High-voltage switch cabinet anti-condensation method based on simulation optimization and storage medium

Abstract

The invention provides a high-voltage switch cabinet anti-condensation method based on simulation optimization and a storage medium. A three-dimensional physical structure model of the high-voltage switch cabinet is established in simulation software, material attributes and boundary conditions of all parts are set, steady-state or transient simulation calculation is carried out, and distribution of a temperature field, a humidity field and a flow velocity field in the cabinet is obtained. And on the basis of a simulation result, constructing a dew point distribution matrix, identifying condensation risk areas, and extracting geometric center, volume and temperature and humidity characteristics of each risk area. And the arrangement point and the power level of the heater are determined by calculating the heating power required by each condensation risk area, so that the anti-condensation design of the high-voltage switch cabinet is realized. According to the method, the condensation risk area in the cabinet can be accurately identified, the configuration of the heating power is optimized, and the balance and high efficiency of the anti-condensation effect are ensured. According to the invention, the precision and reliability of the anti-condensation design are improved, the problem of excessive heating or insufficient heating is avoided, and the safe and stable operation of the high-voltage switch cabinet in a complex environment is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of high - voltage switch cabinets, and particularly relates to a condensation prevention method and storage medium for high - voltage switch cabinets based on simulation optimization. Background Art

[0002] As one of the important equipment in the power system, high - voltage switch cabinets are widely used in fields such as power, communication, petrochemical, etc., and undertake the functions of power equipment distribution, control, and protection. Due to its usually complex and diverse working environment, the temperature, humidity, and air - flow distribution inside the switch cabinet are easily affected by the external environment, equipment operation conditions, and structural design. In some special cases, such as too high temperature or humidity, the gas inside the cabinet may reach the dew point due to temperature changes, leading to the occurrence of condensation. Condensation will form water droplets on the surface of electrical equipment, which may not only cause short - circuits, equipment corrosion, but also affect the insulation performance of the equipment. In severe cases, it may even cause equipment failures or fires, posing a great threat to the safety and stability of equipment operation.

[0003] Therefore, how to effectively prevent condensation in high - voltage switch cabinets and ensure the safe and stable operation of equipment under various environmental conditions has become a key problem that must be solved in the design and maintenance of high - voltage switch cabinets.

[0004] In the prior art, Chinese Patent CN114462235A discloses a condensation prevention method for high - voltage switch cabinets, which establishes a three - dimensional calculation model for the simulation of the condensation process in the switch cabinet. Compared with the traditional two - dimensional model, it can greatly improve the accuracy of the calculation results. The numerical calculation model takes into account the coupling between the electromagnetic - temperature - humidity fields, and can accurately reflect the actual transfer and coupling process of the temperature and humidity inside the switch cabinet during operation. Through the numerical calculation model, the surface convective heat transfer coefficient and moisture transfer coefficient with excellent condensation prevention performance of the insulating parts inside the switch cabinet are obtained, which can effectively guide the condensation prevention design of the switch cabinet.

[0005] However, the above - mentioned method focuses on the calculation of temperature - humidity coupling and moisture diffusion, but ignores the influence of the air - flow distribution inside the cabinet on the condensation prevention effect. The dynamic change of the air - flow inside the switch cabinet will affect the transmission of heat and moisture, which is crucial for the condensation prevention design. Ignoring the influence of the air - flow field may lead to uneven condensation prevention effect, or even unable to effectively prevent condensation in some areas. And this method is more based on the overall temperature - humidity calculation for condensation prevention design, lacking the identification and analysis of specific condensation - risk areas. Summary of the Invention

[0006] The purpose of the present invention is to overcome the above - mentioned defects existing in the prior art and provide a condensation prevention method and storage medium for high - voltage switch cabinets based on simulation optimization.

[0007] The object of the present invention can be achieved by the following technical solutions:

[0008] On the one hand, the present invention provides a method for preventing condensation in high-voltage switchgear based on simulation optimization, including the following steps:

[0009] Step S1: Establish a three-dimensional physical structure model of the high-voltage switchgear in the simulation software;

[0010] Step S2: Add the material properties and boundary conditions of each part of the three-dimensional physical structure model in the simulation software;

[0011] Step S3: Perform steady-state or transient simulation calculations on the three-dimensional physical structure model in the simulation software using an adaptive step-size control time iteration method to obtain simulation results, including the temperature field distribution, humidity field distribution, and flow velocity field distribution of the three-dimensional distribution inside the cabinet body;

[0012] Step S4: Based on the simulation results, construct a dew point distribution matrix, and identify the areas that meet the condensation conditions according to the relationship between the simulation results and the dew point distribution matrix, and construct a condensation risk distribution matrix;

[0013] Step S5: Extract the condensation risk areas, their geometric centers, regional volumes, and average temperature and humidity characteristic parameters according to the condensation risk distribution matrix;

[0014] Step S6: Calculate the heating power required for each condensation risk area according to the condensation risk area, its geometric center, regional volume, and average temperature and humidity characteristic parameters, and determine the corresponding initial heater layout points and power levels;

[0015] Step S7: Arrange heaters in the high-voltage switchgear according to the determined initial heater layout points and power levels to achieve condensation prevention in the high-voltage switchgear.

[0016] Furthermore, the material properties include the thermal conductivity, specific heat capacity, density, and electrical insulation performance parameters of each component, and the boundary conditions include the external environmental temperature, external environmental relative humidity, external wind speed, heat exchange boundary on the cabinet surface, power consumption distribution of internal heating elements, and initial temperature and humidity conditions of the simulation area.

[0017] Furthermore, the heat exchange boundary on the cabinet surface includes the convective heat transfer amount and the radiative heat transfer amount, and the convective heat transfer amount q w satisfies the formula:

[0018] q w = h c (T w - T c )

[0019] where q wis the convective heat transfer quantity between the cabinet shell and the environment, h c is the convective heat transfer coefficient, T w is the surface temperature of the cabinet shell, T c is the external environmental temperature;

[0020] The radiative heat transfer quantity q r satisfies the Stefan–Boltzmann law:

[0021]

[0022] where, q r is the radiative heat transfer quantity between the cabinet shell and the environment, ε1 is the emissivity of the cabinet shell surface, σ b is the Stefan–Boltzmann constant;

[0023] The power consumption distribution of the internal heating elements includes the resistive heat generated by the current-carrying components, and its volumetric heating rate H gen satisfies the formula:

[0024]

[0025] where, K if is the skin effect coefficient, and the formula is:

[0026]

[0027] where, I is the load current, S is the cross-sectional area of the conductor, and ρ0 is the resistivity of the conductor material.

[0028] Further, the temperature field distribution is T(x, y, z), where T(x, y, z) represents the three-dimensional distribution function of the temperature values of each point in the three-dimensional physical structure model changing with position;

[0029] The humidity field distribution is H(x, y, z), representing the relative humidity values of each point in the three-dimensional physical structure model;

[0030] The flow velocity field distribution is V(x, y, z), representing the natural convection air flow velocity vector field generated by the temperature difference of each point in the cabinet interior in the three-dimensional physical structure model.

[0031] Further, based on the simulation results, a dew point distribution matrix is constructed, specifically including:

[0032] Based on the temperature field distribution T(x, y, z) and humidity field distribution H(x, y, z) obtained from the simulation results, the dew point distribution matrix D(x, y, z) is calculated, and its calculation formula is:

[0033]

[0034] Among them, x(x, y, z) represents the dew point temperature at the point (x, y, z) in the three-dimensional space inside the high-voltage switchgear, a and b are constants, and γ(T(x, y, z), H(x, y, z)) is an intermediate variable, and the calculation formula is:

[0035]

[0036] Obtain the dew point distribution matrix D(x, y, z).

[0037] Furthermore, the dew risk distribution matrix is:

[0038]

[0039] Among them, R(x, y, z) is the dew risk distribution matrix, indicating whether the point (x, y, z) is a condensation risk point. 1 means there is a condensation risk, and 0 means there is no risk. T(x, y, z) and H(x, y, z) are the temperature field distribution and humidity field distribution in the simulation results respectively, and D(x, y, z) is the dew point distribution matrix.

[0040] Furthermore, extracting the condensation risk area, its geometric center, regional volume, and average temperature and humidity characteristic parameters according to the condensation risk distribution matrix specifically includes:

[0041] Using the connected region algorithm, extract all condensation risk regions {S1, S2,..., S n} with a value of 1 from the condensation risk distribution matrix R(x, y, z), where each S i represents an independent condensation risk region;

[0042] For each condensation risk region S i , calculate its geometric center C i , and the calculation formula for the geometric center is:

[0043]

[0044] Among them, |S i | is the number of grid points in the region S i , and (x, y, z) are the coordinates of each grid point;

[0045] Calculate the volume V i of each condensation risk region S i :

[0046] V i = |S i |·Δx·Δy·Δz

[0047] Among them, Δx, Δy, and Δz are the grid space resolutions of the region S i in the x, y, and z directions respectively;

[0048] According to the simulation results, extract the average temperature T i inside each condensation risk area S avg (S i ) and the average humidity H avg (S i ). The calculation formula is as follows:

[0049]

[0050] where T(x, y, z) and H(x, y, z) are the temperature field distribution and humidity field distribution in the simulation results respectively.

[0051] Furthermore, the connected region algorithm is used to extract all condensation risk areas {S1, S2,..., S n} with a value of 1 from the condensation risk distribution matrix R(x, y, z). Specifically, it includes:

[0052] Traverse each grid point in the condensation risk distribution matrix, select an unvisited point with a value of 1 as the starting point of the region, and use the depth-first search algorithm to search for all connected points with a value of 1 until there are no more connected points;

[0053] After the DFS algorithm finishes searching for a connected region, add all points in this region to the set S i and add this region to the set of condensation risk areas {S1, S2,..., S n}.

[0054] Furthermore, according to the condensation risk area, its geometric center, regional volume, and average temperature and humidity characteristic parameters, calculate the heating power required for each condensation risk area, and determine the corresponding initial layout points and power levels of the heaters. Specifically, it includes:

[0055] According to the volume V o of each condensation risk area S i and the average temperature T avg (S i ) and the average humidity H avg (S i ), as well as the flow velocity field distribution V(x, y, z), calculate the heating power P i of this region. The calculation formula is as follows:

[0056]

[0057] where k is the thermal conductivity, ΔT i = T target - T avg (S i) is the difference between the target temperature and the average temperature of the current area, ΔH i = H target - H avg (S i ) is the difference between the target humidity and the average humidity of the current area, V i is the area S i 's volume, t is the time required for heating, f(V(x, y, z)) is a function related to the flow velocity field distribution, representing the influence of air flow velocity on the heating power. The formula is:

[0058]

[0059] where, V max is the area S i 's maximum flow velocity;

[0060] Set the initial layout point of the heater as the geometric center C i of each condensation risk area S i .

[0061] On the other hand, the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements a method for preventing condensation in high-voltage switchgear based on simulation optimization as described in any one of the above.

[0062] Compared with the prior art, the present invention has the following advantages:

[0063] (1) By establishing a three-dimensional physical structure model of the high-voltage switchgear in the simulation software and combining a time iteration method with adaptive step control for steady-state or transient simulation calculations, the present invention accurately obtains the three-dimensional distributions of the temperature field, humidity field, and flow velocity field inside the cabinet. This technical means makes the simulation results more accurate and comprehensive, can reflect the actual transfer and coupling process of the temperature, humidity, and air flow inside the cabinet, avoids the limitations of traditional two-dimensional models, and improves the accuracy of the anti-condensation design.

[0064] (2) The present invention not only considers the changes in the temperature and humidity fields, but also fully considers the influence of air flow on the transmission of heat and moisture by calculating the flow velocity field inside the cabinet. This makes the anti-condensation design not only depend on the temperature and humidity conditions, but also can optimize the heating power and the layout of the heaters according to the actual air flow distribution, thus effectively avoiding the influence of the air flow field being ignored by traditional methods and ensuring the balance and comprehensiveness of the anti-condensation effect.

[0065] (3) By constructing a dew point distribution matrix and accurately identifying condensation risk areas based on the relationship between temperature, humidity and dew point, the present invention can effectively locate those areas in the switch cabinet that are most prone to condensation. Unlike the prior art, the present invention not only focuses on the overall temperature and humidity distribution, but also conducts a detailed analysis of each potential condensation point, so that anti-condensation measures can be applied to the areas that need it most, avoiding ineffective or excessive protection.

[0066] (4) The present invention calculates the required heating power based on the geometric center, regional volume, average temperature and humidity of each condensation risk area, and arranges the heaters reasonably based on these calculation results. This optimization scheme can ensure that the power distribution of the heaters in each area of the cabinet is both efficient and uniform, avoiding local overheating or underheating, and can also effectively save energy and improve the economy of system operation.

[0067] (5) The present invention extracts condensation risk areas through a connected area algorithm, and calculates the heating power and heater layout based on the specific conditions of each area (such as volume, temperature and humidity, airflow, etc.). Unlike traditional methods, the present invention can flexibly adjust the heating strategy, not only to solve the condensation problem in high-risk areas in a targeted manner, but also to flexibly adjust the anti-condensation strategy according to actual environmental changes, further enhancing the adaptability and resilience of the system.

[0068] (6) The present invention combines the calculation of temperature and humidity, airflow and heat exchange with the anti-condensation design scheme to form a complete optimization system. Through comprehensive simulation analysis and optimization design, not only the accuracy and effectiveness of anti-condensation measures are improved, but also the stability and safety of system design are ensured. This systematic integrated solution avoids the shortcomings of single factors or local designs, making the operation of high-voltage switchgear more reliable in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 is a flow chart of the method of the present invention;

[0070] Figure 2 A condensation risk area extraction flow chart of the present invention;

[0071] Figure 3 is a temperature field distribution diagram in the simulation results in an embodiment of the present invention;

[0072] Figure 4 is a humidity field distribution diagram in the simulation result in an embodiment of the present invention;

[0073] Figure 5 Graph 1 is the velocity field distribution in the simulation result in the embodiment of the present invention. DETAILED DESCRIPTION

[0074] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0075] On the one hand, this embodiment provides a method for preventing condensation in high-voltage switchgear based on simulation optimization, as Figure 1 shown, which includes the following steps:

[0076] Step S1: Establish a three-dimensional physical structure model of the high-voltage switchgear in the simulation software;

[0077] Among them, the three-dimensional physical structure model includes the following components: cable chamber, busbar chamber, circuit breaker chamber, and each chamber is separated by a metal plate.

[0078] Step S2: Add the material properties and boundary conditions of each part of the three-dimensional physical structure model in the simulation software;

[0079] Step S3: Perform steady-state or transient simulation calculations on the three-dimensional physical structure model in the simulation software using an adaptive step-size control time iteration method to obtain simulation results, including the temperature field distribution, humidity field distribution, and flow velocity field distribution of the three-dimensional distribution inside the cabinet. The simulation results obtained in this embodiment are as Figure 3 , Figure 4 , Figure 5 shown.

[0080] A time iteration method with adaptive step size control is used for steady-state or transient simulation calculations to obtain the temperature field, humidity field, and flow velocity field with three-dimensional distributions inside the cabinet body. The adaptive step size control can automatically adjust the time step according to the changes during the calculation process, thereby improving the calculation efficiency while ensuring the calculation accuracy. Through this simulation calculation, the temperature, humidity, and air flow distributions at different positions inside the high-voltage switchgear cabinet are obtained, accurately reflecting the heat and moisture transmission processes inside the cabinet. The technical effect of this step is that it can comprehensively master the temperature, humidity, and air flow distributions of the high-voltage switchgear cabinet through accurate simulation, providing sufficient data support for subsequent condensation risk analysis and heating design. In the steady-state simulation, it is assumed that the system reaches thermodynamic equilibrium, and the temperature and humidity distributions tend to be stable over time. This calculation method is applicable to the long-term operation of the high-voltage switchgear cabinet and can reflect the temperature, humidity, and air flow distributions under steady-state conditions. In the transient simulation, the time-varying process of the system is considered, such as the impact of instantaneous changes such as the startup of the switchgear cabinet and load fluctuations on the temperature, humidity, and air flow fields. These two simulation methods adjust the calculation accuracy and efficiency through adaptive step size control, ensuring accurate simulation under complex operating conditions. The technical effect of this step is that it can comprehensively master the temperature, humidity, and air flow distributions of the high-voltage switchgear cabinet through accurate simulation, providing sufficient data support for subsequent condensation risk analysis and heating design.

[0081] Step S4: Based on the simulation results, construct a dew point distribution matrix, and identify the regions that meet the condensation conditions according to the relationship between the simulation results and the dew point distribution matrix, and construct a condensation risk distribution matrix;

[0082] This matrix calculates the dew point temperature of each point inside the cabinet body by combining the temperature field distribution and the humidity field distribution, and identifies the regions that meet the condensation conditions. Through the relationship between the dew point and the temperature and humidity fields, it is possible to accurately identify which regions inside the cabinet have the risk of condensation, thus avoiding the inaccurate identification of condensation risk regions in traditional methods. The technical effect of this technical feature is that it can provide a precise target area for anti-condensation design, so that in subsequent anti-condensation measures, these high-risk areas can be focused on and optimized, improving the pertinence and effectiveness of anti-condensation measures.

[0083] Step S5: Extract the condensation risk regions and their geometric centers, regional volumes, and average temperature and humidity characteristic parameters based on the condensation risk distribution matrix;

[0084] Step S6: Calculate the heating power required for each condensation risk region according to the condensation risk regions and their geometric centers, regional volumes, and average temperature and humidity characteristic parameters, and determine the corresponding initial layout points and power levels of the heaters;

[0085] Extract specific condensation risk areas according to the condensation risk distribution matrix, including the geometric center, regional volume, and average temperature and humidity characteristic parameters of each area. Through the connected region algorithm, all areas with condensation risk can be extracted from the condensation risk distribution matrix, and by calculating their geometric centers, regional volumes, and temperature and humidity characteristics, specific bases can be provided for the calculation of heating power and the arrangement of heaters. The technical effect of this technical feature is that each condensation risk area is accurately identified and quantified, providing detailed regional information for the subsequent calculation of heating power and the arrangement of heaters, thus ensuring the scientificity and rationality of the heating design.

[0086] Step S7: Arrange heaters in the high-voltage switchgear according to the determined initial arrangement points and power levels of the heaters to achieve condensation prevention in the high-voltage switchgear.

[0087] The material properties include the thermal conductivity, specific heat capacity, density, and electrical insulation performance parameters of each component, and the boundary conditions include the external environmental temperature, external environmental relative humidity, external wind speed, heat exchange boundary on the cabinet surface, power consumption distribution of internal heating elements, and the initial temperature and humidity conditions of the simulation area.

[0088] The heat exchange boundary on the cabinet surface includes the convective heat transfer amount and the radiative heat transfer amount. The convective heat transfer amount q w Satisfies the formula:

[0089] q w = h c (T w - T c )

[0090] Among them, q w is the convective heat transfer amount between the cabinet shell and the environment, h c is the convective heat transfer coefficient, T w is the temperature of the cabinet shell surface, T c is the external environmental temperature;

[0091] The radiative heat transfer amount q r Satisfies the Stefan–Boltzmann law:

[0092]

[0093] Among them, q r is the radiative heat transfer amount between the cabinet shell and the environment, ε1 is the emissivity of the cabinet shell surface, σ b is the Stefan–Boltzmann constant;

[0094] The power consumption distribution of internal heating elements includes the resistive heat generated by current-carrying components, and its volumetric heating rate H gen Satisfies the formula:

[0095]

[0096] Among them, K if is the skin effect coefficient, and the formula is:

[0097]

[0098] Among them, I is the load current, S is the cross-sectional area of the conductor, and ρ0 is the resistivity of the conductor material.

[0099] The temperature field distribution is T(x, y, z). Among them, T(x, y, z) represents the three-dimensional distribution function of the temperature values of each point in the three-dimensional physical structure model changing with position;

[0100] The humidity field distribution is H(x, y, z), representing the relative humidity values of each point in the three-dimensional physical structure model;

[0101] The flow velocity field distribution is V(x, y, z), representing the natural convection air flow velocity vector field generated by the temperature difference at each point in the cabinet body of the three-dimensional physical structure model.

[0102] Based on the simulation results, a dew point distribution matrix is constructed, specifically including:

[0103] Based on the temperature field distribution T(x, y, z) and humidity field distribution H(x, y, z) obtained from the simulation results, calculate the dew point distribution matrix D(x, y, z), and its calculation formula is:

[0104]

[0105] Among them, D(x, y, z) represents the dew point temperature at the point (x, y, z) in the three-dimensional space inside the high-voltage switchgear, a and b are constants, and γ(T(x, y, z), H(x, y, z)) is an intermediate variable, and the calculation formula is:

[0106]

[0107] Obtain the dew point distribution matrix D(x, y, z).

[0108] The dew risk distribution matrix is:

[0109]

[0110] Among them, R(x, y, z) is the dew risk distribution matrix, indicating whether the point (x, y, z) is a condensation risk point. 1 indicates the existence of condensation risk, 0 indicates no risk, T(x, y, z) and H(x, y, z) are respectively the temperature field distribution and humidity field distribution in the simulation results, and D(x, y, z) is the dew point distribution matrix.

[0111] Extract the condensation risk areas, their geometric centers, regional volumes, and average temperature and humidity characteristic parameters according to the condensation risk distribution matrix, such as Figure 2 shown below, specifically including:

[0112] Using the connected region algorithm, extract all condensation risk areas {S1, S2,..., S n} with a value of 1 from the condensation risk distribution matrix R(x, y, z), where each S i represents an independent condensation risk area;

[0113] For each condensation risk area S i , calculate its geometric center C i , and the calculation formula for the geometric center is:

[0114]

[0115] where |S i | is the number of grid points in area S i , and (x, y, z) are the coordinates of each grid point;

[0116] Calculate the volume V i of each condensation risk area S i :

[0117] V i = |S i |·Δx·Δy·Δz

[0118] where Δx, Δy, and Δz are the grid space resolutions of area S i in the x, y, and z directions respectively;

[0119] According to the simulation results, extract the average temperature T i (S avg ) and average humidity H i (S avg ) within each condensation risk area S i , and the calculation formulas are:

[0120]

[0121] where T(x, y, z) and H(x, y, z) are the temperature field distribution and humidity field distribution in the simulation results respectively.

[0122] Using the connected region algorithm, extract all condensation risk areas {S1, S2,..., S n} with a value of 1 from the condensation risk distribution matrix R(x, y, z), specifically including:

[0123] Traverse each grid point in the condensation risk distribution matrix, select an unvisited point with a value of 1 as the starting point of the area, and use the depth-first search algorithm to search for all connected points with a value of 1 until there are no more connected points;

[0124] After the DFS algorithm finishes searching for a connected area, add all the points in this area to the set S i and add this area to the condensation risk area set {S1, S2, …, S n}.

[0125] According to the condensation risk area, its geometric center, area volume and average temperature and humidity characteristic parameters, calculate the heating power required for each condensation risk area, and determine the corresponding initial layout points and power levels of the heaters, specifically including:

[0126] According to the volume V i and average temperature T i (S avg ) and average humidity H i (S avg ) of each condensation risk area S i , as well as the flow velocity field distribution V(x, y, z), calculate the heating power P i of this area, and the calculation formula is:

[0127]

[0128] where k is the thermal conductivity, ΔT i = T target - T avg (S i ) is the difference between the target temperature and the average temperature of the current area, ΔH i = H target - H avg (S i ) is the difference between the target humidity and the average humidity of the current area, V i is the volume of area S i , t is the heating time required, and f(V(x, y, z)) is a function related to the flow velocity field distribution, representing the influence of air flow velocity on the heating power, and the formula is:

[0129]

[0130] where V max is the maximum value of the flow velocity of area S i ;

[0131] Set the initial layout points of the heaters as the geometric centers C i of each condensation risk area S i .

[0132] In summary, through precise three-dimensional simulation calculations, detailed condensation risk analysis, optimized heating power calculations, and reasonable heater arrangements, the anti-condensation design inside the high-voltage switchgear has been successfully achieved in this embodiment. The effective combination and optimization of each technical feature have improved the accuracy, reliability, and economy of the anti-condensation design, ensuring the safe and stable operation of the high-voltage switchgear in complex environments.

[0133] If the above functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0134] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A method for preventing condensation in high-voltage switchgear based on simulation optimization, characterized in that It includes the following steps: Step S1: Establish a three-dimensional physical structure model of the high-voltage switchgear in the simulation software; Step S2: Add the material properties and boundary conditions of each part of the three-dimensional physical structure model in the simulation software; Step S3: Perform steady-state or transient simulation calculations on the three-dimensional physical structure model in the simulation software using an adaptive step-size control time iteration method to obtain simulation results, including the temperature field distribution, humidity field distribution, and flow velocity field distribution of the three-dimensional distribution inside the cabinet body; Step S4: Based on the simulation results, construct a dew point distribution matrix, and identify the areas that meet the condensation conditions according to the relationship between the simulation results and the dew point distribution matrix, and construct a condensation risk distribution matrix; Step S5: Extract the condensation risk areas, their geometric centers, regional volumes, and average temperature and humidity characteristic parameters according to the condensation risk distribution matrix; Step S6: Calculate the heating power required for each condensation risk area according to the condensation risk area, its geometric center, regional volume, and average temperature and humidity characteristic parameters, and determine the corresponding heater layout points and heating power; Step S7: Arrange heaters in the high-voltage switchgear according to the determined heater layout points and heating power to achieve anti-condensation of the high-voltage switchgear.

2. The method for preventing condensation in a high-voltage switchgear based on simulation optimization according to claim 1, wherein, The material properties include the thermal conductivity, specific heat capacity, density, and electrical insulation performance parameters of each component. The boundary conditions include the external environmental temperature, external environmental relative humidity, external wind speed, heat exchange boundary on the cabinet surface, power consumption distribution of internal heating elements, and the initial temperature and humidity conditions of the simulation area.

3. A method for preventing condensation in high-voltage switchgear based on simulation optimization according to claim 2, characterized in that, The heat exchange boundary on the surface of the cabinet body includes convective heat transfer and radiative heat transfer, and the convective heat transfer q w satisfies the formula: q w = h c (T w - T c ) where q w is the convective heat transfer quantity between the cabinet shell and the environment, h c is the convective heat transfer coefficient, T w is the surface temperature of the cabinet shell, and T c is the external environmental temperature; The radiative heat transfer quantity q r satisfies the Stefan–Boltzmann law: where q r is the radiative heat transfer between the cabinet shell and the environment, ε1 is the emissivity of the cabinet shell surface, and σ b is the Stefan–Boltzmann constant; The power consumption distribution of the internal heating element includes the resistive heat generated by the current-carrying component, and its heating rate per unit volume H gen satisfies the formula: Among them, K if is the skin effect coefficient, and the formula is: Where I is the load current, S is the cross-sectional area of the conductor, and ρ0 is the resistivity of the conductor material.

4. A method for preventing condensation in high-voltage switchgear based on simulation optimization according to claim 1, characterized in that The temperature field distribution is T(x, y, z), where T(x, y, z) represents the three-dimensional distribution function of the temperature values of each point in the three-dimensional physical structure model changing with position; The humidity field distribution is H(x, y, z), representing the relative humidity values of each point in the three-dimensional physical structure model; The flow velocity field distribution is V(x, y, z), representing the natural convection airflow velocity vector field generated by the temperature difference of the air at each point in the three-dimensional physical structure model inside the cabinet body.

5. A method for preventing condensation in high-voltage switchgear based on simulation optimization according to claim 1, characterized in that, Based on the simulation results, constructing a dew point distribution matrix specifically includes: Based on the temperature field distribution T(x, y, z) and humidity field distribution H(x, y, z) obtained from the simulation results, calculate the dew point distribution matrix D(x, y, z), and its calculation formula is: Where D(x, y, z) represents the dew point temperature at the point (x, y, z) in the three-dimensional space inside the high-voltage switchgear, a and b are constants, and γ(T(x, y, z), H(x, y, z)) is an intermediate variable, and the calculation formula is: Obtain the dew point distribution matrix D(x, y, z).

6. The method for preventing condensation in high-voltage switchgear based on simulation optimization according to claim 1, wherein The dew risk distribution matrix is: Where R(x, y, z) is the dew risk distribution matrix, indicating whether the point (x, y, z) is a condensation risk point. 1 indicates the existence of condensation risk, 0 indicates no risk, T(x, y, z) and H(x, y, z) are respectively the temperature field distribution and humidity field distribution in the simulation results, and D(x, y, z) is the dew point distribution matrix.

7. A method for preventing condensation in high-voltage switchgear based on simulation optimization according to claim 1, characterized in that Extracting the condensation risk area, its geometric center, regional volume and average temperature and humidity characteristic parameters according to the condensation risk distribution matrix specifically includes: Using the connected component algorithm, all condensation risk regions {S1, S2, …, S with a value of 1 are extracted from the condensation risk distribution matrix R(x, y, z). n}, where each S i represents an independent condensation risk region; For each condensation risk area S i , calculate its geometric center C i , and the calculation formula for the geometric center is: where |S i | is the number of grid points in region S i , and (x, y, z) are the coordinates of each grid point; Calculate the volume V of each condensation risk area S i i :​ V i = |S i |·Δx·Δy·Δz where Δx, Δy, and Δz are the grid space resolutions of the region S i in the x, y, and z directions, respectively; According to the simulation results, extract the average temperature T within each condensation risk area S i and the average humidity H avg (within S i ) with the calculation formula as follows: avg (within S i ) Among them, T(x, y, z) and H(x, y, z) are the temperature field distribution and humidity field distribution in the simulation results respectively.

8. A method for preventing condensation in high-voltage switchgear based on simulation optimization according to claim 7, characterized in that, Using the connected component algorithm, all dew condensation risk regions {S1, S2, …, S n} with a value of 1 are extracted from the dew condensation risk distribution matrix R(x, y, z), specifically including: Traverse each grid point in the condensation risk distribution matrix, select a point with an unvisited value of 1 as the starting point of the area, and use the depth-first search algorithm to search for all connected points with a value of 1 until there are no more connected points; After the DFS algorithm finishes searching a connected region, add all the points in this region to the set S i and add this region to the condensation risk region set {S1, S2, …, S n}.

9. A method for preventing condensation in high-voltage switchgear based on simulation optimization according to claim 1 or 7, characterized in that Calculating the heating power required for each condensation risk area according to the condensation risk area, its geometric center, regional volume and average temperature and humidity characteristic parameters, and determining the corresponding heater layout points and power levels, specifically including: According to the volume V i of each condensation risk area S i and the average temperature T avg (S i ) and the average humidity H avg (S i ), as well as the flow velocity field distribution V(x, y, z), calculate the heating power P i of this area. The calculation formula is: where k is the thermal conductivity, ΔT i = T target - T avg (S i ) is the difference between the target temperature and the average temperature of the current region, ΔH i = H target - H avg (S i ) is the difference between the target humidity and the average humidity of the current region, V i is the volume of region S i , t is the time required for heating, f(V(x, y, z)) is a function related to the flow velocity field distribution, representing the influence of the air flow velocity on the heating power, and the formula is: Among them, V max is the maximum value of the flow velocity in region S i ; Set the heater arrangement points as the geometric centers C of the respective condensation risk areas S i i .​ 10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the method according to any one of claims 1 to 9.

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