Method and system for improving toughness of power transmission line under typhoon disaster

Abstract

The invention relates to a typhoon disaster-oriented power transmission line toughness improvement method and system. The method comprises the steps of obtaining the wind speed and related data of a typhoon passing through a power transmission line based on distributed optical fibers; calculating an evaluation index of a power transmission key channel based on the wind speed and weighting to obtain a channel importance degree; selecting the power transmission key channels corresponding to the importance degrees of the first k1 channels after the descending sorting to form a power transmission key channel set; calculating the wind load sensitivity and the structure wind resistance of each power transmission key channel span; weighting to obtain span vulnerability; obtaining a final risk level based on the channel importance and the span vulnerability; power transmission key channel spans corresponding to the first k2 final risk levels after descending sorting are selected to form a fragile span set; and constructing and solving a toughness improvement model, and obtaining and executing a toughness improvement scheme.

Description

Technical Field

[0001] This invention relates to the field of power system resilience assessment and enhancement technology, and mainly to a method and system for enhancing the resilience of transmission lines under typhoon disasters. Background Technology

[0002] Existing methods for enhancing the resilience of power transmission systems often employ typhoon wind field models (such as the Batts model) to simulate wind speed information at various points within the wind field after a typhoon makes landfall. While these models can capture wind speeds within the transmission network, they are largely based on theoretical assumptions and lack effective integration with actual on-site engineering conditions. Consequently, they cannot accurately represent the wind speeds on transmission lines during a real typhoon. Due to the inaccuracy of wind speed input, the wind-induced load and fault risk assessment results obtained from these wind field models may deviate from actual operating conditions, thus affecting the reliability and engineering applicability of power transmission system resilience assessments.

[0003] Existing resilience enhancement methods primarily focus on strengthening transmission lines, using system load losses after typhoon disasters as resilience assessment indicators to quantify the resilience of the transmission system and the effectiveness of resilience measures. However, the strengthening of transmission channels often neglects the identification of critical transmission lines within the system and fails to consider the protection of critical channels. The disruption of critical transmission channels during typhoons can trigger multiple risks, weakening the adaptability of resilience enhancement schemes. Resilience-oriented transmission line strengthening schemes are mostly implemented at the line level within the system. However, due to the long length of transmission networks, the differences in meteorological conditions and geographical locations between different spans within transmission channels are ignored. Traditional methods can only identify critical lines but cannot further pinpoint specific vulnerable spans, resulting in transmission line strengthening schemes that are not refined enough and lack economic viability while meeting the resilience requirements of the power system under typhoon disasters. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention proposes a method and system for improving the resilience of power transmission lines under typhoon disasters.

[0005] The technical solution of the present invention is as follows: On the one hand, this invention proposes a method for improving the resilience of transmission lines under typhoon disasters, the method comprising: Wind speed and related data of typhoons passing through power transmission lines were obtained using distributed optical fiber. Evaluation indicators for critical power transmission channels are calculated based on wind speed. The importance of the channels is obtained by weighted calculation of the evaluation indicators and sorted in descending order. The critical power transmission channels corresponding to the top k1 channel importance are selected to form a set of critical power transmission channels. The wind load sensitivity and structural wind resistance of each span of critical power transmission channel in the set are calculated based on relevant data. The span vulnerability is obtained by weighted calculation of wind load sensitivity and structural wind resistance. The final risk levels are obtained based on the importance of the transmission channel and the vulnerability of the span, and then sorted in descending order. The spans of the critical transmission channels corresponding to the top k2 final risk levels are selected to form a set of vulnerable spans. A resilience enhancement model is constructed, including an objective function aimed at minimizing the sum of the overall reinforcement cost of the transmission line, the local reinforcement cost of the span, and the typhoon load loss cost, and constraints based on a set of vulnerable spans. Solve the resilience enhancement model to obtain the resilience enhancement scheme and implement it.

[0006] Preferably, the backscattered Rayleigh light signal is obtained by using distributed optical fibers deployed on the transmission line; The vibration information of the transmission line was obtained by demodulating the backscattered Rayleigh light signal using a phase-sensitive optical time-domain reflectometer, and the wind speed was calculated based on the Karman vortex principle.

[0007] Preferably, the cumulative fault probability of transmission lines during the duration of a typhoon is calculated based on wind speed, specifically as follows: A transmission line is considered to be composed of multiple transmission towers and multiple transmission line segments connected together. The cumulative failure probability of the transmission towers and the cumulative failure probability of the transmission line segments during the duration of the typhoon are calculated respectively. The cumulative failure probability of the transmission line during the typhoon is calculated based on the cumulative failure probability of the transmission tower and the cumulative failure probability of the transmission line segment. Typhoon disaster scenarios are generated based on Monte Carlo simulation and cumulative failure probability.

[0008] Preferably, the evaluation indicators include weighted grid entropy, weighted power flow transfer entropy, and load power supply dependence, wherein: The weighted network entropy is specifically calculated as the average node flow rate of each node after a fault occurs in a critical power transmission channel. The weighted power flow transfer entropy is specifically used to calculate the power flow impact on other critical transmission channels after a failure occurs in a critical transmission channel. The load power supply dependence is specifically calculated as the degree of dependence of load nodes on key power transmission channels.

[0009] Preferably, the wind load sensitivity is calculated as follows: ; ; In the formula, Indicates wind load sensitivity; Indicates wind load sensitivity; Indicates the wind pressure unevenness coefficient; Indicates the coefficient of variation of wind pressure at height; Indicates the wind conductor drag coefficient; Indicates the outer diameter of the conductor; This indicates the horizontal span length of the current transmission line segment; Indicates the wind deflection angle; express Wind speed at the location of the power transmission line at any given time; Indicates the correction factor; This indicates the design wind load for the span of the power transmission channel; The wind resistance of the structure is calculated as follows: ; ; ; In the formula, This indicates the current critical power transmission channel number. The structural wind resistance of each transmission line section; Indicates the vulnerability factor of the span length; This indicates the weight of the gap length vulnerability factor; Indicates the terrain wind speed amplification factor; Indicates the weight of the terrain wind speed amplification factor; Indicates the cumulative fatigue damage factor; Indicates the weight of the cumulative fatigue damage factor; Indicates the standard design span length; Indicates the sag influence coefficient; Indicates the key transmission channel The maximum sag of each transmission line segment.

[0010] Preferably, the objective function is calculated as follows: ; In the formula, Represent the objective function; This indicates the overall cost of reinforcing transmission lines; This indicates the cost of localized reinforcement within the gear range; This indicates the cost of typhoon load loss; The constraints include line DC power flow constraints and vulnerable channel span protection index constraints.

[0011] Preferably, a mathematical programming solver or a heuristic optimization algorithm is used to solve the resilience enhancement model.

[0012] Preferably, the method further includes calculating the disaster risk resistance of the transmission line before and after the implementation of the resilience enhancement scheme; The disaster risk resilience is calculated as follows: ; In the formula, Indicates resilience to disaster risks; express Time of the first The first busbar The actual load level; Indicates the number of busbars; Indicates the first Number of loads on each busbar; Indicates the time of the lowest load level; Indicates the moment when the load level decreases; Indicates the time when the disaster occurred; express Time of the first The first busbar A normal load level.

[0013] Preferably, the disaster risk resistance of the transmission lines before and after the implementation of the resilience enhancement scheme is compared to obtain the resilience enhancement result. Specifically, if the disaster risk resistance of the transmission lines before implementation is greater than that after implementation, it means that the current resilience enhancement scheme has failed to improve the system resilience and a new resilience enhancement scheme needs to be generated.

[0014] On the other hand, the present invention also provides a transmission line resilience enhancement system for typhoon disasters, the system comprising: The data acquisition module acquires wind speed and related data as the typhoon passes through power transmission lines based on distributed optical fiber. The vulnerable span screening module calculates the evaluation indicators of critical transmission channels based on wind speed, performs weighted calculations on the evaluation indicators to obtain the channel importance, and sorts them in descending order; selects the top k1 critical transmission channels corresponding to their importance to form a set of critical transmission channels; calculates the wind load sensitivity and structural wind resistance of each critical transmission channel span in the set based on relevant data; and performs weighted calculations of wind load sensitivity and structural wind resistance to obtain the span vulnerability. The final risk levels are obtained based on the importance of the transmission channel and the vulnerability of the span, and then sorted in descending order. The spans of the critical transmission channels corresponding to the top k2 final risk levels are selected to form a set of vulnerable spans. The resilience scheme generation module constructs a resilience enhancement model, including an objective function that minimizes the sum of the overall reinforcement cost of the transmission line, the local reinforcement cost of the span, and the typhoon load loss cost, and constraints constructed based on the set of vulnerable spans; it solves the resilience enhancement model to obtain and execute the resilience enhancement scheme.

[0015] The present invention has the following beneficial effects: 1. This invention provides a method and system for improving the resilience of transmission lines under typhoon disasters. It utilizes distributed optical fiber sensing and the Karman vortex principle to calculate real-time wind speed, achieving accurate wind speed acquisition. This solves the problem that traditional typhoon wind field models (such as the Batts model) rely solely on theoretical assumptions and are out of touch with engineering realities. It enables synchronous and accurate monitoring of wind speed along the entire transmission line, improving the reliability of risk assessment. 2. This invention provides a method and system for improving the resilience of transmission lines under typhoon disasters. It constructs a channel importance assessment system based on weighted grid entropy, weighted power flow transfer entropy, and load supply dependence from three dimensions: grid topology, power flow transfer, and load dependence. This system screens key transmission channels and achieves precise risk identification. By combining wind load sensitivity (quantifying the load response of spans to wind speed) and structural wind resistance (integrating factors such as span length, terrain amplification, and cumulative fatigue damage), it identifies high-risk and vulnerable spans, overcoming the limitation of not being able to accurately locate vulnerable spans and avoiding resource waste caused by blind reinforcement. 3. This invention provides a method and system for improving the resilience of transmission lines under typhoon disasters. It constructs a resilience improvement model with the goal of minimizing the sum of the overall reinforcement cost of the transmission line, the local reinforcement cost of the span, and the typhoon load loss cost. At the same time, it incorporates the DC power flow constraints of the line and the protection index constraints of the vulnerable channel span. It solves the problem through a mathematical programming solver or a heuristic optimization algorithm. Under the premise of meeting the resilience requirements of the power system under typhoon disasters, it achieves the optimal balance between reinforcement cost and loss cost. It solves the problem of traditional reinforcement schemes emphasizing reinforcement and neglecting cost. It controls the total investment while improving the system resilience, thereby improving the economy and engineering feasibility of the scheme. 4. This invention provides a method and system for enhancing the resilience of transmission lines under typhoon disasters. The transmission line is decomposed into towers and line segments, and the cumulative fault probability during the duration of the typhoon is calculated separately. The Monte Carlo simulation method is used to generate multiple typhoon disaster scenarios, accurately replicating the fault evolution law of transmission lines under typhoon disasters. This provides a more comprehensive scenario input for the resilience enhancement model, enabling the resilience enhancement scheme to adapt to typhoon scenarios of different intensities and durations, and enhancing the risk resistance adaptability and robustness of the scheme. Attached Figure Description

[0016] Figure 1 This is a detailed flowchart of an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0019] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0020] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0021] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0022] Example 1: See Figure 1 This invention provides a method for improving the resilience of power transmission lines under typhoon disasters, the method comprising: S1. Obtain wind speed and related data of typhoons passing through power transmission lines based on distributed optical fiber; S11. Using distributed optical fibers deployed on transmission lines, the backscattered Rayleigh light signal is obtained, specifically: In a distributed optical fiber sensing system, vortex-induced vibrations caused by a typhoon propagate along the conductor to the internal optical fiber, generating local strain and periodic refractive index modulation, which changes the phase and intensity of the backscattered Rayleigh light. By demodulating the time-frequency characteristics of these signals, phase and intensity signals related to wind speed are formed. The backscattered Rayleigh light signal is demodulated using a phase-sensitive optical time-domain reflectometer. By analyzing the characteristics of the scattered signal, information related to line vibration is obtained. The vibration characteristic line spectrum of the line is extracted through fast Fourier transform processing. The monitoring location is distinguished by its echo time difference, and the vibration information of the transmission line is obtained. The wind speed is calculated based on the Karman vortex principle, so as to realize synchronous monitoring of wind speed of the entire line. S12. Calculate the cumulative fault probability of transmission lines during the duration of a typhoon based on wind speed, specifically: A power transmission line can be considered as a combination of multiple transmission towers and multiple transmission line segments. The cumulative failure probability of transmission towers during the duration of a typhoon is calculated as follows: ; ; In the formula, express Time of the first The first of the transmission lines The probability of failure of a transmission tower; express Time of the first The first of the transmission lines Wind speed of each transmission tower; Indicates the design wind speed of the transmission tower; Indicates the first The first of the transmission lines The cumulative failure probability of a transmission tower; Indicates the total duration; Indicates a time interval; The cumulative fault probability of a transmission line segment is calculated as follows: ; ; In the formula, express Time of the first The first of the transmission lines The probability of failure of a transmission line; Indicates the design wind speed of the transmission line section; express Time of the first The first of the transmission lines Wind speed of each transmission line; Indicates the first The first of the transmission lines The cumulative fault probability of a transmission line; Indicates the first [unit] between adjacent transmission towers The span length of each transmission line; The cumulative fault probability of a transmission line during a typhoon is calculated based on the cumulative fault probability of the transmission tower and the cumulative fault probability of the transmission line segment. The calculation method is as follows: ; In the formula, Indicates the first The cumulative failure probability of a power transmission line during the duration of a typhoon; Indicates the total number of transmission towers; Indicates the total number of transmission line segments; Typhoon disaster scenarios are generated based on Monte Carlo simulation and cumulative failure probability. S2. Calculate the evaluation index of key power transmission channels based on wind speed, perform weighted calculation on the evaluation index to obtain the channel importance and sort them in descending order; S21. Evaluation indicators are constructed from three identification perspectives: power grid topology, transmission network state changes, and load power supply dependence. These evaluation indicators include weighted network entropy. Weighted power flow transfer entropy and load power supply dependence ,in: The weighted network entropy is specifically calculated by determining the average node flow of each node after a fault occurs in a critical power transmission channel. The calculation method is as follows: ; ; ; In the formula, Indicates the number of nodes; Indicates the first Traffic probability distribution of each node; Indicates the first Average traffic per node; Indicates the number of critical power transmission channels; Indicates the relationship with the first A set of nodes connected to each other; Indicates the first The first critical power transmission channel to fail The node to the first The flow of each node; The weighted power flow transfer entropy is specifically used to calculate the power flow impact on other critical transmission channels after a fault occurs in a critical transmission channel. The calculation method is as follows: ; ; ; In the formula, Indicates the first Key power transmission channels and the first Power flow transfer probability of a critical power transmission channel; Indicates the first Key power transmission channels and the first Power flow transfer volume of key power transmission channels; Indicates the first The first critical power transmission channel to fail Power flow in key transmission channels; Indicates the first Power flow in key transmission channels; Indicates the first Key power transmission channels and the first Power flow transfer volume of key power transmission channels; The load power supply dependence is specifically calculated as follows: the degree of dependence of load nodes on critical power transmission channels is calculated as follows: ; ; ; ; In the formula, Indicates the first Dependency of each load node; Indicates the first The key power transmission channel is for the first Power supply contribution factor of each load node; Indicates the first The key power transmission channel is for the first Fault impact factors of each load node; Indicates the first The key power transmission channel is for the first Power supply to each load node; Indicates the first Load demand of each load node; Indicates the number of load nodes; Indicates the first The first critical power transmission channel to fail Available power of each load node; S22. The channel importance is calculated as follows: ; In the formula, Indicates the importance of the channel; The weights represent the weights of the weighted network entropy; The weights represent the weights of the weighted power flow transfer entropy; Weights representing the load's dependence on power supply; S3. Select the key transmission channels corresponding to the importance of the top k1 channels to form a set of key transmission channels; S4. In the face of the vulnerability identification of span levels under typhoon disasters, the wind speed of different spans in the same key transmission channel can be monitored based on distributed optical fiber sensing technology. At the same time, considering that the actual span lengths are not consistent, the vulnerability of the span can be determined by two indicators: wind load sensitivity and structural wind resistance. Based on relevant data, the wind load sensitivity and structural wind resistance of each span of the critical power transmission channel in the set of critical power transmission channels were calculated. S41. The wind load sensitivity characterizes the load sensitivity of this span under different wind speeds, and is calculated as follows: ; ; In the formula, Indicates wind load sensitivity; Indicates wind load sensitivity; Indicates the wind pressure unevenness coefficient; Indicates the coefficient of variation of wind pressure at height; Indicates the wind conductor drag coefficient; Indicates the outer diameter of the conductor; This indicates the horizontal span length of the current transmission line segment; Indicates the wind deflection angle; express Wind speed at the location of the power transmission line at any given time; Indicates the correction factor; This indicates the design wind load for the span of the power transmission channel; S42. The structural wind resistance is assessed from the perspective of structural characteristics and environmental conditions to evaluate the inherent ability of the span to resist typhoons. The calculation method is as follows: ; ; ; In the formula, This indicates the current critical power transmission channel number. The structural wind resistance of each transmission line section; This indicates the vulnerability factor of span length. The longer the span, the greater the sag, the greater the wind swing amplitude, and the weaker the wind resistance. This indicates the weight of the gap length vulnerability factor; This indicates the terrain wind speed amplification factor. When the wind speed encounters special terrains such as mountains and canyons, the wind speed will be amplified. Indicates the weight of the terrain wind speed amplification factor; This represents the cumulative fatigue damage factor, which characterizes the cumulative wear and tear on spans during historical typhoons. Indicates the weight of the cumulative fatigue damage factor; Indicates the standard design span length; Indicates the sag influence coefficient; Indicates the key transmission channel The maximum sag of each transmission line segment; S5. Weighted calculation of wind load sensitivity and structural wind resistance yields span vulnerability. The calculation method is as follows: ; In the formula, This indicates the current critical power transmission channel number. Vulnerability of spans in individual transmission line sections; Weights representing sensitivity to wind loads; The weight representing the structure's wind resistance; in and The AHP-entropy weight combination method can be used to determine this. S6. Based on channel importance and gap vulnerability, the final risk level is obtained and sorted in descending order. The calculation method is as follows: , ; In the formula, Indicates the first The first key power transmission channel The final risk level of each transmission line segment; Indicates the first Importance of key power transmission channels; Represents the set of critical power transmission channels; S7. Select the transmission critical channel spans corresponding to the first k2 final risk levels to form a vulnerable span set. S8. Construct a resilience enhancement model, including an objective function that aims to minimize the sum of the overall reinforcement cost of the transmission line, the local reinforcement cost of the span, and the typhoon load loss cost, and constraints based on the set of vulnerable spans. S81. The objective function is calculated as follows: ; ; ; ; In the formula, Represent the objective function; This indicates the overall cost of reinforcing transmission lines; This indicates the cost of localized reinforcement within the gear range; This indicates the cost of typhoon load loss; This represents the set of candidate transmission lines used for hardening decisions; Indicates the first The overall reinforcement cost of the transmission line; Indicates the first Overall reinforcement decision variables for a transmission line; Represents the set of critical power transmission channels; Indicates the first A set of vulnerable spans in key power transmission channels; Indicates the first The first key power transmission channel Individual reinforcement costs for each span of a transmission line section; Indicates the first The first key power transmission channel Individual reinforcement decision variables for each transmission line segment span; This indicates the total number of typhoon-related failure scenarios; Indicates the first Typhoon failure scenario coefficients; Indicates the total number of busbars; This indicates the penalty cost for load loss under typhoon disaster conditions; Indicates the first The first typhoon failure scenario The cost of load loss penalty for a single busbar; S82. The constraints include line DC power flow constraints and vulnerable channel span protection index constraints. The DC power flow constraint of the line is calculated as follows: ; ; ; ; In the formula, Indicates the first The first key power transmission channel The overall operational status of each typhoon fault scenario; Indicates the first The first typhoon failure scenario Voltage phase angle of the busbar; Indicates the first The first typhoon failure scenario Voltage phase angle of the busbar; Indicates the first The key power transmission channel is in the first The busbar and the first Active power flow between busbars; Indicates the first The key power transmission channel is in the first The busbar and the first Admittance between busbars; Indicates the first Decision variables for the overall reinforcement of key power transmission channels; Indicates the first The first key power transmission channel The weakest span condition under a typhoon failure scenario; Indicates the first The set of all spans of a key power transmission corridor; Indicates the first The first key power transmission channel The first typhoon failure scenario The natural survival status of each transmission line segment span; The vulnerability channel span protection index constraint is calculated as follows: ; ; ; In the formula, Indicates the first The importance weight of key power transmission channels; This indicates the preset key channel spacing for protection. Indicates the first The first key power transmission channel Barrier protection rate under typhoon failure scenarios; Indicates the first Importance of key power transmission channels; S9. Solve the toughness improvement model to obtain the toughness improvement scheme and implement it. The resilience enhancement model is solved using a mathematical programming solver or a heuristic optimization algorithm. S10. The method further includes calculating the disaster risk resistance of the transmission line before and after the implementation of the resilience enhancement scheme; The disaster risk resilience is calculated as follows: ; In the formula, Indicates resilience to disaster risks; express Time of the first The first busbar The actual load level; Indicates the first Number of loads on each busbar; Indicates the time of the lowest load level; Indicates the moment when the load level decreases; Indicates the time when the disaster occurred; express Time of the first The first busbar A normal load level; S11. Compare the disaster risk resistance of transmission lines before and after the implementation of the resilience enhancement scheme to obtain the resilience enhancement result. Specifically, if the disaster risk resistance of the transmission lines before implementation is greater than that after implementation, it means that the current resilience enhancement scheme has failed to improve the system resilience and a new resilience enhancement scheme needs to be generated.

[0023] Example 2: This embodiment provides a system for enhancing the resilience of power transmission lines under typhoon disasters, the system comprising: The data acquisition module acquires wind speed and related data as the typhoon passes through power transmission lines based on distributed optical fiber. The vulnerable span screening module calculates the evaluation indicators of critical transmission channels based on wind speed, performs weighted calculations on the evaluation indicators to obtain the channel importance, and sorts them in descending order; selects the top k1 critical transmission channels corresponding to their importance to form a set of critical transmission channels; calculates the wind load sensitivity and structural wind resistance of each critical transmission channel span in the set based on relevant data; and performs weighted calculations of wind load sensitivity and structural wind resistance to obtain the span vulnerability. The final risk levels are obtained based on the importance of the transmission channel and the vulnerability of the span, and then sorted in descending order. The spans of the critical transmission channels corresponding to the top k2 final risk levels are selected to form a set of vulnerable spans. The resilience scheme generation module constructs a resilience enhancement model, including an objective function that minimizes the sum of the overall reinforcement cost of the transmission line, the local reinforcement cost of the span, and the typhoon load loss cost, and constraints constructed based on the set of vulnerable spans; it solves the resilience enhancement model to obtain and execute the resilience enhancement scheme.

[0024] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0025] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0026] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0027] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0028] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for improving the resilience of transmission lines under typhoon disasters, characterized in that, The method includes: Wind speed and related data of typhoons passing through power transmission lines were obtained using distributed optical fiber. Evaluation indicators for critical power transmission channels are calculated based on wind speed. The importance of the channels is obtained by weighted calculation of the evaluation indicators and sorted in descending order. The critical power transmission channels corresponding to the top k1 channel importance are selected to form a set of critical power transmission channels. The wind load sensitivity and structural wind resistance of each span of critical power transmission channel in the set are calculated based on relevant data. The span vulnerability is obtained by weighted calculation of wind load sensitivity and structural wind resistance. The final risk levels are obtained based on the importance of the transmission channel and the vulnerability of the span, and then sorted in descending order. The spans of the critical transmission channels corresponding to the top k2 final risk levels are selected to form a set of vulnerable spans. A resilience enhancement model is constructed, including an objective function aimed at minimizing the sum of the overall reinforcement cost of the transmission line, the local reinforcement cost of the span, and the typhoon load loss cost, and constraints based on a set of vulnerable spans. Solve the resilience enhancement model to obtain the resilience enhancement scheme and implement it.

2. The method for improving the resilience of transmission lines under typhoon disasters according to claim 1, characterized in that, Backscattered Rayleigh light signals are acquired using distributed optical fibers deployed on power transmission lines; The vibration information of the transmission line was obtained by demodulating the backscattered Rayleigh light signal using a phase-sensitive optical time-domain reflectometer, and the wind speed was calculated based on the Karman vortex principle.

3. The method for improving the resilience of transmission lines under typhoon disasters according to claim 2, characterized in that, The cumulative fault probability of transmission lines during the duration of a typhoon is calculated based on wind speed, specifically as follows: A transmission line is considered to be composed of multiple transmission towers and multiple transmission line segments connected together. The cumulative failure probability of the transmission towers and the cumulative failure probability of the transmission line segments during the duration of the typhoon are calculated respectively. The cumulative failure probability of the transmission line during the typhoon is calculated based on the cumulative failure probability of the transmission tower and the cumulative failure probability of the transmission line segment. Typhoon disaster scenarios are generated based on Monte Carlo simulation and cumulative failure probability.

4. A method for improving the resilience of transmission lines under typhoon disasters according to claim 3, characterized in that, The evaluation metrics include weighted network entropy, weighted power flow transfer entropy, and load power supply dependence, among which: The weighted network entropy is specifically calculated as the average node flow rate of each node after a fault occurs in a critical power transmission channel. The weighted power flow transfer entropy is specifically used to calculate the power flow impact on other critical transmission channels after a failure occurs in a critical transmission channel. The load power supply dependence is specifically calculated as the degree of dependence of load nodes on key power transmission channels.

5. A method for improving the resilience of transmission lines under typhoon disasters according to claim 4, characterized in that, The wind load sensitivity is calculated as follows: ； ； In the formula, Indicates wind load sensitivity; Indicates wind load sensitivity; Indicates the wind pressure unevenness coefficient; Indicates the coefficient of variation of wind pressure at height; Indicates the wind conductor drag coefficient; Indicates the outer diameter of the conductor; This indicates the horizontal span length of the current transmission line segment; Indicates the wind deflection angle; express Wind speed at the location of the power transmission line at any given time; Indicates the correction factor; This indicates the design wind load for the span of the power transmission channel; The wind resistance of the structure is calculated as follows: ； ； ； In the formula, This indicates the current critical power transmission channel number. The structural wind resistance of each transmission line section; Indicates the vulnerability factor of the span length; This indicates the weight of the gap length vulnerability factor; Indicates the terrain wind speed amplification factor; Indicates the weight of the terrain wind speed amplification factor; Indicates the cumulative fatigue damage factor; Indicates the weight of the cumulative fatigue damage factor; Indicates the standard design span length; Indicates the sag influence coefficient; Indicates the key transmission channel The maximum sag of each transmission line segment.

6. A method for improving the resilience of transmission lines under typhoon disasters according to claim 1, characterized in that, The objective function is calculated as follows: ； In the formula, Represent the objective function; This indicates the overall cost of reinforcing transmission lines; This indicates the cost of localized reinforcement within the gear range; This indicates the cost of typhoon load loss; The constraints include line DC power flow constraints and vulnerable channel span protection index constraints.

7. A method for improving the resilience of transmission lines under typhoon disasters according to claim 1, characterized in that, The resilience enhancement model is solved using a mathematical programming solver or a heuristic optimization algorithm.

8. A method for improving the resilience of transmission lines under typhoon disasters according to claim 1, characterized in that, The method also includes calculating the disaster risk resistance of transmission lines before and after the implementation of the resilience enhancement scheme; The disaster risk resilience is calculated as follows: ； In the formula, Indicates resilience to disaster risks; express Time of the first The first busbar The actual load level; Indicates the number of busbars; Indicates the first Number of loads on each busbar; Indicates the time of the lowest load level; Indicates the moment when the load level decreases; Indicates the time when the disaster occurred; express Time of the first The first busbar A normal load level.

9. A method for improving the resilience of transmission lines under typhoon disasters according to claim 8, characterized in that, The resilience enhancement scheme is compared with the disaster risk resistance of the transmission lines before and after its implementation to obtain the resilience enhancement result. Specifically, if the disaster risk resistance of the transmission lines before implementation is greater than that after implementation, it means that the current resilience enhancement scheme has failed to improve the system resilience and a new resilience enhancement scheme needs to be generated.

10. A transmission line resilience enhancement system for typhoon disasters, characterized in that, The system includes: The data acquisition module acquires wind speed and related data as the typhoon passes through power transmission lines based on distributed optical fiber. The vulnerable span screening module calculates the evaluation indicators of critical transmission channels based on wind speed, performs weighted calculations on the evaluation indicators to obtain the channel importance, and sorts them in descending order; selects the top k1 critical transmission channels corresponding to their importance to form a set of critical transmission channels; calculates the wind load sensitivity and structural wind resistance of each critical transmission channel span in the set based on relevant data; and performs weighted calculations of wind load sensitivity and structural wind resistance to obtain the span vulnerability. The final risk levels are obtained based on the importance of the transmission channel and the vulnerability of the span, and then sorted in descending order. The spans of the critical transmission channels corresponding to the top k2 final risk levels are selected to form a set of vulnerable spans. The resilience scheme generation module constructs a resilience enhancement model, including an objective function that minimizes the sum of the overall reinforcement cost of the transmission line, the local reinforcement cost of the span, and the typhoon load loss cost, and constraints constructed based on the set of vulnerable spans; it solves the resilience enhancement model to obtain and execute the resilience enhancement scheme.

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