A phased icing process determination and icing amount updating method

Abstract

The application discloses a phased icing process determination and icing amount updating method, establishes a WRF multi-layer nested numerical simulation system, obtains hourly near-surface air temperature, relative humidity, 10m wind speed and total radiation irradiance of a target area; generates icing development, ablation and retention criteria based on the above elements, and performs state transition according to the priority of first judging icing development, then judging ablation under existing icing, and finally judging retention under existing icing, to obtain non-icing, development, retention and ablation states; then, according to the states, the Makkonen model is called to calculate the growth amount, maintain or weakly correct the icing amount, and calculate the decay amount according to the air temperature, radiation and humidity, and the icing thickness is updated through mass-thickness conversion. The method can reduce the thickness error accumulation under non-icing conditions, and improve the continuity and interpretability of the icing simulation of the mountainous power transmission line.

Description

Technical Field

[0001] This application relates to the field of power transmission line technology, and more specifically, to a method for determining the staged icing process and updating the icing amount. Background Technology

[0002] Icing on transmission lines is one of the major hazards affecting the safe operation of power grids, especially in high-altitude and complex mountainous conditions, where the icing process is characterized by strong locality, rapid changes, and long duration. Currently, early warning and simulation methods for transmission line icing mainly include discrimination methods based on empirical thresholds or icing levels, dynamic estimation methods based on micro-meteorological monitoring, thickness prediction methods based on machine learning, and physical growth calculation methods based on the Makkonen model. Methods based on empirical thresholds or icing levels utilize air temperature, humidity, wind speed, precipitation, topography, and historical icing data to establish discrimination rules, which can identify icing risks to a certain extent. However, their output usually stops at whether icing has occurred or the icing risk level, lacking a phased description of the entire icing process. Directly using these methods in numerical simulations can easily lead to incorrect thickness accumulation or deviations in the start and end times of the process.

[0003] Dynamic estimation methods based on micrometeorological monitoring rely on field sensor data and are highly capable of characterizing icing processes at single points or a few observation points. However, they are highly dependent on monitoring deployment, have limited spatial coverage, and struggle to generate continuous spatial distribution simulation results in corridors without observation stations or during future forecast periods. They are more suitable as a means of verification or correction. Machine learning-based icing thickness prediction methods can establish a nonlinear mapping between meteorological parameters and thickness using historical samples. They have good fitting ability when there are sufficient samples and stable station conditions. However, they lack physical interpretability, have limited cross-regional generalization ability, and only output thickness values ​​without determining process stages. Even if the thickness fitting error is small, unreasonable continuous growth or melting delays may occur in the physical process.

[0004] The Makkonen icing model is a widely used classic physical model in atmospheric icing research. It calculates the amount of icing growth per unit time using parameters such as liquid water content, wind speed, conductor diameter, collision efficiency, and freezing efficiency, and has a clear physical basis. However, this model mainly addresses how to calculate the growth under given icing meteorological conditions, and does not directly address the process control issues of when to start the calculation, when to stop growth, when to enter the maintenance phase, and when to melt. Existing studies have attempted to couple the WRF numerical weather prediction model with the Makkonen model, using meteorological elements output by the WRF to drive the calculation of icing growth. However, existing coupling frameworks mostly focus on meteorological inputs and thickness growth, and do not fully utilize the role of output elements in the control of icing occurrence, development, maintenance, and melting. Especially under complex mountainous conditions, total irradiance has a significant impact on icing maintenance and melting, while traditional discrimination methods often emphasize temperature, humidity, wind speed, or precipitation, and do not adequately consider radiation factors. Overall, existing technologies lack a method that addresses the entire numerical simulation process, integrates localized observation criteria from typical ice observation stations, and can explicitly control the transition of icing states, making it difficult to meet the actual needs of dynamic icing simulation for transmission lines in complex mountainous areas. Summary of the Invention

[0005] The purpose of this application is to overcome the shortcomings of existing technologies and provide a method for determining the icing process and updating the icing amount in stages. This method can identify the beginning, development, maintenance, melting and end stages of the icing process, avoid the erroneous accumulation of icing thickness under non-icing conditions, and improve the accuracy, continuity and interpretability of numerical simulation of icing of transmission lines in complex mountainous areas.

[0006] The objective of this application is achieved through the following technical solution: Firstly, this application proposes a method for determining the staged icing process and updating the icing amount, including: Step S1: Establish a WRF multi-layer nested numerical simulation system to obtain hourly meteorological elements for the target area. The hourly meteorological elements should include at least near-surface air temperature. Near-ground relative humidity (RH) and wind speed at 10m and total radiation irradiance R; Step S2: Generate icing development criteria based on hourly meteorological elements. Criteria for ice melting Maintaining the criteria for icing The icing state S(t) at time t is determined by prioritizing the development of icing, the melting of existing icing, and the retention of existing icing. The icing state includes the non-icing state S0, the icing development stage S1, the icing retention stage S2, and the icing melting stage S3. Step S3: Select the corresponding ice accumulation update strategy according to S(t), update the ice accumulation mass M(t) and / or ice accumulation thickness I(t) at time t, and output the ice accumulation stage sequence and ice accumulation thickness time series results; When S(t) = S1, the Makkonen icing model is used to calculate the icing growth. The amount of ice accumulation will be added to the ice accumulation at the previous moment; When S(t) = S2, maintain the icing amount from the previous moment, or adjust according to the preset weak change correction amount. Update icing volume, among which Set to 0 or be determined by the preset sublimation / deposition correction model; When S(t) = S3, according to the near-surface air temperature Calculate the icing attenuation based on total irradiance R and near-surface relative humidity RH. And update the icing amount according to the non-negative constraint.

[0007] In one possible embodiment, near-surface air temperature 2-meter air temperature output by the WRF multi-layer nested numerical simulation system This indicates that corrections may be made based on the actual installation height of the conductor and the corresponding mode layer temperature. The near-surface relative humidity RH is directly output by the WRF multi-layer nested numerical simulation system, or calculated based on the water vapor mixing ratio, temperature and air pressure output by WRF. 10m wind speed 10-meter zonal wind output by WRF and the wind Synthesis, calculation formula is And convert it into an effective wind speed V perpendicular to the conductor axis based on the direction of the conductor; The total irradiance R is represented by the downward shortwave radiation SWDOWN output from the WRF.

[0008] In one possible embodiment, the icing development stage indicates that meteorological conditions are favorable for icing formation or an increase in icing thickness; The icing retention phase indicates that icing has formed and meteorological conditions are favorable for the continuation of icing. The icing melting stage indicates that rising temperature, decreasing humidity, or enhanced radiation leads to a reduction in icing thickness. The non-icing state indicates that the baseline state does not meet the control conditions related to the occurrence, maintenance, or melting of icing.

[0009] In one possible embodiment, the criterion for determining the icing development stage in step S2 is: near-surface air temperature. Temperature ≤-2℃, near-ground relative humidity RH≥85%, total irradiance R≤150W / m², and wind speed 10m ≥3m / s.

[0010] In one possible embodiment, the conditions for entering or maintaining the icing retention stage in step S2 are: Ice has already formed, and the following conditions are met simultaneously: near-surface air temperature ≤0℃, near-ground relative humidity RH>80%, and total irradiance R<500W / m².

[0011] In one possible embodiment, the criterion for determining the ice melting stage in step S2 is: Icing has already occurred, and any one of the following conditions is met: near-surface air temperature Temperature >0℃, relative humidity near the ground RH≤80%, or total radiation irradiance R≥500W / m².

[0012] In one possible embodiment, the icing stage determination and thickness update are performed through state transition rules. Let the icing state at time t-1 be S(t-1) and the icing thickness be I(t-1), and the icing state at time t be S(t) and the icing thickness be I(t). S0, S1, S2, and S3 represent the no-icing state, the icing development stage, the icing maintenance stage, and the icing melting stage, respectively. State transition rules based on icing development criteria Criteria for ice melting Maintaining the criteria for icing For input, and according to priority, Secondly, Execute in the final order; Rule 1: When S(t-1) = S0 and When S(t) = S1, the icing process begins; when S(t-1) = S0 and = When S(t) = S0, I(t) = 0; Rule 2: When S(t-1) = S1, S2, or S3, and When S(t) = S1, the ice formation process begins or continues, and the Makkonen model is invoked to calculate the growth rate. Rule 3: When I(t-1)>0, , and When S(t) = S2, the state of icing is entered or maintained. Rule 4: When I(t-1)>0, and When S(t) = S3, the ice melting stage begins and the ice attenuation is calculated. Rule 5: When S(t) = S3 and I(t) obtained after ablation update ≤ 0, and When the time limit is reached, the process enters the pending termination judgment; if the continuous time constraint is satisfied at the same time, the icing process ends and S(t)=S0.

[0013] In one possible embodiment, the state transition rule also includes consecutive time constraints: When the icing retention condition is not met for two consecutive time periods and the icing thickness drops to 0, the icing process is considered to have ended.

[0014] In one possible embodiment, the Makkonen icing model is as follows: ,in, The mass of ice accumulation per unit length of conductor. For collision efficiency, For freezing efficiency, For capture efficiency or attachment efficiency, The liquid water content in the air. The effective wind speed is perpendicular to the conductor. The diameter is the wire diameter.

[0015] In one possible embodiment, the amount of icing attenuation during the icing ablation phase. Calculate using the following formula: ; , , This is the empirical ablation coefficient. The radiation ablation threshold, The humidity ablation threshold, For time step, Let be the near-surface temperature at time t. Let be the total irradiance at time t. The near-surface relative humidity at time t is given by the above-mentioned main scheme and its various further alternative schemes. These can be freely combined to form multiple schemes, all of which are schemes that can be adopted and are claimed by this application. Non-conflicting alternatives can also be freely combined with each other and with other alternatives. Those skilled in the art, after understanding the scheme of this application, will realize, based on existing technology and common general knowledge, that there are many combinations, all of which are technical solutions to be protected by this application; therefore, no exhaustive list is provided here.

[0016] This application discloses a method for determining the staged icing process and updating the icing amount. First, a multi-layered nested WRF numerical simulation system is established to acquire hourly meteorological elements of the target area. Then, based on the air temperature, relative humidity, 10m wind speed, and total irradiance output by the WRF, the icing stage is determined. Finally, a corresponding icing thickness update strategy is selected based on the determined icing stage, and the icing thickness is updated accordingly. The icing thickness update strategy is as follows: when the icing development stage is determined, the Makkonen icing model is used to calculate the icing growth; when the icing maintenance stage is determined, the icing thickness of the previous moment is maintained or a slight change correction is made; when the icing melting stage is determined, the icing attenuation is calculated. Through staged icing process determination and differentiated thickness updates, the icing process state can be accurately identified, avoiding incorrect thickness accumulation under non-icing conditions, and significantly improving the physical rationality and simulation accuracy of the icing numerical simulation. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A schematic flowchart of the method for determining the staged icing process and updating the icing amount proposed in an embodiment of this application is shown. Detailed Implementation

[0019] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0020] Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0021] Existing transmission line icing early warning and simulation technologies can be divided into five categories, each with varying degrees of limitations: First, early warning methods based on empirical thresholds or icing levels, while capable of identifying icing risk through parameters such as temperature and humidity, only output whether icing has occurred or the risk level, lacking a phased description of the entire icing process. Direct application in numerical simulations can easily lead to incorrect thickness accumulation or deviations in start and end times. Second, dynamic estimation methods based on micro-meteorological monitoring rely on on-site sensor data, possessing strong capabilities for depicting real-time processes at single points, but with limited spatial coverage, making it difficult to support continuous regional simulations in areas without observation stations, complex mountainous regions, and future time periods; they are more suitable as a verification tool. Third, icing thickness prediction methods based on machine learning, while capable of fitting the nonlinear mapping between meteorology and icing,... However, it suffers from problems such as insufficient physical interpretation, weak cross-regional generalization ability, and reliance on training samples. Furthermore, due to the lack of determination of the icing development stage, even if the thickness fitting error is small, the physical process may be unreasonable. Fourth, the physical icing growth calculation method based on the Makkonen model, although it has a clear physical basis and can calculate the growth per unit time, does not solve the process control problem of when to start / stop growth and when to maintain / melt, and is prone to misuse when the icing conditions are not met, leading to incorrect thickness accumulation. Fifth, the WRF coupled with the icing model method, although it uses the WRF output to drive the growth calculation, does not make sufficient use of the role of WRF meteorological elements in the determination of icing state transition, especially ignoring the key influence of total irradiance on icing maintenance and melting.

[0022] Overall, existing technologies generally suffer from five major shortcomings: they focus primarily on icing risk, level, or thickness results, lacking a phase determination mechanism for the entire numerical simulation process; the Makkonen model lacks external process control for initiation, maintenance, ablation, and termination; WRF output elements are not fully used for hourly state transition determination; the role of total irradiance in icing maintenance and ablation is not adequately considered; and icing in complex mountainous areas is highly localized, lacking localized criteria based on actual measurements from typical ice observation stations.

[0023] To address the aforementioned technical issues, this application proposes a method for determining the staged icing process and updating the icing thickness. Based on the results of WRF multi-layer nested high-resolution simulations, criteria for the development, maintenance, and melting stages of icing are established using air temperature, relative humidity, 10m wind speed, and total irradiance. These criteria are then used as a pre-control module of the Makkonen icing model, enabling continuous determination of the start, development, maintenance, melting, and termination of the icing process, as well as updating the icing thickness. Therefore, this method is particularly suitable for identifying the start, development, maintenance, melting, and termination stages of icing processes in complex mountainous transmission lines and can be used for time-series simulation of icing thickness.

[0024] Please refer to Figure 1 , Figure 1This application presents a flowchart illustrating a method for determining the staged icing process and updating the icing amount, including: Step S1: Establish a WRF multi-layer nested numerical simulation system to obtain hourly meteorological elements for the target area. The hourly meteorological elements should include at least near-surface air temperature. Near-ground relative humidity (RH) and wind speed at 10m and total radiation irradiance R; Step S2: Generate icing development criteria based on hourly meteorological elements. Criteria for ice melting Maintaining the criteria for icing The icing state S(t) at time t is determined by prioritizing the development of icing, the melting of existing icing, and the retention of existing icing. The icing state includes the non-icing state S0, the icing development stage S1, the icing retention stage S2, and the icing melting stage S3. Step S3: Select the corresponding ice accumulation update strategy according to S(t), update the ice accumulation mass M(t) and / or ice accumulation thickness I(t) at time t, and output the ice accumulation stage sequence and ice accumulation thickness time series results; When S(t) = S1, the Makkonen icing model is used to calculate the icing growth. The amount of ice accumulation will be added to the ice accumulation at the previous moment; When S(t) = S2, maintain the icing amount from the previous moment, or adjust according to the preset weak change correction amount. Update icing volume, among which It can be set to 0 or determined by a preset sublimation / deposition correction model; When S(t) = S3, according to the near-surface air temperature The icing attenuation ΔMmelt(t) is calculated based on the total irradiance R and the near-surface relative humidity RH, and the icing amount is updated according to the non-negative constraint.

[0025] First, a multi-layered nested WRF numerical simulation system was established to acquire hourly meteorological elements for the target area. The WRF model adopted a multi-layered nested configuration, with the outer layer having a horizontal resolution of 9 km to describe the large-scale circulation background; the middle layer having a horizontal resolution of 3 km; and the innermost layer having a horizontal resolution of 1 km, which can accurately cover the target icing area and the transmission line corridor. Hourly meteorological elements at the target grid points were extracted from the innermost layer output, including near-surface air temperature, near-surface relative humidity, 10m wind speed, and total irradiance.

[0026] Secondly, based on the air temperature, relative humidity, 10m wind speed, and total irradiance output by the WRF multi-layer nested numerical simulation system, the icing stage is determined. The icing stage includes the icing development stage, the icing maintenance stage, and the icing melting stage. This stage determination is based on localized criteria established from the icing thickness observation data and synchronous meteorological data of the icing observation station, following the priority rule of "first judging icing development, then judging melting under existing icing, and finally judging maintenance under existing icing": the icing development stage refers to the stage where meteorological conditions are favorable for icing formation or icing thickness increase; the icing maintenance stage refers to the stage where icing has formed and meteorological conditions are still favorable for icing, including the transitional maintenance situation where relative humidity is between 80% and 85%; the icing melting stage refers to the stage where icing thickness decreases due to rising temperature, decreasing humidity, or increased radiation.

[0027] Based on the determined icing stage, a corresponding icing thickness update strategy is selected, and the icing thickness is updated accordingly. Specifically, the icing thickness update strategy includes: when the stage is determined to be icing development, the Makkonen icing model is used to calculate the icing growth, and the current icing thickness is updated accordingly; when the stage is determined to be icing maintenance, the icing thickness at the previous moment is maintained, or a slight change correction is made to the icing thickness; when the stage is determined to be icing melting, the icing decay is calculated, and the current icing thickness is updated accordingly. Finally, the dynamic update of the icing thickness is completed by combining the state transition results.

[0028] Hourly meteorological elements of the target area include near-surface air temperature Near-surface relative humidity RH, 10m wind speed WS10, total irradiance R; Among them, near-surface temperature The 2-meter air temperature T2 is represented by the output of the WRF multi-layer nested numerical simulation system, or it can be corrected by using the corresponding model layer temperature according to the actual erection height of the conductor; The near-surface relative humidity RH is directly output by the WRF multi-layer nested numerical simulation system, or calculated based on the water vapor mixing ratio, temperature and air pressure output by WRF. The 10m wind speed WS10 is synthesized from the 10m zonal wind U10 and meridional wind V10 output by the WRF, and the calculation formula is WS10=sqrt(U10) 2 +V10 2 The effective wind speed v perpendicular to the conductor axis is calculated based on the conductor's direction. Total irradiance R is represented by the surface downward shortwave radiation SWDOWN output by the WRF, and the liquid water content W in the air is obtained by the cloud-water mixing ratio and air density output by the WRF.

[0029] The WRF model employs a multi-layered nested configuration. The outermost layer has a horizontal resolution of 9 km and is used to describe the large-scale circulation background; the middle layer has a horizontal resolution of 3 km and is used to describe regional water vapor transport and topographic effects; the innermost layer has a horizontal resolution of 1 km and covers the target icing area and transmission line corridor. The meteorological elements required for icing process determination are obtained from WRF output or diagnosed from WRF output.

[0030] The hourly meteorological elements of the target area were obtained using the aforementioned WRF multi-layer nested numerical simulation system. The specific definitions and sources of each element are as follows: Near-surface temperature As the core parameter for determining the thermal conditions of the icing process, the 2-meter air temperature T2 output by the WRF multi-layer nested numerical simulation system is directly represented. When there is a significant difference between the target area topography and the model topography, the model layer temperature corresponding to the actual traverse erection height can be used as a substitute, or the temperature can be corrected according to the altitude lapse rate to ensure the matching of the air temperature parameter with the actual icing environment.

[0031] Near-surface relative humidity (RH) is a key indicator characterizing the amount of supercooled water in the air. It can be obtained through two methods: one is to directly use the near-surface relative humidity variable output by the WRF multi-layer nested numerical simulation system; the other is to calculate it based on the water vapor mixing ratio, temperature and air pressure data output by the system through thermodynamic diagnostic formulas, in order to adapt to the differences in output characteristics of different versions of the WRF model.

[0032] The 10m wind speed WS10 is used to characterize the transport capacity of supercooled water droplets to the surface of the conductor. It is synthesized from the 10m zonal wind U10 and meridional wind V10 output by the WRF multi-layer nested numerical simulation system. Its calculation formula is WS10=sqrt(U10) 2 +V10 2 When the transmission line direction angle θline and wind direction angle θwind are known, the effective wind speed perpendicular to the conductor axis V=WS10·|sin(θwind-θline)| can be further calculated, so that the Makkonen model input matches the windward projection of the conductor better.

[0033] Total irradiance R, as an important factor affecting the thermal balance of icing, is directly represented by the downward shortwave radiation SWDOWN output by the WRF multi-layer nested numerical simulation system. The liquid water content W in the air is obtained by the cloud-water mixing ratio qc and air density ρair output by WRF, preferably W=ρair·qc, which is used to characterize the liquid water content per unit volume of air that can participate in icing growth.

[0034] The icing development stage indicates that meteorological conditions are favorable for icing formation or an increase in icing thickness. The icing retention phase indicates that icing has formed and meteorological conditions are favorable for its existence. The ice melting stage indicates that rising temperatures, decreasing humidity, or increased radiation lead to a reduction in ice thickness.

[0035] The icing development stage represents the critical conditions for icing formation and growth, where the combination of meteorological elements meets the conditions for icing formation and growth. At this stage, the synergistic effect of ambient temperature, air humidity, wind dynamics, and radiative heat conditions supports the condensation of supercooled water droplets on the conductor surface to form new icing, and also drives the continuous accumulation of the thickness of existing icing. This is the main growth period of the icing process.

[0036] The ice retention stage is based on the premise that the ice structure has been initially formed. At this time, although the meteorological conditions have not reached the ice growth threshold, they can still inhibit ice melting and keep the ice morphology relatively stable. This includes the transitional maintenance situation where the relative humidity is in the range of 80% to 85%, under which the ice thickness changes only slightly or not at all.

[0037] The ice melting stage corresponds to the physical process of ice structure thinning. When the temperature rises and exceeds the freezing threshold, the air humidity decreases and accelerates the sublimation process, or the total radiation irradiance increases and provides net heat input, the internal energy balance of the ice is broken, causing the ice thickness to gradually decrease over time until it completely dissipates.

[0038] The above three types of icing process stages, together with the non-icing state, constitute a complete set of icing process states. The non-icing state is defined as the baseline state in which the process control conditions related to the occurrence, maintenance, or melting of icing are not met, providing a judgment boundary for the start and end of the icing process.

[0039] The criterion for determining the icing development stage in step S2 is: near-surface air temperature. ≤-2℃, near-ground relative humidity RH≥85%, total irradiance R≤150W / m², and wind speed WS10≥3m / s at 10m.

[0040] The criteria for determining the stage of icing development are established based on the statistical analysis of observation data of the icing process at the observation station and synchronous meteorological elements, and must simultaneously meet the following four threshold requirements: Near-surface temperature needs to meet ≤-2℃, this threshold ensures that supercooled water droplets have the thermal conditions to freeze after hitting the surface of the conductor, preventing liquid water from being unable to adhere or melting quickly; The relative humidity near the ground needs to be RH≥85%. This threshold ensures that there is sufficient supercooled water vapor or cloud water in the air, providing a sufficient water supply for ice growth. The total irradiance must meet the requirement of R≤150W / m². This threshold limits the thermal input of solar radiation to prevent shortwave radiation heating from causing icing to melt or freezing to be hindered. A wind speed of 10m is required to meet WS10≥3m / s. This threshold provides sufficient dynamic conditions to enable supercooled water droplets to effectively collide with the surface of the conductor, thereby improving the efficiency of icing growth.

[0041] When all four conditions above are met simultaneously, the current time period is determined to have entered the icing development stage, denoted as... At this time, the combination of meteorological elements fully meets the requirements for ice formation and thickening.

[0042] The conditions for entering or maintaining the icing retention stage in step S2 are as follows: Ice has already formed, and the following conditions are met simultaneously: near-surface air temperature ≤0℃, near-ground relative humidity RH>80%, and total irradiance R<500W / m².

[0043] The entry into or maintenance of the icing retention phase requires the existence of an existing icing structure, and must simultaneously meet the following three meteorological threshold conditions: Near-surface temperature needs to meet ≤0℃, this threshold is higher than the icing development stage but still lower than the freezing point, which can prevent the icing from thermally melting due to the rise in the overall ambient temperature; The near-surface relative humidity needs to be RH>80%. This threshold is slightly lower than the icing development stage, allowing the icing to remain structurally stable without immediate sublimation or dry melting in the transitional range where humidity decreases. The total irradiance must meet the requirement of R < 500 W / m². This threshold is significantly higher than that of the icing development stage, which aims to allow a certain degree of solar radiation to exist. As long as its heat flux is insufficient to drive significant melting of the icing, it can be determined to be in a maintenance state.

[0044] When the above conditions are met simultaneously and icing has already occurred, it is determined that the current time period enters or maintains an icing-holding state, denoted as... This stage indicates that although the environmental and meteorological conditions are insufficient to support a significant increase in icing thickness, they are still conducive to the survival of the icing structure. The icing thickness usually remains at the value of the previous moment, or is slightly corrected according to extremely weak microphysical processes.

[0045] The criteria for determining the ice melting stage in step S2 are as follows: Icing has already occurred, and any one of the following conditions is met: near-surface air temperature Temperature >0℃, relative humidity near the ground RH≤80%, or total radiation irradiance R≥500W / m².

[0046] The determination of the icing melting stage is based on the premise that the icing structure already exists. A multi-factor collaborative determination logic is employed. The icing melting stage is determined when any of the following meteorological threshold conditions are met, denoted as... First, the near-surface air temperature meets Ta>0℃, at which point the ambient temperature is above the freezing point, and the ice melts through a thermal ablation process. Second, the near-surface relative humidity meets RH≤80%, at which point the air humidity is low, and the ice sublimates through the action of dry air. Third, the total irradiance meets R≥500W / m², at which point the heat input provided by solar radiation increases significantly, driving the ice to melt due to heat.

[0047] Both the icing stage determination and thickness update are performed using state transition rules, which include: Let the icing state at time t-1 be S(t-1) and the icing thickness be I(t-1), and the icing state at time t be S(t) and the icing thickness be I(t). S0, S1, S2, and S3 represent the no-icing state, the icing development stage, the icing maintenance stage, and the icing melting stage, respectively. Rule 1: When S(t-1) = S0 and When S(t) = S1, the icing process begins; when S(t-1) = S0 and When S(t) = S0, I(t) = 0; Rule 2: When S(t-1) = S1, S2, or S3, and When S(t) = S1, the ice formation process begins or continues, and the Makkonen model is invoked to calculate the growth rate. Rule 3: When I(t-1)>0, , = and When S(t) = S2, the state of icing is entered or maintained. Rule 4: When I(t-1)>0, and When S(t) = S3, the ice melting stage begins and the ice attenuation is calculated. Rule 5: When S(t) = S3 and I(t) obtained after ablation update ≤ 0, and When the time limit is reached, the process enters the pending termination judgment; if the continuous time constraint is satisfied at the same time, the icing process ends and S(t)=S0.

[0048] After determining the icing stage at each time step, the icing state and icing thickness are updated collaboratively using state transition rules. The priority of state transitions follows this order: first, it is determined whether the icing development conditions are met; second, it is determined whether the ablation conditions are met under the existing icing conditions; and finally, it is determined whether the maintenance conditions are met. This avoids state jumps that occur when the icing development conditions and the maintenance / ablation conditions cross over.

[0049] Rule 1: If the previous time step was a non-icing state S(t-1)=S0, and the current meteorological conditions meet the icing development criterion. If the current moment transitions to the icing development state S(t) = S1, it signifies the official start of the icing process. If the previous moment was a non-icing state but the current moment does not meet the icing development criterion... If the current state remains un-iced, S(t) = S0, and the icing thickness I(t) = 0.

[0050] Rule 2: If the previous time step was in the icing development stage, the icing maintenance stage, or the icing melting stage, i.e., S(t-1) = S1, S2, or S3, and the current time step again satisfies the icing development criterion. If the current time step enters or continues to maintain the icing development state S(t) = S1, then the system calls the Makkonen icing model to calculate the icing increase at that time step and adds it to the icing amount.

[0051] Rule 3: When the icing thickness at the previous moment was greater than zero (I(t-1)>0), and the current moment does not simultaneously meet the icing development criterion. The criteria for ice melting are not met. However, the icing retention criterion is met. If the current time is such that the ice accumulation remains in a holding state, then S(t) = S2. In the holding state, the ice accumulation remains the value from the previous time step, or is adjusted according to a preset slight change correction. Make minor adjustments.

[0052] Rule 4: If the ice thickness at the previous moment was greater than zero (I(t-1)>0), and the current moment does not meet the icing development criterion. However, it meets the criteria for ice melting. When the current moment enters the icing melting stage S(t)=S3, the system calculates the icing attenuation and subtracts this attenuation from the icing amount at the previous moment to obtain the updated icing amount.

[0053] Rule 5: If, at the current moment, the ice melting stage S(t) = S3, and the ice thickness I(t) obtained after the melting update is ≤ 0, and the ice development criterion is still not met at the current moment... If the condition is met, the process enters the pending termination judgment; when the consecutive time constraints are met simultaneously, the icing process is determined to end, and the current state becomes the non-icing state S(t)=S0.

[0054] Rule 6: During the icing melting process, if the icing development criterion is met again at some point ( If the melting process is not yet complete, then the ice-covered development state S(t)=S1 will be re-entered according to rule 2, and the ice-covered growth calculation will resume.

[0055] The state transition rules also include consecutive time constraints: When the icing retention condition is not met for two consecutive time periods and the icing thickness drops to 0, the icing process is considered to have ended.

[0056] To effectively avoid frequent changes in icing status caused by single-time WRF model output errors or short-term fluctuations in meteorological elements, thereby improving the stability and engineering applicability of icing process determination, this application further introduces continuous time constraints in the state transition rules: only when the icing maintenance condition is not met for two consecutive time periods and the icing thickness has dropped to 0 is the icing process finally determined to be over, that is, the state changes from the icing melting stage to the ic-free state S0.

[0057] The Makkonen icing model is given by dM / dt = α1·α2·α3·W·v·D, and =α1·α2·α3·W(t)·v(t)·D·Δt, where M is the icing mass per unit length of the conductor, α1 is the collision efficiency, α2 is the freezing efficiency, α3 is the capture efficiency or adhesion efficiency, W is the liquid water content in the air, v is the effective wind speed perpendicular to the conductor axis, D is the conductor diameter, and Δt is the time step.

[0058] The Makkonen icing model is controlled by the aforementioned icing stage determination module and is activated only when the system determines that it is in the icing development stage. This avoids invalid growth calculations under unfavorable weather conditions and prevents erroneous accumulation of icing thickness. In the model, W is preferably obtained from the cloud-water mixing ratio qc and air density ρair output by the WRF, v is preferably calculated from the 10m wind speed combined with the conductor direction, and D is determined by the target transmission conductor type.

[0059] The hourly update of icing thickness employs a phased, differentiated strategy. The icing development stage corresponds to a significant increase in icing, and the update formula for the icing mass per unit length of conductor in this stage is M(t) = M(t-1) + Where M(t-1) is the mass of ice accumulation per unit length of the conductor at the previous moment. This represents the amount of ice growth calculated by the Makkonen icing model within the current time step Δt.

[0060] The icing retention stage corresponds to the stable existence of the icing structure. During this stage, the icing quality update offers two possible modes: M(t) = M(t-1), or M(t) = M(t-1) + .in, The preset weak change correction amount can be 0; it can also be determined based on the weak sublimation or deposition process, and preferably limited to | | Less than the preset ratio of Makkonen growth or ablation in the same time period, to avoid significant growth or significant ablation during the maintenance phase.

[0061] The icing melting stage corresponds to the thinning process of the icing mass. The formula for updating the icing mass per unit length of conductor during this stage is M(t)=max(0,M(t-1)-ΔMmelt(t)). This formula uses the max(0,·) operation to ensure that the icing mass does not become negative due to excessive melting; when the calculation result is 0 and the continuous time constraint is satisfied, it is determined that the icing has completely disappeared.

[0062] Ice attenuation during the ice melting phase Calculate using the following formula: ; , , This is the empirical ablation coefficient. The radiation ablation threshold, The humidity ablation threshold, For time step, Let be the near-surface temperature at time t. Let be the total irradiance at time t. Let be the near-surface relative humidity at time t.

[0063] The conversion between icing mass M and icing thickness I is achieved through conductor geometry. For cylindrical conductors with a radius of D / 2, a preferred method is... A conversion is performed, where ρice is the icing density; an equivalent conversion model can also be established based on the conductor cross-sectional shape, icing eccentricity, or field calibration relationship. The empirical ablation coefficients k1, k2, and k3 are optimally determined based on the measured icing ablation process and synchronous meteorological data from the ice observation station, through least squares fitting, grid search, or cross-validation.

[0064] Preferably, the calibration process of the empirical ablation coefficient includes: taking the measured decrease in ice thickness at the ice observation station as the target value, and taking max(0,Ta(t)), max(0,R(t)-R0), and max(0,RH0-RH(t)) at the corresponding time as independent variables, establishing a linear or piecewise linear fitting relationship to obtain k1, k2, and k3; and verifying it using samples from different ice accretion processes to reduce parameter deviations caused by single process samples.

[0065] When outputting the icing thickness, if the calculated M(t) = 0, then let I(t) = 0; if M(t) > 0, then calculate I(t) in reverse according to the aforementioned mass-thickness conversion relationship. Thus, the mass increase given by the Makkonen model, the mass decrease given by the ablation formula, and the commonly used icing thickness index in engineering can be kept consistent.

[0066] This formula comprehensively considers three physical mechanisms: thermal ablation, radiation ablation, and dry air ablation. Compared with the traditional single-factor ablation model that only relies on air temperature, it significantly improves the simulation accuracy of the ice ablation process under complex diurnal radiation changes and alternating wet and dry conditions in mountainous areas.

[0067] In the specific implementation, data preparation is first performed: observational data of the icing process at the ice observation station are selected, including time, 10m wind speed, average temperature, average relative humidity, total irradiance, and icing thickness. Simultaneously, a multi-layer nested simulation using the WRF model is employed, with the innermost grid resolution at 1km, and hourly meteorological elements at the grid point where the ice observation station is located or nearby interpolation points are extracted. Next, process criteria are applied: at each WRF output time, it is first determined whether the icing development criterion is met. If the development criterion is not met but icing has already occurred, it is then determined whether the ablation criterion is met. If neither the development nor ablation criteria are met, but the maintenance criterion is met, the system enters a maintenance state, and the state transition result determines whether to call the Makkonen model, maintain the thickness, or calculate ablation. Finally, results are output and verified: hourly state S(t), icing mass M(t), and icing thickness I(t) are output and compared with the measured icing thickness, icing start time, and icing end time at the ice observation station to verify the applicability of the threshold and empirical ablation coefficient.

[0068] Compared with the prior art, the embodiments of this application have the following beneficial effects:

[0069] First, this application not only outputs the icing thickness but also clearly defines the complete lifecycle of the icing process, including its initiation, development, maintenance, melting, and termination. Compared to traditional methods that only provide icing risk levels, this approach provides a physically meaningful hourly sequence of state evolution.

[0070] Secondly, by employing a WRF multi-layer nested system with an innermost resolution of 1 km, this application can finely characterize the micro-meteorological features under complex terrain. This makes the method particularly suitable for icing forecasting of transmission line corridors in mountainous areas with large terrain undulations, where conventional methods are difficult to simulate.

[0071] Third, by using the stage criterion as a pre-control module of the Makkonen model, the growth calculation is only invoked when the icing development stage is determined. This fundamentally solves the problem of incorrect thickness accumulation during non-icing periods caused by the lack of process control in traditional coupled methods.

[0072] Fourth, this application innovatively incorporates total irradiance and relative humidity into the ablation criteria, comprehensively considering three mechanisms: thermal ablation, dry air ablation, and radiation ablation. This significantly improves the accuracy of identifying icing ablation under mountainous conditions with large diurnal temperature variations and strong clear-sky radiation.

[0073] Fifth, the "state machine + physical model" architecture established in this application makes the icing simulation process transparent and logically clear, facilitating understanding and application by business personnel. This characteristic gives it higher practical value in real-world engineering scenarios such as power grid disaster prevention and dispatching decisions and transmission line design verification.

[0074] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for determining the staged icing process and updating the icing amount, characterized in that, include: Step S1: Establish a WRF multi-layer nested numerical simulation system to obtain hourly meteorological elements for the target area. The hourly meteorological elements should include at least near-surface air temperature. Near-ground relative humidity (RH) and wind speed at 10m and total radiation irradiance R; Step S2: Generate icing development criteria based on hourly meteorological elements. Criteria for ice melting Maintaining the criteria for icing The icing state S(t) at time t is determined by prioritizing the development of icing, the melting of existing icing, and the retention of existing icing. The icing state includes the non-icing state S0, the icing development stage S1, the icing retention stage S2, and the icing melting stage S3. Step S3: Select the corresponding ice accumulation update strategy according to S(t), update the ice accumulation mass M(t) and / or ice accumulation thickness I(t) at time t, and output the ice accumulation stage sequence and ice accumulation thickness time series results; When S(t) = S1, the Makkonen icing model is used to calculate the icing growth. The amount of ice accumulation will be added to the ice accumulation at the previous moment; When S(t) = S2, maintain the icing amount from the previous moment, or adjust according to the preset slight change. Update icing volume, among which Set to 0 or be determined by the preset sublimation / deposition correction model; When S(t) = S3, according to the near-surface air temperature Calculate the icing attenuation based on total irradiance R and near-surface relative humidity RH. And update the icing amount according to the non-negative constraint.

2. The method for determining the staged icing process and updating the icing amount as described in claim 1, characterized in that, Near-surface temperature 2-meter air temperature output by the WRF multi-layer nested numerical simulation system This indicates that corrections may be made based on the actual installation height of the conductor and the corresponding mode layer temperature. The near-surface relative humidity RH is directly output by the WRF multi-layer nested numerical simulation system, or calculated based on the water vapor mixing ratio, temperature and air pressure output by WRF. 10m wind speed 10-meter zonal wind output by WRF and the wind Synthesis, calculation formula is And convert it into an effective wind speed V perpendicular to the conductor axis according to the direction of the conductor; The total irradiance R is represented by the downward shortwave radiation SWDOWN output from the WRF.

3. The method for determining the staged icing process and updating the icing amount as described in claim 1, characterized in that, The icing development stage indicates that meteorological conditions are favorable for icing formation or an increase in icing thickness. The icing retention phase indicates that icing has formed and meteorological conditions are favorable for the continuation of icing. The icing melting stage indicates that rising temperature, decreasing humidity, or enhanced radiation leads to a reduction in icing thickness. The non-icing state indicates that the baseline state does not meet the control conditions related to the occurrence, maintenance, or melting of icing.

4. The method for determining the staged icing process and updating the icing amount as described in claim 1, characterized in that, The criterion for determining the icing development stage in step S2 is: near-surface air temperature. Temperature ≤-2℃, near-ground relative humidity RH≥85%, total irradiance R≤150W / m², and wind speed 10m ≥3m / s.

5. The method for determining the staged icing process and updating the icing amount as described in claim 1, characterized in that, The conditions for entering or maintaining the icing retention stage in step S2 are as follows: Ice has already formed, and the following conditions are met simultaneously: near-surface air temperature ≤0℃, near-ground relative humidity RH>80%, and total irradiance R<500W / m².

6. The method for determining the staged icing process and updating the icing amount as described in claim 1, characterized in that, The criteria for determining the ice melting stage in step S2 are as follows: Icing has already occurred, and any one of the following conditions is met: near-surface air temperature Temperature >0℃, relative humidity near the ground RH≤80%, or total radiation irradiance R≥500W / m².

7. The method for determining the staged icing process and updating the icing amount as described in claim 1, characterized in that, The determination of the icing stage and the thickness update are performed through the state transition rule. Let the icing state at time t-1 be S(t-1) and the icing thickness be I(t-1), and the icing state at time t be S(t) and the icing thickness be I(t). S0, S1, S2, and S3 represent the no-icing state, the icing development stage, the icing maintenance stage, and the icing melting stage, respectively. State transition rules based on icing development criteria Criteria for ice melting Maintaining the criteria for icing For input, and according to priority, Secondly, Execute in the final order; Rule 1: When S(t-1) = S0 and When S(t) = S1, the icing process begins; when S(t-1) = S0 and = When S(t) = S0, I(t) = 0; Rule 2: When S(t-1) = S1, S2, or S3, and When S(t) = S1, the ice formation process begins or continues, and the Makkonen model is invoked to calculate the growth rate. Rule 3: When I(t-1)>0, , and When S(t) = S2, the state of icing is entered or maintained. Rule 4: When I(t-1)>0, and When S(t) = S3, the ice melting stage begins and the ice attenuation is calculated. Rule 5: When S(t) = S3 and I(t) obtained after ablation update ≤ 0, and When the time limit is reached, the process enters the pending termination judgment; if the continuous time constraint is satisfied at the same time, the icing process ends and S(t)=S0.

8. The method for determining the staged icing process and updating the icing amount as described in claim 7, characterized in that, The state transition rules also include consecutive time constraints: When the icing retention condition is not met for two consecutive time periods and the icing thickness drops to 0, the icing process is considered to have ended.

9. The method for determining the staged icing process and updating the icing amount as described in claim 1, characterized in that, The Makkonen icing model is: ,in, The mass of ice accumulation per unit length of conductor. For collision efficiency, For freezing efficiency, For capture efficiency or attachment efficiency, The liquid water content in the air. The effective wind speed is perpendicular to the conductor. The diameter is the wire diameter.

10. The method for determining the staged icing process and updating the icing amount as described in claim 1, characterized in that, Ice attenuation during the ice melting phase Calculate using the following formula: ; , , This is the empirical ablation coefficient. The radiation ablation threshold, The humidity ablation threshold, For time step, Let be the near-surface temperature at time t. Let be the total irradiance at time t. Let be the near-surface relative humidity at time t.

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