A soft switch access configuration method, device, terminal equipment and storage medium

Abstract

The present invention discloses a soft switch access configuration method, device, terminal equipment and storage medium, which not only considers the load characteristics of distributed power sources under different operating conditions, but also considers the configuration costs corresponding to the closed-loop access mode between feeders and the inter-ring network connection access mode of the soft switch, as well as the line construction cost and loss cost data. When the planning model is iteratively solved under multiple deployment and installation constraints, a soft switch access configuration scheme that meets both technical feasibility requirements and economic operation goals can be generated. The present invention can achieve coordinated optimization between the access configuration scheme of the SOP soft switch and the distribution network line deployment, thereby obtaining a reasonable access configuration scheme of the SOP soft switch, realizing the optimization of the comprehensive benefits, and ensuring that the distribution network operates efficiently and stably when the soft switch of the distribution network is accessed and configured according to the configuration scheme.

Description

Technical Field

[0001] The present invention relates to the technical field of soft switch access configuration, and in particular to a soft switch access configuration method, apparatus, terminal equipment and storage medium. Background Art

[0002] With the continued advancement of energy transformation and upgrading, the proportion of distributed renewable energy resources (DERs) connected to distribution networks has increased year by year. Their operating characteristics are significantly affected by the environment and exhibit significant randomness and volatility, which can cause numerous problems for distribution networks, such as voltage overshoot and network congestion. Soft open points (SOPs), as flexible regulation devices at the "grid" level of distribution systems, can change the system's traditional operating mode, enabling continuous regulation of power flows between feeders and effectively addressing a range of new issues brought about by the integration of distributed power sources. Therefore, when considering the integration of soft open points into distribution networks, it is often necessary to replan the number and routing of lines in the distribution network, as well as to configure the SOP (soft open point) access mode, location, and capacity within the lines.

[0003] There are generally two types of SOP (soft switch) access modes: inter-feeder closed-loop access and inter-ring interconnection access. Line feeder closed-loop access refers to the use of SOPs to connect two or more feeders that were originally open-loop in a distribution network, forming a closed-loop structure. Inter-ring interconnection refers to the use of SOPs to connect different single-ring structures, enabling flexible interconnection of feeders between different rings, further expanding the scope and flexibility of power flow regulation. In existing technologies, when planning distribution network lines and configuring soft switches, both main soft switch access modes require site selection and configuration. Often, based on historical experience, suitable line locations for SOP installation are pre-screened based on the generated distribution network line structure, or only a pre-defined set of lines are considered as candidates for SOP (soft switch) access. This results in a distribution network line deployment and SOP access plan. However, SOP access typically requires consideration of the operating data of distributed generation (DGs) within the distribution network, and different access modes require coordinated optimization with the distribution network line deployment to achieve optimal overall benefits. The existing technology ignores the diversity of distributed power sources under different operating conditions, and does not involve the mutual constraints between the SOP access mode and the line layout of the distribution network and the economic constraints between the operating costs. As a result, the SOP (soft switch) access configuration scheme cannot achieve coordinated optimization with the distribution network line deployment, resulting in unreasonable soft switch access configuration in the planning and deployment of the entire distribution network, which cannot play a role in enhancing the reliability and stability of the distribution network, and cannot ensure the efficient and stable operation of the distribution network. Summary of the Invention

[0004] The embodiments of the present invention provide a soft switch access configuration method, apparatus, and terminal device, which can achieve coordinated optimization between the SOP (soft switch) access configuration scheme and the distribution network line deployment, so that the final configuration scheme meets both technical feasibility requirements and economic operation goals. It can effectively solve the problem in the prior art that the efficient and stable operation of the distribution network cannot be ensured due to unreasonable soft switch access configuration in the planning and deployment of the entire distribution network.

[0005] An embodiment of the present invention provides a method for configuring soft switch access, including:

[0006] Acquire soft switch installation cost data, line construction cost data, and multiple typical daily scenario load curves used to characterize the power variation characteristics of distributed power sources in the distribution network throughout the year; wherein the soft switch installation cost data includes configuration cost data corresponding to different access modes; the access modes include an inter-feeder closed-loop access mode and an inter-ring network interconnection access mode;

[0007] Generate loss cost data based on the soft switch installation cost data and the load data in each typical daily scenario load curve; wherein the loss cost data includes: line loss cost data, soft switch operation loss cost data, and distributed power generation curtailment penalty cost data;

[0008] Based on the soft switch installation cost data, line construction cost data, and loss cost data, a planning model is constructed to characterize the coordinated planning of soft switches and lines. The constraints corresponding to the planning model include: line deployment constraints, soft switch configuration constraints, and power balance constraints.

[0009] Solving the planning model under various constraints to generate a corresponding configuration plan when the total cost is minimized; wherein the configuration plan includes: the number of lines to be deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch;

[0010] The lines of the distribution network are deployed and the access of the soft switches is configured according to the configuration scheme.

[0011] Preferably, the generation of each typical day scenario load curve includes:

[0012] Clustering the data set corresponding to the distribution network, which is used to represent the distributed power generation time series data throughout the year, to generate multiple cluster groups containing several daily scenario load curves;

[0013] For each cluster group, the daily scene load curve with the largest average correlation coefficient in each group is selected as the typical daily scene load curve; wherein the calculation formula of the average correlation coefficient is as follows:

[0014] ;

[0015] in, is the average correlation coefficient, and are the set of daily scenario load curves and the number of daily scenarios contained in a cluster group respectively; and are any two daily scenario load curves within a cluster group;

[0016] for and covariance of and They are and The variance of .

[0017] Preferably, the planning model includes: an upper layer model and a lower layer model; the loss cost data also includes: soft switching loss penalty cost data;

[0018] The objective function corresponding to the planning model is:

[0019] ;

[0020] in, is the total cost corresponding to the planning model, For the upper model, For the lower model; is the preset penalty coefficient;

[0021] The functional formula of the upper model is:

[0022] ;

[0023] ;

[0024] ;

[0025] ;

[0026] in, is the cost value corresponding to the minimum soft switch installation cost, line construction cost and total loss cost, is the line construction cost, is the soft switch installation cost, The total loss cost corresponding to line loss cost, soft switch operation loss cost and distributed generation power curtailment penalty cost;

[0027] α represents the investment cost per unit length of trunk line; represents the preset first-year discount rate; is the service life of the line; represents the length of the jth trunk line of the i-th substation; is the total number of substations; is the number of trunk lines corresponding to the i-th substation; is the investment cost per unit length of branch line; is the length of the qth branch line carried by the kth trunk line; is the total number of branch lines carried by the i-th trunk line; The construction cost per unit length of pipes; is the length of the corridor to be occupied; The length of the cable installed in the conduit; is the construction cost per unit length of cable; is the annual inspection and maintenance cost of the corridor;

[0028] is the preset discount rate for the second year; is the service life of the soft switching SOP; is the unit capacity investment cost of the soft switching SOP; is the installation capacity of the soft switch SOP; is the unit capacity maintenance cost of the soft switching SOP; is the number of soft switch SOPs installed; is the number of ports of the soft switch SOP;

[0029] is the probability of occurrence of the typical day scenario load curve; is the preset loss cost coefficient; Used to represent the line loss cost calculated through multiple typical daily scenario load curves; is the soft switching operation loss cost; is the penalty coefficient for power curtailment of distributed generation; is the penalty cost for power curtailment of distributed generation; It is a collection of typical daily scenario load curves;

[0030] The functional formula of the lower layer model is:

[0031] ;

[0032] in, represents the soft switching loss penalty cost, is the soft switching SOP at time t Active power loss of the port, is the square of the current amplitude of branch ij, is the resistance of the ij branch, is a collection of lines, For time collection.

[0033] Preferably, the constraints of the planning model further include: voltage amplitude constraints of line nodes, soft switch access line length constraints, soft switch operation constraints, reconstruction constraints, nonlinear constraints, and linear tangent plane constraints;

[0034] The line deployment constraints include:

[0035] ;

[0036] in, 、 、 They are respectively the line node set to be newly built, the line node set to be expanded, and the load node set; and Node The child node set and parent node set of ; For the node Flow Node Virtual power; is the flow from node n to node The virtual power, 1 means new substation i is built, 0 means no new substation is built. 1 means line ij is put into construction, and 0 means line ij is not put into construction. Indicates the number of elements in a collection;

[0037] The soft switch configuration constraints include:

[0038] ;

[0039] ;

[0040] in, It is a 0-1 variable, indicating the soft switch access mode; Indicates the soft switch access mode The corresponding access location, It is used to indicate that only one soft switch access mode can be used at the same time at the same line node; is for the preset parameters, is a preset positive number; Refers to the position where the soft switch is installed. lines, Refers to the total installed capacity of the soft switch, The unit installation capacity of the soft switch SOP;

[0041] The power balance constraint includes:

[0042] ;

[0043] ;

[0044] in, For nodes The injected active power, For nodes The injected reactive power, For nodes The voltage amplitude, node The voltage amplitude, 、 Node and nodes The real and imaginary parts of the admittance matrix between For nodes and nodes The phase angle difference between for Node and The current in the branch between nodes, is the node at time t The injected active power, is the node at time t The active power generated, is the node at time t Active power transmitted by soft switching SOP, is the node at time t Active power generated by distributed energy, is the node at time t The active load power, is the node at time t The injected reactive power, is the node at time t The reactive power generated, is the node at time t Reactive power transmitted through SOP, is the node at time t Reactive load power;

[0045] The voltage amplitude constraint of the line node includes:

[0046] ;

[0047] in, and are the voltage amplitudes of node i at time t the lower and upper limits of

[0048] The soft switch access line length constraint includes:

[0049] ;

[0050] in, is the line access length of the i-th soft switch SOP; l sop,max The upper limit of the line access length of the soft switch SOP;

[0051] The soft switching operation constraints include:

[0052] ;

[0053] ;

[0054] ;

[0055] in, is the active power transmitted by port i of the soft-switching SOP at time t, is the soft switching SOP at time t Active power transmitted by the port, is the soft switching SOP at time t Active power loss of the port, is the transmission capacity of the soft switching SOP, is the reactive power transmitted by the i-port of the soft-switching SOP at time t, is the soft switching SOP at time t Reactive power transmitted by the port, is the active power loss of port i of the soft-switching SOP at time t, is the loss coefficient of the i port of the soft switching SOP, For soft switching SOP The loss coefficient of the port, is the soft switching SOP at time t Active power loss of the port;

[0056] The reconstruction constraints include:

[0057] ;

[0058] in, is a branch set, is the set of branches including tie switches, is the branch at time t The state of j, is the number of branches in a single ring network, is the total number of tie switches in a single ring network, is the on / off state of the i-th switch in the t-th period, is the number of periods in the operating cycle, The maximum number of switch operations specified in the operating cycle;

[0059] The nonlinear constraints include:

[0060] ;

[0061] in, is the active power flowing through branch ij, is the reactive power flowing through branch ij, is the square of the current amplitude of branch ij, is the square of the voltage amplitude at node i, is the active power transmitted by sop;

[0062] The linear tangent plane constraint includes:

[0063] ;

[0064] .

[0065] Preferably, solving the planning model under various constraints and generating a corresponding configuration solution when the total cost is minimized includes:

[0066] Under the constraints of line deployment, soft switch configuration, power balance, voltage amplitude at line nodes, soft switch access line length, soft switch operation, and reconfiguration, the upper-level model is solved to generate the configuration scheme to be updated.

[0067] Under the constraints of line deployment, soft switch configuration, power balance, voltage amplitude at line nodes, soft switch access line length, soft switch operation, reconstruction, nonlinearity, and linear tangent plane, the upper and lower models are solved to generate the corresponding configuration plan with the minimum total cost.

[0068] Preferably, solving the upper-layer model and the lower-layer model to generate a corresponding configuration solution when the total cost is minimized includes:

[0069] Randomly generate a number of particles corresponding to a group; each particle includes: the number of lines deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch;

[0070] Initialize the particles of the population, obtain the historical position and historical velocity of each particle, and obtain the historical position of the population and the global fitness of the population;

[0071] Repeat the following target particle determination operation until the current iteration number is the same as the preset iteration number, and output the target particles so that the output target particles all meet the line deployment constraints, soft switch configuration constraints, power balance constraints, line node voltage amplitude constraints, soft switch access line length constraints, soft switch operation constraints, and reconstruction constraints:

[0072] Get the current iteration number;

[0073] When the current number of iterations is less than the preset number of iterations, the local fitness of each particle in the upper model is calculated based on the particle's historical position;

[0074] Generate the updated particle velocity corresponding to each particle based on the particle's historical position, particle's historical velocity, local fitness, population's historical position, and population's global fitness;

[0075] Generate the updated particle position corresponding to each particle based on the particle's historical position and the population's global fitness;

[0076] Generate an updated population position and an updated population global fitness based on the functional formula of the upper model, each updated particle velocity, each updated particle position, and each updated local fitness;

[0077] Output the target particles corresponding to the updated population position;

[0078] Adding a preset iteration increment to the current iteration number value to obtain an updated iteration number, and using the updated iteration number as the iteration number for the next target particle determination operation;

[0079] The updated particle velocity is used as the particle historical velocity when the target particle determination operation is performed next time, the updated particle position is used as the particle historical position when the target particle determination operation is performed next time, the updated population position is used as the population historical position when the target particle determination operation is performed next time, and the updated population global fitness is used as the population global fitness when the target particle determination operation is performed next time.

[0080] Preferably, each particle also corresponds to a coding matrix, and the coding matrix includes:

[0081] ;

[0082] in, is the encoding matrix used to characterize the configuration scheme corresponding to the minimum total cost, the encoding matrix The diagonal elements in the represent that the access mode of the soft switch SOP is the closed-loop access mode between feeders, and the non-diagonal elements represent that the access mode of the soft switch SOP is the inter-ring network connection access mode; Indicates the installation position of the soft switch SOP in each tie switch of the line. Indicates the installation capacity of the soft switch SOP, is the total number of tie switches.

[0083] Based on the above method embodiments, the present invention provides corresponding device embodiments.

[0084] An embodiment of the present invention provides a soft switch access configuration device, comprising: a data acquisition module, a loss cost data generation module, a planning model construction module, a configuration solution solution module, and a soft switch configuration module;

[0085] The data acquisition module is configured to acquire soft switch installation cost data, line construction cost data, and multiple typical daily scenario load curves used to characterize the power variation characteristics of distributed power sources in the distribution network throughout the year; wherein the soft switch installation cost data includes configuration cost data corresponding to different access modes; the access modes include an inter-feeder closed-loop access mode and an inter-ring network interconnection access mode;

[0086] The loss cost data generation module is configured to generate loss cost data based on the soft switch installation cost data and the load data in each typical daily scenario load curve; wherein the loss cost data includes: line loss cost data, soft switch operation loss cost data, and distributed power generation curtailment penalty cost data;

[0087] The planning model construction module is configured to construct a planning model for characterizing the coordinated planning of soft switches and lines based on the soft switch installation cost data, the line construction cost data, and the loss cost data; wherein the constraints corresponding to the planning model include: line deployment constraints, soft switch configuration constraints, and power balance constraints;

[0088] The configuration solution solving module is used to solve the planning model under various constraints and generate a corresponding configuration solution when the total cost is minimized; wherein the configuration solution includes: the number of lines to be deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch;

[0089] The soft switch configuration module is used to deploy the lines of the distribution network and configure the access of the soft switch according to the configuration scheme.

[0090] Based on the above method embodiments, the present invention provides corresponding terminal device embodiments.

[0091] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the soft switch access configuration method described in the above embodiment of the invention is implemented.

[0092] Based on the above method embodiment, the present invention provides a corresponding storage medium embodiment.

[0093] Another embodiment of the present invention provides a storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the soft switch access configuration method described in the above embodiment of the invention.

[0094] The following beneficial effects are achieved by implementing the present invention:

[0095] An embodiment of the present invention provides a soft switch access configuration method, apparatus, terminal equipment and storage medium. The present invention can generate total loss cost data during the operation of the distribution network based on load data in multiple typical daily scenario load curves for characterizing the power change characteristics of distributed power sources throughout the year. Therefore, when constructing and solving the planning model, the load characteristics of the distributed power sources under different operating conditions are fully considered, and two soft switch access modes, namely the feeder-to-feeder closed-loop access mode and the ring network-to-ring network connection access mode, are considered in the planning model, and the configuration costs under different access modes are calculated respectively, so that the constructed planning model not only considers the line construction cost, but also the soft switch installation cost and loss cost data, solves the economic constraint problem between the access mode and line layout of the SOP that is not involved in the prior art, and finally solves the planning model under multiple constraint conditions such as line deployment constraints, soft switch configuration constraints and power balance constraints, ensuring that the generated configuration scheme also meets the deployment constraints between the access installation and line layout of the SOP. Compared with the existing technology, the present invention can achieve coordinated optimization between the SOP (soft switch) access configuration scheme and the distribution network line deployment, so that the final configuration scheme not only meets the technical feasibility requirements, but also meets the economic operation goals and achieves the optimization of comprehensive benefits. A reasonable soft switch access configuration scheme can be obtained. When the distribution network lines are deployed and the access of the soft switch is configured according to the configuration scheme, the SOP (soft switch) access configuration scheme can improve the reliability and stability of the distribution network, thereby ensuring the efficient and stable operation of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] Figure 1 The present invention is a flowchart of a soft switch access configuration method provided by an embodiment of the present invention.

[0097] Figure 2 This is a schematic diagram of the planning of a soft switch SOP access solution in a distribution network provided by an embodiment of the present invention.

[0098] Figure 3 It is a structural diagram of a soft switch access configuration device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0099] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0100] like Figure 1FIG. 1 is a flow chart of a soft switch access configuration method provided by an embodiment of the present invention. The soft switch access configuration method includes:

[0101] Step S1: Acquire soft switch installation cost data, line construction cost data, and multiple typical daily scenario load curves used to characterize the power variation characteristics of distributed power generation in the distribution network throughout the year; wherein the soft switch installation cost data includes configuration cost data corresponding to different access modes; the access modes include inter-feeder closed-loop access mode and inter-ring network connection access mode;

[0102] Step S2: Generate loss cost data based on the soft switch installation cost data and the load data in each typical daily scenario load curve; wherein the loss cost data includes: line loss cost data, soft switch operation loss cost data, and distributed power generation curtailment penalty cost data;

[0103] Step S3: Constructing a planning model for characterizing the coordinated planning of soft switches and lines based on the soft switch installation cost data, the line construction cost data, and the loss cost data; wherein the constraints corresponding to the planning model include: line deployment constraints, soft switch configuration constraints, and power balance constraints;

[0104] Step S4: Solving the planning model under various constraints to generate a corresponding configuration plan when the total cost is minimized; wherein the configuration plan includes: the number of lines to be deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch;

[0105] Step S5: Deploy the lines of the distribution network and configure the access of the soft switches according to the configuration scheme.

[0106] For step S1, in a preferred embodiment, the present invention can obtain soft switch installation cost data and line construction cost data, thereby generating soft switch installation cost and line construction cost; wherein, the soft switch installation cost data includes configuration cost data corresponding to different access modes, such as the closed-loop access mode between feeders and the interconnection access mode between ring networks, so that the subsequent construction of the planning model can iteratively simulate the costs corresponding to different access modes.

[0107] Furthermore, the present invention can also construct typical day scenarios based on the improved GMM clustering method, and the generation of the load curve of each typical day scenario specifically includes:

[0108] Clustering the data set corresponding to the distribution network, which is used to represent the distributed power generation time series data throughout the year, to generate multiple cluster groups containing several daily scenario load curves;

[0109] For each cluster group, the daily scene load curve with the largest average correlation coefficient in each group is selected as the typical daily scene load curve; wherein the calculation formula of the average correlation coefficient is as follows:

[0110] ;

[0111] in, is the average correlation coefficient, and are the set of daily scenario load curves and the number of daily scenarios contained in a cluster group respectively; and are any two daily scenario load curves within a cluster group;

[0112] for and covariance of and They are and The variance of .

[0113] Specifically, the present invention can perform cluster analysis and scenario selection on the time series data sets of load, photovoltaic generation (PVG) and wind power (WTG) in the time series data sets throughout the year, and construct a typical daily scenario that can accurately characterize the wind, solar and load power variation characteristics throughout the year. Distributed Generation (DG) generally refers to small modular, decentralized, efficient and reliable power generation units distributed near users with a power generation capacity ranging from a few kilowatts to tens of megawatts, including but not limited to solar photovoltaic power generation, wind power generation, biomass power generation, geothermal power generation, and small energy comprehensive utilization power generation systems such as gas turbines and fuel cells. Taking into account that the correlation between load power and DG output time series matching will affect the planning results, the present invention selects the mean and standard deviation of the load, PVG and WTG daily power curves as the characterization of a single typical daily scenario, so as to further perform k-means clustering based on the Mahalanobis distance, which can be the multivariate Gaussian distribution parameters. and The iterative solution provides an initial value, and the process of determining the optimal number of clusters is as follows: using the Bayesian information criterion (BIC) to perform probability estimation on the number of GMM cluster groups, and gradually determining the optimal number of clusters U, so that U cluster groups containing several daily scene load curves can be generated. In order to maximize the sum of the correlation coefficients between the typical daily scene and all the daily scenes in the group, the present invention can select the daily scene with the largest average correlation coefficient value in each group as the typical daily scene according to the average correlation coefficient that can be obtained by calculation.

[0114] Through cluster analysis, the embodiment of the present invention can extract representative typical daily scenario load curves from the annual time series data set. These curves can accurately reflect the power variation characteristics of distributed power sources (such as photovoltaic and wind power) and loads throughout the year, thereby ensuring the comprehensiveness and accuracy of the typical daily scenario construction.

[0115] For step S2, an embodiment of the present invention can be based on multiple typical daily scenario load curves for characterizing the distributed power generation power variation characteristics of the distribution network throughout the year, and can generate loss cost data of the distribution network during operation after connecting to the soft switch based on the soft switch installation cost data and the load data in each curve.

[0116] Illustratively, the loss cost data includes: line loss cost data, soft switch operation loss cost data, and distributed power generation curtailment penalty cost data; when constructing a total loss cost function corresponding to the line loss cost, soft switch operation loss cost, and distributed power generation curtailment penalty cost based on each cost data, the following is obtained:

[0117] ;

[0118] in, The total loss cost corresponding to line loss cost, soft switch operation loss cost and distributed generation power curtailment penalty cost; is the probability of occurrence of the typical day scenario load curve; is the preset loss cost coefficient; Used to represent the line loss cost calculated through multiple typical daily scenario load curves; is the soft switching operation loss cost; is the penalty coefficient for power curtailment of distributed generation; is the penalty cost for power curtailment of distributed generation; It is a collection of typical daily scenario load curves.

[0119] The total loss cost function of the present invention not only takes into account the line loss cost (i.e., the energy loss caused by factors such as resistance and reactance during the power transmission process of the power grid), but also incorporates the soft switch operation loss cost (the energy loss caused by the soft switch's own operation after being connected to the power grid) and the distributed power generation curtailment penalty cost (the economic penalty caused by the waste of electricity or curtailment due to the mismatch between the output of the distributed power generation and the grid demand), thereby making the cost assessment after SOP access more accurate and close to reality.

[0120] By introducing typical daily load curves and their probability of occurrence, the distribution network's operation under different operating conditions can be more accurately simulated, leading to more accurate loss cost calculations. Based on the analysis of the total loss cost function, the distribution network's line deployment, soft switch access mode, installation location, and capacity can be optimized to minimize total cost or maximize overall benefits.

[0121] For step S3, in a preferred embodiment, the planning model includes: an upper-level model and a lower-level model; and the loss cost data further includes: soft switch loss penalty cost data; then, when the present invention constructs a planning model for characterizing the coordinated planning of soft switches and lines based on the soft switch installation cost data, the line construction cost data, and the loss cost data, the upper-level model of the planning model can be constructed based on the soft switch installation cost data, the line construction cost data, and the loss cost data, and the lower-level model of the planning model can be constructed based on the soft switch loss penalty cost data.

[0122] In a preferred embodiment, the objective function corresponding to the planning model is:

[0123] ;

[0124] in, is the total cost corresponding to the planning model, For the upper model, For the lower model; is the preset penalty coefficient;

[0125] The functional formula of the upper model is:

[0126] ;

[0127] ;

[0128] ;

[0129] ;

[0130] in, is the cost value corresponding to the minimum soft switch installation cost, line construction cost and total loss cost, is the line construction cost, is the soft switch installation cost, The total loss cost corresponding to line loss cost, soft switch operation loss cost and distributed generation power curtailment penalty cost;

[0131] α represents the investment cost per unit length of trunk line; represents the preset first-year discount rate; is the service life of the line; represents the length of the jth trunk line of the i-th substation; is the total number of substations; is the number of trunk lines corresponding to the i-th substation; is the investment cost per unit length of branch line; is the length of the qth branch line carried by the kth trunk line; is the total number of branch lines carried by the i-th trunk line; The construction cost per unit length of pipes; is the length of the corridor to be occupied; The length of the cable installed in the conduit; is the construction cost per unit length of cable; is the annual inspection and maintenance cost of the corridor;

[0132] is the preset discount rate for the second year; is the service life of the soft switching SOP; is the unit capacity investment cost of the soft switching SOP; is the installation capacity of the soft switch SOP; is the unit capacity maintenance cost of the soft switching SOP; is the number of soft switch SOPs installed; is the number of ports of the soft switch SOP;

[0133] is the probability of occurrence of the typical day scenario load curve; is the preset loss cost coefficient; Used to represent the line loss cost calculated through multiple typical daily scenario load curves; is the soft switching operation loss cost; is the penalty coefficient for power curtailment of distributed generation; is the penalty cost for power curtailment of distributed generation; It is a collection of typical daily scenario load curves;

[0134] The functional formula of the lower layer model is:

[0135] ;

[0136] in, represents the soft switching loss penalty cost, is the soft switching SOP at time t Active power loss of the port, is the square of the current amplitude of branch ij, is the resistance of the ij branch, is a collection of lines, For time collection.

[0137] In a preferred embodiment, the constraints of the planning model also include: voltage amplitude constraints of line nodes, soft switch access line length constraints, soft switch operation constraints, reconstruction constraints, nonlinear constraints and linear tangent plane constraints; it can be understood that the nonlinear constraints and linear tangent plane constraints correspond to the lower-level model.

[0138] The line deployment constraints include:

[0139] ;

[0140] in, 、 、 They are respectively the line node set to be newly built, the line node set to be expanded, and the load node set; and Node The child node set and parent node set of ; For the node Flow Node Virtual power; is the flow from node n to node The virtual power, 1 means new substation i is built, 0 means no new substation is built. 1 means line ij is put into construction, and 0 means line ij is not put into construction. Indicates the number of elements in a collection;

[0141] The soft switch configuration constraints include:

[0142] ;

[0143] ;

[0144] in, It is a 0-1 variable, indicating the soft switch access mode; Indicates the soft switch access mode The corresponding access location, It is used to indicate that only one soft switch access mode can be used at the same time at the same line node; is for the preset parameters, is a preset positive number; Refers to the position where the soft switch is installed. lines, Refers to the total installed capacity of the soft switch, The unit installation capacity of the soft switch SOP;

[0145] The power balance constraint includes:

[0146] ;

[0147] ;

[0148] in, For nodes The injected active power, For nodes The injected reactive power, For nodes The voltage amplitude, node The voltage amplitude, 、 Node and nodes The real and imaginary parts of the admittance matrix between For nodes and nodes The phase angle difference between for Node and The current in the branch between nodes, is the node at time t The injected active power, is the node at time t The active power generated, is the node at time t Active power transmitted by soft switching SOP, is the node at time t Active power generated by distributed energy, is the node at time t The active load power, is the node at time t The injected reactive power, is the node at time t The reactive power generated, is the node at time t Reactive power transmitted through SOP, is the node at time t Reactive load power;

[0149] The voltage amplitude constraint of the line node includes:

[0150] ;

[0151] in, and are the voltage amplitudes of node i at time t the lower and upper limits of

[0152] The soft switch access line length constraint includes:

[0153] ;

[0154] in, is the line access length of the i-th soft switch SOP; l sop,max The upper limit of the line access length of the soft switch SOP;

[0155] The soft switching operation constraints include:

[0156] ;

[0157] ;

[0158] ;

[0159] in, is the active power transmitted by port i of the soft-switching SOP at time t, is the soft switching SOP at time t Active power transmitted by the port, is the soft switching SOP at time t Active power loss of the port, is the transmission capacity of the soft switching SOP, is the reactive power transmitted by the i-port of the soft-switching SOP at time t, is the soft switching SOP at time t Reactive power transmitted by the port, is the active power loss of port i of the soft-switching SOP at time t, is the loss coefficient of the i port of the soft switching SOP, For soft switching SOP The loss coefficient of the port, is the soft switching SOP at time t Active power loss of the port;

[0160] The reconstruction constraints include:

[0161] ;

[0162] in, is a branch set, is the set of branches including tie switches, is the branch at time t The state of j, is the number of branches in a single ring network, is the total number of tie switches in a single ring network, is the on / off state of the i-th switch in the t-th period, is the number of periods in the operating cycle, The maximum number of switch operations specified in the operating cycle;

[0163] The nonlinear constraints include:

[0164] ;

[0165] in, is the active power flowing through branch ij, is the reactive power flowing through branch ij, is the square of the current amplitude of branch ij, is the square of the voltage amplitude at node i, is the active power transmitted by sop;

[0166] The linear tangent plane constraint includes:

[0167] ;

[0168] .

[0169] It can be understood that the present invention can decompose complex planning problems into upper-level and lower-level models, clearly defining the responsibilities and focus of different components. The upper-level model focuses on optimizing economic costs, including line construction costs, soft switch installation costs, and total loss costs; while the lower-level model focuses on evaluating soft switch loss penalty costs. By incorporating soft switch loss penalty costs into the lower-level model for a separate evaluation, a more comprehensive consideration can be given to the actual operation of soft switches in the distribution network and their impact on overall economic costs.

[0170] Illustratively, the upper layer model and the lower layer model of the present invention can independently perform parameter adjustment and optimization, thereby simplifying the processing process of the entire planning problem, reducing the complexity of the problem, and improving the solution efficiency.

[0171] Regarding step S4, in a preferred embodiment, the present invention can solve the planning model under various constraints to generate the corresponding line deployment quantity, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch when the total cost is minimized;

[0172] Specifically, the corresponding configuration solution is generated when the total cost is minimized, including:

[0173] Under the constraints of line deployment, soft switch configuration, power balance, voltage amplitude at line nodes, soft switch access line length, soft switch operation, reconstruction, nonlinearity, and linear tangent plane, the upper and lower models are solved to generate the corresponding configuration plan with the minimum total cost.

[0174] In a preferred embodiment, when solving the upper-layer model and the lower-layer model and generating a corresponding configuration solution when the total cost is minimized, the method specifically includes:

[0175] Randomly generate a number of particles corresponding to a group; each particle includes: the number of lines deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch;

[0176] Initialize the particles of the population, obtain the historical position and historical velocity of each particle, and obtain the historical position of the population and the global fitness of the population;

[0177] Repeat the following target particle determination operation until the current iteration number is the same as the preset iteration number, and output the target particles so that the output target particles all meet the line deployment constraints, soft switch configuration constraints, power balance constraints, line node voltage amplitude constraints, soft switch access line length constraints, soft switch operation constraints, and reconstruction constraints:

[0178] Get the current iteration number;

[0179] When the current number of iterations is less than the preset number of iterations, the local fitness of each particle in the upper model is calculated based on the particle's historical position;

[0180] Generate the updated particle velocity corresponding to each particle based on the particle's historical position, particle's historical velocity, local fitness, population's historical position, and population's global fitness;

[0181] Generate the updated particle position corresponding to each particle based on the particle's historical position and the population's global fitness;

[0182] Generate an updated population position and an updated population global fitness based on the functional formula of the upper model, each updated particle velocity, each updated particle position, and each updated local fitness;

[0183] Output the target particles corresponding to the updated population position;

[0184] Adding a preset iteration increment to the current iteration number value to obtain an updated iteration number, and using the updated iteration number as the iteration number for the next target particle determination operation;

[0185] The updated particle velocity is used as the particle historical velocity when the target particle determination operation is performed next time, the updated particle position is used as the particle historical position when the target particle determination operation is performed next time, the updated population position is used as the population historical position when the target particle determination operation is performed next time, and the updated population global fitness is used as the population global fitness when the target particle determination operation is performed next time.

[0186] Each particle also corresponds to a coding matrix, and the coding matrix includes:

[0187] ;

[0188] in, is the encoding matrix used to characterize the configuration scheme corresponding to the minimum total cost, the encoding matrix The diagonal elements in the represent that the access mode of the soft switch SOP is the closed-loop access mode between feeders, and the non-diagonal elements represent that the access mode of the soft switch SOP is the inter-ring network connection access mode; Indicates the installation position of the soft switch SOP in each tie switch of the line. Indicates the installation capacity of the soft switch SOP, is the total number of tie switches.

[0189] It can be understood that when the present invention solves the objective function, when solving the line deployment and SOP configuration scheme through the particle swarm algorithm, it can be optimized and adjusted based on the above-mentioned encoding matrix, so that in each iteration, each particle updates its position and speed in the solution space by tracking two extreme values, one is the optimal solution of the single particle itself in the iteration process, that is, the individual extreme value; the other is the optimal solution of the particle group in the iteration process, that is, the global extreme value, thereby realizing the search for the optimal solution in the feasible solution space.

[0190] The encoding matrix intuitively and structuredly represents the configuration solution that minimizes total cost. For example, the diagonal and off-diagonal elements represent the closed-loop access mode between feeders and the interconnected access mode between ring networks, respectively. This allows for a clear and quick understanding of the SOP access mode. Other elements in the encoding matrix, such as the SOP installation location and capacity, also provide detailed information about the configuration solution, making it easy to understand and implement.

[0191] The encoding matrix makes it easier for the particle swarm algorithm to search for the optimal solution in the solution space. Each particle (i.e., each potential configuration) can be represented by an encoding matrix, which simplifies the algorithm's implementation and computation. Furthermore, the introduction of the encoding matrix makes it easier to apply various optimization techniques, such as crossover and mutation in genetic algorithms, to further improve the quality of the solution. Therefore, the encoding matrix enables the algorithm to converge to the optimal solution more quickly. Since each particle is represented by an encoding matrix, the algorithm can more easily evaluate each particle's fitness (i.e., total cost) and update particles based on that fitness, improving search efficiency.

[0192] In one embodiment, in order to avoid falling into the local optimum and to maximize the guarantee of obtaining the optimal SOP site selection and volume determination scheme, the present invention introduces adaptive weights and shrinkage factors to improve the algorithm when updating the particle velocity. The specific adjustment method is as follows:

[0193] Introducing adaptive weights: Where: is the weight, and its value range is [0.5, 1]; A random number between 0 and 1; 、 are the maximum and minimum values ​​of the weight respectively.

[0194] In order to effectively search different areas and obtain high-quality solutions, a shrinkage factor is introduced:

[0195] ;

[0196] Where: is the shrinkage factor; It is the sum of the two preset learning factors c1 and c2, and its value is greater than 4.

[0197] Schematically, when solving the lower-level model, the lower-level model can be solved under nonlinear constraints and linear tangent plane constraints. It can be understood that the lower-level model includes DG reduction and SOP operating costs, which are not strictly increasing functions of current. Therefore, through nonlinear constraints and linear tangent plane constraints, the gradually tightened linear tangent plane gradually shrinks the convex relaxation gap to a given threshold, so as to obtain the optimal solution that ultimately meets the operating requirements.

[0198] In a preferred embodiment, a certain area contains two transformers, the main line model is YJV22-3*185, the branch line model is YJV22-3*95, the line type is cable, pipe laying, and the maximum number of loops is 3. At the same time, the load types in the area include four typical loads: commercial, residential, administrative, and industrial, with a total of 97 load points and a total capacity of 20MVA. The regional distributed power access type is photovoltaic, concentrated on the right side of the area, with a total capacity of 6MW, using a two-port hybrid SOP (parallel interconnecting switch), the port planning capacity is an integer multiple of 10kVA, and the maximum number of switches operating in a day is 3 times. After constructing the planning model with the above data and solving it, it can be obtained as follows Figure 2 From the planning diagram of the access scheme shown in the figure, it can be concluded that the configuration scheme for this area is to build a total of 3 groups of lines, of which the first group of lines adopts the closed-loop access mode between feeders, and the second and third groups adopt the inter-ring network connection access mode.

[0199] For step S5, in a preferred embodiment, the present invention can solve the planning model to obtain a solution containing a set of line nodes. These node sets actually define the direction and connection relationship of each line in the distribution network. Based on these node sets, the specific path and length of each planned line can be determined, and then the required number of lines can be obtained, so that the lines can be deployed. Based on the obtained number of installed soft switch SOPs, the installation capacity of the soft switch SOPs, the installation position of the ports of the soft switch SOPs in the interconnecting switches, and the soft switch access mode, the port configuration of the soft switch SOP can be determined, that is, which interconnecting switches each port should be connected to, and the corresponding access mode (such as the closed-loop access mode between feeders and the interconnecting access mode between ring networks) configuration can be implemented.

[0200] like Figure 3 As shown, based on the above-mentioned various embodiments of the soft switch access configuration method, the present invention provides corresponding device embodiments;

[0201] An embodiment of the present invention provides a soft switch access configuration device, comprising: a data acquisition module, a loss cost data generation module, a planning model construction module, a configuration solution solution module, and a soft switch configuration module;

[0202] The data acquisition module is configured to acquire soft switch installation cost data, line construction cost data, and multiple typical daily scenario load curves used to characterize the power variation characteristics of distributed power sources in the distribution network throughout the year; wherein the soft switch installation cost data includes configuration cost data corresponding to different access modes; the access modes include an inter-feeder closed-loop access mode and an inter-ring network interconnection access mode;

[0203] The loss cost data generation module is configured to generate loss cost data based on the soft switch installation cost data and the load data in each typical daily scenario load curve; wherein the loss cost data includes: line loss cost data, soft switch operation loss cost data, and distributed power generation curtailment penalty cost data;

[0204] The planning model construction module is configured to construct a planning model for characterizing the coordinated planning of soft switches and lines based on the soft switch installation cost data, the line construction cost data, and the loss cost data; wherein the constraints corresponding to the planning model include: line deployment constraints, soft switch configuration constraints, and power balance constraints;

[0205] The configuration solution solving module is used to solve the planning model under various constraints and generate a corresponding configuration solution when the total cost is minimized; wherein the configuration solution includes: the number of lines to be deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch;

[0206] The soft switch configuration module is used to deploy the lines of the distribution network and configure the access of the soft switch according to the configuration scheme.

[0207] It should be noted that the device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement the present invention without paying any creative effort.

[0208] Those skilled in the art can clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0209] Based on the above-mentioned various embodiments of the soft switch access configuration method, the present invention provides corresponding embodiments of terminal equipment items.

[0210] An embodiment of the present invention provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a soft switch access configuration method described in any method embodiment of the present invention.

[0211] The terminal device may be a computing terminal device such as a desktop computer, a notebook computer, a palmtop computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0212] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor. The processor is the control center of the terminal device and connects various parts of the entire terminal device using various interfaces and lines.

[0213] The memory can be used to store the computer program. The processor implements the various functions of the terminal device by running or executing the computer program stored in the memory and accessing the data stored in the memory. The memory may primarily include a program storage area and a data storage area. The program storage area may store an operating system, at least one application required for a function, and the data storage area may store data generated based on the use of the mobile phone. Furthermore, the memory may include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0214] Based on the above-mentioned various embodiments of the soft switch access configuration method, the present invention provides corresponding storage medium item embodiments.

[0215] An embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a soft switch access configuration method described in any method embodiment of the present invention.

[0216] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium. It should be noted that the content of the computer-readable medium can be appropriately increased or decreased based on the requirements of legislation and patent practice within a jurisdiction. For example, in some jurisdictions, based on legislation and patent practice, computer-readable media does not include electric carrier signals and telecommunication signals.

[0217] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A soft switch access configuration method, characterized in that: include: Acquire soft switch installation cost data, line construction cost data, and multiple typical daily scenario load curves used to characterize the power variation characteristics of distributed power sources in the distribution network throughout the year; wherein the soft switch installation cost data includes configuration cost data corresponding to different access modes; the access modes include an inter-feeder closed-loop access mode and an inter-ring network interconnection access mode; Generate loss cost data based on the soft switch installation cost data and the load data in each typical daily scenario load curve; wherein the loss cost data includes: line loss cost data, soft switch operation loss cost data, and distributed power generation curtailment penalty cost data; Based on the soft switch installation cost data, line construction cost data, and loss cost data, a planning model is constructed to characterize the coordinated planning of soft switches and lines. The constraints corresponding to the planning model include: line deployment constraints, soft switch configuration constraints, and power balance constraints. Solving the planning model under various constraints to generate a corresponding configuration plan when the total cost is minimized; wherein the configuration plan includes: the number of lines to be deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch; Deploying the lines of the distribution network and configuring the access of the soft switches according to the configuration scheme; The planning model includes: an upper layer model and a lower layer model; the loss cost data also includes: soft switching loss penalty cost data; The objective function corresponding to the planning model is: ； in, is the total cost corresponding to the planning model, For the upper model, For the lower model; is the preset penalty coefficient; The functional formula of the upper model is: ； ； ； ； in, is the cost value corresponding to the minimum soft switch installation cost, line construction cost and total loss cost, is the line construction cost, is the soft switch installation cost, The total loss cost corresponding to line loss cost, soft switch operation loss cost and distributed generation power curtailment penalty cost; α represents the investment cost per unit length of trunk line; represents the preset first-year discount rate; is the service life of the line; represents the length of the jth trunk line of the i-th substation; is the total number of substations; is the number of trunk lines corresponding to the i-th substation; is the investment cost per unit length of branch line; is the length of the qth branch line carried by the kth trunk line; is the total number of branch lines carried by the i-th trunk line; The construction cost per unit length of pipes; is the length of the corridor to be occupied; The length of the cable installed in the conduit; is the construction cost per unit length of cable; is the annual inspection and maintenance cost of the corridor; is the preset discount rate for the second year; is the service life of the soft switching SOP; is the unit capacity investment cost of the soft switching SOP; is the installation capacity of the soft switch SOP; is the unit capacity maintenance cost of the soft switching SOP; is the number of soft switch SOPs installed; is the number of ports of the soft switch SOP; is the probability of occurrence of the typical day scenario load curve; is the preset loss cost coefficient; Used to represent the line loss cost calculated through multiple typical daily scenario load curves; is the soft switching operation loss cost; is the penalty coefficient for power curtailment of distributed generation; is the penalty cost for power curtailment of distributed generation; It is a collection of typical daily scenario load curves; The functional formula of the lower layer model is: ； in, represents the soft switching loss penalty cost, is the soft switching SOP at time t Active power loss of the port, is the square of the current amplitude of branch ij, is the resistance of the ij branch, is a collection of lines, is the time collection; The soft switch configuration constraints include: ； ； in, It is a 0-1 variable, indicating the soft switch access mode; Indicates the soft switch access mode The corresponding access location, It is used to indicate that only one soft switch access mode can be used at the same time at the same line node; is for the preset parameters, is a preset positive number; Refers to the position where the soft switch is installed. lines, Refers to the total installed capacity of the soft switch, This is the unit installation capacity of the soft switching SOP.

2. A soft switch access configuration method according to claim 1, characterized in that: The generation of each typical day scenario load curve includes: Clustering the data set corresponding to the distribution network, which is used to represent the distributed power generation time series data throughout the year, to generate multiple cluster groups containing several daily scenario load curves; For each cluster group, the daily scene load curve with the largest average correlation coefficient in each group is selected as the typical daily scene load curve; wherein the calculation formula of the average correlation coefficient is as follows: ； in, is the average correlation coefficient, and are the set of daily scenario load curves and the number of daily scenarios contained in a cluster group respectively; and are any two daily scenario load curves within a cluster group; for and covariance of and They are and The variance of .

3. A soft switch access configuration method according to claim 2, characterized in that: The constraints of the planning model also include: voltage amplitude constraints of line nodes, soft switch access line length constraints, soft switch operation constraints, reconstruction constraints, nonlinear constraints, and linear tangent plane constraints; The line deployment constraints include: ； in, 、 、 They are respectively the line node set to be newly built, the line node set to be expanded, and the load node set; and Node The child node set and parent node set of ; For the node Flow Node Virtual power; is the flow from node n to node The virtual power, 1 means new substation i is built, 0 means no new substation is built. 1 means line ij is put into construction, and 0 means line ij is not put into construction. Indicates the number of elements in a collection; The power balance constraint includes: ； ； in, For nodes The injected active power, For nodes The injected reactive power, For nodes The voltage amplitude, node The voltage amplitude, 、 Node and nodes The real and imaginary parts of the admittance matrix between For nodes and nodes The phase angle difference between for Node and The current in the branch between nodes, is the node at time t The injected active power, is the node at time t The active power generated, is the node at time t Active power transmitted by soft switching SOP, is the node at time t Active power generated by distributed energy, is the node at time t The active load power, is the node at time t The injected reactive power, is the node at time t The reactive power generated, is the node at time t Reactive power transmitted through SOP, is the node at time t Reactive load power; The voltage amplitude constraint of the line node includes: ； in, and are the voltage amplitudes of node i at time t the lower and upper limits of The soft switch access line length constraint includes: ； in, is the line access length of the i-th soft switch SOP; l sop,max The upper limit of the line access length of the soft switch SOP; The soft switching operation constraints include: ； ； ； in, is the active power transmitted by port i of the soft-switching SOP at time t, is the soft switching SOP at time t Active power transmitted by the port, is the soft switching SOP at time t Active power loss of the port, is the transmission capacity of the soft switching SOP, is the reactive power transmitted by the i-port of the soft-switching SOP at time t, is the soft switching SOP at time t Reactive power transmitted by the port, is the active power loss of port i of the soft-switching SOP at time t, is the loss coefficient of the i port of the soft switching SOP, For soft switching SOP The loss coefficient of the port, is the soft switching SOP at time t Active power loss of the port; The reconstruction constraints include: ； in, is a branch set, is the set of branches including tie switches, is the branch at time t The state of j, is the number of branches in a single ring network, is the total number of tie switches in a single ring network, is the on / off state of the i-th switch in the t-th period, is the number of periods in the operating cycle, The maximum number of switch operations specified in the operating cycle; The nonlinear constraints include: ； in, is the active power flowing through branch ij, is the reactive power flowing through branch ij, is the square of the current amplitude of branch ij, is the square of the voltage amplitude at node i, is the active power transmitted by sop; The linear tangent plane constraint includes: ； 。 4. A soft switch access configuration method according to claim 3, characterized in that: Solving the planning model under various constraints and generating a corresponding configuration solution when the total cost is minimized includes: Under the constraints of line deployment, soft switch configuration, power balance, voltage amplitude at line nodes, soft switch access line length, soft switch operation, reconstruction, nonlinearity, and linear tangent plane, the upper and lower models are solved to generate the corresponding configuration plan with the minimum total cost.

5. A soft switch access configuration method according to claim 4, characterized in that: Solving the upper and lower models to generate a corresponding configuration solution when the total cost is minimized includes: Randomly generate a number of particles corresponding to a group; each particle includes: the number of lines deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch; Initialize the particles of the population, obtain the historical position and historical velocity of each particle, and obtain the historical position of the population and the global fitness of the population; Repeat the following target particle determination operation until the current iteration number is the same as the preset iteration number, and output the target particles so that the output target particles all meet the line deployment constraints, soft switch configuration constraints, power balance constraints, line node voltage amplitude constraints, soft switch access line length constraints, soft switch operation constraints, and reconstruction constraints: Get the current iteration number; When the current number of iterations is less than the preset number of iterations, the local fitness of each particle in the upper model is calculated based on the particle's historical position; Generate the updated particle velocity corresponding to each particle based on the particle's historical position, particle's historical velocity, local fitness, population's historical position, and population's global fitness; Generate the updated particle position corresponding to each particle based on the particle's historical position and the population's global fitness; Generate an updated population position and an updated population global fitness based on the functional formula of the upper model, each updated particle velocity, each updated particle position, and each updated local fitness; Output the target particles corresponding to the updated population position; Adding a preset iteration increment to the current iteration number value to obtain an updated iteration number, and using the updated iteration number as the iteration number for the next target particle determination operation; The updated particle velocity is used as the particle historical velocity when the target particle determination operation is performed next time, the updated particle position is used as the particle historical position when the target particle determination operation is performed next time, the updated population position is used as the population historical position when the target particle determination operation is performed next time, and the updated population global fitness is used as the population global fitness when the target particle determination operation is performed next time.

6. A soft switch access configuration method according to claim 5, characterized in that: Each particle also corresponds to a coding matrix, which includes: ； in, is the encoding matrix used to characterize the configuration scheme corresponding to the minimum total cost, the encoding matrix The diagonal elements in the represent that the access mode of the soft switch SOP is the closed-loop access mode between feeders, and the non-diagonal elements represent that the access mode of the soft switch SOP is the inter-ring network connection access mode; Indicates the installation position of the soft switch SOP in each tie switch of the line. Indicates the installation capacity of the soft switch SOP, is the total number of tie switches.

7. A soft switch access configuration device, characterized in that: include: Data acquisition module, loss cost data generation module, planning model construction module, configuration solution solution module and soft switch configuration module; The data acquisition module is configured to acquire soft switch installation cost data, line construction cost data, and multiple typical daily scenario load curves used to characterize the power variation characteristics of distributed power sources in the distribution network throughout the year; wherein the soft switch installation cost data includes configuration cost data corresponding to different access modes; the access modes include an inter-feeder closed-loop access mode and an inter-ring network interconnection access mode; The loss cost data generation module is configured to generate loss cost data based on the soft switch installation cost data and the load data in each typical daily scenario load curve; wherein the loss cost data includes: line loss cost data, soft switch operation loss cost data, and distributed power generation curtailment penalty cost data; The planning model construction module is configured to construct a planning model for characterizing the coordinated planning of soft switches and lines based on the soft switch installation cost data, the line construction cost data, and the loss cost data; wherein the constraints corresponding to the planning model include: line deployment constraints, soft switch configuration constraints, and power balance constraints; The configuration solution solving module is used to solve the planning model under various constraints and generate a corresponding configuration solution when the total cost is minimized; wherein the configuration solution includes: the number of lines to be deployed, the soft switch access mode corresponding to each line, the installation location of the soft switch, and the installation capacity of each soft switch; The soft switch configuration module is used to deploy the lines of the distribution network and configure the access of the soft switches according to the configuration scheme; The planning model includes: an upper layer model and a lower layer model; the loss cost data also includes: soft switching loss penalty cost data; The objective function corresponding to the planning model is: ； in, is the total cost corresponding to the planning model, For the upper model, For the lower model; is the preset penalty coefficient; The functional formula of the upper model is: ； ； ； ； in, is the cost value corresponding to the minimum soft switch installation cost, line construction cost and total loss cost, is the line construction cost, is the soft switch installation cost, The total loss cost corresponding to line loss cost, soft switch operation loss cost and distributed generation power curtailment penalty cost; α represents the investment cost per unit length of trunk line; represents the preset first-year discount rate; is the service life of the line; represents the length of the jth trunk line of the i-th substation; is the total number of substations; is the number of trunk lines corresponding to the i-th substation; is the investment cost per unit length of branch line; is the length of the qth branch line carried by the kth trunk line; is the total number of branch lines carried by the i-th trunk line; The construction cost per unit length of pipes; is the length of the corridor to be occupied; The length of the cable installed in the conduit; is the construction cost per unit length of cable; is the annual inspection and maintenance cost of the corridor; is the preset discount rate for the second year; is the service life of the soft switching SOP; is the unit capacity investment cost of the soft switching SOP; is the installation capacity of the soft switch SOP; is the unit capacity maintenance cost of the soft switching SOP; is the number of soft switch SOPs installed; is the number of ports of the soft switch SOP; is the probability of occurrence of the typical day scenario load curve; is the preset loss cost coefficient; Used to represent the line loss cost calculated through multiple typical daily scenario load curves; is the soft switching operation loss cost; is the penalty coefficient for power curtailment of distributed generation; is the penalty cost for power curtailment of distributed generation; It is a collection of typical daily scenario load curves; The functional formula of the lower layer model is: ； in, represents the soft switching loss penalty cost, is the soft switching SOP at time t Active power loss of the port, is the square of the current amplitude of branch ij, is the resistance of the ij branch, is a collection of lines, is the time collection; The soft switch configuration constraints include: ； ； in, It is a 0-1 variable, indicating the soft switch access mode; Indicates the soft switch access mode The corresponding access location, It is used to indicate that only one soft switch access mode can be used at the same time at the same line node; is for the preset parameters, is a preset positive number; Refers to the position where the soft switch is installed. lines, Refers to the total installed capacity of the soft switch, This is the unit installation capacity of the soft switch SOP.

8. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for configuring soft switch access according to any one of claims 1 to 6 is implemented.

9. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is executed, the device where the storage medium is located is controlled to execute the soft switch access configuration method according to any one of claims 1 to 6.

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