A practical calculation method for the capacitive current of submarine cable of offshore wind farm

Abstract

The application discloses a practical calculation method for submarine cable capacitance current of offshore wind farm, which comprehensively considers the influence of cross-linked polyethylene insulating material, system electrical equipment cable influence and submarine cable operation environment and other factors on the submarine cable capacitance current, simultaneously takes the submarine cable voltage grade, cable conductor cross-sectional area and cable length as independent variables, and further introduces four characteristic coefficients to establish a nonlinear practical calculation model for the submarine cable capacitance current of offshore wind farm; the residual sum of squares of the measured capacitance current and the output value of the nonlinear parameter estimation formula is taken as the fitness function to construct a nonlinear parameter identification model for the submarine cable capacitance current estimation formula based on the real number coding genetic algorithm, and the optimal solution of the deviation rate and the goodness of fit is obtained through repeated iteration as the parameter identification result. The method has good practicability and can guide the accurate calculation of the submarine cable capacitance current.

Description

Technical Field

[0001] The present invention belongs to the technical field of offshore wind power parameter identification, and in particular relates to a practical calculation method for the capacitance and current of submarine cables in offshore wind farms. Background Art

[0002] Due to the shortage of fossil energy and increasing environmental pollution, the development of the new energy industry is an inevitable trend. my country boasts abundant wind resources and increasingly mature wind power technology. As onshore wind power resources gradually become saturated, the wind power industry has gradually expanded offshore and even into the deep sea. Submarine cables are crucial electrical equipment in offshore wind power projects, connecting wind turbines and transmitting and gathering electrical energy. However, the distributed capacitance of cable lines is much greater than that of overhead lines, generating significant capacitive currents in AC systems. Ground faults can easily cause line tripping, impacting the safe and stable operation of the system. Therefore, accurate calculation of submarine cable capacitive currents is crucial for the safe operation of offshore wind farms and power systems.

[0003] With the increasing cableization rate of power grids, the calculation of capacitive current has attracted considerable attention in recent years. Some researchers have compared the estimated capacitive current of medium-voltage cables using different commonly used methods, concluding that traditional estimation methods are no longer suitable for engineering calculations. Other researchers have combined factory data on cables with recursive algorithms to determine the cross-sectional coefficients for cables of varying cross-sections, refining empirical formulas. However, each cross-section corresponds to a different coefficient, resulting in a large number of formulas. Another study equates the line to two π-type models based on the location of the fault point, calculating the line's capacitive current using the differential current on each capacitive branch. However, this calculation involves cable capacitance parameters, making it unsuitable for practical engineering applications.

[0004] Submarine cables, laid beneath the sea surface, are exposed to high-pressure, highly corrosive environments for extended periods. They must also be protected from damage from fishing boats, marine biodiversity intrusions, and undercurrents. Consequently, the protective measures required for submarine cables are far more stringent than those for land-based cables. This structural difference leads to differences in the calculation of capacitance parameters for submarine and land-based cables. Furthermore, factors such as laying depth, seawater temperature, and sea-soil resistivity all affect the capacitance current. Therefore, calculation methods for land-based cables cannot be applied to submarine cable capacitance current calculations. Existing research has constructed a Pi-type equivalent circuit for a high-resistance submarine cable line and calculated the capacitance current of a three-core submarine cable using relative ground capacitance and phase-to-phase capacitance. However, cable manufacturers often only provide approximate dimensions and some material parameters for each layer of the submarine cable, making it difficult to accurately obtain submarine cable capacitance parameters and thus unable to calculate submarine cable capacitance current from relative ground capacitance. Other researchers have used a distributed parallel capacitance-resistance module to represent the main insulation of a single-core oil-filled cable and calculated the ground capacitance current by assuming a single-phase ground fault. However, in practical engineering applications, the distributed capacitance parameters are difficult to obtain, and the calculation of the capacitance current involved is also very complex, limiting their practicality.

[0005] In summary, existing cable capacitance and current calculation formulas cannot be directly applied to submarine cable capacitance and current calculations. Submarine cable capacitance parameters are difficult to obtain, and accurately calculating the capacitance and current of submarine cables, especially three-core submarine cables, based on ground capacitance is too complex. To accurately understand submarine cable capacitance and current in practical engineering applications, a more practical calculation method for the capacitance and current of high-voltage, large-cross-section submarine cables is needed. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a practical calculation method for the capacitance current of submarine cables in offshore wind farms. The method measures the influence of factors such as cross-linked polyethylene insulation material, the influence of system electrical equipment cables and the submarine cable operating environment on the capacitance current of submarine cables, takes the submarine cable voltage level, cable conductor cross-sectional area and cable length as independent variables, constructs a practical calculation model for the capacitance current of submarine cables in offshore wind farms, repeatedly iterates to obtain the deviation rate and the optimal solution of the goodness of fit between the calculated value and the measured value as the parameter identification result, and proposes a practical calculation method for the capacitance current of submarine cables in offshore wind farms, thereby achieving the purpose of accurately calculating the capacitance current of submarine cables in offshore wind farms.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0008] The present invention discloses a practical calculation method for the capacitance current of submarine cables in offshore wind farms, comprising the following steps:

[0009] S101. Considering the influence of cable cross-section, cable material, electrical equipment and operating environment, a practical calculation model for the capacitance and current of submarine cables in offshore wind farms is established using four characteristic coefficients.

[0010] S102, setting the maximum evolutionary generation, population size, crossover probability, and mutation probability, and randomly generating several feasible solutions of characteristic coefficient vectors consisting of four characteristic coefficients within the feasible region as the initial population;

[0011] S103, using the residual sum of squares between the submarine cable capacitance and current test value and the submarine cable capacitance and current calculated value as a fitness function, calculating the fitness of each characteristic coefficient vector;

[0012] S104: Determine whether the evolutionary generation has reached the maximum evolutionary generation. If so, execute step S108; if not, execute step S105;

[0013] S105: Determine whether the absolute value of the characteristic coefficient vector deviation rate is less than a first threshold. If so, proceed to step S106; if not, proceed to step S107;

[0014] S106: Determine whether the characteristic coefficient vector correction determination coefficient is greater than a second threshold. If so, execute step S108; if not, execute step S107;

[0015] S107, performing a selection operation on the population; randomly selecting two characteristic coefficient vectors from the population and performing a random crossover operation at random positions; randomly selecting one characteristic coefficient vector from the population and performing a mutation operation at a random position; executing step S103;

[0016] S108 , outputting the optimal characteristic coefficient vector, and bringing the optimal characteristic coefficient vector into a practical calculation model for submarine cable capacitance and current in an offshore wind farm to calculate the submarine cable capacitance and current value to be measured.

[0017] Preferably, in step S101, the practical calculation model for the capacitance current of the submarine cable of the offshore wind farm calculates the capacitance current of the submarine cable according to the following formula:

[0018]

[0019] Where, α is the cable material influence coefficient; β is the electrical equipment value-added coefficient; γ is the environmental influence coefficient; S is the cable core cross-sectional area; U r is the rated line voltage of the line; l is the line length; k1, k2, k3, and k4 are four different characteristic coefficients respectively.

[0020] Preferably, in step S102, the maximum evolutionary generation is set to 00, the population size is set to 100, the crossover probability is set to 0.06, and the mutation probability is set to 0.001 according to empirical values.

[0021] Preferably, in step S103, the fitness function is determined according to the residual square sum of the capacitance current test value and the calculated value:

[0022]

[0023] Where I(K) is the calculated value vector of the submarine cable capacitance current under different voltage levels, different cross-sectional areas, and different lengths; is the test value vector of submarine cable capacitance current under different voltage levels, different cross-sectional areas, and different lengths; K is the characteristic coefficient vector, K = [k1, k2, k3, k4] T .

[0024] Preferably, in step S105, the characteristic coefficient vector deviation rate is calculated as follows:

[0025]

[0026] Where y is the test value of submarine cable capacitance current; is the calculated value of the submarine cable capacitance current, which can be calculated by the following formula:

[0027]

[0028] Preferably, in step S106, the characteristic coefficient vector correction determination coefficient is calculated as follows:

[0029]

[0030] Among them, R 2 is the characteristic coefficient vector determination coefficient, which can be calculated by the following formula:

[0031]

[0032] Where, is the average value of the measured output y; n is the number of samples, and p is the number of features.

[0033] Preferably, in step S107, the operation method is selected according to the following method:

[0034] The fitness ratio of each characteristic coefficient vector individual to all characteristic coefficient vector individuals in the current population is calculated, and the characteristic coefficient vector individual with a high fitness ratio is selected from the current population as the parent generation to pass on the gene to the offspring according to the roulette method.

[0035] Preferably, in step S107, the crossover or gene recombination operation is performed according to the following method:

[0036] Randomly select 2 individuals in the population and cross them at random positions (at the individual's variable). The kth characteristic coefficient vector of individual a in the population k and the lth characteristic coefficient vector individual a l Perform crossover operation at random position of the variable at position j, i.e. individual a k After the crossover, the new j-th variable is a kj =a kj (1-b)+a lj b, individual a l After the crossover, the new j-th variable is a lj =a lj (1-b)+a kj b, where b is a random number in the interval [0,1].

[0037] Preferably, in step S107, the mutation operation is performed according to the following method:

[0038] The j-th variable of the i-th characteristic coefficient vector individual is mutated, then the characteristic coefficient vector individual a i The new j-th variable after mutation is:

[0039]

[0040] Where a ij ' represents the characteristic coefficient vector individual a i The new j-th variable after mutation, a ij Represents the characteristic coefficient vector individual a i The j-th variable before mutation, a max Gene a ij The upper bound of a min Gene a ij The lower bound of f(g) = r2(1-g / G max ) 2 , r2 is a random number; g is the current number of iterations; G max is the maximum evolutionary generation; r is a random number in the interval [0,1].

[0041] In summary, this invention addresses the prior art's neglect of submarine cable capacitance and current calculations, as well as the complex and difficult-to-obtain capacitance parameter calculations. It emphasizes the rapid and accurate calculation of capacitance and current in submarine cables used in offshore wind farms, and proposes a practical method for calculating capacitance and current in submarine cables used in offshore wind farms. This invention is suitable for calculating the capacitance and current of various submarine cables, particularly cross-linked polyethylene high-voltage submarine cables, and possesses excellent practicality.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] 1. Existing empirical formulas for cable capacitance and current are primarily applicable to calculating the capacitance and current of oil-impregnated paper-insulated cables. Since submarine cables generally use cross-linked polyethylene insulation, which has a higher relative dielectric constant, existing methods cannot accurately calculate the capacitance and current of submarine cables. Existing empirical formulas cannot be directly applied to calculating the capacitance and current of submarine cables. This invention, however, takes into account the influence of cable materials, electrical equipment, and the operating environment, and can accurately calculate the capacitance and current of submarine cables in offshore wind farms.

[0044] 2. When calculating the capacitance and current of cross-linked polyethylene cables, the existing technology mainly uses a distributed parameter model for theoretical calculations, and ignores the structural differences between submarine cables and land cables. Submarine cables are power cables specially designed for transmitting AC or DC current in special submarine environments. They are exposed to high-voltage and highly corrosive submarine environments for a long time. The laying depth, seawater temperature, and sea soil resistivity will all affect the capacitance and current. Therefore, the calculation method for land cables cannot be used in the calculation of the capacitance and current of submarine cables. The present invention takes into account the structural characteristics and laying environment of submarine cables that are different from those of land cables, introduces the voltage level of submarine cables, the cross-sectional area of ​​cable conductors, and the length of cables as independent variables, establishes a mathematical model for nonlinear parameter estimation formulas, and uses genetic algorithms to identify its parameters, which is conducive to solving the problems of complex acquisition and difficult calculation of submarine cable capacitance parameters.

[0045] 3. When correcting the empirical formula for cable capacitance and current, the existing technology mainly uses the arithmetic mean and multiplication of coefficients to correct the single coefficient in the empirical formula, which has disadvantages such as large errors and a narrow scope of application. The optimization algorithm used in the present invention is a genetic algorithm. This algorithm is self-organizing, adaptive, and self-learning. It starts the search from a cluster of problem solutions and can simultaneously process multiple characteristic coefficient vectors in the group. It evaluates multiple solutions in the search space, reducing the risk of falling into a local optimal solution, covering a wide range, and facilitating global optimization.

[0046] 4. Existing technologies primarily verify parameter identification results by re-experimenting and calculating the error, using a relatively simple method. The present invention utilizes a deviation rate to assess the deviation between the calculated optimal solution found by the genetic algorithm and the test value, which helps improve identification accuracy. Furthermore, to prevent an increase in the coefficient of determination due to an increase in the number of samples, the present invention utilizes a corrected coefficient of determination to assess the goodness of fit of the optimal solution found by the genetic algorithm, offsetting the effect of sample size and enabling a single number between 0 and 1 to describe the quality of the model's fit. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to make the purpose, technical solutions and advantages of the invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings, in which:

[0048] Figure 1 This is a flow chart of a practical method for calculating the capacitance current of submarine cables in offshore wind farms according to an embodiment of the present invention;

[0049] Figure 2 This is an example diagram of an offshore wind farm transmission system in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] like Figure 1 As shown, the present invention discloses a practical calculation method for the capacitance current of submarine cables in offshore wind farms, comprising the following steps:

[0052] S101. Taking into account the influence of cable cross-section, cable material, electrical equipment and operating environment, a practical calculation model for the capacitance and current of submarine cables in offshore wind farms is established using four characteristic coefficients.

[0053] S102, setting the maximum evolutionary generation, population size, crossover probability, and mutation probability, and randomly generating several feasible solutions of characteristic coefficient vectors consisting of four characteristic coefficients within the feasible region as the initial population;

[0054] S103, using the residual sum of squares between the submarine cable capacitance and current test value and the submarine cable capacitance and current calculated value as a fitness function, calculating the fitness of each characteristic coefficient vector;

[0055] S104: Determine whether the evolutionary generation has reached the maximum evolutionary generation. If so, execute step S108; if not, execute step S105;

[0056] S105: Determine whether the absolute value of the characteristic coefficient vector deviation rate is less than a first threshold. If so, proceed to step S106; if not, proceed to step S107;

[0057] S106: Determine whether the characteristic coefficient vector correction determination coefficient is greater than a second threshold. If so, execute step S108; if not, execute step S107;

[0058] S107, performing a selection operation on the population; randomly selecting two characteristic coefficient vectors in the population and performing a random crossover operation at random positions; randomly selecting a characteristic coefficient vector in the population and performing a mutation operation at a random position; executing step S103;

[0059] S108 , outputting the optimal characteristic coefficient vector, and bringing the optimal characteristic coefficient vector into a practical calculation model for submarine cable capacitance and current in an offshore wind farm to calculate the submarine cable capacitance and current value to be measured.

[0060] To further optimize the above technical solution, in step S101, the effects of factors such as cross-linked polyethylene insulation material, system electrical equipment cable, and submarine cable operating environment on the submarine cable capacitance current are measured. Meanwhile, the submarine cable voltage level, cable conductor cross-sectional area, and cable length are used as independent variables, and four characteristic coefficients are introduced to construct a nonlinear practical calculation model for the capacitance current of submarine cables in offshore wind farms. The practical calculation model for the capacitance current of submarine cables in offshore wind farms calculates the capacitance current of submarine cables according to the following formula:

[0061]

[0062] Where, α is the cable material influence coefficient; β is the electrical equipment value-added coefficient; γ is the environmental influence coefficient; S is the cable core cross-sectional area; U r is the rated line voltage of the line; l is the line length; k1, k2, k3, k4 are characteristic coefficients.

[0063] To further optimize the above technical solution, in step S102, the maximum evolutionary generation is set to 300, the population size is 100, the crossover probability is 0.06, and the mutation probability is 0.001 according to empirical values. Of course, those skilled in the art can also design the corresponding maximum evolutionary generation, population size, crossover probability, and mutation probability according to actual conditions, and the present invention does not make specific limitations on this.

[0064] To further optimize the above technical solution, in step S102, the fitness function is determined according to the residual square sum of the capacitance current test value and the calculated value:

[0065]

[0066] Where I(K) is the calculated value vector of the submarine cable capacitance current under different voltage levels, different cross-sectional areas, and different lengths; is the test value vector of submarine cable capacitance current under different voltage levels, different cross-sectional areas, and different lengths; K is the characteristic coefficient vector, K=[k1,k2,k3,k4] T ; k1, k2, k3, k4 are four different characteristic coefficients respectively, and the superscript T represents transposition.

[0067] To further optimize the above technical solution, in step S105, the characteristic coefficient vector deviation rate is calculated according to the following method:

[0068]

[0069] Among them, Δ I represents the characteristic coefficient vector deviation rate, y is the test value of submarine cable capacitance current; is the calculated value of the submarine cable capacitance current, which can be calculated by the following formula:

[0070]

[0071] It can be seen that the calculated value here In fact, it is the value calculated by bringing in the practical calculation model of submarine cable capacitance and current of offshore wind farms. Through the correlation operation of the submarine cable capacitance and current test value and the bottom cable capacitance and current calculation value, the characteristic coefficient vector deviation rate can be obtained. By comparing the characteristic coefficient vector deviation rate with the first threshold, it can be determined whether the characteristic coefficient vector at this time meets the deviation requirements. If the deviation requirements are met, the next step of judgment can be carried out, otherwise it needs to be updated. The size of the first threshold can be set manually. In this embodiment, the first threshold can be 5%. Those skilled in the art can set the corresponding first threshold size according to the actual scenario.

[0072] To further optimize the above technical solution, in step S106, the characteristic coefficient vector correction determination coefficient is calculated according to the following method:

[0073]

[0074] Among them, R 2 is the characteristic coefficient vector determination coefficient, which can be calculated by the following formula:

[0075]

[0076] Where, is the average value of the measured output y; n is the number of samples, and p is the number of features.

[0077] In an embodiment of the present invention, after correcting and judging the characteristic coefficient vector that meets the deviation requirements, the characteristic coefficient vector correction determination coefficient is compared with the second threshold value to determine whether the characteristic coefficient vector at this time meets the correction requirements. If the correction difference requirements are met, the optimal characteristic coefficient vector can be output, otherwise it needs to be updated; the size of the second threshold can be set manually. In this embodiment, the second threshold can be 0.8. Those skilled in the art can set the corresponding second threshold size according to the actual scenario.

[0078] By judging the deviation and correction of the characteristic coefficient vector, the present invention can further find the characteristic coefficient vector that meets the actual calculation requirements of the submarine cable capacitance and current, thereby improving the accuracy of the calculation model and solving the problem of complex acquisition and calculation difficulty of submarine cable capacitance parameters.

[0079] To further optimize the above technical solution, in step S107, the operation method is selected according to the following method:

[0080] According to the fitness ratio of each individual, the roulette wheel method is used to select excellent individuals from the current population to form a mating pool as the parent generation to pass on genes to the offspring.

[0081] To further optimize the above technical solution, in step S107, a crossover or gene recombination operation is performed according to the following method:

[0082] Randomly select 2 individuals in the population and cross them at random positions (at the individual's variable). The kth individual a in the population k and the lth individual a l Perform crossover operation at random position of the variable at position j, i.e. individual a k After the crossover, the new j-th variable is a kj =a kj (1-b)+a lj b, individual a l After the crossover, the new j-th variable is a lj =a lj (1-b)+a kj b, where b is a random number in the interval [0,1].

[0083] To further optimize the above technical solution, in step S107, a mutation operation is performed according to the following method:

[0084] The j-th variable of the i-th individual undergoes mutation operation, then individual a i The new j-th variable after mutation is:

[0085]

[0086] Where a max Gene a ij The upper bound of a min Gene a ij The lower bound of f(g) = r2(1-g / G max ) 2 , r2 is a random number; g is the current number of iterations; G max is the maximum evolutionary generation; r is a random number in the interval [0,1].

[0087] As Figure 2The example system wiring diagram shown is used as an example for analysis and calculation. The voltage of the wind farm is 575V. After being stepped up by the export transformer, it is connected to the offshore booster station via the collecting submarine cable, and then connected to the main power grid via the sending submarine cable. The wind farm consists of 28 doubly-fed wind turbines, and the total rated capacity of the doubly-fed wind turbines is 502MW. Taking the input wind speed of the wind turbine as the rated wind speed of 12m / s, the current on the grounding capacitance branch of the equivalent model of each submarine cable line is measured to calculate the capacitive current of each submarine cable, and the capacitive current waveform is recorded. Under the same experimental conditions, the calculation results of the capacitance current of cross-linked polyethylene submarine cables of different voltage levels and conductor cross-sections of the present invention are compared with the calculation results using the theoretical calculation formula, the traditional empirical formula, and the improved empirical estimation formula to verify the improvement effect of the calculation accuracy of the capacitance current of the submarine cable.

[0088] First, under the condition that the offshore wind farm is operating normally and outputting rated power, the collection of capacitance current experimental data is carried out on cross-linked polyethylene insulated submarine cables at several commonly used voltage levels such as 66kV, 110kV and 220kV. The capacitance current data collected under different conductor cross-sectional areas and line lengths are used for nonlinear system identification modeling. Then, the submarine cable voltage level, cable conductor cross-sectional area and cable length are used as independent variables, and the residual sum of squares between the measured capacitance current and the calculated value of the present invention is used as the objective function to establish a nonlinear parameter identification model of the submarine cable estimation formula based on the real number coding genetic algorithm. The four eigenvectors of the model are identified by the real number coding genetic algorithm, and a practical calculation method for the capacitance current of the submarine cable is proposed. The genetic algorithm parameters are shown in Table 1.

[0089] Table 1 Genetic algorithm parameters

[0090]

[0091] The characteristic coefficient vector identified by the present invention is:

[0092]

[0093] Table 2 shows the improvement effect of the practical calculation accuracy and goodness of fit of the capacitance current of submarine cables in offshore wind farms using the present invention.

[0094] Table 2 Comparison of submarine cable capacitance and current results obtained by different methods

[0095]

[0096] As shown in Table 2, the present invention achieves a low overall deviation rate for practical calculations of submarine cable capacitance and current in offshore wind farms, significantly lower than traditional empirical estimation methods. The proposed method also demonstrates excellent identification results, with a corrected coefficient of determination (0.9695) exceeding 0.8, indicating a high goodness of fit. This invention effectively improves the accuracy of capacitance and current calculations for cross-linked polyethylene high-voltage submarine cables.

[0097] In summary, the present invention discloses a practical calculation method for the capacitance and current of submarine cables in offshore wind farms. The method comprehensively considers the influence of factors such as cross-linked polyethylene insulation materials, the influence of system electrical equipment cables, and the submarine cable operating environment on the capacitance and current of submarine cables. The submarine cable voltage level, cable conductor cross-sectional area, and cable length are used as independent variables. The residual square sum of the measured value of the capacitance and current and the output value of the nonlinear parameter estimation formula is used as the fitness function. A nonlinear parameter identification model of the submarine cable capacitance and current estimation formula based on a real number coded genetic algorithm is constructed. The optimal solution of the deviation rate and goodness of fit is obtained through repeated iterations as the parameter identification result.

[0098] This method is suitable for calculating the capacitance and current of various submarine cables, especially the capacitance and current calculation of cross-linked polyethylene high-voltage submarine cables. It has good practicality and is of great significance to the safe operation and protection settings of offshore wind power systems. It solves the problems of existing technologies that ignore the calculation of submarine cable capacitance and current and the complexity and difficulty in obtaining capacitance parameter calculations, and attaches importance to the rapid and accurate calculation of submarine cable capacitance and current in offshore wind farms.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described with reference to the preferred embodiments of the present invention, it is understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A practical calculation method for the capacitance and current of submarine cables in offshore wind farms, characterized in that: The method comprises the following steps: S101. Considering the influence of cable cross-section, cable material, electrical equipment and operating environment, a practical calculation model for the capacitance and current of submarine cables in offshore wind farms is established using four characteristic coefficients. The practical calculation model for the capacitance current of submarine cables in offshore wind farms uses the following formula: Where, I C It represents the calculated value of submarine cable capacitance current, α is the cable material influence coefficient; β is the electrical equipment value-added coefficient; γ is the environmental influence coefficient; S is the cable core cross-sectional area; U r is the rated line voltage of the line; l is the line length; k1, k2, k3, k4 are four different characteristic coefficients respectively; S102, setting the maximum evolutionary generation, population size, crossover probability, and mutation probability, and randomly generating several feasible solutions of characteristic coefficient vectors consisting of four characteristic coefficients within the feasible region as the initial population; S103, using the residual sum of squares between the submarine cable capacitance and current test value and the submarine cable capacitance and current calculated value as a fitness function, calculating the fitness of each characteristic coefficient vector; The fitness function is expressed as: Where I(K) is the calculated value vector of the submarine cable capacitance current under different voltage levels, different cross-sectional areas, and different lengths; is the test value vector of submarine cable capacitance current under different voltage levels, different cross-sectional areas, and different lengths; K is the characteristic coefficient vector, K=[k1,k2,k3,k4] T ; k1, k2, k3, k4 are four different characteristic coefficients respectively, and the superscript T represents transposition; S104, determine whether the evolutionary generation has reached the maximum evolutionary generation, if so, execute step S108; if not, execute step S105; S105, determining whether the absolute value of the characteristic coefficient vector deviation rate is less than a first threshold, if so, executing step S106; if not, executing step S107; The characteristic coefficient vector deviation rate indicates the degree of deviation between the calculated value and the test value, and is calculated as follows: Among them, Δ I represents the characteristic coefficient vector deviation rate, y is the test value of submarine cable capacitance current; is the calculated value of the submarine cable capacitance current; S106, determining whether the characteristic coefficient vector correction determination coefficient is greater than a second threshold, if so, executing step S108; if not, executing step S107; S107, performing a selection operation on the population; randomly selecting two characteristic coefficient vectors in the population and performing a random crossover operation at random positions; randomly selecting a characteristic coefficient vector in the population and performing a mutation operation at a random position; executing step S103; S108 , outputting the optimal characteristic coefficient vector, and bringing the optimal characteristic coefficient vector into a practical calculation model for submarine cable capacitance and current in an offshore wind farm to calculate the submarine cable capacitance and current value to be measured.

2. A practical calculation method for the capacitance current of submarine cables in offshore wind farms according to claim 1, characterized in that: In step S106, the characteristic coefficient vector correction determination coefficient is calculated as follows: Among them, R 2 is the characteristic coefficient vector determination coefficient, n is the number of samples, and p is the number of features.

3. A practical calculation method for the capacitance current of submarine cables in offshore wind farms according to claim 2, characterized in that: The coefficient of determination of the characteristic coefficient vector is calculated as follows: Where y is the test value of submarine cable capacitance current; is the calculated value of the submarine cable capacitance current; y is the average value of the test output y.

4. A practical calculation method for capacitance current of submarine cables in offshore wind farms according to claim 1, characterized in that: In step S107, the operation method is selected according to the following method: The fitness ratio of each characteristic coefficient vector individual to all characteristic coefficient vector individuals in the current population is calculated, and the characteristic coefficient vector individual with a high fitness ratio is selected from the current population as the parent generation to pass on the gene to the offspring according to the roulette method.

5. A practical calculation method for capacitance current of submarine cables in offshore wind farms according to claim 1, characterized in that: In step S107, the mutation operation is performed according to the following method: The j-th variable of the i-th characteristic coefficient vector individual is mutated, then the characteristic coefficient vector individual a i The new j-th variable after mutation is: Where a ij ' represents the characteristic coefficient vector individual a i The new j-th variable after mutation, a ij Represents the characteristic coefficient vector individual a i The j-th variable before mutation, a max Gene a ij The upper bound of a min Gene a ij The lower bound of f(g) = r2(1-g / G max ) 2 , r2 is a random number; g is the current number of iterations; G max is the maximum evolutionary generation; r is a random number in the interval [0,1].

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