A dynamic current carrying regulation method and device of a submarine cable, an electronic device, and a storage medium

Abstract

This invention discloses a method, device, electronic device, and storage medium for dynamic current-carrying regulation of submarine cables, belonging to the field of power system technology. The method comprises: acquiring real-time temperature data and real-time current data of the submarine cable; inputting the real-time temperature data and real-time current data into a preset cable temperature prediction model, so that the cable temperature prediction model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, and obtains the predicted peak conductor temperature of the submarine cable; calculating the current increment value that the submarine cable can be upgraded with based on the predicted peak conductor temperature and a preset upper limit insulation temperature, and matching the corresponding cable capacity expansion strategy to dynamically regulate the current-carrying capacity of the submarine cable. Therefore, by implementing this invention, the problem of the inability to dynamically regulate the current-carrying capacity of submarine cables in the prior art can be solved.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a dynamic current-carrying regulation method, device, electronic equipment, and storage medium for submarine cables. Background Technology

[0002] High-voltage direct current (HVDC) submarine cables are key equipment for long-distance, transoceanic high-power power transmission, undertaking important tasks such as offshore wind power transmission, island interconnection, and intercontinental power trading. The bottleneck in their operational safety and current-carrying capacity mainly comes from thermal stability, that is, under long-term current load, the temperature that the conductor and insulation materials can withstand must not exceed a certain limit.

[0003] However, existing engineering designs generally adopt a conservative approach, setting a fixed current-carrying limit based on the maximum ambient temperature. While this ensures safety, in actual operation, frequent load changes and favorable environmental conditions often lead to long-term idle capacity of submarine cables, resulting in resource waste and rigid scheduling. Against this backdrop, how to adjust the current-carrying capacity on demand based on the real-time temperature of the cable's operating status is a crucial breakthrough direction for improving the utilization efficiency of transmission channels and building a flexible smart grid. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for dynamic current-carrying regulation of submarine cables, which can solve the problem that existing technologies cannot dynamically regulate the current-carrying capacity of submarine cables.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a dynamic current-carrying regulation method for submarine cables, comprising: Acquire real-time temperature and current data of submarine cables; The real-time temperature data and real-time current data are input into a preset cable temperature prediction model, so that the cable temperature prediction model can predict the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, and obtain and output the predicted peak conductor temperature of the submarine cable; Based on the predicted peak conductor temperature and the preset upper limit insulation temperature, the current increment value that can be increased in the submarine cable is calculated, and the corresponding cable capacity increase strategy is matched in the preset mapping table according to the current increment value. Then, the current carrying capacity of the submarine cable is dynamically adjusted according to the cable capacity increase strategy.

[0006] As a preferred embodiment, the cable temperature prediction model includes: a physical equivalent sub-model, a data-driven sub-model, and a Kalman filter fusion layer; The physical equivalent sub-model is an equivalent thermal resistance-thermal capacity network established based on the heating of the cable conductor and the radial heat transfer of the cable, and the data-driven sub-model is an LSTM network. The step of predicting the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtaining and outputting the predicted peak conductor temperature of the submarine cable, includes: The physical equivalent sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the first predicted temperature data of the submarine cable, and transmits the first predicted temperature data to the Kalman filter fusion layer. The data-driven sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the second predicted temperature data of the submarine cable, and transmits the second predicted temperature data to the Kalman filter fusion layer. The Kalman filter fusion layer performs a weighted summation of the first and second predicted temperature data to obtain and output the predicted peak conductor temperature of the submarine cable.

[0007] As a preferred embodiment, the step of calculating the incremental current value that can be increased in capacity for the submarine cable based on the predicted peak conductor temperature and the preset upper limit insulation temperature, and matching the corresponding cable capacity increase strategy in a preset mapping table according to the incremental current value, includes: Based on the predicted peak conductor temperature and the preset upper limit insulation temperature, calculate the current temperature margin of the submarine cable, and calculate the allowable current increment value under the current temperature margin. Based on the current temperature margin and the current increment value, a corresponding cable capacity expansion strategy is matched in a preset mapping table.

[0008] As a preferred embodiment, the current increment value is calculated according to the following formula; ; ; in, This is the current increment value. As the current temperature margin, Here, t represents the thermal characteristic coefficient of the cable structure, and t represents the current time. To predict duration, For the future Predicted peak conductor temperature within the range, The prediction time interval for forecasting the peak temperature of the conductor; This is the upper limit temperature for insulation.

[0009] Based on the above embodiments, another embodiment of the present invention provides a dynamic current-carrying regulation device for submarine cables, including: a data acquisition module, a temperature prediction module, and a current-carrying regulation module; The data acquisition module is used to acquire real-time temperature data and real-time current data of the submarine cable. The temperature prediction module is used to input the real-time temperature data and real-time current data into a preset cable temperature prediction model, so that the cable temperature prediction model can predict the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, and obtain and output the predicted peak conductor temperature of the submarine cable; The current-carrying regulation module is used to calculate the current increment value that the submarine cable can be increased in capacity based on the predicted peak conductor temperature and the preset upper limit insulation temperature, and to match the corresponding cable capacity increase strategy in the preset mapping table according to the current increment value, and then to dynamically regulate the current-carrying capacity of the submarine cable according to the cable capacity increase strategy.

[0010] As a preferred embodiment, the cable temperature prediction model includes: a physical equivalent sub-model, a data-driven sub-model, and a Kalman filter fusion layer; The physical equivalent sub-model is an equivalent thermal resistance-thermal capacity network established based on the heating of the cable conductor and the radial heat transfer of the cable, and the data-driven sub-model is an LSTM network. The step of predicting the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtaining and outputting the predicted peak conductor temperature of the submarine cable, includes: The physical equivalent sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the first predicted temperature data of the submarine cable, and transmits the first predicted temperature data to the Kalman filter fusion layer. The data-driven sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the second predicted temperature data of the submarine cable, and transmits the second predicted temperature data to the Kalman filter fusion layer. The Kalman filter fusion layer performs a weighted summation of the first and second predicted temperature data to obtain and output the predicted peak conductor temperature of the submarine cable.

[0011] As a preferred embodiment, the step of calculating the incremental current value that can be increased in capacity for the submarine cable based on the predicted peak conductor temperature and the preset upper limit insulation temperature, and matching the corresponding cable capacity increase strategy in a preset mapping table according to the incremental current value, includes: Based on the predicted peak conductor temperature and the preset upper limit insulation temperature, calculate the current temperature margin of the submarine cable, and calculate the allowable current increment value under the current temperature margin. Based on the current temperature margin and the current increment value, a corresponding cable capacity expansion strategy is matched in a preset mapping table.

[0012] As a preferred embodiment, the current increment value is calculated according to the following formula; ; ; in, This is the current increment value. As the current temperature margin, Here, t represents the thermal characteristic coefficient of the cable structure, and t represents the current time. To predict duration, For the future Predicted peak conductor temperature within the range, The prediction time interval for forecasting the peak temperature of the conductor; This is the upper limit temperature for insulation.

[0013] Based on the above embodiments, another embodiment of the present invention provides an electronic device, the device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the dynamic current-carrying control method for submarine cables described in the above embodiments of the invention.

[0014] Based on the above embodiments, another embodiment of the present invention provides a storage medium, the storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the dynamic current-carrying regulation method for submarine cables described in the above embodiments of the invention.

[0015] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: This invention provides a method, apparatus, electronic device, and storage medium for dynamic current-carrying regulation of submarine cables. The method includes: acquiring real-time temperature data and real-time current data of the submarine cable; inputting the real-time temperature data and real-time current data into a preset cable temperature prediction model, so that the cable temperature prediction model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains and outputs the predicted peak conductor temperature of the submarine cable; calculating the current increment value that the submarine cable can be upgraded with based on the predicted peak conductor temperature and a preset upper limit insulation temperature, and matching the corresponding cable capacity-upgrading strategy in a preset mapping table based on the current increment value, and then performing dynamic current-carrying regulation of the submarine cable according to the cable capacity-upgrading strategy.

[0016] Compared to existing technologies that directly set a fixed current-carrying limit based on the maximum ambient temperature, this invention first acquires real-time temperature and current data of the submarine cable. Then, based on this data, it predicts the temperature evolution trend along the optical fiber inside the cable. Next, it matches an adaptive cable capacity expansion strategy based on the predicted peak conductor temperature, and dynamically regulates the current-carrying capacity of the submarine cable according to the strategy. This invention enables dynamic current-carrying control of submarine cables, improving the flexibility of power grid operation and the efficiency of transmission channel utilization. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a dynamic current-carrying control method for submarine cables according to an embodiment of the present invention. Figure 2 This is a cross-sectional view of the submarine cable and a diagram showing the location of the optical fiber layout. Figure 3 This is a flowchart of real-time temperature data acquisition and processing. Figure 4 This is a diagram of the predictive fusion architecture of physical models and data-driven models; Figure 5 It is a curve comparing predicted temperature and measured temperature; Figure 6 This is a comparison chart of static and dynamic current carrying capacity; Figure 7 This is a schematic diagram of the structure of a dynamic current-carrying control device for a submarine cable according to an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0020] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0023] In the description of the embodiments of this application, the terms "multiple" and "several" refer to two or more (including two), similarly, "multiple groups" refer to two or more (including two groups), and "multiple pieces" refer to two or more (including two pieces).

[0024] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0025] Example 1 Please refer to Figure 1 To address the problem of the inability to dynamically regulate the current-carrying capacity of submarine cables in existing technologies, this invention provides a flowchart illustrating a method for dynamic current-carrying capacity regulation of submarine cables. The overall approach involves forming a layered temperature sensing network within the cable body that can operate for extended periods, and organically coupling this network with edge computing data governance, physical-data fusion thermal response modeling, and a secure and controllable scheduling execution link. This allows for real-time optimization of current-carrying capacity without breaching insulation safety boundaries. The specific steps include: S1. Obtain real-time temperature and current data of the submarine cable; In a specific embodiment, for step S1 above, the real-time temperature data of the submarine cable is first monitored and acquired. Existing monitoring schemes often employ fiber-optic distributed temperature sensing systems laid externally on the submarine cable. However, this method cannot accurately reflect the temperature changes of the conductors and insulation layers inside the cable, is highly susceptible to external environmental interference, and suffers from significant monitoring delays, making it difficult to support dynamic current-carrying control requirements. To address these issues, this invention innovatively proposes embedding fiber optic channels in three key locations: the center of the submarine cable conductor, the insulation shield layer, and the armor layer, forming a multi-layer embedded distributed temperature monitoring system. By synchronously collecting temperature data from each layer, a thermal gradient analysis and thermal response model are constructed and linked with a current-temperature rise dynamic hysteresis mechanism, achieving real-time, refined analysis of the submarine cable's operating temperature, thereby providing high-precision support for dynamic current-carrying control. This structure not only breaks through existing technological bottlenecks in thermal response monitoring but also provides a reliable multi-source data foundation for dynamic capacity expansion algorithms.

[0026] For details, please refer to Figure 2 This diagram shows the overall cross-sectional structure of the submarine cable and the location of the optical fiber deployment. The cable structure preferably uses hollow copper stranded conductors. A first layer of high-temperature resistant distributed optical fiber is embedded in the axial capillary channel to sense Joule heating of the conductor in situ. A second layer of optical fiber is laid in a ring or spiral groove between the main insulation and the semi-conductive shielding layer to capture radial heat diffusion and hotspot evolution. A third layer of optical fiber is formed inside the metal armor tape or under the sheath layer to reflect external cooling conditions and environmental disturbances. The three layers of optical fiber are continuously deployed along the longitudinal direction of the line and led out to the distributed temperature sensing (DTS) at the landing end via optical switchers.

[0027] exist Figure 2 The components and functions of a submarine cable are as follows: Copper conductors: the main current channel, responsible for transmitting high-current (HVDC); Conductor shielding layer: Creates a uniform electric field between the conductor and the insulation to prevent insulation breakdown caused by localized electric field concentration; Insulating layer: withstands HVDC voltage and provides electrical isolation between the conductor and the outer metal layer; Insulating shielding layer: works in conjunction with the insulating layer to ensure a uniform distribution of the electric field on the outer surface of the insulating layer; Water-blocking buffer layer: Prevents moisture from entering the insulation system, while providing mechanical cushioning to prevent the metal sleeve from compressing and damaging the insulation; Alloy lead sleeve: a metal protective barrier, mainly used to block water and withstand radial pressure; Polyethylene sheath: Provides electrical insulation and mechanical protection to the alloy lead sheath, preventing direct contact between the metal and the outside environment; Polypropylene inner padding layer: forms a buffer between the sheath and the armor layer, and evenly distributes the armor stress; Armor layer: Bears external mechanical loads and protects the submarine cable during laying and operation; Polyethylene outer sheath: the outermost layer of protection, isolating it from seawater and mechanical abrasion; Specifically, the DTS host is deployed at the substation at the submarine cable landing end or at the submarine cable monitoring end. The host can sequentially excite and demodulate different optical fibers through a multi-channel optical switch to obtain distributed temperature signals for each layer. Then, the signal is analyzed using the Brillouin scattering principle. The DTS host converts the frequency shift of the reflected light into a temperature value and outputs a "fiber length-temperature" curve. By identifying the fiber path and deployment location, the data from each fiber can be mapped to a specific layer of the submarine cable structure.

[0028] Based on the above structure, real-time temperature data acquisition employs distributed temperature demodulation (DTS) based on the Brillouin scattering principle to obtain a continuous "length-temperature" curve for each optical fiber and map it to its respective structural layer: conductor center temperature. Directly characterizes the temperature of the heat source and the insulation layer. Armor temperature is a key variable in insulation life and safety assessment. This characterizes the environmental cooling boundary. Considering the differences in attenuation, signal-to-noise ratio, and sampling phase among the three layers of optical fiber, an edge computing module (preferably an FPGA + embedded CPU collaborative architecture) is set up after DTS to complete data governance and quality improvement. This module performs real-time smoothing and denoising on the continuous temperature sequence, identifies and removes outliers (judged by statistical thresholds and compensated by interpolation), timestamps and aligns the three time series, and averages the 1m resolution in 5–10m segments to reduce data volume and random noise. Please refer to [reference needed]. Figure 3 This is a flowchart of real-time temperature data acquisition and processing. The data processing link and timing alignment are as follows: Figure 3 As shown, the temperature time series of the three layers after treatment has a high signal-to-noise ratio and good consistency, and can be directly used as input for modeling and control.

[0029] After acquiring the real-time temperature data, this invention also acquires the real-time current data of the submarine cable, i.e., the overall operating current data of the submarine cable. Typical submarine cable systems (DC) use DC current transformers installed at the converter station outlet to collect data in real time. This data can also be directly acquired through a SCADA system (Supervisory Control and Data Acquisition). The subsequent data processing flow is similar to that of the real-time temperature data.

[0030] S2. Input the real-time temperature data and real-time current data into a preset cable temperature prediction model, so that the cable temperature prediction model can predict the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, and obtain and output the predicted peak conductor temperature of the submarine cable; Preferably, the cable temperature prediction model includes: a physical equivalent sub-model, a data-driven sub-model, and a Kalman filter fusion layer; the physical equivalent sub-model is an equivalent thermal resistance-thermal capacity network established based on the heating of the cable conductor and radial heat transfer of the cable, and the data-driven sub-model is an LSTM network; the step of predicting the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data to obtain and output the predicted peak conductor temperature of the submarine cable includes: the physical equivalent sub-model predicting the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data to obtain first predicted temperature data of the submarine cable, and transmitting the first predicted temperature data to the Kalman filter fusion layer; the data-driven sub-model predicting the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data to obtain second predicted temperature data of the submarine cable, and transmitting the second predicted temperature data to the Kalman filter fusion layer; the Kalman filter fusion layer performing a weighted summation of the first predicted temperature data and the second predicted temperature data to obtain and output the predicted peak conductor temperature of the submarine cable.

[0031] In a specific embodiment, for step S2 above, after obtaining the real-time temperature data and real-time current data of the submarine cable, the real-time temperature data and real-time current data are input into a preset cable temperature prediction model, and the temperature evolution trend along the optical fiber inside the submarine cable is predicted by the cable temperature prediction model.

[0032] Specifically, the thermal response modeling of the cable temperature prediction model employs a hybrid engine combining a physically equivalent sub-model and a data-driven sub-model. On the physical side, an equivalent thermal resistance-thermal capacity network is established based on conductor heating and radial heat transfer to quickly characterize the dynamic temperature rise caused by current changes. The relationships between heating power and temperature evolution are as follows: (1) (2) in, Indicates the current. For equivalent heat capacity, The equivalent thermal resistance from conductor to insulation layer, This is the temperature-dependent resistance. The parameters were obtained through material thermal constants and calibration using three-dimensional finite element simulation.

[0033] The data-driven side uses a Long Short-Term Memory (LSTM) network as the main model. The inputs are the multivariate time series of the submarine cable conductor temperature Tc, submarine cable insulation temperature Ti, submarine cable armor layer temperature Ta, current value I(t), and ambient temperature Tenv within the most recent window to capture long-term thermal inertia and trends. In other implementations, a gated recurrent unit (GRU) can be added as a lightweight short-term corrector to improve the agility to sudden loads and environmental disturbances.

[0034] Please refer to Figure 4 This is a diagram of the predictive fusion architecture of the physical model and the data-driven model. The outputs of the two models are jointly inferred through the fusion layer, and online weighting is achieved using Kalman filtering. The structure and data flow relationship of physical-data fusion are as follows: Figure 4 As shown, the comparison and verification results between its predicted output and the measured data are as follows: Figure 5 As shown in Table 1, Figure 5 Table 1 shows a comparison of predicted and measured temperatures for a three-layer fiber optic cable. "Measured" can refer to prototype test data or simulation fitting data verified by a three-dimensional finite element model. In other implementations, an approximate extrapolation method based on short-term temperature rise trends can be used. This involves linearly or polynomially fitting the temperature rise slope within the most recent time window and extrapolating it to the prediction window. This serves as a simplified prediction method or a fallback solution when data is missing. Table 1 Comparison of Predicted and Measured Temperatures of Three-Layer Optical Fibers After the data is input into the cable temperature prediction model, the final result is the dynamic evolution trend of temperature distribution along the optical fiber inside the submarine cable, including the short-term predicted peak temperature. Based on the model output, we can first determine whether the cable is approaching its thermal stability limit, and secondly, we can calculate the temperature margin at a certain moment, providing a quantitative basis for subsequent dynamic capacity expansion.

[0035] Specifically, the cable temperature prediction model follows a strategy of "offline pre-training + online adaptive updating" to balance accuracy, speed, and maintainability. In the offline phase, it primarily uses operational data from in-service submarine cables under various seasonal and load conditions, supplemented by boundary expansion samples generated from finite element simulations to complete LSTM (Long Short-Term Memory) training. The validated model is exported as an ONNX computation graph and loaded into TensorRT (NVIDIA Inference Acceleration Engine) for inference acceleration and deployment optimization (operator fusion, graph structure simplification, and FP16 / INT8 quantization). Millisecond-level inference is achieved on a GRU (Gated Recurrent Unit) edge platform to meet minute-level rolling prediction requirements. In other embodiments, low-precision but real-time inference can be achieved based on a high-performance embedded platform. In the online phase, an incremental learning mechanism based on a time-sliding window is preferred, updating the normalization layer and the terminal affine layer with small steps to track field drift. New data is aggregated at predetermined intervals (e.g., 30 days) for offline fine-tuning before safely switching model versions. The system continuously monitors model health based on online residuals. The confidence interval and sliding window MAPE statistics are used to determine the threshold, where, To measure the peak temperature of the conductor, To predict the peak temperature of the conductor, the system automatically increases the weight of the physical model, tightens the control bandwidth, and triggers a rapid recalibration once the health of the conductor decreases, ensuring that conservative and reliable prediction outputs are maintained even under non-ideal data conditions.

[0036] S3. Based on the predicted peak conductor temperature and the preset upper limit insulation temperature, calculate the current increment value that the submarine cable can be upgraded, and match the corresponding cable upgrade strategy in the preset mapping table according to the current increment value, and then perform dynamic current carrying regulation on the submarine cable according to the cable upgrade strategy.

[0037] Preferably, the step of calculating the allowable current increment for increasing the capacity of the submarine cable based on the predicted conductor peak temperature and the preset insulation upper limit temperature, and matching the corresponding cable capacity increase strategy in a preset mapping table based on the current increment, includes: calculating the current temperature margin of the submarine cable based on the predicted conductor peak temperature and the preset insulation upper limit temperature, and calculating the allowable current increment for increasing the capacity under the current temperature margin; matching the corresponding cable capacity increase strategy in a preset mapping table based on the current temperature margin and the current increment.

[0038] Preferably, the current increment value is calculated according to the following formula; (3) (4) in, This is the current increment value. As the current temperature margin, Here, t represents the thermal characteristic coefficient of the cable structure, and t represents the current time. To predict duration, For the future Predicted peak conductor temperature within the range, The prediction time interval for forecasting the peak temperature of the conductor; This is the upper limit temperature for insulation.

[0039] In a specific embodiment, for step S3 above, after the temperature prediction model outputs the predicted peak conductor temperature corresponding to the submarine cable, this step first defines the temperature margin as the difference between "predicted peak temperature - insulation upper limit temperature", and generates an executable current adjustment command according to the mapping relationship. The temperature margin is defined as shown in formula (4), when... When the minimum threshold is exceeded, this invention uses a linear calibration relationship to convert it into a current increment value, as shown in formula (3), where, This refers to the allowable increase in current, which corresponds to the temperature margin. Related to the thermal characteristics of the cable structure (such as equivalent thermal resistance), its values ​​are obtained through type testing and historical operation data playback calibration, thereby ensuring that the model conforms to the physical mechanism and is engineering feasible.

[0040] Specifically, the temperature margin and the current that can be increased are first calculated using formulas (3) and (4). Then, the corresponding interval is found in the preset temperature margin-current increment mapping table, and the corresponding capacity increase execution method is selected. The corresponding rule base is shown in Table 2 below. In other implementation methods, piecewise linear or nonlinear fitting can be used. Table 2 Temperature Margin-Current Increment Mapping Table Control commands follow a ramp-up speed limit and hysteresis strategy to avoid oscillations. During capacity increases, they are implemented gradually, not exceeding the station control's allowed dI / dt, with a minimum hold time set. When the forecast approaches the upper limit, the current status is maintained. If the forecast indicates an over-limit or dT / dt exceeding the threshold, current limiting or load reduction is immediately triggered, and the load is gradually rolled back to the static thermal limit, while the audit trajectory is recorded. Commands are applied to converter valve power settings via the station control interface or sent to SCADA for power flow optimization, ensuring consistency with system-level constraints (such as inter-electrode power, valve temperature, and AC side short-circuit capacity). A comparison of static and dynamic current carrying capacities under different load fluctuation scenarios is provided. Figure 6 As shown in Table 3, Figure 6 Table 3 shows a comparison of static and dynamic current carrying capacity, and the table shows the dynamic capacity increase under different operating conditions.

[0041] Here, dI / dt refers to the time limit of the current increase rate, that is, the allowable increase in current per minute or per scheduling cycle, which is set by the converter station control and protection system. For example, it should not exceed 50A / min to avoid a sharp rise in temperature or system surge. The minimum hold time refers to the period (e.g., 5–10 minutes) required to maintain the current after one adjustment to prevent frequent fluctuations before the next adjustment. This parameter is set by the scheduling strategy to ensure stable operation and allow sufficient observation time. Table 3 Dynamic Capacity Increase under Different Operating Conditions Through the aforementioned closed loop of structure-sensing-modeling-control, the present invention, in its preferred embodiment, can achieve a short-term dynamic capacity increase of approximately 10%-20% within a safety margin, significantly improving the utilization efficiency of the power transmission channel. At the same time, it ensures operational safety and auditability through model health monitoring, abnormal rollback, and multiple protection mechanisms. In other embodiments, the fiber optic deployment, model fusion, and control parameters can be equivalently replaced or engineered based on seabed thermal conditions, laying methods, and operation and maintenance strategies, without departing from the essential concept of the present invention.

[0042] Therefore, this invention provides a dynamic current-carrying regulation method for submarine cables. By introducing a multi-layered built-in optical fiber monitoring structure into high-voltage submarine cables and combining physical modeling with data-driven intelligent algorithms, this invention achieves a closed-loop process across the entire chain, from real-time sensing, data governance, thermal model prediction to dynamic regulation. The beneficial effects are reflected in the following aspects: First, this invention can simultaneously acquire high-resolution continuous temperature distribution information at three key locations: the conductor, insulation layer, and armor / sheath layer. This not only improves the ability to identify hot spots inside the cable but also avoids the limitation of traditional single-point sensing, which struggles to detect hidden defects in a timely manner. This dual-dimensional temperature measurement system, encompassing both longitudinal and radial dimensions, significantly enhances the observability of the cable's operating status, providing a solid physical foundation for subsequent current-carrying capacity control.

[0043] Secondly, this invention utilizes edge computing to perform real-time preprocessing, denoising, and calibration of massive fiber optic signals, ensuring the stability and reliability of data input. Through the fusion prediction of the physical equivalent thermal model and the LSTM / GRU network, the temperature rise trend in the next few minutes to tens of minutes can be accurately extrapolated. In other embodiments, an approximate extrapolation of the short-term temperature rise trend is introduced as a fallback method to ensure that the system can maintain basic predictive capabilities even when data is missing or the model is abnormal.

[0044] Furthermore, this invention achieves an organic combination of short-term dynamic capacity expansion and safe current limiting by defining a temperature margin and mapping it to executable current regulation commands. Through this strategy, submarine cables can achieve a 10%–20% increase in current carrying capacity under short-term load fluctuations or system scheduling requirements, while meeting insulation life and safety constraints. Compared to traditional solutions, this invention effectively improves the utilization efficiency of transmission channels while avoiding resource waste caused by excessive conservatism.

[0045] Finally, the capacity expansion control mechanism provided by this invention possesses closed-loop feedback capability, and control commands can be seamlessly integrated with converter valve, filter control system, or master SCADA platform. Through online model health monitoring and anomaly fallback strategies, this invention ensures safety, controllability, and auditability under extreme or non-ideal data conditions. This technical system, integrating structural innovation, perceptual redundancy, intelligent modeling, and scheduling execution, not only extends the service life of submarine cables but also improves the flexibility and economy of power grid operation, demonstrating significant engineering application prospects and promotional value.

[0046] Example 2 Please refer to Figure 7 This is a schematic diagram of a dynamic current-carrying control device for a submarine cable according to an embodiment of the present invention. The device includes: a data acquisition module, a temperature prediction module, and a current-carrying control module. The data acquisition module is used to acquire real-time temperature data and real-time current data of the submarine cable. The temperature prediction module is used to input the real-time temperature data and real-time current data into a preset cable temperature prediction model, so that the cable temperature prediction model can predict the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, and obtain and output the predicted peak conductor temperature of the submarine cable; The current-carrying regulation module is used to calculate the current increment value that the submarine cable can be increased in capacity based on the predicted peak conductor temperature and the preset upper limit insulation temperature, and to match the corresponding cable capacity increase strategy in the preset mapping table according to the current increment value, and then to dynamically regulate the current-carrying capacity of the submarine cable according to the cable capacity increase strategy.

[0047] Preferably, the cable temperature prediction model includes: a physical equivalent sub-model, a data-driven sub-model, and a Kalman filter fusion layer; The physical equivalent sub-model is an equivalent thermal resistance-thermal capacity network established based on the heating of the cable conductor and the radial heat transfer of the cable, and the data-driven sub-model is an LSTM network. The step of predicting the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtaining and outputting the predicted peak conductor temperature of the submarine cable, includes: The physical equivalent sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the first predicted temperature data of the submarine cable, and transmits the first predicted temperature data to the Kalman filter fusion layer. The data-driven sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the second predicted temperature data of the submarine cable, and transmits the second predicted temperature data to the Kalman filter fusion layer. The Kalman filter fusion layer performs a weighted summation of the first and second predicted temperature data to obtain and output the predicted peak conductor temperature of the submarine cable.

[0048] Preferably, the step of calculating the incremental current value that can be increased in capacity for the submarine cable based on the predicted peak conductor temperature and the preset upper limit insulation temperature, and matching the corresponding cable capacity increase strategy in a preset mapping table according to the incremental current value, includes: Based on the predicted peak conductor temperature and the preset upper limit insulation temperature, calculate the current temperature margin of the submarine cable, and calculate the allowable current increment value under the current temperature margin. Based on the current temperature margin and the current increment value, a corresponding cable capacity expansion strategy is matched in a preset mapping table.

[0049] Preferably, the current increment value is calculated according to the following formula; ; ; in, This is the current increment value. As the current temperature margin, Here, t represents the thermal characteristic coefficient of the cable structure, and t represents the current time. To predict duration, For the future Predicted peak conductor temperature within the range, The prediction time interval for forecasting the peak temperature of the conductor; This is the upper limit temperature for insulation.

[0050] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0051] Those skilled in the art will clearly understand that, for convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0052] Example 3 Accordingly, embodiments of the present invention provide an electronic device, the device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the dynamic current-carrying control method for submarine cables described in the above embodiments of the invention.

[0053] The electronic device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The device may include, but is not limited to, a processor and a memory.

[0054] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the device, connecting various parts of the device via various interfaces and lines.

[0055] Example 4 Accordingly, embodiments of the present invention provide a storage medium, the storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the dynamic current-carrying regulation method for submarine cables described in the above embodiments of the invention.

[0056] The memory can be used to store the computer program. The processor implements various functions of the device by running or executing the computer program stored in the memory and calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0057] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0058] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for dynamic current-carrying regulation of submarine cables, characterized in that, include: Acquire real-time temperature and current data of submarine cables; The real-time temperature data and real-time current data are input into a preset cable temperature prediction model so that the cable temperature prediction model can predict the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, and obtain and output the predicted peak conductor temperature of the submarine cable. Based on the predicted peak conductor temperature and the preset upper limit insulation temperature, the current increment value that can be increased in the submarine cable is calculated, and the corresponding cable capacity increase strategy is matched in the preset mapping table according to the current increment value. Then, the current carrying capacity of the submarine cable is dynamically adjusted according to the cable capacity increase strategy.

2. The dynamic current-carrying regulation method for submarine cables as described in claim 1, characterized in that, The cable temperature prediction model includes: a physical equivalent sub-model, a data-driven sub-model, and a Kalman filter fusion layer; The physical equivalent sub-model is an equivalent thermal resistance-thermal capacity network established based on the heating of the cable conductor and the radial heat transfer of the cable, and the data-driven sub-model is an LSTM network. The step of predicting the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtaining and outputting the predicted peak conductor temperature of the submarine cable, includes: The physical equivalent sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the first predicted temperature data of the submarine cable, and transmits the first predicted temperature data to the Kalman filter fusion layer. The data-driven sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the second predicted temperature data of the submarine cable, and transmits the second predicted temperature data to the Kalman filter fusion layer. The Kalman filter fusion layer performs a weighted summation of the first and second predicted temperature data to obtain and output the predicted peak conductor temperature of the submarine cable.

3. The dynamic current-carrying regulation method for submarine cables as described in claim 2, characterized in that, The step of calculating the incremental current value that can be increased in capacity for the submarine cable based on the predicted peak conductor temperature and the preset upper limit insulation temperature, and matching the corresponding cable capacity increase strategy in a preset mapping table according to the incremental current value, includes: Based on the predicted peak conductor temperature and the preset upper limit insulation temperature, calculate the current temperature margin of the submarine cable, and calculate the allowable current increment value under the current temperature margin. Based on the current temperature margin and the current increment value, a corresponding cable capacity expansion strategy is matched in a preset mapping table.

4. The dynamic current-carrying regulation method for submarine cables as described in claim 3, characterized in that, The current increment value is calculated according to the following formula; ； ； in, This is the current increment value. As the current temperature margin, Here, t represents the thermal characteristic coefficient of the cable structure, and t represents the current time. To predict duration, For the future Predicted peak conductor temperature within the range, The prediction time interval for forecasting the peak temperature of the conductor; This is the upper limit temperature for insulation.

5. A dynamic current-carrying regulation device for submarine cables, characterized in that, include: Data acquisition module, temperature prediction module, and current control module; The data acquisition module is used to acquire real-time temperature data and real-time current data of the submarine cable. The temperature prediction module is used to input the real-time temperature data and real-time current data into a preset cable temperature prediction model, so that the cable temperature prediction model can predict the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, and obtain and output the predicted peak conductor temperature of the submarine cable; The current-carrying regulation module is used to calculate the current increment value that the submarine cable can be increased in capacity based on the predicted peak conductor temperature and the preset upper limit insulation temperature, and to match the corresponding cable capacity increase strategy in the preset mapping table according to the current increment value, and then to dynamically regulate the current-carrying capacity of the submarine cable according to the cable capacity increase strategy.

6. The dynamic current-carrying control device for submarine cables as described in claim 5, characterized in that, The cable temperature prediction model includes: a physical equivalent sub-model, a data-driven sub-model, and a Kalman filter fusion layer; The physical equivalent sub-model is an equivalent thermal resistance-thermal capacity network established based on the heating of the cable conductor and the radial heat transfer of the cable, and the data-driven sub-model is an LSTM network. The step of predicting the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtaining and outputting the predicted peak conductor temperature of the submarine cable, includes: The physical equivalent sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the first predicted temperature data of the submarine cable, and transmits the first predicted temperature data to the Kalman filter fusion layer. The data-driven sub-model predicts the temperature evolution trend along the optical fiber inside the submarine cable based on the real-time temperature data and real-time current data, obtains the second predicted temperature data of the submarine cable, and transmits the second predicted temperature data to the Kalman filter fusion layer. The Kalman filter fusion layer performs a weighted summation of the first and second predicted temperature data to obtain and output the predicted peak conductor temperature of the submarine cable.

7. The dynamic current-carrying control device for submarine cables as described in claim 6, characterized in that, The step of calculating the incremental current value that can be increased in capacity for the submarine cable based on the predicted peak conductor temperature and the preset upper limit insulation temperature, and matching the corresponding cable capacity increase strategy in a preset mapping table according to the incremental current value, includes: Based on the predicted peak conductor temperature and the preset upper limit insulation temperature, calculate the current temperature margin of the submarine cable, and calculate the allowable current increment value under the current temperature margin. Based on the current temperature margin and the current increment value, a corresponding cable capacity expansion strategy is matched in a preset mapping table.

8. The dynamic current-carrying control device for submarine cables as described in claim 7, characterized in that, The current increment value is calculated according to the following formula; ； ； in, This is the current increment value. As the current temperature margin, Here, t represents the thermal characteristic coefficient of the cable structure, and t represents the current time. To predict duration, For the future Predicted peak conductor temperature within the range, The prediction time interval for forecasting the peak temperature of the conductor; This is the upper limit temperature for insulation.

9. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the dynamic current-carrying control method for submarine cables as described in any one of claims 1 to 4.

10. A storage medium, characterized in that, The storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the storage medium to perform the dynamic current-carrying regulation method for submarine cables as described in any one of claims 1 to 4.

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