized harmonic voltage, including:

[0074] Based on the particle swarm optimization algorithm, the filter deployment factor with the optimized harmonic voltage as the target optimized harmonic voltage is determined, and multiple filter node combinations of the distribution network under the target optimized harmonic voltage are obtained.

[0075] Specifically, the server constructs an objective function f1 corresponding to the optimized harmonic voltage as shown in formula (3), and then uses a particle swarm optimization algorithm to solve the objective function f1 with the target optimized harmonic voltage as the target, and obtains the specific data of the filter deployment factor when the optimized harmonic voltage meets the target optimized harmonic voltage. The specific data of the filter deployment factor may include multiple groups of filter node combinations.

[0076] Specifically, the server considers the feasible solution of each harmonic filter under the objective function f1 as a particle without volume in the search space, so the position z of the particle is r =[z r1 ,z r1 ,…,z rd ] represents a set of possible values ​​of the harmonic filter position P, that is, a set of filter node combinations. Each particle moves in the search space at a certain speed v r =[v r1 ,v r1 ,…,v rd ] and constantly adjusts its trajectory according to its own position and the positions of other particles. The optimal position it has experienced is The global optimal position experienced by all particles is represented by In the algorithm, the particle of the k+1 iteration updates its velocity and position according to the particle information of the k iteration according to the following formula (5) to determine P that best satisfies the objective function f1 in formula (3).

[0077]

[0078] Among them, c1, c2 are the individual and global learning factors of the particle, which are 1.5 and 1.7 respectively; rd1, rd2 are random numbers between 0 and 1; ω is the inertia weight, which is 0.9 here.

[0079] As the number of iterations increases, the sum of the squares of the harmonic voltages after treatment becomes smaller and smaller. When the number of iterations exceeds the "elbow" point, the rate of decrease of the sum of the squares of the harmonic voltages will slow down. The "elbow" point n0 is calculated by calculating the objective function value f1[P n ] The minimum first-order derivative of the iteration number k is determined, as shown in formula (6).

[0080] n0=argmin(f1′(P n ))=argmin(f1[P n ]-f1[P n-1 ]) 0<n<N PSO (6)

[0081] Among them, N PSO is the total number of PSO iterations; Pn and Pn-1 are the APF installation positions in the nth and n-1th iterations; n0 is f1[P n ]-f1[P n-1 ] is the n when it takes the minimum value.

[0082] In this embodiment, the accuracy and effectiveness of the filter node combination are ensured by solving the objective function f1 for each filter node combination.

[0083] In one embodiment, step 106, based on the historical harmonic data set and the simulated filtering parameters corresponding to each filter node in the filter node combination, calculates the target harmonic compensation current corresponding to each filter node in the filter node combination, including:

[0084] Harmonic compensation currents are calculated based on the sub-harmonic data sets and simulation filter parameters corresponding to each historical moment, and the harmonic compensation currents corresponding to each filter node in the filter node combination at each historical moment are obtained;

[0085] Based on the harmonic compensation currents corresponding to the respective historical moments, a target harmonic compensation current corresponding to each filter node in the filter node combination is determined.

[0086] Specifically, the server calculates the harmonic compensation current according to the sub-harmonic data sets and analog filtering parameters corresponding to each historical moment, and obtains the harmonic compensation current corresponding to each filter node in the filter node combination at each historical moment. For example, the sum of squares of the historical harmonic data corresponding to each monitoring node in each sub-harmonic data set is minimized, and the least squares theory is used to calculate the harmonic compensation current corresponding to each filter node at each historical moment.

[0087] Then, the server determines the maximum harmonic compensation current from the harmonic compensation currents corresponding to each filter node at each historical moment, and obtains the target harmonic compensation current corresponding to each filter node.

[0088] In this embodiment, the target harmonic compensation current corresponding to each filter node is calculated so that the total power capacity can be subsequently calculated, thereby ensuring the accuracy of the total power capacity.

[0089] In one embodiment, step 108, based on the target harmonic compensation current, determines the total power capacity corresponding to each filter node combination, including:

[0090] Obtain the basic power capacity corresponding to the distribution network and the rated voltage corresponding to each filter node in each filter node combination;

[0091] For any filter node combination, power calculation is performed based on the basic capacity, the rated voltage corresponding to each filter node in the filter node combination, and the target harmonic compensation current to obtain the node power corresponding to each filter node in the filter node combination;

[0092] The node powers corresponding to the various filter nodes in the same filter node combination are combined to obtain the total power capacity corresponding to each filter node combination.

[0093] Among them, basic capacity refers to the minimum capacity required for the operation of the distribution network, which can be power capacity.

[0094] Specifically, in the process of optimizing the objective function f1 corresponding to the optimized harmonic voltage shown in formula (3), the Ns schemes (filter node combinations) in each iteration after the "elbow" point are all close to the extreme value point of the objective function, and there is generally no significant difference in the optimization effect of the harmonic voltage. On this basis, we can further select the scheme with the lowest harmonic filter deployment cost, that is, select a filter node combination with the smallest total power capacity as the target filter node combination.

[0095] Specifically, the server simulates and runs harmonic filters at the corresponding network nodes of the distribution network according to each filter node combination. Then the server obtains the basic power capacity corresponding to the distribution network and the rated voltage corresponding to each filter node in each filter node combination. For any filter node combination, the server uses the basic capacity, the rated voltage corresponding to each filter node in the filter node combination, and the target harmonic compensation current to perform power calculation to obtain the node power corresponding to each filter node in the filter node combination. Then the server merges the node power corresponding to each filter node in the same filter node combination to obtain the total power capacity corresponding to each filter node combination, as shown in formula (7).

[0096]

[0097] Among them, f2 represents the objective function obtained when the investment cost of the harmonic filter is minimized without affecting the treatment effect, that is, the investment capacity of the harmonic filter is minimized; H is the highest harmonic order to be considered; S base is the base capacity of the distribution network; τ is the coefficient introduced to consider the possible fluctuations of harmonics based on historical harmonic data, which can be taken as 1.5; p i For the i-th node where the harmonic filter is installed, For node p i Rated voltage; For node p i The maximum h-order harmonic current that the installed harmonic filter needs to output is No. i The maximum value of the row, that is, the maximum h-th harmonic current when the harmonic voltage is optimized for the historical harmonic data set during the simulation of the operation of the harmonic filter, is the target harmonic compensation current, as shown in formula (8).

[0098]

[0099] in, express The pth matrix i OK.

[0100] Then, taking the objective function f2 in formula (6) as the target, the scheme with the smallest required harmonic filter capacity among all schemes after the n0th iteration of PSO is selected, as shown in formula (9). The optimization result obtained by formula (9) is the optimal scheme for deploying the harmonic filter.

[0101] P * =argmin(f2(P n )) n0<n<N PSO (9)

[0102] In this embodiment, by determining the target filter node when the harmonic filter capacity is minimum according to the objective function f2, the harmonic optimization cost of the distribution network is reduced.

[0103] In one embodiment, the harmonic optimization method of the power distribution network further includes:

[0104] After the harmonic filters are deployed on the corresponding network nodes in the distribution network based on the target filter node combination; the current harmonic data corresponding to each monitoring node in the distribution network is obtained;

[0105] Obtain current filtering parameters corresponding to network nodes where harmonic filters are deployed in the distribution network, and calculate the harmonic compensation current of the network nodes where harmonic filters are deployed at the next moment based on current harmonic data and current filtering parameters;

[0106] The harmonic filter is controlled to perform harmonic optimization on the distribution network at the next moment according to the harmonic compensation current.

[0107] Specifically, the server sends the target filter node combination and the corresponding total power capacity to the management terminal corresponding to the distribution network, and the management personnel deploy harmonic filters at the corresponding network nodes of the distribution network according to the target filter node combination and the corresponding total power capacity, and coordinate the installation of each harmonic filter. The server can use a central controller to perform rolling optimization on the compensation current of the harmonic filter in each control cycle, that is, use the harmonic voltage data and harmonic impedance coefficient at the current moment to calculate the harmonic compensation current output by the harmonic filter at the next moment, and then control the harmonic filter to output the corresponding harmonic compensation current to achieve global governance of the harmonics in the distribution network.

[0108] When performing global harmonic management of the distribution network, the server obtains the current harmonic data corresponding to each monitoring node in the distribution network, calculates the harmonic compensation current of the network node deployed with the harmonic filter at the next moment based on the current harmonic data and the current filtering parameters, and controls the harmonic filter to perform harmonic optimization on the distribution network at the next moment according to the harmonic compensation current.

[0109] In a specific embodiment, a harmonic filter model for harmonic control of distribution network can be constructed to collect N m Harmonic voltage data of each node at the current moment As shown in formula (10).

[0110]

[0111] in, is the hth harmonic voltage data of node i at the current moment. After being treated by the harmonic filter, N m The harmonic voltage of each monitoring node can be reduced as shown in the following equation (11).

[0112]

[0113] in, It represents the hth harmonic voltage of each monitoring node after treatment; It represents the change of the hth harmonic voltage of each monitoring node after treatment, which can be calculated by formula (12).

[0114]

[0115] in, N is the installed P The hth harmonic current vector injected into the distribution network by a harmonic filter; is the harmonic impedance coefficient from the harmonic filter to each monitoring node.

[0116] In order to minimize the sum of the squares of the harmonic voltages at each monitoring point, the least squares theory is used to calculate the harmonic compensation current output by each harmonic filter at the next moment, as shown in equation (13).

[0117]

[0118] Then the server uses a central controller to control the harmonic filter to output the corresponding harmonic compensation current in each control cycle, thereby completing the coordinated regulation of the installed distributed harmonic filters.

[0119] In this embodiment, by coordinated regulation of the installed distributed harmonic filters, it is possible to coordinate distributed governance resources to achieve global optimization of distribution network harmonics when governance resources are limited.

[0120] In a specific embodiment, Figure 4 As shown, a schematic diagram of the harmonic control process of a distribution network is provided. The server collects the historical harmonic data sets corresponding to each monitoring node in the distribution network in the historical time period, and constructs the objective function f1 for screening multiple filter node combinations and the objective function f2 for calculating the minimum total power capacity based on the inferior historical harmonic data sets. Then, the example group algorithm is used to optimize the objective function f1, and according to each filter node group in the optimization result, the target filter node group with the minimum total power capacity is calculated for the objective function f2, the site selection and sizing of the harmonic filter is completed, and the management personnel are notified to install and operate the harmonic filter on the corresponding network nodes of the distribution network according to the site selection and sizing results of the harmonic filter.

[0121] The server collects the current harmonic data of each monitoring node, performs rolling optimization on the compensation current of the harmonic filter, and realizes distributed collaborative management of distribution network harmonics.

[0122] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0123] Based on the same inventive concept, the embodiment of the present application also provides a harmonic optimization device for a distribution network for implementing the harmonic optimization method for a distribution network involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the harmonic optimization device for the distribution network provided below can refer to the limitations of the harmonic optimization method for the distribution network above, and will not be repeated here.

[0124] In an exemplary embodiment, Figure 5 As shown, a harmonic optimization device 500 for a distribution network is provided, comprising: a data acquisition module 502, a node combination determination module 504, a compensation current calculation module 506 and a harmonic optimization module 508, wherein:

[0125] The data acquisition module 502 is used to acquire the historical harmonic data set corresponding to each monitoring node in the distribution network in the historical time period;

[0126] A node combination determination module 504 is used to determine a plurality of filter node combinations of the distribution network under a target optimized harmonic voltage based on a historical harmonic data set;

[0127] The compensation current calculation module 506 is used to obtain the analog filtering parameters corresponding to each filter node in the filter node combination for any filter node combination, and calculate the target harmonic compensation current corresponding to each filter node in the filter node combination based on the historical harmonic data set and the analog filtering parameters corresponding to each filter node in the filter node combination;

[0128] The harmonic optimization module 508 is used to determine the total power capacity corresponding to each filter node combination based on the target harmonic compensation current, and determine the target filter node combination in each filter node combination based on the total power capacity; the target filter node combination is used to deploy harmonic filters on corresponding network nodes in the distribution network, and perform harmonic optimization on the distribution network through the harmonic filters.

[0129] In one embodiment, the node combination determination module 504 is also used to obtain historical harmonic data corresponding to the same historical moment from the historical harmonic data sets corresponding to the various monitoring nodes in the historical time period, and obtain sub-harmonic data sets corresponding to each historical moment; obtain a filter deployment factor, and determine a compensating harmonic voltage based on the filter deployment factor; obtain an optimized harmonic voltage based on the compensating harmonic voltage and the sub-harmonic data set; and obtain multiple filter node combinations of the distribution network under the target optimized harmonic voltage based on the filter deployment factor that makes the optimized harmonic voltage the target optimized harmonic voltage.

[0130] In one embodiment, the node combination determination module 504 is further used to determine the filter deployment factor of the optimized harmonic voltage as the target optimized harmonic voltage based on the particle swarm optimization algorithm, and obtain multiple filter node combinations of the distribution network under the target optimized harmonic voltage.

[0131] In one embodiment, the compensation current calculation module 506 is also used to perform harmonic compensation current calculations based on the sub-harmonic data sets corresponding to each historical moment and the analog filtering parameters, to obtain the harmonic compensation currents corresponding to each filter node in the filter node combination at each historical moment; based on the harmonic compensation currents corresponding to each historical moment, determine the target harmonic compensation currents corresponding to each filter node in the filter node combination.

[0132] In one embodiment, the harmonic optimization module 508 is also used to obtain the basic power capacity corresponding to the distribution network and the rated voltage corresponding to each filter node in the filter node combination; for any filter node combination, power calculation is performed based on the basic capacity, the rated voltage corresponding to each filter node in the filter node combination, and the target harmonic compensation current to obtain the node power corresponding to each filter node in the filter node combination; the node power corresponding to each filter node in the same filter node combination is merged to obtain the total power capacity corresponding to each filter node combination.

[0133] In one embodiment, the harmonic optimization device 500 of the distribution network is also used for, after deploying harmonic filters on corresponding network nodes in the distribution network based on the target filtering node combination; obtaining current harmonic data corresponding to each monitoring node in the distribution network; obtaining current filtering parameters corresponding to the network nodes in the distribution network where harmonic filters are deployed, and calculating the harmonic compensation current of the network nodes in the distribution network where harmonic filters are deployed at the next moment based on the current harmonic data and the current filtering parameters; and controlling the harmonic filter to perform harmonic optimization on the distribution network at the next moment according to the harmonic compensation current.

[0134] Each module in the above-mentioned harmonic optimization device for the distribution network can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0135] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 6As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. 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 database of the computer device is used to store historical harmonic data sets. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a harmonic optimization method for a distribution network is implemented.

[0136] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. 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 and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (Near Field Communication, NFC) or other technologies. When the computer program is executed by the processor, a harmonic optimization method for a distribution network is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0137] Those skilled in the art will understand that Figure 6-7The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0138] In an exemplary embodiment, in one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0139] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0140] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0141] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0142] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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 embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0143] The technical features of the above embodiments may 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 there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0144] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations 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 shall be subject to the attached claims.

Claims

1. A harmonic optimization method for a distribution network, characterized in that: The method comprises: Obtain the historical harmonic data set corresponding to each monitoring node in the distribution network in the historical time period; Based on the historical harmonic data set, determining a plurality of filter node combinations of the distribution network under a target optimized harmonic voltage; For any filter node combination, obtain the analog filter parameters corresponding to each filter node in the filter node combination, and calculate the target harmonic compensation current corresponding to each filter node in the filter node combination based on the historical harmonic data set and the analog filter parameters corresponding to each filter node in the filter node combination; Based on the target harmonic compensation current, the total power capacity corresponding to each filter node combination is determined, and based on the total power capacity, the target filter node combination is determined in each filter node combination; the target filter node combination is used to deploy harmonic filters on corresponding network nodes in the distribution network, and perform harmonic optimization on the distribution network through the harmonic filters.

2. The method according to claim 1, characterized in that The determining, based on the historical harmonic data set, a plurality of filter node combinations of the distribution network under a target optimized harmonic voltage comprises: From the historical harmonic data sets corresponding to the respective monitoring nodes in the historical time period, the historical harmonic data corresponding to the same historical moment are obtained to obtain the sub-harmonic data sets corresponding to the respective historical moments; Acquire a filter deployment factor, and determine a compensatory harmonic voltage based on the filter deployment factor; Based on the compensated harmonic voltage and the sub-harmonic data set, an optimized harmonic voltage is obtained; Based on the filter deployment factor that makes the optimized harmonic voltage equal to the target optimized harmonic voltage, a plurality of filter node combinations of the distribution network under the target optimized harmonic voltage are obtained.

3. The method according to claim 2, characterized in that The obtaining of a plurality of filter node combinations of the distribution network under the target optimized harmonic voltage based on the filter deployment factor that makes the optimized harmonic voltage the target optimized harmonic voltage comprises: Based on the particle swarm optimization algorithm, the filter deployment factor of the optimized harmonic voltage as the target optimized harmonic voltage is determined, and a plurality of filter node combinations of the distribution network under the target optimized harmonic voltage are obtained.

4. The method according to claim 2, characterized in that: The calculating the target harmonic compensation current corresponding to each filter node in the filter node combination based on the historical harmonic data set and the simulated filtering parameters corresponding to each filter node in the filter node combination includes: Based on the sub-harmonic data sets corresponding to the respective historical moments and the analog filtering parameters, harmonic compensation currents are calculated respectively to obtain harmonic compensation currents corresponding to the respective filter nodes in the filter node combination at the respective historical moments; Based on the harmonic compensation currents corresponding to the respective historical moments, a target harmonic compensation current corresponding to each filter node in the filter node combination is determined.

5. The method according to claim 1, characterized in that The determining, based on the target harmonic compensation current, the total power capacity corresponding to each filter node combination, includes: Obtaining a basic power capacity corresponding to the distribution network and a rated voltage corresponding to each filter node in each filter node combination; For any filter node combination, power calculation is performed based on the basic capacity, the rated voltage corresponding to each filter node in the filter node combination, and the target harmonic compensation current to obtain the node power corresponding to each filter node in the filter node combination; The node powers corresponding to the respective filter nodes in the same filter node combination are combined to obtain the total power capacities corresponding to the respective filter node combinations.

6. The method according to claim 1, characterized in that The method further comprises: After deploying harmonic filters on corresponding network nodes in the distribution network based on the target filter node combination; obtaining current harmonic data corresponding to each monitoring node in the distribution network; Acquire current filtering parameters corresponding to the network node where the harmonic filter is deployed in the distribution network, and calculate the harmonic compensation current of the network node where the harmonic filter is deployed at the next moment based on the current harmonic data and the current filtering parameters; The harmonic filter is controlled to perform harmonic optimization on the distribution network at the next moment according to the harmonic compensation current.

7. A harmonic optimization device for a distribution network, characterized in that: The device comprises: A data acquisition module is used to obtain historical harmonic data sets corresponding to each monitoring node in the distribution network in a historical time period; A node combination determination module, used to determine a plurality of filter node combinations of the distribution network under a target optimized harmonic voltage based on the historical harmonic data set; A compensation current calculation module is used to obtain, for any filter node combination, analog filter parameters corresponding to each filter node in the filter node combination, and calculate the target harmonic compensation current corresponding to each filter node in the filter node combination based on the historical harmonic data set and analog filter parameters corresponding to each filter node in the filter node combination; A harmonic optimization module is used to determine the total power capacity corresponding to each filter node combination based on the target harmonic compensation current, and determine a target filter node combination among the filter node combinations based on the total power capacity; the target filter node combination is used to deploy harmonic filters on corresponding network nodes in the distribution network, and perform harmonic optimization on the distribution network through the harmonic filters.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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