Power transmission line toughness evaluation method and system considering important load under ice disaster

Abstract

The invention relates to the technical field of power transmission lines, in particular to a power transmission line toughness evaluation method and system considering important loads under an ice disaster. The method comprises the following steps: firstly, constructing an icing thickness real-time growth model considering multiple parameters such as water-ice density, an ice precipitation rate, a wind speed and air water content, carrying out regionalization analysis on a power transmission line according to weather parameters such as the wind speed and the precipitation rate, respectively calculating a unit length fault rate of each section, and comprehensively obtaining an overall fault probability of the whole line; then establishing a toughness evaluation system comprising a disturbance performance index, a recovery speed index and an important load maximum loss index, and dividing the affected process into five stages of system normal operation, performance reduction, performance maintenance, preliminary recovery and complete recovery; and finally, carrying out normalization processing on the evaluation indexes, determining the weight by adopting an optimization algorithm, and calculating the toughness value of the system. The fault prediction accuracy and the system recovery efficiency are remarkably improved through regional analysis and multi-dimensional evaluation, and the power supply reliability of important loads is effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission lines, and in particular to a method and system for evaluating the resilience of power transmission lines taking into account important loads under ice disasters. Background Art

[0002] In the power system, facing extreme weather disturbances such as ice disasters, how to build an accurate and reliable resilience assessment model is crucial to ensure the safe and stable operation of the power system and specify an effective resilience improvement plan. Most of the existing transmission line failure models under ice disaster disturbances are single models for unit length lines, which do not take into account the locality of extreme weather. Specifically, different areas of the same line may have significant differences in weather parameters such as wind speed and precipitation rate due to factors such as geographical location, altitude, and surrounding environment. This difference will directly affect the icing of the line and thus affect its failure rate. Therefore, in order to accurately assess the impact of ice disasters on the power system, it is necessary to divide and calculate the lines according to weather parameters.

[0003] The existing system resilience assessment indicators only consider the performance of the entire system, while ignoring the study of important loads such as hospitals, whose power supply stability and reliability are crucial to the normal operation of society. Therefore, when constructing a resilience assessment model, it is necessary to fully consider the particularity of these important loads and incorporate them into the assessment system. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to solve the problem that the existing system resilience evaluation indicators only consider the performance of the entire system, while ignoring the study of important loads such as hospitals, whose power supply stability and reliability are crucial to the normal operation of society. Therefore, when constructing a resilience evaluation model, it is necessary to fully consider the particularity of these important loads and incorporate them into the evaluation system.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster, which includes constructing a transmission line disconnection failure rate model and performing regional analysis on the line;

[0008] Establish a disaster-affected system resilience assessment index system to evaluate various system performance indicators;

[0009] The system resilience value is calculated based on the evaluation indicators and weights.

[0010] As a preferred solution of the method for evaluating the resilience of a power transmission line taking into account important loads under ice disasters of the present invention, the transmission line disconnection failure rate model includes:

[0011] A real-time ice thickness growth model was established, which takes into account parameters such as water ice density, ice precipitation rate, wind speed and air moisture content;

[0012] Calculate line ice thickness in real time based on meteorological parameters;

[0013] Assess line failure risk based on ice thickness data.

[0014] As a preferred solution of the power transmission line resilience assessment method taking into account important loads under ice disasters of the present invention, the line break failure rate model further includes: dividing the power transmission line into multiple sections according to weather parameters such as wind speed and precipitation rate;

[0015] Calculate the failure rate per unit length of each section separately;

[0016] Taking into account the length and failure rate of each section, the overall failure probability of the entire line is obtained.

[0017] As a preferred solution of the method for evaluating the resilience of a power transmission line taking into account important loads under ice disasters of the present invention, the resilience evaluation index includes:

[0018] Disturbance performance index: used to evaluate the degree of impact of ice disasters on the system;

[0019] Recovery speed index: used to measure the system's ability to recover from failures;

[0020] Maximum loss index of important loads: used to evaluate the power supply reliability of critical loads.

[0021] As a preferred solution of the method for evaluating the resilience of a power transmission line taking into account important loads under ice disasters of the present invention, the calculation of the evaluation index includes:

[0022] The disturbance performance index is calculated by comparing the actual performance of the system when it is disturbed with the normal operating performance;

[0023] The recovery speed index is determined by calculating the ratio of system recovery time to fault duration;

[0024] The important load loss index is determined by analyzing the ratio of the minimum power supply of important loads during the disaster period to the normal total load.

[0025] As a preferred solution of the method for evaluating the resilience of a power transmission line taking into account important loads under ice disasters of the present invention, the disaster process is divided into five time nodes and four stages:

[0026] Normal system operation stage;

[0027] Performance degradation stage;

[0028] Performance maintenance phase;

[0029] Initial recovery phase;

[0030] Full recovery phase.

[0031] As a preferred solution of the method for evaluating the resilience of a power transmission line taking into account important loads under ice disasters of the present invention, the calculation of the system resilience value includes:

[0032] Normalize the three evaluation indicators;

[0033] Use optimization algorithm to determine the weight of each indicator;

[0034] The final system resilience value is obtained through weighted calculation. The closer the value is to 1, the better the system resilience.

[0035] In a second aspect, an embodiment of the present invention provides a transmission line resilience assessment system taking into account important loads under ice disasters, which includes a fault prediction module construction module, constructs a transmission line disconnection failure rate model, and performs regional analysis on the line;

[0036] The indicator calculation module establishes an indicator system for disaster-affected system resilience assessment, which is used to evaluate various performance indicators of the system;

[0037] The resilience assessment module calculates the system resilience value based on the assessment indicators and weights.

[0038] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the method for assessing the resilience of a transmission line taking into account important loads under an ice disaster as described in the first aspect of the present invention are implemented.

[0039] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the method for assessing the resilience of a transmission line taking into account important loads under an ice disaster as described in the first aspect of the present invention are implemented.

[0040] The beneficial effects of the present invention are as follows: the present invention establishes a transmission line disconnection failure rate model under ice disasters, taking into account comprehensive performance, response speed, and the loss of important loads, and can comprehensively and accurately evaluate the impact of ice disasters on the power system. A real-time growth model of ice thickness that divides different areas is constructed. This method can track the impact of ice disasters on transmission lines in real time, and dynamically adjust evaluation indicators and weights according to actual conditions to make the evaluation results more accurate. This method takes into account transmission lines with important loads when conducting evaluations, and can more accurately reflect the performance of key lines in ice disasters, providing strong support for the optimized operation and emergency response of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 A flow chart of the method for assessing the resilience of transmission lines taking into account important loads under ice disasters;

[0043] Figure 2 Computer equipment diagram for the method of evaluating the resilience of power transmission lines taking into account important loads under ice disasters;

[0044] Figure 3 This is a simplified line graph of the disturbance caused by ice disasters on the system, which is a method for evaluating the resilience of transmission lines taking into account important loads during ice disasters. DETAILED DESCRIPTION

[0045] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0046] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0047] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0048] Example 1

[0049] Reference Figure 1 to Figure 3 , which is the first embodiment of the present invention, provides a method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster, including:

[0050] S100: Construct a transmission line disconnection failure rate model and conduct regional analysis of the lines;

[0051] S101: Transmission line disconnection failure rate model includes:

[0052] A real-time ice thickness growth model was established, which takes into account parameters such as water ice density, ice precipitation rate, wind speed and air moisture content;

[0053] Calculate line ice thickness in real time based on meteorological parameters;

[0054] Assess line failure risk based on ice thickness data.

[0055] S102: The line disconnection failure rate model further includes: dividing the transmission line into a plurality of sections according to weather parameters of wind speed and precipitation rate;

[0056] Calculate the failure rate per unit length of each section separately;

[0057] Taking into account the length and failure rate of each section, the overall failure probability of the entire line is obtained.

[0058] According to existing research, the freezing rain model is used to establish an ice thickness model:

[0059]

[0060] Where: R ice (t) is the ice thickness on the line at time t, ρ I and ρ W are the densities of water and ice, respectively, P I (t) is the ice precipitation rate at time t, ν w (t) is the wind speed at the location of the transmission line at time t, W(t) is the water content in the air at time t, and the calculation formula of W(t) is usually:

[0061] W(t)=0.067P I (t) 0.846

[0062] S103. The present invention calculates the failure probability of the transmission line per unit length based on the ice coverage thickness. Since the wind speed, precipitation rate and other parameters at different locations are different, the ice coverage thickness is also different. Therefore, the transmission line is divided into N sections according to different weather conditions. The failure rate model per unit length of the i-th section of the line at time tj is:

[0063]

[0064] In the formula, R i (t j ) is the ice thickness of the i-th line at time tj, R li Design of ice thickness threshold for transmission lines, 5R li It is the maximum ice thickness that the transmission line can withstand.

[0065] Discretizing time, the failure probability of the i-th line during the disaster period is:

[0066]

[0067] Where N t is the number of discrete time divisions, Δt j is the length of the jth discrete time segment.

[0068] The failure probability of the entire line during the disaster period is:

[0069]

[0070] Where, L i is the length of the i-th line segment.

[0071] S200: Establish a disaster-affected system resilience assessment index system to evaluate various system performance indicators;

[0072] S201: Resilience assessment indicators include:

[0073] Disturbance performance index: used to evaluate the degree of impact of ice disasters on the system;

[0074] Recovery speed index: used to measure the system's ability to recover from failures;

[0075] Maximum loss index of important loads: used to evaluate the power supply reliability of critical loads.

[0076] S202. Simplify the disturbance of the ice disaster to the system as shown in the attached figure. Figure 3 As shown, it is divided into five time nodes and four stages:

[0077] T0-T1: At T0, the ice disaster disturbance begins. Due to the system's own anti-interference ability, the disturbance does not cause the system performance to decline, that is, it can still maintain the performance under normal operating conditions.

[0078] T1-T2: The impact of the disaster continues to increase. At T1, the system performance begins to decline and continues to decline until it reaches the lowest point at T2.

[0079] T2-T3: Disaster interference no longer degrades system performance, but the system's automatic response and operators do not perform corresponding recovery operations.

[0080] T3-T4: At T3, the system recovery operation begins and the performance gradually recovers.

[0081] T4-T5: At T4, the disaster has been mitigated to the point where it no longer affects the system, and recovery operations continue until normal conditions are restored at T5.

[0082] S203. The present invention proposes three performance indicators to evaluate the resilience of the system during a disaster.

[0083] 1. Disturbance performance index: The performance ratio of the system during the disturbance, from the beginning of the disturbance until the system returns to normal operating performance.

[0084]

[0085] In the formula, E(·) is the mathematical expectation, AL(t) is the actual performance curve of the system after being disturbed by ice disasters, and IL(t) is the performance curve under normal operation. The larger the index is, the less the system is disturbed by ice disasters.

[0086] 2. Recovery speed index: the ratio of interference duration to recovery duration.

[0087]

[0088] The larger the indicator is, the faster the recovery speed is.

[0089] 3. Maximum loss of important loads: the maximum loss of important loads during the entire disaster period.

[0090]

[0091] In the formula, Ls,min is the minimum important load of the system during the disaster period, and Ls,total is the total important load under normal system operation. The larger the index is, the smaller the loss of important load is.

[0092] S300: Calculate the system resilience value based on the evaluation indicators and weights.

[0093] S301: Calculation of evaluation indicators includes:

[0094] The disturbance performance index is calculated by comparing the actual performance of the system when it is disturbed with the normal operating performance;

[0095] The recovery speed index is determined by calculating the ratio of system recovery time to fault duration;

[0096] The important load loss index is determined by analyzing the ratio of the minimum power supply of important loads during the disaster period to the normal total load.

[0097] S302: Divide the disaster process into five time nodes and four stages:

[0098] Normal system operation stage;

[0099] Performance degradation stage;

[0100] Performance maintenance phase;

[0101] Initial recovery phase;

[0102] Full recovery phase.

[0103] S303: Calculation of system resilience value includes:

[0104] Normalize the three evaluation indicators;

[0105] Use optimization algorithm to determine the weight of each indicator;

[0106] The final system resilience value is obtained through weighted calculation. The closer the value is to 1, the better the system resilience.

[0107] Preferably, the weights corresponding to the above three indicators are ω i ,ω s ,ω l , the sum of the three is 1, and the Pareto optimal solution is calculated using a mathematical optimization algorithm.

[0108] S302. The present invention uses weighted Euclidean distance to calculate system resilience:

[0109]

[0110] In the formula, The coordinate values ​​of the three indicators after normalization in this evaluation system are as follows. In this process, the origin is considered to be the optimal point of toughness. The closer the result of this calculation method is to 1, the better the toughness of the system, and vice versa.

[0111] Furthermore, this embodiment also provides a transmission line resilience assessment system taking into account important loads under ice disasters, including:

[0112] The fault prediction module builds a module to construct a transmission line disconnection failure rate model and conduct regional analysis of the line;

[0113] The indicator calculation module establishes an indicator system for disaster-affected system resilience assessment, which is used to evaluate various performance indicators of the system;

[0114] The resilience assessment module calculates the system resilience value based on the assessment indicators and weights.

[0115] In summary, by establishing a real-time growth model of ice thickness that takes into account multiple parameters such as water ice density, ice precipitation rate, wind speed and air moisture content, and combining it with a regional analysis method, an accurate assessment of the fault risk in different sections of the same transmission line is achieved, thereby overcoming the defect that a single model in the existing technology cannot adapt to geographical differences and achieving the effect of improving the accuracy of fault prediction.

[0116] Specifically, it can track the development trend of ice disasters in real time, accurately reflect geographical differences, and dynamically assess fault risks.

[0117] By constructing a multi-dimensional evaluation system that includes disturbance performance indicators, recovery speed indicators and maximum loss indicators of important loads, a comprehensive quantitative evaluation of system resilience is achieved, which solves the problem that existing technologies only focus on overall performance and ignore important loads, and achieves the effect of differentiated evaluation.

[0118] Specifically, it is reflected in: quantitative assessment of the degree of system disturbance; objective measurement of recovery capabilities; and highlighting the degree of protection of important loads.

[0119] By dividing the disaster process into five time nodes and four stages and adopting a weighted Euclidean distance calculation method, a dynamic assessment of system resilience is achieved, overcoming the shortcomings of existing technical assessment methods that are too static and one-sided, and achieving a more scientific and reasonable assessment result.

[0120] Regional analysis not only improves the accuracy of the assessment, but also unexpectedly finds that it can be used to guide differentiated reinforcement strategies and achieves coordinated optimization of assessment and protection. The five-stage division was originally used in the assessment process, and unexpectedly formed an early warning mechanism and increased the system's active defense capabilities.

[0121] Originally aimed at power supply reliability assessment, it has been extended to include social impact assessment function, providing a scientific basis for policy making.

[0122] This invention comprehensively improves the scientificity and accuracy of transmission line resilience assessment by constructing a regionalized line failure rate model, establishing a multi-dimensional evaluation index system, and realizing dynamic resilience calculation. This method can not only accurately assess the impact of ice disasters on the transmission system, but also provide reliable technical support for the optimized operation and emergency management of the power system through early warning functions and the formulation of differentiated strategies, which has important practical significance.

[0123] Example 2

[0124] Reference Figure 1 - Figure 3 , which is the second embodiment of the present invention, and this embodiment provides a method for evaluating the resilience of a transmission line taking into account important loads under an ice disaster. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0125] In order to verify the effectiveness and practicality of the method of the present invention, a large-scale ice disaster event that occurred in a certain province in January 2023 was selected as the research object. The impact area of ​​this ice disaster covered an area of ​​about 12,000 square kilometers in the eastern mountainous area of ​​the province, causing 35 500kV transmission lines and 86 220kV transmission lines to be damaged to varying degrees. In this experiment, one of the 500kV transmission lines (numbered NGQ-5321) across the mountainous area was selected for resilience assessment research. The line is 186 kilometers long and spans three meteorological zones. There are two large hospitals, a chemical park and other important load facilities along the line.

[0126] First, based on meteorological station data and geographic information, the line was divided into five characteristic sections: plain section (0-42km), hilly transition section (42-78km), mountain section (78-126km), canyon section (126-156km) and mountain exit section (156-186km). By analyzing historical meteorological data, an ice growth model for each section was established. High-precision real-time data from meteorological stations was used in the experiment, including hourly temperature, wind speed, precipitation rate and atmospheric moisture content.

[0127] Parameters were set according to the terrain characteristics of each section: the average wind speed in the plain section was 4.2m / s, and the precipitation rate was 0.8mm / h; the average wind speed in the mountain section was 8.6m / s, and the precipitation rate was 2.1mm / h; due to the terrain effect, the maximum wind speed in the canyon section reached 12.3m / s, and the precipitation rate was 2.8mm / h. Based on these parameters, the improved ice growth model was used to calculate the ice thickness in each section, and the failure risk was evaluated in real time.

[0128] In terms of the construction of the evaluation index system, differentiated weights are set according to the power supply needs of important loads: the power supply reliability weight of hospitals and chemical parks is 0.5, the weight of industrial loads is 0.3, and the weight of ordinary users is 0.2. At the same time, the entire ice disaster process is divided into five key time nodes for dynamic monitoring: T0 (ice disaster begins) - 0h, T1 (performance begins to decline) - 6h, T2 (reaches the lowest point) - 18h, T3 (begins to recover) - 24h, T4 (basic recovery) - 36h.

[0129] Table 1 Comparison of meteorological parameter data between our scheme and various models

[0130]

[0131] Through the comparative analysis of the experimental data in Table 1 above, the method of the present invention is significantly superior to the existing technical solutions in multiple key indicators:

[0132] Improved fault prediction capabilities: The prediction accuracy rate increased from 72.3% of the traditional single model to 94.6%, an increase of 22.3 percentage points; the warning lead time was extended from 2.1 hours to 6.8 hours, an increase of 4.7 hours; providing more sufficient time for emergency plan preparation.

[0133] Important load protection effect:

[0134] Power supply reliability increased from 85.6% to 97.8%, an increase of 12.2 percentage points; in particular, key facilities such as hospitals and chemical parks have achieved near-round-the-clock power supply guarantees; system recovery time was shortened by 41.7%, from 48 hours to 28 hours;

[0135] The system resilience is comprehensively improved: the resilience index value is increased from 0.683 to 0.926, an increase of 35.6%; the resource utilization rate is increased from 65.8% to 91.3%, an increase of 25.5 percentage points; this reflects the adaptability and reliability of the invention in extreme weather conditions;

[0136] These significant improvements are due to three innovations of the present invention:

[0137] First, the regional analysis method overcomes the limitations of the traditional single model. By dividing the transmission line into five characteristic sections and establishing ice growth models for each section, the fault prediction is more in line with the actual situation. Especially in the canyon section, the prediction accuracy is nearly 30% higher than the traditional model due to the consideration of the wind speed amplification effect caused by the terrain.

[0138] Second, the multi-dimensional evaluation index system achieves a comprehensive characterization of system performance. By introducing indicators in three dimensions: disturbance performance, recovery speed, and loss of important loads, and adopting a dynamic weight adjustment mechanism, the evaluation results are made more objective and comprehensive. Experimental data show that this method performs significantly better than other solutions in terms of power supply reliability of important loads.

[0139] Third, the five-stage dynamic assessment mechanism provides more accurate decision-making support. By dividing the ice disaster process into key time nodes and adopting different assessment strategies at each stage, refined management of the system status is achieved. This method significantly increases the advance warning time and wins valuable time for emergency response.

[0140] In order to verify the effectiveness of the method of the present invention, a second simulation experiment was conducted, and a severe ice disaster event that occurred in a certain province from January 12 to January 18, 2023 was selected as the research object. The ice disaster caused the cumulative ice thickness in the area to reach 32mm-56mm, and the affected area was about 12,000 square kilometers. In this experiment, a 500kV transmission line (NGQ-5321) across the mountainous area was selected for resilience assessment research. The line is 186 kilometers long, with 15 meteorological monitoring stations along the line. The loads include: 2 Class A hospitals (power consumption 54MW), 1 chemical park (power consumption 85MW), 3 industrial parks (total power consumption 156MW), etc.

[0141] 1. Meteorological parameter monitoring:

[0142] The line is divided into five characteristic sections according to the terrain characteristics. The meteorological parameters of each section are as follows:

[0143] 1.1 Plain section (0-42km): Temperature: -5℃ to -2℃; Wind speed: 3.8-4.6m / s; Precipitation rate: 0.6-0.9mm / h; Relative humidity: 85%~92%; Atmospheric pressure: 101.2-101.8kPa.

[0144] 1.2 Mountainous section (78-126km): Temperature: -8℃ to -4℃; Wind speed: 7.8-9.2m / s; Precipitation rate: 1.8-2.4mm / h; Relative humidity: 88%~95%; Atmospheric pressure: 98.4-99.2kPa.

[0145] 1.3 Canyon section (126-156km): Temperature: -7℃ to -3℃; Wind speed: 11.5-13.8m / s (maximum wind speed at the valley entrance is 15.2m / s); Precipitation rate: 2.5-3.2mm / h; Relative humidity: 90%~97%; Atmospheric pressure: 97.8-98.6kPa.

[0146] 2. Calculation of ice thickness

[0147] Calculation results based on the improved ice growth model:

[0148] δ(t)=0.35ρw / ρiΔ*P(t)*v(t)Δ*w(t)*t

[0149] The 24-hour ice growth data of typical sections are as follows:

[0150] Plain section: 15.8mm→18.2mm→21.5mm→23.8mm;

[0151] Mountain area: 22.4mm→28.6mm→35.2mm→42.5mm;

[0152] Canyon section: 26.8mm→34.5mm→42.8mm→51.6mm.

[0153] 3. Failure rate calculation example

[0154] Taking the canyon section as an example, the failure rate per unit length λ(t) at t = 18h is:

[0155] λ(t)=0.0023*(δ(t) / δc) 2.35 =0.0023*(42.8 / 25) 2.35 =0.0085 times / km·h

[0156] Table 2 Comparison of meteorological parameter prediction accuracy

[0157]

[0158] Table 3 System performance evaluation results

[0159]

[0160]

[0161] Table 4 Economic Benefit Analysis

[0162]

[0163] Compared with the prior art, the method of the present invention has achieved significant technical progress:

[0164] Prediction accuracy: Through regional analysis and multi-parameter dynamic monitoring, the present invention has achieved a major breakthrough in the prediction of key meteorological parameters:

[0165] The temperature prediction error was reduced by 83.3% (from ±1.8℃ to ±0.3℃); the wind speed prediction error was reduced by 80.8% (from ±2.6m / s to ±0.5m / s); and the icing prediction error was reduced by 85.9% (from ±8.5mm to ±1.2mm).

[0166] System performance improvement

[0167] The multi-dimensional evaluation system has significantly improved the overall performance of the system: the accuracy of fault prediction has increased by 34.5% to 96.2%; the reliability of power supply to important loads has increased by 19.6% to 98.4%; the average system recovery time has been shortened by 50%, from 52 hours to 26 hours; and the advance warning time has increased by 227.3%, from 2.2 hours to 7.2 hours.

[0168] Improved economic benefits

[0169] The implementation of the present invention brings significant economic benefits: fault repair costs are reduced by 50.2% (from 2.85 million yuan to 1.42 million yuan); load losses are reduced by 73.8% (from 1856 MWh to 486 MWh); and overall economic losses are reduced by 68.3% (from 12.13 million yuan to 3.85 million yuan).

[0170] By dividing the line into characteristic sections and establishing a differentiated model, the limitations of the traditional single model are overcome. In particular, in the canyon section, the prediction accuracy is significantly improved by taking into account the wind speed amplification effect caused by the terrain (the maximum wind speed reaches 15.2m / s). Calculations show that in this section:

[0171] The traditional model predicts the ice thickness: 36.5 mm; the actual ice thickness: 51.6 mm; the present invention predicts the ice thickness: 50.8 mm; the prediction error is reduced by 93.4%.

[0172] Dynamic evaluation mechanism

[0173] The five-stage division combined with dynamic weight adjustment enables refined management of system status:

[0174] T0-T1 stage (0-6h): focus on early warning indicators; T1-T2 stage (6-18h): strengthen fault prediction; T2-T3 stage (18-24h): optimize resource allocation

[0175] T3-T4 stage (24-36h): accelerate system recovery.

[0176] Through experimental verification, the present invention not only achieves a comprehensive breakthrough in technical indicators, but also demonstrates significant economic benefits and social value in practical applications, providing reliable technical support for ice disaster prevention and control in power systems.

[0177] Example 3

[0178] This embodiment also provides a computer device, which is applicable to a method for evaluating the resilience of a transmission line taking into account important loads during an ice disaster, and includes a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement a forced oscillation detection and positioning method for a distribution network as proposed in the above embodiment.

[0179] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, a forced oscillation detection and positioning method for a distribution network is implemented as proposed in the above embodiment.

[0180] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0181] If the function 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 technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0182] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0183] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0184] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0185] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster, characterized in that: include, Construct a transmission line disconnection failure rate model and conduct regional analysis of the lines; Establish a disaster-affected system resilience assessment index system to evaluate various system performance indicators; The system resilience value is calculated based on the evaluation indicators and weights.

2. The method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster as claimed in claim 1, characterized in that: The transmission line disconnection failure rate model includes: A real-time ice thickness growth model was established, which takes into account parameters such as water ice density, ice precipitation rate, wind speed and air moisture content; Calculate line ice thickness in real time based on meteorological parameters; Assess line failure risk based on ice thickness data.

3. The method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster as claimed in claim 2, characterized in that: The line disconnection failure rate model further includes: dividing the transmission line into a plurality of sections according to weather parameters of wind speed and precipitation rate; Calculate the failure rate per unit length of each section separately; Taking into account the length and failure rate of each section, the overall failure probability of the entire line is obtained.

4. The method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster as claimed in claim 3, characterized in that: The toughness evaluation indicators include: Disturbance performance index: used to evaluate the degree of impact of ice disasters on the system; Recovery speed index: used to measure the system's ability to recover from failures; Maximum loss index of important loads: used to evaluate the power supply reliability of critical loads.

5. The method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster as claimed in claim 4, characterized in that: The calculation of the evaluation index includes: The disturbance performance index is calculated by comparing the actual performance of the system when it is disturbed with the normal operating performance; The recovery speed index is determined by calculating the ratio of system recovery time to fault duration; The important load loss index is determined by analyzing the ratio of the minimum power supply of important loads during the disaster period to the normal total load.

6. The method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster as claimed in claim 5, characterized in that: The disaster process is divided into five time nodes and four stages: Normal system operation stage; Performance degradation stage; Performance maintenance phase; Initial recovery phase; Full recovery phase.

7. The method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster as claimed in claim 6, characterized in that: The calculation of the system toughness value includes: Normalize the three evaluation indicators; Use optimization algorithm to determine the weight of each indicator; The final system resilience value is obtained through weighted calculation. The closer the value is to 1, the better the system resilience.

8. A transmission line resilience assessment system taking into account important loads under ice disasters, based on the transmission line resilience assessment method taking into account important loads under ice disasters according to any one of claims 1 to 7, characterized in that: Also includes, The fault prediction module builds a module to construct a transmission line disconnection failure rate model and conduct regional analysis of the line; The indicator calculation module establishes an indicator system for disaster-affected system resilience assessment, which is used to evaluate various performance indicators of the system; The resilience assessment module calculates the system resilience value based on the assessment indicators and weights.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for evaluating the resilience of a power transmission line taking into account important loads under an ice disaster as described in any one of claims 1 to 7 are implemented.

Images