An Adaptive Grid Connection Method and System for Ship-to-Shore Power Systems Based on Digital Twin

Abstract

This invention proposes an adaptive grid connection method and system for ship-to-shore power systems based on digital twins, relating to the fields of ship-to-shore power, digital twins, and power system health management. The method includes: collecting multi-source heterogeneous operational status data from both the ship and port sides; constructing a ship-to-port joint digital twin model; determining the health status of the shore power system based on the ship-to-port joint digital twin model and the multi-source heterogeneous operational status data; generating grid connection condition parameter constraints based on the health status of the shore power system; determining whether the ship initiates a grid connection request; if so, executing an adaptive grid connection strategy based on improved virtual synchronous generator control under the grid connection condition parameter constraints; continuously updating the ship-to-port joint digital twin model synchronously, and providing real-time feedback on the health status of the shore power system, forming a closed-loop optimization. This invention can be integrated and deployed based on existing shore power monitoring platforms, edge computing gateways, and grid connection control devices, facilitating implementation in port areas.

Description

Technical Field

[0001] This invention relates to the fields of ship shore power, digital twins and power system health management, and in particular to an adaptive grid connection method and system for ship shore power systems based on digital twins. Background Technology

[0002] Shore power technology for ships plays a crucial role in reducing pollutant emissions and noise pollution from berthing vessels as a key measure for green port development. However, shore power systems face two prominent problems in actual operation: First, the health of key equipment such as transformers, inverters, and interface devices in shore power systems continuously deteriorates under long-term operation, frequent switching, and load impacts. Traditional operation and maintenance methods lack the ability to assess the health status and predict the lifespan of equipment in real time, making it difficult to determine whether the system meets the conditions for safe grid connection before grid connection. This poses a safety hazard of grid connection failure or even equipment damage due to hidden equipment faults. Second, existing shore power grid connection control strategies mostly use fixed parameters and do not consider the impact of changes in equipment health status on the system's dynamic response capability. When the health of equipment declines, if grid connection is still performed according to rated parameters, it can easily cause problems such as excessive grid connection impact, prolonged frequency recovery time, and accelerated equipment aging.

[0003] Currently, digital twin technology has been initially applied in areas such as ship power system monitoring and transformer condition assessment. Digital twins construct virtual mirror images of physical systems, enabling real-time data interaction and synchronization between physical entities and virtual models, thereby accurately representing and predicting the state of the physical system. Existing digital twin-based shore power equipment management methods mainly focus on equipment operation monitoring and power supply management, but have not established a collaborative mechanism between equipment health assessment and grid connection control. Research on the health management of ship multi-energy power supply systems has proposed an integrated perception-decision-execution management system, but it focuses on energy collaborative management on the ship side and does not address health assessment and adaptive grid connection control issues in ship-port joint grid connection scenarios. Regarding shore power grid connection control, improved virtual synchronous generator control strategies, by introducing adaptive control strategies for inertia and damping, have effectively improved the frequency stability of shore power grid connection; ship-shore power synchronization control optimization methods based on improved droop control have solved problems such as poor frequency stability and large grid connection impact. However, none of these methods incorporate the equipment health status into the adaptive adjustment mechanism of control parameters.

[0004] In summary, existing technologies have the following shortcomings: 1) Health assessment and grid connection control of shore power systems are disconnected, lacking a closed-loop collaborative mechanism to feed health status information back to the grid connection controller; 2) Health assessments largely rely on offline detection of single devices, lacking the capability for real-time health assessment and lifespan prediction based on digital twins across the entire system and at multiple levels; 3) Grid connection control strategy parameters are fixed and cannot be adaptively adjusted according to changes in device health, resulting in grid connection being performed with rated parameters even when the health status is poor, increasing the risk of device failure and the probability of grid connection failure. Therefore, it is necessary to propose an adaptive grid connection method that combines digital twin-driven health assessment with edge sensing to improve the operational safety and grid connection reliability of shore power systems. Summary of the Invention

[0005] To alleviate or solve one or more of the above-mentioned technical problems, this invention proposes an adaptive grid connection method and system for ship shore power systems based on digital twins.

[0006] According to one aspect of the present invention, an adaptive grid connection method for ship-to-shore power systems based on digital twins is proposed, the method comprising the following steps: Collect multi-source heterogeneous operational status data from both sides of the ship-port; Based on the physical topology and operational status data of both sides of the ship and port, a joint digital twin model of ship and port is constructed. The health status of the shore power system is determined based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data. Generate grid connection condition parameter constraints based on the health status of the shore power system; Determine whether the ship initiates a grid connection request. If it does, execute an adaptive grid connection strategy based on improved virtual synchronous generator control under the constraints of grid connection condition parameters. After the ship-shore synchronous grid connection is completed, the ship-port joint digital twin model is continuously updated synchronously, and the health status of the shore power system is fed back to the grid connection controller in real time, forming a closed-loop optimization.

[0007] Furthermore, the multi-source heterogeneous operational status data includes ship-side operational status data and port-side operational status data; after collecting the multi-source heterogeneous operational status data from both the ship and port sides, the data is further cleaned, specifically including: outlier removal and data missing filling, multi-source data timestamp alignment and resampling.

[0008] Furthermore, the ship-port joint digital twin model includes a ship-side equivalent circuit model, a port-side shore power inverter model, a shore power transformer thermal-aging model, and a ship-shore interface equipment model. The ship-side equivalent circuit model consists of an equivalent impedance network describing a linear load connected in parallel with a controlled current source describing a nonlinear load. The port-side shore power inverter model employs a combination of switching function modulation and dynamic filters, where the switching function describes the DC-to-AC voltage transformation, and the filters describe the dynamic response of the output current. The shore power transformer thermal-aging model uses thermoelectric analogy to describe the transformer's heating process and describes the insulation aging process based on the temperature accumulation effect. The ship-shore interface equipment model describes the electrical connections, switching states, protection relay operation logic, and communication protocol status of the shore power interface box. The ship-port joint digital twin model uses an extended Kalman filter algorithm to achieve real-time synchronous updates with the physical entities.

[0009] Furthermore, determining the health status of the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data includes: extracting multiple health characteristic parameters for each key device in the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data; calculating the health index of the key devices based on the health characteristic parameters; and calculating the health index of the shore power system based on the health index of the key devices. The key devices include transformers, shore power inverters, and ship-shore interface devices. The health indices of the key devices include transformer health indices, inverter health indices, and interface device health indices.

[0010] Furthermore, the formula for calculating the transformer health index is as follows: ; In the formula, This represents the transformer health index at time t; For the health factor of winding hot spot temperature, , This refers to the hot spot temperature of the winding. This is a reference value for hotspot temperature. This is the temperature decay coefficient; As a health factor for insulation aging, , The degree of polymerization of insulating paper, For the amplitude limiting function, The initial degree of polymerization of the insulating paper. The degree of polymerization at the end of the lifetime; As a load rate health factor, , For transformer load rate, To achieve the optimal load rate, The penalty coefficient for load rate deviation; , , These are the weighting coefficients for temperature, insulation aging, and load rate factors, respectively, satisfying... ; The formula for calculating the inverter health index is as follows: ; In the formula, This indicates the inverter's health index; For IGBT power module junction temperature health factors, , For the first The cumulative number of power cycles within a junction temperature fluctuation range. To the junction temperature fluctuation amplitude and average junction temperature Number of failure cycles under the given conditions; For the DC bus capacitor health factor, , This is the current equivalent series resistance of the DC bus capacitor. This is the initial equivalent series resistance. This is the capacitor failure threshold; Harmonic distortion health factors , The harmonic distortion rate of the inverter output current. The threshold for allowable harmonic distortion rate; , , These are the weight coefficients of each factor, satisfying... ; The formula for calculating the health index of the interface device is as follows: ; In the formula, min represents taking the minimum value; For switch operation health factors, , To accumulate the number of switch operations, The rated mechanical lifespan; As an insulating health factor, , The current insulation resistance, The initial insulation resistance, Minimum allowable insulation resistance; As a temperature health factor, , For the number of temperature anomalies, The threshold for the number of times temperature anomalies are allowed.

[0011] Furthermore, the calculation of the shore power system's health index based on the health index of key equipment includes: weighting the health indices of multiple key equipment to obtain the health index of each subsystem; and weighting the health indices of multiple subsystems to obtain the health index of the shore power system.

[0012] Furthermore, the grid connection condition parameter constraints include grid connection permission flags, power limiting coefficients, and dynamic response adjustment coefficients; the generation rules for the grid connection condition parameter constraints are as follows: When the health index of the shore power system is greater than or equal to the preset maximum system health threshold, the grid connection permission flag is equal to 1, and the grid connection operation is performed normally; power limiting coefficient and dynamic response adjustment coefficient All equal to 1; When the health index of the shore power system is less than the preset maximum system health threshold but greater than or equal to the minimum system health threshold, the grid connection permission flag equals 1, and the derating grid connection mode is activated; power limiting coefficient and dynamic response adjustment coefficient Calculate using the following formula: ; ; In the formula, This is a health index for shore power systems. As the minimum requirement for system health, The highest threshold for system health. For response adjustment coefficient; When the health index of the shore power system is less than the preset minimum health threshold or the health index of any key device is less than the health threshold of that device, the grid connection permission flag is equal to 0, and grid connection is prohibited.

[0013] Furthermore, the adaptive grid connection strategy based on improved virtual synchronous generator control includes a pre-synchronization phase and a grid connection operation phase; wherein, the pre-synchronization phase employs phase-amplitude-frequency triple synchronization control to ensure that the shore power output voltage and the ship's grid voltage meet the grid connection conditions; the grid connection operation phase employs improved virtual synchronous generator control, and the active power-frequency control equation is improved to: ; In the formula, This is a reference value for active power. This refers to electromagnetic power or active power output from the inverter. This is the actual angular frequency. The rated angular frequency is used; the adaptive virtual moment of inertia J(t) and the adaptive virtual damping coefficient D(t) are dynamically adjusted according to the health index of the shore power system as follows: ; ; ; ; In the formula, and These are the virtual moment of inertia reference value and the virtual damping coefficient reference value, respectively. and All are smoothing adjustment functions; , To adjust the upper and lower thresholds for inertia, , The upper and lower threshold values ​​are used for damping adjustment.

[0014] Furthermore, it also includes: after obtaining the health index of critical equipment, predicting the remaining service life of the critical equipment according to the following formula: ; In the formula, The remaining service life of the i-th critical device; This refers to the rated service life of the equipment. The current health index of the device; α is the accelerated aging index; This is the equivalent operating time of the equipment.

[0015] According to another aspect of the present invention, an adaptive grid connection system for a ship-to-shore power system based on digital twins is proposed. This system is used to implement the aforementioned adaptive grid connection method for a ship-to-shore power system based on digital twins. The system includes: The data acquisition module is used to collect multi-source heterogeneous operational status data from both sides of the ship and the port. The digital twin modeling module is used to construct a joint digital twin model of the ship and port based on the physical topology and operational status data of both sides of the ship and port. The health assessment module is used to determine the health status of the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data. The grid connection constraint generation module is used to generate grid connection condition parameter constraints based on the health status of the shore power system. The adaptive grid connection control module is used to determine whether the ship initiates a grid connection request. If a grid connection request is initiated, an adaptive grid connection strategy based on improved virtual synchronous generator control is executed under the constraints of grid connection condition parameters. The closed-loop feedback and synchronous update module is used to continuously update the ship-port joint digital twin model after the ship-shore synchronous grid connection is completed, and the health status of the shore power system is fed back to the grid connection controller in real time, forming a closed-loop optimization.

[0016] This invention proposes an adaptive grid connection method and system for ship-to-shore power systems based on digital twins, which has the following beneficial effects: 1) Closed-loop coordination of health assessment and grid connection control: This invention establishes a closed-loop mechanism for digital twin-driven equipment health assessment and shore power grid connection control for the first time. The health assessment results are fed back to the grid connection controller in real time, and grid connection condition parameter constraints are dynamically generated. This solves the problem of the separation between health assessment and grid connection control in traditional methods and realizes the integration of perception-assessment-control.

[0017] 2) Real-time health assessment and lifespan prediction based on edge perception: Data cleaning and feature extraction at edge computing nodes reduce data transmission pressure and improve response speed; a multi-level health assessment system based on digital twin model covers three levels: equipment level, subsystem level and system level, to achieve observability of the health status of the entire system; the proposed remaining service life prediction formula comprehensively considers the cumulative effect of health index and accelerated aging factors, which can provide a basis for equipment maintenance and replacement.

[0018] 3) Health-first adaptive grid connection strategy: The virtual moment of inertia and damping coefficient of the improved virtual synchronous generator control can be adaptively adjusted according to the health status of the equipment. When the health of the equipment declines, the system automatically slows down the response speed, limits the power change rate, reduces the impact stress on aging equipment, and extends the service life of the equipment; when the health of the equipment declines severely, grid connection is automatically prohibited and an alarm is issued to ensure operational safety.

[0019] 4) Real-time synchronization of digital twin model: The extended Kalman filter algorithm is used to realize the real-time synchronization and update of digital twin model and physical entity, so that the model continuously tracks the changes in the state of physical system and provides an accurate virtual data basis for health assessment and adaptive control.

[0020] 5) High feasibility of engineering: This invention can be integrated and deployed based on existing shore power monitoring platforms, edge computing gateways and grid-connected control devices without large-scale hardware modifications, making it easy to implement in port areas. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a flowchart of an adaptive grid connection method for a ship-to-shore power system based on digital twins, as described in an embodiment of the present invention. Figure 2This is a schematic diagram of the overall architecture of the method described in the embodiments of the present invention; Figure 3 This is a schematic diagram of the hierarchical structure of the multi-level health assessment indicator system in an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating the trend of the transformer health index changing with operating time in an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the relationship between remaining lifespan prediction and health index in an embodiment of the present invention; Figure 6 This is a block diagram of the health assessment-driven adaptive grid connection control in an embodiment of the present invention; Figure 7 This is a schematic diagram comparing the grid connection frequency response under different health states in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of an adaptive grid-connected ship-to-shore power system based on digital twin, as described in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are part of this invention.

[0024] This invention provides an adaptive grid connection method and system for a ship shore power system based on digital twins, in order to solve the problems in the prior art where the health assessment and grid connection control of the shore power system are disconnected and the grid connection control parameters are fixed and cannot adapt to changes in the health status of the equipment, so as to realize the safe and flexible grid connection of the shore power system under the condition of dynamic changes in the health status of the equipment.

[0025] This invention proposes a health-adaptive grid connection method for ship-to-shore power systems based on digital twins, such as... Figures 1-2 As shown, the method includes: S1. Collect multi-source heterogeneous operational status data from both sides of the ship-port; S2. Based on the physical topology and operational status data of both sides of the ship and port, construct a joint digital twin model of the ship and port; S3. Determine the health status of the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data; S4. Generate grid connection condition parameter constraints based on the health status of the shore power system; S5. Determine whether the ship initiates a grid connection request. If it does, execute an adaptive grid connection strategy based on improved virtual synchronous generator control under the constraints of grid connection condition parameters. S6. After the ship-shore synchronous grid connection is completed, the ship-port joint digital twin model is continuously updated synchronously, and the health status of the shore power system is fed back to the grid connection controller in real time, forming a closed-loop optimization.

[0026] The method begins with S1. In S1, multi-source heterogeneous operational status data from both the ship and port sides are collected.

[0027] According to an embodiment of the present invention, the multi-source heterogeneous operational status data collected from both the ship and port sides includes ship-side operational status data and port-side operational status data. The sampling period is 10 ms to 100 ms. The ship-side operational status data includes: three-phase voltage of the shore power interface. Three-phase current Active power reactive power ,frequency Current harmonic distortion rate Shore power interface switch status and protective action record The port area side's operational status data includes: three-phase voltage and current on the high-voltage and low-voltage sides of the shore power transformer, and transformer oil temperature collected via an oil temperature sensor. Winding temperature Ambient temperature shore power inverter DC bus voltage Output current PWM modulation signal or switching function IGBT junction temperature Output current harmonic distortion rate Switching frequency and the temperature of the ship-to-shore interface box Contact resistance Insulation resistance and cumulative number of switch operations .

[0028] After collecting multi-source heterogeneous operational status data from both the ship and port sides, the data cleaning process is also included. Edge computing nodes are deployed in the edge gateways within the port's shore power station to perform the following data cleaning operations: 1) Outlier removal and data gap filling: Data exceeding the physically reasonable range is removed, and short-term data gaps are filled using a sliding window-based linear interpolation method. For example, data with voltage exceeding 1.2 times the rated value or temperature exceeding 200℃ are removed, and the 3σ criterion can be used to identify outliers; linear interpolation is used to fill data with a sampling period of 5 or less; 2) Multi-source data timestamp alignment and resampling: Using the unified time grid t of the control center as a reference, the multi-source data from the ship side and the port area side are resampled and aligned. ; In the formula, For the first Each measurement source (i.e., ship-side or port-side) at the local timestamp The data collected below This is the resampled data; This represents the resampling function.

[0029] Data preprocessing via edge computing nodes can effectively reduce data transmission volume, alleviate the computational burden on the cloud or central controller, and improve data quality and real-time performance, enabling edge-aware shore power system status monitoring.

[0030] Then, in S2, a joint digital twin model of ship and port is constructed based on the physical topology and operational status data of both sides of the ship and port.

[0031] According to embodiments of the present invention, the ship-port joint digital twin model is a precise mapping of the physical shore power system in the digital space, and includes the following sub-models: (1) Ship-side equivalent circuit model: It consists of an equivalent impedance network describing a linear load and a controlled current source describing a nonlinear load connected in parallel. The controlled current source and the impedance network describe the electrical characteristics of the ship load; the model equations are: ; In the formula, The equivalent current vector on the ship side is the three-phase current collected by S1. Obtained through coordinate transformation or effective value calculation; The busbar voltage vector is the three-phase voltage collected by S1. get; The ship-side equivalent admittance matrix is ​​initially determined by the ship's shore power access topology and typical load parameters, and is identified and corrected online using recursive least squares or extended Kalman filtering based on measured voltage and current. This is a controlled load function used to describe the ship's nonlinear load and harmonic characteristics. Its input is the active power acquired by S1 and extracted by the edge computing nodes. reactive power and harmonic distortion rate get.

[0032] (2) Port-side shore power inverter model: It adopts a combination of switching function modulation and dynamic filter, where the switching function describes the DC-to-AC voltage transformation (i.e., the inverter's dynamic behavior), and the filter circuit describes the dynamic response of the output current; the mathematical model is: ; ; In the formula, This refers to the AC output voltage of the inverter. The inverter switching function vector is obtained from the PWM modulation signal output by the inverter controller or the gate drive state, and is used as the port area side operation status data acquisition in S1. This is the DC bus voltage; This refers to the inverter output current. The voltage is the low-voltage busbar or grid connection point voltage of the shore power, which is obtained from the three-phase voltage on the port side. and These are the AC side filter inductance and equivalent filter resistance of the inverter, respectively, which are identified from the inverter design parameters, filter nameplate parameters, or field parameters.

[0033] (3) Shore power transformer thermal-aging model: The thermoelectric analogy method is used to describe the temperature rise process of the transformer, and the insulation aging process is described based on the temperature accumulation effect; the model equation is: ; ; ; In the formula, For the equivalent heat capacity of the winding, The equivalent heat capacity of oil, The thermal resistance from the winding to the oil. The thermal resistance from oil to the environment. For winding temperature, Oil temperature For ambient temperature, This represents the total transformer loss. The degree of polymerization of insulating paper, This is the aging rate coefficient. For activation energy, is the gas constant.

[0034] in, , , Data collected from S1 or estimated using a shore power transformer thermal-aging model; It is calculated from the voltage and current on the high and low voltage sides of the transformer, as well as the no-load loss and load loss parameters. , , , , , It is identified from equipment factory data, test data, or historical operating data, and can be corrected online during the digital twin synchronization process.

[0035] (4) Ship-to-shore interface equipment model: This model describes the electrical connections, switch states, protection relay operation logic, and communication protocol status of the shore power interface box. The model uses interface switch states, protection action records, contact resistance, insulation resistance, and interface box temperature as inputs to establish the interface equipment operating state vector as follows: ; The interface device operating status vector is used for subsequent interface device health feature extraction and interface device health index calculation.

[0036] The real-time synchronous update of the digital twin model employs an extended Kalman filter algorithm, using the residual between the measured data of the physical entity and the simulation output of the digital twin model as feedback to correct the model's state variables and parameters in real time. Prediction step: ; ; Update steps: ; ; ; In the formula, k represents the discrete sampling time; This represents the state estimation vector at time k predicted based on information from time k-1. This represents the state estimation vector at time k after correction based on measured data; Let represent the posterior state estimate vector at time k-1; The control input vector at time k is represented, including the inverter modulation signal, switching state, and grid-connected control command; f(.) represents the nonlinear state transition function determined by the ship-port joint digital twin model; h(.) represents the observation function, which is used to map the state variables to measurable observations such as voltage, current, temperature, and power. This represents the measured output vector of the physical entity at time k; The Jacobian matrix of the state transition function f(.) with respect to the state variables; This represents the Jacobian matrix of the observation function h(.) with respect to the state variables; Represents the prediction error covariance matrix; This represents the updated estimated error covariance matrix; Indicates Kalman gain; Represents the process noise covariance matrix; The superscript T represents the observation noise covariance matrix; I represents the identity matrix; the superscript T represents the matrix transpose; and the superscript -1 represents the matrix inversion.

[0037] Using the extended Kalman filter algorithm described above, the digital twin model can continuously track the real state of the physical entity, providing accurate virtual state data for subsequent health assessments.

[0038] Then, in S3, the health status of the shore power system is determined based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data; including: S31, extracting multiple health feature parameters of each key device in the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data; S32, calculating the health index of the key devices based on the health feature parameters; S33, calculating the health index of the shore power system based on the health index of the key devices.

[0039] According to an embodiment of the present invention, firstly, in S31, multiple health characteristic parameters of each key device in the shore power system are extracted based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data. Specifically, the key devices in the shore power system are divided into three categories: transformers, shore power inverters, and ship-shore interface devices, and health characteristic parameters are extracted from the different sub-models constructed in S2 and the data obtained in S1, respectively.

[0040] The extracted transformer health characteristic parameters include: winding hot spot temperature. Oil temperature Degree of polymerization of insulating paper Load rate Among them, the winding hot spot temperature and oil temperature The winding hot spot temperature is calculated from the thermal-aging model of the shore power transformer or obtained by sensor data and corrected by extended Kalman filtering. It is the highest temperature in the winding; the degree of polymerization of the insulating paper. The polymerization degree degradation equation in the thermal-aging model of shore power transformers in S2 ( Calculated load rate It is calculated from the high and low voltage sides of the transformer, the current, and the rated capacity.

[0041] The extracted health characteristic parameters of the shore power inverter include: IGBT power module junction temperature fluctuation amplitude. Junction temperature cycle number DC bus capacitor equivalent series resistance Output current harmonic distortion rate Among them, the IGBT power module is the core power switching device in the shore power inverter, and the DC bus capacitor is the DC-side supporting capacitor of the inverter; the IGBT junction temperature fluctuation amplitude and number of junction temperature cycles The equivalent series resistance of the DC bus capacitor is obtained by rainflow counting from the inverter model, junction temperature sensor, or thermal network estimation results; The output current harmonic distortion rate is estimated from the DC bus voltage ripple and capacitor current. The frequency domain analysis is obtained by sampling the inverter output current in S1.

[0042] The extracted health characteristic parameters of the ship-to-shore interface equipment include: cumulative number of switching operations. Contact resistance Insulation resistance Number of times the interface box temperature was abnormal Among them, the cumulative number of switch operations. Contact resistance is accumulated from the interface device model based on changes in switch state. and insulation resistance Data can be collected in real time by the online detection unit of the interface equipment; in the absence of an online detection unit or if online detection data is unavailable, it can be obtained from periodic inspection records and used as external input parameters for the ship-shore interface equipment model. Number of times the interface box temperature abnormality occurred. From the interface box temperature The number of times the preset threshold was exceeded was counted.

[0043] Then, in S32, the health index of key equipment is calculated based on health characteristic parameters.

[0044] Specifically, such as Figure 3 As shown, a multi-level health assessment indicator system is constructed, including three levels: equipment-level health indicators, subsystem-level health indicators, and system-level health indicators. Equipment-level health indicators include the transformer health index. Inverter health index Health index of interface devices .

[0045] Among them, the transformer health index The calculation formula is as follows: ; in, For the health factor of winding hot spot temperature, As a health factor for insulation aging, Load rate health factor; , , These are the weighting coefficients for temperature, insulation aging, and load rate factors, respectively, satisfying... As an example, the weights of each factor in the transformer are taken as follows: .

[0046] ; ; ; In the formula, This refers to the hot spot temperature of the winding. This is a reference value for hotspot temperature. The temperature decay coefficient is The initial degree of polymerization of the insulating paper. The degree of polymerization at the end of the lifetime. For transformer load rate, To achieve the optimal load rate, The penalty coefficient for load rate deviation. This is the amplitude limiting function. As an example, Take 110℃ (110℃ is the reference temperature for insulation heat resistance class A of oil-immersed transformers), attenuation coefficient Take 0.02; initial degree of polymerization of insulating paper Take 1000, the degree of polymerization at the end of the lifetime. Set the value to 200; optimal load factor Take 0.7, Take 0.5. Figure 4 The trend of the transformer health index over 2000 hours of continuous operation is shown: under constant rated load conditions, It decreases slowly from the initial value of 1.0; when an overload condition occurs, the rate of decrease increases significantly.

[0047] Inverter Health Index The calculation formula is as follows: ; in, For IGBT power module junction temperature health factors, For the DC bus capacitor health factor, Harmonic distortion health factors; , , These are the weight coefficients of each factor, satisfying... As an example, the weights of each factor in the inverter are taken as follows: .

[0048] ; ; ; In the formula, For the first The cumulative number of power cycles within a junction temperature fluctuation range. To the junction temperature fluctuation amplitude and average junction temperature Number of failure cycles under the given conditions This is the current equivalent series resistance of the DC bus capacitor. This is the initial equivalent series resistance. This is the capacitor failure threshold, typically 2 to 3 times the initial value. The harmonic distortion rate of the inverter output current. The threshold for permissible harmonic distortion rate.

[0049] Interface device health index The calculation formula is as follows: ; ; ; ; The minimum value fusion strategy is adopted, meaning that the health status of the interface device is determined by the weakest link. Among other things... For switch operation health factors, As an insulating health factor, Temperature-related health factors; To accumulate the number of switch operations, This refers to the rated mechanical life cycles, typically taken as 10,000 cycles. The current insulation resistance, The initial insulation resistance, Minimum allowable insulation resistance, For the number of temperature anomalies, This is the threshold for the number of allowed temperature anomalies; min indicates taking the minimum value.

[0050] Then, in S33, the health index of the shore power system is calculated based on the health index of the key equipment.

[0051] Specifically, the shore power system includes: a transformer subsystem comprising transformers and cooling equipment. Inverter subsystem including inverter and filter and the interface subsystem including the interface box and connecting cables The subsystem-level health index is obtained by weighting its internal device-level health indices: In the formula, This represents the weighting coefficient of the health index of the j-th critical equipment in the k-th subsystem, satisfying 0 ≤ ≤1, and ; This represents the health index of the j-th critical device in the k-th subsystem; This represents the total number of critical devices in the k-th subsystem. Weighting coefficient. The determination can be made based on the equipment's rated capacity, the degree of impact of a failure, operational importance, or expert experience.

[0052] In one implementation, each subsystem is based on a core device, therefore: .

[0053] The system-level health index, i.e., the health index of the shore power system, is obtained by weighted fusion of the health indices of each subsystem: ; In the formula, 、 、 The weight coefficients for each subsystem satisfy the following conditions: As an example, weighting coefficients =0.35 、 = 0.45 、 = 0.2, the inverter has the highest weight because it is the core power conversion link of shore power supply, and its failure has the greatest impact.

[0054] Furthermore, the remaining service life of critical equipment can be predicted using a health index, with the following prediction formula: ; In the formula, The remaining service life of the i-th critical device; For the rated design life of the equipment, transformers are taken as 30 to 40 years (equivalent full-load operation time of about 180,000 hours), inverters as 10 to 15 years (about 90,000 hours), and interface equipment as 8 to 12 years. α is the current health index of the i-th critical device; α is the accelerated aging index, which is determined according to the device type. For transformers, α is 1.2 to 1.5, and for inverters, α is 1.5 to 2.0. The equivalent operating time of the equipment is obtained by integrating the cumulative curve of the health index: β is the time-weighted exponent. When When the equipment lifespan falls below the preset alarm threshold, the system automatically issues a device replacement warning. Figure 5 The non-linear relationship between remaining useful life (RUL) and health index is shown. It can be seen that during the period when the health index drops from 1.0 to 0.8, the remaining useful life (RUL) shortens slowly; when the health index is below 0.6, the remaining useful life (RUL) decreases rapidly, indicating that the equipment has entered the accelerated aging stage.

[0055] Then, in S4, grid connection condition parameter constraints are generated based on the health index of the shore power system, including grid connection permission flags, power limiting coefficients, and dynamic response adjustment coefficients.

[0056] According to embodiments of the present invention, such as Figure 6As shown, the health assessment results are transformed into input constraints for the grid-connected controller, establishing a closed-loop coordination mechanism between health status and grid-connected control. Grid-connected condition parameter constraints include grid-connected permission flags. Power limiting factor and dynamic response adjustment coefficient .

[0057] Scenario 1: When the system-level health index hour: The system performed grid connection operations normally. ;in, It is the highest threshold for system health.

[0058] Scenario 2: When hour: However, when the reduced-rated grid connection mode is activated, the power limiting coefficient... and dynamic response adjustment coefficient Calculate using the following formula: ; ; In the formula, This is the minimum requirement for system health (e.g., 0.6). This represents the highest threshold for system health (e.g., 0.85). The response adjustment coefficient can be taken from 0.5 to 1.0. For example, when When = 0.70, = (0.70 - 0.60) / (0.85 - 0.60) = 0.40, = 1 + 0.8×(1 - 0.40) = 1.48, which means that the maximum allowable grid-connected power is limited to 40% of the rated value, and the dynamic response adjustment coefficient is increased to 1.48 times.

[0059] Power limiting factor Limiting the maximum allowable rate of power change during grid connection, dynamic response adjustment coefficient The virtual inertia and damping coefficient of the virtual synchronous generator are used to adjust the system response more smoothly when the equipment health deteriorates, thereby reducing the impact stress on the equipment.

[0060] Scenario 3: When the system-level health index or any key equipment ( These are critical health values ​​for equipment, such as those corresponding to transformers. = 0.50, corresponding to the inverter = 0.55, corresponding to the interface device When = 0.45): Grid connection is prohibited; and a health alert is sent to the shore power management platform, indicating that equipment maintenance or replacement is required.

[0061] Then, in S5, it is determined whether the ship initiates a grid connection request. If a grid connection request is initiated, an adaptive grid connection strategy based on improved virtual synchronous generator control is executed under the constraints of grid connection condition parameters.

[0062] According to an embodiment of the present invention, it is determined whether the ship initiates a grid connection request; whether the ship initiates a grid connection request is determined by the grid connection request signal. Judgment. The grid connection request signal is generated by the ship's shore power interface communication message, the shore power management platform scheduling instruction, or the manual grid connection operation instruction. When When, the system remains in standby monitoring state; when At that time, the system reads the grid connection permission flag generated by S4. Power limiting factor and dynamic response adjustment coefficient ;like If the grid connection request is rejected and a health alert is issued; if Then it enters the pre-synchronization phase, and according to and Perform normal grid connection or reduced grid connection.

[0063] The improved adaptive grid connection strategy for virtual synchronous generator control includes a pre-synchronization phase and a grid connection operation phase.

[0064] (1) Pre-synchronization stage: Before the grid connection switch is closed, phase synchronization is used. Triple synchronization control of amplitude U and frequency f ensures that the shore power output voltage and the ship's grid voltage meet the grid connection requirements. The pre-synchronization stage calculates the amplitude difference between the shore power output voltage and the ship's grid voltage. Frequency difference and phase difference : ; ; ; When the following conditions are met: And the duration exceeds the preset confirmation time. When the pre-synchronization is completed, the grid connection switch can be closed. Indicates the phase of the ship's electrical grid voltage; , , These represent the amplitude, frequency, and phase of the output voltage on the port side, respectively. , , These represent the amplitude difference threshold, frequency difference threshold, and phase difference threshold, respectively. As an example, the synchronization threshold is set as follows: =5% of rated voltage = 0.05 Hz = 3°; when the triple synchronization conditions are met simultaneously and the duration exceeds When the time reaches 50 ms, the pre-synchronization is determined to be complete, and the grid connection switch is closed.

[0065] (2) Grid-connected operation phase: After the grid-connected switch is closed, switch to the improved virtual synchronous generator control mode.

[0066] In traditional virtual synchronous generator control, the active-frequency control equations typically employ fixed virtual moment of inertia and fixed virtual damping coefficients, and their expressions are as follows: ; The reactive power-voltage control equation is: ; In the formula, To fix the virtual moment of inertia, To fix the virtual damping coefficient, This is a reference value for active power. This refers to electromagnetic power or active power output from the inverter. This is the actual angular frequency. The rated angular frequency, The magnitude of the virtual internal potential. This is the no-load potential. This is the reactive power-voltage droop factor. This is a reference value for reactive power. To output reactive power.

[0067] This invention will fix parameters and Improved to adaptive parameters related to health assessment results and And introduce a power limiting coefficient The improved active-frequency control equation is: ; The reactive power-voltage control equations remain unchanged. Among them, the adaptive virtual moment of inertia... and adaptive virtual damping coefficient According to the system's health index Dynamic adjustment: ; ; ; ; In the formula, and These are the virtual moment of inertia reference value and the virtual damping coefficient reference value, respectively, which are adjusted according to the inverter capacity and dynamic response requirements; The dynamic response adjustment coefficient generated for S4; and All are based on the system's health index The smoothing adjustment function; , To adjust the upper and lower thresholds for inertia, , These are the upper and lower threshold values ​​for damping adjustment. Among them, the virtual moment of inertia reference value... Based on the inverter's rated capacity And expected response time tuning: In this embodiment Take 0.1 s; Virtual damping coefficient reference value Pick The parameters for the inertia adjustment function and the damping adjustment function are set as follows: H J,min = 0.6, H J,max =0.9, H D,min = 0.55, H D,max = 0.85.

[0068] Figure 7 The comparison of grid connection frequency response under different health states is shown, where a good health state is... When the frequency ratio is 0.90, the system responds quickly, with a maximum frequency deviation of 0.15 Hz and a recovery time of 2.1 s; its health status is generally good. When =0.70, = 0.40, = 1.48, the system response slowed down, the maximum frequency deviation was 0.22 Hz, and the recovery time was 2.6 s, but the power surge was greatly reduced, effectively protecting the aging equipment.

[0069] The above adaptive adjustment mechanism has the following effect: when the system health index is high, that is... When J(t) and D(t) are close to 1, they are close to the baseline value, indicating that the system has a fast response capability; when the system health index decreases, and Decrease, at the same time The combined effect of increasing the virtual inertia and damping coefficient is a moderate increase, a suitable slowdown in system response speed, and a constraint on the power change rate, thereby reducing the stress impact on aging equipment and achieving health-first adaptive grid connection.

[0070] Finally, in S6, after the ship-shore synchronous grid connection is completed, the ship-port joint digital twin model is continuously updated synchronously, and the health status of the shore power system is fed back to the grid connection controller in real time, forming a closed-loop optimization.

[0071] According to an embodiment of the present invention, the system continuously monitors changes in ship load and the operating status of the shore power system. When a sudden change in load or system status occurs, the digital twin model is updated in real time, the health assessment is dynamically refreshed, and the grid connection control parameters are adaptively adjusted accordingly to ensure safe operation throughout the entire cycle.

[0072] For example, during a 6-hour grid-connected power supply process, the transformer winding temperature rose due to load fluctuations, and the digital twin model detected a health index. The system-level health index decreased from 0.92 to 0.88. The corresponding value decreased from 0.89 to 0.86. Although It is still greater than 0.85, which is within the normal grid connection range. However, the grid connection controller has fine-tuned the virtual inertia and damping parameters according to the new health index, so that the response to subsequent load changes is smoother, and real-time tracking and active protection of the health status are realized.

[0073] Through the above steps S1 to S6, this invention forms a closed-loop system at four levels: edge perception, digital twin modeling, health assessment and life prediction, and adaptive grid-connected control. This achieves the organic integration of the health status of the shore power system and grid-connected control. It not only has engineering feasibility, but also has clear mathematical description and verifiability in health assessment model, life prediction, and adaptive adjustment of control parameters.

[0074] The technical effects of the present invention were further verified through experiments.

[0075] In a scenario where two vessels connect to shore power sequentially, when the first vessel docks and requests grid connection, the system executes steps S1-S6 as described above. During the grid connection process, the digital twin model continuously runs, accumulating and recording the thermal stress, electrical stress, and mechanical operating stress of the equipment. Before the second vessel requests grid connection, the system has already completed an updated assessment of the equipment health status during the first vessel's power supply period. If the health assessment results show a system-level health index... The value has decreased from 0.92 before grid connection to 0.72, so the system automatically enters the reduced-rate grid connection mode: Calculated... = 0.48, = 1.42. When the second vessel was connected to the grid, the system completed the pre-synchronization and grid connection switching with a low power change rate. The maximum frequency deviation during the grid connection process was 0.24 Hz, lower than 0.38 Hz under no health constraints; the power overshoot was 15%, far lower than 35% under no constraints. At the same time, the system pushed a "suggestion to arrange equipment maintenance" prompt to the shore power management platform.

[0076] If the health assessment results show that the health index of any critical equipment is below the critical value, for example, the cumulative cycle count of the inverter's IGBT is close to the failure threshold. = 0.48 < If the value is 0.55, the system rejects the second vessel's request to connect to the grid. = 0, and trigger an emergency alarm, prompting "The equipment health status does not meet the grid connection conditions, please arrange maintenance immediately".

[0077] In the health assessment effectiveness verification, a scenario was simulated where a shore power transformer operated continuously for 5000 hours under rated conditions. A digital twin thermal model accurately tracked the temperature changes of the transformer windings, and insulation aging health factors were calculated based on the cumulative temperature effect. The transformer health index gradually decreased from 1.0 to 0.92. The value decreased from 1.0 to 0.94. (Model-predicted remaining useful life) The time decreased from the initial 180,000 hours to 169,200 hours, which is more than 92% consistent with the actual accelerated aging test data.

[0078] In verifying the adaptive grid connection effect, three sets of comparative experiments were set up: Group A used traditional virtual synchronous generator fixed parameter control, i.e., J and D were constant; Group B used the adaptive control of the present invention, wherein the system health index was... =0.9, Group C adopts the adaptive control of this invention, which simulates the equipment aging scenario. =0.7. Experimental results show that under the same load step conditions, the maximum grid-connected frequency deviation of group C is 0.18 Hz, lower than that of group A (0.32 Hz); the frequency recovery time of group C is 2.8 s, shorter than that of group A (4.2 s); and the power overshoot of group C is 12%, far lower than that of group A (28%). When the value drops below 0.6, the system automatically prohibits grid connection and issues an alarm, verifying the effectiveness of the health constraint mechanism.

[0079] In another aspect, this invention proposes an adaptive grid connection system for ship-to-shore power systems based on digital twins. This system is used to implement the aforementioned adaptive grid connection method for ship-to-shore power systems based on digital twins. Figure 8 As shown, the system includes: Data acquisition module 810 is used to collect multi-source heterogeneous operational status data from both sides of the ship and port; The digital twin modeling module 820 is used to construct a joint digital twin model of the ship and port based on the physical topology and operational status data of both sides of the ship and port. Health assessment module 830 is used to determine the health status of the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data; Grid connection constraint generation module 840 is used to generate grid connection condition parameter constraints based on the health status of the shore power system; The adaptive grid connection control module 850 is used to determine whether the ship initiates a grid connection request. If a grid connection request is initiated, an adaptive grid connection strategy based on improved virtual synchronous generator control is executed under the constraints of grid connection condition parameters. The closed-loop feedback and synchronous update module 860 is used to continuously update the ship-port joint digital twin model after the ship-shore synchronous grid connection is completed, and the health status of the shore power system is fed back to the grid connection controller in real time, forming a closed-loop optimization.

[0080] It should be noted that the function of the adaptive grid connection system of a ship shore power system based on digital twin described in the embodiments of the present invention can be described by the aforementioned adaptive grid connection method of a ship shore power system based on digital twin. Therefore, for the parts not described in detail in the system embodiments, please refer to the above method embodiments, and they will not be repeated here.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive grid connection method for ship-to-shore power systems based on digital twins, characterized in that, Includes the following steps: Collect multi-source heterogeneous operational status data from both the ship and port sides; the multi-source heterogeneous operational status data includes ship-side operational status data and port-side operational status data. Based on the physical topology and operational status data of both sides of the ship and port, a joint digital twin model of ship and port is constructed. The health status of the shore power system is determined based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data. Generate grid connection condition parameter constraints based on the health status of the shore power system; Determine whether the ship initiates a grid connection request. If it does, execute an adaptive grid connection strategy based on improved virtual synchronous generator control under the constraints of grid connection condition parameters. After the ship-shore synchronous grid connection is completed, the ship-port joint digital twin model is continuously updated synchronously, and the health status of the shore power system is fed back to the grid connection controller in real time, forming a closed-loop optimization.

2. The adaptive grid connection method for a ship-to-shore power system based on digital twins according to claim 1, characterized in that, After collecting multi-source heterogeneous operational status data from both sides of the ship and port, the data cleaning process is also included, specifically: outlier removal and missing data filling, multi-source data timestamp alignment and resampling.

3. The adaptive grid connection method for a ship-to-shore power system based on digital twins according to claim 1, characterized in that, The ship-port joint digital twin model includes a ship-side equivalent circuit model, a port-side shore power inverter model, a shore power transformer thermal-aging model, and a ship-shore interface equipment model. The ship-side equivalent circuit model consists of an equivalent impedance network describing a linear load connected in parallel with a controlled current source describing a nonlinear load. The port-side shore power inverter model employs a combination of switching function modulation and dynamic filters, where the switching function describes the DC-to-AC voltage transformation, and the filters describe the dynamic response of the output current. The shore power transformer thermal-aging model uses thermoelectric analogy to describe the transformer's heating process and describes the insulation aging process based on the temperature accumulation effect. The ship-shore interface equipment model describes the electrical connections, switching states, protection relay operation logic, and communication protocol status of the shore power interface box. The ship-port joint digital twin model uses an extended Kalman filter algorithm to achieve real-time synchronization updates with the physical entities.

4. The adaptive grid connection method for a ship-to-shore power system based on digital twins according to claim 1, characterized in that, The determination of the health status of the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data includes: extracting multiple health characteristic parameters for each key device in the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data; calculating the health index of the key devices based on the health characteristic parameters; and calculating the health index of the shore power system based on the health index of the key devices. The key devices include transformers, shore power inverters, and ship-shore interface devices. The health indices of the key devices include transformer health index, inverter health index, and interface device health index.

5. The adaptive grid connection method for a ship-to-shore power system based on digital twins according to claim 4, characterized in that, The formula for calculating the transformer health index is as follows: ； In the formula, This represents the transformer health index at time t; For the health factor of winding hot spot temperature, , This refers to the hot spot temperature of the winding. This is a reference value for hotspot temperature. This is the temperature decay coefficient; As a health factor for insulation aging, , The degree of polymerization of insulating paper, For the amplitude limiting function, The initial degree of polymerization of the insulating paper. The degree of polymerization at the end of the lifetime; As a load rate health factor, , For transformer load rate, To achieve the optimal load rate, The penalty coefficient for load rate deviation; , , These are the weighting coefficients for temperature, insulation aging, and load rate factors, respectively, satisfying... ; The formula for calculating the inverter health index is as follows: ； In the formula, This indicates the inverter's health index; For IGBT power module junction temperature health factors, , For the first The cumulative number of power cycles within a junction temperature fluctuation range. To the junction temperature fluctuation amplitude and average junction temperature Number of failure cycles under the given conditions; For the DC bus capacitor health factor, , This is the current equivalent series resistance of the DC bus capacitor. This is the initial equivalent series resistance. This is the capacitor failure threshold; Harmonic distortion health factors , The harmonic distortion rate of the inverter output current. The threshold for allowable harmonic distortion rate; , , These are the weight coefficients of each factor, satisfying... ; The formula for calculating the health index of the interface device is as follows: ； In the formula, min represents taking the minimum value; For switch operation health factors, , To accumulate the number of switch operations, The rated mechanical lifespan; As an insulating health factor, , The current insulation resistance, The initial insulation resistance, Minimum allowable insulation resistance; As a temperature health factor, , For the number of temperature anomalies, The threshold for the number of times temperature anomalies are allowed.

6. The adaptive grid connection method for a ship-to-shore power system based on digital twins according to claim 5, characterized in that, The calculation of the shore power system's health index based on the health index of key equipment includes: weighting the health indices of multiple key equipment to obtain the health index of each subsystem; and weighting the health indices of multiple subsystems to obtain the health index of the shore power system.

7. The adaptive grid connection method for a ship-to-shore power system based on digital twins according to claim 6, characterized in that, The grid connection condition parameter constraints include the grid connection permission flag, power limiting coefficient, and dynamic response adjustment coefficient; The rules for generating grid connection condition parameter constraints are as follows: When the health index of the shore power system is greater than or equal to the preset maximum system health threshold, the grid connection permission flag is equal to 1, and the grid connection operation is performed normally; power limiting coefficient and dynamic response adjustment coefficient All equal to 1; When the health index of the shore power system is less than the preset maximum system health threshold but greater than or equal to the minimum system health threshold, the grid connection permission flag equals 1, and the derating grid connection mode is activated; power limiting coefficient and dynamic response adjustment coefficient Calculate using the following formula: ； ； In the formula, This is a health index for shore power systems. As the minimum requirement for system health, The highest threshold for system health. For response adjustment coefficient; When the health index of the shore power system is less than the preset minimum health threshold or the health index of any key device is less than the health threshold of that device, the grid connection permission flag is equal to 0, and grid connection is prohibited.

8. The adaptive grid connection method for a ship-to-shore power system based on digital twins according to claim 7, characterized in that, The adaptive grid connection strategy based on improved virtual synchronous generator control includes a pre-synchronization phase and a grid connection operation phase. The pre-synchronization phase employs phase-amplitude-frequency triple synchronization control to ensure that the shore power output voltage and the ship's grid voltage meet the grid connection requirements. The grid connection operation phase uses improved virtual synchronous generator control, with the active power-frequency control equation improved as follows: ； In the formula, This is a reference value for active power. This refers to electromagnetic power or active power output from the inverter. This is the actual angular frequency. The rated angular frequency is used; the adaptive virtual moment of inertia J(t) and the adaptive virtual damping coefficient D(t) are dynamically adjusted according to the health index of the shore power system as follows: ； ； ； ； In the formula, and These are the virtual moment of inertia reference value and the virtual damping coefficient reference value, respectively. and All are smoothing adjustment functions; , To adjust the upper and lower thresholds for inertia, , The upper and lower threshold values ​​are used for damping adjustment.

9. A method for adaptive grid connection of a ship-to-shore power system based on digital twins according to any one of claims 1-8, characterized in that, Also includes: After obtaining the health index of critical equipment, the remaining service life of the critical equipment is predicted according to the following formula: ； In the formula, The remaining service life of the i-th critical device; This refers to the rated service life of the equipment. The current health index of the device; α is the accelerated aging index; This is the equivalent operating time of the equipment.

10. An adaptive grid-connected system for ship-to-shore power systems based on digital twins, characterized in that, The system is used to implement the adaptive grid connection method for a ship-to-shore power system based on digital twins as described in any one of claims 1-9, the system comprising: The data acquisition module is used to collect multi-source heterogeneous operational status data from both sides of the ship and the port. The digital twin modeling module is used to construct a joint digital twin model of the ship and port based on the physical topology and operational status data of both sides of the ship and port. The health assessment module is used to determine the health status of the shore power system based on the ship-port joint digital twin model and the multi-source heterogeneous operating status data. The grid connection constraint generation module is used to generate grid connection condition parameter constraints based on the health status of the shore power system. The adaptive grid connection control module is used to determine whether the ship initiates a grid connection request. If a grid connection request is initiated, an adaptive grid connection strategy based on improved virtual synchronous generator control is executed under the constraints of grid connection condition parameters. The closed-loop feedback and synchronous update module is used to continuously update the ship-port joint digital twin model after the ship-shore synchronous grid connection is completed, and the health status of the shore power system is fed back to the grid connection controller in real time, forming a closed-loop optimization.

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