Cable hot spot temperature identification method and device, terminal equipment and storage medium

Abstract

The invention discloses a cable hot-spot temperature identification method and device, terminal equipment and a storage medium. The method comprises the following steps: acquiring a steady-state temperature field reduced-order model, a cable surface temperature monitoring value and a ground surface temperature monitoring value of a power distribution network cable; obtaining an initial equivalent current based on a preset parameter space; taking the initial equivalent current as input, repeatedly executing an equivalent current iteration adjustment operation through a cable surface temperature monitoring value and a steady-state temperature field reduced-order model, stopping executing the equivalent current iteration adjustment operation when residual data is smaller than a residual threshold or the number of iterations is equal to an iteration threshold, and outputting a final iteration equivalent current; and inputting the iterative equivalent current and the surface temperature monitoring value into the steady-state temperature field reduced-order model to obtain a cable internal transient temperature field reconstruction result of the power distribution network cable. According to the invention, cable current changing in real time does not need to be monitored, the internal temperature field of the cable can be reconstructed only by monitoring the surface temperature of the cable, and the simulation accuracy of the cable temperature field is improved.

Description

Technical Field

[0001] The present invention relates to the field of simulation technology, and particularly to a method, device, terminal device and storage medium for identifying the hot spot temperature of a cable. Background Art

[0002] The three-core cross-linked polyethylene (XLPE) power cable is an important part of the urban 10 kV distribution network. Under the background of building a new power system, the digitalization of cable lines is an important guarantee for the urban distribution network to achieve rapid and accurate state assessment and safe and stable operation. The digital twin model can map the real state of physical devices in real time and quickly predict the state of physical devices in specific operating scenarios, so as to realize accurate and real-time device state assessment, which is one of the most concerned research directions in the field of digitalization of power equipment in recent years. Based on cutting-edge information technology, the digital twin model can map the full life cycle state of physical devices in real time through the interaction between virtual and real, and improve the operation efficiency of the industry, and its application in the digitalization and intelligent development of the power industry is becoming more and more extensive.

[0003] The material parameters, geometric structure and laying method of the distribution network cable are basically unchanged, but the load current is in real-time change, resulting in the difficulty of the traditional simulation calculation results to truly map the transient temperature field inside the cable at the current moment. Therefore, there is a problem of low accuracy in identifying the hot spot temperature of the cable temperature field.

[0004] Therefore, there is an urgent need for a strategy for identifying the hot spot temperature of a cable to solve the problem of low accuracy in the simulation of the cable temperature field. Summary of the Invention

[0005] Embodiments of the present invention provide a method, device, terminal device and storage medium for identifying the hot spot temperature of a cable to solve the problem of low accuracy in the simulation of the cable temperature field.

[0006] To solve the above problems, an embodiment of the present invention provides a method for identifying the hot spot temperature of a cable, including:

[0007] Obtain the reduced-order model of the steady-state temperature field of the distribution network cable, the measured value of the cable surface temperature and the measured value of the ground surface temperature; wherein, the measured value of the cable surface temperature is obtained by compensating the acquisition value of the temperature sensor for the thermal time constant;

[0008] Based on a preset parameter space, obtain an initial equivalent current;

[0009] Take the initial equivalent current as the input, and repeatedly perform the equivalent current iterative adjustment operation through the measured value of the cable surface temperature and the reduced-order model of the steady-state temperature field. When the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, stop performing the equivalent current iterative adjustment operation and output the final iterative equivalent current;

[0010] Input the iterative equivalent current and the monitored surface temperature value into the reduced-order model of the steady-state temperature field to obtain the reconstructed result of the transient temperature field inside the cable of the distribution network.

[0011] As an improvement to the above solution, the equivalent current iterative adjustment operation includes:

[0012] Input the current input and the monitored cable surface temperature value into the reduced-order model of the steady-state temperature field to obtain the calculated cable surface temperature value;

[0013] Substitute the monitored cable surface temperature value and the calculated cable surface temperature value into the cable heat transfer objective function to obtain the residual data;

[0014] Judge the residual data and the number of iterations;

[0015] If the residual data is greater than or equal to the residual threshold and the number of iterations is less than the iteration threshold, calculate the current input by the secant method to obtain the iterative equivalent current, and perform the next equivalent current iterative adjustment operation based on the iterative equivalent current;

[0016] If the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, stop performing the equivalent current iterative adjustment operation and output the final iterative equivalent current.

[0017] As an improvement to the above solution, the cable heat transfer objective function satisfies the following conditions:

[0018]

[0019] In the formula, is the equivalent current is the calculated surface temperature value of the i-th cable output by the reduced-order model of the steady-state temperature field under the action of the equivalent current; is the monitored surface temperature value of the i-th cable.

[0020] As an improvement to the above solution, the acquisition value of the temperature sensor is compensated for the thermal time constant to obtain the monitored cable surface temperature value, including:

[0021] Obtain the location and acquisition value of the temperature sensor;

[0022] Determine the cable surface temperature rise data based on the location;

[0023] Determine the time-domain difference equation based on the cable surface temperature rise data and the preset expression of the time constant compensation link;

[0024] Substitute the acquisition value into the time-domain difference equation to obtain the monitored cable surface temperature value.

[0025] As an improvement to the above solution, the obtaining of the reduced-order model of the steady-state temperature field of the distribution network cable includes:

[0026] Obtain the basic physical parameters of the distribution network cable;

[0027] Construct a full-order finite element model of the distribution network cable according to the basic physical parameters;

[0028] Randomly extract in the parameter space through a preset sampling method to obtain a number of input parameter column vectors; wherein, the input parameter column vector is the cable load current;

[0029] Substitute each parameter matrix into the full-order finite element model for solution, obtain the node temperature column vector corresponding to each parameter matrix, and combine all the node temperature column vectors into a snapshot matrix;

[0030] According to the snapshot matrix, obtain the reduced-order model of the steady-state temperature field through singular value decomposition.

[0031] As an improvement to the above solution, the obtaining of the reduced-order model of the steady-state temperature field according to the snapshot matrix through singular value decomposition includes:

[0032] Perform singular value decomposition on the snapshot matrix to obtain a number of left singular vectors;

[0033] Select a target left singular vector from the number of left singular vectors;

[0034] Based on the target left singular vector, construct a linear combination of left singular vectors corresponding to each node temperature column vector in the snapshot matrix, and summarize each linear combination of left singular vectors into a reduced-order modal reconstruction matrix; wherein, the linear combination of left singular vectors is the product of each target left singular vector and an unknown linear combination coefficient;

[0035] Based on the preset constraint conditions and the snapshot matrix, solve the unknown linear combination coefficients corresponding to each linear combination of left singular vectors to obtain the target linear combination coefficients corresponding to each linear combination of left singular vectors;

[0036] According to each target linear combination coefficient, fit the response surface function of the linear combination coefficient;

[0037] According to the response surface function and the target left singular vector, obtain the reduced-order model of the steady-state temperature field; wherein, the reduced-order model of the steady-state temperature field satisfies the following conditions:

[0038]

[0039] In the formula, ψ rei is the reduced-order model of the steady-state temperature field, is the linear combination coefficient, ui is the target left singular vector, and f i (ξ) is the response surface function, ξ is the equivalent current, and r is the number of modes; among them, the equivalent current includes: the initial equivalent current and the iterative equivalent current.

[0040] As an improvement of the above solution, the constraint condition satisfies the following conditions:

[0041]

[0042] In the formula, χ is the truncation error, M is the snapshot matrix, and M re is the reduced-order mode reconstruction matrix, σ i is the singular value of M, and |||| is the Frobenius norm.

[0043] Correspondingly, an embodiment of the present invention further provides a cable hot spot temperature identification device, including: a data acquisition module, a current acquisition module, an iteration module, and a temperature field reduction module;

[0044] The data acquisition module is used to acquire the reduced-order model of the steady-state temperature field of the distribution network cable, the cable surface temperature monitoring value, and the ground surface temperature monitoring value;

[0045] The current acquisition module is used to obtain the initial equivalent current based on the preset parameter space;

[0046] The iteration module is used to use the initial equivalent current as the input, and repeatedly perform the equivalent current iteration adjustment operation through the cable surface temperature monitoring value and the steady-state temperature field reduction model. When the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, stop performing the equivalent current iteration adjustment operation and output the final iterative equivalent current;

[0047] The temperature field reduction module is used to input the iterative equivalent current and the ground surface temperature monitoring value into the steady-state temperature field reduction model to obtain the reconstruction result of the internal transient temperature field of the distribution network cable.

[0048] Correspondingly, an embodiment of the present invention further provides a computer terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a cable hot spot temperature identification method as described in the present invention.

[0049] Correspondingly, an embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute a cable hot spot temperature identification method as described in the present invention.

[0050] As can be seen from the above, the present invention has the following beneficial effects:

[0051] The present invention provides a method for identifying the hot spot temperature of a cable, which obtains a reduced-order model of the steady-state temperature field of a distribution network cable, the monitored value of the cable surface temperature, and the monitored value of the ground surface temperature; based on a preset parameter space, an initial equivalent current is obtained; taking the initial equivalent current as an input, the equivalent current iterative adjustment operation is repeatedly executed through the monitored value of the cable surface temperature and the reduced-order model of the steady-state temperature field. When the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, the equivalent current iterative adjustment operation is stopped, and the final iterative equivalent current is output; the iterative equivalent current and the monitored value of the ground surface temperature are input into the reduced-order model of the steady-state temperature field to obtain the reconstruction result of the transient temperature field inside the distribution network cable. By generating the initial equivalent current through the parameter space, the present invention does not need to monitor the current of the distribution network cable, and based on the reduced-order model of the steady-state temperature field and the monitored value of the cable surface temperature obtained by monitoring, the iteration of the initial equivalent current is carried out, so as to obtain the iterative equivalent current of the current monitored value of the cable surface of the load, and further, the reconstruction result of the transient temperature field inside the cable can be obtained by substituting the iterative equivalent current and the monitored value of the meter temperature into the reduced-order model of the steady-state temperature field. The present invention does not need to monitor the real-time changing cable current, and only needs to monitor the surface temperature of each loop cable to reconstruct the internal temperature field of the cable, improving the simulation accuracy of the cable temperature field. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 is a schematic flow chart of a method for identifying the hot spot temperature of a cable provided by an embodiment of the present invention;

[0053] Figure 2 is a schematic structural diagram of a device for identifying the hot spot temperature of a cable provided by an embodiment of the present invention;

[0054] Figure 3 is a schematic structural diagram of a terminal device provided by an embodiment of the present invention;

[0055] Figure 4 is a schematic flow chart of modeling a reduced-order model of a steady-state temperature field provided by an embodiment of the present invention;

[0056] Figure 5 is a schematic flow chart of real-time reconstruction of a transient temperature field inside a cable provided by an embodiment of the present invention;

[0057] Figure 6 is a schematic simplified longitudinal cross-sectional view of a 10kV cable line provided by an embodiment of the present invention;

[0058] Figure 7 is a schematic simplified transverse cross-sectional view of a 10kV cable line provided by an embodiment of the present invention;

[0059] Figure 8It is the cable finite element simulation model after the geometric model simplification provided by an embodiment of the present invention;

[0060] Figure 9 It is the calculation grid of the 11.7m line module provided by an embodiment of the present invention;

[0061] Figure 10 It is the geometric parameters of the transverse cross-section of the model provided by an embodiment of the present invention;

[0062] Figure 11 It is the comparison of the calculation results of the full-order model and the reduced-order model provided by an embodiment of the present invention;

[0063] Figure 12 It is the cable surface temperature monitoring system provided by an embodiment of the present invention;

[0064] Figure 13 It is the real-time reconstruction result of the internal transient temperature field of the 11.7m line module cable provided by an embodiment of the present invention;

[0065] Figure 14 It is the real-time reconstruction result of the 11.7m line module and the simulation result of the full-order model provided by an embodiment of the present invention. Specific embodiments

[0066] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0067] Embodiment 1

[0068] Refer to Figure 1 , Figure 1 It is a schematic flow chart of a method for identifying the hot spot temperature of a cable provided by an embodiment of the present invention. As Figure 1 shown, this embodiment includes steps 101 to 104, and the specific steps are as follows:

[0069] Step 101: Obtain the reduced-order model of the steady-state temperature field of the distribution network cable, the cable surface temperature monitoring value, and the ground surface temperature monitoring value; among them, the thermal time constant compensation is performed on the collected value of the temperature sensor to obtain the cable surface temperature monitoring value.

[0070] In this embodiment, the obtaining of the reduced-order model of the steady-state temperature field of the distribution network cable includes:

[0071] Obtain the basic physical parameters of the distribution network cable;

[0072] Construct a full-order finite element model of the distribution network cable according to the basic physical parameters;

[0073] Randomly extract in the parameter space through a preset sampling method to obtain a number of input parameter column vectors; wherein, the input parameter column vector is the cable load current;

[0074] Substitute each parameter matrix into the full-order finite element model for solution to obtain a node temperature column vector corresponding to each parameter matrix, and combine all the node temperature column vectors into a snapshot matrix;

[0075] According to the snapshot matrix, obtain the reduced-order model of the steady-state temperature field through singular value decomposition.

[0076] In a specific embodiment, according to the basic parameters of the 10kV cable (i.e., the distribution network cable described in the present invention) and its laying environment (i.e., the basic physical parameters described in the present invention), establish a full-order finite element model for cable multi-physical field coupling simulation.

[0077] It can be understood that a full-order finite element model for three-dimensional magnetic-thermal-fluid multi-physical field coupling simulation is established according to the cable structure, laying method, surrounding environmental conditions and their parameters.

[0078] In this embodiment, the obtaining of the reduced-order model of the steady-state temperature field through singular value decomposition according to the snapshot matrix includes:

[0079] Perform singular value decomposition on the snapshot matrix to obtain a number of left singular vectors;

[0080] Select a target left singular vector from the number of left singular vectors;

[0081] Based on the target left singular vector, construct a linear combination of left singular vectors corresponding to each node temperature column vector in the snapshot matrix, and summarize each linear combination of left singular vectors into a reduced-order modal reconstruction matrix; wherein, the linear combination of left singular vectors is the product of each target left singular vector and an unknown linear combination coefficient;

[0082] Based on the preset constraint conditions and the snapshot matrix, solve the unknown linear combination coefficients corresponding to each linear combination of left singular vectors to obtain the target linear combination coefficients corresponding to each linear combination of left singular vectors;

[0083] According to each target linear combination coefficient, fit the response surface function of the linear combination coefficient;

[0084] According to the response surface function and the target left singular vector, obtain the reduced-order model of the steady-state temperature field; wherein, the reduced-order model of the steady-state temperature field satisfies the following conditions:

[0085]

[0086] In the formula, ψ rei is the reduced-order model of the steady-state temperature field, is the linear combination coefficient, u i is the target left singular vector, f i (ξ) is the response surface function, ξ is the equivalent current, r is the number of modes; among them, the equivalent current includes: the initial equivalent current and the iterative equivalent current.

[0087] In this embodiment, the constraint conditions satisfy the following conditions:

[0088]

[0089] In the formula, χ is the truncation error, M is the snapshot matrix, M re is the reduced-order mode reconstruction matrix, σ i is the singular value of M, |||| is the Frobenius norm.

[0090] In a specific embodiment, based on the finite element model of the cable multi-physical field coupling simulation, a reduced-order model of the steady-state temperature field of a 10 kV cable is established for the pre-given parameter space.

[0091] In a specific embodiment, the acquisition of the reduced-order model of the steady-state temperature field is specifically as follows:

[0092] S1. Randomly extract m input parameter column vectors ξ in the parameter space X by using the Latin hypercube sampling method to form the input parameter matrix I = [ξ1, ξ2,..., ξ m . After solving the finite element full-order model m times, extract the grid node temperature values of each calculation result to form the node temperature column vector ψ, and combine the obtained m node temperature column vectors ψ into the snapshot matrix M = [ψ1, ψ2,..., ψ m .

[0093] S2. Perform singular value decomposition on the snapshot matrix M:

[0094] M = UΣ σ V T

[0095] In the formula, U and V are the left singular matrix and the right singular matrix of n×n respectively, Σ σ = diag(σ1, σ2,..., σ m , 0,..., 0) is an n×m diagonal matrix composed of the singular values of the matrix M, and each singular value is stored in descending order: σ1≥σ2≥...≥σ m ≥0. Generally, n >> m, and there are only m non-zero singular values. Therefore, it can be considered that the rank of the singular value matrix Σ σ is at most m.

[0096] S3. According to the mathematical properties of singular value decomposition, by intercepting the first r left singular vectors u i , i = 1, …, r (r ≤ m) as the reduced-order modes, any node temperature column vector ψ in the snapshot matrix M p can be approximated as a linear combination of u i :

[0097]

[0098] where α p,i is the linear combination coefficient, p = 1, …, m, i = 1, …, r (r ≤ m), and r is the number of modes.

[0099] The matrix M reconstructed by the reduced-order modes re is approximately equivalent to the snapshot matrix M, and the satisfied constraint condition is:

[0100]

[0101] where χ is the truncation error of the reduced-order model; |||| is the Frobenius norm; σ i is the singular value of M.

[0102] Among them, the smaller the value of the number of modes r, the better the data compression effect of the steady-state temperature field reduced-order model, and the less computational time and computational resources required to evaluate the reduced-order model.

[0103] S4. On the premise that u i has been solved, for the problem of solving any field solution Y = [ψ1, ψ2, …] in the parameter space, it is simplified to the solution of α i . The response surface interpolation method fits the mapping relationship (i.e., the response surface function) between the response variable and multiple independent variables through interpolation methods such as polynomial regression and least squares. Since the non-linear steady-state field solution is unique

[70] , there is a single mapping relationship between α i and ξ. The response surface function of α p,i can be fitted with α i as the sample data in the parameter space X and the field solution space Y re = [ψ re1 , ψ re2 , …] is reconstructed:

[0104]

[0105] S5. Finally, based on the interpolation response surface the node temperature column vector ψ corresponding to any input parameter column vector ξ can be quickly solved, realizing the reduced-order calculation of the steady-state temperature field.

[0106] It should be noted that the acquisition of the reduced-order model of the steady-state temperature field can be referred to Figure 4 .

[0107] In a specific embodiment, the idea of obtaining the cable heat transfer objective function is as follows: construct the inverse heat transfer problem of a multi-circuit cable, and verify whether the position of the temperature measurement point satisfies the constraints of the inverse problem. If not, it is necessary to compensate the temperature measurement data by combining the thermal time constant compensation measures; specifically, refer to the following steps:

[0108] S1. When n cable surface temperatures T surf are measured and satisfy the cable conductor thermal time constant ≥ cable surface thermal time constant , the transient temperature calculation problem of the interaction of n independent electromagnetic heat sources can be transformed into the steady-state response of n equivalent currents I eq corresponding to each independent electromagnetic heat source under discrete conditions. Therefore, only by solving the equivalent current I surf through the surface temperature T eq , the transient temperature field inside the multi-circuit cable can be reconstructed.

[0109] S2. The inverse problem of the equivalent current of the n-circuit cable can be defined as the following objective function:

[0110]

[0111] In the formula, is the calculated value of the surface temperature of the i-th cable output by the reduced-order model under the action of the equivalent current , °C; is the monitored value of the surface temperature of the i-th cable, °C.

[0112] S3. The well-posedness condition of the inverse heat transfer problem of the multi-circuit cable is that the cable conductor thermal time constant ≥ cable surface thermal time constant When the constraint condition for real-time reconstruction is not satisfied, that is, τ con <τ surf , the monitored value of the cable surface temperature rise is used as the input x(k) of the thermal time constant compensation link, and the output y(k) is the monitored value of the cable surface temperature rise that satisfies the constraint condition. The time-domain difference equation of the thermal time constant compensation link is:

[0113]

[0114] In the formula, T s is the sampling time, and T s = 900 s according to the data acquisition time of the temperature sensor.

[0115] In this embodiment, compensating the acquisition value of the temperature sensor for the thermal time constant to obtain the cable surface temperature monitoring value includes:

[0116] Obtaining the location and acquisition value of the temperature sensor;

[0117] Based on the location, determining the cable surface temperature rise data;

[0118] Based on the cable surface temperature rise data and the preset time constant compensation link expression, determining the time-domain difference equation;

[0119] Substituting the acquisition value into the time-domain difference equation to obtain the cable surface temperature monitoring value.

[0120] In a specific embodiment, based on the cable surface temperature rise data and the preset time constant compensation link expression, determining the time-domain difference equation is specifically:

[0121] The expression of the cable surface temperature rise data ΔT surf (t) is:

[0122]

[0123] In the formula, τ sur f is the equivalent thermal time constant of the surface temperature monitoring position; Rth am is the equivalent thermal resistance of the surrounding medium, (m 2 ·K) / W; Q(t) is the electromagnetic heat source inside the cable that changes with time;

[0124] Performing Laplace transform on the expression to obtain the s-domain expression:

[0125]

[0126] Assuming that the equivalent thermal time constant of the real-time reconstruction target position is τ con , then after introducing the thermal time constant compensation link H(s), it should satisfy:

[0127]

[0128] After sorting, the s-domain expression of the thermal time constant compensation link H(s) can be obtained:

[0129]

[0130] It is not difficult to find that the thermal time constant compensation link H(s) is actually a lead-lag compensator with a lead time constant of τ surf and a lag time constant of τ con . Its discretized expression after Z-transform is:

[0131]

[0132] In the formula, T s is the sampling time, and T is taken according to the data acquisition time of the temperature sensor s = 900 s, then the time-domain difference equation of the thermal time constant compensation link is:

[0133]

[0134] In the formula, x(k) and y(k) are respectively the input (i.e., the acquisition value of the temperature sensor described in the present invention) and output (i.e., the cable surface temperature monitoring value described in the present invention) of the thermal time constant compensation link at the k-th time step.

[0135] In summary, when the constraint condition of real-time reconstruction is not satisfied, that is, τ con < τ surf , the cable surface temperature rise monitoring value is used as the input x(k) of the thermal time constant compensation link, and the output y(k) is the cable surface temperature rise monitoring value that meets the constraint conditions.

[0136] To better illustrate the effect of the thermal time constant compensation of the present application, the following case is given:

[0137] First, the step temperature rise curves of different axial length line modules are obtained through finite element FOM simulation. According to the physical definition of the thermal time constant, the moment corresponding to 0.632 times the steady-state temperature rise is the value of the first-order equivalent thermal time constant. Taking the initial current as 100 A and the step current as 600 A, the thermal time constants of the cable surface at 0.1 m from the edge of the pipe (the position where the temperature measurement sensor is arranged) and the cable conductor in the middle of the pipe with different axial lengths L are fitted as shown in Table 1.

[0138] Table 1

[0139]

[0140] Analysis shows that the thermal time constant of the cable A surface position at the edge of the pipe of the 4 m line module is greater than that of the cable conductor position in the middle of the pipe, which does not meet the constraint conditions of real-time reconstruction, but cable B always meets the constraint conditions. As the axial length L increases, the thermal time constants of the cable surface at the edge of the pipe and the cable conductor in the middle of the pipe of cable A are stabilized at 290 min and 410 min respectively. Then, for line modules with an axial length greater than 6.1 m, the cable surface at 0.1 m from the edge of the pipe can be selected as the monitoring point for reconstructing the temperature of the cable conductor in the middle of the pipe. At the same time, it can be seen from Table 1 that as the axial length L decreases, the thermal time constant of the cable surface at 0.1 m from the edge of the pipe no longer meets the constraint conditions of real-time reconstruction.

[0141] Step 102: Obtain the initial equivalent current based on the preset parameter space.

[0142] In this embodiment, the parameter space X refers to the input parameters and their upper and lower limits of the 10 kV cable three-dimensional magnetic-thermal-fluid coupling field finite element simulation model established in step S1, generally including the load currents I1 to I of n circuits of cables n , the surface temperature T ground , and they form an input parameter column vector

[0143] Step 103: Using the initial equivalent current as the input, repeatedly perform the equivalent current iterative adjustment operation through the cable surface temperature monitoring value and the steady-state temperature field reduced-order model. When the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, stop performing the equivalent current iterative adjustment operation and output the final iterative equivalent current.

[0144] In this embodiment, the equivalent current iterative adjustment operation includes:

[0145] Input the current input and the cable surface temperature monitoring value into the steady-state temperature field reduced-order model to obtain the calculated value of the cable surface temperature;

[0146] Substitute the cable surface temperature monitoring value and the calculated value of the cable surface temperature into the cable heat transfer objective function to obtain the residual data;

[0147] Judge the residual data and the number of iterations;

[0148] If the residual data is greater than or equal to the residual threshold and the number of iterations is less than the iteration threshold, calculate the current input by the secant method to obtain the iterative equivalent current, and perform the next equivalent current iterative adjustment operation based on the iterative equivalent current;

[0149] If the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, stop performing the equivalent current iterative adjustment operation and output the final iterative equivalent current.

[0150] In this embodiment, the cable heat transfer objective function satisfies the following conditions:

[0151]

[0152] In the formula, is the equivalent current is the calculated value of the surface temperature of the i-th cable output by the steady-state temperature field reduced-order model under the action of is the monitoring value of the surface temperature of the i-th cable.

[0153] In this embodiment, the secant method satisfies the following conditions:

[0154]

[0155] In the formula, Represents the equivalent current of the i-th cable under the k-th iteration.

[0156] In a specific embodiment, the reconstruction of the internal temperature field of the cable is specifically as follows:

[0157] S1. Obtain the surface temperature and the monitored value of the cable surface temperature through the sensors pre-laid on site, and initialize the equivalent current and model parameters according to the input parameter space X.

[0158] S2. Continuously adjust and iterate the equivalent current of each loop of the cable based on the secant method or the optimization algorithm. Calculate the calculated value of the cable surface temperature corresponding to the equivalent current of each loop of the cable under the k-th iteration through the steady-state temperature field reduced-order model, and calculate the objective function in combination with the monitored value of the cable surface temperature. The formula of the secant method is:

[0159]

[0160] In the formula, Represents the equivalent current of the i-th cable under the k-th iteration.

[0161] S3. Determine whether the objective function reaches the convergence condition. In this study, the convergence condition is taken as the residual being less than 0.05 or the number of iterations exceeding the limit. If the objective function does not converge, return to step S42 until the residual is less than 0.05 or the number of iterations exceeds the limit.

[0162] S4. If the objective function reaches the convergence condition, substitute the identified value of the equivalent current of each loop of the cable and the monitored value of the surface temperature into the steady-state temperature field reduced-order model (i.e., output the calculation result of the last reduced-order model) to obtain the reconstruction result of the internal transient temperature field of the cable at the current moment.

[0163] It should be noted that for the real-time reconstruction of the internal transient temperature field of the cable, refer to Figure 5 .

[0164] Step 104: Input the iterative equivalent current and the monitored value of the surface temperature into the steady-state temperature field reduced-order model to obtain the reconstruction result of the internal transient temperature field of the cable of the distribution network.

[0165] In a specific embodiment, refer to Figure 5 , Figure 13 , Figure 14 . Among them, Figure 5 Is the calculation process of the reconstruction result of the internal transient temperature field of the cable. The parameter position of the monitored value of the surface temperature is T ground , and in the calculation results Figure 13 , 14 , the actually used long-term monitored surface temperature is T ground MEAThe sensor is arranged on a tree near the ground surface, and the average temperature of the day is taken. This value remains constant during the calculation process. Additionally, Figure 14 The reconstructed results of the equivalent current input to each circuit and the cable temperature at each moment are given, and the ground surface temperature is 27 °C.

[0166] It should be noted that in this step, the input of the steady-state temperature field reduction model is the currents I A 、I B 、I other of cables A, B and other cables, which are the variables of the reconstruction algorithm; T ground and L are the ground surface temperature and the axial length, which are the fixed values of the reconstruction algorithm. The function of the steady-state reduction model is to take the cable current, the ground surface temperature, and the axial length as inputs and output the steady-state temperature field of the cable. Since the reduction model has a fast calculation speed, the reconstruction algorithm can continuously adjust and iterate the current input of the cable group within a short time to find the set of equivalent current values equivalent to the transient temperature field at the current moment. During this process, the ground surface temperature and the axial length are fixed values.

[0167] In a specific embodiment, please refer to the following case:

[0168] S1. According to the basic parameters of the 10 kV cable and its laying environment, establish a finite element full-order model for the multi-physical field coupling simulation of the cable;

[0169] In this case, a certain section of the actual operating 10 kV distribution network cable line is taken as the research object. This line has a total of 6 YJV22 - 8.7 / 15 - 3×300 mm 2 cables, with a total length of 177.6 m and a total of 11 cable wells, as shown in Figure 6 、 7 . Since the symmetry plane in the thermal field is the adiabatic surface and there is no axial heat flow passing through, the local line between adjacent symmetry planes can be independently evaluated, and the geometric model can be further simplified as shown in Figure 8 , the divided calculation grid as shown in Figure 9 and the geometric parameters of the transverse cross-section of the model as shown in Figure 10 . By solving the mathematical model of the magnetic-thermal flow coupling field at the discretized grid nodes, the temperature field distribution output can be solved with the load current of each circuit cable and the ground surface temperature as inputs.

[0170] The input parameters φ of the cable finite element simulation model in this case include the heavy-load cable currents I A and I B , the light-load cable current I other , the ground surface temperature T ground and the axial length L of the model, which form the input parameter column vector ξ = [φ1, φ2, …, φ N T ​, the number of input parameters is N. The output of the module is the node temperature of the steady-state temperature field inside the cable. The column vector of node temperatures formed The number of nodes is n. For any ξ within the range of input parameters, the input parameter space X = [ξ1, ξ2, …] is formed as shown in Table 2, and the corresponding output steady-state field solution space is Y = [ψ1, ψ2, …]. If the mapping relationship between X and Y is determined, the output ψ corresponding to the input ξ can be obtained quickly.

[0171] Table 2

[0172]

[0173] S2. Based on the finite element model of the cable multi-physical field coupling simulation, establish a reduced-order model of the 10kV cable steady-state temperature field for the pre-given input parameter space;

[0174] Take the axial length L = 11.7m, apply a continuous current of 300A to the heavy-load cables A and B, and apply a continuous current of 200A to the surrounding light-load cables. Use the finite element full-order model and the reduced-order model (r = 20) to calculate the distribution of the steady-state temperature field inside the cable, and the results are as Figure 11 shown. The results show that the calculation results of the reduced-order model are basically consistent with those of the full-order model, and the maximum error is 0.42°C.

[0175] S3. Construct a multi-loop cable heat transfer inverse problem to verify whether the position of the temperature measurement point satisfies the constraints of the inverse problem. If not, it is necessary to compensate the temperature measurement data in combination with the thermal time constant compensation measures;

[0176] In this case, an integrated temperature measurement system is used to build a cable surface temperature monitoring system, which mainly consists of a wireless temperature measurement integrated machine, a wireless intelligent base station, and an Internet of Things platform, as Figure 12 shown.

[0177] Considering the humid environment in the cable shaft and the high equipment maintenance cost, the temperature measurement integrated machine is powered by batteries and has a waterproof and airtight shell, and uses a PT1000 temperature measurement cable to monitor the cable surface temperature data. In order to reduce power consumption and extend the service life, the temperature measurement integrated machine is set to send data to the nearest wireless intelligent base station every 15 minutes. The wireless intelligent base station is installed in a nearby switch station and powered by a distribution box, and uploads the temperature data to the Internet of Things platform through the 4G network.

[0178] The local hot spots of the actually operating 10 kV cable line are generally located in the middle position of the pipe rack with the worst heat dissipation conditions. Therefore, for different axial length line modules, the reconstructed target position is the middle position of the pipe rack. When calculating the temperature of the conductor in the middle of the pipe rack by the real-time reconstruction method on the actually operating 10 kV cable line, it is necessary to first select the temperature measurement positions that meet the constraint conditions, that is, it is necessary to ensure that the thermal time constant of the thermocouple installation position is not greater than the position of the cable conductor in the middle of the pipe rack.

[0179] In this embodiment, first, the stepwise temperature rise curves of different axial length line modules are obtained by finite element full-order model simulation. According to the physical definition of the thermal time constant, the moment corresponding to 0.632 times the steady-state temperature rise is the value of the first-order equivalent thermal time constant. Taking the initial current as 100 A and the step current as 600 A, the thermal time constants of the cable surface at 0.1 m from the edge of the pipe rack (the position where the temperature measurement sensor is arranged) and the cable conductor in the middle of the pipe rack with different axial lengths L are fitted as shown in Table 3.

[0180] Table 3

[0181]

[0182] Analysis shows that the thermal time constant of the cable A surface position at the edge of the pipe rack of the 4 m line module is greater than the position of the cable conductor in the middle of the pipe rack, which does not meet the constraint conditions of real-time reconstruction, but cable B always meets the constraint conditions. As the axial length L increases, the thermal time constants of the cable surface at the edge of the pipe rack and the cable conductor in the middle of the pipe rack of cable A are stabilized at 290 min and 410 min respectively. Then, for line modules with an axial length greater than 6.1 m, the cable surface at 0.1 m from the edge of the pipe rack can be selected as the monitoring point for reconstructing the temperature of the cable conductor in the middle of the pipe rack. At the same time, it can be seen from Table 3 that as the axial length L decreases, the thermal time constant of the cable surface at 0.1 m from the edge of the pipe rack no longer meets the constraint conditions of real-time reconstruction.

[0183] S4. Combine the steady-state temperature field reduced-order model with the cable surface temperature data, and solve the inverse heat transfer problem of the multi-circuit cable to reconstruct the internal transient temperature field of the cable in real time when the cable surface temperature is known and the load current is unknown;

[0184] In this embodiment, the maximum load day data of the monitored cable line in August is selected as the research object, and the surface temperature is taken as the measured average value of 30 °C on that day. Since the surrounding cable current I other is relatively low and the fluctuation is small, in this calculation example, the measured value of I other is taken as the equivalent current, and only the equivalent currents of cables A and B are identified. Taking the reconstruction process of the line module with L = 11.7 m as an example, the surface temperature measurement data of cables A and B at 0.1 m from the edge of the pipe rack collected by the Internet of Things platform are substituted into the real-time reconstruction algorithm, and the internal transient temperature field of the 11.7 m line module cable at some moments is reconstructed asFigure 13 as shown

[0185] Take the conductor temperature in the middle of the cable ducts of cables A and B as the reconstruction target value and compare it with the full-order simulation value of the finite element as Figure 14 shown. The results show that the reconstructed values of the conductor temperatures in the middle of the cable ducts of cables A and B are in good agreement with the curves of the full-order simulation values, and the maximum absolute errors are 0.47°C and 0.84°C respectively, and the maximum relative errors are 1.10% and 1.76% respectively. During this reconstruction process, it takes about 20 steady-state temperature field calculations on average for the real-time reconstruction algorithm to converge. Using the steady-state finite element full-order model to reconstruct the transient temperature field of the cable takes about 80h on average, while the single reconstruction calculation time of this method on a 16-core workstation is 8.1s, and the calculation efficiency is increased by 35555 times.

[0186] See Figure 2 , Figure 2 which is a schematic structural diagram of a cable hot spot temperature identification device provided by an embodiment of the present invention, including: a data acquisition module 201, a current acquisition module 202, an iteration module 203, and a temperature field reduction module 204;

[0187] The data acquisition module is used to acquire the steady-state temperature field reduction model of the distribution network cable, the cable surface temperature monitoring value, and the ground surface temperature monitoring value;

[0188] The current acquisition module is used to obtain an initial equivalent current based on a preset parameter space;

[0189] The iteration module is used to take the initial equivalent current as an input, and repeatedly perform an equivalent current iteration adjustment operation through the cable surface temperature monitoring value and the steady-state temperature field reduction model. When the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, stop performing the equivalent current iteration adjustment operation, and output the final iterative equivalent current;

[0190] The temperature field reduction module is used to input the iterative equivalent current and the ground surface temperature monitoring value into the steady-state temperature field reduction model to obtain the reconstruction result of the internal transient temperature field of the distribution network cable.

[0191] It can be understood that the above system item embodiments correspond to the method item embodiments of the present invention, and can implement the cable hot spot temperature identification method provided by any one of the above method item embodiments of the present invention.

[0192] In this embodiment, a reduced-order model of the steady-state temperature field of the distribution network cable, the monitored value of the cable surface temperature, and the monitored value of the ground surface temperature are obtained; based on a preset parameter space, an initial equivalent current is obtained; using the initial equivalent current as the input, the equivalent current iterative adjustment operation is repeatedly performed through the monitored value of the cable surface temperature and the reduced-order model of the steady-state temperature field. When the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, the equivalent current iterative adjustment operation is stopped, and the final iterative equivalent current is output; the iterative equivalent current and the monitored value of the ground surface temperature are input into the reduced-order model of the steady-state temperature field to obtain the reconstructed result of the transient temperature field inside the distribution network cable. The present invention generates an initial equivalent current through a parameter space, without the need to monitor the current of the distribution network cable. Based on the reduced-order model of the steady-state temperature field and the monitored value of the cable surface temperature obtained by monitoring, the initial equivalent current is iterated, so as to obtain the iterative equivalent current corresponding to the currently monitored value of the cable surface temperature of the load. Furthermore, the reconstructed result of the transient temperature field inside the cable can be obtained by substituting the iterative equivalent current and the monitored value of the meter temperature into the reduced-order model of the steady-state temperature field. The present invention does not need to monitor the real-time changing cable current, and only needs to monitor the surface temperature of each loop cable to reconstruct the internal temperature field of the cable, improving the simulation accuracy of the cable temperature field.

[0193] Embodiment 2

[0194] See Figure 3 , Figure 3 which is a schematic structural diagram of a terminal device provided by an embodiment of the present invention.

[0195] A terminal device in this embodiment includes: a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program, the steps in the above-mentioned various cable hot-spot temperature identification methods in the embodiment are implemented, for example Figure 1 all the steps of the cable hot-spot temperature identification method shown. Or, when the processor executes the computer program, the functions of each module in the above-mentioned device embodiments are implemented, for example: Figure 2 all the modules of the cable hot-spot temperature identification device shown.

[0196] In addition, an embodiment of the present invention also provides a computer-readable storage medium, which includes a stored computer program. When the computer program runs, the device where the computer-readable storage medium is located is controlled to execute the cable hot-spot temperature identification method described in any one of the above embodiments.

[0197] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the attached drawings of the device embodiments provided by the present invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0198] The above is the preferred embodiment of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as the protection scope of the present invention.

Claims

1. A cable hot spot temperature identification method, characterized in that: include: Obtain the steady-state temperature field reduced-order model of the distribution network cable, the cable surface temperature monitoring value and the ground surface temperature monitoring value; wherein, the collected value of the temperature sensor is compensated for the thermal time constant to obtain the cable surface temperature monitoring value; Based on the preset parameter space, an initial equivalent current is obtained; Taking the initial equivalent current as input, repeatedly performing an equivalent current iterative adjustment operation through the cable surface temperature monitoring value and the steady-state temperature field reduced-order model, stopping the equivalent current iterative adjustment operation when the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, and outputting the final iterative equivalent current; The iterative equivalent current and the surface temperature monitoring values ​​are input into the steady-state temperature field reduced-order model to obtain the reconstruction result of the transient temperature field inside the cable of the distribution network cable.

2. The cable hot spot temperature identification method according to claim 1, characterized in that: The equivalent current iterative adjustment operation includes: Input the current input and the cable surface temperature monitoring value into the steady-state temperature field reduced-order model to obtain the cable surface temperature calculation value; Substituting the cable surface temperature monitoring value and the cable surface temperature calculation value into the cable heat transfer objective function to obtain residual data; Judge the residual data and the number of iterations; If the residual data is greater than or equal to the residual threshold and the number of iterations is less than the iteration threshold, the current input is calculated by the secant method to obtain the iterative equivalent current, and the next equivalent current iterative adjustment operation is performed based on the iterative equivalent current; If the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, the equivalent current iterative adjustment operation is stopped and the final iterative equivalent current is output.

3. The cable hot spot temperature identification method according to claim 2, characterized in that: The cable heat transfer objective function satisfies the following conditions: In the formula, is the equivalent current The calculated value of the surface temperature of the i-th cable output by the steady-state temperature field reduced-order model under the action; is the surface temperature monitoring value of the i-th cable.

4. The cable hot spot temperature identification method according to claim 3, characterized in that: The thermal time constant compensation is performed on the collected value of the temperature sensor to obtain the cable surface temperature monitoring value, including: Get the location and collected value of the temperature sensor; Based on the location, determining the cable surface temperature rise data; Determining a time domain difference equation based on the cable surface temperature rise data and a preset time constant compensation link expression; Substitute the collected values ​​into the time domain difference equation to obtain the cable surface temperature monitoring value.

5. The cable hot spot temperature identification method according to claim 1, characterized in that: The step of obtaining a reduced-order model of a steady-state temperature field of a distribution network cable comprises: Obtain basic physical parameters of distribution network cables; Constructing a finite element full-order model of the distribution network cable according to basic physical parameters; By using a preset sampling method, a random sampling is performed in the parameter space to obtain a number of input parameter column vectors; wherein the input parameter column vector is the cable load current; Substituting each parameter matrix into the finite element full-order model for solving, obtaining the node temperature column vector corresponding to each parameter matrix, and combining all the node temperature column vectors into a snapshot matrix; According to the snapshot matrix, the steady-state temperature field reduced-order model is obtained through singular value decomposition.

6. The cable hot spot temperature identification method according to claim 5, characterized in that: The step of obtaining the steady-state temperature field reduced-order model by singular value decomposition according to the snapshot matrix comprises: Performing singular value decomposition on the snapshot matrix to obtain a number of left singular vectors; Selecting a target left singular vector from a number of left singular vectors; Based on the target left singular vector, a linear combination of left singular vectors corresponding to each node temperature column vector in the snapshot matrix is ​​constructed, and each linear combination of the left singular vectors is summarized into a reduced-order modal reconstruction matrix; wherein the linear combination of the left singular vectors is the product of each target left singular vector and an unknown linear combination coefficient; Based on the preset constraints and snapshot matrix, the unknown linear combination coefficients corresponding to each left singular vector linear combination are solved to obtain the target linear combination coefficients corresponding to each left singular vector linear combination; According to each target linear combination coefficient, fit the response surface function of the linear combination coefficient; According to the response surface function and the target left singular vector, the steady-state temperature field reduced-order model is obtained; wherein the steady-state temperature field reduced-order model satisfies the following conditions: In the formula, ψ rei is a reduced-order model for the steady-state temperature field, is the linear combination coefficient, u i is the target left singular vector, f i (ξ) is the response surface function, ξ is the equivalent current, and r is the modal number; the equivalent current includes: initial equivalent current and iterative equivalent current.

7. The cable hot spot temperature identification method according to claim 6, characterized in that: The constraints satisfy the following conditions: Where χ is the truncation error, M is the snapshot matrix, and M re is the reduced-order modal reconstruction matrix, σ i are the singular values ​​of M, and |||| is the Frobenius norm.

8. A cable hot spot temperature identification device, characterized in that: include: Data acquisition module, current acquisition module, iteration module and temperature field reduction module; The data acquisition module is used to obtain the steady-state temperature field reduced-order model of the distribution network cable, the cable surface temperature monitoring value and the ground surface temperature monitoring value; The current acquisition module is used to obtain an initial equivalent current based on a preset parameter space; The iteration module is used to take the initial equivalent current as input, repeatedly perform the equivalent current iterative adjustment operation through the cable surface temperature monitoring value and the steady-state temperature field reduced-order model, stop performing the equivalent current iterative adjustment operation when the residual data is less than the residual threshold or the number of iterations is equal to the iteration threshold, and output the final iterative equivalent current; The temperature field reduction module is used to input the iterative equivalent current and the surface temperature monitoring value into the steady-state temperature field reduction model to obtain the reconstruction result of the transient temperature field inside the cable of the distribution network cable.

9. A computer terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a cable hot spot temperature identification method as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute a cable hot spot temperature identification method as described in any one of claims 1 to 7.

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