Submarine cable lightning overvoltage suppression and insulation cooperation collaborative design scheme generation method and device based on particle swarm optimization algorithm, computer equipment and storage medium

Abstract

The embodiment of the invention relates to the field of power systems, and provides a collaborative design scheme generation method and device for submarine cable lightning overvoltage suppression and insulation cooperation based on a particle swarm optimization algorithm, computer equipment and a storage medium, and the method comprises the steps: carrying out the initial configuration of optimization basic data of a to-be-simulated experiment, constructing to obtain a simulation environment after initialization configuration; based on the simulation environment after initialization configuration, parallel electromagnetic transient program simulation is carried out so as to construct a bidirectional coupling framework simulation model of submarine cable lightning overvoltage suppression and insulation cooperation; and based on an improved hybrid particle swarm optimization algorithm, solving the bidirectional coupling framework simulation model to generate a collaborative design scheme corresponding to the submarine cable lightning overvoltage suppression and insulation cooperation process. By adopting the method, the overvoltage level of the submarine cable system and the technical implementation effect of insulation cooperation can be improved, and the safety of the system is improved.

Description

Technical Field

[0001] This application relates to the field of power system technology, and in particular to a method, apparatus, computer equipment, and storage medium for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm. Background Technology

[0002] In the field of power system technology, submarine cables are susceptible to lightning strikes, switching overvoltages, and system faults during operation, leading to insulation breakdown, partial discharge, and even system shutdown. Traditional overvoltage protection measures (such as surge arresters and shielding layers) are mostly passive responses, lacking optimized design for overall system insulation coordination, and are difficult to adapt to the multi-physics coupling problems in the complex marine environment.

[0003] Meanwhile, there is a highly nonlinear relationship between the insulation structural parameters of submarine cables (such as insulation thickness, shielding structure, grounding method, etc.) and overvoltage levels. Traditional design methods rely on experience or static simulation, making it difficult to achieve multi-objective optimization design.

[0004] In summary, the traditional technology for overvoltage level and insulation coordination in submarine cable systems is ineffective, reducing system safety. Summary of the Invention

[0005] This application provides a method, apparatus, computer equipment, and storage medium for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm. More specifically, this application provides a method, apparatus, computer equipment, computer storage medium, and computer program product for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm, which can improve the technical implementation effect of overvoltage level and insulation coordination of submarine cable system and enhance system safety.

[0006] In a first aspect, embodiments of this application provide a method for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm, including: The basic data for the simulation experiment is initialized and configured to build the simulation environment after initialization. Based on the simulation environment after initialization, parallel electromagnetic transient program simulation is performed to construct a two-way coupled framework simulation model of lightning overvoltage suppression and insulation coordination for submarine cables. Based on the improved hybrid particle swarm optimization algorithm, the simulation model of the bidirectional coupling framework is solved to generate a collaborative design scheme corresponding to the process of lightning overvoltage suppression and insulation coordination of submarine cables.

[0007] Secondly, embodiments of this application provide a device for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm. This device has the function of generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm, corresponding to the method provided in the first aspect above. This function can be implemented in hardware or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above function, and these modules can be software and / or hardware.

[0008] In one possible design, the device includes: The initialization configuration module is used to initialize the basic data for the simulation experiment and build the simulation environment after initialization. The simulation model construction module is used to perform parallel electromagnetic transient program simulation based on the simulation environment after initialization configuration, so as to construct a two-way coupled framework simulation model of lightning overvoltage suppression and insulation coordination of submarine cables. The scheme generation module is used to solve the bidirectional coupled framework simulation model based on the improved hybrid particle swarm optimization algorithm to generate a collaborative design scheme corresponding to the lightning overvoltage suppression and insulation coordination process of submarine cables.

[0009] In another aspect, this application provides a computer device including at least one connected processor and a memory, wherein the memory is used to store program code, and the processor is used to call the program code in the memory to execute the methods described in the above aspects.

[0010] In another aspect, embodiments of this application provide a computer storage medium including instructions that, when executed on a computer, cause the computer to perform the methods described in the above aspects.

[0011] In another aspect, this application provides a computer program product containing instructions that, when run on a computer, cause the computer to perform the methods described in the above aspects.

[0012] Compared with traditional technologies, the technical solution of this application achieves global optimization of surge arrester and cable parameters. Compared with single-physics field empirical selection, the design cycle is significantly shortened, the overall cost and lightning strike risk are significantly reduced, and the problems of excessive insulation or excessive margin are overcome. It can improve the technical implementation effect of overvoltage level and insulation coordination of submarine cable system, thereby improving the safety and economy of the system. Attached Figure Description

[0013] Figure 1 This is an application environment diagram from one embodiment; Figure 2This is a flowchart illustrating a method for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm in one embodiment. Figure 3 This is an overall flowchart of one embodiment; Figure 4 This is a structural block diagram of a device for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm in one embodiment. Figure 5 This is an internal structural diagram of a computer device in one embodiment; Figure 6 This is a diagram of the internal structure of a computer device in another embodiment. Detailed Implementation

[0014] The terms "first," "second," etc., used in the embodiments of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. The division of modules appearing in the embodiments of this application is only a logical division. In actual applications, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not performed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interface, and the indirect coupling or communication connection between modules may be electrical or other similar forms. None of these are limited in the embodiments of this application. Furthermore, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed among multiple circuit modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of this application.

[0015] Figure 1 As shown in the application environment diagram of one embodiment, this application provides a method for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm, which can be applied to, for example... Figure 1 In the application scenario shown, terminal 102 communicates with server 104 via a network.

[0016] The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0017] It should be noted that the terminal 102 involved in the embodiments of this application can be a wired terminal or a wireless terminal, and can be a device that provides voice and / or data connectivity to a user, a handheld device with wireless connectivity, or other processing devices connected to a wireless modem. The wireless terminal can communicate with one or more core networks via a wireless access network, and the wireless terminal can be a mobile terminal, such as a mobile phone or a computer with a mobile terminal.

[0018] Figure 2 This is a flowchart illustrating a method for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm in one embodiment. Figure 2 As shown in the embodiments of this application, the method for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm includes: S2100 initializes the basic data for the simulation experiment and builds the simulation environment after initialization.

[0019] Among them, optimizing the basic data refers to the various basic parameters used for the initial configuration of the simulation experiment, such as the parameters of the multiphysics model and environmental parameters; initial configuration refers to the parameter setting process for building the basic environment for the simulation experiment.

[0020] The simulation environment after initial configuration refers to the computing runtime environment that meets the simulation and optimization requirements after initial configuration.

[0021] S2200, based on the simulation environment after initial configuration, performs parallel electromagnetic transient program simulation to construct a two-way coupled framework simulation model of lightning overvoltage suppression and insulation coordination of submarine cables.

[0022] Among them, the parallel electromagnetic transient program simulation is an electromagnetic transient simulation operation that is executed synchronously by multiple processes.

[0023] The bidirectional coupling framework simulation model is implemented through an electromagnetic transient parallel simulation process, which specifically integrates the interactive coupling effect of electromagnetic field and thermomechanical field.

[0024] S2300, based on an improved hybrid particle swarm optimization algorithm, solves the bidirectional coupled frame simulation model to generate a collaborative design scheme for the process of lightning overvoltage suppression and insulation coordination of submarine cables.

[0025] The improved hybrid particle swarm optimization algorithm refers to the algorithm used to solve the model obtained by adaptively improving the particle swarm optimization algorithm in this application.

[0026] The collaborative design scheme is the output solution obtained after solving the problem. It is a comprehensive solution that takes into account both overvoltage suppression and insulation coordination in submarine cables. For example, in JSON format, the file corresponding to the collaborative design scheme can include data such as submarine cable parameters, protection equipment parameters, and performance indicators.

[0027] Compared to traditional technologies, in this embodiment, the optimized basic data for the simulation experiment is first initialized and configured to construct a simulation environment after initialization. Then, based on the initialized simulation environment, parallel electromagnetic transient program simulation is performed to construct a two-way coupled framework simulation model for lightning overvoltage suppression and insulation coordination of submarine cables. Finally, based on the improved hybrid particle swarm optimization algorithm, the two-way coupled framework simulation model is solved to generate a collaborative design scheme corresponding to the lightning overvoltage suppression and insulation coordination process of submarine cables. The technical solution of this embodiment achieves global optimization of surge arrester and cable parameters. Compared with single-physics field empirical selection, the design cycle is significantly shortened, the overall cost and lightning strike risk are significantly reduced, and the problems of excessive insulation or excessive margin are overcome. It can improve the technical implementation effect of overvoltage level and insulation coordination of submarine cable system, thereby improving the safety and economy of the system.

[0028] Optionally, in some embodiments of this application, the optimization base data for the simulation experiment is initialized and configured to construct the simulation environment after initialization, including: constructing a multiphysics model; inputting submarine cable routes and environmental parameters with preset data formats; generating a lightning waveform library; constructing a three-dimensional fitness function; and initializing the improved hybrid particle swarm optimization algorithm.

[0029] Among them, submarine cable routing refers to parameters such as the laying length, path, and joint locations of the submarine cable; environmental parameters are environmental data affecting the operation of the submarine cable, such as seawater temperature, salinity, and soil type. Preset data format refers to the standardized storage format of the parameters; in this solution, it is JSON format.

[0030] Among them, the lightning waveform library is a standardized waveform collection containing various direct lightning strike and induced lightning waveforms; Among them, the three-dimensional fitness function is a function that evaluates the merits of a scheme by comprehensively considering overvoltage, insulation margin, and cost.

[0031] The improved hybrid particle swarm optimization algorithm is an optimization algorithm that incorporates techniques such as hybrid coding and adaptive weights. For details of the improvements, please refer to the following embodiments.

[0032] In this embodiment, by constructing a multiphysics model, standardizing input parameters, and generating a lightning waveform library, the adaptability and stability of the simulation environment are improved, the startup reliability of the optimization algorithm is enhanced, and the efficiency and accuracy of subsequent optimization simulations are improved, providing a solid foundation for the optimization of submarine cable lightning protection.

[0033] Optionally, in some embodiments of this application, the construction of a multiphysics model includes: constructing an electromagnetic sub-model based on the mathematical expression of bidirectional coupling along a preset direction of the cable and the mathematical expression of the radial diffusion term; constructing a thermomechanical sub-model based on the mathematical expressions of the temperature field calculation, thermomechanical stress calculation, and insulation damage assessment; and determining the multiphysics model based on the electromagnetic sub-model and the thermomechanical sub-model.

[0034] Among them, the multiphysics model refers to a coupled simulation model that integrates multiple physical fields such as the electromagnetic sub-model and the thermomechanical sub-model. The electromagnetic sub-model is an electromagnetic transient simulation model built based on the bidirectional coupling and radial diffusion equations along the cable; the thermomechanical sub-model, also known as the thermo-mechanical sub-model, is a simulation model used to calculate temperature field, thermal stress, and insulation damage.

[0035] Among them, bidirectional coupling along the predetermined direction of the cable refers to coupling along the cable direction. x radial r Bidirectional coupling, or bidirectional coupling along the predetermined direction of the cable, is the electromagnetic parameter coupling mechanism of the submarine cable along its length and radial direction.

[0036] The radial diffusion term is an electromagnetic conduction equation that describes the penetration of the electric field between the seawater and sediment layers.

[0037] In this embodiment, by constructing an electromagnetic sub-model and a thermomechanical sub-model that integrate bidirectional coupling and radial diffusion characteristics respectively, a multiphysics coupling model is formed, which improves the accuracy and comprehensiveness of the simulation and enhances the ability to characterize the multiphysics response of submarine cables.

[0038] Optionally, in some embodiments of this application, the initialization of the improved hybrid particle swarm optimization algorithm includes: determining the encoding method of the improved hybrid particle swarm optimization algorithm based on hybrid encoding technology; and setting adaptive inertia weights for the improved hybrid particle swarm optimization algorithm.

[0039] Hybrid encoding technology combines real-number encoding and binary encoding to encode multiple types of variables. Adaptive inertia weights are particle swarm optimization (PSO) weight parameters that are dynamically adjusted as the iteration process progresses.

[0040] In this embodiment, by employing hybrid coding technology and setting adaptive inertia weights to complete the algorithm initialization, the algorithm's adaptability to multiple types of variables is improved, the ability to balance global search and local optimization is enhanced, and the efficiency and accuracy of subsequent optimization are improved.

[0041] For example, the initialization configuration process is step S1: the initialization phase, which establishes the foundation for optimization. This phase completes the initialization of the "model, parameters, objective function, and algorithm," providing input conditions for subsequent iterative optimization.

[0042] Among them, constructing a multiphysics model refers to step S11: establishing an electromagnetic simulation model + thermomechanical simulation multiphysics model.

[0043] In the electromagnetic sub-model, along the cable direction x radial r The mathematical expression for bidirectional coupling is as follows.

[0044] (1); in, C’ The capacitance per unit length of the cable core-sheath layer is expressed in Fm. -1 ; G’ Indicates the insulation conductivity per unit length, S m -1 ; L’ Hm represents the loop inductance per unit length. -1 ; R’ The resistance per unit length of the cable core, in Ω m -1 ; I Indicates the cable core current, in A; V This represents the voltage of the cable core relative to seawater, in V; The current density injected per unit length, Am -1 .

[0045] In the electromagnetic sub-model, the radial diffusion term (seawater-sediment layer) is mathematically expressed as follows.

[0046] (2); in, σ Sm represents the electrical conductivity of seawater. -1 ; Indicates the frequency of the current, in Hz; ε Fm represents the complex permittivity of seawater. -1 .

[0047] The mathematical expression of the thermo-mechanical sub-model is as follows.

[0048] (3); in, Density is expressed in kg / m³ 3(Different for aluminum / PE / seawater); C p Specific heat capacity, J k ¹ ¹(Different for aluminum / PE / seawater); k W represents thermal conductivity. ¹ ¹; T Indicates temperature, °C or K; This represents the volumetric Joule thermal power, in W. ³; W represents the radiative heat flux of a lightning channel. ³.

[0049] (4); in, Represents circumferential stress, Pa; This represents the elastic modulus of aluminum, expressed in Pa. Indicates the coefficient of linear expansion of aluminum. ¹; This represents the constraint strain of the protective layer, and is dimensionless. v This represents Poisson's ratio, which is dimensionless. δR / R Represents the relative change in radius, dimensionless; (5); in, This represents the lightning damage coefficient, which is dimensionless. This represents the temperature-dependent yield strength, expressed in Pa.

[0050] It should be noted that formulas (3), (4) and (5) in the above embodiments are the core physical field equations of the thermo-mechanical sub-model, which correspond to the three key links of "temperature field calculation, thermo-mechanical stress calculation, and insulation damage assessment". The specific calculation process can be as follows: first calculate the temperature distribution under lightning impact, then derive the stress from the temperature change, and finally assess the insulation damage based on the stress and temperature, thus forming a complete "thermal-stress-damage" coupling chain.

[0051] For example, inputting the submarine cable route and environmental parameters with a preset data format refers to step S12: inputting the submarine cable route and environmental JSON.

[0052] The input parameters are standardized using JSON format to facilitate subsequent algorithm calls and data interaction. The input content includes the submarine cable route and environmental parameters. The submarine cable route includes length, burial depth, laying path, and joint location; the environmental parameters include seawater temperature, salinity (affecting resistivity), seabed soil type, and historical lightning activity frequency.

[0053] For example, step S13: Generate a lightning waveform library.

[0054] In this embodiment, lightning is not a single waveform. A typical lightning waveform library (including current / voltage waveforms of direct lightning strikes and induced lightning) needs to be generated based on international standards. This application uses Monte Carlo sampling to randomly select samples from the waveform library to simulate random impact scenarios of "lightning of different intensities and types" to ensure the "robustness" of the optimized scheme to the actual lightning environment (rather than just adapting to a single extreme scenario).

[0055] The specific process of Monte Carlo sampling is as follows: Latin Hypercube 500 times / generation (PSO only uses the first 32 times per generation to accelerate convergence).

[0056] For example, constructing the three-dimensional fitness function refers to step S14: constructing the three-dimensional fitness function.

[0057] The fitness function is an "objective-oriented" optimization function; here it is a multi-objective function, and the meanings of the core variables are as follows.

[0058] Its function is essentially: to allocate weights to "security ( V max Margin E tot ")" and "economic efficiency" C cost The fitness function is transformed into a quantifiable fitness value, and the algorithm aims to minimize this value. The mathematical expression for the three-dimensional fitness function is: (6); in, V ref =0.85·LIWL (hard constraint upper limit), where LIWL represents the standard lightning impulse withstand level of the cable, in kV; E ref =20 kJ (single surge arrester 2 ms square wave reference); C ref =100 million yuan (engineering experience benchmark).

[0059] in, V max The maximum lightning overvoltage [kV] of the main insulation of the cable can be calculated and output by the multiphysics coupling model. E tot Total energy absorption requirement of surge arrester group [kJ]. Margin: (LIWL- V max ) / LIWL. C cost = n Surge arrester purchase cost + cable insulation incremental cost + offshore construction incremental cost [100 million yuan], where n represents the number of surge arresters. – Supports real-time adjustment of the slider, with default values ​​of 0.25 / 0.25 / 0.3 / 0.2c.

[0060] For example, performing the initialization of the improved hybrid particle swarm optimization algorithm refers to step S15: HPSO initialization.

[0061] This embodiment uses the particle swarm optimization (PSO) algorithm mathematical model, and the specific technical details are as follows.

[0062] This embodiment uses the original bird metaphor, where each bird is represented as a particle; the bird's position is represented as a candidate solution vector. The bird's speed is expressed as search direction / step length. Food sources are represented by fitness functions. F ( x The global minimum value of ).

[0063] This embodiment adopts the standard position-velocity update (continuous real numbers) update method. Specifically, for the first... i The particle, the first d dimension( d = 1…D (D represents the total dimension): (7); in, w It is inertial weight (exploration vs. exploitation); It is the cognitive coefficient (the particle's own memory); It is the social coefficient (swarm collective memory). , ~ U(0,1); This represents the optimal position found by the entire group so far.

[0064] This embodiment uses hybrid encoding, and the technical details of different segments in the encoding process are shown in the table below.

[0065]

[0066] In terms of hybrid encoding, the total dimension D = 3N + N = 4N, where N ≤ 30 (the upper limit of engineering experience). Therefore, the mathematical expression of the encoding in this embodiment is: = [ U ref , , …, Uref_N , E N LIWL , , …, b N ]; The improved strategy in this embodiment is to use an improved Hybrid Particle Swarm Optimization Algorithm (HPSO) with adaptive inertia weights: (8); Among them, the first section is large w Facilitates global search, and the backend is small. w It facilitates precise mining. K The maximum number of iterations. k This refers to the current iteration number.

[0067] Optionally, in some embodiments of this application, a bidirectional coupled framework simulation model is solved based on an improved hybrid particle swarm optimization algorithm to generate a collaborative design scheme corresponding to the process of lightning overvoltage suppression and insulation coordination of submarine cables. This includes: inputting preset model input data into the bidirectional coupled framework simulation model to obtain model output data associated with the model input data; determining preliminary solution results based on the model output data; calculating fitness values ​​to update individual or global optimal solutions when the preliminary solution results meet preset constraints; and determining a collaborative design scheme with a preset data format based on the updated individual or global optimal solutions when the number of iterations meets preset convergence conditions.

[0068] Among them, the two-way coupled frame simulation model is realized through the electromagnetic transient parallel simulation process, specifically referring to the submarine cable simulation model that integrates electromagnetic and thermomechanical field coupling.

[0069] The preset model input data includes: lightning current source, injection node number, electric field amplitude at the bottom of the current channel, submarine cable distribution parameter table, system topology and boundary data; the model output data includes: Joule heat element density, instantaneous total current of cable metal sheath, and radiative heat flux of lightning channel.

[0070] The preliminary solution result refers to the overvoltage peak value obtained from the preliminary calculation. V max Surge arrester spacing and surge arrester reference voltage U ref .

[0071] Among them, the preset constraints refer to the hard and soft constraints in the HPSO constraints, which are the hard and soft engineering restrictions for judging the compliance of the scheme.

[0072] Among them, the individual optimal solution is the optimal solution found by a single optimized particle; the global optimal solution is the optimal solution found by the entire particle swarm.

[0073] The preset convergence condition is the criterion for determining whether the optimization iteration should terminate. The preset convergence condition can be: the relative improvement of global fitness is less than 0.01% after 15 consecutive iterations or the maximum iteration limit. k ≥200.

[0074] In this embodiment, by improving the algorithm to solve the bidirectional coupled simulation model and iteratively updating the optimal solution, the accuracy and compliance of the collaborative design scheme are improved, the technical capability of submarine cable lightning protection is enhanced, and the optimization efficiency is improved.

[0075] For example, the process of solving the simulation model of the bidirectional coupled frame refers to step S2: the optimization iteration stage, which involves core calculations and iterations.

[0076] In the parallel electromagnetic transient simulation in step S21, the preset model input data is loaded into the bidirectional coupled simulation model, and the corresponding model output data is obtained. Then, the preliminary solution result is determined based on the output data.

[0077] The specific simulation configuration is as follows: Multi-threaded parallel technology with shared memory is employed, enabling 32 computational threads. The simulation speed is increased to 28 times the original benchmark through a decomposition strategy of the electromagnetic computation domain. Simultaneously, a graphics processing unit is used to accelerate the finite element sparse matrix solution process. Combined with an optimized sparse matrix library and conjugate gradient algorithm, the time required for a single-step electromagnetic field calculation is kept within 40 milliseconds.

[0078] During the simulation, input the following data into the electromagnetic transient simulation module to enable the bidirectional coupling framework of "electromagnetic transient simulation model + thermomechanical simulation".

[0079] The data input (model input data) includes: 1) Lightning current source, injection node number, and electric field amplitude at the bottom of the current channel in S13.

[0080] 2) Submarine cable distribution parameter table (temperature = initial 20℃): f , R (20℃) L ′(f), G (20℃) C’ Route length, segment node number, seawater-sediment layer σ , ε . C’ The capacitance per unit length of the cable core-sheath layer is expressed in Fm. -1 ; G’Indicates the insulation conductivity per unit length, S m -1 ; L’ Hm represents the loop inductance per unit length. -1 ; R’ The resistance per unit length of the cable core, in Ωm -1 ; σ Sm represents the electrical conductivity of seawater. -1 ; ε Fm represents the complex permittivity of seawater. -1 .

[0081] 3) System topology and boundaries: Thevenin equivalent RL of the first-end converter station and the last-end power grid. Initial position of the surge arrester (binary). b i =1 node number) and U ref Initial values. Time step Δt = 3 ns, total duration 2 ms, output node list.

[0082] The electromagnetic transient simulation module outputs the following data to the thermomechanical simulation module at each step (model output data): 1) Joule calorific density W ³; By cable segmentation r With time t The volumetric heat source term is given for the thermal equation used in the thermomechanical simulation module.

[0083] 2) I armor(t) , I armor(t) It is the "instantaneous total current of the cable's metal sheath (armor wire)," which is the "time-domain current waveform flowing through the armored steel wire (or lead sheath + armor)" directly read from the branch current output by the electromagnetic transient simulation module at the moment of arrester operation / lightning strike. The unit is A. It is used by the thermomechanical simulation module to calculate the electromagnetic force boundary (optional) and the additional Joule heat of the armor.

[0084] 3) Radiative heat flow from lightning channels [W ²] is applied uniformly along the entire cable line as the outer surface heat flow boundary.

[0085] The thermomechanical simulation module treats the "electromagnetic source" sent by the electromagnetic transient simulation module as the boundary / heat source, and calculates the radial temperature field of the cable according to formulas (3) and (4). T (r,t) With thermo-mechanical stress And give the insulation degradation coefficient. After the thermal solution is completed, T (r,t)Interpolate to each finite element node, and then update. σ (T) , ε (T) Then, rerun the frequency scan to obtain the value at the "current temperature". R ′、 L ′、 C ′、 G → To provide the electromagnetic transient simulation module for writing back to calculate the next electromagnetic transient.

[0086] The corresponding convergence criterion is: | T n – T n-1 |<0.1°C and| | < 0.5 MPa, here n This represents the number of calculations performed by the thermomechanical simulation module.

[0087] Among them, calculating the fitness value to update the optimal solution for individuals or the world when the preliminary solution results meet the preset constraints refers to steps S22 and S23.

[0088] Step S22: Determine whether the result of S21 satisfies the HPSO constraint.

[0089] The hard constraints in the HPSO constraint conditions are: V max < 0.85·LIWL; Surge arrester spacing ≥ 2 km; U ref ∈[1.2 U 0, 0.8 LIWL]. U 0 refers to the rated operating voltage, the long-term effective value of the cable system at power frequency [kV]; U ref This refers to the surge arrester reference voltage (RMS value), the valve plate voltage measured at 1mA DC, and the conduction threshold [kV].

[0090] Among them, the soft constraints in the HPSO constraints are E tot ≤ ∑ E single Cost ceiling ≤ 1.5 × initial design. E single The energy withstand capability of a single surge arrester for a 2 ms square wave [kJ].

[0091] In violation of hard constraint particle endowment F =1×10^6 (maximum penalty), immediate elimination. If the constraint is met, proceed to S23.

[0092] Step S23: Update the individual or global optimum.

[0093] For solutions that satisfy the constraints, calculate their fitness values. The specific calculation process includes: Individual optimal ( p best If the current particle's fitness value is greater than its historical best value, then update. p best Global optimal ( g best If the current particle's fitness value is greater than the historical best value of all particles, then update. g best (i.e., the current optimal solution for the entire population).

[0094] Among them, steps S24 and S25 refer to determining a collaborative design scheme with a preset data format based on the updated individual or global optimal solution when the number of iterations meets the preset convergence condition.

[0095] S24: HPSO convergence judgment.

[0096] If (the relative improvement in global fitness is less than 0.01% after 15 consecutive iterations) or the maximum iteration limit is reached... k ≥200 (default 200 generations to prevent infinite loops); returns the current gbest as the optimal surge arrester configuration and insulation level scheme.

[0097] If the convergence condition is not met, return to S21: Parallel Electromagnetic Transient Simulation. HPSO will then update the current surge arrester configuration and... C’ , G’ , L’ , R’ Updated to the electromagnetic transient simulation module.

[0098] S25: Output the JSON file of the optimal solution.

[0099] The contents of the JSON file include: 1) Submarine cable parameters: burial depth, insulation class.

[0100] 2) Protective equipment parameters: surge arrester model, grounding grid material / structure.

[0101] 3) Performance indicators: Maximum lightning overvoltage amplitude of cable main insulation V Max, safety margin, cost budget.

[0102] Optionally, in some embodiments of this application, the method further includes: during the execution of the collaborative design scheme, collecting online monitoring data based on pre-deployed monitoring equipment; determining the scheme evaluation results associated with the collaborative design scheme based on the online monitoring data; and performing rolling correction on the weights of the fitness function based on the scheme evaluation results.

[0103] The pre-deployed monitoring equipment refers to lightning monitoring instruments deployed along the submarine cable route. Online monitoring data is the real-time collection of actual lightning frequency data.

[0104] The evaluation result refers to the assessment result of whether the initial optimized solution is suitable for the current environment.

[0105] Rolling correction refers to dynamically and continuously adjusting the weights of each dimension index in the fitness function based on the actual results of each round of scheme evaluation.

[0106] For example, the method for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm provided in this application further includes step S3: subsequent monitoring and adjustment.

[0107] Lightning monitoring instruments are deployed along the submarine cable to collect real-time data on actual lightning frequencies, providing data support for subsequent "environmental drift assessment." Environmental drift refers to the deviation between the actual operating environment and the initial simulation assumptions (in this application, the frequency of lightning activity in the nearshore area suddenly increases).

[0108] Specifically, by comparing the "online monitoring data" with the "initial input environmental parameters", if the deviation is greater than the preset threshold (e.g., the change in lightning frequency is greater than 10%), it indicates that the initial optimization scheme may no longer be suitable for the current environment and needs to be re-optimized; if the deviation is less than or equal to the threshold, the scheme remains effective.

[0109] In addition, this application supports rolling self-correcting weights (triggered when environmental drift exceeds a threshold).

[0110] Specifically, this function does not directly reinitialize, but rather performs rolling self-correction. This includes: adjusting the "..." based on the direction of environmental drift (e.g., increasing the frequency of lightning). V max "Constraint weights", update the weights of the fitness function, increase The value is then returned to step S21 for iterative optimization to achieve "dynamic adaptation".

[0111] In this embodiment, by conducting online monitoring and scheme evaluation and rolling correction of the fitness function weights, the adaptability of the collaborative design scheme to environmental changes is improved, the dynamic adjustment capability of the scheme is enhanced, and the long-term reliability of submarine cable lightning protection is improved.

[0112] The technical research process and other technical details of this application are described below with reference to a specific embodiment.

[0113] A conventional technology provides an overvoltage suppression scheme, specifically including: 1) Arrestor placement: Installing metal oxide surge arresters (MOA) at both ends and intermediate joints of the submarine cable is the most common method; 2) Parallel reactor + neutral point small reactor: To address the "power frequency overvoltage + reactive power excess" problem in long-distance AC submarine cables, high-voltage line reactors (50–150MVar) are commonly used, with a small reactor (500–800Ω) connected in series at the neutral point to suppress resonant overvoltage; this needs to be considered for distances >31.6km. 3) Metal sheath protector: A sheath protector is installed at the insulation joint of a single-ended grounding or cross-connection section. The residual voltage of 10kA is ≤25kV. It is used to clamp the sheath overvoltage during short circuits or lightning strikes.

[0114] 4) SVG / SVC Dynamic Reactive Power Compensation: The offshore wind farm is equipped with ±30–50MVar SVG, which can generate / absorb reactive power within 50ms and suppress transient overvoltage to below 1.2pu; when combined with parallel reactors, it forms a “segmented-dynamic” synergistic suppression.

[0115] 5) Special lightning protection measures for the landing section: Lightning protection wires and coupling ground wires are installed at the connection between the landing section and the overhead line, and a primary lightning arrester is installed in the transfer well; the impulse grounding resistance is ≤5Ω, which can reduce the amplitude of lightning intrusion waves by 30–40%.

[0116] A conventional technology provides an existing solution for insulation coordination and design, specifically including: 1) "Simulation-Verification" Insulation Coordination: Establish an electromagnetic transient model of the submarine cable, calculate the three overvoltages of power frequency, switching and lightning respectively → select the insulation level according to GB / Z 24841 → verify the XLPE thickness and margin.

[0117] 2) Empirical formula method for insulation thickness: Currently, engineering projects still mostly use the empirical value of "electric field strength ≤ 12kV / mm (long-term) / 15kV / mm (short-term)" to back-calculate the thickness; there is a lack of quantitative optimization that is directly linked to the overvoltage probability distribution.

[0118] 3) Coordination of metal sheath grounding methods: Cross-interconnection + single-point grounding can significantly reduce sheath circulating current and induced voltage, but will generate transient overvoltage at the ungrounded end; the current practice is to make a compromise between "induced voltage ≤100V (normal operation)" and "sheath protector residual voltage ≤25V (transient)".

[0119] 4) Pareto multi-objective trade-offs: Some studies have introduced a two-dimensional Pareto frontier of cost-insulation margin, but the optimization variables only reach the level of "reactor capacity and compensation degree", and have not yet been reduced to structural parameters such as "insulation thickness and shielding diameter".

[0120] 5) Standard-Specification System: The specifications provide recommended value ranges and only offer a general description of "collaborative optimization," without providing automatic optimization algorithms or closed-loop design processes.

[0121] Regarding cable overvoltage suppression and insulation coordination, one implementation scheme integrates zinc oxide components, high-voltage vacuum circuit breakers, waveform recorders, temperature controllers, and fans into an "integrated handcart," allowing for complete removal and convenient maintenance. Forced air cooling and dual-threshold temperature control (≥1 level starts the fan, ≥2 level directly trips) address the issue of high-heat aging of valve plates, theoretically doubling their lifespan. However, the cabinet size is significantly larger than traditional surge arresters, imposing stringent space requirements on community substations and underground stations; the handcart track and valves increase initial costs by approximately 30% to 40%. With the fan, drive motor, and control power supply all centralized, loss of power to any component results in the loss of active cooling and automatic shutdown functions, and the reliability model lacks redundancy design. While the 13.2kV ​​protection limit is low, it means the valve plate charge rate is >0.85, accelerating aging under long-term energization; if the fan stops, the temperature rise rate is higher than that of ordinary surge arresters.

[0122] In another implementation, the overvoltage of the three layers—tower, armor, shield, and core wire—is incorporated into the probabilistic assessment in one go, avoiding blind spots in single-point assessments and explaining the true cause of lightning tripping. The introduction of IEEE lightning current cumulative probability and Heidler waveforms marks the first time that the "return stroke sequence" has been quantified into wind power lightning protection design, a leading academic achievement. A cost-benefit comprehensive index W is provided, allowing operators to dynamically select solutions (≥80% or ≥90% lightning withstand probability), which has direct value for insurance pricing and wind farm transactions. However, the critical lightning current is derived from a simplified circuit model simulation and has not been cross-validated with actual field measurements of real wind turbines (e.g., blade down conductor current shunting coefficient), so the error range is unknown. The probabilistic model assumes that each return stroke is independent; in reality, multiple return strokes have a thermal accumulation effect, which may underestimate the risk of shield breakdown. Only the "cable" segment is assessed; overvoltage coupling of downstream equipment such as transformer substations and ring main units is not modeled, which may deviate from the overall system economics.

[0123] In another implementation scheme, a complete insulation coordination process for a "diode uncontrolled rectification + low-frequency AC" power transmission system is presented for the first time, filling a gap in the standard. A three-step closed-loop system of simulation, verification, and selection can directly output surge arrester parameter tables, demonstrating strong engineering feasibility. A charge rate-reference voltage comparison table is provided, which can be applied by design units with a single click, reducing trial-and-error costs. However, all conclusions are based on offline electromagnetic transient simulation models, lacking a closed-loop system of measured data, and insufficiently considering the distribution parameters of submarine cables and the randomness of seawater temperature / salinity. Only "operating overvoltage" is used as a constraint, without quantifying combined operating conditions such as lightning and fault reclosing, potentially leading to an overly optimistic insulation margin. The surge arrester placement principle follows onshore DC experience, without addressing the mechanical-thermal coupling aging of floating foundations and dynamic cables.

[0124] In another implementation, the lightning rod-zinc oxide-grounding wire is made into an "external cable jacket," eliminating the need for a separate lightning protection tower on site. The hydraulic-pulley anti-breakage mechanism can clamp the cable online, with a wind resistance of >2kN, theoretically reducing the breakage rate during thunderstorms and strong winds by more than 50%. The silicone rubber umbrella skirt + central spring structure allows for on-site valve plate replacement, eliminating the need for complete cable dismantling during maintenance and reducing power outage time. However, this increases the overall thickness and weight by approximately 15% to 20%, posing a challenge to the load margin of older towers and bridge sections; a structural review is required. The lightning rod extending 1-1.5m above the cable may actually act as a "lightning attractor," increasing the probability of side strikes if the grounding resistance is >4Ω; improper design can be counterproductive. The significant difference in thermal expansion coefficients between the zinc oxide valve plate and the cable sheath means that after long-term cycles of sunlight and heavy rain, partial discharge may occur due to micro-air gaps at the interface; the lifespan model has not yet been verified.

[0125] In another implementation scheme, "intermittent load of electrified railways" is used as the induced overvoltage correction term for the first time. FFT is used to extract harmonic current-mutual inductance coupling, addressing the underestimation of sheath overvoltage in parallel sections of urban rail and high-speed rail. A four-level screening method—"state coefficient ZP-insulation resistance prediction-hazard level-index correction factor"—is employed, with clear logic and software-based implementation, suitable for provincial grid companies to implement batch technical upgrade schemes. However, it relies entirely on historical database matching; if regional data is missing (newly built lines, remote mountainous areas), the similarity algorithm will fail, leading to selection drift. The mutual inductance M in the correction formula is a fixed value, failing to consider cable segmentation, sheath cross-interconnection, and seasonal variations in soil resistivity, potentially overestimating or underestimating the induced voltage.

[0126] Traditional technologies have covered a multi-level suppression system of "surge arrester-reactor-sheath protection-reactive power compensation" and can perform insulation coordination verification through electromagnetic transient simulation; however, they are still largely at the stage of "component selection + experience margin," and have not yet formed a multi-objective automatic optimization and closed-loop feedback system encompassing "structural parameters-overvoltage-insulation life-cost." Specifically, traditional technologies have the following shortcomings: 1) Surge arresters, reactors, and insulation thickness are selected independently, lacking an integrated collaborative search encompassing structure, electrical systems, and cost. 2) Reliance on experience or static simulation is lacking, failing to establish a multi-objective quantitative optimization model considering overvoltage probability, insulation failure probability, lifespan, and cost. 3) No online closed-loop system: design values ​​are fixed, preventing dynamic adjustment of compensation or protection strategies based on operational monitoring data (fiber optic temperature measurement, partial discharge, lightning strikes). 4) Insufficient consideration is given to new high-proportion renewable energy grid-connected scenarios (offshore wind power, flexible DC transmission); existing standards are based on traditional AC systems.

[0127] Based on this, this application provides a method for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm. This method can also be called a collaborative design method for overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm, a method for lightning overvoltage protection and insulation coordination of submarine cables based on particle swarm optimization algorithm, an intelligent optimization method, or simply the scheme generation method provided in this application. Details are as follows.

[0128] The solution generation method provided in this application solves the problems of inaccurate insulation structure design and lack of system optimization in overvoltage control in traditional technologies, improves the anti-interference capability and operational reliability of submarine cable systems, and realizes the synergistic optimization of overvoltage level and insulation coordination of submarine cable systems, thereby improving system safety and economy.

[0129] The scheme generation method provided in this application establishes a lightning-electromagnetic-thermal-mechanical coupled simulation model, constructs a three-dimensional comprehensive fitness function of overvoltage amplitude, energy, insulation margin, and cost, and adopts an improved hybrid particle swarm optimization algorithm to simultaneously optimize the number, location, parameters, and cable insulation level of surge arresters in one go, achieving a multi-objective balance with minimum global cost and maximum margin; and supports rolling self-correction based on online monitoring data to solve the problem of insulation coordination failure caused by long-term environmental drift.

[0130] Figure 3 This is an overall flowchart of one embodiment. For example... Figure 3 As shown, the solution generation method provided in this application includes steps S1, S2 and S3, as detailed below.

[0131] S1: Initialization phase, establishing and optimizing the foundation.

[0132] This stage initializes the "model, parameters, objective function, and algorithm," providing input conditions for subsequent iterative optimization. Step S1 includes steps S11 to S15.

[0133] S11: Establish an electromagnetic simulation model + thermomechanical simulation multiphysics model.

[0134] Specifically, it is constructed using an electromagnetic sub-model and a thermo-mechanical sub-model.

[0135] S12: Input submarine cable routing and environment JSON.

[0136] The input parameters are standardized using JSON format to facilitate subsequent algorithm calls and data interaction. The input content includes submarine cable routes and environmental parameters.

[0137] S13: Generate a lightning waveform library.

[0138] S14: Construct the three-dimensional fitness function.

[0139] S15: HPSO initialization.

[0140] The mathematical model of this particle swarm optimization algorithm uses the original bird metaphor, where each bird is represented as a particle; the position of the bird is represented as a candidate solution vector. The bird's speed is expressed as search direction / step length. Food sources are represented by fitness functions. F ( x The global minimum value of ) is determined. A standard position-velocity update mode is used, employing hybrid encoding; adaptive inertial weights are set.

[0141] S2: Optimization and iteration phase, core calculations and iterations.

[0142] Step S2 includes steps S21 to S25.

[0143] S21: Parallel electromagnetic transient simulation.

[0144] S22: Determine whether the result of S21 satisfies the HPSO constraint.

[0145] HPSO constraints include hard constraints and soft constraints. Violation of a hard constraint results in immediate elimination. If the constraint is satisfied, proceed to step S23.

[0146] S23: Update the individual or global optimum.

[0147] For a scheme that satisfies the constraints, calculate its fitness value.

[0148] S24: HPSO convergence judgment.

[0149] If the convergence condition is met, the current gbest is returned as the optimal surge arrester configuration and insulation level scheme.

[0150] If the convergence condition is not met, return to step S21: Parallel electromagnetic transient simulation. HPSO will update the current surge arrester configuration and... C’ , G’ , L’ , R’ Updated to electromagnetic transient simulation model.

[0151] S25: Output the JSON file of the optimal solution.

[0152] S3: Subsequent monitoring and adjustments.

[0153] If monitoring reveals that the initial optimization scheme is no longer suitable for the current environment, it needs to be re-optimized, and rolling self-correcting weights are supported.

[0154] The scheme generation method provided in this application offers a way to simultaneously optimize the "surge arrester configuration (quantity, location, reference voltage)". U ref The global optimization method of “cable insulation level (lightning impulse withstand voltage LIWL)” and “cable insulation level (lightning impulse withstand voltage LIWL)” achieves a balance of three objectives: minimum overall cost, maximum insulation margin, and optimal energy dissipation.

[0155] The solution generation method provided in this application solves the problem that traditional methods can only be designed offline once and cannot self-correct as environmental parameters drift, thus enabling the system to have the ability of "rolling optimization".

[0156] In traditional technologies, the design of lightning protection for submarine cables generally adopts an "experience + verification" model: first, the rated voltage and energy of the surge arrester are given according to the specifications, and then, with the help of electromagnetic transient simulation tools, parameters are repeatedly adjusted through manual calculations to verify the overvoltage level under different lightning current amplitudes until the insulation coordination specifications are met. This process is time-consuming, relies on the engineer's experience, and can only obtain a "feasible solution," not a "globally optimal solution."

[0157] The scheme generation method provided in this application uses particle swarm optimization to simultaneously weigh the entire lightning electromagnetic-thermal-mechanical-cost link and depreciate insulation strength in real time, thereby achieving global optimization of the parameters of the surge arrester and cable.

[0158] The scheme generation method provided in this application significantly shortens the design cycle, reduces overall cost and lightning strike risk, and eliminates excessive insulation or inflated margins compared to single-physics field empirical selection.

[0159] It should be noted that any technical feature in any of the above embodiments provided in this application is also applicable to any of the following embodiments provided in this application, and similar details will not be repeated hereafter.

[0160] Figure 4 This is a structural block diagram of a device for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm in one embodiment. (Refer to...) Figure 4 The device includes: The initialization configuration module 401 is used to initialize the basic data of the simulation experiment to be simulated and build the simulation environment after initialization configuration. The simulation model construction module 402 is used to perform parallel electromagnetic transient program simulation based on the simulation environment after initial configuration, so as to construct a two-way coupled framework simulation model of lightning overvoltage suppression and insulation coordination of submarine cables. The scheme generation module 403 is used to solve the bidirectional coupled framework simulation model based on the improved hybrid particle swarm optimization algorithm to generate a collaborative design scheme corresponding to the lightning overvoltage suppression and insulation coordination process of submarine cables.

[0161] In this embodiment of the application, based on, as follows Figure 4 The connection relationships between the various modules or units shown in the diagram can improve the technical implementation effect of overvoltage level and insulation coordination in submarine cable systems through the cooperation between these modules or units, thereby enhancing the safety of the system.

[0162] In another embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, it includes a processor, memory, input / output interfaces, and a communication interface. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface is connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores relevant data. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. The computer program can be executed by the processor to implement the various methods described in the above embodiments.

[0163] In yet another embodiment, a computer device is provided, such as a terminal, whose internal structure diagram may be as follows: Figure 6As shown, it includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. The computer program can be executed by the processor to implement the various methods described in the above embodiments.

[0164] Those skilled in the art will understand that Figure 5 and Figure 6 The structure shown is only a block diagram of a part of the structure related to the solution of this application, and does not constitute a limitation on the computer device on which the solution of this application is applied. It may also include more or fewer components than shown in the figure, or combine some components, or have different component arrangements, so as to realize the function of the terminal or server.

[0165] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0166] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the systems, devices, equipment, modules or units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0167] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, devices, or methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0168] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0169] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0170] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0171] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium, or a semiconductor medium (e.g., a solid-state drive), etc.

[0172] The technical solutions provided by the embodiments of this application have been described in detail above. Specific examples have been used in the embodiments of this application to illustrate the principles and implementation methods of the embodiments of this application. The description of the above embodiments is only for the purpose of helping to understand the methods and core ideas of the embodiments of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the embodiments of this application. Therefore, the content of this specification should not be construed as a limitation on the embodiments of this application.

Claims

1. A method for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm, characterized in that, The method includes: The basic data for the simulation experiment is initialized and configured to build the simulation environment after initialization. Based on the simulation environment after initialization, parallel electromagnetic transient program simulation is performed to construct a two-way coupled framework simulation model of lightning overvoltage suppression and insulation coordination for submarine cables. Based on the improved hybrid particle swarm optimization algorithm, the simulation model of the bidirectional coupled framework is solved to generate a collaborative design scheme corresponding to the process of lightning overvoltage suppression and insulation coordination of submarine cables.

2. The method according to claim 1, characterized in that, The initialization configuration of the optimized basic data for the simulation experiment, and the construction of the initialized simulation environment, includes: A multiphysics model is constructed; the submarine cable route and environmental parameters with a preset data format are input; a lightning waveform library is generated; a three-dimensional fitness function is constructed; and the improved hybrid particle swarm optimization algorithm is initialized.

3. The method according to claim 2, characterized in that, The constructed multiphysics model includes: An electromagnetic sub-model is constructed based on the mathematical expressions for bidirectional coupling along the predetermined direction of the cable and the mathematical expressions for radial diffusion terms. Based on the mathematical expressions of the temperature field calculation, thermomechanical stress calculation, and insulation damage assessment, a thermomechanical sub-model is constructed. The multiphysics model is determined based on the electromagnetic sub-model and the thermomechanical sub-model.

4. The method according to claim 2, characterized in that, The initialization of the improved hybrid particle swarm optimization algorithm includes: The encoding method of the improved hybrid particle swarm optimization algorithm is determined based on hybrid encoding technology; An adaptive inertia weight is set for the improved hybrid particle swarm optimization algorithm.

5. The method according to claim 1, characterized in that, The improved hybrid particle swarm optimization algorithm is used to solve the bidirectional coupled framework simulation model to generate a collaborative design scheme for the lightning overvoltage suppression and insulation coordination process of submarine cables, including: The preset model input data is input into the bidirectional coupled frame simulation model to obtain the model output data associated with the model input data, and the preliminary solution result is determined based on the model output data. If the preliminary solution results satisfy the preset constraints, the fitness value is calculated to update the optimal solution for the individual or the global solution; If the number of iterations meets the preset convergence condition, the collaborative design scheme with a preset data format is determined based on the updated optimal solution for the individual or global problem.

6. The method according to claim 5, characterized in that, The model input data includes: lightning current source, injection node number, electric field amplitude at the bottom of the current channel, submarine cable distribution parameter table, system topology and boundary data; the model output data includes: Joule heat element density, instantaneous total current of the cable metal sheath, and radiative heat flux of the lightning channel.

7. The method according to claim 1, characterized in that, The method further includes: During the execution of the collaborative design scheme, online monitoring data is collected based on pre-deployed monitoring equipment; The evaluation results of the collaborative design scheme are determined based on the online monitoring data. The weights of the fitness function are adjusted using a rolling process based on the evaluation results of the proposed scheme.

8. A device for generating a collaborative design scheme for lightning overvoltage suppression and insulation coordination of submarine cables based on particle swarm optimization algorithm, characterized in that, The device includes: The initialization configuration module is used to initialize the basic data for the simulation experiment and build the simulation environment after initialization. The simulation model construction module is used to perform parallel electromagnetic transient program simulation based on the simulation environment after initialization configuration, so as to construct a two-way coupled framework simulation model of lightning overvoltage suppression and insulation coordination of submarine cables. The scheme generation module is used to solve the bidirectional coupled framework simulation model based on the improved hybrid particle swarm optimization algorithm to generate a collaborative design scheme corresponding to the lightning overvoltage suppression and insulation coordination process of submarine cables.

9. A computer device, characterized in that, The computer device includes: At least one processor and memory; The memory is used to store program code, and the processor is used to call the program code stored in the memory to execute the method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, It includes instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 7.

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