Cable parameter calculation method considering material frequency change and temperature change characteristics

Abstract

The invention discloses a cable parameter calculation method considering material frequency change and temperature change characteristics. The cable parameter calculation method comprises the following steps: 1, measuring the temperature change and frequency change characteristics of a cable material in a laboratory; 2, establishing a corresponding relation between impedance and admittance of a cable material and temperature and frequency; 3, setting a neural network model, and training a neural network by using the actually measured data in the step 1 to obtain a corresponding relationship between the impedance and the admittance in the step 2 and the temperature and the frequency; 4, modeling a cable system, and writing a voltage and current equation along the cable; 5, obtaining the impedance and admittance of each cable material at the current temperature and frequency by using the neural network trained in the step 3, and substituting the impedance and admittance into a voltage and current equation to solve the equation; and 6, for a new cable structure, solving an impedance matrix and an admittance matrix of the corresponding cable according to the step 4. According to the method, the influence of the frequency and the temperature on the series impedance and the parallel admittance matrix of the cable is comprehensively considered, so that the calculation result is more practical, and the method has great engineering value.

Description

Technical Field

[0001] The present invention relates to the technical field of cable parameter calculation, and in particular to a cable parameter calculation method taking into account material frequency variation and temperature variation characteristics. Background Art

[0002] In recent years, with the rapid development of China's economy, the domestic urbanization process has also developed rapidly. Therefore, the scale of urban power grids, which is an important indicator of urbanization, has also expanded rapidly. The use of power cables, which are the main power transmission of urban power grids, has naturally increased significantly. Compared with overhead lines, power cables have the advantages of saving space, being less affected by nature, having high operating efficiency and strong safety. At present, power cables have become the main medium for power transmission in urban power grids.

[0003] With the advancement of science and technology and the growth of electricity demand, the requirements for cable performance are getting higher and higher. The study of cable parameter calculation methods, especially the study considering the frequency change (frequency change) and temperature change (temperature change) characteristics of materials, is of great significance to improving the accuracy of cable design and the stability of power systems. First, the material properties of cables will change with the changes in frequency and temperature, and this change directly affects the electrical parameters of cables, such as resistance, inductance and capacitance. Traditional cable parameter calculation methods often assume that these parameters are constants, but in fact they are variables. Therefore, the study of cable parameter matrix calculation methods considering the frequency change and temperature change characteristics of materials can more accurately reflect the performance of cables under different working conditions. Secondly, as the power system develops towards high frequency and high temperature, the reliability of cables in high frequency and high temperature environments has become a focus of attention. For example, in flexible DC power grids, cables need to withstand wider frequency bands and higher temperatures. This requires that the calculation method of cable parameters can accurately take into account the frequency change and temperature change characteristics of materials. Thirdly, accurate cable parameter matrix calculation methods are also very important for cable fault location and diagnosis. If the cable parameters can be accurately calculated, the fault point can be located faster, the power outage time can be reduced, and the power supply reliability can be improved.

[0004] At present, for the calculation of voltage and current along the cable, domestic and foreign scholars and engineers mainly use formula method and simulation software calculation method. For the fine calculation involving temperature-varying characteristics and frequency-varying characteristics, they are more inclined to use simulation software for modeling and analysis, such as EMTP-ATP, COMSOL, etc. This method requires first establishing a simulation model of the cable electric field and magnetic field, and then iteratively solving by setting the temperature and frequency. For different temperatures and frequencies, it is necessary to repeat the solution. The steps are cumbersome and require high computing power. As for the formula method, the impedance matrix and admittance matrix of the cable are calculated by formula derivation, and the operating state of the cable is obtained by solving the voltage and current equations. In the formula method solution, the material properties of the cable are often replaced by parameters at room temperature and power frequency for rough calculation. In the formula method, the cable distributed parameter matrix is ​​corrected according to the temperature and frequency characteristics of the material, and there are few research cases at home and abroad. Summary of the invention

[0005] In view of the problems existing in the prior art, the purpose of the present invention is to propose a cable parameter calculation method taking into account the frequency-varying and temperature-varying characteristics of the material. This method accurately calculates the cable series impedance and parallel admittance matrix by considering the temperature-varying and frequency-varying characteristics of the cable material, so that the calculation results are more in line with reality.

[0006] In order to achieve the above object, the present invention adopts the following technical scheme:

[0007] A method for calculating cable parameters taking into account the frequency-varying and temperature-varying characteristics of materials comprises the following steps:

[0008] Step 1: Determine the temperature and frequency characteristics of the cable material in the laboratory;

[0009] Step 2: Based on the measured data, comprehensively consider the influence of temperature and frequency, and establish the corresponding relationship between the impedance and admittance of the cable material and the temperature and frequency: Z = f(T, ω), Y = f(T, ω);

[0010] Step 3: Set up a neural network model, use the measured data in step 1 to train the neural network, and obtain the corresponding relationship between the impedance and admittance and the temperature and frequency in step 2;

[0011] Step 4: Model the cable system according to the cable structure and laying method; according to the coupling relationship between the electric field and the magnetic field, all cable materials are regarded as conductors, the self-impedance and mutual impedance, self-admittance and mutual admittance of the cable are calculated, and the voltage and current equations along the cable, namely the impedance matrix and admittance matrix, are written;

[0012] Step 5: Use the neural network trained in step 3 to obtain the impedance and admittance of each cable material at the current temperature and frequency, and substitute them into the voltage-current equation to solve the voltage-current equation;

[0013] Step 6. For the new cable structure, the impedance matrix and admittance matrix of the corresponding cable are obtained according to step 4. During the calculation process, the neural network trained in step 3 is used to obtain the impedance and admittance of each material at the corresponding temperature and frequency, so that the voltage and current distribution along the cable can be accurately solved.

[0014] In step 1, the laboratory measures the temperature-dependent and frequency-dependent characteristics of the cable materials, including: the impedance and admittance of the conductor, insulation layer, sheath, shielding layer, and filling material changing with temperature and frequency; measuring the impedance and admittance of the cable material changing with frequency at a certain temperature and the impedance and admittance of the cable material per unit length changing with temperature at a certain frequency.

[0015] In step 2, based on the measured data and taking into account the influence of temperature and frequency, a neural network is used to fit the impedance and admittance curves of each cable material, and the corresponding relationship between the impedance and admittance of the cable material and the temperature and frequency is established: Z = f(T, ω), Y = f(T, ω).

[0016] Preferably, in step 3, the neural network in the neural network model is set to an input layer, a hidden layer, and an output layer; the number of hidden layers is set to 1, and the number of neurons is set to 20; the activation function of the hidden layer selects RELU, and the output layer does not use an activation function; the loss function selects the MSE loss function.

[0017] Compared with the prior art, the present invention proposes a cable parameter matrix calculation method that takes into account the frequency-varying and temperature-varying characteristics of the material, comprehensively considering the influence of frequency and temperature on the cable series impedance and parallel admittance matrix, making the calculation results more practical and having great engineering value. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0019] Figure 1 A flow chart of a cable parameter matrix calculation method taking into account the frequency-varying and temperature-varying characteristics of materials is shown.

[0020] Figure 2 A schematic diagram of the neural network model training process is shown. DETAILED DESCRIPTION

[0021] The purpose of the present invention is to propose a cable parameter matrix calculation method taking into account the frequency-varying and temperature-varying characteristics of the material. The method accurately calculates the cable series impedance and parallel admittance matrix by considering the temperature-varying and frequency-varying characteristics of the cable material, making the calculation results more practical.

[0022] like Figure 1As shown, the present invention provides a cable parameter calculation method taking into account the frequency change and temperature change characteristics of the material, the method comprising the following steps:

[0023] 1. The laboratory measures the temperature-dependent and frequency-dependent characteristics of cable materials, such as the impedance and admittance of conductors, insulation layers, sheaths, shielding layers, and filling materials as a function of temperature and frequency. The impedance and admittance of cable materials are measured as a function of frequency at a certain temperature, and the impedance and admittance per unit length of cable materials are measured as a function of temperature and frequency at a certain frequency, to obtain a data set of impedance changes of various cable materials as a function of temperature and frequency.

[0024] 2. Based on the measured data, the influence of temperature and frequency is comprehensively considered, and the impedance and admittance curves of each cable material are fitted using a neural network. The relationship between impedance and temperature and frequency is a binary function relationship Z = f (T, ω), and the purpose of neural network training is to find the corresponding relationship f. The input of the neural network is the point set (T, ω) → Z, which means that a certain temperature and frequency correspond to a certain impedance value. For the admittance of the cable material, the corresponding relationship is Y = f (T, ω).

[0025] 3. For each cable material, train a neural network to fit the relationship between its impedance and admittance and temperature and frequency. Figure 2 For each cable material, the data set obtained in step 1 is divided into training set X and 1 and the test set X 2 . Set the neural network model, the neural network is set to input layer, hidden layer, output layer. The number of hidden layers is set to 1, and the number of neurons is set to 20. The activation function of the hidden layer is selected as RELU, and the output layer does not use an activation function. The loss function is selected as the MSE loss function, that is, Use the training set to train the neural network, and use the test set to verify the prediction performance of the neural network. When the model inputs the test set X 2 When 2 and the true value Y 2 When the MSE of the value is less than n*(1e-2), the training ends, where n is the test set X 2 If Y 2 and Y′ 2 When the MSE is greater than n*(1e-2), you should adjust the number of model iterations or increase the training set X 1 Retrain in the same way. Obtain the corresponding model of impedance, temperature and frequency. For the admittance of each cable material, establish the corresponding neural network model in the same way. After all the networks of various cable materials are trained, they are integrated together to realize the input of cable material type, temperature, frequency, and automatic calculation of its impedance and admittance.

[0026] 4. Model the cable system according to the cable structure and laying method, consider the influence of frequency and temperature, and establish the impedance and admittance matrix of the cable. For example, for a single-loop single-core cable, from the inside to the outside, they are the core, main insulation, metal sheath, sheath insulation, armor, and outer sheath. If all these structures are regarded as conductors, there are a total of 18 conductors for coupling in the three phases. The relationship between the voltage drop and current loss along the cable, that is, the impedance matrix, can be written as:

[0027]

[0028] The self-impedance Z XX and mutual impedance Z XY It can be obtained from the coupling relationship between the electric field and the magnetic field according to the structure of the cable, which are functions of temperature T and frequency ω. Similarly, the admittance matrix of the cable can be written as:

[0029]

[0030] For single-circuit cable systems with different arrangements, self-impedance and mutual impedance, self-admittance and mutual admittance should be calculated according to the actual laying conditions. For multi-circuit systems, in addition to calculating self-impedance and mutual impedance, self-admittance and mutual admittance according to actual conditions, the number of unknown voltages U and currents I should also be increased accordingly.

[0031] 5. Solve the impedance equation and admittance equation to obtain the voltage and current distributed along the cable. In the solution process, use the neural network trained in step 3, input the type of cable material, the current temperature and frequency combination T, ω, and you can get the impedance and admittance of each material at the current position, substitute them into the voltage and current equations for solution, and use the temperature and frequency characteristics of the cable material to get a more accurate voltage and current distribution along the cable.

[0032] 6. For the new cable structure, the corresponding impedance matrix and admittance matrix are obtained according to step 4. During the calculation process, the corresponding temperature and frequency, the impedance and admittance of each material are obtained by relying on the neural network in step 3, so as to accurately solve the voltage and current distribution along the cable, thereby improving the accuracy of solving the cable voltage and current using the series impedance matrix and the parallel admittance matrix.

Claims

1. A cable parameter calculation method taking into account the frequency and temperature variation characteristics of materials, characterized in that: The following steps are involved: Step 1: Determine the temperature and frequency characteristics of the cable material in the laboratory; Step 2: Based on the measured data, comprehensively consider the influence of temperature and frequency, and establish the corresponding relationship between the impedance and admittance of the cable material and the temperature and frequency: Z = f(T, ω), Y = f(T, ω); Step 3, setting a neural network model, using the measured data in step 1 to train the neural network, and obtaining the corresponding relationship between the impedance and admittance of each cable material in step 2 and the temperature and frequency; Step 4: Model the cable system according to the cable structure and laying method; According to the coupling relationship between electric field and magnetic field, all cable materials are regarded as conductors, the self-impedance and mutual impedance, self-admittance and mutual admittance of the cable are calculated, and the voltage and current equations along the cable, namely the impedance matrix and admittance matrix, are written; Step 5: Use the neural network trained in step 3 to obtain the impedance and admittance of each cable material at the current temperature and frequency, and substitute them into the voltage-current equation to solve the voltage-current equation; Step 6. For the new cable structure, the impedance matrix and admittance matrix of the corresponding cable are obtained according to step 4. During the calculation process, the neural network trained in step 3 is used to obtain the impedance and admittance of each material at the corresponding temperature and frequency, so that the voltage and current distribution along the cable can be accurately solved.

2. The cable parameter calculation method taking into account the frequency and temperature variation characteristics of materials according to claim 1 is characterized in that: In step 1, the laboratory measures the temperature-dependent and frequency-dependent characteristics of the cable materials, including: the impedance and admittance of the conductor, insulation layer, sheath, shielding layer, and filling material changing with temperature and frequency; measuring the impedance and admittance of the cable material changing with frequency at a certain temperature and the impedance and admittance of the cable material per unit length changing with temperature at a certain frequency.

3. The cable parameter calculation method taking into account the frequency and temperature variation characteristics of materials according to claim 1, characterized in that: In step 2, based on the measured data and taking into account the influence of temperature and frequency, a neural network is used to fit the impedance and admittance curves of each cable material, and the corresponding relationship between the impedance and admittance of the cable material and the temperature and frequency is established: Z = f(T, ω), Y = f(T, ω).

4. The cable parameter calculation method taking into account the material frequency variation and temperature variation characteristics according to claim 1, characterized in that: In step 3, the neural network in the neural network model is set as input layer, hidden layer, and output layer; the number of hidden layers is set to 1, and the number of neurons is set to 20; the activation function of the hidden layer is selected as RELU, and the output layer does not use an activation function; the loss function is selected as the MSE loss function.

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