Port power grid toughness optimization method and system

Abstract

The invention relates to a port power grid toughness optimization method and system, and the method comprises the steps: obtaining the structure parameters and operation data of a port power grid, carrying out the scoring through employing a port power grid toughness index evaluation system, determining the weight of each index through employing a multi-layer index weight calculation method after obtaining the score of each index, and obtaining the toughness of the port power grid. And thus, a final port power grid toughness evaluation result is obtained, and the port power grid is optimized and adjusted. The first-level indexes of the evaluation system comprise a panoramic monitoring level, a flexible switching capability, a boundary protection level, a fault healing capability, a linkage response and a knowledge conversion capability; the multi-layer index weight calculation method comprises the following steps: calculating the subjective weight of each level of index by adopting a DEMATEL-AHP method, calculating the objective weight of each level of index by adopting an entropy weight method, and synthesizing the subjective weight and the objective weight to obtain a comprehensive weight. Compared with the prior art, the accuracy and credibility of the evaluation result are improved, and the toughness can be continuously improved.

Description

Technical Field

[0001] This invention relates to the field of power grid optimization technology, and in particular to a method and system for optimizing the resilience of port power grids. Background Technology

[0002] As a key hub in the modern logistics system and a core engine of regional economic development, the stable and reliable operation of the power grid in ports is of paramount importance. Disruptions to the port power grid due to extreme events such as natural disasters (e.g., typhoons, earthquakes), human attacks, or equipment failures can paralyze port operations, causing significant economic losses and supply chain risks. Therefore, scientifically assessing the "resilience" of port power grids—the grid's ability to anticipate, withstand, recover from, and adapt to faults after being subjected to disturbances—and accurately identifying its weaknesses has become an urgent need to ensure the safe operation of ports.

[0003] While existing technologies can assess grid resilience to some extent, they have the following significant drawbacks when applied to a specific complex system like a port power grid: Insufficient Specificity and Depth: Existing solutions are mostly general power grid models, failing to fully consider key factors unique to port power grids, such as resource characteristics (e.g., shore power systems, large loading and unloading equipment loads), grid structure (radial, ring, or hybrid structure), and geographical location (coastal, susceptible to meteorological disasters). Their evaluation index systems lack port-specific characteristics, leading to discrepancies between evaluation results and the actual resilience of port power grids.

[0004] The weighting methods are one-sided: while existing schemes combine subjective and objective weighting methods, they fail to deeply reveal the interactions and causal relationships among the various evaluation indicators. The AHP method relies on expert judgment and may be subject to subjective arbitrariness; the entropy weighting method only depends on the degree of data dispersion, which sometimes does not reflect the actual importance of the indicators. Combining these two methods can compensate for some of their respective shortcomings, but it is still not perfect. In particular, it is not suitable when the indicator structure is more complex, such as when the resilience of port power grids has multiple evaluation dimensions.

[0005] The identification of weak links is crude: Existing methods typically only output a comprehensive score or ranking, which, while reflecting which indicators have significant deficiencies, ignores the specific reasons for insufficient resilience, key weaknesses, and the transmission paths between different links during the calculation process. This makes the identified "weak links" often just a result, failing to provide guidance for future power grid construction and improving power grid resilience. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method and system for optimizing the resilience of port power grids, thereby improving the pertinence and depth of port power grid resilience assessment and optimization.

[0007] The objective of this invention can be achieved through the following technical solutions: A method for optimizing the resilience of a port power grid includes the following steps: The structural parameters and operational data of the port power grid are acquired, and a pre-set port power grid resilience index assessment system is used for scoring. After obtaining the scores of each index, a multi-level index weight calculation method is used to determine the weight of each level of index, thereby obtaining the final port power grid resilience assessment result. The primary indexes of the port power grid resilience index assessment system include panoramic monitoring level, flexible switching capability, boundary protection level, fault healing capability, linkage response, and knowledge transformation capability. The secondary indicators corresponding to the panoramic monitoring level include the real-time perception rate of key loads in the port area and the accuracy of AGV battery swapping demand prediction; the secondary indicators corresponding to the flexible switching capability include the rapid load shedding capability and various response speeds or sensitivities; the secondary indicators corresponding to the boundary protection level include reactive power capacity configuration margin and environmental adaptability; the secondary indicators corresponding to the fault healing capability include the recovery time of various functions and the actual fault isolation operation speed; the secondary indicators corresponding to the linkage response include various linkage and information interaction levels, as well as multi-party collaborative comprehensive evaluation; and the knowledge transformation capability includes the prediction accuracy of the port power grid resilience impact and the application and performance evaluation of new technologies.

[0008] Furthermore, the calculation expression for the real-time perception rate of the port area's critical loads is as follows: In the formula, Real-time sensing rate of critical loads in the port area. The number of i-resource units that are already equipped with monitoring devices. The weight allocated to resource i. The total number of i-resource units; The formula for calculating the accuracy of AGV battery swapping demand prediction is as follows: In the formula, To improve the accuracy of AGV battery swapping demand forecasting Predict the number of AGV battery swaps within a time period of length T starting at time t. The actual number of AGV battery swaps during a time period of length T starting at time t.

[0009] Furthermore, the calculation expression for the rapid load shedding capability is as follows: In the formula, To enable rapid load shedding, For non-core load capacity that can be remotely and quickly removed, Total load capacity; The calculation expressions for the various response speeds or sensitivities are as follows: In the formula, For various response speeds or sensitivities, For the removal speed of resource i, The weight for the response speed of resource i is determined by the removal rate. This represents the standard response speed for resource i.

[0010] Furthermore, the calculation expressions for the recovery time of the various functions are as follows: In the formula, For the recovery time of various functions, Configure capacity for reactive power. This represents the estimated maximum reactive power impact load capacity. The formula for calculating the environmental adaptability is: In the formula, For environmental adaptability, The defense level of the port area's power grid facilities is designed accordingly. This represents the highest disaster level in the area's five-year history.

[0011] Furthermore, the calculation expressions for the recovery time of the various functions are as follows: In the formula, For the recovery time of various functions, For the recovery speed of resource i, For the standard recovery speed of resource i, The recovery speed weight for resource i; The expression for calculating the actual fault isolation operation speed is as follows: In the formula, To determine the actual speed of fault isolation operations, This refers to the number of times the recovery time meets the set standard when a fault requiring restoration actually occurs within the past five years. This represents the actual number of faults that required restoration within the past five years.

[0012] Furthermore, the calculation expressions for the various levels of linkage and information interaction are as follows: In the formula, To enhance various levels of collaboration and information exchange, For the interaction level of resource i, The interaction importance weight of resource i, The design interaction level for resource i; The calculation expression for the multi-party collaborative comprehensive evaluation is as follows: In the formula, For multi-party collaborative and comprehensive evaluation, This represents the number of times that resource i and resource j have achieved the required interaction effectiveness in the past five years. This represents the number of interactions that have occurred between resource i and resource j in the past five years. The interaction importance weight between resource i and resource j; The formula for calculating the accuracy of the prediction of the port power grid resilience under impact is as follows: In the formula, To improve the accuracy of predictions regarding the resilience of port power grids to shocks. This represents the number of times the port power grid has been accurately predicted to be impacted in the past five years. This represents the actual number of times the port's power grid has been impacted in the past five years. The calculation expression for the application and performance evaluation of the new technology is as follows: In the formula, For the application and performance evaluation of new technologies, The number of times the port power grid is subjected to impacts is accurately predicted within a time period of length T starting at time t. This represents the actual number of times the port's power grid is impacted during a time period of length T, starting at time t. This represents the expected increase in accuracy due to the application of new technologies during time period T.

[0013] Furthermore, the secondary indicators corresponding to the panoramic monitoring level also include one or more of the following: completeness of monitoring of the operating conditions of the upper-level municipal power cables, panoramic perception capability of the main transformer operating status, sensitivity of shore power ship access perception, dynamic identification capability of distribution network topology, and monitoring rate of reactive power compensation equipment. The secondary indicators corresponding to the flexible switching capability also include one or more of the following: main transformer N-1 fault switching time, shore power system voltage sag tolerance capability, and distribution network bus islanding switching speed. The secondary indicators corresponding to the boundary protection level also include one or more of the following: external power supply corridor redundancy, main transformer N-1 operation redundancy configuration, shore crane / factory crane power supply circuit redundancy rate, AGV power swapping station power supply reliability level, port distribution network frame structure strength, and flood / typhoon protection standards. The secondary indicators corresponding to the fault healing capability also include one or more of the following: priority restoration rate of shore bridge power supply, accessibility of emergency resources for main transformer maintenance, black start power supply capacity coverage, and production synergy during the restoration process. The secondary indicators corresponding to the linkage response also include one or more of the following: compliance rate with the interface coordination standard of the ship's electrical system, frequency and depth of multi-department emergency drills, and effectiveness of government-enterprise emergency support agreements. The secondary indicators corresponding to the knowledge transformation capability also include one or more of the following: the level of construction of typical fault case library, the rate of exercise evaluation and closed-loop improvement, the coverage rate of special training for port power systems for employees, the dynamic update mechanism of resilience indicators, and the rate of benchmarking against peers and introduction of best practices.

[0014] Furthermore, the method for calculating the weight of the multi-level indicators is as follows: the subjective weight of each level of indicators is calculated using the DEMATEL-AHP method, the objective weight of each level of indicators is calculated using the entropy weight method, and the comprehensive weight is obtained by combining the subjective weight and the objective weight to determine the resilience assessment result of the port power grid. The DEMATEL-AHP method uses the DEMATEL method to calculate the weights of secondary indicators and the AHP method to calculate the weights of primary indicators. The processing steps of the DEMATEL method include: Obtain the direct impact matrix of the secondary indicators obtained by the expert method; Normalize each element of the matrix that directly affects it according to the sum of the largest row; Calculate the inverse matrix of the difference between the identity matrix and the normalized direct influence matrix, and multiply the normalized direct influence matrix by the inverse matrix to obtain the comprehensive influence matrix; The sum of data in each row D and the sum of data in each column E in the comprehensive influence matrix are calculated. The sum of data in each row D and the sum of data in each column E are then summed to obtain the centrality B of the corresponding element. Normalization is performed using the centrality of each element as the standard to obtain the weights of each secondary indicator; The AHP method processing procedure includes: Obtain the relative importance judgment matrix of the primary indicators obtained by the expert method; Calculate the eigenvalues ​​and eigenvectors of the relative importance judgment matrix, select the eigenvector corresponding to the eigenvalue with the largest real part, and for element j in the eigenvector, normalize it with the magnitude of element j to use as the weight of element j.

[0015] Furthermore, the entropy weight method processing includes: obtaining the evaluation results of multiple experts on each indicator whose weight is to be calculated, and constructing an evaluation matrix d; after normalizing the evaluation matrix d, calculating the anti-entropy value e of each element, using 1-e as the basis for weight calculation, and after normalizing, obtaining the weight of each indicator. The subjective and objective weights are geometrically averaged to obtain the comprehensive weight of the indicators. After normalization, the comprehensive weight is multiplied by the corresponding indicator scores to obtain the final port power grid resilience assessment result.

[0016] The present invention also provides a port power grid resilience optimization system, comprising: The data acquisition module is used to acquire the structural parameters and operational data of the port power grid; The resilience index scoring module is used to score each indicator using a preset port power grid resilience index assessment system. The resilience assessment module is used to determine the weights of each level of indicators using a multi-level indicator weighting calculation method, thereby obtaining the final port power grid resilience assessment result. The port power grid optimization module is used to optimize and adjust the port power grid based on the final port power grid resilience assessment results.

[0017] Compared with the prior art, the present invention has the following advantages: (1) Significantly improved assessment targeting and accuracy: This invention obtains first-hand data on resource characteristics, grid structure and geographical location of the target port power grid through on-site investigation, and constructs a resilience assessment index system in six key aspects, including flexible switching capability, boundary protection level, fault healing capability, panoramic monitoring level, linkage response and knowledge transformation capability. Among them, flexible switching capability, boundary protection level and fault healing capability are the core, corresponding to the key response capabilities of the port power grid in the three stages before, during and after disturbances, respectively; panoramic monitoring level and linkage response run through the entire disturbance process, not only providing support for the first three core capabilities, but also applicable to port daily operations and energy dispatch; knowledge transformation capability represents the port power grid's ability to summarize experience from historical events and achieve self-optimization, which is an important mechanism for its continuous improvement of resilience in long-term operation; The evaluation index system constructed by this invention is fundamentally closely aligned with the actual situation of port power grids, solving the problem of "incompatibility" of general models and greatly improving the accuracy and credibility of evaluation results.

[0018] (2) The weight determination method is scientific, comprehensive, and in-depth: This invention creatively integrates multiple methods, including AHP (Analytic Hierarchy Process), entropy weight method, and DEMATEL (Decision Laboratory and Evaluation Laboratory Method). First, the DEMATEL method is introduced to effectively analyze the mutual influence relationships and causal logic among various resilience indicators, thereby calculating the influence weights that reflect the true importance of the indicators in the system network. This step only calculates the weights of secondary indicators under a certain "major category of evaluation indicators" in the comprehensive evaluation. Further, in order to obtain the weights of each "major category of evaluation indicators," AHP is used to incorporate expert wisdom to determine subjective weights. Finally, the entropy weight method is used to mine measured data information to determine objective weights. This step also combines a multi-level indicator system, rather than only calculating a series of parallel indicators. Ultimately, the final comprehensive weights not only include human knowledge and reflect data patterns, but also reveal the internal structure of the system, making it more scientific and profound than the weight determination methods of existing technologies.

[0019] (3) Precise and Visualized Identification of Weak Links: By analyzing the causal degree and centrality obtained from DEMATEL, as well as the contribution and shortcomings of each indicator in the comprehensive score, this invention can clearly identify which are the "root causes" of low system resilience and which are the "outcome" links that are affected. This enables port power grid operators to make a leap from "assessment" to "diagnosis", and has stronger guiding significance. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a port power grid resilience optimization method provided in an embodiment of the present invention; Figure 2 This is an evaluation result diagram plotted based on the weights and scores of each key aspect in a comprehensive evaluation provided in an embodiment of the present invention. Figure 3 This is a schematic diagram of a port power grid resilience optimization system provided in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0022] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0023] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0024] Example 1 like Figure 1 As shown, this embodiment provides a port power grid resilience optimization method, including the following steps: The structural parameters and operational data of the port power grid are obtained, and a pre-set port power grid resilience index assessment system is used to score them. After obtaining the scores of each index, a multi-level index weight calculation method is used to determine the weight of each level of index, thereby obtaining the final port power grid resilience assessment result. The primary indicators of the port power grid resilience assessment system include the level of panoramic monitoring, flexible switching capability, boundary protection level, fault healing capability, linkage response, and knowledge transformation capability.

[0025] The above scheme is described in detail below: I. Primary Indicators 1.1 Panoramic Monitoring Level This refers to the ability to comprehensively, rapidly, and accurately perceive the operational status of the port power grid, port-specific environmental factors (such as ship berthing and departure, shore power connection, salt spray concentration, and wind speed changes), and the operating conditions of key equipment, and to predict potential risks. Its characteristics include: sensitivity (rapidly capturing subtle changes in the complex port environment and load), accuracy (precisely predicting typhoon paths, fluctuations in shore power demand, and equipment corrosion trends), and proactivity (actively detecting potential threats arising from the coupling between the power grid and port operations).

[0026] The indicator design focuses on three key aspects: port environment and operational condition sensing coverage, sensor robustness management, and port multi-source data fusion and mining. Specifically, the port environment and operational condition sensing coverage indicator measures the monitoring coverage of port-specific elements such as berth shore power status, large loading and unloading equipment start-up and shutdown, critical node corrosion, and nearshore meteorology, reflecting the system's sensitivity and accuracy in acquiring situational information. The sensor robustness management indicator assesses the availability, calibration rate, and protection level of sensors in high salt spray, high humidity, and strong vibration environments to ensure sensing reliability. The port multi-source data fusion and mining indicator evaluates the real-time transmission, intelligent correlation analysis, and proactive early warning capabilities of power grid data, port operation data (AIS, TOS), and meteorological and oceanographic data.

[0027] 1.2 Flexible switching capability This refers to the port power grid's ability to proactively predict the impact of extreme events (such as typhoon landfall or ship collision warnings) on shore power supply, critical equipment power supply, and network topology, based on port operation plans and environmental forecasts, and to formulate and implement targeted contingency plans. Its characteristics include: foresight (predicting risks based on port operations), efficiency (rapidly generating scenario-based contingency plans for the port), and reliability (ensuring the effectiveness of the plans in the complex port environment).

[0028] The indicator design primarily focuses on four aspects: port disaster prediction, predictable accident prevention, port risk assessment, and port scenario contingency plan development. Specifically, the port disaster prediction indicator measures the accuracy and lead time of forecasts for extreme weather events affecting ports, such as typhoons, storm surges, and heavy fog; the predictable accident prevention indicator assesses the power grid's ability to prevent typical port accidents by evaluating the N-1 / N-2 throughput rate and full shutdown / full rotation capability of the port's core loads (shore power and gantry cranes); the port risk assessment indicator identifies weak points in the port power grid by calculating power quality at shore power connection points, load margins of critical lines, and equipment corrosion indices; and the port scenario contingency plan development indicator measures the level of efficiency and reliability in developing contingency plans for specific scenarios such as emergency power supply for ship departures, emergency power supply for refrigerated containers in storage yards, and equipment protection against salt spray damage.

[0029] 1.3 Boundary Protection Level This refers to the ability of a port power grid to proactively implement defense strategies to contain the spread of impact and ensure core functions during the dynamic development of disturbance events (such as cyberattacks or localized failures) by coordinating controllable resources (energy storage, adjustable loads) on the port side. Its characteristics include: agility (rapid response to port disturbances), coordination (linking port resources for defense), and resilience (maintaining critical port services).

[0030] The indicator design mainly includes four aspects: active port disturbance suppression, port equipment resilience, network attack defense, and coordinated defense of power generation, grid, load, and port. Among them, the active port disturbance suppression indicator measures the speed and effectiveness of using port energy storage and interruptible loads for voltage support, frequency regulation, and fault isolation; the port equipment resilience indicator reflects the ability of medium-voltage shore power cables, terminal power distribution equipment, and automated control systems to withstand electrical shocks and environmental stresses; the network attack defense indicator focuses on evaluating the network security protection strength of the port's industrial control system and shore power management platform; and the coordinated defense of power generation, grid, load, and port measures the coordination efficiency and contribution of multiple resources such as the power grid, ships, energy storage, and port load during the defense process.

[0031] 1.4 Fault Healing Capability This refers to the ability of a port power grid to prioritize power supply to core loads such as shore power, loading and unloading equipment, and cold chain storage after damage, and to efficiently repair damaged facilities and restore the overall network function in complex port environments. Its characteristics include: priority (rapid restoration of power to core port loads), high efficiency (strong emergency repair capabilities in harsh environments), and comprehensiveness (including a black start solution for port scenarios).

[0032] The design of the indicators focuses on four aspects: port core load recovery, complex environment repair capability, port black start, and network reconfiguration autonomy. Specifically, the port core load recovery indicator measures the mean time to recovery (MTTR) and power supply reliability of shore power systems, large gantry cranes, and refrigerated container areas; the complex environment repair capability indicator assesses the efficiency of equipment repair and replacement after typhoons, in salt spray conditions, and under tidal influences; the port black start indicator focuses on the coverage area and startup success rate of power sources with black start capability in the core terminal area; and the network reconfiguration autonomy indicator reflects the reliability of maintaining power supply to local areas of the port after a fault through microgrid islanding and intelligent distribution network reconfiguration.

[0033] 1.5 Linkage Response This refers to the port power grid's ability to deeply coordinate with external entities such as port operators, maritime authorities, pilotage agencies, logistics companies, and emergency management departments, as well as with internal links such as the source, grid, load, storage, and port, to jointly respond to disturbances and restore operations. Its characteristics include: coordinated action (multi-department command coordination), mutual assistance (resource cross-system support), and seamless operation (efficient information sharing).

[0034] The indicator design covers four aspects: port-city emergency response coordination, transmission and distribution port synergy, power generation, grid-load, storage and port optimization, and cross-border / regional support. Among them, the port-city emergency response coordination indicator assesses the frequency of joint exercises and the completeness of information sharing mechanisms between the power grid company and port, maritime, and emergency management departments; the transmission and distribution port synergy indicator measures the power support capability and switching speed of the main grid, distribution grid, and port microgrid / shore power system during faults; the power generation, grid-load, storage and port optimization indicator focuses on the synergistic optimization effects such as ship load forecasting participation in dispatching and refrigerated container energy storage participation in peak shaving; and the cross-border / regional support indicator measures the accessibility and response efficiency of obtaining external emergency repair forces and temporary power supply equipment support.

[0035] 1.6 Knowledge Transformation Ability This refers to port power grids learning from their own failures and domestic and international port accident cases, proactively integrating new technologies such as corrosion-resistant materials, flexible DC transmission, and AI prediction, and continuously optimizing the dynamic adaptability of the resilience system through stress testing. Its characteristics include: self-driven (proactively tracking risks and technologies), iterative (continuous upgrading of systems and technologies), and verification (improvement through extreme scenario simulations).

[0036] The indicator design focuses on three aspects: port knowledge management, technological integration and innovation, and resilience simulation and improvement. Among them, the port knowledge management indicator measures the effectiveness of establishing a port accident case database, compiling targeted operation and maintenance manuals, and feedback closure rate; the technological integration and innovation indicator evaluates the application rate of new anti-corrosion coatings, the accuracy of port disaster AI models, and the iteration speed of digital twin systems; the resilience simulation and improvement indicator examines the dynamic improvement capability of the system through the application rate of results from regular typhoon full-process simulations and large-scale power outage stress tests, as well as the implementation rate of improvement measures.

[0037] Based on these six key aspects, a port power grid resilience optimization index system is constructed. These key aspects correspond to the six primary indicators of the port power grid resilience optimization system, and each key aspect has several secondary indicators. This multi-level system constitutes the port power grid resilience optimization index system. It should be noted that neither the number of primary nor secondary indicators is a fixed value. The index system used in this invention is only based on preliminary research conducted for this invention, and its purpose is to propose an architecture and method. Other researchers can arbitrarily add, subtract, and adapt it based on the actual situation of the target port power grid.

[0038] Secondary and secondary indicators The number of secondary indicators is more flexible and variable than that of primary indicators. Instead of listing them in as much detail as possible, this invention points out the indicator calculation method that is universal for power grids in various ports for demonstration purposes.

[0039] 2.1 Panoramic Monitoring Level (1) Real-time perception rate of critical loads in the port area: The critical loads in the port area mainly include quay cranes, factory cranes, and AGVs, including: In the formula, Real-time sensing rate of critical loads in the port area. The number of i-resource units that are already equipped with monitoring devices. The weight allocated to resource i is: , The total number of i-resource units; (2) Accuracy of AGV battery swapping demand forecast: In the formula, To improve the accuracy of AGV battery swapping demand forecasting Predict the number of AGV battery swaps within a time period of length T starting at time t. The actual number of AGV battery swaps during a time period of length T starting at time t.

[0040] 2.2 Flexible switching capability (1) Rapid load shedding capability: In the formula, To enable rapid load shedding, For non-core load capacity that can be remotely and quickly removed, Total load capacity; (2) Various response speeds or sensitivities: In the formula, For various response speeds or sensitivities, among which Let i be the rate at which resource i is removed (expressed in response time). For the standard response speed of resource i, The weight for the response speed of resource i is determined by the resource i. i can take values ​​such as the main transformer N-1 fault switching time, AGV dispatch response time to grid commands, SVG dynamic reactive power response speed, and distribution network bus islanding switching speed.

[0041] 2.3 Boundary Protection Level (1) Reactive power capacity configuration margin: In the formula, For the recovery time of various functions, Configure capacity for reactive power. This represents the estimated maximum reactive power impact load capacity. (2) Environmental adaptability: In the formula, For environmental adaptability, The defense level of the port area's power grid facilities is designed accordingly. This represents the highest disaster level in the area's five-year history.

[0042] 2.4 Fault Healing Capability (1) Recovery time for various functions: In the formula, For the recovery time of various functions; Let i be the recovery speed of resource i (expressed as recovery time). For the standard recovery speed of resource i, The recovery speed weight is denoted by i. i can take the recovery speed of the quay crane power supply, the recovery speed of the AGV battery swapping function, the recovery speed of the long-distance grid busbar, etc.

[0043] (2) Actual fault isolation operation speed: In the formula, To determine the actual speed of fault isolation operations, This refers to the number of times the recovery time meets the set standard when a fault requiring restoration actually occurs within the past five years. This represents the actual number of faults that required restoration within the past five years.

[0044] 2.5 Linkage Response: (1) Level of various linkages and information exchange: In the formula, To enhance various levels of collaboration and information exchange, For the interaction level of resource i, The interaction importance weight of resource i, The design interaction level of resource i; i can take port-power grid dispatch information interaction, power grid-production dispatch linkage, and ship-shore real-time information interaction.

[0045] (2) Multi-party collaborative comprehensive assessment: In the formula, For multi-party collaborative and comprehensive evaluation, This represents the number of times that resource i and resource j have achieved the required interaction effectiveness in the past five years. This represents the number of interactions that have occurred between resource i and resource j in the past five years. The interaction importance weights between resource i and resource j; i and j can be power grids, ports, production departments, ships, etc.

[0046] 2.6 Knowledge Transformation Ability (1) Prediction accuracy of the resilience of port power grids under impact: In the formula, To improve the accuracy of predictions regarding the resilience of port power grids to shocks. This represents the number of times the port power grid has been accurately predicted to be impacted in the past five years. This represents the actual number of times the port's power grid has been impacted in the past five years. (2) Application and performance evaluation of new technologies: In the formula, For the application and performance evaluation of new technologies, The number of times the port power grid is subjected to impacts is accurately predicted within a time period of length T starting at time t. This represents the actual number of times the port's power grid is impacted during a time period of length T, starting at time t. This represents the expected increase in accuracy due to the application of new technologies during time period T.

[0047] After designing a comprehensive indicator evaluation system and calculating the scores of each indicator, you can begin to calculate the weight of each indicator.

[0048] Optionally, the secondary indicators corresponding to the panoramic monitoring level may include one or more of the following: completeness of monitoring of the operating conditions of the municipal power cables, panoramic perception capability of the main transformer operating status, sensitivity of shore power ship access perception, dynamic identification capability of distribution network topology, and monitoring rate of reactive power compensation equipment. The secondary indicators corresponding to flexible switching capability also include one or more of the following: main transformer N-1 fault switching time, shore power system voltage sag tolerance capability, and distribution network bus islanding switching speed; The secondary indicators corresponding to the boundary protection level also include one or more of the following: external power supply corridor redundancy, main transformer N-1 operation redundancy configuration, shore crane / plant crane power supply circuit redundancy rate, AGV power swapping station power supply reliability level, port distribution network frame structure strength, and flood / typhoon protection standards. The secondary indicators corresponding to fault healing capability also include one or more of the following: priority restoration rate of shore crane power supply, accessibility of emergency resources for main transformer maintenance, black start power supply capacity coverage, and production synergy during the recovery process. The secondary indicators for coordinated response also include one or more of the following: compliance rate with standards for interface coordination with ship electrical systems, frequency and depth of multi-department emergency drills, and effectiveness of government-enterprise emergency support agreements; The secondary indicators corresponding to knowledge transformation capability also include one or more of the following: the level of construction of typical failure case library, the rate of exercise evaluation and closed-loop improvement, the coverage rate of special training for port power systems for employees, the dynamic update mechanism of resilience indicators, and the rate of benchmarking against peers and introduction of best practices.

[0049] III. Multi-level indicator weight calculation method Preferably, the multi-level indicator weight calculation method is as follows: the subjective weight of each level of indicator is calculated using the DEMATEL-AHP method, the objective weight of each level of indicator is calculated using the entropy weight method, and the comprehensive weight is obtained by combining the subjective weight and the objective weight to determine the resilience assessment result of the port power grid. The specific description is as follows: First, the indicator system constructed in this invention is divided into two layers: six key aspects as primary indicators and a number of secondary indicators, each of which must belong to a primary indicator. Therefore, the weight calculation is divided into two parts. The first part is the weight of the secondary indicator under each primary indicator. For example, if there are seven secondary indicators under "panoramic monitoring level," then the sum of the weights of these seven indicators should be 1. It must be emphasized that this applies to the object "panoramic monitoring level." The second part is the weight of each primary indicator. Before calculating the weight of the primary indicator in the total indicators, it may be necessary to calculate the weight of each secondary indicator and perform some operations. This may not be necessary.

[0050] The weight calculation method proposed in this embodiment is divided into subjective and objective parts, each adapted to the calculation of two levels of indicators. The subjective part employs the DEMATEL-AHP method, where the DEMATEL method is used to calculate the weights of secondary indicators, and the AHP method is used to calculate the weights of primary indicators. The direct influence matrix required by the DEMATEL method and the importance judgment matrix required by the AHP method are provided by authoritative experts. The objective part utilizes the entropy weight method, where multiple experts conduct qualitative evaluations and scores for each secondary indicator. First, the weights of the secondary indicators are calculated based on their scores. Then, the primary indicator scores are obtained by weighting the objectively calculated secondary indicator scores according to these weights. Finally, the primary indicator weights are calculated using the calculated primary indicator scores. After normalization, the subjective and objective weights are first transformed into the form of the weights of the secondary indicators within the total indicators. Then, a geometric average is applied and normalized to obtain the final weights of each secondary indicator. Alternatively, the overall evaluation result can be obtained by summing the weights of all secondary indicators under a certain primary indicator to obtain the weight of that primary indicator. This method combines expert experience with data-driven approaches, improving the scientific rigor and robustness of weight allocation. The calculation process is as follows: Figure 1 As shown.

[0051] 3.1 Demetel Method Decision laboratory analysis is a methodology in systems science, employing graph theory and matrix tools for system analysis. By analyzing the logical relationships and direct influence matrices among the elements in a system, the influence and affected degree of each element on other elements can be calculated, thereby determining the causal degree and centrality of each element. This serves as the basis for constructing a model, ultimately determining the causal relationships between elements and the position of each element within the system. This method requires a relatively clear correlation between factors, rather than directly judging their importance. Considering that primary indicators address different directions for evaluating the overall indicator, and the correlation between primary indicators is actually low, the Dematel method is not applicable. However, secondary indicators under a primary indicator are all evaluation content related to that primary indicator, exhibiting extremely high correlation, yet unsuitable for directly evaluating their importance; therefore, the Dematel method is applicable. Thus, the Dematel method is used to calculate the subjective weights of each secondary indicator under a primary indicator.

[0052] The direct impact matrix provided by authoritative experts is as follows: As you can see, this is an n*n square matrix, where n is the number of mutually influencing factors. This represents the degree of direct influence of factor i on factor j, and is a non-negative number with no limit on its range, only requiring that all elements of the matrix share the same evaluation criterion (normalization must be performed subsequently). Since the influence of a factor on itself is meaningless, the diagonal elements are set to 0. Furthermore, the matrix elements do not need to satisfy... For a given value, if factor i has a significant effect on factor j, then factor j can have a more significant effect on factor i. This differs from the relative importance judgment matrix.

[0053] Normalizing the direct influence matrix yields W', which has... in satisfy: The divisor satisfies: That is, normalization is performed based on the maximum row sum.

[0054] Then, calculate the inverse matrix of the difference between the identity matrix and the normalized direct influence matrix. Multiplying the normalized direct influence matrix by the inverse matrix yields the comprehensive influence matrix, i.e.: By statistically summing the rows (D) and columns (E) in the comprehensive influence matrix, we can obtain the influence degree of the element corresponding to that row and the degree of influence of the element corresponding to that column. This is because a row records the degree of influence of the element corresponding to that row on all elements, while a column records the degree of influence of the element corresponding to that column on all elements. Summing D and E yields the centrality B of the element, representing its importance. By normalizing again using centrality B as the standard, the weights of each secondary indicator can be obtained. 3.2 AHP method The main idea of ​​the Analytic Hierarchy Process (AHP) is to decompose a complex problem into several levels and factors, compare the importance of each pair of indicators, establish a judgment matrix, and calculate the weights of the importance of different solutions by calculating the largest eigenvalue and the corresponding eigenvector of the judgment matrix, thus providing a basis for selecting the optimal solution. This method is suitable for situations where the correlation between factors is not high. Based on the subjective importance judgment matrix of experts, it calculates the importance of different directions represented by six key aspects.

[0055] The relative importance judgment matrix given by authoritative experts is as follows: The elements in the matrix above satisfy: Because in a logically sound judgment, if A is more important than B, then B must be less important than A. The scale is 1-9, where 9 represents that element i is much more important than element j, and 1 represents that the two elements are about the same importance.

[0056] Then calculate the eigenvalues ​​and eigenvectors of the matrix: Take the eigenvalue with the largest real part, and let its index be i, that is... Select the eigenvector corresponding to this eigenvalue ,make Representing the eigenvector The j-th element is then normalized according to its modulus to serve as the weight of factor j, i.e. It should be noted that if we consider the eigenvector matrix to be X, then we have This is because the i-th eigenvector actually corresponds to the i-th column in the eigenvector matrix, and j represents the index of the factor weight to be determined, which is actually the row number in that column.

[0057] 3.3 Entropy Weight Method According to the basic principles of information theory, information is a measure of the orderliness of a system, while entropy is a measure of the disorderliness of a system. Based on the definition of information entropy, for a given indicator, the entropy value can be used to judge the degree of dispersion of that indicator. The smaller the information entropy value, the greater the dispersion of the indicator, and the greater its influence (i.e., weight) on the comprehensive evaluation. If all values ​​of an indicator are equal, then that indicator has no effect in the comprehensive evaluation. Therefore, information entropy can be used to calculate the weight of each indicator, providing a basis for multi-indicator comprehensive evaluation. It can be seen that the entropy weight method does not concern itself with people's subjective judgments, but focuses on the objective characteristics of certain parameters or indicators. For example, when all experts agree on the score of a certain indicator, regardless of whether the score is high or low, it indicates that its evaluation rules are completely fixed, and no expert believes that there is room for change in the indicator. Therefore, this indicator has insufficient value or efficiency to be prioritized for improvement, and naturally, it will not have any weight in the overall evaluation. Some studies use the anti-entropy weight method to calculate weights, arguing that it is difficult to find improvement directions for indicators with large evaluation differences, while indicators with small differences should be given priority. However, this invention argues that this view is invalid. For example, when all experts believe that a certain indicator deserves full marks and there is no room for improvement, the weight obtained by the anti-entropy weight method is meaningless. On the other hand, indicators with large differences in evaluation indicate that the evaluation standards and related measures still need to be improved and should be given priority.

[0058] This invention assumes that m experts evaluate n factors whose weights need to be calculated, and the evaluation matrix is ​​as follows: In the formula Let represent the score of the i-th expert on factor j. Then, d is normalized, with the goal of amplifying the differences in scores among experts, normalizing experts with different score ranges to a range of 0-1, where 0 represents the lowest score and 1 represents the unique highest score. Then, normalization is performed again so that the sum of all factors is 1, i.e.: Next, we calculate the inverse entropy value: Clearly, the value of i is 1, 2, ..., n. Considering that when there are many factors, the value of e will be very close to 1, we let 1-e be used as the basis for calculating the weights and then normalize it, that is... The entropy weighting method is applicable to both primary and secondary indicators. It only requires inputting scores from multiple experts for multiple factors. As mentioned earlier, after calculating the weights of the secondary indicators, the weights of the primary indicators need to be further calculated. However, this requires calculating the scores of the primary indicators. Therefore, a weighted calculation method for the primary indicator scores from each expert is provided. In the formula, Let j be the score given by the j-th expert to the i-th primary indicator. It represents the original score given by the j-th expert to the k-th secondary indicator within the i-th primary indicator. It is the weight of the kth secondary indicator in the i-th primary indicator calculated in the previous step.

[0059] 3.4 Comprehensive Calculation Finally, the overall weight is obtained by combining subjective and objective weights. First, the subjective and objective weights for the sub-indicators are calculated, namely: In the formula, C represents the weight of the secondary indicator (i.e., the sum of dozens of such weights may be 1), i is the primary indicator number, j is the secondary indicator number, c is the weight of the primary indicator calculated by the method above, or the weight of each secondary indicator under the primary indicator, s represents subjective, and o represents objective. Then, the geometric mean is used as the comprehensive weight of the indicators and normalized, that is: In the formula, n is the number of secondary indicators under the i-th primary indicator. The number of primary indicators is considered to be 6 (which can be modified arbitrarily according to the actual situation).

[0060] Then the total score G and the total points lost can be calculated, that is: In the formula The deduction in the comprehensive evaluation caused by the j-th secondary indicator within the i-th primary indicator, sorted in descending order, identifies the weakest links in the port's power grid. Returning to the comprehensive impact matrix obtained using the DEMATEL method, we can further analyze the causes and consequences of these weaknesses, allowing for targeted maintenance or improvement of the root causes and prevention of more serious threats or hidden dangers that may arise from the weakness in these links.

[0061] The following is a specific example illustrating the process of the above scheme, such as... Figure 1 As shown, it includes the following steps: S1: Design an indicator system and calculate the indicator scores based on the specific conditions of the port power grid.

[0062] After conducting research, this invention established six primary indicators, each of which corresponds to 7, 6, 8, 7, 6, and 7 secondary indicators. The specific information of these indicators is shown in Table 1.

[0063] Table 1 Then, the scores for each indicator are calculated using the formulas shown in Table 2 or the form of expert qualitative assessment.

[0064] Table 2 S2: Combining the direct impact matrix provided by authoritative experts, the DEMATEL method is used to calculate the subjective weights of each secondary indicator under each primary indicator. The calculation process is illustrated below using panoramic monitoring level as an example.

[0065] S201: Please provide the direct impact matrix from authoritative experts, as shown in Table 3.

[0066] Table 3 S202: Normalize according to the maximum row sum.

[0067] S203: Calculate the comprehensive influence matrix.

[0068] S204: Calculate the centrality and normalize it to obtain the subjective weights of the secondary indicators, as shown in Table 4.

[0069] Table 4 S3: Calculate the subjective weights of the primary indicators based on the relative importance matrix and the AHP method.

[0070] S301: Invite authoritative experts to provide a relative importance matrix, as shown in Table 5.

[0071] Table 5 S302: Find its eigenvalues ​​and eigenvectors, as shown in Tables 6 and 7.

[0072] Table 6 Table 7 S303: Subjective weights of first-level indicators are normalized according to the magnitude of the eigenvector corresponding to the real part of the largest eigenvalue, as shown in Table 10.

[0073] Table 8 S4: Based on the expert scoring table, the objective weight of each indicator is calculated using the entropy weight method.

[0074] S401: Experts provide a scoring table. Taking panoramic monitoring level as an example, as shown in Table 9.

[0075] Table 9 S402: Standardize and normalize the scoring table by column.

[0076] S403: Calculate the entropy value of the secondary index.

[0077] S404: Normalize according to the coefficient of variation to obtain the objective weight of the secondary indicator.

[0078] S405: The scores from each expert are weighted according to the weights obtained in S404 to obtain the primary indicator scores for each expert.

[0079] S406: Obtain the objective weight of the primary indicator through the same process as S402-S404.

[0080] S5: Calculate the overall weight of each secondary indicator.

[0081] S501: Give the subjective and objective weights of each secondary indicator in the comprehensive evaluation.

[0082] S502: Obtain the comprehensive weight of the secondary indicators using the geometric mean method.

[0083] S6: Results summary and visualization.

[0084] S601: Draw an evaluation result graph according to the weights and scores of each key aspect in the comprehensive evaluation, such as... Figure 2 As shown.

[0085] S602: Summarize the comprehensive scores of secondary indicators (i.e., weighted scores, not percentages) and primary indicators, i.e., refine the scores. Figure 2 The parameters are shown in Table 10.

[0086] Table 10 S603: Statistics on the combined deductions and rankings of secondary and primary indicators are shown in Table 11.

[0087] Table 11 S604: Analyze the results and draw conclusions.

[0088] As can be seen from the table above, although the boundary protection level has the lowest overall score, it does not have the greatest impact on the final overall evaluation. On the other hand, the flexible switching capability, which has the second highest overall score, is the biggest factor in the deduction of points in the overall evaluation.

[0089] The comprehensive evaluation in the table above identifies weaknesses in the resilience of the port power grid. It's clear that the primary areas for improvement should be flexible switching capabilities and knowledge transfer capabilities, reflecting a potential lack of resilience in the currently operational port power grid due to insufficient responsiveness and self-learning ability. Specifically, the five secondary indicators C12, C40, C13, C30, and C9 are the weakest: SVG dynamic reactive power response speed, new technology application and effectiveness assessment, distribution network bus islanding switching speed, the completeness of the power grid-production dispatching linkage mechanism, and main transformer N-1 fault switching time. Improving the resilience of the port power grid should begin with addressing these aspects.

[0090] Example 2 like Figure 3 As shown, this embodiment provides a port power grid resilience optimization system, including: The data acquisition module is used to acquire the structural parameters and operational data of the port power grid; The resilience index scoring module is used to score each indicator using a preset port power grid resilience index assessment system. The resilience assessment module is used to determine the weights of each level of indicators using a multi-level indicator weighting calculation method, thereby obtaining the final port power grid resilience assessment result. The port power grid optimization module is used to optimize and adjust the port power grid based on the final port power grid resilience assessment results.

[0091] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for optimizing the resilience of a port power grid, characterized in that, Includes the following steps: The structural parameters and operational data of the port power grid are obtained, and a pre-set port power grid resilience index evaluation system is used to score them. After obtaining the scores of each index, a multi-level index weight calculation method is used to determine the weight of each level of index, thereby obtaining the final port power grid resilience evaluation result, and thus optimizing and adjusting the port power grid. The primary indicators of the port power grid resilience assessment system include panoramic monitoring level, flexible switching capability, boundary protection level, fault healing capability, linkage response and knowledge transformation capability. The secondary indicators corresponding to the panoramic monitoring level include the real-time perception rate of key loads in the port area and the accuracy of AGV battery swapping demand prediction; the secondary indicators corresponding to the flexible switching capability include the rapid load shedding capability and various response speeds or sensitivities; the secondary indicators corresponding to the boundary protection level include reactive power capacity configuration margin and environmental adaptability; the secondary indicators corresponding to the fault healing capability include the recovery time of various functions and the actual fault isolation operation speed; the secondary indicators corresponding to the linkage response include various linkage and information interaction levels, as well as multi-party collaborative comprehensive evaluation. The knowledge transformation capability includes the accuracy of predicting the impact on the resilience of port power grids and the application and performance evaluation of new technologies.

2. The port power grid resilience optimization method according to claim 1, characterized in that, The formula for calculating the real-time sensing rate of key loads in the port area is as follows: In the formula, Real-time sensing rate of critical loads in the port area. The number of i-resource units that are already equipped with monitoring devices. The weight allocated to resource i. The total number of i-resource units; The formula for calculating the accuracy of AGV battery swapping demand prediction is as follows: In the formula, To improve the accuracy of AGV battery swapping demand forecasting Predict the number of AGV battery swaps within a time period of length T starting at time t. The actual number of AGV battery swaps during a time period of length T starting at time t.

3. The port power grid resilience optimization method according to claim 1, characterized in that, The calculation expression for the rapid load shedding capability is as follows: In the formula, To enable rapid load shedding, For non-core load capacity that can be remotely and quickly removed, Total load capacity; The calculation expressions for the various response speeds or sensitivities are as follows: In the formula, For various response speeds or sensitivities, For the removal speed of resource i, The weight for the response speed of resource i is determined by the removal rate. This represents the standard response speed for resource i.

4. The port power grid resilience optimization method according to claim 1, characterized in that, The calculation expressions for the recovery time of the various functions are as follows: In the formula, For the recovery time of various functions, Configure capacity for reactive power. This represents the estimated maximum reactive power impact load capacity. The formula for calculating the environmental adaptability is: In the formula, For environmental adaptability, The defense level of the port area's power grid facilities is designed accordingly. This represents the highest disaster level in the area's five-year history.

5. The port power grid resilience optimization method according to claim 1, characterized in that, The calculation expressions for the recovery time of the various functions are as follows: In the formula, For the recovery time of various functions, For the recovery speed of resource i, For the standard recovery speed of resource i, The recovery speed weight for resource i; The expression for calculating the actual fault isolation operation speed is as follows: In the formula, To determine the actual speed of fault isolation operations, This refers to the number of times the recovery time meets the set standard when a fault requiring restoration actually occurs within the past five years. This represents the actual number of faults that required restoration within the past five years.

6. The port power grid resilience optimization method according to claim 1, characterized in that, The calculation expressions for the various levels of linkage and information interaction are as follows: In the formula, To enhance various levels of collaboration and information exchange, For the interaction level of resource i, The interaction importance weight of resource i, The design interaction level for resource i; The calculation expression for the multi-party collaborative comprehensive evaluation is as follows: In the formula, For multi-party collaborative and comprehensive evaluation, This represents the number of times that resource i and resource j have achieved the required interaction effectiveness in the past five years. This represents the number of interactions that have occurred between resource i and resource j in the past five years. The interaction importance weight between resource i and resource j; The formula for calculating the accuracy of the prediction of the port power grid resilience under impact is as follows: In the formula, To improve the accuracy of predictions regarding the resilience of port power grids to shocks. This represents the number of times the port power grid has been accurately predicted to be impacted in the past five years. This represents the actual number of times the port's power grid has been impacted in the past five years. The calculation expression for the application and performance evaluation of the new technology is as follows: In the formula, For the application and performance evaluation of new technologies, The number of times the port power grid is subjected to impacts is accurately predicted within a time period of length T starting at time t. This represents the actual number of times the port's power grid is impacted during a time period of length T, starting at time t. This represents the expected increase in accuracy due to the application of new technologies during time period T.

7. The port power grid resilience optimization method according to claim 1, characterized in that, The secondary indicators corresponding to the panoramic monitoring level also include one or more of the following: completeness of monitoring of the operating conditions of the upper-level municipal power cables, panoramic perception capability of the main transformer operating status, sensitivity of shore power ship access perception, dynamic identification capability of distribution network topology, and monitoring rate of reactive power compensation equipment. The secondary indicators corresponding to the flexible switching capability also include one or more of the following: main transformer N-1 fault switching time, shore power system voltage sag tolerance capability, and distribution network bus islanding switching speed. The secondary indicators corresponding to the boundary protection level also include one or more of the following: external power supply corridor redundancy, main transformer N-1 operation redundancy configuration, shore crane / factory crane power supply circuit redundancy rate, AGV power swapping station power supply reliability level, port distribution network frame structure strength, and flood / typhoon protection standards. The secondary indicators corresponding to the fault healing capability also include one or more of the following: priority restoration rate of shore bridge power supply, accessibility of emergency resources for main transformer maintenance, black start power supply capacity coverage, and production synergy during the restoration process. The secondary indicators corresponding to the linkage response also include one or more of the following: compliance rate with the interface coordination standard of the ship's electrical system, frequency and depth of multi-department emergency drills, and effectiveness of government-enterprise emergency support agreements. The secondary indicators corresponding to the knowledge transformation capability also include one or more of the following: the level of construction of typical fault case library, the rate of exercise evaluation and closed-loop improvement, the coverage rate of special training for port power systems for employees, the dynamic update mechanism of resilience indicators, and the rate of benchmarking against peers and introduction of best practices.

8. The port power grid resilience optimization method according to claim 1, characterized in that, The method for calculating the weight of the multi-level indicators is as follows: the subjective weight of each level of indicators is calculated using the DEMATEL-AHP method, the objective weight of each level of indicators is calculated using the entropy weight method, and the comprehensive weight is obtained by combining the subjective weight and the objective weight to determine the resilience assessment result of the port power grid. The DEMATEL-AHP method uses the DEMATEL method to calculate the weights of secondary indicators and the AHP method to calculate the weights of primary indicators. The processing steps of the DEMATEL method include: Obtain the direct impact matrix of the secondary indicators obtained by the expert method; Normalize each element of the matrix that directly affects it according to the sum of the largest row; Calculate the inverse matrix of the difference between the identity matrix and the normalized direct influence matrix, and multiply the normalized direct influence matrix by the inverse matrix to obtain the comprehensive influence matrix; The sum of data in each row D and the sum of data in each column E in the comprehensive influence matrix are calculated. The sum of data in each row D and the sum of data in each column E are then summed to obtain the centrality B of the corresponding element. Normalization is performed using the centrality of each element as the standard to obtain the weights of each secondary indicator; The AHP method processing procedure includes: Obtain the relative importance judgment matrix of the primary indicators obtained by the expert method; Calculate the eigenvalues ​​and eigenvectors of the relative importance judgment matrix, select the eigenvector corresponding to the eigenvalue with the largest real part, and for element j in the eigenvector, normalize it with the magnitude of element j to use as the weight of element j.

9. A port power grid resilience optimization method according to claim 8, characterized in that, The entropy weight method includes the following steps: obtaining the evaluation results of multiple experts on each indicator whose weight is to be calculated, and constructing an evaluation matrix d; normalizing the evaluation matrix d and calculating the inverse entropy value e of each element, using 1-e as the basis for weight calculation, and normalizing it to obtain the weight of each indicator. The subjective and objective weights are geometrically averaged to obtain the comprehensive weight of the indicators. After normalization, the comprehensive weight is multiplied by the corresponding indicator scores to obtain the final port power grid resilience assessment result.

10. A system for implementing a port power grid resilience optimization method as described in any one of claims 1-9, characterized in that, include: The data acquisition module is used to acquire the structural parameters and operational data of the port power grid; The resilience index scoring module is used to score each indicator using a preset port power grid resilience index assessment system. The resilience assessment module is used to determine the weights of each level of indicators using a multi-level indicator weighting calculation method, thereby obtaining the final port power grid resilience assessment result. The port power grid optimization module is used to optimize and adjust the port power grid based on the final port power grid resilience assessment results.

Images