Flexible soft switch configuration method considering extreme weather risk and related equipment

Abstract

The invention discloses a flexible soft switch configuration method considering extreme weather risk and related equipment, and the method comprises the steps: obtaining historical weather data which comprises extreme weather data; a typical scene set is generated based on historical weather data, the typical scene set is a set of scenes in which power distribution network branches have faults, and objective functions of a flexible soft switch optimization configuration model are established, including soft switch investment cost, power distribution network operation cost and extreme weather risk cost; establishing constraint conditions including a power flow constraint, a distribution network security constraint, a network reconstruction constraint, a flexible soft switching operation constraint, a distributed power supply operation constraint and a main network transmission power constraint; and inputting the typical scene set into the flexible soft switch optimal configuration model, and solving to obtain a configuration scheme of the flexible soft switch which meets the constraint condition and has the minimum value of the target function. The configuration scheme of the soft switch can meet the fault recovery requirements in most scenes, and prevents extreme weather events from severely affecting the power distribution network.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution network maintenance, and in particular to a flexible soft switch configuration method and related equipment taking extreme weather risks into consideration. Background Art

[0002] A flexible soft switch is a typical power electronic device that is often installed on the interconnection line of a distribution system. Compared with traditional interconnection switches, a flexible soft switch can achieve accurate and continuous regulation of power and voltage. Under normal operating conditions, soft switches help balance the load between feeders, improve node voltage conditions, and reduce network active power losses; when a fault occurs, soft switches can isolate the fault area and transfer the load. In addition, soft switches have voltage support capabilities and can achieve rapid power supply restoration by establishing autonomous areas. During the fault recovery process, soft switches are often coordinated with distributed power sources, distribution network reconstruction and other means to improve the resilience of the distribution network.

[0003] High-impact, low-probability extreme weather events can wreak havoc on power systems, leading to major blackouts and economic losses. Existing flexible soft-switch configuration technologies do not comprehensively consider distribution network failures caused by extreme weather risks. Summary of the invention

[0004] The present invention provides a flexible soft switch configuration method taking extreme weather risks into consideration, so as to solve the problem in the prior art that it is difficult to quickly recover after a distribution network failure caused by extreme weather risks.

[0005] In a first aspect, the present invention provides a flexible soft switch configuration method considering extreme weather risks, comprising:

[0006] Acquiring historical weather data, wherein the historical weather data includes extreme weather data;

[0007] Generate a typical scenario set based on the historical weather data, where the typical scenario set is a collection of scenarios in which a distribution network branch fails;

[0008] Establishing an objective function of the flexible soft switch optimization configuration model, wherein the objective function includes soft switch investment cost, distribution network operation cost and extreme weather risk cost;

[0009] Establishing constraint conditions of the flexible soft switch optimization configuration model, wherein the constraint conditions include power flow constraint, distribution network security constraint, network reconstruction constraint, flexible soft switch operation constraint, distributed power supply operation constraint and main network transmission power constraint;

[0010] The typical scenario set is input into the flexible soft switch optimization configuration model to solve the flexible soft switch configuration scheme that satisfies the constraint conditions and minimizes the value of the objective function.

[0011] In a second aspect, the present invention provides a flexible soft switch configuration system considering extreme weather risks, comprising:

[0012] A data acquisition module, used to acquire historical weather data, wherein the historical weather data includes extreme weather data;

[0013] A typical scenario set generation module, used to generate a typical scenario set based on the historical weather data, wherein the typical scenario set is a collection of scenarios in which a distribution network branch fails;

[0014] An objective function building module is used to establish an objective function of the flexible soft switch optimization configuration model, wherein the objective function includes soft switch investment cost, distribution network operation cost and extreme weather risk cost;

[0015] A constraint condition establishment module is used to establish the constraint conditions of the flexible soft switch optimization configuration model, wherein the constraint conditions include power flow constraint, distribution network security constraint, network reconstruction constraint, flexible soft switch operation constraint, distributed power supply operation constraint and main network transmission power constraint;

[0016] The configuration scheme generating module is used to input the typical scenario set into the flexible soft switch optimization configuration model to solve the configuration scheme of the flexible soft switch that satisfies the constraint conditions and minimizes the value of the objective function.

[0017] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the flexible soft switch configuration method considering extreme weather risks described in the first aspect of the present invention.

[0021] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a processor to implement the flexible soft switch configuration method considering extreme weather risks described in the first aspect of the present invention when executed.

[0022] The embodiment of the present invention provides a flexible soft switch configuration method considering extreme weather risks, which obtains historical weather data, including extreme weather data; generates a typical scenario set based on the historical weather data, which is a set of scenarios where a distribution network branch fails, establishes an objective function of a flexible soft switch optimization configuration model, and the objective function includes soft switch investment cost, distribution network operation cost and extreme weather risk cost; establishes constraints for the flexible soft switch optimization configuration model, and the constraints include flow constraints, distribution network safety constraints, network reconstruction constraints, flexible soft switch operation constraints, distributed power supply operation constraints and main network transmission power constraints; inputs the typical scenario set into the flexible soft switch optimization configuration model, and solves the configuration scheme of the flexible soft switch that satisfies the constraints and minimizes the value of the objective function. The configuration scheme of the flexible soft switch finally obtained can meet the constraints, minimize the total cost, and meet the fault recovery requirements in most scenarios (including extreme weather), reduce the major power outages and economic losses caused by high-impact, low-probability extreme weather events, and the soft switch configuration can quickly realize the distribution network fault recovery.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of a flexible soft switch configuration method considering extreme weather risks provided by an embodiment of the present invention;

[0026] Figure 2 is a structural schematic diagram of a flexible soft switch configuration system considering extreme weather risks provided by an embodiment of the present invention;

[0027] Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] Figure 1 A flowchart of a flexible soft switch configuration method considering extreme weather risks is provided in an embodiment of the present invention. This embodiment is applicable to the situation of configuring flexible soft switches for different weather conditions. The method can be executed by a flexible soft switch configuration system considering extreme weather risks. The device can be implemented in the form of hardware and / or software, and the device can be configured in an electronic device.

[0030] like Figure 1 As shown, the flexible soft switch configuration method considering extreme weather risks includes:

[0031] S100: Acquire historical weather data, where the historical weather data includes extreme weather data.

[0032] Historical weather data is usually stored in the management platform of the distribution network, and the historical weather data can be obtained from the management platform. Weather data may include time, weather type, weather intensity, etc., wherein, for weather intensity, for example, when the weather type is a typhoon, the weather intensity is expressed by wind speed, and when the weather type is a rainstorm, the weather intensity is expressed by precipitation. Extreme weather data refers to low-probability, high-impact weather events, such as typhoons, rainstorms, blizzards, etc., which are usually prone to cause distribution network failures. Therefore, when the present invention configures and plans the flexible soft switch, it focuses on extreme weather data to ensure that the configuration scheme of the flexible soft switch can adapt to different extreme weather conditions.

[0033] S200. Generate a typical scenario set based on historical weather data, where the typical scenario set is a collection of scenarios in which a distribution network branch fails.

[0034] Historical weather data generates a typical scenario set. Specifically, the historical weather data can be clustered to obtain multiple scenarios, and the probability of failure of the distribution network branch in each scenario is calculated, and the scenarios with probabilities greater than the set probability threshold are taken as subsets of the typical scenario set.

[0035] In an optional embodiment, the historical weather data includes weather intensity, and generating a typical scene set based on the historical weather data includes the following steps:

[0036] S21, processing the weather parameters in the historical weather data by a non-parametric kernel density estimation method to obtain probability distribution functions of different scenarios, where the weather intensity of different scenarios is different;

[0037] S22. Determine the probability P of a distribution network branch failing in different scenarios fail (v), and obtain the vulnerability curve of the distribution network branch:

[0038]

[0039] Among them, P nm is the inherent probability of damage under normal weather conditions, w cr 、w co are the turning strength and collapse strength, P hw(w) is a function that reflects the characteristic that the probability of failure increases with the weather intensity w, that is, the greater the weather intensity, the greater the probability of failure P in scenario ω fail (v)The larger.

[0040] S23. Perform Monte Carlo sampling on the distribution network branches according to the probability distribution function and the distribution line vulnerability curve to obtain a set of faulty branches:

[0041]

[0042] in, is the set of branches where the fault occurs, is the connectivity status of branch (i, j) under scenario ω, P ij,ω is a random number in the range [0,1] obtained by sampling, w ij Indicates the weather intensity corresponding to the sampled branch (i, j).

[0043] When sampling, the weather intensity w corresponding to the scene ω and branch (i, j) is obtained ij , calculate the failure probability P fail (w ij ), generate a random number P in the range [0,1] ij,ω If P ij,ω Less than P fail (w ij ), then the branch (i, j) is considered to have a fault. That is, the connectivity state of the branch (i, j) is disconnected.

[0044] S24. The set of scenarios corresponding to the set of branches where failures occur is taken as a typical scenario set.

[0045] That is, to obtain the scenario when all distribution network branches fail.

[0046] In an optional embodiment, after generating a distribution network failure scenario set based on the historical weather data, it also includes: reducing the number of scenarios in the typical scenario set through a hierarchical clustering method, and the features used for clustering include the status of each branch, the number of islands formed, and the number of isolated nodes.

[0047] Considering that the number of scenarios in the generated scenario set is large, the algorithm and time complexity of the configuration model containing these scenarios are high, and it is difficult to solve the optimal solution within a limited time. Therefore, the number of scenarios can be reduced by the hierarchical clustering method, and then the various types of centers are obtained based on the Euclidean distance calculation to form a typical distribution network failure scenario set Ω under extreme weather risks. The occurrence probability p of the scenario ω is calculated according to the number of samples in the class. ω .

[0048] S300, establishing an objective function of a flexible soft switch optimization configuration model.

[0049] The purpose of opening the flexible soft switch is to reduce the probability of occurrence of all scenarios ω in the typical scenario set Ω. In order to configure the soft switch on the basis of reducing costs, the objective function of the embodiment of the present invention includes the soft switch investment cost, the distribution network operation cost and the extreme weather risk cost. When planning the flexible soft switch optimization configuration plan, the soft switch investment cost, the distribution network operation cost and the extreme weather risk cost can be reduced.

[0050] In an optional embodiment, the objective function expression is:

[0051]

[0052] Among them, C inv is the soft switching investment cost, is the distribution network operating cost, For extreme weather

[0053] Risk cost, μ is the risk aversion coefficient, μ∈[0,1]; E[.] is the expected value operator; μ represents the risk aversion tendency of the configuration scheme. A value of μ close to 1 indicates that the configuration scheme focuses on avoiding extreme weather risks, and a value of μ close to 0 indicates that the configuration scheme focuses on avoiding normal operating cost risks, that is, saving operating costs in all scenarios.

[0054] QUR α is the risk value of conditions related to extreme weather events, representing the first 100(1-α)% of the scenarios The expectation is expressed as:

[0055]

[0056] Among them, α is the confidence level, η is the slack variable, pω is the probability of occurrence of scenario ω.

[0057] In an optional embodiment, the soft switch investment cost C inv The expression is:

[0058]

[0059] Among them, B sop is the set of candidate construction locations for the flexible soft switch, Indicates whether to invest in the soft switch on branch (i, j), Continuous variables is the investment capacity of the branch (i, j) where the flexible soft switch is located, are the fixed investment cost and variable investment cost of the branch (i, j) where the flexible soft switch is located; π crf is the capital recovery factor;

[0060]

[0061] Among them, r is the discount rate, T is the planning period, and m is the maintenance cost coefficient;

[0062] Distribution network operating costs Including the distributed power generation cost and the main grid power purchase cost, the expression is:

[0063]

[0064] Among them, N dg 、N mg are the set of nodes where distributed generation is located and the set of transformer nodes respectively. are the active power generated by the distributed generation at node i and the active power transmitted by the main grid under scenario ω, is the unit power generation cost of the distributed generation at node i, is the main grid electricity purchase cost under the scenario;

[0065] Extreme weather risk costs The expression is:

[0066]

[0067] in, w i are the active load and weight of node i, R ij ,I ij，ω are the resistance and current of branch (i, j), π ls is the load loss cost caused by the failure, π nl is the network loss cost, λ i,ω is the load recovery rate of node i.

[0068] S400. Establish constraint conditions for a flexible soft switch optimization configuration model.

[0069] There may be multiple configuration schemes for the flexible soft switch optimization configuration, but in order to ensure the safe and normal operation of the distribution network, the basic requirements for the distribution network operation must be met, so it is necessary to set constraints on the flexible soft switch optimization configuration model. Constraints include power flow constraints, distribution network safety constraints, network reconstruction constraints, flexible soft switch operation constraints, distributed power supply operation constraints, and main network transmission power constraints, which can make the configuration scheme output by the configuration model feasible.

[0070] In an optional embodiment, the expression of the power flow constraint is:

[0071]

[0072] a ij,ω ∈{0,1}; 0≤λ i,ω ≤1;

[0073] Among them, P ij,ω , Q ij,ω are the active power and reactive power of branch (i, j), P ji,ω , Q ji,ω ,I ji,ω are the active power, reactive power and current of branch (j,i), P i,ω , Q i,ω are the active power and reactive power injected into node i, respectively, X ij is the reactance of branch (i,j), are the active power and reactive power injected by the flexible soft switch at node i, is the reactive load of node i, λ i,ω is the load recovery rate of node i, U i,ω , U j,ω are the voltage amplitudes of nodes i and j respectively, a ij,ω is the connectivity status of branch (i, j) after network reconstruction, M is a sufficiently large integer, R ij ,I ij，w are the resistance and current of branch (i, j) respectively, are the active power generated by the distributed generation at node i and the active power transmitted by the main grid respectively; ω represents the scenario; among them, the distributed generation is connected to the node.

[0074] The expression of the distribution network security constraint is:

[0075]

[0076] -a ij,ω M≤Pij,ω ,Q ij,ω ≤a ij,ω M;

[0077] Among them, U max , U min are the upper and lower limits of the node voltage, I max The upper limit of branch current;

[0078] The expression of the network reconstruction constraint is:

[0079] ∑ (i,j)∈B a ij,ω =|N|-∑ i∈N z i,ω ;

[0080] a ij,ω =b ij,ω +b ji,ω ,

[0081] ∑ (i,j)∈B b ij,ω =1-z i,ω ,

[0082]

[0083] a ij,ω =0,

[0084] z i,ω ,b ij,ω ,b ji,ω ∈{0,1};

[0085] Among them, z i,ω Indicates whether node i acts as a root node, b ij,ω Indicates whether the direction of the branch (i, j) is from node i to node j, b ji,ω Indicates whether the direction of the branch (j, i) is from node j to node i, N dg 、N mg 、N sop They are the set of nodes where distributed power sources are located, the set of transformer nodes, and the set of nodes where flexible soft switches are installed. is the set of branches where faults occur;

[0086] The expression of the flexible soft switch operation constraint is:

[0087]

[0088] z i,ω +z j,ω ≤1,

[0089]

[0090] in, are the upper and lower limits of the flexible soft switch investment construction capacity, respectively. are the loss rates of soft switches at nodes i and j respectively; ||.|| 2 is the 2-norm operator.

[0091] The expression of the distributed power supply operation constraint is:

[0092]

[0093] in, is the upper limit of the active output of the distributed generation at node i, are the upper and lower limits of the reactive power output of distributed generation at node i, is the power factor angle of the distributed generation at node i;

[0094] The expression of the main network transmission power constraint is:

[0095]

[0096] in, They are respectively the upper limits of active power and reactive power input from the main grid.

[0097] S500: Input the typical scenario set into the flexible soft switch optimization configuration model to solve the flexible soft switch configuration scheme that satisfies the constraint conditions and minimizes the value of the objective function.

[0098] The flexible soft switch optimization configuration model is solved by using a mixed integer second-order cone programming method and a preset solver, and can be specifically solved by commercial optimization solvers such as GUROBI and MOSEK.

[0099] After obtaining the configuration plan of the flexible soft switch, the flexible soft switch can be installed in the distribution network based on the configuration plan. When the distribution network encounters a fault, regardless of whether the fault is caused by extreme weather, the installed flexible soft switch can be used to reduce the economic losses during major power outages and improve the resilience of the distribution network.

[0100] The embodiment of the present invention provides a flexible soft switch configuration method considering extreme weather risks, which obtains historical weather data, including extreme weather data; generates a typical scenario set based on the historical weather data, which is a set of scenarios where a distribution network branch fails, establishes an objective function of a flexible soft switch optimization configuration model, and the objective function includes soft switch investment cost, distribution network operation cost and extreme weather risk cost; establishes constraints for the flexible soft switch optimization configuration model, and the constraints include flow constraints, distribution network safety constraints, network reconstruction constraints, flexible soft switch operation constraints, distributed power supply operation constraints and main network transmission power constraints; inputs the typical scenario set into the flexible soft switch optimization configuration model to obtain a configuration scheme of the flexible soft switch that satisfies the constraints and minimizes the value of the objective function. The configuration scheme of the flexible soft switch finally obtained can satisfy the constraints, minimize the total cost, and meet the fault recovery requirements in most scenarios (including extreme weather), reduce the serious damage to the power system caused by high-impact, low-probability extreme weather events, and reduce major power outages and economic losses.

[0101] Corresponding to the flexible soft switch configuration method considering extreme weather risks of the present invention, the present invention also provides a flexible soft switch configuration system considering extreme weather risks. Figure 2 The following is a schematic diagram of a flexible soft switch configuration system considering extreme weather risks provided by an embodiment of the present invention. Figure 2 As shown, the flexible soft switch configuration system considering extreme weather risks includes:

[0102] A data acquisition module 201 is used to acquire historical weather data, wherein the historical weather data includes extreme weather data;

[0103] A typical scenario set generation module 202, used to generate a typical scenario set based on the historical weather data, wherein the typical scenario set is a collection of scenarios in which a distribution network branch fails;

[0104] An objective function building module 203 is used to establish an objective function of the flexible soft switch optimization configuration model, wherein the objective function includes soft switch investment cost, distribution network operation cost and extreme weather risk cost;

[0105] A constraint condition establishment module 204 is used to establish the constraint conditions of the flexible soft switch optimization configuration model, wherein the constraint conditions include power flow constraint, distribution network security constraint, network reconstruction constraint, flexible soft switch operation constraint, distributed power supply operation constraint and main network transmission power constraint;

[0106] The configuration scheme generating module 205 is used to input the typical scenario set into the flexible soft switch optimization configuration model to solve and obtain a configuration scheme of the flexible soft switch that satisfies the constraint conditions and minimizes the value of the objective function.

[0107] The flexible soft switch configuration system considering extreme weather risks provided by the embodiment of the present invention can execute the flexible soft switch configuration method considering extreme weather risks provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0108] Figure 3 A schematic diagram of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0109] like Figure 3 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0110] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0111] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as a flexible soft switch configuration method considering extreme weather risks.

[0112] In some embodiments, the flexible soft switch configuration method considering extreme weather risks may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the flexible soft switch configuration method considering extreme weather risks described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to execute the flexible soft switch configuration method considering extreme weather risks in any other appropriate manner (e.g., by means of firmware).

[0113] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0114] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0115] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0116] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0117] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0118] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0119] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0120] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A flexible soft switch configuration method considering extreme weather risks, characterized in that: include: Acquiring historical weather data, wherein the historical weather data includes extreme weather data; Generate a typical scenario set based on the historical weather data, where the typical scenario set is a collection of scenarios in which a distribution network branch fails; Establishing an objective function of the flexible soft switch optimization configuration model, wherein the objective function includes soft switch investment cost, distribution network operation cost and extreme weather risk cost; Establishing constraint conditions of the flexible soft switch optimization configuration model, wherein the constraint conditions include power flow constraint, distribution network security constraint, network reconstruction constraint, flexible soft switch operation constraint, distributed power supply operation constraint and main network transmission power constraint; The typical scenario set is input into the flexible soft switch optimization configuration model to solve the flexible soft switch configuration scheme that satisfies the constraint conditions and minimizes the value of the objective function.

2. The method according to claim 1, characterized in that The historical weather data includes weather intensity, and generating a typical scene set based on the historical weather data includes: Processing weather parameters in the historical weather data by a nonparametric kernel density estimation method to obtain probability distribution functions of different scenarios, where the weather intensities of different scenarios are different; Determine the probability P of a distribution network branch failing under different scenarios fail (v), and obtain the vulnerability curve of the distribution network branch: Among them, P nm is the inherent probability of damage under normal weather conditions, w cr 、w co are the turning strength and collapse strength, P hw(w) is a function that reflects the characteristic that the probability of failure increases with the weather intensity w; Performing Monte Carlo sampling on distribution network branches according to the probability distribution function and the distribution line vulnerability curve to obtain a set of faulty branches; in, is the set of branches where the fault occurs, is the connectivity status of branch (i, j) under scenario ω, P ij,ω is a random number in the range of [0, 1] obtained by sampling, w ij Indicates the weather intensity corresponding to the sampled branch (i, j); The set of scenarios corresponding to the set of branches where faults occur is taken as a typical scenario set.

3. The method according to claim 1, characterized in that After generating a typical scenario set of distribution network failure based on the historical weather data, the method further includes: The number of scenes in the typical scene set is reduced by a hierarchical clustering method, and the features used for clustering include the state of each branch, the number of isolated islands formed, and the number of isolated nodes.

4. The method according to claim 1, characterized in that The objective function expression is: Among them, C inv is the soft switching investment cost, is the distribution network operating cost, is the extreme weather risk cost, μ is the risk aversion coefficient, μ∈[0,1]; E[.] is the expected value operator; QUR α is the risk value of conditions related to extreme weather events, representing the first 100(1-α)% of the scenarios The expectation is expressed as: Among them, α is the confidence level, η is the slack variable, p ω is the probability of occurrence of scenario ω.

5. The method according to claim 4, characterized in that Soft switching investment cost C inv The expression is: Among them, B sop is the set of candidate construction locations for the flexible soft switch, Indicates whether to invest in the soft switch on branch (i, j), Continuous variables is the investment capacity of the branch (i, j) where the flexible soft switch is located, are the fixed investment cost and variable investment cost of the branch (i, j) where the flexible soft switch is located; π crf is the capital recovery factor; Among them, r is the discount rate, T is the planning period, and m is the maintenance cost coefficient; Distribution network operating costs Including the distributed power generation cost and the main grid power purchase cost, the expression is: Among them, N dg 、N mg are the set of nodes where distributed generation is located and the set of transformer nodes respectively. are respectively the active power generated by the distributed generation at node i and the active power transmitted by the main grid under scenario ω. is the unit power generation cost of the distributed generation at node i, is the main grid electricity purchase cost under the scenario; Cost of extreme weather risk The expression is: in, w i are the active load and weight of node i, R ij ,I ij，ω are the resistance and current of branch (i, j), π ls is the load loss cost caused by the failure, π nl is the network loss cost, λ i,ω is the load recovery rate of node i.

6. The method according to any one of claims 1 to 2, characterized in that: The expression of the power flow constraint is: a ij,ω ∈{0,1};0≤λ i,ω ≤1; Among them, P ij,ω , Q ij,ω are the active power and reactive power of branch (i, j), P ji,ω , Q ji,ω ,I ji,ω are the active power, reactive power and current of branch (j,i), P i,ω , Q i,ω are the active power and reactive power injected into node i, respectively, X ij is the reactance of branch (i,j), are the active power and reactive power injected by the flexible soft switch at node i, is the reactive load of node i, λ i,ω is the load recovery rate of node i, U i,ω , U j,ω are the voltage amplitudes of nodes i and j respectively, a ij,ω is the connectivity status of branch (i, j) after network reconstruction, M is a sufficiently large integer, R ij ,I ij，ω are the resistance and current of branch (i, j) respectively, are the active power generated by the distributed generation at node i and the active power transmitted by the main grid; ω represents the scenario; The expression of the distribution network security constraint is: -a ij,ω M≤P ij,ω ,Q ij,ω ≤a ij,ω M; Among them, U max , U min are the upper and lower limits of the node voltage, I max The upper limit of branch current; The expression of the network reconstruction constraint is: Among them, z i,ω Indicates whether node i acts as a root node, b ij,ω Indicates whether the direction of the branch (i, j) is from node i to node j, b ji,ω Indicates whether the direction of the branch (j, i) is from node j to node i, N dg 、N mg 、N sop They are the set of nodes where distributed power sources are located, the set of transformer nodes, and the set of nodes where flexible soft switches are installed. is the set of branches where faults occur; The expression of the flexible soft switch operation constraint is: in, are the upper and lower limits of the flexible soft switch investment construction capacity, respectively. are the loss rates of soft switches at nodes i and j respectively; The expression of the distributed power supply operation constraint is: in, is the upper limit of the active output of the distributed generation at node i, are the upper and lower limits of the reactive power output of distributed generation at node i, is the power factor angle of the distributed generation at node i; The expression of the main network transmission power constraint is: in, They are respectively the upper limits of active power and reactive power input from the main grid.

7. The method according to any one of claims 1 to 6, characterized in that: The flexible soft switch optimization configuration model is solved by using a mixed integer second-order cone programming method and a preset solver.

8. A flexible soft switch configuration system considering extreme weather risks, characterized in that: include: A data acquisition module, used to acquire historical weather data, wherein the historical weather data includes extreme weather data; A typical scenario set generation module, used to generate a typical scenario set based on the historical weather data, wherein the typical scenario set is a collection of scenarios in which a distribution network branch fails; An objective function building module is used to establish an objective function of the flexible soft switch optimization configuration model, wherein the objective function includes soft switch investment cost, distribution network operation cost and extreme weather risk cost; A constraint condition establishment module is used to establish the constraint conditions of the flexible soft switch optimization configuration model, wherein the constraint conditions include power flow constraint, distribution network security constraint, network reconstruction constraint, flexible soft switch operation constraint, distributed power supply operation constraint and main network transmission power constraint; The configuration scheme generating module is used to input the typical scenario set into the flexible soft switch optimization configuration model to solve the configuration scheme of the flexible soft switch that satisfies the constraint conditions and minimizes the value of the objective function.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the flexible soft switch configuration method considering extreme weather risks described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the flexible soft switch configuration method considering extreme weather risks according to any one of claims 1 to 7 when executed.

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