A weather forecast-oriented method and system for predicting time-varying conductor outages

Abstract

The present invention belongs to the field of electric power, and in particular relates to a weather forecast-oriented method and system for predicting time-varying outages of conductors. The method comprises the following steps: calculating the dynamic current-carrying capacity value of the conductor at a future moment based on numerical weather forecasts and physical parameters of the conductor; calculating the outage risk value of the conductor based on the dynamic current-carrying capacity value and the static current-carrying capacity value; and calculating the time-varying outage prediction value of the conductor based on the failure frequency of the conductor and the repair time corresponding to the outage risk value. By calculating the dynamic current-carrying capacity value of the conductor at a future moment based on numerical weather forecasts and physical parameters of the conductor, the working state of the conductor can be predicted; calculating the outage risk value of the conductor based on the dynamic current-carrying capacity value and the static current-carrying capacity value can predict the possible working risk of the conductor; and calculating the time-varying outage prediction value of the conductor based on the failure frequency of the conductor and the repair time corresponding to the outage risk value, the time-varying outage risk of the conductor can be calculated to provide a reference for risk assessment of the scheduling plan.

Description

Technical Field

[0001] The present invention belongs to the field of electric power, and in particular relates to a weather forecast-oriented method and system for predicting time-varying outage of conductors. Background Art

[0002] The static ampacity of overhead lines is calculated based on the steady-state thermal balance equation and the conductor's maximum allowable operating temperature, using very conservative meteorological factors as boundary conditions. This pre-set boundary condition cannot dynamically reflect real-time changes in the line's operating status. In contrast to the static ampacity, the dynamic ampacity is calculated online using the conductor's thermal balance equation based on real-time meteorological parameters, providing a real-time reflection of the line's operating status.

[0003] Currently, dynamic current-carrying capacity (DCC) is not widely applied to overhead lines because conductor temperature measurement and micrometeorological parameter monitoring devices are not widely installed throughout the entire overhead line corridor. However, if grid dispatchers and substation operators can use relevant technologies to predict the dynamic DCC of overhead lines during the peak summer electricity demand period, this can provide a decision-making basis for scheduling and optimizing operation modes, thereby fully utilizing the dynamic DCC of overhead lines while ensuring their safe operation. Summary of the Invention

[0004] In order to solve or improve the above problems, the present invention provides a weather forecast-oriented method and system for predicting time-varying conductor outages. The specific technical solutions are as follows:

[0005] The present invention provides a weather forecast-oriented method for predicting time-varying outages of conductors, comprising: calculating a dynamic current-carrying capacity value of the conductor at a future moment based on numerical weather forecasts and physical parameters of the conductor; calculating an outage risk value of the conductor based on the dynamic current-carrying capacity value and a static current-carrying capacity value; and calculating a time-varying outage prediction value of the conductor based on a conductor failure frequency and a repair time corresponding to the outage risk value.

[0006] Preferably, calculating the dynamic current-carrying capacity value of the conductor at a future moment based on the numerical weather forecast and the conductor physical parameters includes: calculating the dynamic current-carrying capacity value of the conductor at a future moment based on the numerical weather forecast, the conductor physical parameters, and a conductor thermal balance equation; the conductor thermal balance equation is: in,

[0007] Where Tc is the conductor temperature, R(Tc) is the AC resistance per kilometer of the conductor at temperature Tc, I is the dynamic current carrying capacity of the conductor, Ta is the ambient temperature, π is the circumference of the conductor, D0 is the outer diameter of the conductor, σ Bis the Boltzmann constant, ε is the radiation coefficient of the conductor surface, ρ f is the relative air density, V δω is the predicted wind speed, θ S is the angle between the wind direction and the conductor, α is the heat absorption coefficient of the conductor surface, Q S is the intensity of sunlight on the Earth's surface.

[0008] Preferably, when the conductor temperature Tc is the maximum allowable operating temperature of the line, R(Tc) is a constant value.

[0009] Preferably, the future time includes a time within the next 24 hours; correspondingly,

[0010] The calculating of the dynamic current carrying capacity value of the conductor at a future moment according to the numerical weather forecast, the physical parameters of the conductor, and the conductor heat balance equation includes:

[0011] The dynamic current carrying capacity value of the conductor at a future moment is calculated according to the numerical weather forecast for the next 24 hours, the physical parameters of the conductor and the conductor heat balance equation.

[0012] Preferably, the maximum allowable operating temperature of the circuit is 70°.

[0013] Preferably, the time-varying outage prediction value of the conductor is calculated based on the conductor failure frequency and the repair time corresponding to the outage risk value, including: setting normal climate conditions and abnormal climate periods based on historical data, and obtaining the corresponding conductor failure probability and repair time of the outage event; setting weights for the probability of the normal climate condition and the probability of the abnormal climate period, and weighting the conductor failure probability and the repair time of the outage event to obtain the comprehensive conductor failure probability and the comprehensive conductor repair time; and calculating the time-varying outage prediction value of the conductor based on the comprehensive conductor failure probability and the comprehensive conductor repair time.

[0014] Preferably, the outage risk value of the conductor is calculated based on the dynamic current-carrying capacity value and the static current-carrying capacity value, including: determining the outage risk value of the conductor based on the magnitude by which the dynamic current-carrying capacity is greater than the static current-carrying capacity value; the outage risk value is used to describe the type, probability of occurrence and degree of hazard of an outage event.

[0015] Preferably, obtaining the corresponding conductor failure probability and repair time of the outage event includes:

[0016] The average failure frequency f of the conductor is obtained by the formula to , f to =f ad P ad +f no (1-P ad), the repair time r corresponding to the outage risk value to , r to =r ad P ad +r no (1-P ad );

[0017] Among them, f ad and f no are the conductor failure frequencies of the conductor under the severe climate conditions and the normal climate conditions in the area where the conductor is located, r ad and r no are the repair times corresponding to the outage risks under the severe climate conditions and the normal climate conditions, respectively, ad and (1-P ad ) is the probability of occurrence of the severe weather conditions and the normal weather conditions in the area where the conductor is located.

[0018] Preferably, the numerical weather forecast is derived from the WRF calculation model.

[0019] The present invention provides a weather forecast-oriented time-varying conductor outage prediction system, comprising:

[0020] The first unit is used to calculate the dynamic current carrying capacity value of the conductor at a future moment according to the numerical weather forecast and the physical parameters of the conductor;

[0021] A second unit is configured to calculate an outage risk value of the conductor according to the dynamic current carrying capacity value and the static current carrying capacity value;

[0022] The third unit is configured to calculate a time-varying outage prediction value of the conductor according to the conductor failure frequency and the repair time corresponding to the outage risk value.

[0023] The beneficial effects of the present invention are as follows: by calculating the dynamic current-carrying capacity value of the conductor at a future moment based on numerical weather forecasts and the physical parameters of the conductor, the working state of the conductor can be predicted; by calculating the outage risk value of the conductor based on the dynamic current-carrying capacity value and the static current-carrying capacity value, the possible working risk of the conductor can be predicted; based on the failure frequency of the conductor and the repair time of the outage risk value, the time-varying outage prediction value of the conductor is calculated, and the time-varying outage risk of the conductor can be calculated to provide a reference for risk assessment of the scheduling plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 is a schematic diagram of a weather forecast-oriented time-varying conductor outage prediction method according to the present invention;

[0025] Figure 2 2 is a schematic diagram of a weather forecast-oriented conductor time-varying outage prediction system according to the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] It will be understood that when used in this specification and the appended claims, the terms “comprises” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0028] It should also be understood that the terms used in the present specification are only for the purpose of describing particular embodiments and are not intended to limit the present invention. As used in the present 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.

[0029] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0030] In order to solve or improve the scheduling problem, the following Figure 1 A weather forecast-oriented method for predicting time-varying conductor outages is shown, comprising: S1, calculating the dynamic current-carrying capacity of the conductor at a future moment based on numerical weather forecasts and physical parameters of the conductor; S2, calculating the conductor outage risk value based on the dynamic current-carrying capacity value and the static current-carrying capacity value; and S3, calculating the time-varying conductor outage prediction value based on the conductor failure frequency and the repair time corresponding to the outage risk value.

[0031] Numerical weather prediction (NWP) involves using large computers to perform numerical calculations based on atmospheric conditions, under certain initial and boundary conditions, to solve the fluid dynamics and thermodynamics equations that describe weather evolution. This method aims to predict atmospheric motion and weather phenomena for a specific time period in the future. Outputs include temperature, humidity, precipitation, light intensity, and wind speed. Conductor physical parameters include the conductor's physical specifications and external environmental parameters, such as conductor length, diameter, elongation, strength, and heat resistance, as well as external environmental parameters such as temperature, humidity, precipitation, light intensity, and wind speed.

[0032] By combining numerical weather forecasts and conductor physical parameters with existing formulas, the dynamic current-carrying capacity of conductors at future times can be calculated. The specific existing formulas can be set based on different power operation theories or actual experience.

[0033] The static current-carrying capacity value is a property of the conductor itself, describing its current-carrying capacity or a value derived by adding other values ​​to the conductor's current-carrying capacity value. By comparing the dynamic current-carrying capacity value with the static current-carrying capacity value, it is determined whether the difference between the dynamic and static current-carrying capacity values ​​will cause a conductor outage. The outage risk value can include the probability, severity, and type of outage event.

[0034] Historical data / records can be used to determine the corresponding repair time for conductor failure frequency and outage risk. This data can then be used to calculate the conductor's time-varying outage prediction value. This time-varying outage prediction value describes the temporal changes in conductor-related outage events and the content of outage events in the power system.

[0035] Calculating the dynamic current-carrying capacity value of the conductor at a future moment based on the numerical weather forecast and the conductor physical parameters includes: calculating the dynamic current-carrying capacity value of the conductor at a future moment based on the numerical weather forecast, the conductor physical parameters, and a conductor thermal balance equation; the conductor thermal balance equation is: in,

[0036] Where Tc is the conductor temperature, R(Tc) is the AC resistance per kilometer of the conductor at temperature Tc, I is the dynamic current carrying capacity of the conductor, Ta is the ambient temperature, π is the circumference of the conductor, D0 is the outer diameter of the conductor, σ B is the Boltzmann constant, ε is the radiation coefficient of the conductor surface, ρ f is the relative air density, V δω is the predicted wind speed, θ S is the angle between the wind direction and the conductor, α is the heat absorption coefficient of the conductor surface, Q S is the intensity of sunlight on the Earth's surface.

[0037] When the conductor temperature Tc is the maximum allowable operating temperature of the line, R(Tc) is a constant value.

[0038] The value of the maximum allowable operating temperature of the line can be set by yourself. In this embodiment, there is a certain relationship between the maximum allowable operating temperature of the line and R(Tc), that is, when the conductor temperature Tc is the maximum allowable operating temperature of the line, R(Tc) is a fixed value.

[0039] The future moment includes a moment within the next 24 hours; correspondingly, calculating the dynamic current-carrying capacity value of the conductor at a future moment based on the numerical weather forecast, the physical parameters of the conductor, and the thermal balance equation of the conductor includes: calculating the dynamic current-carrying capacity value of the conductor at a future moment based on the numerical weather forecast for the next 24 hours, the physical parameters of the conductor, and the thermal balance equation of the conductor.

[0040] The maximum allowable operating temperature of the circuit is 70°.

[0041] In this embodiment, the conductor adopts steel core aluminum stranded wire, and the corresponding maximum allowable operating temperature of the line complies with Chinese regulations, that is, steel core aluminum stranded wire is 70 degrees Celsius (same as 70°).

[0042] The method of calculating the time-varying outage prediction value of the conductor based on the conductor failure frequency and the repair time corresponding to the outage risk value includes: setting normal climate conditions and abnormal climate periods based on historical data, and obtaining the corresponding conductor failure probabilities and repair times of outage events; setting weights for the probabilities of the normal climate conditions and the abnormal climate periods, and weighting the conductor failure probabilities and the repair times of the outage events to obtain a comprehensive conductor failure probability and a comprehensive conductor repair time; and calculating the time-varying outage prediction value of the conductor based on the comprehensive conductor failure probability and the comprehensive conductor repair time.

[0043] Power system conductors may be exposed to harsh or even catastrophic environments. Although these conditions are infrequent and of short duration, the probability of conductor failure increases significantly during these periods, and may lead to overlapping failures of multiple conductors or failure of the entire subsystem.

[0044] Harsh environments typically refer to unsuitable climatic conditions such as wind, rain, and snow, while catastrophic environments refer to natural disasters such as blizzards, tornadoes, fires, floods, and earthquakes. Because the probability of catastrophic environments and their impact can only be roughly estimated, it is difficult to develop accurate models for them.

[0045] For general climatic conditions, since meteorological statistics are always available, better simulation methods can be designed to analyze them. Traditionally, the climate is divided into two basic states: normal and severe. The probabilities of normal and severe climatic conditions can be calculated based on meteorological data. If the failure frequency and repair time of conductors under normal and severe climatic conditions can be distinguished, the system risk under the two climatic conditions can be assessed separately, and the final risk index is derived by weighting the probabilities of the two climatic conditions.

[0046] Historical data includes various data related to the power system, including climate-related data, such as temperature, humidity, wind speed, and light intensity. Based on these climate-related data and certain judgment indicators / thresholds, historical data can be divided into different data sets to describe the operation of the power system (mainly referring to the conductors in this embodiment) in different periods, namely, normal climate periods and abnormal climate periods.

[0047] Under the constraints of normal and abnormal weather periods, the corresponding conductor failure probabilities and outage repair times are obtained. The time periods corresponding to normal and abnormal weather periods constitute the complete power system operation cycle. The probabilities of each time period are calculated based on their proportion of the total cycle, and weights are assigned to the probabilities of normal and abnormal weather periods. These weights are then used to weight the conductor failure probabilities and outage repair times to obtain the comprehensive conductor failure probability and comprehensive conductor repair time. Combining the comprehensive conductor failure probability and comprehensive conductor repair time, the time-varying conductor outage prediction value is calculated.

[0048] Calculating the outage risk value of the conductor based on the dynamic current-carrying capacity value and the static current-carrying capacity value includes: determining the outage risk value of the conductor based on the magnitude by which the dynamic current-carrying capacity is greater than the static current-carrying capacity value; the outage risk value is used to describe the type, probability of occurrence, and degree of hazard of an outage event.

[0049] The method of obtaining the corresponding conductor failure probability and repair time of the outage event includes:

[0050] The average failure frequency f of the conductor is obtained by the formula to , f to =f ad P ad +f no (1-P ad ), the repair time r corresponding to the outage risk value to , r to =r ad P ad +r no (1-P ad );

[0051] Among them, f ad and f no are the conductor failure frequencies of the conductor under the severe climate conditions and the normal climate period in the area where the conductor is located, r ad and r no are the repair times corresponding to the outage risks under the severe weather conditions and the normal weather period, respectively, ad and (1-P ad) is the probability of occurrence of the severe weather conditions and the normal weather period in the area where the conductor is located.

[0052] When the conductor temperature Tc is the maximum allowable operating temperature of the line, 70°C, R(Tc) is a constant. By substituting the weather forecast data along the overhead line and the conductor operating parameters for the next 24 hours into the conductor thermal balance equation, the calculated value of the conductor's dynamic current-carrying capacity I for the next 24 hours at the maximum allowable operating temperature can be calculated.

[0053] According to the temperature T contained in the weather forecast data a The error between the actual temperature, forecast wind speed and actual wind speed. The ambient forecast temperature and forecast wind speed along the overhead line in the next 24 hours are Ta and V respectively. δω , then the line conductor dynamic current carrying capacity has maximum values ​​Imax and Imin. There is an error between the ideal value and the actual value provided by the weather forecast data, which is used to calculate the predicted value of the conductor dynamic current carrying capacity in the next 24 hours.

[0054] The dynamic current-carrying capacity of conductors can have significant errors, so the volatility of weather forecast data needs to be considered to improve the accuracy of predicted dynamic current-carrying capacity values. With the advancement of weather forecasting technology, 24-hour forecast intervals have become relatively accurate. Therefore, it can be assumed that actual weather forecast data is randomly distributed within the numerical forecast interval, and therefore the actual dynamic current-carrying capacity of overhead line conductors is also randomly distributed within the predicted dynamic current-carrying capacity interval. By considering that overhead lines follow a probability distribution set manually or determined based on historical experience under weather forecast conditions, a probabilistic outage model due to high temperature weather can be derived.

[0055] The numerical weather forecast is derived from the WRF calculation model.

[0056] The present invention provides Figure 2 A weather forecast-oriented conductor time-varying outage prediction system is shown, comprising:

[0057] The first unit is used to calculate the dynamic current carrying capacity value of the conductor at a future moment according to the numerical weather forecast and the physical parameters of the conductor;

[0058] A second unit is configured to calculate an outage risk value of the conductor according to the dynamic current carrying capacity value and the static current carrying capacity value;

[0059] The third unit is configured to calculate a time-varying outage prediction value of the conductor according to the conductor failure frequency and the repair time corresponding to the outage risk value.

[0060] Through numerical weather forecasts and conductor physical parameters, the dynamic current-carrying capacity of the conductor at future moments is predicted and compared with the static current-carrying capacity. When the dynamic current-carrying capacity is greater than or equal to the static current-carrying capacity, the conductor outage risk is determined. Based on the conductor failure frequency and the repair time corresponding to the outage risk, an outage prediction is made for the conductor to obtain a time-varying outage prediction result of the conductor. By considering that conductor-related parameters (such as operating parameters) obey a certain probability distribution under numerical weather forecasts, a probabilistic outage model caused by weather can be obtained, thereby predicting the time-varying outage results of the conductor under different weather conditions, thereby achieving early warning and reducing economic losses.

[0061] Numerical weather prediction (NWP) is a method based on the current state of the atmosphere. It uses mathematical models of the atmosphere, sets appropriate initial values ​​and boundary conditions, and utilizes large computers to perform numerical calculations on massive amounts of meteorological data. By solving the physical equations that describe weather evolution, the method predicts atmospheric motion and weather for a specific time period in the future. Currently, the following numerical weather prediction models are widely used: 1) WRF, the Weather Research and Forecasting Model, supported by the National Center for Meteorological Research, the National Oceanic and Atmospheric Administration, and the Air Force Weather Service; 2) RAMS, the Regional Atmospheric Model System, developed and researched by Colorado State University; 3) GEM-LAM, the Global Environmental Multiscale Limited Area Model, a Canadian meteorological service; 4) HIRLAM, the High-Resolution Limited Area Model, supported by the European Meteorological Cooperation Institute; and 5) ALADIN, supported by a consortium of several European and North African countries led by the French Meteorological Center. Because the WRF model comprehensively considers the influencing factors of micrometeorological processes, its forecasts include wind speed, temperature, solar radiation, humidity, and precipitation, and its relative error limit for these forecasts is 8%.

[0062] This embodiment uses the WRF numerical forecast product to obtain the meteorological environment data along the overhead line in the next 24 hours, and studies the current carrying capacity of the overhead line in the future. A method for predicting and calculating the dynamic current carrying value using the meteorological forecast parameters of the numerical weather forecast is proposed, which can provide a reference for emergency personnel to complete risk assessment in continuous high temperature weather without installing actual meteorological environment monitoring equipment. Of course, other methods can also be used when necessary.

[0063] Those skilled in the art will appreciate that the units of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0064] In the embodiments provided in the present application, it should be understood that the division of units is merely a logical function division, and there may be other division methods in actual implementation, for example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0065] Finally, 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 above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A weather forecast-oriented method for predicting time-varying conductor outages, characterized in that: include: Calculate the dynamic current carrying capacity of the conductor at future moments based on numerical weather forecasts and conductor physical parameters; The calculation of the dynamic current carrying capacity of the conductor at a future moment based on the numerical weather forecast and the physical parameters of the conductor includes: Calculating the dynamic current carrying capacity value of the conductor at a future moment according to the numerical weather forecast, the physical parameters of the conductor and the conductor heat balance equation; The heat balance equation of the conductor: ， Where, Tc is the conductor temperature, R(Tc) is the AC resistance per kilometer of the conductor at temperature Tc, when the conductor temperature Tc is the maximum allowable operating temperature of the line, R(Tc) is a constant value, I is the dynamic current carrying capacity of the conductor, Ta is the ambient temperature, π is the circumference of the circle, D0 is the outer diameter of the conductor, σ B is the Boltzmann constant, ε is the radiation coefficient of the conductor surface, ρ f is the relative air density, V δω is the predicted wind speed, θ S is the angle between the wind direction and the conductor, α is the heat absorption coefficient of the conductor surface, Q S is the intensity of sunlight on the Earth's surface; Calculating the outage risk value of the conductor according to the dynamic current carrying capacity value and the static current carrying capacity value; calculating the outage risk value of the conductor according to the dynamic current carrying capacity value and the static current carrying capacity value includes: determining an outage risk value of the conductor according to a magnitude by which the dynamic current-carrying capacity is greater than the static current-carrying capacity value; The outage risk value is used to describe the type, probability of occurrence and degree of harm of an outage event; Calculating a time-varying outage prediction value of the conductor based on the conductor failure frequency and the repair time corresponding to the outage risk value; calculating the time-varying outage prediction value of the conductor based on the conductor failure frequency and the repair time corresponding to the outage risk value includes: Based on historical data, set normal climate conditions and abnormal climate periods, and obtain the corresponding conductor failure probability and repair time of outage events; Setting weights for the probability of the normal weather condition and the probability of the abnormal weather period, and weighting the conductor failure probability and the repair time of the outage event to obtain a comprehensive conductor failure probability and a comprehensive conductor repair time; A time-varying outage prediction value of the conductor is calculated based on the comprehensive failure probability of the conductor and the comprehensive maintenance time of the conductor.

2. The weather forecast-oriented time-varying conductor outage prediction method according to claim 1, characterized in that: The future time includes the time within the next 24 hours; correspondingly, The calculating of the dynamic current carrying capacity value of the conductor at a future moment according to the numerical weather forecast, the physical parameters of the conductor, and the conductor heat balance equation includes: The dynamic current carrying capacity value of the conductor at a future moment is calculated according to the numerical weather forecast for the next 24 hours, the physical parameters of the conductor and the conductor heat balance equation.

3. The weather forecast-oriented time-varying conductor outage prediction method according to claim 1, characterized in that: The maximum allowable operating temperature of the circuit is 70°.

4. The weather forecast-oriented time-varying conductor outage prediction method according to claim 1, characterized in that: The method of obtaining the corresponding conductor failure probability and repair time of the outage event includes: The average failure frequency of the conductor is obtained by the formula , , the repair time corresponding to the outage risk value , ; Among them, f ad and f no are the conductor failure frequencies of the conductor under the severe climate conditions and the normal climate conditions in the area where the conductor is located, r ad and r no are the repair times corresponding to the outage risks under the severe climate conditions and the normal climate conditions, respectively, ad and (1-P ad ) is the probability of occurrence of the severe weather conditions and the normal weather conditions in the area where the conductor is located.

5. The weather forecast-oriented time-varying conductor outage prediction method according to claim 4, characterized in that: The numerical weather forecast is derived from the WRF calculation model.

6. A weather forecast-oriented conductor time-varying outage prediction system, characterized by: Using the method according to any one of claims 1 to 5, comprising: The first unit is used to calculate the dynamic current carrying capacity value of the conductor at a future moment according to the numerical weather forecast and the physical parameters of the conductor; A second unit is configured to calculate an outage risk value of the conductor according to the dynamic current carrying capacity value and the static current carrying capacity value; The third unit is configured to calculate a time-varying outage prediction value of the conductor according to the conductor failure frequency and the repair time corresponding to the outage risk value.

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