Toughness evaluation method and system for emergency power supply response of power transmission network under extreme strong wind

Abstract

The invention discloses a power transmission network emergency power supply response toughness evaluation method and system under extreme strong wind. The fault probability of each line of a power transmission network is calculated based on to-be-evaluated power transmission network data; generating a probability fault scene; constructing an optimized mathematical model under the power transmission network fault scene according to the power transmission network rack and the data information in combination with the generated probability fault scene; and solving the optimized mathematical model in the power transmission network fault scene to obtain an expected load shedding of the power transmission network, and evaluating the toughness of the disaster area power system based on the expected load shedding. The power transmission element vulnerability model under the disaster is established, a power transmission system fault scene under the strong wind disaster is established through a sampling method, and the toughness index of the system under the disaster is evaluated, so that decision suggestions are provided for toughness improvement measures of a power system.

Description

Background Art

[0002] As the global climate warms, the frequency and intensity of extreme weather such as strong winds have increased. Power system lines and towers are greatly affected by wind speed. The probability of line breakage and tower collapse under extremely strong winds is greatly increased, which may cause large-scale power outages and pose a serious threat to the safe operation of the power system. In this context, the concept of "resilience" is introduced to describe the ability of the power grid to resist and prevent extreme disasters and restore power supply after disasters.

[0003] At present, the research on power system resilience mainly focuses on the impact of extreme events such as typhoons and rainstorms on the resilience of distribution networks. The concept of "resilience trapezoid" is proposed to describe the resilience level of distribution networks under extreme weather conditions, and a set of resilience assessment indicators is established to measure the degree of damage and recovery time of distribution networks under disasters. As the end of the power system, the distribution network has poor stability and a high probability of failure. Therefore, the resilience assessment is mainly carried out around the distribution network. Compared with the distribution network, the transmission network is more stable, and there are fewer devices that fail in the face of extreme events. Therefore, there are fewer studies on the resilience of the transmission network. However, it should be noted that the low probability of transmission network failure is also accompanied by a larger scale of power outages when failures occur, which has a more far-reaching impact on the overall power supply of the power system and may lead to longer emergency repair and failure recovery time.

[0004] In terms of improving the resilience of the power system, the main considerations are to improve the design standards of components from the design level and to carry out preventive reinforcement and resource deployment before disasters occur. Due to the large number of pole and line components in the power system, the cost of upgrading all existing components to improve the disaster resistance of the components is high and difficult to achieve economically; and the cost of reinforcing all components or deploying power generation resources at all nodes before a disaster is also high. At the same time, the number of reinforcement workers is limited and the reinforcement takes a long time. It is probably difficult to complete before a disaster occurs. Therefore, a reinforcement strategy that balances investment economy and disaster prevention level is needed. By evaluating the resilience of the power grid, the weak links of the power grid can be obtained, so that the power grid can be reinforced in a targeted manner. Considering that emergency mobile power supplies are currently widely used in power system emergency response, maintaining short-term power supply, and reducing the load of the power system, it is necessary to consider the effect of emergency power supplies on improving resilience when evaluating the resilience of the power grid.

[0005] In the statistics of power system faults, faults caused by extreme strong winds account for a large proportion. In order to support the improvement of the disaster prevention capabilities of the power system, the present invention studies the vulnerability of components in the transmission network under extreme strong wind disasters, and proposes a transmission network resilience assessment method considering emergency power response scheduling under extreme strong winds. The optimal scheduling plan for emergency resources and the system load shedding situation are obtained, and the vulnerable components in the disaster scenario are explored, and targeted reinforcement suggestions are made. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a resilience assessment method and system for emergency power supply response of a transmission network under extreme strong winds in response to the above-mentioned deficiencies in the prior art, so as to solve the technical problem that emergency power supply scheduling affects the resilience level of the transmission network under the resilience assessment framework.

[0007] The present invention adopts the following technical solutions: A method for evaluating the resilience of emergency power supply response of a transmission network under extreme gale conditions comprises the following steps: Calculating the failure probability of each line of the transmission network based on the transmission network data to be evaluated; Generate probabilistic failure scenarios; According to the transmission network grid and data information, combined with the generated probabilistic fault scenarios, an optimized mathematical model under the transmission network fault scenario is constructed; Solve the optimization mathematical model under the transmission network failure scenario to obtain the expected load shedding of the transmission network, and evaluate the resilience of the power system in the disaster area based on the expected load shedding.

[0008] Preferably, the transmission network data to be evaluated includes: System grid topology , node set , power node collection , non-power node set , each node load , the upper and lower limits of the power node output power , ; Line collection , the impedance of each line and and line capacity ; The local wind speed to be calculated, including the wind speed at each tower of the line , wind speed of the conductor section between the two towers ; Enter the design wind speed for the tower and conductor segment and , and the length of the wire segment ; Input the emergency mobile power supply set , output power upper and lower limits , ; Transmission Network Node Index , ; Line Index , ; Emergency Power Supply Index , ; Fault scenario index , .

[0009] Preferably, the transmission line is composed of multiple transmission towers and conductors connected in series, and the failure probability of the transmission line is calculated as follows:

[0010] in, For transmission lines The failure rate, is the number of transmission towers on the line, is the number of conductor segments of the line, For transmission lines On The failure rate of transmission towers, For transmission lines On The failure rate of a conductor segment.

[0011] Preferably, the failure rate of a single transmission tower The calculation is as follows:

[0012] in, It is the failure probability curve model of transmission tower.

[0013] Preferably, the failure rate of the conductor section between two transmission towers is The calculation is as follows:

[0014] in, is the fault probability model of the conductor segment.

[0015] Preferably, the failure probability curve model of the transmission tower Fault probability model of conductor segments for:

[0016]

[0017] in, For line Previous The real-time wind speed of the tower, is the model coefficient, is the design wind speed for each tower, For line Previous The wind speed of the conductor segment, is the design wind speed of the line segment, Wire segment length.

[0018] Preferably, define a binary variable Indicates the status of the line in extremely windy weather. Indicates that the line is in normal operation. Indicates that the line is in a failed state, and the interval is randomly generated according to the Monte Carlo simulation method A random number that follows a uniform distribution , generate a large number of fault scenarios through random sampling and build a set of fault scenarios .

[0019] Preferably, the objective function of the optimization mathematical model in the transmission network failure scenario is:

[0020] in, Represents the set of all scenes; Represents the set of all nodes in the transmission network; For failure scenarios The node below of load shedding.

[0021] Preferably, the constraints of the optimization mathematical model under the transmission network failure scenario are as follows: Power balance constraints

[0022]

[0023]

[0024] in, For the scene Down Line The trend, For the scene Next Node The output power, For Node The load demand, It is a collection of transmission network lines; Power flow constraints

[0025] in, For Node The phase angle, Indicates line The reactance, For Node The phase angle, is a sufficiently large coefficient, It is a 0-1 variable, indicating the line Whether it is in a fault state; Emergency power dispatch constraints

[0026]

[0027] in, A 0-1 variable indicating emergency power supply Whether to connect to the node superior, For failure scenarios Emergency power supply The output power, For emergency power supply The lower limit of output power is For emergency power supply The output power limit of Node output power constraints:

[0028] The range of node power output power is limited as follows:

[0029] Output power of non-power nodes:

[0030] in, is the power output power of the power node, is the lower limit of the output power of the power node, is the output power upper limit of the power node, A collection of power supply nodes.

[0031] In a second aspect, an embodiment of the present invention provides a resilience assessment system for emergency power supply response of a power transmission network under extreme gale conditions, comprising: A calculation module, which calculates the failure probability of each line of the transmission network based on the transmission network data to be evaluated; Scenario module, generates probabilistic failure scenarios; The optimization module builds an optimization mathematical model under the transmission network failure scenario based on the transmission network grid and data information and the generated probabilistic failure scenario; The evaluation module solves the optimization mathematical model under the transmission network failure scenario, obtains the expected load shedding of the transmission network, and evaluates the resilience of the power system in the disaster area based on the expected load shedding.

[0032] In a third aspect, a computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for resilience assessment of emergency power supply response of a transmission network under extreme wind conditions when executing the computer program.

[0033] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for resilience assessment of emergency power supply response of a power transmission network under extreme winds.

[0034] In a fifth aspect, a chip comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the above-mentioned method for resilience assessment of emergency power supply response of a power transmission network under extreme wind conditions are implemented.

[0035] In a sixth aspect, an embodiment of the present invention provides an electronic device, including a computer program, which, when executed by the electronic device, implements the steps of the above-mentioned method for resilience assessment of emergency power supply response of a power transmission network under extreme winds.

[0036] Compared with the prior art, the present invention has at least the following beneficial effects: A resilience assessment method for the emergency power supply response of a transmission network under extreme strong winds provides reference suggestions for the decision-making of wind-proof measures for power systems, so that power system components can be reinforced in a more targeted manner to achieve a balance between economic costs and improved disaster resilience. First, under extreme strong wind disasters, the vulnerability modeling of transmission line towers and components is carried out. According to the vulnerability curve, a system failure scenario is generated by a random sampling method. Combined with the pre-disaster disaster prevention measures, the degree of damage caused by the disaster to the system is evaluated. According to the system failure scenario, the weak links in the system's disaster prevention may be obtained, so that they can be strengthened in a targeted manner to achieve the purpose of improving the resilience of the power system. In actual applications, technicians can evaluate the existing disaster prevention capabilities of the power system in the disaster area based on the forecast of the disaster-stricken area or the past wind speed meteorological information through the assessment method provided by the present invention, and obtain the components of the system that need to be reinforced, providing guidance and suggestions for the reinforcement sequence of electrical components in actual projects.

[0037] Furthermore, a transmission line is composed of transmission towers and conductors in series. When one of the transmission towers or a conductor segment fails, the entire line will be shut down. Therefore, the established method for calculating the failure probability of a transmission line can obtain a transmission line with a high failure probability.

[0038] Furthermore, the failure probability curve model of the transmission tower and the conductor segment can well capture the wind resistance of the transmission tower and the conductor segment under the corresponding wind speed. By establishing the failure probability curve of the transmission tower and the conductor segment, the failure probability of the transmission line can be calculated.

[0039] Furthermore, when there are a large number of transmission lines, it is challenging to calculate the expected load shedding of the entire transmission network based on the failure probability of the transmission lines. Therefore, the load loss of the transmission network is obtained by generating fault scenarios. Transmission lines have only two states: fault and normal operation. Therefore, it is necessary to use a random sampling method to generate transmission line fault scenarios. In order to make the generated fault scenarios more accurately describe the failure probability of the transmission line, a large number of fault scenarios are generated by sampling, which are recorded as a set When there are enough fault scenarios, the average system load loss calculated based on the fault scenarios is very close to the expected load shedding under the probability of transmission line failure, and can be regarded as the expected load shedding of the system within the allowable error range.

[0040] Furthermore, for the generated fault scenarios, in order to obtain the system load loss situation of the transmission network, the system load shedding under all fault scenarios is added up and divided by the number of scenarios to obtain the system average load loss of the transmission network.

[0041] Furthermore, in the case of a fault, in order to reduce the power loss of the transmission network and minimize the load shedding of the transmission network, the transmission network adjusts the line flow through flow optimization to maintain the load supply to the greatest extent. In addition, since the described transmission system contains an emergency power supply, the emergency power supply can be dispatched to the node to provide emergency power supply, so the emergency power supply dispatch constraint is used to realize the power supply of the emergency power supply in the fault scenario.

[0042] It can be understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0043] In summary, the present invention realizes the resilience assessment of the transmission network containing emergency power supply through the method of calculating the probability of transmission lines, generating fault scenarios by sampling, and establishing a fault scenario optimization model. The present invention can effectively assess the power loss of the transmission network under extreme strong winds, and can provide an emergency power supply scheduling plan under the extreme strong winds, which can provide a reference for the reinforcement of the transmission network.

[0044] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 A schematic diagram of a computer device provided by an embodiment of the present invention; Figure 3 A block diagram of a chip provided according to an embodiment of the present invention; Figure 4 FIG. 4 is a transmission line failure probability diagram according to an example of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are 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 are within the scope of protection of the present invention.

[0047] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0048] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0049] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0050] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0051] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0052] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0053] In the statistics of power system faults, faults caused by extreme strong winds account for a large proportion. In order to support the improvement of the disaster prevention capability of the power system, the present invention studies the vulnerability of components of the transmission network under extreme strong wind disasters, provides a resilience assessment method for the emergency power supply response of the transmission network under extreme strong winds, establishes a vulnerability model of transmission components under disasters, establishes a failure scenario of the transmission system under strong wind disasters through a sampling method, evaluates the resilience index of the system under the disaster, obtains the optimal scheduling plan of emergency resources and the system load shedding situation, explores the vulnerable components under the disaster scenario, and puts forward targeted reinforcement suggestions, thereby providing decision-making suggestions for measures to improve the resilience of the power system.

[0054] See also Figure 1 The present invention provides a method for evaluating the resilience of an emergency power supply response of a power transmission network under extreme gale conditions, comprising the following steps: S1. Input the transmission network data to be evaluated; The transmission network data to be evaluated includes the system grid topology , node set , power node collection , non-power node set , each node load , the upper and lower limits of the power node output power , ; Line collection , the impedance of each line and and line capacity ; The local wind speed to be calculated, including the wind speed at each tower of the line , wind speed of the conductor section between the two towers ; Enter the design wind speed for the tower and conductor segment and , and the length of the wire segment ; Input the emergency mobile power supply set , output power upper and lower limits , .

[0055] The transmission network node index is , ; The line index is , ; Emergency power supply index is , ; The fault scenario index is , .

[0056] S2. Calculate the failure probability of each line of the transmission network; The failure probability curve model of the tower is as follows: (1) in, For line Previous The real-time wind speed of the tower, is the model coefficient, set to 0.2, is the design wind speed for each tower.

[0057] The failure rate of a single transmission tower is calculated as follows: (2) The fault probability model of the conductor segment is as follows: (3) in, For line Previous The wind speed of the conductor segment, is the design wind speed of the line segment, Wire segment length.

[0058] Calculation method for the failure rate of the conductor section between two transmission towers: (4) The transmission line is a series of multiple transmission towers and conductors. Once a tower or conductor segment fails in the line, the entire line will trip. Assuming that the failures of each component are independent of each other, the failure probability of the transmission line is calculated as follows: (5) S3. Generate probabilistic failure scenarios ; Defining binary variables To indicate the status of the line in extremely windy weather. Indicates that the line is in normal operation. Indicates that the line is in a failed state.

[0059] Randomly generate intervals based on Monte Carlo simulation A random number that follows a uniform distribution , the line status is expressed as: (6) Generate a large number of fault scenarios through random sampling and build a set of fault scenarios .

[0060] S4, constructing an optimized mathematical model under the transmission network failure scenario based on the transmission network grid and data information and the probabilistic failure scenario generated in step S3; 1) Objective function The goal of optimizing the resilience of the power grid under extreme winds is to minimize the expected load shedding under disasters through power flow optimization and emergency power dispatch; the objective function is as follows: (7) in, Represents the set of all scenes; Represents the set of all nodes in the transmission network; For failure scenarios The node below The objective function is to minimize the average load shedding of all scenarios.

[0061] 2) Operational constraints Optimizing the resilience of power grids under extreme weather conditions needs to meet a series of constraints: (1) Power balance constraints (8) (9) (10) in, For the scene Down Line The trend, For the scene Next Node The output power, For Node Equation (8) is the power balance equation, Equation (9) makes the power flow on the disconnected line equal to 0, and Equation (10) ensures that the load shedding does not exceed the node load demand.

[0062] (2) Power flow constraints (11) in, For Node The phase angle, Indicates line The reactance of the resistor. Equation (11) is a simplified DC power flow equation. to relax the constraint corresponding to the disconnected line.

[0063] (3) Emergency power supply dispatch constraints (12) (13) in, A 0-1 variable indicating emergency power supply Whether to connect to the node If yes, then it is 1, otherwise it is 0; For failure scenarios Emergency power supply The output power of the power grid is 1000MW. When the local wind speed is known, only the probability of line failure can be obtained, but it is impossible to determine whether the line is faulty. Therefore, when executing emergency power dispatch, the optimal dispatch strategy of emergency resources under all possible fault scenarios should be considered. Formula (12) indicates that each emergency resource can only be connected to one node. Formula (13) limits the output range of the emergency power supply.

[0064] (4) Node output power constraints Formula (14) represents the scene Next Node The output power of the emergency power supply is equal to the output power of the emergency power supply plus the output power of the node power supply. Not connected to the node ,have ; The details are as follows: (14) Formula (15) is the range limit of the node power supply output power; the details are as follows: (15) Formula (16) is the output power of the non-power node; specifically, it is as follows: (16) in, is the power output power of the power node.

[0065] S5. Solve the resilience optimization model established in step S4 to obtain the average load shedding of the transmission network. The larger the value, the worse the resilience of the system and the weaker its disaster resistance.

[0066] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as systems, methods or program products. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "circuits", "modules" or "platforms".

[0067] In another embodiment of the present invention, a resilience assessment system for emergency power supply response of a transmission network under extreme strong winds is provided. The system can be used to implement the above-mentioned resilience assessment method for emergency power supply response of a transmission network under extreme strong winds. Specifically, the resilience assessment system for emergency power supply response of a transmission network under extreme strong winds includes a calculation module, a scenario module, an optimization module and an evaluation module.

[0068] Wherein, the calculation module calculates the failure probability of each line of the transmission network based on the transmission network data to be evaluated; Scenario module, generates probabilistic failure scenarios; The optimization module builds an optimization mathematical model under the transmission network failure scenario based on the transmission network grid and data information and the generated probabilistic failure scenario; The evaluation module solves the optimization mathematical model under the transmission network failure scenario, obtains the expected load shedding of the transmission network, and evaluates the resilience of the power system in the disaster area based on the expected load shedding.

[0069] In another embodiment of the present invention, a terminal device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, graphics processing units (GPU), tensor processing units (TPU), digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the resilience assessment method of the emergency power supply response of the transmission network under extreme winds, including: Based on the transmission network data to be evaluated, the failure probability of each line in the transmission network is calculated; a probabilistic failure scenario is generated; based on the transmission network grid and data information, an optimized mathematical model under the transmission network failure scenario is constructed in combination with the generated probabilistic failure scenario; the optimized mathematical model under the transmission network failure scenario is solved to obtain the expected load shedding of the transmission network, and the resilience of the power system in the disaster area is evaluated based on the expected load shedding.

[0070] See also Figure 2 , the terminal device is a computer device. The computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, the method for evaluating the resilience of the emergency power supply response of the power transmission network under extreme gale in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program 63 is executed by the processor 61, the functions of each model / unit in the system for evaluating the resilience of the emergency power supply response of the power transmission network under extreme gale in the embodiment are implemented. To avoid repetition, it is not described one by one here.

[0071] The computer device 60 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will appreciate that Figure 2This is only an example of the computer device 60 and does not constitute a limitation of the computer device 60. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0072] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, graphics processing units (GPU), tensor processing units (TPU), digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0073] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 60.

[0074] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0075] See also Figure 3 The terminal device is an electronic device 600, which is in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0076] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention described in the above method section of this specification. For example, the processing unit 610 can perform the following steps: Figure 1 Follow the steps shown in .

[0077] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0078] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0079] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0080] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, etc.

[0081] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium, which is a memory device in a terminal device for storing programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs. It should be noted that the computer-readable storage medium here can be a high-speed RAM memory, or a non-volatile memory (Non-VolatileMemory), such as at least one disk memory.

[0082] One or more instructions stored in a computer-readable storage medium may be loaded and executed by a processor to implement the corresponding steps of the method for assessing resilience of emergency power supply response of a power transmission network under extreme wind conditions in the above-mentioned embodiment; one or more instructions in the computer-readable storage medium may be loaded and executed by a processor as follows: Based on the transmission network data to be evaluated, the failure probability of each line in the transmission network is calculated; a probabilistic failure scenario is generated; based on the transmission network grid and data information, an optimized mathematical model under the transmission network failure scenario is constructed in combination with the generated probabilistic failure scenario; the optimized mathematical model under the transmission network failure scenario is solved to obtain the expected load shedding of the transmission network, and the resilience of the power system in the disaster area is evaluated based on the expected load shedding.

[0083] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions 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 part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0084] Example structure: To verify the effectiveness of the present invention, an IEEE 24-node system is used as an example for testing. The system is equipped with three emergency power supplies, each with a rated power of 100MW. The test example includes the following steps: 1) Using the power transmission line failure probability calculation method of the present invention to obtain the line failure probability of the system; 2) Generate 10,000 fault scenarios based on the failure probability of transmission lines using Monte Carlo simulation method; 3) Establish a resilience optimization model to calculate the system's load shedding and emergency power supply scheduling.

[0085] In the test, the resilience optimization results of the present invention including emergency power supply scheduling and the resilience evaluation results without considering emergency power supply scheduling were compared.

[0086] Example results: The system line failure probability obtained according to the transmission line failure probability calculation method is as follows: Figure 4 shown.

[0087] According to the calculation results of the resilience optimization model, the average system load shedding is 598.82MW, and the three emergency power supplies are dispatched to nodes 6, 8, and 10 respectively. The average system load shedding under the resilience assessment results without considering the emergency power supply dispatch is 893.75MW. From the results, it can be seen that the average system load shedding is reduced by 33.00% under the method proposed in the present invention, indicating that the resilience of the system will be significantly improved when considering the emergency power supply dispatch. The example results show that for a system equipped with an emergency power supply, not considering the impact of the emergency power supply dispatch on the system resilience will make the obtained resilience assessment results lower than the actual situation of the system, and considering the emergency power supply dispatch can make the system resilience assessment more accurate. At the same time, the example results also provide a reference for the dispatch of emergency resources under this extreme wind speed.

[0088] In summary, the method and system for evaluating the resilience of the emergency power supply response of a power transmission network under extreme wind conditions of the present invention can better evaluate the resilience of the power transmission network containing the emergency power supply and provide an optimized scheduling strategy for the emergency power supply.

[0089] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0090] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0091] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0092] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0094] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0095] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0096] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices, and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0099] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A method for evaluating the resilience of emergency power supply response of a power transmission network under extreme wind conditions, characterized in that: The following steps are involved: Calculating the failure probability of each line of the transmission network based on the transmission network data to be evaluated; Generate probabilistic failure scenarios; According to the transmission network grid and data information, combined with the generated probabilistic fault scenarios, an optimized mathematical model under the transmission network fault scenario is constructed; Solve the optimization mathematical model under the transmission network failure scenario to obtain the expected load shedding of the transmission network, and evaluate the resilience of the power system in the disaster area based on the expected load shedding.

2. The method for evaluating the resilience of emergency power supply response of power transmission network under extreme wind conditions according to claim 1 is characterized in that: The transmission grid data to be evaluated include: System grid topology , node set , power node collection , non-power node set , each node load , the upper and lower limits of the power node output power , ; Line collection , the impedance of each line and and line capacity ; The local wind speed to be calculated, including the wind speed at each tower of the line , wind speed of the conductor section between the two towers ; Enter the design wind speed for the tower and conductor segment and , and the length of the wire segment ; Input the emergency mobile power supply set , output power upper and lower limits , ; Transmission Network Node Index , ; Line Index , ; Emergency Power Supply Index , ; Fault scenario index , .

3. The method for evaluating the resilience of emergency power supply response of power transmission network under extreme wind conditions according to claim 1 is characterized in that: The transmission line route consists of multiple transmission towers and conductors in series. The failure probability of the transmission line is calculated as follows: in, For transmission lines The failure rate, is the number of transmission towers on the line, is the number of conductor segments of the line, For transmission lines On The failure rate of transmission towers, For transmission lines On The failure rate of a conductor segment.

4. The method for evaluating the resilience of emergency power supply response of a power transmission network under extreme wind conditions according to claim 3 is characterized in that: Failure rate of a single transmission tower The calculation is as follows: in, It is the failure probability curve model of transmission tower.

5. The method for evaluating the resilience of emergency power supply response of power transmission network under extreme wind conditions according to claim 4 is characterized in that: Failure rate of the conductor section between two transmission towers The calculation is as follows: in, is the fault probability model of the conductor segment.

6. The method for evaluating resilience of emergency power supply response of power transmission network under extreme wind conditions according to claim 5 is characterized in that: Failure Probability Curve Model of Transmission Towers Fault probability model of conductor segments for: in, For line Previous The real-time wind speed of the tower, is the model coefficient, is the design wind speed for each tower, For line Previous The wind speed of the conductor segment, is the design wind speed of the line segment, Wire segment length.

7. The method for evaluating the resilience of emergency power supply response of power transmission network under extreme wind conditions according to claim 1 is characterized in that: Defining binary variables Indicates the status of the line in extremely windy weather. Indicates that the line is in normal operation. Indicates that the line is in a failed state, and the interval is randomly generated according to the Monte Carlo simulation method A random number that follows a uniform distribution , generate a large number of fault scenarios through random sampling and build a set of fault scenarios .

8. The method for evaluating resilience of emergency power supply response of power transmission network under extreme wind conditions according to claim 1 is characterized in that: The objective function of the optimization mathematical model under the transmission network fault scenario is: in, Represents the set of all scenes; Represents the set of all nodes in the transmission network; For failure scenarios The node below of load shedding.

9. The method for evaluating resilience of emergency power supply response of power transmission network under extreme gale conditions according to claim 8, characterized in that: The constraints of the optimization mathematical model under the transmission network fault scenario are as follows: Power balance constraints in, For the scene Down Line The trend, For the scene Next Node The output power, For Node The load demand, It is a collection of transmission network lines; Power flow constraints in, For Node The phase angle, Indicates line The reactance, For Node The phase angle, is a sufficiently large coefficient, It is a 0-1 variable, indicating the line Whether it is in a fault state; Emergency power dispatch constraints in, A 0-1 variable indicating emergency power supply Whether to connect to the node superior, For failure scenarios Emergency power supply The output power, For emergency power supply The lower limit of output power, For emergency power supply The output power limit of Node output power constraints: The range of node power output power is limited as follows: Output power of non-power nodes: in, is the power output power of the power node, is the lower limit of the output power of the power node, is the output power upper limit of the power node, A collection of power nodes.

10. A resilience assessment system for emergency power supply response of a power transmission network under extreme wind conditions, characterized in that: include: A calculation module, which calculates the failure probability of each line of the transmission network based on the transmission network data to be evaluated; Scenario module, generates probabilistic failure scenarios; The optimization module builds an optimization mathematical model under the transmission network failure scenario based on the transmission network grid and data information and the generated probabilistic failure scenario; The evaluation module solves the optimization mathematical model under the transmission network failure scenario, obtains the expected load shedding of the transmission network, and evaluates the resilience of the power system in the disaster area based on the expected load shedding.

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