A power transmission tunnel ventilation system optimization design method based on negative heat source equivalence and multi-field coupling

Abstract

The application discloses a kind of based on negative heat source equivalence and multi-field coupling power transmission tunnel ventilation system optimization design method, belong to electric power transmission engineering technical field.The application is aimed at the problem that the three-dimensional fluid simulation calculation amount of long-distance underground power transmission tunnel is huge and difficult to parameterize optimization, first, two-dimensional finite element model containing equivalent negative heat source is constructed, and the heat dissipation effect of air axial flow is mapped as section heat absorption power;Subsequently, by electromagnetic-thermal-flow multi-physical field coupling calculation, the maximum allowable flow capacity under different ventilation wind speed and shaft spacing is obtained;Finally, the whole life cycle comprehensive cost function including capital construction quantity, ventilation node quantity and operation energy consumption is established, and the optimal ventilation design parameter is determined by optimization decision.The application significantly reduces the calculation time under the premise of ensuring the calculation accuracy, and can quickly realize the economy and technicality collaborative optimization of power transmission tunnel ventilation system.

Description

Technical Field

[0001] This invention relates to the field of power engineering and power transmission technology, specifically to an optimized design method for a power transmission tunnel ventilation system based on the equivalent negative heat source and multi-field coupling. Background Technology

[0002] With the advancement of the global energy transition, transmitting renewable energy resources concentrated in mountainous areas to load centers via long-distance power transmission channels has become a key requirement for energy development. Compared with traditional overhead transmission lines, underground tunnel power transmission technology has advantages such as less susceptibility to terrain limitations, lower environmental impact, and larger transmission capacity, and has been increasingly widely used.

[0003] In the design and operation of underground power transmission tunnels, heat dissipation and ventilation are core issues restricting their transmission capacity and safety. During operation, power conductors generate a significant amount of Joule heat. If this heat cannot be dissipated from the tunnel in a timely manner, causing the conductor temperature to exceed the tolerance limit of the insulation material, it will severely affect the service life of the line and even lead to safety accidents. Therefore, forced ventilation is essential to control the tunnel temperature.

[0004] However, existing design methods for power transmission tunnel ventilation systems have the following drawbacks:

[0005] 1. Inefficient simulation computation and difficulty in global optimization: Traditional tunnel ventilation simulations typically rely on three-dimensional computational fluid dynamics models to simulate airflow and heat transfer along the tunnel's axial direction. Since power transmission tunnels are often several kilometers or even tens of kilometers long and contain slender conductor structures, the number of three-dimensional meshes is extremely large, making computational convergence difficult and time-consuming. This makes it difficult for designers to perform large-scale scanning and optimization of parameters such as wind speed and shaft spacing within a limited timeframe, often forcing them to rely on experience to select fixed design parameters, thus failing to obtain the optimal solution.

[0006] 2. Lack of coupled evaluation of physical field and economics: Existing design methods usually only focus on the single technical indicator of temperature, while ignoring the economic cost of the ventilation system throughout its entire life cycle, which often leads to problems such as over-ventilation or redundant shafts in the design scheme.

[0007] 3. Insufficient consideration of multi-physics coupling mechanisms: In actual operation, the heat generated by the transmission conductor is not a fixed value, but varies with the load current; at the same time, the conductor loss is closely related to the spatial arrangement and temperature of the cable. Existing simplified calculation methods often treat the heat source as a constant value, ignoring the dynamic coupling relationship between the electromagnetic field, thermal field, and fluid field, resulting in a large deviation in the calculated current carrying capacity limit and affecting the accuracy of engineering design. Summary of the Invention

[0008] The purpose of this invention is to provide a design method for a power transmission tunnel ventilation system that can significantly reduce computational complexity, accurately simulate multi-field coupling effects, and optimize parameters based on full life-cycle performance.

[0009] To achieve the above objectives, this invention provides an optimized design method for a power transmission tunnel ventilation system based on the equivalent negative heat source and multi-field coupling, the method comprising:

[0010] Based on the geometric structure and material parameters of the power transmission tunnel, a two-dimensional finite element simulation model is constructed to analyze the electromagnetic-thermal coupling field of the power transmission tunnel section.

[0011] Based on the principles of fluid thermodynamics, an equivalent negative heat source model is constructed to characterize the axial ventilation and heat dissipation effect of power transmission tunnels;

[0012] Set an optimization variable set and constraints, wherein the optimization variables in the optimization variable set include ventilation wind speed and ventilation shaft spacing, and the constraints include restrictions on conductor temperature;

[0013] The equivalent negative heat source model is coupled to the two-dimensional finite element simulation model. For the combination of optimization variables in the set of optimization variables, electromagnetic field-thermal field joint simulation calculation is performed. The maximum allowable current carrying capacity of the conductor that meets the constraints is obtained by iterative solution.

[0014] Based on the maximum allowable current carrying capacity of the conductor, a comprehensive cost function is constructed to characterize the engineering resource consumption of a unit power transmission task throughout its entire life cycle;

[0015] The optimization is performed with the goal of minimizing the value of the comprehensive cost function to obtain the optimal solution for ventilation velocity and ventilation shaft spacing;

[0016] The optimal solution is used as the optimal design parameter for the power transmission tunnel ventilation system.

[0017] This invention constructs a two-dimensional finite element simulation model of an electromagnetic-thermal coupled field to characterize the spatial distribution of heat sources such as conductor Joule loss and induced heating of metal components at the cross-sectional scale. Simultaneously, it innovatively constructs an equivalent negative heat source model, transforming the macroscopic heat dissipation effect of axial ventilation into an equivalent heat dissipation term that can be embedded in the two-dimensional finite element simulation model, thus achieving a realistic physical coupling between the heat generation and heat dissipation mechanisms within a unified simulation framework. Based on this, ventilation velocity and ventilation shaft spacing are defined as optimization variables, and a safety constraint centered on conductor temperature is set. By iteratively solving for the maximum allowable current carrying capacity for each set of ventilation parameters, the transmission capacity under the thermal stability limit of any ventilation scheme is accurately determined. Furthermore, based on this transmission capacity, a comprehensive life-cycle cost function is constructed. This function normalizes the construction costs and operating energy consumption related to the ventilation scheme to the lifetime transmission capacity it can achieve. Its mathematical minimum value corresponds to the optimal design with the lowest unit transmission cost. This method integrates physical simulation, safety constraints, and economic evaluation. Through system optimization, it automatically outputs design parameters that theoretically combine safety and economy, realizing a fundamental shift from qualitative design that relies on experience to quantitative decision-making based on coupled simulation and multi-objective optimization.

[0018] Furthermore, the description of the axial ventilation and heat dissipation effect of the power transmission tunnel includes:

[0019] The heat carried away by the air flowing along the axial direction of the power transmission tunnel is equivalently mapped to the heat absorption power density applied to the air domain of the two-dimensional finite element simulation model.

[0020] The essence of axial ventilation in tunnels is the inflow of cold air, which absorbs heat along the way and then flows out—a process extremely complex in three-dimensional calculations. The equivalent mapping proposed in this invention abandons the simulation of flow field details and instead focuses on its macroscopic energy exchange nature: the total heat net removed by airflow within a tunnel section is considered as a sink uniformly applied to the air domains of all corresponding two-dimensional cross-sections of that tunnel section. The heat absorption power density is not a real physical source, but an equivalent mathematical model whose intensity represents the average heat dissipation capacity of ventilation at that cross-section. This innovative transformation simplifies a three-dimensional problem involving fluid dynamics into a source term problem that can be incorporated into a two-dimensional steady-state heat conduction partial differential equation, forming the basis for subsequent parametric analysis of ventilation.

[0021] Furthermore, the formula for calculating the heat absorption power applied to the air domain of the two-dimensional finite element simulation model is as follows:

[0022] ;

[0023] Where q is the heat absorption power applied to the air domain of the two-dimensional finite element simulation model; air density; The effective ventilation cross-sectional area of ​​the power transmission tunnel; Ventilation speed; The specific heat capacity of air; This refers to the spacing between ventilation shafts; For the local air temperature within the computational domain; Reference temperature for ventilation inlet; The unit computational length of the two-dimensional finite element simulation model is given.

[0024] This invention achieves high-precision two-dimensional modeling of complex three-dimensional ventilation and heat dissipation effects, effectively improving computational efficiency. The principle of this calculation formula is as follows: First, based on the principles of mass and energy conservation, the energy difference carried by air flowing through a certain cross-section of the tunnel per unit time is expressed as the product of air mass flow rate, air specific heat capacity, and temperature difference. This is the macroscopic heat dissipation power. Then, this originally continuously varying three-dimensional process along the axial direction is equivalently mapped onto a two-dimensional cross-section. Specifically, this is achieved by dividing the total heat dissipation power by the ventilation shaft spacing. The heat dissipation power per unit length along the tunnel axis was obtained, and further calculated using the unit calculation length of the two-dimensional finite element simulation model. This is converted into an endothermic power density q applied per unit volume within the air domain of the two-dimensional model. The formula uses the local air temperature within the computational domain. Instead of the average temperature, the heat sink intensity can dynamically change with the spatial temperature field, automatically enhancing heat dissipation in high-temperature areas and weakening heat dissipation in low-temperature areas, thereby accurately simulating the bidirectional coupling effect between ventilation and thermal field. As a result, this invention reduces simulation computing resources and time by two orders of magnitude.

[0025] Furthermore, the two-dimensional finite element simulation model includes an electromagnetic field calculation module and a thermal field calculation module;

[0026] Specifically, for any combination of optimization variables, a joint electromagnetic field-thermal field simulation is performed, and the maximum allowable current carrying capacity of the conductor that meets the constraints is obtained through iterative solution, including:

[0027] S1. Set the current test current carrying capacity;

[0028] S2. The Joule loss and induced current loss of the conductor under the current test current carrying capacity are calculated by the electromagnetic field calculation module.

[0029] S3. Using Joule loss and induced current loss as heat sources, and the heat absorption power applied to the air domain of the two-dimensional finite element simulation model as heat dissipation source, input the heat field calculation module to perform steady-state heat conduction calculation, obtain the conductor temperature distribution under the current test current carrying capacity, and extract the highest conductor temperature under the current test current carrying capacity.

[0030] S4. Determine whether the highest conductor temperature under the current test current carrying capacity meets the maximum operating temperature allowed by the constraint conditions. If it does, determine the current test current carrying capacity as the maximum allowable current carrying capacity of the conductor under the combination of optimized variables, and the iteration ends.

[0031] If the requirements are not met, adjust the value of the test current carrying capacity and return to step S2.

[0032] Finding the maximum current-carrying capacity of a conductor under a given combination of optimization variables is extremely difficult through direct analytical solutions. This invention decomposes this problem into sequential electromagnetic and thermal calculations, achieving automatic optimization. Specifically, starting with the initial experimental current-carrying capacity, each iteration executes the entire process of electromagnetic calculation of heat generation, equivalent heat dissipation, and thermal conduction calculation of temperature rise. Based on the comparison between the output conductor's highest temperature and the constraints, the current-carrying capacity input is intelligently adjusted. When the temperature constraint is met, the corresponding current-carrying capacity is the safe capacity limit under this ventilation scheme. This solves the problems of low accuracy and inability to consider complex coupling effects in traditional trial-and-error or empirical formula methods.

[0033] Furthermore, the maximum operating temperature allowed to meet the aforementioned constraints includes:

[0034] The highest conductor temperature under the current test current carrying capacity is not higher than the highest operating temperature allowed by the constraints, and the difference between the two is within the preset tolerance range.

[0035] Furthermore, the expression for the comprehensive cost function is:

[0036] ;

[0037] in, The value of the comprehensive cost function. The basic cost of the tunnel's main construction. The total construction cost of ventilation shafts is related to the spacing between ventilation shafts; its value is related to the spacing between ventilation shafts. Inversely proportional; In order to match the ventilation speed The relevant annual ventilation operation energy consumption cost, its value is related to wind speed It is directly proportional to the cube of the power; The entire lifespan; The transmission power is calculated based on the maximum allowable current carrying capacity. This refers to the transmission distance.

[0038] This function uses the ratio of total cost to total transmitted power, and its economic essence is the amortized cost per unit of transmitted electricity over its entire life cycle. The denominator contains the transmitted power. It is not a fixed value, but rather the ultimate power transmission capacity dynamically solved from the current ventilation parameters through the aforementioned multiphysics simulation. This constitutes a two-way feedback optimization mechanism: increasing wind speed... Although it can improve heat dissipation and increase transmission capacity However, this will increase energy costs. The increase is dramatic. Thus, minimizing this function means finding the ventilation scheme that minimizes the total cost of transmitting each kilowatt-hour of electricity while ensuring safe power transmission, fundamentally solving the problem of the disconnect between technical design and economic evaluation.

[0039] Furthermore, optimization is performed with the goal of minimizing the value of the comprehensive cost function to obtain the optimal solutions for ventilation velocity and ventilation shaft spacing, including:

[0040] Within the set of optimization variables, several different combinations of optimization variables are selected as samples;

[0041] Based on all samples and their corresponding comprehensive cost function values, a continuous response surface model is constructed from ventilation wind speed and ventilation shaft spacing to the comprehensive cost function value.

[0042] An extreme value search is performed on the response surface model to find the combination of ventilation velocity and ventilation shaft spacing that minimizes the comprehensive cost function value, which is the optimal solution.

[0043] In the high-dimensional continuous design space comprised of ventilation velocity and shaft spacing, global optimization would be computationally prohibitively expensive if coupled simulation iterations were performed for every point. Therefore, this paper proposes an optimization strategy. The principle is as follows: First, a finite number of sample points are selected within the design space, and their comprehensive cost function values ​​are obtained through accurate simulation calculations. Then, using these discrete data, a continuous response surface model covering the entire design space is constructed through mathematical interpolation or fitting methods. This model is a computationally inexpensive mathematical function that can approximate the complex physical simulation process. Finally, an extremum search is performed on this smooth response surface model to quickly locate the optimal solution.

[0044] Furthermore, the power transmission tunnel includes a gas-insulated power transmission line tunnel or a high-voltage AC cable tunnel;

[0045] When the power transmission tunnel is a gas-insulated power transmission line tunnel, the induced current loss includes the induced current loss of the tunnel shell.

[0046] When the power transmission tunnel is a high-voltage AC cable tunnel, the induced current loss includes the circulating current loss and eddy current loss of the cable's metal sheath.

[0047] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method for optimizing the design of a power transmission tunnel ventilation system based on the equivalent negative heat source and multi-field coupling.

[0048] The present invention also provides an optimized design device for a power transmission tunnel ventilation system, the device comprising:

[0049] The modeling module is used to construct a two-dimensional finite element simulation model for analyzing the electromagnetic-thermal coupling field of the power transmission tunnel cross section based on the geometric structure and material parameters of the power transmission tunnel; and to construct an equivalent negative heat source model for characterizing the axial ventilation and heat dissipation effect of the power transmission tunnel based on the principles of fluid thermodynamics.

[0050] The calculation module is used to set the set of optimization variables and constraints. The optimization variables in the set of optimization variables include ventilation wind speed and ventilation shaft spacing, and the constraints include restrictions on conductor temperature. The equivalent negative heat source model is coupled to the two-dimensional finite element simulation model. For the combination of optimization variables in the set of optimization variables, electromagnetic field-thermal field joint simulation calculation is performed. The maximum allowable current carrying capacity of the conductor that meets the constraints is obtained through iterative solution.

[0051] The evaluation module is used to construct a comprehensive cost function based on the maximum allowable current carrying capacity of the conductor to characterize the engineering resource consumption of a unit transmission task throughout its entire life cycle;

[0052] The optimization module is used to find the optimal solution for ventilation velocity and ventilation shaft spacing by minimizing the value of the comprehensive cost function; the optimal solution is used as the optimal design parameters for the power transmission tunnel ventilation system.

[0053] One or more technical solutions provided by this invention have at least the following technical effects or advantages:

[0054] 1. Significantly Improved Computational Efficiency: This invention utilizes a pioneering negative heat source equivalent model to reduce the dimensionality of complex 3D fluid-thermal coupling problems to 2D planar problems. Simulation experiments show that, while ensuring minimal calculation errors for key temperature parameters, the computation time for a single operating condition can be reduced from thousands of seconds to tens of seconds, improving computational efficiency by two orders of magnitude. This makes it possible to perform traversal optimization for hundreds or even thousands of operating conditions.

[0055] 2. High accuracy of multi-field coupling: Compared with simple empirical formulas, this invention retains the electromagnetic field calculation based on finite element method, which can accurately reflect the influence of skin effect, proximity effect and circulating current loss of cable metal sheath on thermal field, and ensure the accuracy of maximum current carrying capacity calculation.

[0056] 3. Achieves global optimization in both economy and technology: This invention breaks through the limitation of traditional design that only focuses on thermal safety. Through a comprehensive cost function throughout the entire life cycle, it quantifies the economic trade-off between drilling more vertical shafts and increasing wind speed, and can provide engineering design with a design scheme that meets the transmission capacity requirements while achieving maximum economic benefits. Attached Figure Description

[0057] The accompanying drawings, which are provided to further illustrate embodiments of the invention and constitute a part of this invention, are not intended to limit the scope of the invention.

[0058] Figure 1 This is a flowchart illustrating an optimization design method for a power transmission tunnel ventilation system based on the equivalent negative heat source and multi-field coupling, as described in this invention.

[0059] Figure 2 This is a schematic diagram illustrating the principle of simplifying the three-dimensional tunnel ventilation and heat dissipation model to a two-dimensional negative heat source equivalent model in Embodiment 1 of the present invention.

[0060] Figure 3 This is a schematic diagram of the two-dimensional cross-sectional modeling structure of the gas-insulated transmission line (GIL) tunnel in Embodiment 1 of the present invention;

[0061] Figure 4 This is a simplified two-dimensional modeling diagram of a high-voltage AC cable tunnel in Embodiment 1 of the present invention;

[0062] Figure 5 This is a thermal map of the maximum allowable current carrying capacity of a conductor obtained in the GIL tunnel scenario according to Embodiment 1 of the present invention;

[0063] Figure 6 This is a continuous response surface plot obtained for the GIL tunnel scenario in Embodiment 1 of the present invention;

[0064] Figure 7 This is a thermal diagram of the maximum allowable current carrying capacity of a conductor obtained in a high-voltage AC cable tunnel scenario according to Embodiment 1 of the present invention;

[0065] Figure 8 This is a continuous response surface plot obtained in Embodiment 1 of the present invention for a high-voltage AC cable tunnel scenario;

[0066] In the diagram, 1-inner insulating gas, 2-center conductor, 3-outer insulating gas, 4-metal shell, 5-copper conductor, 6-XLPE insulation layer, 7-semiconductor layer, 8-corrugated aluminum shielding layer, 9-outer sheath. Detailed Implementation

[0067] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, where there is no conflict, the embodiments of the present invention and the features thereof can be combined with each other.

[0068] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0069] Example 1

[0070] Please refer to Figure 1 Embodiment 1 of the present invention provides an optimization design method for a power transmission tunnel ventilation system based on the equivalent negative heat source and multi-field coupling. The method includes:

[0071] Based on the geometric structure and material parameters of the power transmission tunnel, a two-dimensional finite element simulation model is constructed to analyze the electromagnetic-thermal coupling field of the power transmission tunnel section.

[0072] Based on the principles of fluid thermodynamics, an equivalent negative heat source model is constructed to characterize the axial ventilation and heat dissipation effect of power transmission tunnels;

[0073] Set an optimization variable set and constraints, wherein the optimization variables in the optimization variable set include ventilation wind speed and ventilation shaft spacing, and the constraints include restrictions on conductor temperature;

[0074] The equivalent negative heat source model is coupled to the two-dimensional finite element simulation model. For the combination of optimization variables in the set of optimization variables, electromagnetic field-thermal field joint simulation calculation is performed. The maximum allowable current carrying capacity of the conductor that meets the constraints is obtained by iterative solution.

[0075] Based on the maximum allowable current carrying capacity of the conductor, a comprehensive cost function is constructed to characterize the engineering resource consumption of a unit power transmission task throughout its entire life cycle;

[0076] The optimization is performed with the goal of minimizing the value of the comprehensive cost function to obtain the optimal solution for ventilation velocity and ventilation shaft spacing;

[0077] The optimal solution is used as the optimal design parameter for the power transmission tunnel ventilation system.

[0078] The following uses GIL (Gas Insulated Line) tunnels and high-voltage AC cable tunnels as examples to illustrate the specific implementation process:

[0079] When obtaining the geometric structure and material parameters of the target tunnel, for GIL tunnels, the parameters include the tunnel inner diameter, the outer diameter and spacing of the GIL pipes, and the properties of each layer of materials, such as the electromagnetic and thermophysical parameters of the concrete lining, the inner insulating gas, and the outer shell. For high-voltage AC cable tunnels, the parameters include the tunnel inner diameter, the cable arrangement, and the conductor and sheath materials. Based on these parameters, a two-dimensional axisymmetric finite element simulation model is constructed in finite element software to analyze the tunnel cross-section.

[0080] In this embodiment, the optimization variables are set such that the ventilation velocity ranges from 0.5 to 5.0 m / s, and the spacing between ventilation shafts ranges from 1 to 10 km. When setting constraints, the maximum allowable conductor temperature is typically 105°C for GIL tunnels and 90°C for high-voltage AC cable tunnels. The maximum air temperature inside both types of tunnels does not exceed 40°C.

[0081] The description of the axial ventilation and heat dissipation effect of the power transmission tunnel includes:

[0082] The heat carried away by the air flowing along the axial direction of the power transmission tunnel is equivalently mapped to the heat absorption power density applied to the air domain of the two-dimensional finite element simulation model.

[0083] Among them, such as Figure 2 As shown on the left, traditional three-dimensional computational fluid dynamics simulation requires building a three-dimensional model of a tunnel several kilometers long, resulting in extremely long computation times. This invention proposes an equivalent dimensionality reduction approach, such as... Figure 2 As shown on the right, the cooling effect of three-dimensional axial flow is equivalent to applying a distributed endothermic power density to the air domain of a two-dimensional cross-sectional model. Figure 2 In this context, degC represents degrees Celsius. This method is applicable to both GIL tunnels and high-voltage AC cable tunnels. For a tunnel section with a length equal to the distance between ventilation shafts, the axial flow of air inside is considered as a negative heat source on that cross-section. Figure 2 In the three-dimensional model, the heat flux of tunnel ventilation is 434.18 W / m, the air temperature at the ventilation outlet is 20.678℃, the average conductor temperature is 100.56℃, and the simulation time for a single set of parameters is 5283 s. In the two-dimensional simplified model, the simplified negative heat source power is 434.56 W / m, the air temperature at the ventilation outlet is 20.629℃, the average conductor temperature is 96.95℃, and the simulation time for a single set of parameters is 47 s. This demonstrates that through this equivalent mapping, the present invention, while ensuring minimal calculation errors for key temperature indicators, reduces the calculation time for a single operating condition from thousands of seconds to tens of seconds, improving computational efficiency by two orders of magnitude. This makes it possible to perform optimization across hundreds or thousands of operating conditions.

[0084] The formula for calculating the heat absorption power applied to the air domain of the two-dimensional finite element simulation model is as follows:

[0085] ;

[0086] Where q is the heat absorption power applied to the air domain of the two-dimensional finite element simulation model; air density; The effective ventilation cross-sectional area of ​​the power transmission tunnel; Ventilation speed; The specific heat capacity of air; This refers to the spacing between ventilation shafts; For the local air temperature within the computational domain; Reference temperature for ventilation inlet; The unit computational length of the two-dimensional finite element simulation model is given.

[0087] In the formula, air density Specific heat capacity of air Reference temperature of ventilation inlet These are basic physical property parameters. Ventilation velocity. Spacing between ventilation shafts The effective ventilation cross-sectional area of ​​the power transmission tunnel is a design variable to be optimized. and local air temperature within the computational domain It needs to be determined based on the specific tunnel type. For example, for GIL tunnels, The area occupied by the GIL pipeline needs to be deducted; for high-voltage AC cable tunnels, The area occupied by multiple cables and their supports needs to be deducted. The simulation process is then fed back in real time by the two-dimensional finite element simulation model.

[0088] The two-dimensional finite element simulation model includes an electromagnetic field calculation module and a thermal field calculation module.

[0089] Specifically, for any combination of optimization variables, a joint electromagnetic field-thermal field simulation is performed, and the maximum allowable current carrying capacity of the conductor that meets the constraints is obtained through iterative solution, including:

[0090] S1. Set the current test current carrying capacity;

[0091] S2. The Joule loss and induced current loss of the conductor under the current test current carrying capacity are calculated by the electromagnetic field calculation module.

[0092] S3. Using Joule loss and induced current loss as heat sources, and the heat absorption power applied to the air domain of the two-dimensional finite element simulation model as heat dissipation source, input the heat field calculation module to perform steady-state heat conduction calculation, obtain the conductor temperature distribution under the current test current carrying capacity, and extract the highest conductor temperature under the current test current carrying capacity.

[0093] S4. Determine whether the highest conductor temperature under the current test current carrying capacity meets the maximum operating temperature allowed by the constraint conditions. If it does, determine the current test current carrying capacity as the maximum allowable current carrying capacity of the conductor under the combination of optimized variables, and the iteration ends.

[0094] If the requirements are not met, adjust the value of the test current carrying capacity and return to step S2.

[0095] The initial test current carrying capacity can be set based on experience or rated current. For example, for a 525kV GIL line, the initial test current carrying capacity can be set to 1000A; for a 220kV high-voltage AC cable line, the initial test current carrying capacity can be set to 800A.

[0096] When calculating the Joule loss and induced current loss of the conductor under the current test current carrying capacity, for GIL pipes, the following method is used: Figure 3 The four-layer structure shown is modeled as follows, from the inside out: inner layer insulating gas 1 (e.g., ... 1. Gas), 2. Center conductor, 3. Outer insulating gas, 4. Metal shell. For high-voltage AC cables, due to their complex internal structure, direct modeling leads to difficulties in mesh generation. This invention employs... Figure 4 The simplified layered model shown merges non-critical non-metallic layers, focusing on retaining the copper conductor layer and aluminum sheath layer. The conductor cross-section is corrected based on the equivalent conductive area principle to ensure the accuracy of electromagnetic loss calculations. From the inside out, the layers are: copper conductor 5, XLPE insulation layer 6, semiconductor layer 7, corrugated aluminum shielding layer 8, and outer sheath 9 (HDPE).

[0097] S2 to S4 are executed automatically by the program in the software. The specific processes for calculating Joule loss, induced current loss, and steady-state heat conduction are existing technologies in the field, and the present invention does not limit them.

[0098] The maximum operating temperature allowed to meet the constraints includes:

[0099] The highest conductor temperature under the current test current carrying capacity is not higher than the highest operating temperature allowed by the constraints, and the difference between the two is within the preset tolerance range.

[0100] The specific preset tolerance range is set by those skilled in the art based on the actual situation.

[0101] The expression for the comprehensive cost function is as follows:

[0102] ;

[0103] in, The value of the comprehensive cost function. for , The total construction cost of ventilation shafts is related to the spacing between them, and its value is proportional to the shaft spacing. Inversely proportional; In order to match the ventilation speed The relevant annual ventilation operation energy consumption cost, its value is related to wind speed It is directly proportional to the cube of the power; The entire lifespan; The transmission power is calculated based on the maximum allowable current carrying capacity. This refers to the transmission distance.

[0104] For different tunnel types, the specific formula parameters are as follows: , Differences may exist, and the determination shall be made by those skilled in the art after comprehensive evaluation.

[0105] The optimization process, which aims to minimize the value of the comprehensive cost function, yields optimal solutions for ventilation velocity and ventilation shaft spacing, including:

[0106] Within the set of optimization variables, several different combinations of optimization variables are selected as samples;

[0107] Based on all samples and their corresponding comprehensive cost function values, a continuous response surface model is constructed from ventilation wind speed and ventilation shaft spacing to the comprehensive cost function value.

[0108] An extreme value search is performed on the response surface model to find the combination of ventilation velocity and ventilation shaft spacing that minimizes the comprehensive cost function value, which is the optimal solution.

[0109] The selected samples should cover the possible range of wind speed and spacing values ​​as evenly as possible. A continuous response surface model is constructed using mathematical interpolation methods, such as regular grid interpolators or spline interpolation. The specific construction steps are existing technologies, and this invention does not impose further limitations on them. The minimum point of the function value is found on this continuous surface using optimization algorithms (such as gradient descent, genetic algorithms, etc.).

[0110] For example, regarding the optimized design results of the ventilation system obtained for the GIL tunnel scenario, please refer to [reference needed]. Figure 5 and Figure 6 .in, Figure 5This is a heatmap of the maximum permissible current carrying capacity of conductors obtained in a GIL tunnel scenario. It reflects the distribution of the maximum permissible current carrying capacity of conductors obtained through multi-field coupling simulation and iterative calculation as described in this invention under different samples. The figure is labeled Max: 7203 A, indicating that the theoretical current carrying capacity limit achievable within the selected sample is 7203 A; Opt: 5902 A, v = 1 m / s. =3km indicates that the optimal design parameters found through the optimization algorithm are a ventilation velocity of 1m / s and a ventilation shaft spacing of 3km. Under these design parameters, the corresponding maximum allowable flow rate is 5902 A.

[0111] Figure 6 The continuous response surface plot obtained for the GIL tunnel scenario is labeled Opt: 211.26, representing the lowest total life-cycle cost per unit transmission task under optimal design parameters, which is $211.26 / year / MW / km. Compared to unoptimized designs (such as the Sutong GIL tunnel project which uses full-length ventilation), the optimized scheme of this invention can reduce the total life-cycle cost by approximately 20%.

[0112] comprehensive Figure 5 , Figure 6 It can be seen that when the ventilation velocity is too low or the spacing between ventilation shafts is too large, insufficient heat dissipation leads to low flow rate, which results in a high construction cost per unit capacity (high cost areas on the left and rear sides of the curved surface); when the ventilation velocity is too high, although the flow rate increases, the growth rate of ventilation energy consumption costs exceeds the capacity gains, resulting in an increase in the overall cost.

[0113] The same optimization method was used for high-voltage AC cable tunnels. However, due to the lower temperature resistance of the cable insulation layer (90℃) and the existence of circulating current loss in the metal sheath, the optimization results differed from those of GIL.

[0114] Please refer to the detailed results. Figure 7 and Figure 8 ,in, Figure 7 The diagram shows the optimized design results of the ventilation system for a high-voltage AC cable tunnel scenario. Similarly, the left diagram is a heat map of the maximum allowable current carrying capacity of the conductor. It can be seen that within the selected sample, the theoretical current carrying capacity limit of the high-voltage AC cable tunnel is 2081A. The optimal design parameters found by the optimization algorithm are a ventilation velocity of 0.5m / s and a ventilation shaft spacing of 6km. Under these design parameters, the corresponding maximum allowable current carrying capacity is 2002A.

[0115] Figure 8 As shown in the continuous response surface plot, under the optimal design parameters, the comprehensive cost of a unit power transmission task in a high-voltage AC cable tunnel is the lowest over the entire life cycle, which is US$404.83 / year / MW / km.

[0116] This indicates that for cable tunnels, due to their inherently limited current carrying capacity, using more sparse shafts and lower wind speeds is more economical.

[0117] In this embodiment, the power transmission tunnel includes a gas-insulated power transmission line tunnel or a high-voltage AC cable tunnel;

[0118] When the power transmission tunnel is a gas-insulated power transmission line tunnel, the induced current loss includes the induced current loss of the tunnel shell.

[0119] When the power transmission tunnel is a high-voltage AC cable tunnel, the induced current loss includes the circulating current loss and eddy current loss of the cable's metal sheath.

[0120] Through the aforementioned differentiated settings, the method of the present invention can be precisely applied to two mainstream types of power transmission tunnels, ensuring that the optimized design results meet both technical safety constraints and their respective economic principles.

[0121] Example 2

[0122] Based on Embodiment 1, Embodiment 2 provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the steps of the above-described method for optimizing the design of a power transmission tunnel ventilation system based on the equivalent negative heat source and multi-field coupling in Embodiment 1.

[0123] Example 3

[0124] Based on Embodiment 1, Embodiment 3 provides an optimized design device for a power transmission tunnel ventilation system, the device comprising:

[0125] The modeling module is used to construct a two-dimensional finite element simulation model for analyzing the electromagnetic-thermal coupling field of the power transmission tunnel cross section based on the geometric structure and material parameters of the power transmission tunnel; and to construct an equivalent negative heat source model for characterizing the axial ventilation and heat dissipation effect of the power transmission tunnel based on the principles of fluid thermodynamics.

[0126] The calculation module is used to set the set of optimization variables and constraints. The optimization variables in the set of optimization variables include ventilation wind speed and ventilation shaft spacing, and the constraints include restrictions on conductor temperature. The equivalent negative heat source model is coupled to the two-dimensional finite element simulation model. For the combination of optimization variables in the set of optimization variables, electromagnetic field-thermal field joint simulation calculation is performed. The maximum allowable current carrying capacity of the conductor that meets the constraints is obtained through iterative solution.

[0127] The evaluation module is used to construct a comprehensive cost function based on the maximum allowable current carrying capacity of the conductor to characterize the engineering resource consumption of a unit transmission task throughout its entire life cycle;

[0128] The optimization module is used to find the optimal solution for ventilation velocity and ventilation shaft spacing by minimizing the value of the comprehensive cost function; the optimal solution is used as the optimal design parameters for the power transmission tunnel ventilation system.

[0129] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0130] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for optimizing the design of a power transmission tunnel ventilation system based on the equivalent negative heat source and multi-field coupling, characterized in that, The method includes: Based on the geometric structure and material parameters of the power transmission tunnel, a two-dimensional finite element simulation model is constructed to analyze the electromagnetic-thermal coupling field of the power transmission tunnel section. Based on the principles of fluid thermodynamics, an equivalent negative heat source model is constructed to characterize the axial ventilation and heat dissipation effect of power transmission tunnels; Set an optimization variable set and constraints, wherein the optimization variables in the optimization variable set include ventilation wind speed and ventilation shaft spacing, and the constraints include restrictions on conductor temperature; The equivalent negative heat source model is coupled to the two-dimensional finite element simulation model. For the combination of optimization variables in the set of optimization variables, electromagnetic field-thermal field joint simulation calculation is performed. The maximum allowable current carrying capacity of the conductor that meets the constraints is obtained by iterative solution. Based on the maximum allowable current carrying capacity of the conductor, a comprehensive cost function is constructed to characterize the engineering resource consumption of a unit power transmission task throughout its entire life cycle; The optimization is performed with the goal of minimizing the value of the comprehensive cost function to obtain the optimal solution for ventilation velocity and ventilation shaft spacing; The optimal solution is used as the optimal design parameter for the power transmission tunnel ventilation system. The description of the axial ventilation and heat dissipation effect of the power transmission tunnel includes: The heat carried away by the air flowing along the axial direction of the power transmission tunnel is equivalently mapped to the heat absorption power density applied to the air domain of the two-dimensional finite element simulation model. The formula for calculating the heat absorption power applied to the air domain of the two-dimensional finite element simulation model is as follows: ； Where q is the heat absorption power applied to the air domain of the two-dimensional finite element simulation model; air density; The effective ventilation cross-sectional area of ​​the power transmission tunnel; Ventilation speed; The specific heat capacity of air; This refers to the spacing between ventilation shafts; For the local air temperature within the computational domain; Reference temperature for ventilation inlet; The unit computational length of the two-dimensional finite element simulation model is given. The expression for the comprehensive cost function is: ； in, The value of the comprehensive cost function. The basic cost of the tunnel's main construction. The total construction cost of ventilation shafts is related to the spacing between ventilation shafts; its value is related to the spacing between ventilation shafts. Inversely proportional; In order to match the ventilation speed The relevant annual ventilation operation energy consumption cost, its value is related to wind speed It is directly proportional to the cube of the power; The entire lifespan; The transmission power is calculated based on the maximum allowable current carrying capacity. This refers to the transmission distance.

2. The optimization design method for a power transmission tunnel ventilation system based on negative heat source equivalent and multi-field coupling as described in claim 1, characterized in that, The two-dimensional finite element simulation model includes an electromagnetic field calculation module and a thermal field calculation module; Specifically, for any combination of optimization variables, a joint electromagnetic field-thermal field simulation is performed, and the maximum allowable current carrying capacity of the conductor that meets the constraints is obtained through iterative solution, including: S1. Set the current test current carrying capacity; S2. The Joule loss and induced current loss of the conductor under the current test current carrying capacity are calculated by the electromagnetic field calculation module. S3. Using Joule loss and induced current loss as heat sources, and the heat absorption power applied to the air domain of the two-dimensional finite element simulation model as heat dissipation source, input the heat field calculation module to perform steady-state heat conduction calculation, obtain the conductor temperature distribution under the current test current carrying capacity, and extract the highest conductor temperature under the current test current carrying capacity. S4. Determine whether the highest conductor temperature under the current test current carrying capacity meets the maximum operating temperature allowed by the constraint conditions. If it does, determine the current test current carrying capacity as the maximum allowable current carrying capacity of the conductor under the combination of optimized variables, and the iteration ends. If the requirements are not met, adjust the value of the test current carrying capacity and return to step S2.

3. The optimization design method for a power transmission tunnel ventilation system based on negative heat source equivalent and multi-field coupling as described in claim 2, characterized in that, The maximum permissible operating temperature for meeting the aforementioned constraints includes: The highest conductor temperature under the current test current carrying capacity is not higher than the highest operating temperature allowed by the constraints, and the difference between the two is within the preset tolerance range.

4. The optimization design method for a power transmission tunnel ventilation system based on negative heat source equivalent and multi-field coupling as described in claim 1, characterized in that, The optimization aims to minimize the value of the comprehensive cost function to obtain the optimal solutions for ventilation velocity and ventilation shaft spacing, including: Within the set of optimization variables, several different combinations of optimization variables are selected as samples; Based on all samples and their corresponding comprehensive cost function values, a continuous response surface model is constructed from ventilation wind speed and ventilation shaft spacing to the comprehensive cost function value. An extreme value search is performed on the response surface model to find the combination of ventilation velocity and ventilation shaft spacing that minimizes the comprehensive cost function value, which is the optimal solution.

5. The optimization design method for a power transmission tunnel ventilation system based on negative heat source equivalent and multi-field coupling as described in claim 2, characterized in that, The power transmission tunnel includes a gas-insulated power transmission line tunnel or a high-voltage AC cable tunnel; When the power transmission tunnel is a gas-insulated power transmission line tunnel, the induced current loss includes the induced current loss of the tunnel shell. When the power transmission tunnel is a high-voltage AC cable tunnel, the induced current loss includes the circulating current loss and eddy current loss of the cable's metal sheath.

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