Method and system for dynamically adjusting temperature rise of medium-voltage switch cabinet based on heat flow field simulation

Abstract

The invention discloses a medium-voltage switch cabinet temperature rise dynamic adjustment method and system based on heat flow field simulation, and relates to the technical field of industrial equipment thermal state control, and the method comprises the steps: carrying out the modeling of a cabinet body, electrical connection and ventilation structure of a medium-voltage switch cabinet, mapping the operation current state of a busbar into a heating boundary condition, and carrying out the thermal state control; and constructing a heat transfer and air flow coupled heat flow field simulation model. A heat flow distribution result is obtained through the model, characteristics such as heat flow density change are extracted, a heat flow behavior state quantity is constructed, a matching relation between a heat flow dominant transfer path and a ventilation heat dissipation structure is analyzed to establish structural change, and then a dynamic response adjustment strategy is configured. The technical problems that a traditional temperature rise control mode is difficult to adapt to the dynamic matching relation between heat transfer and a heat dissipation structure in the equipment, temperature rise adjustment lacks pertinence and the control effect is poor are solved, and the technical effects of accurately and dynamically regulating and controlling the temperature rise of the medium-voltage switch cabinet and optimizing heat flow distribution in the equipment are achieved.

Description

Technical Field

[0001] This invention relates to the field of thermal control technology for industrial equipment, and in particular to a method and system for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation. Background Technology

[0002] Medium-voltage switchgear is a core piece of equipment in power systems, and its temperature rise control falls under the category of critical non-electrical variable control, directly affecting the equipment's operational stability and lifespan. Existing temperature rise control methods largely rely on fixed ventilation or overall heat dissipation designs, which play a certain role in stable operating environments. However, with increasing fluctuations in power load, traditional methods have revealed significant limitations: the internal structure of medium-voltage switchgear is complex, and the matching relationship between heat flow transfer and ventilation structure changes dynamically. Traditional methods cannot accurately capture the characteristics of various heat flow behaviors, resulting in a lack of targeted regulation and incomplete or inaccurate heat flow data, making it difficult to meet the needs for precise control and adaptive adjustment of the internal temperature rise of medium-voltage switchgear. Summary of the Invention

[0003] This application provides a method and system for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation, which solves the technical problems that traditional temperature rise control methods are difficult to adapt to the dynamic matching relationship between internal heat transfer and heat dissipation structure of equipment, and that temperature rise adjustment lacks pertinence and control effect is poor.

[0004] The first aspect of this application provides a method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation. The method includes: performing structured modeling based on the cabinet structure, electrical connection structure, and ventilation structure of the medium-voltage switchgear, and uniformly mapping the operating current states of busbars, electrical contacts, and cable connections as heating boundary conditions; constructing a thermal flow field simulation model to characterize the coupling relationship between internal heat transfer and airflow based on the structured model; using the thermal flow field simulation model to obtain the heat flow distribution results inside the medium-voltage switchgear under the current operating conditions; extracting thermal flow behavior features based on the heat flow distribution results, including the heat flow density change trend, the dominant heat flow transmission path, and the distribution characteristics of the heat flow stagnation area; constructing thermal flow behavior state variables based on the thermal flow behavior features; analyzing the matching relationship between the dominant heat flow transmission path and the predetermined ventilation and heat dissipation structure of the medium-voltage switchgear to establish structural changes; configuring the temperature rise trend determination result according to the structural changes; and configuring a dynamic response adjustment strategy based on the thermal flow behavior state variables.

[0005] The second aspect of this application provides a dynamic temperature rise adjustment system for medium-voltage switchgear based on thermal flow field simulation. The system includes: a thermal flow field simulation model construction module, which performs structured modeling based on the cabinet structure, electrical connection structure, and ventilation structure of the medium-voltage switchgear, and uniformly maps the operating current states of busbars, electrical contacts, and cable connections as heating boundary conditions. Based on the structured modeling, a thermal flow field simulation model is constructed to characterize the coupling relationship between internal heat transfer and airflow. A thermal flow behavior feature acquisition module is used to obtain the temperature rise characteristics of the medium-voltage switchgear under the current operating conditions using the thermal flow field simulation model. The heat flow distribution results inside the switchgear are used to extract heat flow behavior features, including heat flow density variation trends, dominant heat flow transmission paths, and heat flow stagnation area distribution characteristics. A structural change construction module is used to construct heat flow behavior state variables based on these heat flow behavior features, analyze the matching relationship between the dominant heat flow transmission paths and the established ventilation and heat dissipation structure of the medium-voltage switchgear, and establish structural changes. A dynamic response adjustment strategy configuration module is used to configure dynamic response adjustment strategies based on the temperature rise trend determination results according to the structural changes and the heat flow behavior state variables.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application constructs a thermal flow field simulation model that couples heat transfer and airflow by structurally modeling the structure and operating state of medium-voltage switchgear, extracting thermal flow behavior characteristics and establishing thermal flow behavior state variables, analyzing the matching relationship between heat flow transfer and heat dissipation structure to determine structural changes, and configuring dynamic response adjustment strategies and performing feedback optimization based on these changes and thermal flow behavior state variables to ensure stable equipment operation. This achieves the technical effect of precise dynamic control of temperature rise in medium-voltage switchgear and optimization of internal heat flow distribution. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1 This is a flowchart illustrating the dynamic temperature rise adjustment method for medium-voltage switchgear based on thermal flow field simulation provided in this application embodiment.

[0009] Figure 2 This is a schematic diagram of the structure of the medium-voltage switchgear temperature rise dynamic adjustment system based on thermal flow field simulation provided in the embodiments of this application.

[0010] Figure labeling: Module 1 for building the thermal flow field simulation model, Module 2 for acquiring thermal flow behavior characteristics, Module 3 for building structural changes, and Module 4 for configuring dynamic response adjustment strategies. Detailed Implementation

[0011] This application provides a method and system for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation, which solves the technical problems that traditional temperature rise control methods are difficult to adapt to the dynamic matching relationship between internal heat transfer and heat dissipation structure of equipment, and that temperature rise adjustment lacks pertinence and control effect is poor.

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0013] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, a dynamic temperature rise adjustment method for medium-voltage switchgear based on thermal flow field simulation is described, wherein the method includes: Based on the cabinet structure, electrical connection structure and ventilation structure of the medium-voltage switchgear, structured modeling is performed, and the operating current state of the busbar, electrical contacts and cable connection parts is uniformly mapped as the heating boundary condition. On the basis of structured modeling, a thermal flow field simulation model is constructed to characterize the coupling relationship between internal heat transfer and air flow.

[0015] In this embodiment of the application, the medium-voltage switchgear is the core electrical equipment in the medium-voltage power system that undertakes power distribution, electrical equipment control and fault protection, and ensures stable power transmission and equipment operation.

[0016] Specifically, the process begins by dividing the functional areas of the medium-voltage switchgear into finite volume units and establishing corresponding nodes to characterize the spatial topological relationships of the relevant structures. Next, the operating currents of components such as busbars are mapped to the unit nodes, and the local heat generation power density is calculated based on material parameters to form heat flow boundary conditions. Finally, combining airflow characteristics with the heat flow boundary conditions, a simulation model coupling heat transfer and airflow is constructed. This model reflects the temporal evolution of unit node temperature and heat flux, as well as the internal heat flow distribution and transfer paths. This step will be explained in detail later.

[0017] Using the aforementioned heat flow field simulation model, the heat flow distribution inside the medium-voltage switchgear under the current operating conditions is obtained. Based on the heat flow distribution results, heat flow behavior features are extracted, including the heat flow density variation trend, the dominant heat flow transfer path, and the distribution characteristics of the heat flow retention area.

[0018] Optionally, the nodal temperatures, heat flux vectors, and local heat flux output from the thermal flux field simulation model are first spatiotemporally discretized to construct a three-dimensional heat flux data matrix. Then, based on this matrix, the heat flux density variation trend of each finite volume element node is calculated to identify regions of concentrated or sparse heat flux. Subsequently, a dominant heat flux transfer network is formed along the dominant heat flux direction through connectivity analysis, and relevant information is recorded. Finally, regions of stagnant or recirculating heat flux are detected in this network, their spatial distribution characteristics are marked, and thus, a heat flux behavior feature is jointly constructed. This step will be explained in detail later.

[0019] After constructing the heat flow behavior state variables based on the aforementioned heat flow behavior characteristics, the matching relationship between the dominant heat flow transmission path and the predetermined ventilation and heat dissipation structure of the medium-voltage switchgear is analyzed to establish structural changes.

[0020] In one embodiment of this application, firstly, based on the heat flow behavior state variables, multiple continuous spatial sections are divided inside the switchgear along the ventilation direction. A corresponding local heat flow organization map is generated on each spatial section using the heat flow vector component and the heat flow quantity component. Then, a continuity analysis is performed on the heat flow organization maps of adjacent sections. When the heat flow direction deviates from the ventilation and heat dissipation structure's guiding direction by more than a preset threshold, or when the heat flow exhibits a trend of attenuation, dispersion, or circulatory recirculation exceeding a preset threshold, it is determined that the dominant heat flow transmission path of the corresponding section has been structurally interrupted. Finally, using the structural interruption locations marked by the local heat flow organization maps, the evolutionary mode of heat flow from unidirectional dominant transmission to multidirectional circulation or local accumulation is identified. This evolutionary mode is then correlated with the spatial distribution characteristics of the heat flow behavior state variables, thereby establishing a structural change. This step will be described in detail later.

[0021] After determining the temperature rise trend based on the structural changes, a dynamic response adjustment strategy is configured based on the thermal flow behavior state variables.

[0022] Specifically, the temperature rise sensitivity of each functional area inside the medium-voltage switchgear is first determined based on structural changes, and then mapped to a priority matrix for heat flow regulation. This priority matrix is ​​then combined with heat flow behavior state variables to configure a dynamic response regulation strategy. Finally, targeted adjustments are made to the local ventilation holes, air duct openings, or heat dissipation devices in the corresponding functional areas. The core of the dynamic response regulation strategy is to take measures to enhance local ventilation or adjust heat conduction in areas where heat flow stagnation and areas where the dominant heat flow path is deflected, respectively, to optimize the heat flow distribution inside the switchgear. This step will be explained in detail later.

[0023] Furthermore, the method provided in this application embodiment includes: The cabinet of the medium-voltage switchgear is divided into multiple finite volume units, and corresponding geometric nodes and boundary nodes are established in each finite volume unit to characterize the spatial topology of the cabinet structure, electrical connection parts, and ventilation channels. The operating current state of the busbars, electrical contacts, and cable connections is mapped to the corresponding finite volume unit nodes. The local heating power density of each finite volume unit node is calculated based on the material thermal conductivity, resistance, and contact impedance to form heat flow boundary conditions. Based on the structured modeling, combined with the air flow characteristics and heat flow boundary conditions, a heat flow field simulation model coupling heat transfer and air flow is constructed, so that the temperature and heat flux of each finite volume unit node can evolve with time, reflecting the heat flow distribution and heat transfer path inside the medium-voltage switchgear.

[0024] Specifically, firstly, 3D structural drawings of the medium-voltage switchgear are obtained, clarifying the specific dimensions, locations, and functional zones of the cabinet, electrical connections, and ventilation channels. The finite volume method is then used for unit division. Combining the geometric characteristics of heat-concentrated areas (such as busbars and electrical contacts) and ventilation channels within the switchgear, the structured meshing function of ICEM CFD software is used to progressively divide the internal space of the cabinet according to functional areas: smaller unit sizes are used for heat-concentrated areas to ensure calculation accuracy (e.g., 5mm×5mm×5mm), while larger unit sizes are used for ventilation channels and cabinet edges to balance calculation efficiency (e.g., 10mm×10mm×10mm). During the division process, it is ensured that there is no overlap or gap between units, ultimately forming a set of finite volume units covering the entire cabinet. Subsequently, the divided finite volume units are imported into SolidWorks software. Using the software's node generation function, geometric nodes are set at the center of each unit, and boundary nodes are set at the contact surfaces of the units and at the intersections with the cabinet structure, electrical components, and ventilation channels. The spatial topological relationships between each unit and the cabinet structure, electrical connections, and ventilation channels are established through node coordinate association, completing the structured modeling.

[0025] Next, real-time operating current data of the busbars, electrical contacts, and cable connections are collected through the current monitoring module of the switchgear. A coordinate matching mapping method is used to map the physical locations of each component to finite volume units after structured modeling. By measuring the installation coordinates of each electrical component and comparing them with the spatial coordinates of the finite volume units, the corresponding finite volume unit and node for each electrical component are determined. The collected operating current values ​​are then assigned to the corresponding nodes, completing the mapping of the current state. Afterwards, standard physical properties of conductor materials such as copper and aluminum, such as thermal conductivity and resistivity, are consulted. The volume resistance of each electrical component is calculated using the formula R=ρL / S, where ρ is the material resistivity, L is the component length, and S is the cross-sectional area. Contact impedance testing is performed on the busbars, electrical contacts, and cable connections using the four-terminal method to obtain the contact impedance. Numerical values. Combining the mapped operating current I, the calculated volume resistance R, and the contact impedance... The volume V of the corresponding finite volume element is calculated by multiplying the length, width, and height of the element using the formula. Calculate the local heat generation power density at each node of the finite volume element. This integrates the local heat generation power density of all nodes, thereby forming heat flow boundary conditions.

[0026] Finally, ANSYS Fluent software, well-known to those skilled in the art, was used to construct a thermal flow field simulation model. First, the finite volume element mesh and node information obtained from structured modeling were imported into the software. The physical model was then set up within the software: for heat transfer, a solid heat conduction model and a fluid convection heat transfer model were selected, coupling the heat conduction and convection heat transfer processes; for air flow, air was set as an incompressible fluid, and the density of air under standard operating conditions was input. Specific heat capacity Dynamic viscosity Physical property parameters were then calculated. Subsequently, the heat flux boundary conditions obtained from the above steps were imported into the software, and the corresponding local heating power density was assigned to each finite volume element node. Simultaneously, the cabinet wall was set as an adiabatic boundary, and the vent was set as a pressure outlet boundary. Transient solution parameters were set, with a time step of 0.1 s and a convergence criterion of residuals less than [a certain value]. The solver is started to perform iterative calculations. The software will update the temperature and heat flux of each finite volume element node in real time based on the heat transfer equation, fluid momentum equation, and energy equation, so as to realize the coupled simulation of heat transfer and air flow.

[0027] By using mesh generation, coordinate mapping, parameter calculation, and CFD simulation methods, we gradually completed structured modeling, heat flow boundary condition construction, and coupled simulation model building, realizing the dynamic characterization of heat flow distribution and heat transfer path inside medium-voltage switchgear.

[0028] Furthermore, the method provided in this application embodiment includes: The nodal temperatures, heat flux vectors, and local heat flux output from the heat flow field simulation model are discretized in space and time to construct a three-dimensional heat flow data matrix to describe the evolution of heat flow. Based on the three-dimensional heat flow data matrix, the heat flux density variation trend of each finite volume unit node is calculated. The heat flux density variation trend includes the increase / decrease rate, gradient direction, and amplitude of local heat flux density over time, and heat flow concentration or sparse regions are identified. Connectivity analysis is performed on the heat flux density variation trend to identify the dominant path of continuous heat flow transfer along the dominant heat flow direction, forming a dominant heat flow transfer network, and recording the heat flux and deflection information on the path. Heat flow stagnation or backflow regions are detected in the dominant heat flow transfer network. Combining the characteristics of heat flux density, flux, and vector direction, heat flow stagnation regions and spatial distribution characteristics are marked, and heat flow behavior characteristics are jointly constructed.

[0029] In this embodiment, heat flux density is the amount of heat passing through a unit area per unit time, and is a physical quantity characterizing the intensity of heat transfer.

[0030] Optionally, the temperature, heat flux vector, and local heat flux data of each finite volume element node output from the thermal flux field simulation model are first acquired, and spatiotemporal discretization is performed using a uniform sampling method. Data is extracted at fixed intervals of 0.1 seconds in time, and spatially, the geometric nodes of the finite volume elements, i.e., the center of each finite volume element, are used as sampling points to ensure that sampling covers all finite volume element nodes. The temperature, heat flux vector x / y / z components, and local heat flux data corresponding to each time point and each spatial node are then organized according to a time dimension-spatial coordinate dimension-physical parameter dimension to construct a three-dimensional heat flux data matrix, achieving structured storage of heat flux evolution information.

[0031] Next, based on the constructed three-dimensional heat flux data matrix, the x / y / z components of the heat flux vector at each finite volume element node are extracted, and the magnitude of the heat flux density is calculated using the vector magnitude calculation formula. Where x, y, and z are the three-dimensional components of the heat flux vector, the heat flux density of each node is calculated, and the direction of the heat flux vector is the direction of heat flux density transfer at that node, thus completing the acquisition of the heat flux density of each node.

[0032] Then, based on the obtained heat flux density and three-dimensional heat flux data matrix, the time increase / decrease rate of heat flux density at each node is calculated using the difference method, that is, the difference in heat flux density between adjacent time points is divided by the time interval to obtain the increase / decrease amplitude per unit time. By comparing the heat flux density values ​​of a finite volume unit node with its adjacent nodes, the gradient operator is used to calculate the direction of the heat flux density gradient and the gradient amplitude to clarify the strength of the heat flux density change. A critical value for heat flux density is set, which can be determined based on the heat resistance limit of commonly used switchgear materials and the engineering experience of those skilled in the art. Areas above the critical value are marked as heat flux concentrated areas, and areas below the critical value are marked as heat flux sparse areas, thereby completing the analysis of heat flux density change trends and area identification.

[0033] Connectivity analysis was then performed using a neighborhood search method. Specifically, starting from a finite volume element node in a region of concentrated heat flux, the neighboring finite volume element nodes of each node were traversed. Preset connectivity criteria were established: the heat flux density of adjacent finite volume element nodes was higher than a critical heat flux density value, the angle between the heat flux vector directions of the two nodes was less than 30 degrees, and the heat flux attenuation ratio did not exceed 20%. If these criteria were met, the two nodes were considered connected, and the adjacent node was added to the current connectivity path. The neighborhood search continued from this adjacent node as a new starting point until no more adjacent nodes met the criteria.

[0034] Furthermore, there are multiple independent heat flow concentration areas inside the medium-voltage switchgear, such as busbar groups, different electrical contact clusters, and cable connection convergence areas. Each area forms a non-overlapping active heat flow area due to the dispersed arrangement of heat-generating components. The above process is repeated for the finite volume unit nodes of all heat flow concentration areas. That is, for each independent heat flow concentration area, neighborhood search, connectivity analysis, and optimal path selection are performed. That is, each heat flow concentration area corresponds to a heat flow dominant transmission path with the largest total heat flux and the most consecutive nodes in the area. All heat flow dominant transmission paths are associated and integrated according to spatial location to form a heat flow dominant transmission network. At the same time, the heat flux value of each node on each path and the deflection angle of the heat flow vector relative to the starting direction of the path are recorded.

[0035] Finally, in the heat flux-dominant transport network, a method combining vector direction comparison and flux threshold determination is used to detect stagnant regions. The heat flux vector direction of each finite volume unit node is compared with the overall transport direction of its respective heat flux-dominant transport path; if the directions are opposite, it is identified as a recirculation region. A heat flux stagnation threshold is set, which is 10% of the average heat flux of the path. If the heat flux of a node is lower than this threshold and the heat flux vector has no clear dominant direction, it is identified as a stagnant region. Combining the heat flux density data, specific flux values, and spatial coordinate information of these finite volume unit nodes, the spatial distribution characteristics such as the location, range, and shape of the stagnant regions are marked. Finally, the heat flux density variation trend, the heat flux-dominant transport network, and the distribution characteristics of the stagnant regions are integrated to complete the construction of heat flux behavior features.

[0036] By employing steps such as uniform sampling, differential calculation, neighborhood search, and threshold determination, the heat flow data processing, feature calculation, network construction, and region labeling are completed sequentially, enabling accurate extraction and complete characterization of the internal heat flow behavior features of medium-voltage switchgear.

[0037] Furthermore, the method provided in this application embodiment includes: The thermal behavior state variables include the nodal heat load index calculated based on the heat flux density change trend, which is used to reflect the temperature rise sensitivity of each area inside the medium-voltage switchgear.

[0038] Specifically, the relevant data on the heat flux density variation trend of each finite volume element node are first extracted, including the rate of increase / decrease of heat flux density over time, the magnitude of the heat flux density gradient, and the quantization coefficient corresponding to the gradient direction. The gradient direction quantization coefficient is determined as follows: taking the predetermined ventilation direction of the medium-voltage switchgear as the positive direction, the gradient direction quantization coefficient along this direction is set to 1, perpendicular to this direction is 0.5, and opposite to this direction is -0.5, thus achieving the numerical conversion of the gradient direction. Referring to engineering practice experience in this field, the weights of each data point are set: the weight of the heat flux density gradient magnitude is set to 0.5, the weight of the rate of increase / decrease of heat flux density over time is set to 0.3, and the weight of the gradient direction quantization coefficient is set to 0.2, with a total weight of 1.

[0039] Next, the heat load index of each finite volume unit node is calculated using a weighted summation method. Specifically, the calculation method is: Node heat load index = Heat flux density increase / decrease rate × 0.3 + Heat flux density gradient magnitude × 0.5 + Gradient direction quantization coefficient × 0.2. This process is repeated for all nodes. The node heat load indices are then divided into three intervals based on their numerical values: intervals with indices greater than 0.7 correspond to high temperature rise sensitivity; intervals with indices between 0.3 and 0.7 correspond to medium temperature rise sensitivity; and intervals with indices less than 0.3 correspond to low temperature rise sensitivity. This forms a thermal flow behavioral state quantity that includes the temperature rise sensitivity of each region within the medium-voltage switchgear.

[0040] Furthermore, the method provided in this application embodiment includes: Based on the heat flow behavior state variables, multiple continuous spatial sections are divided along the ventilation direction inside the medium-voltage switchgear. A corresponding local heat flow organization map is generated on each spatial section using the heat flow vector component and heat flow quantity component. Continuity analysis is performed on the heat flow organization map between adjacent sections. When the detected heat flow direction deviates from the predetermined ventilation and heat dissipation structure guidance direction by more than a preset threshold, or when the heat flow exhibits a trend of attenuation, dispersion, or circulatory recirculation exceeding a preset threshold, it is determined that the dominant heat flow transmission path of the corresponding section has been structurally interrupted. Using the structural interruption locations marked in the local heat flow organization map, the evolutionary pattern of heat flow in the corresponding functional structural area from unidirectional dominant transmission to multidirectional circulation or local accumulation is identified. This evolutionary pattern is then correlated with the spatial distribution characteristics of the heat flow behavior state variables to establish structural changes.

[0041] Specifically, the process begins by acquiring the nodal heat load index and spatial distribution data of each finite volume element node in the heat flow behavior state variables, thus clarifying the predetermined ventilation direction of the medium-voltage switchgear, i.e., the axial extension direction of the ventilation channel. Spatial sections are then divided along this ventilation direction. The spacing between these sections is determined based on the internal length of the medium-voltage switchgear and its sensitivity to heat flow changes, typically set to 10 to 20 millimeters. This ensures that the sections completely cover the ventilation path and the main functional structural areas, forming multiple continuous spatial sections. For each spatial section, the x / y / z components of the heat flow vector and local heat flow flux data of all finite volume element nodes on that section are extracted. A vector visualization drawing method is used, with the section as a two-dimensional plane. Arrow symbols represent the direction of the heat flow vector, and the arrow length corresponds proportionally to the magnitude of the heat flow flux, generating a local heat flow organization map for each spatial section, visually presenting the heat flow distribution state of that section.

[0042] Next, the guiding direction of the predetermined ventilation and heat dissipation structure of the medium-voltage switchgear is clarified, that is, the expected heat flow transfer direction of the ventilation channel design, which is used as the reference direction. Preset thresholds for heat flow direction deviation and heat flux change. Referring to engineering practice experience, the direction deviation threshold is set to 30 degrees, and the heat flux attenuation threshold is set to 20%. The criteria for determining dispersion trends are that the proportion of nodes with a heat flow vector direction difference angle exceeding 60 degrees within the same cross-section is greater than 30%, and the criteria for determining ring-shaped return trends are the existence of a closed heat flow vector circulation path within the cross-section. The vector angle calculation method is used to perform continuity analysis on the heat flow organization map of adjacent cross-sections. The angle between the heat flow vector of the node at the next cross-section and the reference direction is calculated using the dot product formula. If the angle exceeds the deviation threshold, the heat flow direction corresponding to that node is determined to have deviated. Simultaneously, the heat flux ratio of the corresponding region of adjacent cross-sections is calculated. If the ratio is less than 0.8 (i.e., attenuation exceeds 20%), or if the criteria for dispersion trends and ring-shaped return trends are met, the dominant heat flow transfer path of the corresponding cross-section is determined to have been structurally interrupted, and the interruption location is marked in the local heat flow organization map.

[0043] Finally, for the structural interruption locations marked in the local heat flow organization map, heat flow vector distribution data of the location and surrounding functional structural areas are extracted. The evolution pattern is identified by observing the directional distribution characteristics of the heat flow vectors: if the heat flow vectors are all distributed unidirectionally along the ventilation direction, it is a unidirectional dominant transmission pattern; if the heat flow vectors form multidirectional intersecting circulation paths, it is a multidirectional circulation evolution pattern; if multiple heat flow vectors point to the same local area, it is a local aggregation evolution pattern. The heat flow behavior state data of all finite volume unit nodes within the functional structural area, i.e., the node heat load index, are extracted. The identified evolution patterns are correlated with the spatial distribution characteristics of the node heat load index. For example, when a multidirectional circulation or local aggregation evolution pattern corresponds to a high-temperature rise sensitivity area with a node heat load index greater than 0.7, it is marked as a high-influence structural change; when it corresponds to a medium- or low-temperature rise sensitivity area, it is marked as a medium- or low-influence structural change, respectively, thus completing the establishment of the structural change.

[0044] By employing methods such as uniform segmentation, vector visualization, angle calculation, and threshold determination, the system seamlessly completes spatial section division, heat flow organization map generation, continuity analysis, evolution pattern recognition, and correlation, thereby achieving accurate analysis of the matching relationship between the dominant heat flow transfer path and the ventilation and heat dissipation structure, and effectively establishing structural changes.

[0045] Furthermore, the method provided in this application embodiment includes: Based on the aforementioned thermal flow behavior state variables, the thermal flow vector deflection amplitude, flux change rate, and stability index of the dominant thermal flow direction are calculated at the marked structural interruption locations and adjacent spatial sections. The stability index is used to quantify the local stability of the thermal flow transfer path. The identified evolution patterns are weighted and evaluated using the stability index to determine the degree of thermal flow evolution from a stable state to an unstable state within the corresponding functional structural region, thus establishing structural changes.

[0046] Specifically, firstly, the heat flux vectors and heat flux data of all nodes within two adjacent spatial sections at the marked structural interruption locations in the heat flux behavioral state variables are extracted. Simultaneously, the node heat load index and spatial distribution information for each node are extracted. The heat flux vector deflection amplitude is calculated using the vector angle calculation method. Taking the heat flux vector at the section where the structural interruption location is located as the reference vector, the angle between the heat flux vector of the corresponding node at the adjacent section and the reference vector is calculated using the dot product formula. This angle value is the heat flux vector deflection amplitude for that node. This process is repeated for all relevant finite volume element nodes, resulting in deflection amplitude distribution data.

[0047] Next, based on the heat flux data extracted in the above steps, the flux change rate is calculated using the difference method. Taking the heat flux of the section where the structural interruption is located as the reference value, the difference between the heat flux of the corresponding nodes of the adjacent front and rear sections and the reference value is calculated. Then, the difference is divided by the reference value to obtain the heat flux change rate of each node. If the change rate is negative, it indicates flux decay, and if it is positive, it indicates flux enhancement. The flux change rate data of all nodes are recorded.

[0048] Then, combining the heat flux vector deflection amplitude, flux change rate, and fluctuations in the dominant heat flux direction, the stability index of the dominant heat flux direction is calculated. Based on engineering practice, the weights of each parameter are set: heat flux vector deflection amplitude is weighted at 0.4, flux change rate at 0.3, and the fluctuation coefficient of the dominant heat flux direction at 0.3. The fluctuation coefficient is obtained by calculating the average angle between the dominant heat flux directions at three adjacent time points. The stability index is calculated using a weighted summation method, with the specific formula: Stability Index = (1 - Deflection Amplitude / 90°) × 0.4 + (1 - |Flux Change Rate|) × 0.3 + (1 - Flux Coefficient / 30°) × 0.3. The index value ranges from 0 to 1; the closer the value is to 1, the stronger the local stability of the heat flux transfer path, and vice versa.

[0049] Next, the heat flow evolution patterns identified in the preceding steps are extracted. The stability index is used as the core evaluation parameter, combined with the temperature rise sensitivity in the heat flow behavioral state variables, i.e., the nodal heat load index, for weighted evaluation. The stability index is weighted at 0.6, and the nodal heat load index at 0.4. A comprehensive evaluation value is calculated for each evolution pattern. Based on the comprehensive evaluation value, the evolution degree is classified into levels: less than 0.3 indicates high-degree unstable evolution, 0.3 to 0.7 indicates medium-degree unstable evolution, and greater than 0.7 indicates low-degree unstable evolution. This level determines the specific degree of heat flow evolution from a stable to an unstable state, thereby refining and establishing a structural change model that incorporates evolution degree information.

[0050] By using methods such as vector angle calculation, difference method, and weighted summation, parameter calculation and evolution mode evaluation are completed in a coherent manner, achieving accurate quantification of the degree of heat flux unsteady state evolution and establishing a more comprehensive structural change.

[0051] Furthermore, the method provided in this application embodiment includes: Based on the structural changes, the temperature rise sensitivity of each functional area inside the medium-voltage switchgear is determined, and the temperature rise sensitivity is mapped to a priority matrix for heat flow regulation. After configuring a dynamic response regulation strategy using the priority matrix and heat flow behavior state variables, directional adjustments are made to the local ventilation holes, air duct openings, or heat dissipation devices of the corresponding functional areas. In one embodiment, the established structural change data is first extracted, including the heat flow evolution mode of each functional area and the degree of unstable evolution (high, medium, and low). Simultaneously, the node heat load index in the heat flow behavior state variables is extracted. A weighted summation method is used to comprehensively determine the temperature rise sensitivity of each functional area, setting the weight of unstable evolution degree to 0.6 and the weight of the node heat load index to 0.4. High degree of unstable evolution corresponds to a quantified value of 1.0, medium degree to 0.5, and low degree to 0.2; the node heat load index directly uses the calculated value, ranging from 0 to 1. The comprehensive value of the temperature rise sensitivity of each functional area is calculated using the formula: Temperature rise sensitivity = Quantified value of unstable evolution degree × 0.6 + Node heat load index × 0.4. Sensitivity levels are determined based on the comprehensive value: a comprehensive value greater than 0.8 indicates high temperature rise sensitivity, between 0.5 and 0.8 indicates medium temperature rise sensitivity, and less than 0.5 indicates low temperature rise sensitivity. This completes the determination of the temperature rise sensitivity of each functional area.

[0052] Then, a list mapping method is used to convert temperature rise sensitivity into a priority matrix for heat flux regulation. The priority matrix contains three core dimensions: functional area number, temperature rise sensitivity level, and regulation priority. High temperature rise sensitivity corresponds to first-level regulation priority (preferred regulation), medium temperature rise sensitivity corresponds to second-level regulation priority (second-preferred regulation), and low temperature rise sensitivity corresponds to third-level regulation priority (last regulation). The matrix content is organized according to the distribution order of functional areas within the switchgear, clarifying the corresponding priority of each area, forming a structured priority matrix, providing a clear basis for subsequent regulation strategy configuration.

[0053] Based on the priority matrix of heat flux regulation and the heat flux distribution characteristics in the heat flux behavioral state variables, including the heat flux stagnation region and the heat flux dominant path deflection region, a dynamic response regulation strategy is configured. The specific steps are as follows: For the first-level priority adjustment area, if it is a heat flow stagnation area, a local ventilation enhancement strategy is adopted. The opening of the corresponding local ventilation holes in this area is adjusted by controlling a stepper motor, gradually increasing the opening from the initial state to 80% to 100%. If it is a heat flow path deflection area, a heat conduction adjustment strategy is adopted. The direction of the air duct opening is changed by electrically adjusting the baffle, so that the opening faces the expected direction of heat flow. For the second-level priority adjustment area, the same type of adjustment strategy is selected according to the heat flow characteristics, but the ventilation hole opening is adjusted to 60% to 80%, and the air duct opening direction is fine-tuned to a deviation of less than 10 degrees. For the third-level priority adjustment area, adjustment is only initiated when the heat flow density exceeds the safety threshold. The ventilation hole opening is maintained at 40% to 60%, and the speed of heat dissipation devices such as small cooling fans is adjusted to a low to medium speed. All adjustment actions are completed through the actuator connected to the controller. The actuator receives control signals corresponding to the priority matrix and heat flow characteristics, and precisely executes directional adjustment operations.

[0054] Through steps such as weighted summation, list mapping, and feature matching, the system sequentially completes the determination of temperature rise sensitivity, construction of priority matrix, and configuration and execution of adjustment strategy, thereby achieving precise and directional adjustment of internal heat flow in medium-voltage switchgear and ensuring the pertinence and effectiveness of temperature rise control.

[0055] Furthermore, the method provided in this application embodiment includes: Configure a mapping monitoring window for the dynamic response adjustment strategy. During the execution of the dynamic response adjustment strategy, use the mapping monitoring window to perform temperature monitoring feedback, establish a feedback verification signal, and use the feedback verification signal to perform adaptive strategy optimization of the dynamic response adjustment strategy.

[0056] Optionally, based on the priority matrix of heat flux regulation and the spatial distribution characteristics of each functional region, a mapping monitoring window for the dynamic response regulation strategy is configured. Using a region-based mapping method, an independent mapping monitoring window is assigned to each functional region with regulation priority. The mapping monitoring window for the first-level regulation priority region covers the entire spatial range of that region, while the second- and third-level regulation priority regions are divided into monitoring sub-windows according to functional zones. Within each mapping monitoring window, temperature monitoring points are determined using a coordinate matching method: one monitoring point is set every 50 square millimeters for the first-level regulation priority region, one every 80 square millimeters for the second-level region, and one every 100 square millimeters for the third-level region, ensuring that the monitoring points are evenly distributed and cover key heat flux areas. The monitoring sampling frequency is set: 1 second / sample for the first-level regulation priority region, 2 seconds / sample for the second-level region, and 5 seconds / sample for the third-level region. The monitoring range, monitoring point locations, and sampling frequency parameters of the mapping monitoring window are defined, completing the configuration of the mapping monitoring window.

[0057] During the execution of the dynamic response adjustment strategy, real-time temperature data is collected using digital temperature sensors installed at each monitoring point. The temperature signals collected by the digital temperature sensors are transmitted to the central controller via wired transmission. The central controller preprocesses the received temperature data, removing random interference noise through a moving average filtering method, and takes the average of five consecutive samples as the effective temperature value for that monitoring point. The preprocessed effective temperature value is compared with the preset safe temperature threshold for each functional area. This safe temperature threshold is determined based on the heat resistance rating of the switchgear insulation material and engineering standards. Simultaneously, the temperature change and rate of change before and after the execution of the dynamic response adjustment strategy are calculated, completing the temperature monitoring feedback.

[0058] Then, a feedback verification signal is established based on the temperature monitoring feedback results. Three types of verification standards are set: when the effective temperature value of the monitoring point is lower than the safe temperature threshold and the temperature change rate tends to stabilize (i.e., the absolute value of the change rate is less than 0.5℃ / minute), a feedback signal indicating that the adjustment has met the standard is generated; when the effective temperature value is higher than the safe temperature threshold or the temperature drop rate is lower than the preset requirement (i.e., lower than 1℃ / minute), a feedback signal indicating that the adjustment is insufficient is generated; when the effective temperature value is lower than 80% of the safe temperature threshold and continues to drop, a feedback signal indicating that the adjustment is excessive is generated. The feedback signals from each mapped monitoring window are integrated according to the area number to form a unified set of feedback verification signals.

[0059] Finally, the dynamic response adjustment strategy is adaptively optimized using feedback verification signals. If a "adjustment met" signal is received, the current adjustment parameters are maintained, and temperature changes continue to be monitored through the mapping monitoring window. If a "adjustment insufficient" signal is received, the adjustment strategy for the corresponding area is strengthened. In the first-level adjustment priority area, the ventilation opening is increased by 10% to 20% or the speed of the heat dissipation device is increased. In the second and third-level adjustment priority areas, the adjustment range is increased proportionally. If a "adjustment excessive" signal is received, the adjustment intensity is reduced by decreasing the ventilation opening by 10% to 15% or reducing the speed of the heat dissipation device to prevent excessively low temperatures from affecting equipment operation. After optimization, the monitoring frequency is kept constant, temperature data is continuously collected, and new feedback verification signals are generated. The monitoring, feedback, and optimization process is repeated until the temperature of each functional area stabilizes within the safe temperature threshold range.

[0060] By employing existing mature methods such as region mapping, sensor monitoring, filtering, threshold determination, and iterative optimization, the system seamlessly completes the configuration of the monitoring window, temperature feedback, signal establishment, and strategy optimization. This enables adaptive optimization of the dynamic response adjustment strategy, ensuring the stability and accuracy of temperature rise control in medium-voltage switchgear.

[0061] Furthermore, the method provided in this application embodiment includes: The dynamic response adjustment strategy includes implementing local ventilation enhancement or heat conduction adjustment in the heat flow retention area and the heat flow dominance path deflection area, respectively, to optimize the heat flow distribution inside the medium-voltage switchgear.

[0062] In one embodiment, data on heat flow stagnation areas and heat flow dominance path deflection areas marked in the heat flow behavior characteristics are first extracted, including the spatial coordinates, size, heat flow density values, and heat flow vector directions of the two types of areas. A coordinate matching method is used to correlate these data with the actual structural drawings of the medium-voltage switchgear, clarifying the cabinet's local ventilation holes and cooling fan installation positions corresponding to the heat flow stagnation areas, as well as the air duct distribution and guide baffle installation nodes corresponding to the heat flow dominance path deflection areas. This accurately locates the hardware components that need adjustment, providing a positional basis for directional adjustment.

[0063] A localized ventilation enhancement strategy is implemented for areas where heat flux is trapped. The enhancement level is determined based on the heat flux density of the area, with enhancement levels set at a preset high threshold. At that time, it was a level one enhancement. It is a second-order enhancement, less than This system employs a three-stage enhancement approach. A stepper motor drives the corresponding local ventilation vent baffles, with pulse signals controlling the motor's rotation angle. For the first stage of enhancement, the ventilation vent opening is adjusted from the initial level to 80%-100%; for the second stage, to 60%-80%; and for the third stage, to 40%-60%. If a small axial-flow cooling fan is installed in the area, PWM speed control is used to adjust the fan speed simultaneously: 3000 rpm for the first stage, 2500 rpm for the second, and 2000 rpm for the third, increasing the local airflow rate to remove trapped heat.

[0064] A heat flow adjustment strategy is implemented for areas where the dominant heat flow path is deflected. First, the angle between the deflection direction and the predetermined ventilation direction is determined using heat flow vector data. An angle between 30° and 60° is considered a slight deflection, 60° to 90° a moderate deflection, and greater than 90° a severe deflection. For ducts equipped with electrically adjustable baffles, an angle closed-loop control method is used to adjust the baffle angle. For slight deflection, the baffle is adjusted to an angle less than 10° with the predetermined ventilation direction; for moderate deflection, the angle is adjusted to less than 5°; and for severe deflection, the baffle is directly aligned with the ventilation direction to guide the heat flow along the expected path. For areas without electrically adjustable baffles, detachable guide vanes are added. The angle of the guide vanes is cut according to the deflection direction, and they are fixed to the inside of the duct with bolts, ensuring that the guide surface of the vanes is parallel to the expected heat flow direction, thus forcibly correcting the heat flow deflection path.

[0065] After completing the above adjustment steps, real-time temperature data is collected using digital temperature sensors distributed in the two types of areas. The temperature change rate within 10 minutes before and after adjustment is calculated using the difference method. If the temperature change rate in the heat flow stagnation area is less than -1℃ / minute, i.e., the temperature continues to decrease, and the angle between the heat flow vector in the area where the dominant heat flow path deflects and the predetermined ventilation direction is less than 15°, then the adjustment is considered effective. If the above standard is not met, the above adjustment steps are repeated, appropriately increasing the ventilation enhancement or fine-tuning the guide angle until the requirements are met, ensuring that the adjustment effect meets the standard.

[0066] By employing methods such as coordinate matching, hierarchical adjustment, and closed-loop control, the system seamlessly integrates area positioning, ventilation enhancement, airflow adjustment, and effect verification. This achieves precise improvement in the problems of heat flow retention and path deflection within medium-voltage switchgear, and optimizes the overall heat flow distribution.

[0067] In summary, the method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation provided in this application has the following technical effects: This application performs structured modeling based on the medium-voltage switchgear structure, constructs a thermal flow field simulation model, extracts behavioral features such as heat flux density changes and dominant paths, establishes structural changes, and combines thermal flow behavioral state variables to configure dynamic response adjustment strategies and adaptively optimize them. This improves the optimization effect of heat flux distribution and the reliability of temperature rise control, achieving precise dynamic control of temperature rise in medium-voltage switchgear and optimizing the technical effect of internal heat flux distribution in the equipment.

[0068] Example 2, as Figure 2 As shown, based on the same inventive concept as in Embodiment 1 above, this application provides a dynamic temperature rise adjustment system for medium-voltage switchgear based on thermal flow field simulation, the system comprising: The thermal flow field simulation model construction module 1 is based on the cabinet structure, electrical connection structure and ventilation structure of the medium-voltage switchgear. It performs structured modeling and maps the operating current state of the busbar, electrical contacts and cable connection parts as heating boundary conditions. On the basis of structured modeling, a thermal flow field simulation model is constructed to characterize the coupling relationship between internal heat transfer and air flow.

[0069] The heat flow behavior feature acquisition module 2 is used to obtain the heat flow distribution results inside the medium-voltage switchgear under the current operating conditions using the heat flow field simulation model, and extract heat flow behavior features based on the heat flow distribution results. The heat flow behavior features include the heat flow density change trend, the dominant heat flow transfer path, and the distribution characteristics of the heat flow stagnation area.

[0070] The structural change construction module 3, after constructing the heat flow behavior state quantity based on the heat flow behavior characteristics, analyzes the matching relationship between the dominant heat flow transmission path and the predetermined ventilation and heat dissipation structure of the medium-voltage switchgear, and establishes the structural change.

[0071] The dynamic response adjustment strategy configuration module 4 is used to configure a dynamic response adjustment strategy based on the thermal flow behavior state quantity after configuring the temperature rise trend determination result according to the structural change.

[0072] Furthermore, the structural change construction module 3 is used to perform the following steps: Based on the heat flow behavior state variables, multiple continuous spatial sections are divided along the ventilation direction inside the medium-voltage switchgear. A corresponding local heat flow organization map is generated on each spatial section using the heat flow vector component and heat flow quantity component. Continuity analysis is performed on the heat flow organization map between adjacent sections. When the detected heat flow direction deviates from the predetermined ventilation and heat dissipation structure guidance direction by more than a preset threshold, or when the heat flow exhibits a trend of attenuation, dispersion, or circulatory recirculation exceeding a preset threshold, it is determined that the dominant heat flow transmission path of the corresponding section has been structurally interrupted. Using the structural interruption locations marked in the local heat flow organization map, the evolutionary pattern of heat flow in the corresponding functional structural area from unidirectional dominant transmission to multidirectional circulation or local accumulation is identified. This evolutionary pattern is then correlated with the spatial distribution characteristics of the heat flow behavior state variables to establish structural changes.

[0073] Furthermore, the structural change construction module 3 is used to perform the following steps: Based on the aforementioned thermal flow behavior state variables, the thermal flow vector deflection amplitude, flux change rate, and stability index of the dominant thermal flow direction are calculated at the marked structural interruption locations and adjacent spatial sections. The stability index is used to quantify the local stability of the thermal flow transfer path. The identified evolution patterns are weighted and evaluated using the stability index to determine the degree of thermal flow evolution from a stable state to an unstable state within the corresponding functional structural region, thus establishing structural changes.

[0074] Furthermore, the thermal flow field simulation model construction module 1 is used to perform the following steps: The cabinet of the medium-voltage switchgear is divided into multiple finite volume units, and corresponding geometric nodes and boundary nodes are established in each finite volume unit to characterize the spatial topology of the cabinet structure, electrical connection parts, and ventilation channels. The operating current state of the busbars, electrical contacts, and cable connections is mapped to the corresponding finite volume unit nodes. The local heating power density of each finite volume unit node is calculated based on the material thermal conductivity, resistance, and contact impedance to form heat flow boundary conditions. Based on the structured modeling, combined with the air flow characteristics and heat flow boundary conditions, a heat flow field simulation model coupling heat transfer and air flow is constructed, so that the temperature and heat flux of each finite volume unit node can evolve with time, reflecting the heat flow distribution and heat transfer path inside the medium-voltage switchgear.

[0075] Furthermore, the thermal flow behavior feature acquisition module 2 is used to perform the following steps: The nodal temperatures, heat flux vectors, and local heat flux output from the heat flow field simulation model are discretized in space and time to construct a three-dimensional heat flow data matrix to describe the evolution of heat flow. Based on the three-dimensional heat flow data matrix, the heat flux density variation trend of each finite volume unit node is calculated. The heat flux density variation trend includes the increase / decrease rate, gradient direction, and amplitude of local heat flux density over time, and heat flow concentration or sparse regions are identified. Connectivity analysis is performed on the heat flux density variation trend to identify the dominant path of continuous heat flow transfer along the dominant heat flow direction, forming a dominant heat flow transfer network, and recording the heat flux and deflection information on the path. Heat flow stagnation or backflow regions are detected in the dominant heat flow transfer network. Combining the characteristics of heat flux density, flux, and vector direction, heat flow stagnation regions and spatial distribution characteristics are marked, and heat flow behavior characteristics are jointly constructed.

[0076] Furthermore, the dynamic response adjustment strategy configuration module 4 is used to perform the following steps: Based on the structural changes, the temperature rise sensitivity of each functional area inside the medium-voltage switchgear is determined, and the temperature rise sensitivity is mapped to a priority matrix for heat flow regulation. After configuring a dynamic response regulation strategy using the priority matrix and heat flow behavior state variables, directional regulation of local ventilation holes, air duct openings, or heat dissipation devices in the corresponding functional areas is executed.

[0077] Furthermore, the dynamic response adjustment strategy configuration module 4 is used to perform the following steps: Configure a mapping monitoring window for the dynamic response adjustment strategy. During the execution of the dynamic response adjustment strategy, use the mapping monitoring window to perform temperature monitoring feedback, establish a feedback verification signal, and use the feedback verification signal to perform adaptive strategy optimization of the dynamic response adjustment strategy.

[0078] Furthermore, the dynamic response adjustment strategy configuration module 4 is used to perform the following steps: The dynamic response adjustment strategy includes implementing local ventilation enhancement or heat conduction adjustment in the heat flow retention area and the heat flow dominance path deflection area, respectively, to optimize the heat flow distribution inside the medium-voltage switchgear.

[0079] Furthermore, the structural change construction module 3 is used to perform the following steps: The thermal behavior state variables include the nodal heat load index calculated based on the heat flux density change trend, which is used to reflect the temperature rise sensitivity of each area inside the medium-voltage switchgear.

[0080] The medium-voltage switchgear temperature rise dynamic adjustment system based on thermal flow field simulation provided in this embodiment of the invention can execute the medium-voltage switchgear temperature rise dynamic adjustment method based on thermal flow field simulation provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0081] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0082] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation, characterized in that, The method includes: Based on the cabinet structure, electrical connection structure and ventilation structure of medium-voltage switchgear, structured modeling is performed, and the operating current state of busbars, electrical contacts and cable connection parts is uniformly mapped as heating boundary conditions. On the basis of structured modeling, a thermal flow field simulation model is constructed to characterize the coupling relationship between internal heat transfer and air flow. Using the aforementioned heat flow field simulation model, the heat flow distribution inside the medium-voltage switchgear under the current operating conditions is obtained. Based on the heat flow distribution results, heat flow behavior features are extracted, including the heat flow density variation trend, the dominant heat flow transfer path, and the distribution characteristics of the heat flow stagnation area. After constructing the heat flow behavior state variables based on the aforementioned heat flow behavior characteristics, the matching relationship between the dominant heat flow transmission path and the predetermined ventilation and heat dissipation structure of the medium-voltage switchgear is analyzed to establish structural changes. After determining the temperature rise trend based on the structural changes, a dynamic response adjustment strategy is configured based on the thermal flow behavior state variables.

2. The method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation as described in claim 1, characterized in that, Using the aforementioned heat flow field simulation model, the heat flow distribution inside the medium-voltage switchgear under the current operating conditions is obtained. Based on the heat flow distribution results, heat flow behavior features are extracted, including: The nodal temperatures, heat flux vectors, and local heat flux output by the heat flow field simulation model are discretized in space and time to construct a three-dimensional heat flow data matrix for describing the evolution of heat flow. Based on the three-dimensional heat flux data matrix, the heat flux density variation trend of each finite volume unit node is calculated. The heat flux density variation trend includes the increase / decrease rate, gradient direction and amplitude of local heat flux density over time, and the heat flux concentration or sparse region is identified. Connectivity analysis is performed on the heat flux density variation trend to identify the dominant path of continuous heat flow along the dominant heat flow direction, forming a dominant heat flow transfer network, and recording the heat flux and deflection information on the path. In the heat flow-dominant transport network, regions of heat flow stagnation or backflow are detected. By combining the characteristics of heat flow density, flux, and vector direction, the heat flow stagnation regions and spatial distribution characteristics are marked, and heat flow behavior characteristics are jointly constructed.

3. The method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation as described in claim 2, characterized in that, After constructing the heat flow behavior state variables based on the aforementioned heat flow behavior characteristics, the matching relationship between the dominant heat flow transmission path and the predetermined ventilation and heat dissipation structure of the medium-voltage switchgear is analyzed, including: Based on the heat flow behavior state quantity, multiple continuous spatial sections are divided inside the medium-voltage switchgear along the ventilation direction, and a corresponding local heat flow organization map is generated on each spatial section using the heat flow vector component and the heat flow quantity component. A continuity analysis of the heat flow pattern is performed between adjacent sections. When the detected heat flow direction deviates from the predetermined ventilation and heat dissipation structure guidance direction by more than a preset threshold, or when the heat flow shows a trend of attenuation, dispersion or annular backflow exceeding a preset threshold, it is determined that the dominant heat flow transfer path of the corresponding section has been structurally interrupted. By utilizing the structural interruption locations marked in the local heat flow organization map, the evolutionary pattern of heat flow in the corresponding functional structural region from unidirectional dominant transmission to multidirectional circulation or local accumulation is identified. The evolutionary pattern is then correlated with the spatial distribution characteristics of heat flow behavioral state variables to establish structural changes.

4. The method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation as described in claim 3, characterized in that, Establishing structural changes also includes: Based on the heat flow behavior state variables, the heat flow vector deflection amplitude, flux change rate, and stability index of the dominant heat flow direction are calculated at the marked structural interruption location and adjacent spatial cross-sections. The stability index is used to quantify the local stability of the heat flow transfer path. The identified evolutionary patterns are weighted and evaluated using the stability index to determine the degree to which heat flow evolves from a stable state to an unstable state within the corresponding functional structural region, thus establishing structural changes.

5. The method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation as described in claim 1, characterized in that, Based on structured modeling, a thermal flow field simulation model is constructed to characterize the coupling relationship between internal heat transfer and airflow, including: The cabinet of the medium-voltage switchgear is divided into multiple finite volume units, and corresponding geometric nodes and boundary nodes are established in each finite volume unit to characterize the spatial topological relationship of the cabinet structure, electrical connection parts and ventilation channels. The operating current state of the busbar, electrical contacts and cable connection parts is mapped to the corresponding finite volume unit node. The local heating power density of each finite volume unit node is calculated based on the material thermal conductivity, resistance and contact impedance to form the heat flow boundary condition. Based on structured modeling, and combined with airflow characteristics and heat flow boundary conditions, a thermal flow field simulation model that couples heat transfer and airflow is constructed, so that the temperature and heat flux of each finite volume unit node can evolve over time, reflecting the heat flow distribution and heat transfer path inside the medium-voltage switchgear.

6. The method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation as described in claim 1, characterized in that, After determining the temperature rise trend based on the structural changes, a dynamic response adjustment strategy is configured based on the thermal flow behavior state variables, including: Based on the structural changes, the temperature rise sensitivity of each functional area inside the medium-voltage switchgear is determined, and the temperature rise sensitivity is mapped into a priority matrix for heat flow regulation. After configuring a dynamic response adjustment strategy using the priority matrix and thermal flow behavior state variables, directional adjustment of local ventilation holes, air duct openings, or heat dissipation devices in the corresponding functional areas is performed.

7. The method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation as described in claim 6, characterized in that, Configure a mapping monitoring window for the dynamic response adjustment strategy. During the execution of the dynamic response adjustment strategy, use the mapping monitoring window to perform temperature monitoring feedback, establish a feedback verification signal, and use the feedback verification signal to perform adaptive strategy optimization of the dynamic response adjustment strategy.

8. The method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation as described in claim 1, characterized in that, The dynamic response adjustment strategy includes implementing local ventilation enhancement or heat conduction adjustment in the heat flow retention area and the heat flow dominance path deflection area, respectively, to optimize the heat flow distribution inside the medium-voltage switchgear.

9. The method for dynamic temperature rise adjustment of medium-voltage switchgear based on thermal flow field simulation as described in claim 1, characterized in that, The thermal behavior state variables include the nodal heat load index calculated based on the heat flux density change trend, which is used to reflect the temperature rise sensitivity of each area inside the medium-voltage switchgear.

10. A dynamic temperature rise adjustment system for medium-voltage switchgear based on thermal flow field simulation, characterized in that, The system is used to implement the dynamic temperature rise adjustment method for medium-voltage switchgear based on thermal flow field simulation as described in any one of claims 1-9, the system comprising: The thermal flow field simulation model building module performs structured modeling based on the cabinet structure, electrical connection structure and ventilation structure of the medium-voltage switchgear, and maps the operating current state of the busbar, electrical contacts and cable connection parts as heating boundary conditions. Based on the structured modeling, a thermal flow field simulation model is built to characterize the coupling relationship between internal heat transfer and air flow. The heat flow behavior feature acquisition module is used to obtain the heat flow distribution results inside the medium-voltage switchgear under the current operating conditions using the heat flow field simulation model, and extract heat flow behavior features based on the heat flow distribution results. The heat flow behavior features include the heat flow density change trend, the dominant heat flow transfer path, and the distribution characteristics of the heat flow stagnation area. The structural change construction module, after constructing the heat flow behavior state variables based on the heat flow behavior characteristics, analyzes the matching relationship between the dominant heat flow transmission path and the predetermined ventilation and heat dissipation structure of the medium-voltage switchgear, and establishes structural changes. The dynamic response adjustment strategy configuration module is used to configure a dynamic response adjustment strategy based on the thermal flow behavior state variables after configuring the temperature rise trend determination result according to the structural changes.

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