An operation parameter optimization method of an ultrahigh-voltage electrothermal air heating deicing device

Abstract

The application discloses a kind of operating parameter optimization methods of superhigh voltage live hot air deicing device, belong to the technical field of live deicing of electric power equipment.The method includes: obtaining the environmental temperature, ice thickness and ice type and other parameters of operating site;Establish the multi-constraint optimization model with the minimum total energy consumption of deicing as the optimization goal, and the live operating safety distance, the thermal protection of bushing outer insulating material, the ice melting effectiveness and the jet impact safety as the constraint condition;Using the jet heat exchange model based on the circular tube free jet theory, calculate the ice surface temperature, bushing surface temperature and jet dynamic pressure under different outlet temperature, outlet air speed and operating distance combinations;Select the optimal parameter combination that makes the energy consumption lowest among the feasible parameter combinations that meet all constraint conditions;The optimal parameter combination is output to the deicing device control system to perform deicing operation.The application is suitable for live hot air deicing operation of 750kV and above voltage grade substation bushing.

Description

Technical Field

[0001] This invention belongs to the field of live-line de-icing technology for power equipment, specifically relating to a multi-constraint parameter optimization control method for live-line hot air de-icing operations of bushings in ultra-high voltage substations, which is particularly suitable for live-line de-icing operations in substations with voltage levels of 750kV and above. Background Technology

[0002] In the harsh winter conditions, the outer insulation surface of transformer bushings in ultra-high voltage substations is highly susceptible to icing. As the ice thickness increases, ice bridging can form between the bushing skirts, significantly reducing the bushing's insulation strength. Under severe weather conditions, the iced bushing surface is prone to localized arcing, which can lead to flashover accidents, causing equipment tripping and large-scale power outages, posing a serious threat to the safe and stable operation of the power grid. Therefore, timely and effective removal of ice from substation bushing surfaces is a crucial measure to ensure the safe operation of the ultra-high voltage power grid during winter.

[0003] Currently, de-icing technologies for substation bushings mainly include manual de-icing during power outages, mechanical vibration de-icing, Joule heating de-icing, and hot air de-icing while the equipment is energized. Among these, manual de-icing during power outages requires equipment to be taken out of service, directly impacting power supply reliability. Furthermore, during peak winter electricity consumption periods, dispatching departments often struggle to schedule sufficient power outage windows, leading to significant delays in de-icing operations. Mechanical vibration de-icing removes the ice layer through external tapping or vibration, but the operation is difficult to control, easily causing mechanical damage to the bushing's outer insulation material, and posing significant operational risks to ultra-high voltage live equipment. Joule heating de-icing technology is primarily used in transmission lines, using increased conductor current to generate Joule heat to melt the ice. However, transformer bushings are static equipment, and increasing the load current cannot achieve de-icing; therefore, this method is unsuitable for bushing de-icing.

[0004] Live-line hot air de-icing technology is a novel method of de-icing that has emerged in recent years. This technology utilizes a blower to deliver ambient air into a heater, generating a high-temperature airflow that is then sprayed through a duct onto the surface of the ice-covered bushing. The hot airflow and the ice layer absorb heat through convection and conduction, causing the ice to melt or peel off. Compared to traditional power-off de-icing methods, live-line hot air de-icing does not require power outages and can be implemented while the equipment is energized, greatly improving the flexibility and timeliness of de-icing operations. Compared to mechanical de-icing, hot air de-icing is a non-contact operation, avoiding mechanical impact damage to the bushing's external insulation. Therefore, live-line hot air de-icing technology has become one of the important technical means for bushing de-icing in ultra-high voltage substations.

[0005] However, live-line hot air de-icing involves several interdependent operating parameters, primarily including outlet temperature, outlet air velocity, and the operating distance from the outlet to the casing surface. The selection of these parameters directly determines de-icing efficiency, energy consumption, and operational safety. In practical engineering applications, the selection of these parameters currently relies heavily on operator experience and lacks scientific quantitative optimization methods. Experience-based parameter selection often presents the following problems: First, unreasonable parameter combinations lead to excessively high de-icing energy consumption, resulting in energy waste; second, blindly increasing temperature or air velocity to ensure de-icing effectiveness may exceed safety constraints, causing equipment damage or personnel accidents; third, overly conservative parameter selection, while ensuring safety, results in low de-icing efficiency, prolonged operation time, and increased exposure time to the risks of live-line work.

[0006] From the perspective of current academic research, some scholars have conducted single-factor experimental studies on hot air de-icing, exploring the influence of single parameters such as wind speed and temperature on de-icing time. However, these studies are mostly limited to single-variable analysis in laboratory environments, failing to consider the multiple safety constraints under ultra-high voltage live-line working scenarios, and failing to establish a multi-parameter joint optimization model with the goal of minimizing energy consumption. In actual engineering environments, hot air de-icing operations must simultaneously meet multiple safety constraints: the working distance must be greater than the minimum safe distance for live-line working at the corresponding voltage level to prevent air gap breakdown; excessively high outlet air temperature or excessively long fixed-point purging time may lead to localized overheating of the bushing skirt surface, damaging the silicone rubber or ceramic outer insulation material; the temperature of the hot air reaching the ice surface must be higher than the freezing point, otherwise effective de-icing cannot be achieved; excessive jet impact force may cause ice blocks to splash at high speed, damaging the bushing surface or endangering the safety of operators. These constraints are intertwined, forming a complex multi-constraint feasible region, within which single-parameter research methods cannot find the globally optimal parameter combination.

[0007] Therefore, there is an urgent need to establish a method for optimizing operational parameters that can minimize the total energy consumption of de-icing while ensuring multiple safety measures. This method would elevate the selection of parameters for hot air de-icing from experience-based judgment to scientific optimization, thereby improving the scientific, economic, and safety aspects of live hot air de-icing operations. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a method for optimizing the operating parameters of an ultra-high voltage live-line hot air de-icing device. This method aims to minimize the total energy consumption for de-icing, and uses constraints such as the safety distance for live-line work, thermal protection of the bushing's external insulation material, the effectiveness of de-icing, and the safety of jet impact as conditions. A multi-constraint optimization model is established, and key physical quantities under different parameter combinations are calculated using a jet heat transfer model. The optimal operating parameter combination with the lowest energy consumption is selected from the parameter combinations that satisfy all safety constraints, thereby minimizing de-icing energy consumption while ensuring operational safety.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for optimizing the operating parameters of an ultra-high voltage energized hot air de-icing device includes the following steps: Step S1: Obtain environmental parameters and icing status parameters of the work site.

[0010] The environmental parameters include at least the ambient temperature T0, and the icing state parameters include at least the icing thickness D. ice And icing type. The ambient temperature T0 is acquired in real time by meteorological sensors deployed at the substation site. These sensors are installed in unobstructed locations near the work area to accurately reflect the atmospheric temperature of the microenvironment where the bushing is located. Icing thickness D. ice The methods for obtaining icing thickness include direct manual observation and prediction based on equivalent models. Manual observation involves operators using standard thickness gauges to measure multiple points at different heights on the casing and taking the arithmetic mean. Equivalent model prediction is based on accumulated meteorological parameters, including ambient temperature, relative humidity, wind speed, precipitation, and icing duration, calculating the equivalent icing thickness using a physical empirical model. Icing types are determined comprehensively based on meteorological conditions at formation and on-site observation characteristics, mainly divided into three types: rime, glaze, and mixed icing. Rime typically forms in a supercooled fog environment, appearing as white crystals with a loose structure, low density, and relatively weak adhesion. Glaze is formed when supercooled raindrops freeze upon contact with an object surface, appearing as transparent or translucent rime with a dense and hard structure and strong adhesion. Mixed icing is a mixture of rime and glaze, with physical properties intermediate between the two.

[0011] Step S2: Establish an optimization model with the goal of minimizing the total energy consumption E for de-icing and with multiple safety constraints.

[0012] The optimization objective is to minimize the total de-icing energy consumption E, expressed as min E = P·t, where P is the heating power of the hot air de-icing device (kW), t is the time required to complete the de-icing operation at the current ice thickness (hours), and E is the total de-icing energy consumption (kWh). When the rated power of the de-icing device is fixed, the optimization objective is equivalent to minimizing the de-icing time; when the power is adjustable, an optimal balance must be sought between power and time to minimize their product.

[0013] The constraints include the following four aspects: Constraint C1 is a safety distance constraint: the working distance L from the air outlet to the surface of the bushing must not be less than the minimum safe distance L for live working at the corresponding voltage level. min That is, L≥L minThis constraint is a basic electrical insulation requirement to prevent high voltage from breaking down air gaps and to ensure the safety of workers and equipment. For 750kV ultra-high voltage substations, according to the safety regulations for live-line work, the minimum safe distance L... min Take 0.20 meters. For other voltage levels, L min Determined in accordance with relevant national standards and industry specifications.

[0014] Constraint C2 is a material protection constraint: the highest temperature T on the surface of the sleeve skirt during de-icing. surface The operating temperature T of the outer insulation material of the bushing shall not exceed the maximum allowable operating temperature. max That is, T surface ≤T max This constraint aims to prevent prolonged hot air blowing from causing localized overheating of the outer insulation material of the bushing, which could lead to thermal aging, cracking of the silicone rubber material, or localized thermal stress damage to the ceramic material. For silicone rubber composite outer bushings, the maximum permissible operating temperature T... max The temperature is set at 170℃; for porcelain outer sleeves, T max The temperature was set to 190℃. surface The value is calculated by combining the convective heat transfer relationship between the casing surface and the hot jet using the jet heat transfer model. Its magnitude is related to the outlet temperature, outlet air velocity, working distance, and heat transfer characteristics of the casing surface.

[0015] Constraint C3 is the ice-melting effectiveness constraint: the temperature T when the hot air reaches the ice surface. ice It must not be lower than 0℃, i.e., T ice ≥0℃. This constraint is the fundamental thermodynamic condition that ensures ice can melt from a solid to a liquid state. If T ice Below 0°C, the hot jet cannot provide sufficient latent heat of melting to the ice layer, and the de-icing process cannot be carried out effectively. It can only produce a very slow de-icing effect through sublimation or weak heat conduction, which does not meet the requirements of engineering practicality.

[0016] Constraint C4 is a jet safety constraint: the dynamic pressure P generated by the hot air jet on the ice surface. d The ice layer safety stripping pressure threshold P must not be exceeded. safe That is, P d ≤P safe The purpose of this constraint is to prevent excessive jet impact force from causing ice to peel off at high speed. High-speed ice splashes could damage the casing skirt or pose a safety threat to personnel working below. The ice layer safe peeling pressure threshold P... safe Different settings are applied based on the type of icing: When rime ice forms, due to its loose structure and weak adhesion, P... safe The value is taken as 500 Pa; when rime ice forms an ice layer, due to its dense and hard structure and strong adhesion, P safeThe Pa value is taken as 800 Pa; when mixed frost covers ice, P safe The median value of the thresholds corresponding to rime and glaze is taken, which is 650 Pa. By setting different thresholds, effective de-icing is ensured while providing appropriate safety margins for different types of icing.

[0017] Step S3: Use the jet heat transfer model to calculate the key physical quantities under different parameter combinations.

[0018] The jet heat transfer model is based on the theory of free jets in circular tubes and is used to calculate the temperature and dynamic pressure attenuation characteristics of hot air as it travels from a circular outlet to the ice surface. After exiting the circular tube, the flow field structure of the free jet can be divided into a potential flow core region, a transition region, and a fully developed region along the axial direction. Within the potential flow core region, the temperature and velocity in the central region of the jet remain essentially at their exit values. Upon entering the transition and fully developed regions, the jet undergoes intense mass, momentum, and heat exchange with the ambient air, resulting in significant axial attenuation of temperature and dynamic pressure.

[0019] The formula for calculating temperature decay is: T ice = T0 + (T out - T0 )·η(L) Among them, T ice T is the temperature at which hot air reaches the surface of the ice layer, T0 is the ambient temperature, and T out Let L be the outlet temperature, L be the operating distance, and η(L) be the temperature retention coefficient related to distance L. The temperature retention coefficient η(L) reflects the degree of temperature loss caused by mixing and heat exchange with ambient cold air during jet transmission. Its value is determined by a pre-calibrated temperature decay test curve. The calibration method is as follows: under standard environmental conditions, the mass average temperature of the jet cross-section is measured using an array of thermocouples arranged at different axial distances to obtain temperature retention rate test data corresponding to different distances L. The decay curve of η(L) as a function of L is established by data fitting. According to the test calibration data, under the conditions of ambient temperature 20℃ and outlet temperature 200℃, when the operating distance L is 0.20 meters, the ice surface temperature is approximately 171.7℃, and the corresponding temperature retention coefficient is approximately 0.843; when the operating distance L increases to 1.0 meter, the ice surface temperature drops to approximately 145.2℃, and the corresponding temperature retention coefficient is approximately 0.696.

[0020] The formula for calculating dynamic pressure attenuation is: P d = 0.5·ρ·v²·μ(L) Among them, P dLet ρ be the dynamic pressure of the hot air jet on the ice surface, ρ be the air density, v be the jet center velocity, and μ(L) be the dynamic pressure retention coefficient related to distance L. Within the potential flow core region, the jet center velocity v is approximately equal to the outlet air velocity V. out In the fully developed region, the central wind speed decreases with increasing distance. The dynamic pressure retention coefficient μ(L) reflects the degree of jet momentum loss during transmission, and its value is determined by a pre-calibrated dynamic pressure attenuation test curve. The calibration method is as follows: using a Pitot tube or hot-wire anemometer, the dynamic pressure or wind speed at the jet center is measured at different axial distances to obtain dynamic pressure retention rate test data corresponding to different distances L. The attenuation curve of μ(L) as a function of L is established by data fitting. According to the test calibration data, at an operating distance L of 0.20 meters, this location is within the potential flow core region, and the dynamic pressure retention rate is approximately 100%, i.e., μ(L) is approximately 1.0; when the operating distance L increases to 0.50 meters, the dynamic pressure attenuates to approximately 73.5%, i.e., μ(L) is approximately 0.735.

[0021] The air density ρ can be calculated using the ideal gas law based on the local atmospheric pressure and the average jet temperature. Under standard atmospheric pressure and normal temperature conditions, it can be approximated as 1.2 kg / m³. For high-temperature jets, the air density value at the average jet temperature should be used to improve the calculation accuracy.

[0022] Step S4: Among the parameter combinations that satisfy all constraints C1 to C4, select the optimal parameter combination that minimizes the total de-icing energy consumption E.

[0023] The selection process is conducted within a preset range of outlet temperature, outlet air velocity, and operating distance parameters. Specifically, the parameter search space is determined based on the rated performance of the de-icing device. For example, the outlet temperature can be discretized within a certain step size from room temperature to 200℃, the outlet air velocity can be discretized within a certain step size within the flow velocity range corresponding to the rated air volume of the device, and the operating distance is within L, provided that C1 is satisfied. min Discretize within the effective range of the device. For each discrete parameter combination (T) out V out , L), and sequentially execute the jet heat transfer model calculation in step S3 to obtain T ice T surface and P d The process involves verifying whether all constraints C1 to C4 are satisfied. For feasible parameter combinations that satisfy all constraints, the total de-icing energy consumption E = P·t is calculated based on the de-icing time t and the device heating power P. By comparing the energy consumption values ​​of all feasible combinations, the optimal parameter combination (T) that minimizes E is determined. out V out 、L).

[0024] The de-icing time t and the outlet temperature Tout Outlet air velocity V out Working distance L and icing thickness D ice The specific values ​​are determined through a pre-calibrated empirical model or experimental database. The empirical model or experimental database is established by conducting systematic de-icing tests under different ambient temperatures, ice thicknesses, ice types, and different combinations of operating parameters, recording the actual time required to completely remove the ice under each condition, and using methods such as multiple regression fitting or neural networks to establish the mapping relationship between the de-icing time t and the above-mentioned influencing factors, or constructing a directly queryable experimental data comparison table.

[0025] When multiple feasible parameter combinations exist in the parameter space that simultaneously minimize the total de-icing energy consumption E, the parameter combination with the largest working distance L is selected as the optimal solution to maximize electrical safety margin and reduce the operational risks under high voltage conditions.

[0026] Step S5: Output the optimal parameter combination to the control system of the de-icing device to perform the de-icing operation.

[0027] The output methods include digital signal output, analog signal output, or transmission via industrial communication protocols. After receiving the optimal parameter combination, the de-icing device's control system automatically adjusts the heater's output power to achieve the optimal outlet temperature T. out Adjust the blower speed to achieve the optimal airflow velocity (V). out The system maintains the optimal working distance L between the air outlet and the casing surface through a robotic arm or manual operation, thereby enabling the de-icing operation to be performed according to the optimized parameters.

[0028] The beneficial effects of this invention are as follows: (1) This invention elevates the parameter selection in hot air de-icing operations from traditional experience-based judgment to scientific optimization based on mathematical models, establishes clear optimization objectives and quantitative constraints, makes the determination of operation parameters based on evidence, significantly improves the scientificity and accuracy of parameter selection, and avoids the subjectivity and blindness of experience-based judgment. (2) This invention is the first to incorporate four constraints—safe distance for live-line work, thermal protection of the outer insulation material of the bushing, effectiveness of de-icing, and safety of jet impact—into a unified optimization model, thus constructing a complete multi-constraint optimization framework. Through quantitative calculation of the jet heat transfer model, it ensures that the optimized parameter combination operates within all safety boundaries, effectively preventing risks such as electrical breakdown, insulation damage, de-icing failure, and ice splashing caused by improper parameter selection, and comprehensively ensuring operational safety. (3) The present invention takes the minimum total energy consumption for de-icing as the optimization goal, and achieves the minimization of energy consumption under the premise of ensuring safety constraints. It takes into account both de-icing efficiency and economy, reduces unnecessary energy waste, conforms to the green and low-carbon power grid operation and maintenance concept, and has good engineering application value and promotion prospects. (4) The present invention sets different jet safety pressure thresholds for different icing types, so that the optimization method can adaptively adjust the safety boundary according to the actual icing physical characteristics on site. This ensures strict safety control under loose icing type and avoids the reduction in de-icing efficiency due to overly conservative thresholds under dense icing type, thus improving the on-site adaptability and practicality of the method. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating the method for optimizing the operating parameters of the ultra-high pressure electrified hot air de-icing device of the present invention. It shows the complete technical process from obtaining environmental parameters, establishing an optimization model, calculating jet heat transfer, selecting optimal parameters, to control output.

[0030] Figure 2 The graph shows the average temperature decay curve of the cross-sectional mass of hot air under different ambient temperatures and working distances. The horizontal axis represents the working distance and the vertical axis represents the ice surface temperature. It shows the changing trend of the temperature retention coefficient η(L) as the distance increases, providing a calibration basis for the temperature decay calculation in step S3.

[0031] Figure 3 This is a schematic diagram of a hot air de-icing device operating on a bushing in an ultra-high voltage substation. The diagram shows the relative positions of the blower, heater, duct, air outlet, icing bushing, and operating distance L, intuitively demonstrating the operating scenario of live hot air de-icing. Detailed Implementation

[0032] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made to the present invention without departing from the spirit and substance of the present invention should be included within the protection scope of the present invention. Example

[0033] This embodiment uses a typical winter live-line hot air de-icing operation at a 750kV ultra-high voltage substation in Xinjiang, Northwest my country, as an example. The following refers to... Figures 1 to 3 This section details the specific implementation process of the operation parameter optimization method of the present invention.

[0034] Figure 1 The overall flow of the method of the present invention is shown. The operator first follows... Figure 1Step S1, as shown, involves obtaining the environmental parameters and icing status parameters of the work site. The environmental parameters for the day of the operation were obtained from the meteorological monitoring station located within the substation: ambient temperature T0 was 8℃, relative humidity was 65%, wind speed was 2 m / s, and the weather was cloudy with no precipitation. The work target was the high-voltage side bushing of a 750kV main transformer at the substation, with a silicone rubber composite outer insulation. On-site observation revealed that the icing type on the bushing surface was hoarfrost, appearing as a white, opaque crystalline substance, uniformly covering the surface. Workers used a standard thickness gauge to measure the icing thickness at three typical locations on the upper, middle, and lower parts of the bushing, obtaining thicknesses of 14 mm, 16 mm, and 15 mm respectively. The arithmetic mean was taken to obtain the icing thickness D. ice It is 15 millimeters.

[0035] The main technical parameters of the electric hot air de-icing device are as follows: the rated heating power P of the device is 42 kilowatts, the outlet temperature adjustment range is from room temperature to 200℃, the rated air volume is 500 cubic meters per hour, the diameter of the circular outlet is about 50 millimeters, and the corresponding outlet air speed under rated working conditions is about 70 meters per second. However, in actual operation, it can be continuously adjusted within a certain range under the control system.

[0036] according to Figure 1 Step S1 of the process shown involves inputting the obtained environmental parameters and icing state parameters into the optimization system: T0 = 8℃, D ice =15 mm, ice type (ice type I) is rime.

[0037] Enter Figure 1 Step S2, as shown, establishes an optimization model. The optimization objective is to minimize the total de-icing energy consumption min E = P·t, where P is taken as the rated power of the device, 42 kW. The specific constraints are set as follows: Constraint C1 (Safety Distance Constraint): The working distance L must not be less than the minimum safe distance for live-line work at 750kV, i.e., L≥0.20 meters.

[0038] Constraint C2 (Material Protection Constraint): Due to the silicone rubber composite outer sleeve, its maximum permissible operating temperature T max Take 170℃, i.e., T surface ≤170℃.

[0039] Constraint C3 (Ice Melting Effectiveness Constraint): The temperature of the hot air reaching the ice surface must satisfy T. ice ≥0℃.

[0040] Constraint C4 (Jet Safety Constraint): Due to the icing type being hoarfrost, the ice layer safety peeling pressure threshold P... safe Let it be 500 Pascals, i.e., P d ≤500 Pascals.

[0041] Enter Figure 1 Step S3, as shown, uses a jet heat transfer model to calculate key physical quantities under different parameter combinations. Based on the performance range of the de-icing device and the on-site operating conditions, the parameter search space is determined as: outlet air temperature T out The value is taken in increments of 20°C within the range of 140°C to 200°C, i.e., T out ∈ {140, 160, 180, 200}℃; Outlet air velocity V out Values ​​are taken in steps of 5 meters per second within the range of 15 to 30 meters per second, i.e., V out ∈ {15, 20, 25, 30} meters per second; the working distance L takes three levels of 0.20 meters, 0.30 meters and 0.40 meters under the premise of satisfying C1, that is, L ∈ {0.20, 0.30, 0.40} meters.

[0042] When calculating temperature decay, refer to Figure 2 The curves showing the average temperature decay of the cross-sectional mass of hot air under different ambient temperatures and working distances are shown. The temperature retention coefficient η(L) corresponding to each working distance can be obtained by looking up or interpolation. Figure 2 The horizontal axis represents the working distance, and the vertical axis represents the temperature retention coefficient. This curve is obtained by fitting pre-calibrated experimental data and reflects the degree of temperature loss caused by the mixing and heat exchange of hot air with ambient cold air during transmission. Under the ambient temperature conditions of this embodiment, combined with... Figure 2 The attenuation trend shown is calculated using the jet heat transfer model. The calculation results of the key physical quantities for each parameter combination are shown in the table below (only some typical combinations are listed below): When L = 0.20 meters: Combination A: T out = 180℃, V out = 25 meters per second. (Reference) Figure 2 The decay curve shows a high temperature retention coefficient at this distance, and T is calculated. ice The temperature is approximately 152℃, far exceeding the 0℃ requirement for effective ice melting; T surface The temperature is approximately 38℃, far below the 170℃ temperature resistance limit of silicone rubber materials; P d The energy consumption is approximately 425 Pascals, which is below the safe threshold of 500 Pascals for rime ice. This combination satisfies all four constraints and is a feasible solution. According to a pre-calibrated empirical model for de-icing time, the time t required to melt 15 mm thick rime ice under this parameter combination is approximately 8 minutes (i.e., 0.133 hours), corresponding to a total de-icing energy consumption of E = 42 kW × 0.133 hours ≈ 5.6 kWh.

[0043] Combination B: T out = 200℃, V out= 30 meters per second. (Reference) Figure 2 Although the outlet temperature of this combination is higher, calculated T ice Approximately 170℃, meeting the ice-melting effectiveness constraint; T surface Approximately 45℃, meeting material protection constraints; but P d The pressure is approximately 540 Pascals, exceeding the safe peeling pressure threshold of 500 Pascals for rime ice, thus violating constraint C4. Therefore, this combination is an infeasible solution and is excluded.

[0044] Combination C: T out = 160℃, V out = 20 meters per second. Calculated, T ice Approximately 135℃, T surface Approximately 32℃, P d The value is approximately 320 Pascals, satisfying all constraints, making it a feasible solution. However, due to the relatively low outlet temperature and wind speed, the heat transfer power from the hot jet to the ice layer decreases. Based on the empirical model, the de-icing time is estimated to be extended to approximately 12 minutes (0.20 hours), corresponding to an energy consumption of E = 42 × 0.20 = 8.4 kWh, which is higher than the energy consumption of combination A.

[0045] Combination D: T out = 140℃, V out = 15 meters per second. Calculated, T ice Approximately 118℃, T surface Approximately 26℃, P d The energy consumption is approximately 185 Pascals, which meets the constraints. However, the de-icing time is further extended to approximately 18 minutes (0.30 hours), with an energy consumption of E = 12.6 kWh, resulting in poor economic efficiency.

[0046] When L = 0.30 meters: Combination E:T out = 180℃, V out = 25 meters per second. (By...) Figure 2 It can be seen that as the operating distance increases, the temperature retention coefficient η(L) decreases accordingly, and the jet temperature decay and dynamic pressure decay intensify. Calculations show that T... ice Approximately 145℃, T surface Approximately 35℃, P d The value is approximately 310 Pascals, which satisfies the constraints and is a feasible solution. However, due to the decrease in temperature of the hot jet reaching the ice surface, the heat transfer driving force decreases, and the de-icing time is extended to approximately 10 minutes (0.167 hours), with energy consumption E ≈ 7.0 kWh, which is higher than combination A when L = 0.20 meters.

[0047] Combination F:T out = 200℃, V out= 30 meters per second. Calculated T ice Approximately 162℃, T surface Approximately 42℃, but P d The pressure is approximately 395 Pascals, satisfying constraint C4 (dynamic pressure decreases with increasing distance). This combination satisfies all constraints and is a feasible solution. The de-icing time is approximately 8.5 minutes (0.142 hours), and the energy consumption E ≈ 6.0 kWh, which is still higher than combination A.

[0048] When L = 0.40 meters: Combination G:T out = 200℃, V out = 30 meters per second. (Reference) Figure 2 The temperature retention coefficient at this distance further decreases, and T is calculated. ice Approximately 155℃, T surface Approximately 40℃, P d The energy consumption is approximately 290 Pascals, satisfying all constraints. However, the de-icing time is extended to approximately 10.5 minutes (0.175 hours), with an energy consumption of E ≈ 7.4 kWh.

[0049] Enter Figure 1 Step S4, as shown, compares the energy consumption among all feasible solutions. These feasible solutions include combinations A (5.6 kWh), C (8.4 kWh), D (12.6 kWh), E (7.0 kWh), F (6.0 kWh), and G (7.4 kWh). The comparison shows that combination A has the lowest total de-icing energy consumption, at 5.6 kWh. Therefore, the optimal parameter combination is determined as follows: outlet temperature T... out = 180℃, outlet air velocity V out = 25 meters per second, working distance L = 0.20 meters.

[0050] It should be noted that in the parameter space search of this embodiment, the energy consumption values ​​of each feasible solution are significantly different, and the optimal solution is uniquely determined to be the above combination. Under other possible operating conditions or more refined parameter discretization step sizes, if two or more different parameter combinations simultaneously reach the minimum energy consumption, then according to the provisions of the method of this invention, the parameter combination with the largest working distance L is preferentially selected to maximize the electrical safety margin.

[0051] Enter Figure 1Step S5, as shown, outputs the optimal parameter combination (180°C, 25 m / s, 0.20 m) to the de-icing device's control system as a control command. Upon receiving the command, the control system adjusts the heater power to stabilize the outlet temperature at 180°C and adjusts the blower speed to stabilize the outlet air velocity at 25 m / s. The operator uses an insulated operating rod or robotic arm to aim the outlet at the ice-covered area of ​​the casing and maintains a working distance of 0.20 meters to perform the de-icing operation.

[0052] Figure 3 This is a schematic diagram of the above-mentioned live hot air de-icing operation. Figure 3 As shown, the blower sends ambient air into the heater for heating, and the high-temperature airflow is then ejected from the outlet through the air duct, spraying onto the surface of the icing sleeve. A working distance L is maintained between the outlet and the sleeve surface. The actual operating scenario of this embodiment is similar to... Figure 3 As shown: the de-icing device is located on the lower side of the casing, with the air outlet facing the ice-covered area of ​​the casing. The operator controls the position and angle of the air outlet through the insulated operating rod to ensure that the working distance is stable at 0.20 meters.

[0053] The actual de-icing operation took approximately 8 minutes, which is largely consistent with the optimized prediction. After the operation, the ice on the casing surface was completely removed, and the bushing surface showed no cracks, burns, or mechanical damage; the casing's external insulation was in good condition. No abnormal discharges or high-speed ice splashes occurred during the entire operation, ensuring the safety of both personnel and equipment. The actual energy consumption was approximately 5.6 kWh, demonstrating that the optimized method of this invention achieves minimal energy consumption while ensuring safety, proving its effectiveness. Example

[0054] This embodiment uses a live-line hot air de-icing operation at a 750kV ultra-high voltage substation in central my country as its application example. The main difference from Embodiment 1 is the lower ambient temperature and the type of icing being rime ice, demonstrating the applicability of the method under different icing types and environmental conditions. This embodiment also refers to... Figure 1 The process shown is executed.

[0055] Environmental parameters on the day of the operation: ambient temperature T0 was -5℃, relative humidity was 80%, wind speed was 3 m / s, and the weather condition was freezing rain. The object of the operation was a 750kV line bushing, with porcelain outer insulation. On-site observation showed that the bushing surface was covered with frost, appearing as a transparent, smooth, and hard ice shell. The frost thickness D was measured manually. ice It is 10 millimeters.

[0056] The de-icing device used is the same as in Example 1, with a rated heating power P of 42 kilowatts.

[0057] according to Figure 1Step S1: Obtain parameters: T0 = -5℃, D ice =10 mm, icing type is rime.

[0058] according to Figure 1 Step S2: Establish the optimization model: Optimization objective: min E = 42·t C1: L ≥ 0.20 meters (750kV safety distance) C2:T surface ≤190℃ (maximum allowable operating temperature of the ceramic jacket) C3:T ice ≥0℃ C4:P d ≤800 Pascals (Safe peel pressure threshold for icing) according to Figure 1 Step S3 involves calculating the jet heat transfer model: As the ambient temperature drops to -5℃, the temperature difference between the jet and the environment increases, leading to relatively greater heat loss. Therefore, the calibration curve for the temperature retention coefficient η(L) needs to be corrected for the low-temperature environment or a calibrated full-range ambient temperature curve should be used. In this embodiment, an established full-range ambient temperature calibration database is used, referring to… Figure 2 The decay trend shown is used to find the corresponding η(L) value and then perform the calculation.

[0059] The calculation results for typical parameter combinations are as follows: Combination H:T out = 190℃, V out = 28 meters per second, L = 0.20 meters. (Refer to...) Figure 2 Under these distance and ambient temperature conditions, T was calculated. ice Approximately 158℃, satisfying C3; T surface The temperature is approximately 48℃, far below the 190℃ limit for the ceramic outer layer, thus satisfying C2; P d The energy density is approximately 470 Pascals, which is below the 800 Pascal threshold for rime ice, satisfying C4. This combination satisfies all constraints and is a feasible solution. According to the empirical model, the time required to melt 10 mm thick rime ice is approximately 7 minutes (0.117 hours), with an energy consumption of E ≈ 4.9 kWh.

[0060] Combination I: T out = 170℃, V out = 22 meters per second, L = 0.20 meters. Calculations show that T... ice Approximately 141℃, T surface Approximately 39℃, P dThe energy consumption is approximately 290 Pascals, which satisfies the constraints. However, the de-icing time is extended to approximately 10 minutes (0.167 hours), and the energy consumption E ≈ 7.0 kWh is higher than that of combination H.

[0061] Combination J:T out = 200℃, V out = 32 meters per second, L = 0.20 meters. Calculations show that T... ice Approximately 172℃, T surface It was approximately 52°C, but P d The value is approximately 610 Pascals, which is lower than 800 Pascals. However, considering the local stress concentration in the ice shell of the rime ice, this combination is mathematically feasible but not optimal in order to leave sufficient safety margin.

[0062] Combination K:T out = 190℃, V out = 28 meters per second, L = 0.30 meters. (Refer to...) Figure 2 As the distance increases, the temperature decay intensifies, according to calculations T ice Approximately 148℃, T surface Approximately 44℃, P d The energy consumption is approximately 340 Pascals, which satisfies all constraints. The de-icing time is approximately 8.5 minutes (0.142 hours), and the energy consumption is approximately 6.0 kWh.

[0063] according to Figure 1 Step S4 involves selecting the optimal parameters: comparing the energy consumption of feasible solutions, combination H has the lowest energy consumption of 4.9 kWh, and is therefore determined as the optimal parameter combination: T out = 190℃, V out = 28 meters per second, L = 0.20 meters.

[0064] according to Figure 1 Step S5 output execution: The control system executes the de-icing operation according to the optimal parameters. The actual operation scenario is also referred to. Figure 3 The arrangement shown has the air outlet aligned with the ice-covered area of ​​the ceramic sleeve, maintaining a working distance of 0.20 meters. In actual operation, it took approximately 7 minutes to completely remove the frost and ice from the surface of the ceramic sleeve, without damage or abnormal discharge, verifying the applicability of the method of this invention to frost and ice accumulation.

[0065] As can be seen from Examples 1 and 2, the method of the present invention can automatically adjust the optimization objectives and constraints according to different ambient temperatures, icing thicknesses, and icing types. Through quantitative calculations using a jet heat transfer model, it finds the optimal combination of operating parameters with the lowest energy consumption within the feasible region that satisfies all safety constraints. This method is not only applicable to the two typical icing types, rime and glaze, but also to mixed icing; it simply requires adjusting P in constraint C4. safeSimply set it to 650 Pascals; the optimization process remains exactly the same.

[0066] In summary, the present invention provides a method for optimizing the operating parameters of an ultra-high voltage live-line hot air de-icing device. By establishing an optimization model with the goal of minimizing energy consumption, it incorporates four constraints—safe distance for live-line work, material thermal protection, de-icing effectiveness, and jet impact safety—into a unified framework. A jet heat transfer model is used to quantitatively evaluate the parameter combinations, ultimately outputting the optimal operating parameters to guide on-site de-icing operations. This method elevates empirical judgment to scientific optimization, minimizing de-icing energy consumption while ensuring multiple safety measures, demonstrating significant engineering practical value and promising prospects for widespread application.

[0067] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing the operating parameters of an ultra-high voltage live-lined hot air de-icing device, characterized in that, Includes the following steps: Step S1: Obtain environmental parameters and icing status parameters of the work site, including at least the ambient temperature T0 and the icing thickness D. ice and icing type; Step S2: Establish an optimization model with the goal of minimizing the total de-icing energy consumption E and multiple safety constraints. The optimization goal is min E = P·t, where P is the heating power and t is the de-icing time. The constraints include: the working distance L from the air outlet to the surface of the sleeve is not less than the minimum safe distance L for live working at the corresponding voltage level. min Safety distance constraints; maximum surface temperature T of the sleeve skirt surface The maximum allowable operating temperature T of the material shall not exceed max Material protection constraints; temperature T when hot air reaches the ice surface ice The effective melting temperature requirement is no lower than 0°C; and the dynamic pressure P of the hot air jet on the ice surface is also considered. d Not exceeding the ice layer safe peel pressure threshold P safe Jet safety constraints; Step S3: Calculate the outlet temperature T using a jet heat transfer model. out Outlet air velocity V out T combined with working distance L ice T surface and P d The jet heat transfer model is based on the free jet theory of circular tubes, and calculates the temperature attenuation and dynamic pressure attenuation during the process of hot air reaching the ice surface from the air outlet. Step S4: Among the parameter combinations that satisfy all constraints, select the optimal parameter combination that minimizes the total de-icing energy consumption E. Step S5: Output the optimal parameter combination to the control system of the de-icing device to perform the de-icing operation.

2. The method according to claim 1, characterized in that, The ice layer safety stripping pressure threshold P mentioned in step S2 safe Determined based on the type of icing: When rime ice forms, P safe =500Pa, P when rime ice forms safe =800Pa, when mixed frost covers ice, take the median value of the corresponding thresholds of rime and glaze.

3. The method according to claim 1, characterized in that, In step S2, for a voltage level of 750kV, the minimum safe distance L for live-line work is... min The value is taken as 0.20m; for silicone rubber composite outer sleeves, the maximum allowable operating temperature T is... max The maximum allowable operating temperature is set at 170℃; for porcelain outer sleeves, the maximum allowable operating temperature T is... max The temperature was set at 190℃.

4. The method according to claim 1, characterized in that, In step S3, the formula for calculating the temperature decay is: T ice = T0 + (T out - T0)·η(L), where η(L) is the temperature retention coefficient related to distance L, determined by a pre-calibrated attenuation curve; the calculation formula for the dynamic pressure attenuation is: P d = 0.5·ρ·v²·μ(L), where ρ is the air density, v is the center wind speed, and μ(L) is the dynamic pressure retention coefficient related to distance L, which is determined by a pre-calibrated attenuation curve.

5. The method according to claim 4, characterized in that, The calibration method for the temperature retention coefficient η(L) and dynamic pressure retention coefficient μ(L) includes: under standard environmental conditions, using a thermocouple array and a dynamic pressure measuring device to measure the cross-sectional mass average temperature and central dynamic pressure of the hot air at different operating distances L, obtaining experimental data, and establishing the attenuation curve through data fitting.

6. The method according to claim 1, characterized in that, In step S4, when there are multiple feasible parameter combinations that simultaneously minimize the total de-icing energy consumption E, the parameter combination with the largest working distance L is selected first to maximize the electrical safety margin.

7. The method according to claim 1, characterized in that, In step S1, the ambient temperature T0 is obtained through an on-site meteorological sensor; the icing thickness D... ice The ice type is obtained through manual observation or prediction based on an equivalent model; the ice type is determined according to meteorological conditions and on-site observation, and is mainly divided into rime, glaze and mixed glaze.

8. The method according to claim 1, characterized in that, The de-icing time t and the outlet temperature T mentioned in step S2 out Outlet air velocity V out Working distance L and icing thickness D ice The relevant information is determined through a pre-calibrated empirical model or experimental database.

9. The method according to claim 1, characterized in that, In step S4, the process of selecting the optimal parameter combination is as follows: within the preset range of outlet temperature, outlet wind speed and working distance parameters, the jet heat transfer model calculation of step S3 is performed sequentially for each discrete parameter combination to determine whether all the constraints of step S2 are met. For the parameter combination that meets the constraints, the corresponding total de-icing energy consumption E is calculated, and the optimal parameter combination that minimizes E is obtained by comparison.

10. The method according to claim 1, characterized in that, In step S5, the optimal parameter combination is output to the control system of the de-icing device in the form of a digital signal or communication protocol. The control system adjusts the output power of the heater and the speed of the blower according to the optimal parameter combination to make the outlet temperature T out and outlet air velocity V out To achieve the optimal value and maintain a stable working distance L.

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