Method and system for optimizing current-carrying capacity of high-voltage cable in complex construction environment

Abstract

The invention discloses a high-voltage cable current-carrying capability optimization method and system in a complex construction environment, and relates to the technical field of current-carrying optimization, and the method comprises the following steps: collecting first data along a cable to be laid; based on the first data, performing local thermal resistance calculation and temperature rise simulation on each section of the cable, generating an along-line space-thermal coupling map, and identifying paragraphs with local overheating risks; according to the identified overheating risk segment, dividing the cable along the line into a plurality of variable current-carrying intervals, and generating the maximum allowable current-carrying capacity; based on the variable current-carrying interval and the maximum allowable current-carrying capacity thereof, designing and optimizing a laying scheme; in the cable operation process, temperature and environment sensors are arranged based on the optimized laying scheme, local temperature rise is monitored in real time, and the operation current-carrying capacity of each interval is dynamically adjusted according to the monitoring result. According to the method, the variable current-carrying interval is divided by analyzing the spatial constraint and thermal characteristics along the cable, so that the problem that the current-carrying capacity is difficult to accurately evaluate in a complex environment is solved.

Description

Technical Field

[0001] This invention relates to the field of current-carrying capacity optimization technology, and more specifically, to a method and system for optimizing the current-carrying capacity of high-voltage cables in complex construction environments. Background Technology

[0002] With the acceleration of urbanization and the continuous expansion of power systems, high-voltage cables are widely laid in urban underground utility tunnels, complex building environments, and confined spaces such as bridges and tunnels. However, in these complex construction environments, the spatial constraints along the cable route vary significantly, and the thermal disturbances from the surrounding medium and nearby heat sources are complex and variable. Traditional current-carrying capacity calculation methods are usually based on the assumption of uniformity or empirical formulas, which are difficult to accurately reflect local thermal resistance changes and thermal coupling effects between cables.

[0003] Therefore, accurate assessment of the current-carrying capacity of high-voltage cables in complex construction environments, identification of local overheating risks, and dynamic current-carrying optimization based on space constraints and thermal coupling characteristics have become urgent technical problems to be solved.

[0004] The above-disclosed technical solutions have at least the following technical problems: In complex construction environments, the current-carrying capacity of high-voltage cables cannot be accurately determined, especially the maximum allowable current-carrying capacity of local space-constrained sections and thermally coupled sections is difficult to assess, resulting in a failure to balance operational safety and current-carrying potential. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a method and system for optimizing the current-carrying capacity of high-voltage cables in complex construction environments. By analyzing the spatial constraints and thermal characteristics along the cable route, the variable current-carrying range is divided and the laying scheme is optimized. Combined with real-time monitoring during operation, dynamic adjustment of the current-carrying capacity is achieved, thereby solving the problems of difficulty in accurately assessing the current-carrying capacity and difficulty in controlling the risk of local overheating in complex environments.

[0006] To achieve the above objectives, the present invention provides the following technical solution: On the one hand, a method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments includes the following steps: In the target complex construction environment, first data is collected along the cable to be laid; based on the first data, local thermal resistance calculation and temperature rise simulation are performed on each cable segment to generate a spatial-thermal coupling map along the route and identify segments with local overheating risks; according to the identified overheating risk segments, the cable route is divided into several variable current-carrying intervals, and the maximum allowable current-carrying capacity of each interval is generated; based on the variable current-carrying intervals and their maximum allowable current-carrying capacity, an optimized laying scheme is designed for the locally spatially confined intervals; during cable operation, temperature and environmental sensors are deployed based on the optimized laying scheme to monitor the local temperature rise in real time, and the operating current-carrying capacity of each interval is dynamically adjusted according to the monitoring results.

[0007] In a preferred embodiment, the step of calculating local thermal resistance and simulating temperature rise for each cable segment based on the first data to generate a spatial-thermal coupling map along the cable line specifically involves: constructing a geometric constraint matrix based on the collected spatial constraint parameters; generating a thermal conductivity curve of the underground medium varying with depth based on environmental parameters; constructing an external thermal disturbance distribution based on the surface temperature of adjacent equipment collected in the first data and its temperature sequence changing over time; solving for the local thermal resistance and temperature rise response of each cable segment in the corresponding spatial environment by coupling the geometric constraint matrix, the thermal conductivity curve of the underground medium, and the external thermal disturbance distribution to obtain a continuous thermal resistance-temperature rise sequence along the cable line; and mapping the thermal resistance-temperature rise sequence according to the spatial coordinates along the cable line to generate a spatial-thermal coupling map along the cable line.

[0008] In a preferred embodiment, identifying segments with local overheating risk specifically involves: jointly analyzing the temperature rise response, local thermal resistance, spatial constraint strength, and external thermal disturbance amplitude of each cable segment in the graph, and constructing a multidimensional thermal risk index based on the thermal field gradient change rate; comparing the multidimensional thermal risk index with the thermal cycle accumulation characteristics under historical operating conditions to identify segments that may overheat due to limited local heat dissipation, periodic heat accumulation, or enhanced thermal coupling, and generating a list of risk segments according to the thermal risk level.

[0009] In a preferred embodiment, the joint analysis of the temperature rise response, local thermal resistance, spatial constraint strength, and external thermal disturbance amplitude of each cable segment in the spectrum specifically involves: normalizing the temperature rise response, local thermal resistance, spatial constraint strength, and external thermal disturbance amplitude of each cable segment along the line; combining the normalized parameters according to preset weights to obtain a comprehensive thermal risk score for each cable segment; calculating the spatial gradient of temperature rise along the line and incorporating the gradient change rate into the comprehensive score for correction to reflect local heat accumulation and thermal coupling effects; and forming a multidimensional thermal risk index based on the corrected comprehensive score.

[0010] In a preferred embodiment, the step of dividing the cable along the route into several variable current-carrying intervals based on the identified overheating risk sections and generating the maximum allowable current-carrying capacity of each interval specifically involves: based on the risk section list, spatially merging risk sections with their adjacent low-risk sections to construct a segment clustering feature vector containing thermal risk level, spatial constraint strength, and external thermal disturbance amplitude; grouping the segments along the route based on the segment clustering feature vector, so that segments with similar heat dissipation capacity and thermal coupling characteristics form the same variable current-carrying interval; and solving the maximum allowable current-carrying capacity of the variable current-carrying interval based on the basic thermal resistance, external temperature rise response, spatial constraint coefficient, and thermal coupling strength of each interval, combined with the safe temperature rise limit, to form a variable current-carrying interval current-carrying configuration table along the route.

[0011] In a preferred embodiment, the step of spatially merging risk segments with their adjacent low-risk segments based on the risk segment list specifically involves: extracting the spatial boundary coordinates and corresponding thermal coupling characteristic change rate of each risk segment based on the spatial-thermal coupling map along the route, and generating a risk segment boundary set; identifying low-risk segments spatially adjacent to each risk segment based on the risk segment boundary set, and calculating the thermal gradient continuity index between the risk segment and the adjacent low-risk segment; filtering adjacent low-risk segments according to the thermal gradient continuity index, and only selecting low-risk segments that meet a preset continuity threshold as mergeable segments; performing regional fusion between the mergeable segments and the corresponding risk segments, and redefining the effective spatial boundary of the fusion interval based on the thermal coupling characteristic change rate within the fusion region; and finally generating the merged variable current-carrying interval based on the effective spatial boundary of the fusion interval.

[0012] In a preferred embodiment, the step of designing and optimizing the laying scheme for locally confined spaces based on variable current-carrying intervals and their maximum allowable current-carrying capacity specifically involves: using the current-carrying configuration table of the variable current-carrying intervals as input, identifying locally confined spaces where there is a gap between current-carrying capacity and operational requirements and which belong to a high thermal risk level, and using the maximum allowable current-carrying capacity of the interval as a design constraint to determine the target temperature rise and safety margin to be optimized; for each target interval, calculating and listing candidate thermal resistance reduction measures based on the spatial-thermal coupling pattern along the route and the effective thermal resistance of the interval; initially ranking the candidate measures according to the unit thermal resistance reduction effect and construction feasibility, and selecting several priority measure sets as preliminary optimization combinations; establishing a local refined simulation model, calculating the expected effective thermal resistance and temperature rise curve of the optimized interval, and verifying whether the temperature rise under the maximum allowable current-carrying capacity is lower than the safety threshold after the target temperature rise is reduced; if the simulation verification does not meet the safety margin, additional candidate measures are introduced in sequence and the simulation is repeated until the safety margin is met or the construction cost limit is reached.

[0013] In a preferred embodiment, during cable operation, temperature and environmental sensors are deployed based on an optimized laying scheme to monitor local temperature rise in real time, and the operating current carrying capacity of each section is dynamically adjusted according to the monitoring results. Specifically, temperature and environmental sensors are deployed in each variable current carrying capacity section. The sensor placement locations are determined based on the thermal gradient distribution and heat accumulation points in the optimized laying scheme to ensure coverage of areas with maximum temperature rise changes and spatially confined sections. Temperature and environmental data from each sensor are collected in real time, and the collected data is correlated with the corresponding variable current carrying capacity section to form a dynamic monitoring dataset along the line. Time-series analysis and temperature rise prediction are performed on the dynamic monitoring data to calculate the deviation between the instantaneous temperature rise of each section and the expected temperature rise of the optimized design. Based on the deviation and the maximum allowable current carrying capacity of each section, the actual operating current carrying capacity of each section is dynamically adjusted. The adjusted operating current carrying capacity and real-time monitoring data are continuously fed back, and the parameters of the variable current carrying capacity section division and optimized laying scheme are updated based on long-term monitoring results.

[0014] On the other hand, a high-voltage cable current-carrying capacity optimization system for complex construction environments includes the following modules: a data acquisition module for acquiring initial data along the cable to be laid in the target complex construction environment; a local thermal resistance and temperature rise simulation module for calculating local thermal resistance and simulating temperature rise for each cable segment based on the initial data, generating a spatial-thermal coupling map along the cable, and identifying segments with local overheating risks; a variable current-carrying interval division module for dividing the cable into several variable current-carrying intervals based on the identified overheating risk segments, and generating the maximum allowable current-carrying capacity of each interval; a local optimization design module for designing optimized laying schemes for spatially confined intervals based on the variable current-carrying intervals and their maximum allowable current-carrying capacity; and a real-time monitoring and dynamic adjustment module for deploying temperature and environmental sensors based on the optimized laying scheme during cable operation, monitoring local temperature rise in real time, and dynamically adjusting the operating current-carrying capacity of each interval based on the monitoring results.

[0015] The technical effects and advantages of this invention, which describes a method and system for optimizing the current-carrying capacity of high-voltage cables in complex construction environments, are as follows: This invention systematically collects and analyzes spatial constraints, thermal resistance, and external thermal disturbances along cable routes in complex construction environments to form a spatial-thermal coupling map along the route. It identifies local overheating risk sections and divides variable current-carrying intervals based on these risk sections, determining the maximum allowable current-carrying capacity of each interval. For spatially confined intervals, it designs and optimizes the laying scheme and verifies it through simulation. Simultaneously, during the operation phase, it deploys temperature and environmental sensors to achieve real-time monitoring of local temperature rise and dynamic adjustment of current-carrying capacity. This significantly improves the overall current-carrying capacity of the cable, fully utilizes local current-carrying potential, and achieves closed-loop optimization of laying and operation management while ensuring operational safety. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments, as proposed by the present invention. Figure 2 This is a schematic diagram of the structure of a high-voltage cable current-carrying capacity optimization system for complex construction environments according to the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, Figure 1 This invention presents a method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments, comprising the following steps: S1, in the complex construction environment of the target, collect the first data along the route of the cable to be laid; The first data includes spatial constraint parameters and environmental parameters; The spatial constraint parameters include the width of the pipe gallery or channel, the distance between adjacent pipelines, the bending radius limit, and the local heat source distribution information; The environmental parameters include soil type, groundwater level, and local humidity; In this embodiment, the step of collecting the first data along the route of the cable to be laid in the target complex construction environment specifically includes: The available space width of each cable segment and the spacing between adjacent pipelines can be obtained by using a pipe rack rangefinder or laser scanning device. The surface temperature and distribution location of nearby heat sources are measured using wearable or fixed temperature sensors. Information on soil type, moisture content, and groundwater level was obtained through soil sampling and groundwater level sensors.

[0019] S2, based on the first data, performs local thermal resistance calculation and temperature rise simulation for each cable segment, generates a spatial-thermal coupling map along the line, and identifies segments with local overheating risks; In this embodiment, the along-line space-thermal coupling map is a comprehensive map used to describe the local heat dissipation capacity and temperature rise distribution characteristics of high-voltage cable segments. It establishes a local thermal resistance model for each cable segment by coupling calculations of spatial constraints around the cable (such as pipe gallery width, trench size, distance between adjacent pipelines, and bending radius limitations) with environmental factors such as the location of nearby heat sources, surface temperature, soil type, moisture content, and groundwater level. Combined with the cable's own load-heating characteristics, temperature rise simulation is performed, thereby generating the local heat dissipation capacity, predicted temperature rise, and thermal risk indicators for each cable segment along the line. This map not only intuitively reflects the thermal state of the cable under the influence of spatial constraints and environmental conditions along the line, but also provides a quantitative basis for subsequent variable current-carrying section division, laying scheme optimization, and dynamic operation control, enabling accurate analysis and optimization of cable current-carrying capacity in complex construction environments.

[0020] Based on the first data, local thermal resistance calculation and temperature rise simulation are performed on each cable segment to generate a spatial-thermal coupling map along the cable, specifically: Based on the collected spatial constraint parameters, a geometric constraint matrix is ​​constructed to characterize the available heat dissipation space and spatial shading degree of each segment. Based on environmental parameters, thermal conductivity curves of underground media varying with depth are generated to characterize the thermal diffusion capacity of different burial depth sections. Based on the surface temperature of adjacent equipment collected in the first data and its temperature sequence over time, an external thermal disturbance distribution is constructed to characterize the superimposed effect of external periodic heat sources on cable temperature rise. By coupling the geometric constraint matrix, the thermal conductivity curve of the underground medium, and the distribution of external thermal disturbance, the local thermal resistance and temperature rise response of each cable segment in the corresponding spatial environment are solved, and a continuous thermal resistance-temperature rise sequence along the line is obtained. The thermal resistance-temperature rise sequence is mapped along the spatial coordinates to generate a spatial-thermal coupling map, which is used to characterize the location of the thermal bottleneck and the thermal accumulation trend caused by spatial compression, uneven thermal diffusion of the medium and superposition of external heat sources.

[0021] The section that identifies the risk of localized overheating specifically includes: The temperature rise response, local thermal resistance, spatial constraint strength and external thermal disturbance amplitude of each cable segment in the spectrum are jointly analyzed, and a multidimensional thermal risk index is constructed based on the thermal field gradient change rate. By comparing multidimensional thermal risk indicators with the thermal cycle accumulation characteristics under historical operating conditions, sections that may overheat due to limited local heat dissipation, periodic heat accumulation, or enhanced thermal coupling are identified, and a list of risk sections is generated according to the thermal risk level to guide the automatic division of variable current carrying ranges.

[0022] In this embodiment, the joint analysis of the temperature rise response, local thermal resistance, spatial constraint strength, and external thermal disturbance amplitude of each cable segment in the spectrum, and the construction of a multidimensional thermal risk index based on the thermal field gradient change rate, specifically involves: The temperature rise response, local thermal resistance, spatial constraint strength, and external thermal disturbance amplitude of each cable segment along the line are normalized. The normalized parameters are combined according to the preset weights to obtain the comprehensive thermal risk score for each cable segment. The spatial gradient of temperature rise along the line is calculated, and the gradient change rate is incorporated into the comprehensive score for correction, so as to reflect the local thermal accumulation and thermal coupling effects. The revised comprehensive score is used to form a multidimensional thermal risk index, which is used to quantify the overheating risk of each cable segment and provide a basis for risk segment identification and variable current carrying range division.

[0023] S3, based on the identified overheat risk sections, divide the cable line into several variable current-carrying intervals and generate the maximum allowable current-carrying capacity for each interval; In this embodiment, the process of dividing the cable along its length into several variable current-carrying intervals based on the identified overheating risk sections and generating the maximum allowable current-carrying capacity for each interval is specifically as follows: Based on the list of risk segments, risk segments are spatially merged with their adjacent low-risk segments to construct a segment clustering feature vector that includes thermal risk level, spatial constraint strength and external thermal disturbance amplitude. Based on the segment clustering feature vector, each segment along the line is grouped so that segments with similar heat dissipation capacity and thermal coupling characteristics form the same variable current carrying range. Based on the basic thermal resistance, external temperature rise response, spatial constraint coefficient and thermal coupling strength of each section, and combined with the safe temperature rise limit, the maximum allowable current carrying capacity of the variable current carrying section is calculated to form a current carrying capacity configuration table of the variable current carrying section along the line, which is used to guide the subsequent laying scheme optimization and operation adjustment.

[0024] The process of spatially merging risky segments with their adjacent low-risk segments based on the risk segment list is as follows: Based on the spatial-thermal coupling map along the route, the spatial boundary coordinates and corresponding thermal coupling feature change rates of each risk segment are extracted, and a risk segment boundary set is generated. Based on the risk segment boundary set, low-risk segments that are spatially adjacent to each risk segment are identified, and the thermal gradient continuity index between the risk segment and the adjacent low-risk segment is calculated. Adjacent low-risk segments are screened based on the thermal gradient continuity index, and only low-risk segments that meet the preset continuity threshold are considered as mergeable segments. Merge the mergeable segments with the corresponding risk segments, and redefine the effective spatial boundary of the fusion interval based on the rate of change of thermal coupling characteristics within the fusion region. Finally, based on the effective spatial boundary of the fusion interval, a merged variable current-carrying interval is generated, providing input conditions for subsequent calculation of the maximum allowable current-carrying capacity.

[0025] The maximum allowable current carrying capacity is specifically as follows:

[0026]

[0027]

[0028] in, For the maximum allowable flow rate, This represents the safe temperature rise limit for the corresponding range. The external temperature rise response is obtained by superimposing an external thermal disturbance model, including factors such as nearby heat sources, intersecting pipelines, and backfill material temperature. To balance thermal resistance, The spatial constraint coefficient is... Based on the fundamental thermal resistance (obtained through conventional calculations). The thermal coupling strength coefficient, extracted from the space-thermal coupling map, is used to characterize the proportion of increase in thermal resistance caused by nearby heat source groups and narrow spatial constraints. , , These are the actual cable spacing, actual bending radius, and actual backfill thickness, respectively. , , These are the standard cable spacing, minimum allowable bending radius, and standard backfill thickness, respectively.

[0029] S4, based on the variable current-carrying range and its maximum allowable current-carrying capacity, design an optimized laying scheme for the locally space-constrained section; In this embodiment, the optimized laying scheme for locally confined areas based on the variable current-carrying range and its maximum allowable current-carrying capacity is specifically as follows: Using the variable current-carrying interval current-carrying configuration table as input, identify the local space-restricted intervals where there is a gap between the current-carrying capacity and the operational requirements and which belong to the "high thermal risk level". Then, use the maximum allowable current-carrying capacity of the interval as a design constraint to determine the target temperature rise and safety margin that need to be optimized. For each target section, based on the aforementioned spatial-thermal coupling map along the line and the effective thermal resistance of the section, a set of candidate thermal resistance reduction measures are calculated and listed. The candidate measures include, but are not limited to: increasing cable spacing, adjusting the relative arrangement order of cables, increasing the bending radius to the specified minimum value, replacing with conductors with larger cross-sections or laying conductors in parallel, installing heat conduction backplates or heat sinks in the pipe gallery, filling the space between the cable and the enclosure structure with high thermal conductivity backfill, adding local ventilation or forced cooling modules, installing local grounding heat sinks or heat pipe heat dissipation units, and increasing the thermal conductivity of the cable outer sheath. The candidate measures are initially ranked according to "unit thermal resistance reduction effect and construction cost", and several priority measure sets are selected based on the spatial constraint strength and construction feasibility of the interval, which serve as the initial optimized combination for the interval. For the aforementioned preliminary optimized combination, a local refined simulation model is established (based on the aforementioned geometric constraint matrix, thermal conductivity curve and external thermal disturbance distribution), the expected effective thermal resistance and expected temperature rise curve of the optimized interval are calculated, and it is verified whether the temperature rise is lower than the safety threshold after the target temperature rise is reduced under the action of the maximum allowable current carrying capacity of the interval. If the simulation verification fails to meet the safety margin determined in item 1, additional candidate measures will be introduced in sequence according to the preliminary sorting and the temperature rise will be repeatedly verified to ensure that the temperature rise is lower than the safety threshold after the target temperature rise is reduced, until the safety margin is met or the preset construction cost limit is reached.

[0030] The optimized laying scheme for locally confined sections based on the variable current-carrying range and its maximum allowable current-carrying capacity also includes: Generate the final optimized cable laying plan document, including the optimized cable geometry layout, recommended backfill materials and thickness, heat dissipation units or ventilation / cooling devices to be installed, bending radius correction requirements and construction tolerance range; Identify and mark the sensor deployment points for real-time verification during the operation phase, including local surface temperature sensors, multi-point temperature probes along the section, and environmental sensors. The deployment locations are based on the areas of maximum change in the optimized thermal field gradient and the points of thermal accumulation. The optimized plan and sensor deployment points are combined into an integrated delivery list for construction and monitoring, and include operation control recommendations based on the optimized parameters, including a time-sharing table of current carrying capacity or dynamic current limiting curve, triggering conditions for local forced cooling strategy, and graded emergency load reduction measures. The expected effective thermal resistance, sensor layout, and operation control recommendations are used as inputs for subsequent real-time monitoring and closed-loop feedback adjustments to achieve dynamic current carrying capacity correction and operation strategy optimization for variable current carrying ranges, thereby forming a closed-loop optimization process from range division to optimized laying and then to operation adjustment.

[0031] S5, during cable operation, temperature and environmental sensors are installed based on the optimized laying scheme to monitor local temperature rise in real time, and the operating current carrying capacity of each section is dynamically adjusted according to the monitoring results.

[0032] In this embodiment, during cable operation, temperature and environmental sensors are installed based on an optimized laying scheme to monitor local temperature rise in real time, and the operating current carrying capacity of each section is dynamically adjusted according to the monitoring results. Specifically: Temperature sensors and environmental sensors are deployed in each variable current-carrying interval. The locations of the sensors are determined based on the thermal gradient distribution and heat accumulation points in the optimized laying scheme to ensure coverage of the area with the greatest temperature rise and the space-constrained section. Real-time data collection of temperature, humidity, soil, and air environment from various sensors is performed, and the data is correlated with the corresponding variable current carrying range to form a dynamic monitoring dataset along the line. The monitoring data is subjected to time series analysis and temperature rise prediction to calculate the deviation between the instantaneous temperature rise in each interval and the expected temperature rise of the optimized design. The actual operating capacity of each interval is dynamically adjusted based on the aforementioned deviation and the maximum allowable capacity of each interval. The actual operating current carrying capacity and monitored temperature rise data are continuously fed back after dynamic adjustment, and the parameters of the variable current carrying capacity range division and the optimized laying scheme are updated based on long-term monitoring results.

[0033] The dynamic adjustment of the actual operating capacity of each interval is specifically as follows: If the deviation is greater than or equal to the preset deviation threshold, the actual operating current carrying capacity is reduced to control the temperature rise within the safe threshold. If the deviation is less than the preset deviation threshold and there is still thermal margin, the actual operating current carrying capacity can be appropriately increased to improve the line utilization rate. For confined spaces or areas with significant thermal accumulation, a graded current-carrying control strategy can be applied, allowing for the setting of point-based current limits within the same interval.

[0034] Example 2, Figure 2 This invention presents a system for optimizing the current-carrying capacity of high-voltage cables in complex construction environments, comprising the following modules: Data acquisition module: Used to collect initial data along the cable to be laid in complex construction environments. Local thermal resistance and temperature rise simulation module: Based on the first data, it is used to calculate the local thermal resistance and simulate the temperature rise of each cable segment, generate a spatial-thermal coupling map along the line, and identify segments with local overheating risks. Variable current carrying range division module: used to divide the cable along the line into several variable current carrying ranges based on the identified overheat risk sections, and generate the maximum allowable current carrying capacity of each range; Local optimization design module: used to design and optimize laying schemes for local space-constrained sections based on variable current-carrying range and its maximum allowable current-carrying capacity; Real-time monitoring and dynamic adjustment module: Used to monitor local temperature rise in real time during cable operation by deploying temperature and environmental sensors based on the optimized laying scheme, and dynamically adjust the operating current carrying capacity of each section according to the monitoring results.

[0035] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0036] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0037] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0038] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0039] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0040] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments, characterized in that, Includes the following steps: In a complex construction environment, collect the first data along the route of the cable to be laid; Based on the first data, local thermal resistance calculation and temperature rise simulation are performed on each cable segment to generate a spatial-thermal coupling map along the line and identify segments with local overheating risks. Based on the identified overheating risk sections, the cable route is divided into several variable current-carrying intervals, and the maximum allowable current-carrying capacity of each interval is generated. Based on the variable current-carrying range and its maximum allowable current-carrying capacity, an optimized laying scheme is designed for locally space-constrained sections. During cable operation, temperature and environmental sensors are installed based on the optimized laying scheme to monitor local temperature rise in real time, and the operating current carrying capacity of each section is dynamically adjusted according to the monitoring results.

2. The method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments according to claim 1, characterized in that, Based on the first data, local thermal resistance calculation and temperature rise simulation are performed on each cable segment to generate a spatial-thermal coupling map along the cable, specifically: A geometric constraint matrix is ​​constructed based on the collected spatial constraint parameters; Generating thermal conductivity curves of underground media that vary with depth based on environmental parameters; Based on the surface temperature of adjacent devices collected in the first data and its temperature sequence changing over time, an external thermal disturbance distribution is constructed. By coupling the geometric constraint matrix, the thermal conductivity curve of the underground medium, and the distribution of external thermal disturbance, the local thermal resistance and temperature rise response of each cable segment in the corresponding spatial environment are solved, and a continuous thermal resistance-temperature rise sequence along the line is obtained. The thermal resistance-temperature rise sequence is mapped along the spatial coordinates to generate a spatial-thermal coupling map along the line.

3. The method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments according to claim 2, characterized in that, The section that identifies the risk of localized overheating specifically includes: The temperature rise response, local thermal resistance, spatial constraint strength and external thermal disturbance amplitude of each cable segment in the spectrum are jointly analyzed, and a multidimensional thermal risk index is constructed based on the thermal field gradient change rate. By comparing the multidimensional thermal risk indicators with the thermal cycle accumulation characteristics under historical operating conditions, sections that may overheat due to limited local heat dissipation, periodic heat accumulation, or enhanced thermal coupling are identified, and a list of risk sections is generated according to the thermal risk level.

4. The method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments according to claim 3, characterized in that, The joint analysis of the temperature rise response, local thermal resistance, spatial constraint strength, and external thermal disturbance amplitude of each cable segment in the spectrum is as follows: The temperature rise response, local thermal resistance, spatial constraint strength, and external thermal disturbance amplitude of each cable segment along the line are normalized. The normalized parameters are combined according to the preset weights to obtain the comprehensive thermal risk score for each cable segment. The spatial gradient of temperature rise along the line is calculated, and the gradient change rate is incorporated into the comprehensive score for correction, so as to reflect the local thermal accumulation and thermal coupling effects. A multidimensional thermal risk index is formed based on the revised comprehensive score.

5. The method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments according to claim 4, characterized in that, Based on the identified overheating risk sections, the cable route is divided into several variable current-carrying intervals, and the maximum allowable current-carrying capacity of each interval is generated, specifically as follows: Based on the list of risk segments, risk segments are spatially merged with their adjacent low-risk segments to construct a segment clustering feature vector that includes thermal risk level, spatial constraint strength and external thermal disturbance amplitude. Based on the segment clustering feature vector, each segment along the line is grouped so that segments with similar heat dissipation capacity and thermal coupling characteristics form the same variable current carrying range. Based on the basic thermal resistance, external temperature rise response, spatial constraint coefficient and thermal coupling strength of each interval, and combined with the safe temperature rise limit, the maximum allowable current carrying capacity of the variable current carrying interval is calculated to form a current carrying capacity configuration table of the variable current carrying interval along the line.

6. The method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments according to claim 5, characterized in that, The process of spatially merging risky segments with their adjacent low-risk segments based on the risk segment list is as follows: Based on the spatial-thermal coupling map along the route, the spatial boundary coordinates and corresponding thermal coupling feature change rates of each risk segment are extracted, and a risk segment boundary set is generated. Based on the risk segment boundary set, low-risk segments that are spatially adjacent to each risk segment are identified, and the thermal gradient continuity index between the risk segment and the adjacent low-risk segment is calculated. Adjacent low-risk segments are screened based on the thermal gradient continuity index, and only low-risk segments that meet the preset continuity threshold are considered as mergeable segments. Merge the mergeable segments with the corresponding risk segments, and redefine the effective spatial boundary of the fusion interval based on the rate of change of thermal coupling characteristics within the fusion region. Finally, based on the effective spatial boundary of the fusion interval, the merged variable current-carrying interval is generated.

7. The method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments according to claim 6, characterized in that, The optimized laying scheme for locally space-constrained sections, based on the variable current-carrying range and its maximum allowable current-carrying capacity, is as follows: Using the variable current-carrying interval current-carrying configuration table as input, identify the local space-restricted intervals where there is a gap between current-carrying capacity and operational requirements and which belong to the high thermal risk level, and use the maximum allowable current-carrying capacity of the interval as a design constraint to determine the target temperature rise and safety margin that need to be optimized. For each target interval, based on the spatial-thermal coupling pattern along the line and the effective thermal resistance of the interval, candidate thermal resistance reduction measures are calculated and listed. Candidate measures were initially ranked according to their unit thermal resistance reduction effect and construction feasibility, and several priority measures were selected as preliminary optimization combinations. Establish a localized refined simulation model, calculate the expected effective thermal resistance and temperature rise curve of the optimized interval, and verify whether the temperature rise under the maximum allowable current carrying capacity is lower than the safety threshold after the target temperature rise is reduced. If the simulation verification does not meet the safety margin, additional candidate measures are introduced in sequence and the simulation is repeated until the safety margin is met or the construction cost limit is reached.

8. The method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments according to claim 7, characterized in that, During cable operation, temperature and environmental sensors are installed based on an optimized laying scheme to monitor local temperature rise in real time, and the operating current-carrying capacity of each section is dynamically adjusted according to the monitoring results. Specifically: Temperature sensors and environmental sensors are deployed in each variable current-carrying interval. The locations of the sensors are determined based on the thermal gradient distribution and heat accumulation points in the optimized laying scheme to ensure coverage of the area with the greatest temperature rise and the space-constrained section. Real-time collection of temperature and environmental data from each sensor, and correlation of the collected data with the corresponding variable current carrying range to form a dynamic monitoring dataset along the line; The dynamic monitoring data is subjected to time series analysis and temperature rise prediction to calculate the deviation between the instantaneous temperature rise in each interval and the expected temperature rise of the optimized design. Based on the aforementioned deviation and the maximum allowable flow rate of each interval, the actual operating flow rate of each interval is dynamically adjusted; The adjusted operating current carrying capacity and real-time monitoring data will be continuously fed back, and the parameters for the variable current carrying capacity range division and optimized laying scheme will be updated based on long-term monitoring results.

9. A system using the method for optimizing the current-carrying capacity of high-voltage cables in complex construction environments as described in any one of claims 1-8, characterized in that, Includes the following modules: Data acquisition module: Used to collect initial data along the cable to be laid in complex construction environments. Local thermal resistance and temperature rise simulation module: Based on the first data, it is used to calculate the local thermal resistance and simulate the temperature rise of each cable segment, generate a spatial-thermal coupling map along the line, and identify segments with local overheating risks. Variable current carrying range division module: used to divide the cable along the line into several variable current carrying ranges based on the identified overheat risk sections, and generate the maximum allowable current carrying capacity of each range; Local optimization design module: used to design and optimize laying schemes for local space-constrained sections based on variable current-carrying range and its maximum allowable current-carrying capacity; Real-time monitoring and dynamic adjustment module: Used to monitor local temperature rise in real time during cable operation by deploying temperature and environmental sensors based on the optimized laying scheme, and dynamically adjust the operating current carrying capacity of each section according to the monitoring results.

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