A cable ampacity calculation method considering soil stratification and temperature variation characteristics

Abstract

The application discloses a cable ampacity calculation method considering soil layering and temperature variation characteristics, obtains power cable laying environment parameters, obtains power cable laying environment parameters, selects different models to obtain soil temperature at the cable burial depth according to whether there is soil temperature-depth measured data set, and then, in combination with thermal resistance of each layer of the cable body and laying environment thermal resistance, the cable ampacity is calculated, the influence of soil layering and temperature variation is accurately reflected, and accurate ampacity basis is provided for safe operation of the cable.

Description

Technical Field

[0001] This invention provides a method for calculating cable current carrying capacity that takes into account soil stratification and temperature variation characteristics, belonging to the field of cable current carrying capacity technology. Background Technology

[0002] As a crucial component of new energy transmission, the accurate calculation of the current-carrying capacity of high-voltage power cables is of paramount importance to the engineering project itself. Based on experimental and engineering monitoring data, currently used methods for calculating cable current-carrying capacity are overly conservative, leading to lower cable operating temperatures after project commissioning and resulting in a heavier investment burden. Current research, both domestically and internationally, typically uses the local average ground temperature as the initial temperature for current-carrying capacity calculations. This temperature reflects the temperature of the hottest month at the cable laying location, without considering soil stratification and temperature variations at the cable burial depth after stratification. Therefore, traditional methods struggle to accurately reflect the heat generation at the cable burial location. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for calculating cable current carrying capacity that takes into account soil stratification and temperature variation characteristics, thereby solving the technical problem of overly conservative cable current carrying capacity calculation.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0005] In a first aspect, the present invention provides a method for calculating the current-carrying capacity of cables that takes into account soil stratification and temperature variation characteristics, characterized by comprising the following steps:

[0006] To obtain environmental parameters for power cable laying, depending on the availability of a measured soil temperature-depth dataset, select the following steps:

[0007] If a measured dataset exists, the soil temperature model parameters are retrieved using the artificial bee colony algorithm to obtain the soil temperature at the cable burial depth.

[0008] If no actual measured dataset is available, a layered soil heat conduction temperature model containing soil stratification thermophysical parameters is used to obtain the soil temperature at the cable burial depth.

[0009] The current carrying capacity of the cable is calculated based on the soil temperature at the cable burial depth, combined with the thermal resistance of each layer of the cable body and the thermal resistance of the laying environment.

[0010] In conjunction with the first aspect, furthermore, the soil temperature model parameters are retrieved using an artificial bee colony algorithm to obtain the soil temperature at the cable burial depth, including:

[0011] The measured dataset was organized into a standard sample set, which includes multiple sets of soil depths and corresponding measured soil temperatures.

[0012] Select the soil temperature-depth function model and determine the model parameters to be inverted;

[0013] Initialize the nectar source population, parameter upper and lower bounds, and algorithm control parameters for the artificial bee colony algorithm, where each nectar source represents a set of model parameters to be inverted;

[0014] The process iteratively executes steps such as neighbor search for hired bees, probability selection and neighbor search for follower bees, and random reset for scout bees, aiming to minimize the fitting error between the model-calculated temperature and the measured soil temperature, until the maximum number of iterations is reached.

[0015] The globally optimal nectar source is output as the final inversion model parameter, and the soil temperature at the cable burial depth is obtained using this parameter.

[0016] Furthermore, the soil temperature-depth function model is an exponential decay model, as follows:

[0017] ,

[0018] Among them, the dataset to be determined T(z,t) represents the soil temperature at depth z at time t, in °C. s λ represents the deep steady-state geothermal temperature in °C; A0 represents the annual fluctuation amplitude constant in °C; and λ represents the temperature decay characteristic constant.

[0019] Furthermore, the fitting error is the mean squared error, and the fitness value in the artificial bee colony algorithm is inversely proportional to the mean squared error.

[0020] Furthermore, the stratified soil heat conduction temperature model is as follows:

[0021] ;

[0022] In the formula, T(z,t) is the temperature at time t at depth z, z is the cable burial depth in meters (m), and t is the annual cycle time in seconds (s). The average ground temperature of the region, in units ; ω is the annual fluctuation amplitude constant; ω is the annual periodic angular frequency. ; The soil thermal resistivity; The soil thermal diffusivity is a value that is differentiated based on the soil stratification structure.

[0023] Furthermore, the formula for calculating the current carrying capacity of a cable is as follows:

[0024]

[0025] In the formula, The current carrying capacity of the cable is expressed in units of 1. ; The maximum allowable temperature for cable insulation material is specified for AC cables. ; The dielectric loss per unit length of the conductor's insulation layer, measured in units of... ; This refers to the number of conductor cores. AC resistance at operating temperature, in units of ; This represents the ratio of metal sheath loss to conductor loss. T1 is the ratio of armor loss to conductor loss; T2 is the thermal resistance of the insulation layer between the conductor and the metal sheath; T3 is the thermal resistance of the padding layer between the metal sheath and the armor layer; T4 is the thermal resistance between the cable outer sheath and the surrounding medium.

[0026] Furthermore, when the laying method is pipe laying, the thermal resistance between the cable surface and the surrounding medium is composed of three parts connected in series: the thermal resistance of the external medium of the pipe, the thermal resistance of the air gap inside the pipe, and the thermal resistance of the pipe wall itself.

[0027] Furthermore, the environmental parameters for laying the power cable include the cable burial depth, the average ground temperature of the area, the soil thermal resistivity, and the soil thermal diffusivity.

[0028] In a second aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the first aspects.

[0029] Thirdly, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the program, implements the steps of the method described in any of the first aspects.

[0030] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0031] This invention provides a method for calculating cable current carrying capacity considering soil stratification and temperature variation characteristics. Depending on the availability of a measured soil temperature-depth dataset, the method selects parameters from the exponential decay model obtained via artificial bee colony algorithm or employs a stratified soil heat conduction model incorporating soil thermal resistivity and thermal diffusivity to obtain the soil temperature at the cable burial depth. The current carrying capacity is then calculated by combining the thermal resistance of each layer of the cable body and the thermal resistance of the laying environment. This method overcomes the shortcomings of traditional methods that only use the average ground temperature of the hottest month and ignore soil stratification and temperature variation characteristics. When measured data is available, intelligent optimization improves the accuracy of temperature calculation; when no measured data is available, the influence of stratified thermophysical parameters is still taken into account. This makes the current carrying capacity calculation closer to actual operating conditions, avoiding oversized cable cross-sections and wasted investment due to conservative design. It optimizes cable selection and reduces engineering costs while ensuring reliable power transmission. Attached Figure Description

[0032] Figure 1 A cross-sectional view of a typical cable structure provided in an embodiment of the present invention;

[0033] Figure 2 This invention provides a method for calculating the current carrying capacity of artificial honeycomb cables, taking into account soil stratification and temperature variation characteristics.

[0034] Figure 3 A flowchart of soil temperature-depth relationship calculation based on artificial bee colony algorithm provided in an embodiment of the present invention;

[0035] In the diagram: 1. Water-blocking copper conductor; 2. Conductor shielding; 3. XLPE insulation; 4. Insulation shielding; 5. Semiconductor water-blocking tape; 6. Alloy lead sheath; 7. PE sheath; 8. Optical unit filler; 9. Optical unit; 10. Polypropylene inner lining; 11. Circular copper wire armor and asphalt; 12. Polypropylene outer sheath. Detailed Implementation

[0036] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0037] Example 1:

[0038] This embodiment provides a method for calculating cable current carrying capacity based on soil stratification and temperature changes. The specific process is as follows: Figure 2 As shown, it includes the following steps:

[0039] S1: Obtain environmental parameters for power cable laying, mainly including cable burial depth. The unit is The average ground temperature of the area ,unit ;

[0040] S2: Determine whether there is a soil temperature-depth measured dataset based on the actual engineering situation.

[0041] Scenario 1: If measured data is available, the soil temperature model parameters are retrieved using the artificial bee colony algorithm, such as... Figure 3 The diagram illustrates the calculation process for the soil temperature-depth relationship based on the artificial bee colony algorithm. The steps are as follows:

[0042] S021: Organize the measured samples and remove abnormally abrupt measurement points. Obtain the soil depth. Measured soil temperature The standard dataset is

[0043] S022: Select a function model suitable for the study area and determine the location parameters to be inverted. This invention uses the exponential decay model as an example: The dataset to be determined T(z,t) represents the soil temperature at depth z at time t, in °C. s λ represents the deep steady-state geothermal temperature in °C; A0 represents the annual fluctuation amplitude constant in °C; and λ represents the temperature decay characteristic constant.

[0044] S023: Set the basic parameters of the artificial bee colony algorithm, determine the algorithm's running configuration and parameter search range, and unify the symbol definitions as follows:

[0045] Total number of nectar sources;

[0046] : Dimensions of parameters to be inverted, such as exponential models ;

[0047] : No. The first honey source, the Dimensional parameters;

[0048] New candidate solutions generated by neighborhood search;

[0049] Another randomly selected honey source number. ;

[0050] :[-1,1] uniform random numbers;

[0051] : No. Number of consecutive periods of stagnation due to lack of optimization for a single honey source;

[0052] : Scout bee trigger threshold;

[0053] : No. Upper and lower bounds of the dimension parameter;

[0054] : No. The mean square error of the fit to each nectar source;

[0055] : No. Each nectar source fitness value;

[0056] : No. The probability of a nectar source being selected by a following bee for the next neighborhood search;

[0057] S024: Initialize the nectar source population, randomly generating it within the upper and lower bounds of the parameters. Initial model parameters for each group of nectar sources. Each group of nectar sources represents a complete set of unknown parameters for the soil temperature-depth model.

[0058] (1) Substitute the parameters of each honey source model into the model and calculate the theoretical temperature at each depth.

[0059] (2) Calculate the fitting error of each set of parameters.

[0060] (3) Convert to fitness of artificial bee colony algorithm: the smaller the error, the larger the fitness value, and the optimization logic of the adaptation algorithm is maximized.

[0061] S025: Hired bees, local search and greedy optimization, as detailed below:

[0062] (1) In the current honey source Nearby, random perturbations generate new solutions. ;

[0063] (2) If Then update Otherwise, retain the original solution. .

[0064] S026: Follow-the-bee, adaptive optimization and local search, as detailed below:

[0065] (1) Fitness calculations are performed to minimize the error of the artificial bee colony.

[0066] (2) The higher the fitness, the greater the probability of being selected by the follower bees.

[0067] (3) Local neighborhood search, consistent with hired bees: .

[0068] S027: Scout Bee, new solution for interval random formula reset.

[0069] (1) Triggering conditions The lack of optimization of nectar sources over a long period triggered the scout bee mechanism.

[0070] (2) New honey sources are randomly reset. A new set of soil model parameters is randomly generated within the physical range of the parameters.

[0071] S028: Output the optimal inversion model parameters for the artificial bee colony after reaching the maximum number of iterations. .

[0072] The population size, scout bee threshold, and number of iterations should be adjusted according to the number of data samples. If the number of samples D < 30 groups, the population size should be 60~90; if 30 ≤ D < 100 groups, the population size should be 200~300; if D ≥ 100 groups, the population size should be 3×D.

[0073] The threshold for detecting bees should be set to approximately limit = SN × D × 1.5.

[0074] Number of iterations: According to the principle of convergence stopping, the iteration can be stopped when the change of the optimal value is less than 1e-3, thus avoiding invalid iterations.

[0075] Scenario 2: If there is no measured data on soil temperature depth, then a layered soil heat conduction temperature model should be established. ;

[0076] In the formula, T(z,t) is the temperature at time t at depth z, z is the cable burial depth in meters (m), and t is the annual cycle time in seconds (s). The average ground temperature of the region, in units

[0077] The annual fluctuation amplitude constant is generally taken as 10~15℃ in temperate regions;

[0078] ω is the annual angular frequency.

[0079] Soil thermal resistivity.

[0080] Soil thermal diffusivity, wherein the soil thermal diffusivity α is assigned a value that varies depending on the soil stratification structure.

[0081] S3: Preferably, the soil temperature at the cable burial depth is obtained by inverting the soil temperature model or the heat conduction temperature model using the artificial bee colony algorithm. .

[0082] S4: Calculate the thermal resistance of the inner insulation shield, insulation layer, outer insulation shield, and outer sheath respectively based on the thermal resistance coefficient of each layer of the cable.

[0083] Figure 1 A cross-sectional view of a typical cable structure is shown, with the following layers labeled: 1. Water-blocking copper conductor; 2. Conductor shield; 3. XLPE insulation; 4. Insulation shield; 5. Semiconductor water-blocking tape; 6. Alloy lead sheath; 7. PE sheath; 8. Optical unit filler; 9. Optical unit; 10. Polypropylene inner lining; 11. Circular copper wire armor and bitumen; 12. Polypropylene outer sheath.

[0084] based on Figure 1 The layered structure shown can be used to obtain the thermal resistance of each layer of the cable using the following formula.

[0085]

[0086] in, , , These represent the thermal resistance of the insulation layer between the conductor and the metal sheath, the thermal resistance of the padding layer between the metal sheath and the armor layer, and the thermal resistance of the cable outer sheath, respectively, in (°C, m / W).

[0087] Thermal resistance of cable insulation layer, inner lining layer, and outer sheath layer; These represent the thermal resistance coefficients of the insulating layer material, the composite structure of the metal sheath and armor layer, and the outer sheath layer, respectively, with units of . ; These correspond to the insulation layer thickness, the total thickness of the metal sheath and armor layer, and the outer sheath layer thickness, respectively, with units of . ; The outer diameters of the metal sheath crests, the equivalent circles of the metal sheath troughs, and the armor layer are respectively defined in units of . .

[0088] S5: Calculate the environmental thermal resistance of the cable according to the burial method. Different calculation methods are used for different laying methods due to the differences in heat transfer medium.

[0089] For direct burial installations, the external thermal resistance is typically approximated by the following formula:

[0090]

[0091] Where T4 is the thermal resistance between the cable surface and the surrounding medium, expressed in °C, m / W. The soil thermal resistivity; The laying depth of the cable centerline; This refers to the outer diameter of the cable's outer sheath.

[0092] For pipeline laying methods (including duct laying and jacking), the external thermal resistance of the cable consists of three parts connected in series: the external medium thermal resistance of the pipeline. Thermal resistance of the air gap inside the pipe and the thermal resistance of the pipe wall itself It can be expressed by the formula:

[0093]

[0094] In the formula, Dpi represents the inner diameter of the pipe, Dc represents the outer diameter of the cable, and Dpo represents the outer diameter of the pipe, all in mm. λg represents the thermal conductivity of air, λp represents the thermal conductivity of the pipe material, and ρs represents the thermal resistance coefficient of the soil, all in W / (m•K). L represents the burial depth of the pipe, in meters.

[0095] S6: Calculate the cable current carrying capacity Ic based on the above parameters, taking into account soil stratification and temperature changes.

[0096] ,

[0097] In the formula, The current carrying capacity of the cable is expressed in units of 1. ; The maximum allowable temperature for cable insulation material is 90℃ for AC cables. The dielectric loss per unit length of the conductor's insulation layer, measured in units of... ; This refers to the number of conductor cores. AC resistance at operating temperature, in units of ; This represents the ratio of metal sheath loss to conductor loss. This represents the ratio of armor loss to conductor loss.

[0098] Through the above steps, the cable current carrying capacity calculation method proposed in this invention can accurately calculate the temperature change at the cable burial depth. At the same time, considering the influence of different soil layers, a cable current carrying capacity calculation method that takes into account soil layering and temperature changes is proposed, which meets the requirements of cable insulation and electric field distribution, ensures the long-term stable operation of the cable, and realizes reliable power transmission.

[0099] Example 2:

[0100] This embodiment provides a computer-readable storage medium, such as a hard disk, flash drive, optical disk, or other non-volatile storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the cable current carrying capacity calculation method considering soil stratification and temperature variation characteristics as described in Embodiment 1.

[0101] Specifically, the computer program includes instruction modules for performing the following steps: a module for acquiring environmental parameters of the power cable laying environment; a module for determining the existence of a measured soil temperature-depth dataset and selectively performing artificial bee colony algorithm inversion or layered soil thermal conduction temperature model calculation to obtain the soil temperature at the cable burial depth based on the determination result; and a module for calculating the cable current carrying capacity based on the thermal resistance of each layer of the cable, the thermal resistance of the laying environment, and the soil temperature.

[0102] Furthermore, the artificial bee colony algorithm inversion module includes sub-modules for initializing nectar sources, searching for hired bees, selecting and searching for follower bees, resetting scout bees, and iteratively outputting optimal parameters.

[0103] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements all the steps of the method described in Embodiment 1.

[0104] This electronic device can be a computer for engineering design, a power grid condition monitoring server, or an embedded analysis terminal. The processor calls a program in memory, receives input cable laying environmental parameters and optional measured temperature datasets, automatically calculates and outputs cable current-carrying capacity results that take into account soil stratification and temperature variation characteristics.

[0105] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for calculating the current-carrying capacity of cables considering soil stratification and temperature variation characteristics, characterized in that, Includes the following steps: To obtain environmental parameters for power cable laying, and depending on the availability of a measured soil temperature-depth dataset, perform the following steps: If a measured dataset exists, the soil temperature model parameters are retrieved using the artificial bee colony algorithm to obtain the soil temperature at the cable burial depth. If no actual measured dataset is available, a layered soil heat conduction temperature model containing soil stratification thermophysical parameters is used to obtain the soil temperature at the cable burial depth. The current carrying capacity of the cable is calculated based on the soil temperature at the cable burial depth, combined with the thermal resistance of each layer of the cable body and the thermal resistance of the laying environment.

2. The method according to claim 1, characterized in that, The soil temperature at the cable burial depth was obtained by inverting soil temperature model parameters using an artificial bee colony algorithm, including: The measured dataset was organized into a standard sample set, which includes multiple sets of soil depths and corresponding measured soil temperatures. Select the soil temperature-depth function model and determine the model parameters to be inverted; Initialize the nectar source population, parameter upper and lower bounds, and algorithm control parameters for the artificial bee colony algorithm, where each nectar source represents a set of model parameters to be inverted; The process iteratively executes steps such as neighbor search for hired bees, probability selection and neighbor search for follower bees, and random reset for scout bees, aiming to minimize the fitting error between the model-calculated temperature and the measured soil temperature, until the maximum number of iterations is reached. The globally optimal nectar source is output as the final inversion model parameter, and the soil temperature at the cable burial depth is obtained using this parameter.

3. The method according to claim 2, characterized in that, The soil temperature-depth function model is an exponential decay model, as follows: ， Among them, the dataset to be determined T(z,t) represents the soil temperature at depth z at time t, in °C. s λ represents the deep steady-state geothermal temperature in °C; A0 represents the annual fluctuation amplitude constant in °C; and λ represents the temperature decay characteristic constant.

4. The method according to claim 2, characterized in that, The fitting error is the mean squared error, and the fitness value in the artificial bee colony algorithm is inversely proportional to the mean squared error.

5. The method according to claim 1, characterized in that, The stratified soil thermal conduction temperature model is as follows: ； In the formula, T(z,t) is the temperature at time t at depth z, and z is the cable burial depth in meters. t represents the time in the annual cycle, expressed in seconds (s). The average ground temperature of the region, in units ; ω is the annual fluctuation amplitude constant; ω is the annual periodic angular frequency. ; The soil thermal resistivity; The soil thermal diffusivity is a value that is differentiated based on the soil stratification structure.

6. The method according to claim 1, characterized in that, The formula for calculating the current carrying capacity of a cable is as follows: ， In the formula, The current carrying capacity of the cable is expressed in units of 1. ; The maximum allowable temperature for cable insulation material is 90℃ for AC cables; The dielectric loss per unit length of the conductor's insulation layer, measured in units of... ; This refers to the number of conductor cores. AC resistance at operating temperature, in units of ; This represents the ratio of metal sheath loss to conductor loss. T1 is the ratio of armor loss to conductor loss; T2 is the thermal resistance of the insulation layer between the conductor and the metal sheath; T3 is the thermal resistance of the padding layer between the metal sheath and the armor layer; T4 is the thermal resistance between the cable outer sheath and the surrounding medium.

7. The method according to claim 6, characterized in that, When the cable is laid in a conduit, the thermal resistance between the cable surface and the surrounding medium is composed of three parts connected in series: the thermal resistance of the medium outside the conduit, the thermal resistance of the air gap inside the conduit, and the thermal resistance of the conduit wall itself.

8. The method according to claim 1, characterized in that, The environmental parameters for laying power cables include cable burial depth, average ground temperature of the area, soil thermal resistivity, and soil thermal diffusivity.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method according to any one of claims 1 to 8.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method according to any one of claims 1 to 8.

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