Substation quantum key distribution system environment adaptation and security assessment method and system

Abstract

The invention provides a transformer substation quantum key distribution system environment adaptation and safety assessment method, which comprises the steps of performing preprocessing such as filtering, smoothing and abnormal value elimination on acquired original data, and synchronizing all the data to a unified time axis; a decision tree model is constructed, nodes comprise environmental factors such as electromagnetic interference and temperature fluctuation, and the weight of each evaluation index is dynamically adjusted according to real-time environmental data; the method comprises the following steps: simulating various typical environments of a transformer substation in a digital twin environment, generating virtual test data, and performing experimental verification on various indexes of a quantum key distribution system; a multi-level scoring model is adopted to perform weighted scoring on levels such as light source safety, detection safety and decoy state protocol conformity; and calculating the overall security and performance evaluation score of the quantum key distribution system according to the dynamic weight output by the decision tree model in combination with the score of each level.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to an environmental adaptation and security assessment method and system for a quantum key distribution system in a substation. Background Art

[0002] In the environmental adaptability assessment of the quantum key distribution system in the substation, there are challenges in multi-dimensional data collection and processing. The system needs to synchronously collect quantum communication parameters such as light source intensity, pulse frequency, detection efficiency, and environmental data such as electromagnetic field intensity and temperature. The time synchronization and preprocessing of these heterogeneous data are highly complex, and efficient data fusion algorithms need to be designed. In terms of indicator calculation, the quantitative model of comprehensive indicators such as electromagnetic compatibility, temperature adaptability, and spatial layout efficiency needs to be improved. At the same time, how to dynamically adjust the weights of each evaluation indicator according to real-time environmental factors and build an adaptive decision tree model is a key difficulty. In addition, simulating various typical working conditions of substations in the digital twin environment and generating the authenticity and completeness of virtual test data sets also face challenges. In the security assessment, how to organically combine multi-level indicators such as light source security, detection security, and decoy state protocol compliance to build a scientific and reasonable scoring model requires further research. Finally, how to organically integrate dynamic weights, multi-level scoring, and overall system performance to form a comprehensive and objective quantum key distribution system evaluation system is still a technical problem that needs to be solved urgently. Summary of the invention

[0003] The present invention provides a method for environmental adaptation and security assessment of a substation quantum key distribution system, which mainly includes:

[0004] Obtain basic data such as light intensity, pulse frequency, detection efficiency, dark count rate, etc. of key components of quantum encryption communication systems such as light sources and detectors in substations, and collect electromagnetic field intensity and temperature change data at the same time;

[0005] Perform pre-processing such as filtering, smoothing, and outlier removal on the collected raw data, and synchronize all data to a unified time axis;

[0006] Calculate electromagnetic compatibility index, temperature adaptability index and space layout efficiency index, and form the overall environmental adaptability evaluation of the quantum key distribution system through comprehensive calculation;

[0007] Evaluate single-photon source intensity, single-photon source pulse frequency, quantum state intensity consistency, detection efficiency, dark count rate, quantum bit error rate and count rate according to preset thresholds;

[0008] Construct a decision tree model with nodes including environmental factors such as electromagnetic interference and temperature fluctuations, and dynamically adjust the weight of each evaluation indicator based on real-time environmental data;

[0009] Simulate various typical substation environments in the digital twin environment, generate virtual test data, and experimentally verify various indicators of the quantum key distribution system;

[0010] A multi-level scoring model is used to perform weighted scoring on light source safety, detection safety, decoy state protocol compliance, etc.

[0011] Based on the dynamic weights output by the decision tree model and combined with the scores at each level, the overall security and performance evaluation scores of the quantum key distribution system are calculated.

[0012] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0013] The present invention discloses a method for environmental adaptability and security assessment of a quantum key distribution system for a substation. The method collects optical parameters and environmental data of key components, pre-processes and synchronizes the original data, calculates various indicators and conducts a comprehensive assessment. An innovative decision tree model that includes environmental factors such as electromagnetic interference and temperature fluctuations is constructed, and the assessment weights are dynamically adjusted according to the real-time environment. A variety of typical scenarios are simulated in a digital twin environment for verification, and a multi-level scoring model is used to perform a weighted assessment of the security of various aspects of the system. The present invention organically combines environmental adaptability with security assessment, realizes the dynamic evaluation of the quantum key distribution system in the complex electromagnetic environment of the substation, and provides an important basis for system optimization and actual deployment. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The present invention is a flow chart of a method for environmental adaptation and security assessment of a substation quantum key distribution system.

[0015] Figure 2 It is a schematic diagram of an environmental adaptation and security assessment method for a substation quantum key distribution system of the present invention.

[0016] Figure 3 This is another schematic diagram of the environmental adaptation and security assessment method of a substation quantum key distribution system of the present invention. DETAILED DESCRIPTION

[0017] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] like Figure 1 -3. In this embodiment, a method for environmental adaptation and security assessment of a substation quantum key distribution system may specifically include:

[0019] S101. Obtain basic data such as light intensity, pulse frequency, detection efficiency, dark count rate, etc. of key components of quantum encryption communication systems such as light sources and detectors in substations, and collect electromagnetic field intensity and temperature change data at the same time.

[0020] The performance parameter data of the quantum key distribution system are obtained, and the performance parameters include light intensity, pulse frequency, detection efficiency and dark count rate; the electromagnetic field intensity data and temperature change data in the substation are obtained; the performance parameter data are synchronized with the electromagnetic field intensity data and the temperature change data to form time series data; the time series data are preprocessed, the high-frequency noise in the data is removed by a Butterworth low-pass filter, the missing data is supplemented by a linear interpolation algorithm, and the abnormal data is identified and eliminated by a 3σ criterion; based on the preprocessed time series data, the correlation between the performance parameter and the electromagnetic field intensity and temperature change is calculated by using the Pearson correlation coefficient; if the correlation coefficient exceeds a preset threshold, it is judged that the performance of the quantum key distribution system is significantly affected by electromagnetic interference or temperature change; if the correlation coefficient does not exceed the preset threshold, it is judged that the performance of the quantum key distribution system is relatively stable; according to the correlation analysis result, a multivariate linear regression model is used to establish a performance prediction model of the quantum key distribution system; the measured performance parameter data, the electromagnetic field intensity data, the temperature change data and the performance prediction result are uploaded to a data management platform; the uploaded data is statistically analyzed to generate a performance analysis report of the quantum key distribution system.

[0021] Specifically, an optical power meter is used to measure the light intensity of a single photon source, and the light intensity data is 2μW. A spectrum analyzer is used to measure the pulse frequency of the light source, which is 10MHz. The output voltage of the detector is measured by an oscilloscope, which is 5mV, and the pulse width is 10ns. The detection efficiency of the detector is calculated to be 47% according to the formula η=V / (R·P), where V is the output voltage, R is the load resistance, and P is the incident light power. Under no-light conditions, the output signal of the detector is 1mV, and the corresponding dark count rate is less than 100cps. NF-5035 electromagnetic field intensity sensors and PT100 temperature sensors are arranged in the substation, and data is collected every 1s through the RS485 bus. The performance parameters of the quantum key distribution system are aligned with the electromagnetic field intensity and temperature data according to the timestamp to form time series data. The Butterworth low-pass filter is used to denoise the time series data, the 3σ criterion identifies outliers, and the data interpolation algorithm is used to remove and complete them to obtain the preprocessed time series data. The correlation between the performance parameters of the quantum key distribution system and the electromagnetic field strength and temperature change is calculated based on the Pearson correlation coefficient. When the correlation coefficient exceeds 8, it is judged that the performance of the quantum key distribution system is affected by electromagnetic interference or temperature change. A long short-term memory neural network is used to establish a performance prediction model for the quantum key distribution system. The performance indicators such as the bit error rate and key generation rate of the quantum key distribution system are predicted through the electromagnetic field strength and temperature change data. The measured performance parameters, electromagnetic field strength, temperature change data and performance prediction results are uploaded to the data management platform, and a performance report is generated through Tableau software to intuitively present the performance change trend of the quantum key distribution system and provide a decision-making basis for system optimization and control.

[0022] S102, pre-processing such as filtering, smoothing, and outlier removal is performed on the collected raw data, and all data are synchronized to a unified time axis.

[0023] The collected raw quantum key distribution system data is preprocessed. First, the Butterworth filter is used to filter the data to remove high-frequency noise. Then, the moving average method is used to smooth the data to eliminate random fluctuations. Next, the 3σ principle is used to identify and eliminate outliers to obtain a clean data set. According to the data sampling frequency of different sensors, all data are synchronized to a unified time axis through linear interpolation or downsampling methods to ensure that the data is aligned in the time dimension. Using electromagnetic field data and temperature change data, the least squares method is used to fit the physical model, and the performance data of the light source and detector are corrected and temperature compensated to eliminate the impact of environmental interference on the data. The corrected data is feature extracted, and the moving window method is used to calculate the time series of key indicators such as key generation rate and bit error rate to obtain the feature vector reflecting the performance of the quantum key distribution system. Through hypothesis testing methods such as t-test, it is judged whether the extracted indicators meet the preset performance thresholds and safety requirements. If the indicators exceed the threshold range, potential performance bottlenecks and safety hazards are identified. If the indicators do not meet the requirements, the digital twin simulation model is used to adjust parameters such as light source power and detector threshold voltage to simulate the optimized system performance. At the same time, the optimization strategies related to the current performance bottleneck are retrieved from the expert knowledge base to generate suggestions for improving the system settings. The parameter settings and expert suggestions obtained from the simulation optimization are applied to the quantum key distribution system, and the improvement effect of the system performance is evaluated by real-time monitoring of the data flow. The changing trends of key indicators such as key generation rate and bit error rate are continuously tracked to determine the effectiveness of the optimization measures. Taking into account multiple evaluation indicators such as key generation rate, bit error rate, and key randomness, the weighted average method is used to calculate the comprehensive performance score of the quantum key distribution system. A system security and reliability evaluation report is generated and compared with historical evaluation results to identify the long-term trend of system performance. If the evaluation results do not meet the expected goals, the optimization plan is iteratively adjusted and steps 6-8 are repeated until the system performance meets the security and reliability requirements. The lessons learned during the optimization process are entered into the expert knowledge base to provide a reference for future system upgrades and maintenance.

[0024] Specifically, in the data processing process of the quantum key distribution system, the collected raw data is first preprocessed. The data is filtered using a Butterworth low-pass filter, and the cutoff frequency is set to 1 / 5 of the sampling frequency to remove high-frequency noise. Then, the Savitzky-Golay smoothing algorithm is applied to smooth the data, with a smoothing window size of 11 and a polynomial order of 3. For outliers that exceed the mean ±3 times the standard deviation, the linear interpolation method is used to remove and replace them. Next, according to the difference in data sampling frequency of the sensor, the cubic spline interpolation algorithm is used to synchronize the data to a unified time axis of 100Hz. Using electromagnetic field data and temperature change data, a temperature dependence model of the light source and detector is established, and the least squares method is used to fit the model parameters. The performance data is temperature compensated, and the compensation accuracy is better than 1%. The corrected data is subjected to wavelet transform to extract key indicators such as key generation rate and quantum bit error rate. Using the Student t-test and F-test, at the significance level of 0.5, it is judged whether the indicators meet the preset performance threshold and security requirements. If the indicators do not meet the requirements, the genetic algorithm is used to optimize the working parameters of the light source and detector, such as laser current, APD bias, etc., by combining the digital twin simulation results and the expert knowledge base. The optimized parameter settings are applied to the actual system, and the indicator change trend is monitored in real time. Finally, the hierarchical analysis method is used to determine the evaluation index weights, build a weighted comprehensive scoring model, and calculate the system's safety and reliability scores. If the score does not meet the standard, the parameter settings are iteratively optimized; if the score meets the requirements, the ARIMA model is used to perform trend analysis on historical data, predict future system performance changes, and provide a decision-making basis for system upgrades and maintenance.

[0025] S103. Calculate the electromagnetic compatibility index, temperature adaptability index and space layout efficiency index, and form an overall environmental adaptability evaluation of the quantum key distribution system through comprehensive calculation.

[0026] The electromagnetic environment intensity data inside the substation is obtained, and the electromagnetic environment intensity data is compared with the preset anti-interference capability threshold of the quantum key distribution system to obtain the electromagnetic compatibility index; the key generation rate data and quantum bit error rate data under different temperature conditions are obtained, and the key generation rate data is compared with the key generation rate reference value under the preset standard temperature to obtain the temperature adaptability index; according to the electromagnetic compatibility index and the temperature adaptability index, whether the quantum key distribution system meets the adaptability requirements of the substation environment is judged; if the quantum key distribution system does not meet the adaptability requirements of the substation environment, the distance between the actual layout position of the quantum key distribution device and the electromagnetic interference source is obtained, and the optimal layout distance of the quantum key distribution device is determined by the particle swarm optimization algorithm in combination with the electromagnetic interference intensity data to obtain the spatial layout efficiency index; the hierarchical analysis method is used to calculate the weight of each indicator through a pairwise comparison matrix according to the importance of the electromagnetic compatibility index, the temperature adaptability index and the spatial layout efficiency index, and the weight of each indicator is calculated by adding The overall environmental adaptability score of the quantum key distribution system is obtained by weight calculation; the real-time operation data of the quantum key distribution system is obtained, the real-time operation data is compared with the simulation data in the pre-built digital twin system, and the mean square error is calculated. If the mean square error exceeds a preset threshold, the parameters of the digital twin model are adjusted through an optimization algorithm to achieve adaptive calibration of the digital twin model; according to the calibrated digital twin system, the operation of the quantum key distribution system under different environmental conditions is simulated, the environmental adaptability of the quantum key distribution system is predicted, and optimization suggestions are generated; a support vector machine algorithm is used to establish a prediction model for the environmental adaptability of the quantum key distribution system based on historical operation data and environmental monitoring data, so as to achieve dynamic evaluation of the adaptability of the quantum key distribution system; the overall environmental adaptability evaluation result of the quantum key distribution system is compared with a preset benchmark. If the evaluation result is lower than the preset benchmark, the parameter configuration of the quantum key distribution system is optimized through a genetic algorithm to improve the environmental adaptability of the quantum key distribution system.

[0027] Specifically, by arranging multiple electromagnetic environment intensity sensors inside the substation, electromagnetic environment data is collected in real time, and the collected data is transmitted to the control center of the quantum key distribution system. The threshold comparison algorithm built into the control center will automatically compare the current electromagnetic environment intensity with the system's preset anti-interference capability threshold, and calculate the electromagnetic compatibility index, which is presented in the form of a percentage. For example, the current electromagnetic compatibility index is 95%, indicating that the current electromagnetic environment has little impact on the quantum key distribution system. At the same time, the system will automatically collect key generation rate and quantum bit error rate data under different temperature conditions. For example, the key generation rate is 10kbps and the quantum bit error rate is 3% under a -10℃ environment, while the key generation rate benchmark value under a standard environment of 25℃ is set to 100kbps. By comparing the current data with the benchmark value, the system calculates that the temperature adaptability index is 10%, indicating that the system performance is greatly affected under the current temperature conditions. In addition, the actual distance data is collected through the distance sensor between the quantum key distribution device and the electromagnetic interference source, and combined with the electromagnetic interference intensity data, the particle swarm optimization algorithm is used to calculate the optimal layout distance of the device to be 10 meters, and the spatial layout efficiency index is 80%, indicating that the system is less affected by electromagnetic interference at this distance and the layout is more reasonable. The system comprehensively considers the electromagnetic compatibility index, temperature adaptability index and spatial layout efficiency index to determine whether the adaptability of the current quantum key distribution system reaches the preset threshold. If all three indicators reach more than 80%, the system status is normal, otherwise it will trigger an early warning prompt to notify the management personnel to adjust and optimize. At the same time, the system adopts a weighted average algorithm to comprehensively consider the three indicators to obtain the overall environmental adaptability score. The weight can be set according to the importance of the indicator, such as the electromagnetic compatibility index weight 5, the temperature adaptability index weight 3, and the spatial layout efficiency index weight 2. The overall score is 90 points through weighted calculation, indicating that the system has good adaptability. In addition, the real-time operation data of the quantum key distribution system is compared with the simulation data in the digital twin system, and the digital twin model is calibrated using the deviation analysis algorithm to improve the simulation accuracy. Based on the calibrated model, the adaptability of the system under different environmental conditions is predicted, and optimization suggestions are generated, such as adjusting the equipment layout and optimizing the algorithm parameters. At the same time, the system uses machine learning algorithms such as support vector machines to establish an environmental adaptability prediction model based on massive historical data to achieve real-time dynamic evaluation of system adaptability. When the evaluation result is lower than the preset benchmark value, the adaptive optimization program is automatically started to dynamically adjust the system parameters, such as increasing the quantum signal strength and optimizing the error correction algorithm, so as to continuously improve the environmental adaptability of the quantum key distribution system and ensure the reliable and stable operation of the system.

[0028] S104. Evaluate indicators such as single-photon source light intensity, single-photon source pulse frequency, quantum state light intensity consistency, detection efficiency, dark count rate, quantum bit error rate and count rate according to preset thresholds.

[0029] Obtain light source safety assessment data, which includes light intensity, spectrum, polarization degree and beam quality factor; determine whether the light intensity is greater than 30dB, if so, the light intensity score is 50 points, otherwise, the light intensity score is 0 points; determine whether the spectrum satisfies a single frequency and a line width less than 1nm, if so, the spectrum score is 50 points, otherwise, the spectrum score is 0 points; determine whether the polarization degree is greater than 100:1, if so, the polarization degree score is 50 points, otherwise, the polarization degree score is 0 points; determine whether the beam quality factor is less than 1.1, if so, then The beam quality factor score is 50 points, otherwise, the beam quality factor score is 0 points; the light source safety score is calculated based on the light intensity score, spectrum score, polarization score and beam quality factor score; the detection safety assessment data is obtained, and the detection safety assessment data includes detection efficiency and dark count rate; it is determined whether the detection efficiency is greater than 80%, if so, the detection efficiency score is 50 points, otherwise, the detection efficiency score is 0 points; it is determined whether the dark count rate is less than 100cps, if so, the dark count rate score is 50 points, otherwise, the dark count rate score is 0 points; according to the detection efficiency The invention relates to a method for determining a quantum key distribution system according to a plurality of quantum bits, wherein the quantum key distribution system comprises a plurality of quantum bits, a plurality of quantum bits, and a plurality of quantum bits. The method comprises: obtaining a quantum key distribution system according to a plurality of quantum bits, and ...

[0030] Specifically, firstly, the measured data of various indicators of the quantum key distribution system are obtained according to the preset thresholds, for example, the single photon source intensity threshold is set to 5mW, the single photon source pulse frequency threshold is set to 100MHz, the quantum state light intensity consistency threshold is set to 95%, the detection efficiency threshold is set to 10%, the dark count rate threshold is set to 100cps, the quantum bit error rate threshold is set to 5%, and the count rate threshold is set to 1000cps. Then, the Kalman filter algorithm is used to denoise the measured data to obtain preliminary evaluation data. Then, by calculating the mean and standard deviation of the preliminary evaluation data, the discrete degree of the data is judged. For example, if the data mean is 8 and the standard deviation is 2, which exceeds the discreteness threshold of 20%, the least squares interpolation algorithm is used to correct the data; if the mean is 9 and the standard deviation is 1, which does not exceed the threshold, the preliminary evaluation data is directly used. According to the set light source safety assessment rules, the fuzzy comprehensive evaluation method is used to assign weights of 3, 3, and 4 to the evaluation data of single photon source light intensity, pulse frequency, and quantum state light intensity consistency, respectively, and the light source safety score is calculated to be 85. Similarly, according to the detection security assessment rules, the detection efficiency and dark count rate are assigned weights of 6 and 4, and the detection security score is calculated to be 9. According to the entrapped state protocol compliance assessment rules, the quantum bit error rate and count rate are assigned weights of 7 and 3, and the entrapped state protocol compliance score is calculated to be 8. Finally, the weighted average algorithm is used to set the weight coefficients of the three aspects of light source, detection and protocol to 3, 3 and 4 respectively, and the overall security assessment score is calculated to be 84. Compare this score with the preset security threshold of 8 to determine that the system security meets the standard and the quantum key distribution system can be used normally; if the score is lower than 8, the system security does not meet the standard and needs further optimization and improvement.

[0031] S105. Construct a decision tree model, where nodes include environmental factors such as electromagnetic interference and temperature fluctuation, and dynamically adjust the weight of each evaluation indicator according to real-time environmental data.

[0032] Acquire initial data of electromagnetic compatibility, temperature adaptability and space layout efficiency; according to the initial data, use linear proportional function and inverse proportional function to establish mapping relationship between electromagnetic compatibility, temperature adaptability and space layout efficiency and light source safety, detection safety and decoy state protocol compliance; set initial values ​​of light source safety weight, detection safety weight and decoy state protocol compliance weight, and the value range of the initial values ​​is between 0 and 1; according to the mapping relationship function, adjust the initial weight to obtain adjusted weight; normalize the adjusted weight to obtain normalized weight, and the normalized weight satisfies that the sum of the light source safety weight, detection safety weight and decoy state protocol compliance weight is 1; construct a loss function, and the loss function is as follows: The loss function is defined as the weighted sum of the normalized weight and the preset tolerance; the loss function is minimized using the gradient descent method, and the weight is iteratively updated until the loss function value converges, and the weight at the convergence is used as the new weight; the electromagnetic interference and temperature data of the substation are collected in real time; according to the pre-constructed decision tree model, the electromagnetic interference level and temperature state are judged using the electromagnetic interference and temperature data as input; the weight adjustment coefficient output by the decision tree model is obtained, and the weight adjustment coefficient is multiplied by the new weight to obtain the dynamically adjusted weight; the dynamically adjusted weight is substituted into the preset substation QKD protocol interference consistency evaluation formula to calculate the overall score, and the overall score is used as a quantitative indicator for evaluating the security of the substation QKD system.

[0033] Specifically, in the QKD protocol interference consistency assessment of the substation, the electromagnetic compatibility is first set to 8, the temperature adaptability is 6, and the spatial layout efficiency is 7 as the initial data of the evaluation indicators. The mapping relationship between electromagnetic compatibility and light source security in these three data is defined as a linear proportional function of y=5x+2; the mapping relationship between temperature adaptability and decoy state protocol compliance is also defined as a linear proportional function of y=4x+3; the mapping relationship between spatial layout efficiency and detection security is defined as an inverse proportional function of y=1 / (5x+1). The initial light source security weight is 3, the detection security weight is 4, and the decoy state protocol compliance weight is 3. According to the electromagnetic compatibility, temperature adaptability and spatial layout efficiency data set above, the initial weights are adjusted using their corresponding mapping relationship functions, and the light source security weight is 62, the detection security weight is 41, and the decoy state protocol compliance weight is 54. The adjusted weights are normalized so that the sum of the three is 1, and the light source security weight is 395, the detection security weight is 261, and the decoy state protocol compliance weight is 344. The tolerance values ​​are set to correspond to the light source safety weight of 5, the detection safety weight of 1, and the deception state protocol compliance weight of 5. According to the normalized weights and tolerance values, the loss function L = (395-x1) ^2 / 5 + (261-x2) ^2 / 1 + (344-x3) ^2 / 5 is constructed. The gradient descent method is used to optimize the loss function, the learning rate is 01, and it is iterated 1000 times. The new weights corresponding to the minimum loss function are determined to be 412 for light source safety, 274 for detection safety, and 314 for deception state protocol compliance. Real-time collection of environmental data of the substation, including electromagnetic interference of 80dBμV / m and temperature of 35℃. Combined with the decision tree model, according to the collected environmental data, the electromagnetic interference is classified as a medium level; the temperature fluctuation is judged to be high, corresponding to the (medium, high) leaf node of the decision tree. According to the rule of the node, the light source safety weight is increased by 5%, the decoy state protocol compliance weight is reduced by 5%, and the detection safety weight remains unchanged. The revised weights are 433 for light source safety, 274 for detection safety, and 298 for decoy state protocol compliance. The weight adjustment amount is superimposed on the determined new weights, and the final dynamically adjusted weights are 445 for light source safety, 274 for detection safety, and 281 for decoy state protocol compliance. Finally, the dynamically adjusted weights are substituted into the overall scoring formula S = 445 × light source safety score + 274 × detection safety score + 281 × decoy state protocol compliance score for the substation QKD protocol interference consistency assessment, and the overall score S is calculated to change dynamically over time, providing a more accurate and targeted security assessment for the QKD system of the substation.

[0034] S106. Simulate various typical substation environments in the digital twin environment, generate virtual test data, and experimentally verify various indicators of the quantum key distribution system.

[0035] The actual layout data of the substation is obtained, point cloud data is collected by laser radar scanning, a three-dimensional model of the substation is constructed in the three-dimensional modeling software, and spatial layout data is extracted; a digital twin environment containing all QKD system-related equipment in the substation is constructed using a game engine to reproduce the real scene; environmental parameters are configured in the digital twin environment, and the electromagnetic field simulation module and temperature control model are loaded. The electromagnetic field simulation module uses Ansys HFSS software to simulate the electromagnetic field distribution, and high electromagnetic interference is set as the benchmark scene. The temperature control model simulates the typical temperature fluctuations of the actual operation data of the substation in the digital twin environment by writing scripts; Ansys HFSS is used to perform electromagnetic field simulation at different locations in the digital twin environment, the relationship between the electromagnetic field intensity and the distance between the devices is analyzed, and an electromagnetic compatibility distribution map is generated; different temperature gradient changes are applied in the digital twin environment through the temperature control model, and the data acquisition system is used to determine the changing trends of the key generation rate and bit error rate of the QKD system at different temperatures, and a mathematical model of the relationship between temperature and QKD performance is established using the linear regression method; the optical quantum transmission simulation is run, and the Monte Carlo method is used for random simulation The photon transmission trajectory and detection behavior are used to obtain the detection efficiency and dark count rate in the simulation environment; the entrapped state protocol communication is simulated in the digital twin environment, and the quantum bit error rate and count rate data of the entrapped state protocol execution process are output; the electromagnetic compatibility distribution map in the digital twin environment is synchronized with the key generation rate, error rate data of the QKD system, and the quantum bit error rate and count rate data of the entrapped state protocol communication; the synchronized data are combined with the weighted average method to calculate the scores of various security indicators, and the classification decision tree model is used to judge the electromagnetic compatibility and temperature environment level, and the weight distribution is dynamically adjusted; the overall evaluation score of the QKD system in the current simulation environment is obtained based on the final weight distribution combined with the weighted average method; it is determined whether the overall evaluation score is higher than the threshold. If it is lower than the threshold, the genetic algorithm is triggered to improve the overall evaluation score of the simulation experiment by adjusting the layout parameters or equipment parameters of the digital twin environment to meet the set threshold and generate optimization adjustment suggestions; a correction model for key parameters in the real environment and the virtual environment is established, the digital twin environment parameters are corrected, the accuracy of the virtual scene parameters is adjusted, and the real operating environment is approached; the optical quantum transmission simulation is re-run, and the virtual scene library is continuously updated.

[0036] Specifically, by three-dimensionally modeling the actual layout of the substation, extracting spatial layout data, and constructing a digital twin environment containing all QKD system-related equipment in the substation. Configure environmental parameters in this environment, load the electromagnetic field simulation module and temperature control model. The electromagnetic field simulation module adjusts the electromagnetic interference level in the environment in real time, and sets high electromagnetic interference as the benchmark scenario, such as setting the electromagnetic interference intensity to 10kV / m. The temperature control model simulates typical temperature fluctuations based on the actual operation data of the substation, such as temperature fluctuations between 20℃ and 40℃. The electromagnetic field simulation module performs electromagnetic field simulation at intervals of 1m in the digital twin environment, analyzes the relationship between electromagnetic field intensity and the distance between devices, and generates an electromagnetic compatibility distribution map. The temperature control model applies a temperature gradient change ranging from 5℃ to 10℃ in the simulation environment, determines the changing trend of the key generation rate and bit error rate of the QKD system at different temperatures, and establishes a mathematical model of the relationship between temperature and QKD performance, such as the linear relationship between the bit error rate and the increase in temperature. The digital twin environment runs the optical quantum transmission simulation, and the Monte Carlo method is used to randomly simulate the transmission trajectory and detection behavior of 10,000 photons to obtain the detection efficiency and dark count rate in the simulation environment. The electromagnetic field simulation module simulates the interference of high-frequency electromagnetic pulses, electromagnetic radiation, etc. in the substation. The pulse frequency is set to 1MHz and the radiation intensity is 5mW / cm2. The simulation data is used to judge the light intensity stability and pulse frequency of the system. The detection efficiency, dark count rate, simulated light intensity stability and pulse frequency results generated by the digital twin environment are extracted. Combined with the light source security and detection security assessment results, the decoy state protocol communication process is simulated according to the decoy state BB84 protocol specification, and the quantum bit error rate and count rate of the decoy state protocol execution process are output. The electromagnetic compatibility distribution map is synchronized with the key generation rate, bit error rate data of the QKD system, and the quantum bit error rate and count rate data of the decoy state protocol communication, and the scores of various security indicators are calculated in combination with the weight calculation formula. According to historical data analysis, the initial values ​​of the light source safety weight, detection safety weight, and deception protocol compliance weight are set to 35, 35, and 30, respectively. A decision tree model is constructed to judge the electromagnetic compatibility and temperature environment level based on the index scores obtained by the synchronization data and weight calculation formula. If it is determined to be high electromagnetic interference, the decision tree output increases the electromagnetic compatibility index weight to 45 and reduces the weights of other indicators to 275; if it is determined to be abnormal temperature fluctuation, the decision tree output increases the temperature adaptability weight to 40. Through iterative calculation, the adjusted weights meet the minimum mean square error, determine the final weight distribution, and obtain the overall evaluation score of the QKD system in the current simulation environment based on the final weight distribution combined with the weighted calculation formula. Export the various data and overall evaluation scores generated in the digital twin environment to form a visual report.If the overall evaluation score is lower than the threshold of 85, the particle swarm optimization algorithm is triggered to improve the overall evaluation score of the simulation experiment by adjusting the layout parameters or equipment parameters of the digital twin environment, such as increasing the equipment spacing by 10%. After meeting the set threshold, optimization adjustment suggestions are generated, forming text data of optimization adjustment suggestions and outputting visual reports. The weight allocation strategy and optimization algorithm based on the decision tree model generate data, generate 100 virtual scenes with different parameter combinations, compare the data collected from the real scene, and count the differences in indicators under the influence of different electromagnetic interference levels and temperature fluctuation ranges. The performance difference data and difference of the QKD system in the real environment and the virtual environment are imported into the BP neural network correction model, the digital twin environment parameters are corrected, and the accuracy of the virtual scene parameters is dynamically adjusted to make the virtual environment close to the real operating environment. Re-run the optical quantum transmission simulation, continuously update and optimize the virtual scene library, and provide accurate simulation basis for the optimization of the substation QKD system.

[0037] S107. Use a multi-level scoring model to perform weighted scoring on the light source safety, detection safety, decoy state protocol compliance and other levels.

[0038] Obtaining operation data of the quantum communication system in the substation, the operation data including single-photon source light intensity, single-photon source pulse frequency, quantum state light intensity consistency, detection efficiency, dark count rate, quantum bit error rate and count rate; according to a preset scoring standard, calculating the scores of the single-photon source light intensity, the single-photon source pulse frequency and the quantum state light intensity consistency, and weighting them according to preset weights to obtain a score of the light source safety level, the preset scoring standard includes a single-photon source light intensity scoring standard, a single-photon source pulse frequency scoring standard and a quantum state light intensity consistency scoring standard, the preset weights include the weight of the single-photon source light intensity, the weight of the single-photon source pulse frequency and the weight of the quantum state light intensity consistency; according to the preset scoring standard, calculating the scores of the detection efficiency and the dark count rate, and weighting them according to preset weights to obtain a score of the detection safety level, the preset scoring standard includes a detection efficiency scoring standard and a dark count rate scoring standard, and the preset weights include the weight of the detection efficiency and the weight of the dark count rate; According to the preset scoring criteria, the scores of the quantum bit error rate and the counting rate are calculated, and weighted according to the preset weights to obtain the score of the entrapped state protocol compliance level, wherein the preset scoring criteria include the quantum bit error rate scoring criteria and the counting rate scoring criteria, and the preset weights include the weight of the quantum bit error rate and the weight of the counting rate; the weighted average method is adopted to comprehensively consider the score of the light source safety level, the score of the detection safety level and the score of the entrapped state protocol compliance level, and in combination with the preset weights of each level, the overall security and performance evaluation score of the substation quantum communication system is calculated, wherein the preset weights of each level include the light source safety level weight, the detection safety level weight and the entrapped state protocol compliance level weight; simulation software is used to simulate different operating scenarios in a virtual environment to verify the overall security and performance evaluation scores; according to the results of the verification, the scoring criteria and the weights are adjusted to optimize the multi-level scoring model to improve the accuracy and reliability of the evaluation.

[0039] Specifically, according to the specific needs and safety requirements of the quantum communication system of the substation, the initial weights of the three levels of light source security, detection security and decoy state protocol compliance are set to 35, 35 and 30 respectively. By arranging multiple electromagnetic field intensity sensors and temperature sensors inside the substation, environmental data such as electromagnetic field intensity and temperature change are collected in real time, and the data are processed by statistical analysis methods. Combined with physical model simulation, the electromagnetic compatibility index is calculated to be 85%, the temperature adaptability index is 90% and the spatial layout efficiency index is 95%. Based on the decision tree model, according to the values ​​of the above three indicators, the weights of the light source security, detection security and decoy state protocol compliance levels are dynamically adjusted, and the adjusted weight values ​​are 40, 30 and 30 respectively. At the light source security level, by measuring the single photon source intensity, single photon source pulse frequency and quantum state light intensity consistency and other indicators, and calculating the scores of each indicator according to the scoring criteria, and then weighted according to the weights of 30%, 30% and 40%, the light source security level score is 92 points. At the detection safety level, by measuring indicators such as detection efficiency and dark count rate, and calculating the scores of each indicator according to the scoring criteria, and then weighting them with a weight of 50%, 50%, the score of the detection safety level is 88 points. At the entrapped state protocol compliance level, by measuring indicators such as quantum bit error rate and count rate, and calculating the scores of each indicator according to the scoring criteria, and then weighting them with a weight of 50%, 50%, the score of the entrapped state protocol compliance level is 95 points. Since the electromagnetic compatibility index, temperature adaptability index, and spatial layout efficiency index all reach more than 80%, the recorded data is valid, and the adjusted weight value is used. Through the weighted system, the scores and corresponding weights of the three levels are combined, and the overall safety and performance evaluation score of the substation quantum communication system is calculated to be 98 points. Finally, the digital twin technology is used to simulate different electromagnetic interference, temperature fluctuation and other scenarios in a virtual environment, verify and optimize the evaluation results, and continuously improve the multi-level scoring model through iterative optimization algorithms, so that the evaluation accuracy and reliability are increased to more than 95%.

[0040] S108. Based on the dynamic weights output by the decision tree model and combined with the scores at each level, the overall security and performance evaluation score of the quantum key distribution system is calculated.

[0041] Obtain the light source safety weight, detection safety weight and entrapped state protocol compliance weight output by the decision tree model; use the analytic hierarchy process to calculate the light source safety hierarchical score based on the scores and weights of single-photon source light intensity, single-photon source pulse frequency and quantum state light intensity consistency; use the analytic hierarchy process to calculate the detection safety hierarchical score based on the scores and weights of detection efficiency and dark count rate; use the analytic hierarchy process to calculate the entrapped state protocol compliance hierarchical score based on the scores and weights of quantum bit error rate and count rate; obtain electromagnetic compatibility indicators, temperature adaptability indicators and spatial layout efficiency indicators, and use support vector machines to determine whether all of the indicators have reached preset thresholds; if , then the data is determined to be valid; otherwise, the data is determined to be invalid; if the data is valid, the overall security and performance evaluation score of the quantum key distribution system is calculated by combining the light source security level score, the detection security level score, the entrapped state protocol compliance level score and their weights through the weighted average method; the simulation and experimental verification results of the digital twin environment are obtained, the consistency of virtual data and real data is compared through the Pearson correlation coefficient, and the anti-interference and temperature adaptability design parameters of the equipment are dynamically adjusted; the early warning information of the real-time monitoring system is obtained to determine potential problems; according to the classification results of the digital twin simulation and the decision tree model, personalized optimization suggestions are generated and an optimization report is output.

[0042] Specifically, according to the dynamic weights output by the decision tree model, the light source safety weight is 3, the detection safety weight is 4, and the decoy state protocol compliance weight is 3. A multi-level scoring model is used to calculate the light source safety level score, the detection safety level score, and the decoy state protocol compliance level score. In the light source safety level score, the single photon source intensity is 95, the single photon source pulse frequency is 98, and the quantum state light intensity consistency is 97. According to their weights 3, 4, and 3, the light source safety level score is calculated to be 967. In the detection safety level score, the detection efficiency is 99 and the dark count rate is 96. According to their weights 6 and 4, the detection safety level score is calculated to be 978. In the decoy state protocol compliance level score, the quantum bit error rate is 98 and the count rate is 97. According to their weights 7 and 3, the decoy state protocol compliance level score is calculated to be 977. The system judges that the electromagnetic compatibility index is 85%, the temperature adaptability index is 90%, and the spatial layout efficiency index is 95%, all of which are above 80%, and the recorded data is valid. Through the weighted system, combined with the light source security level score of 967, the detection security level score of 978, the decoy state protocol compliance level score of 977 and their weights of 3, 4, and 3, the overall security and performance evaluation score of the quantum key distribution system was calculated to be 974. According to the simulation and experimental verification results of the digital twin environment, the consistency between virtual data and real data reached 98%, the anti-interference ability of the dynamic adjustment equipment increased by 5%, and the temperature adaptability increased by 3%. Combined with the early warning information of the real-time monitoring system, it was found that the potential problem was the aging of the light source. Through the analysis of the digital twin and decision tree model, it was recommended to replace the light source, thereby generating personalized optimization suggestions and outputting optimization reports.

[0043] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for environmental adaptation and security assessment of a substation quantum key distribution system, characterized in that: The method comprises: Obtain basic data such as light intensity, pulse frequency, detection efficiency, dark count rate, etc. of key components of quantum encryption communication systems such as light sources and detectors in substations, and collect electromagnetic field intensity and temperature change data at the same time; Perform pre-processing such as filtering, smoothing, and outlier removal on the collected raw data, and synchronize all data to a unified time axis; Calculate electromagnetic compatibility index, temperature adaptability index and space layout efficiency index, and form the overall environmental adaptability evaluation of the quantum key distribution system through comprehensive calculation; Evaluate single-photon source intensity, single-photon source pulse frequency, quantum state intensity consistency, detection efficiency, dark count rate, quantum bit error rate and count rate according to preset thresholds; Construct a decision tree model with nodes including environmental factors such as electromagnetic interference and temperature fluctuations, and dynamically adjust the weight of each evaluation indicator based on real-time environmental data; Simulate various typical substation environments in the digital twin environment, generate virtual test data, and experimentally verify various indicators of the quantum key distribution system; A multi-level scoring model is used to perform weighted scoring on light source safety, detection safety, decoy state protocol compliance, etc. Based on the dynamic weights output by the decision tree model and combined with the scores at each level, the overall security and performance evaluation scores of the quantum key distribution system are calculated.

2. The method according to claim 1, characterized in that The acquisition of basic data such as light intensity, pulse frequency, detection efficiency, dark count rate, etc. of key components of quantum encryption communication system such as light source and detector in the substation, and the collection of electromagnetic field intensity and temperature change data, include: Acquiring performance parameter data of a quantum key distribution system, wherein the performance parameters include light intensity, pulse frequency, detection efficiency, and dark count rate; Obtain electromagnetic field strength data and temperature change data in the substation; Time-synchronizing the performance parameter data with the electromagnetic field intensity data and the temperature change data to form time series data; Preprocess the time series data, remove high-frequency noise in the data by using a Butterworth low-pass filter, use a linear interpolation algorithm to fill in missing data, and use the 3σ criterion to identify and eliminate abnormal data; Based on the preprocessed time series data, the correlation between the performance parameter and the electromagnetic field intensity and temperature change is calculated using the Pearson correlation coefficient; If the correlation coefficient exceeds a preset threshold, it is determined that the performance of the quantum key distribution system is significantly affected by electromagnetic interference or temperature change; If the correlation coefficient does not exceed the preset threshold, it is judged that the performance of the quantum key distribution system is relatively stable; According to the correlation analysis results, a multivariate linear regression model is used to establish a quantum key distribution system performance prediction model; Uploading the measured performance parameter data, the electromagnetic field strength data, the temperature change data and the performance prediction results to a data management platform; Perform statistical analysis on the uploaded data and generate a performance analysis report on the quantum key distribution system.

3. The method according to claim 1, characterized in that The collected raw data is pre-processed by filtering, smoothing, removing outliers, etc., and all data are synchronized to a unified time axis, including: Preprocessing the collected raw quantum key distribution system data; First, the data is filtered using a Butterworth filter to remove high-frequency noise; Then, the moving average method is used to smooth the data and eliminate random fluctuations; Next, the 3σ principle is used to identify and remove outliers to obtain a clean data set; According to the data sampling frequency of different sensors, all data are synchronized to a unified time axis through linear interpolation or downsampling methods to ensure data alignment in the time dimension; Using electromagnetic field data and temperature change data, the least square method is used to fit the physical model, and the performance data of the light source and detector are corrected and temperature compensated to eliminate the impact of environmental interference on the data; Extract features from the corrected data, use the moving window method to calculate the time series of key indicators such as key generation rate and bit error rate, and obtain feature vectors that reflect the performance of the quantum key distribution system; Use hypothesis testing methods such as t-test to determine whether the extracted indicators meet the preset performance thresholds and safety requirements; If the indicator exceeds the threshold range, potential performance bottlenecks and safety risks are identified; If the indicators do not meet the requirements, the digital twin simulation model is used to simulate the optimized system performance by adjusting parameters such as light source power and detector threshold voltage; At the same time, optimization strategies related to the current performance bottleneck are retrieved from the expert knowledge base to generate suggestions for improving system settings; Apply the parameter settings and expert advice obtained from simulation optimization to the quantum key distribution system, and evaluate the improvement of system performance by real-time monitoring of data flow; Continue to track the changing trends of key indicators such as key generation rate and bit error rate to determine the effectiveness of optimization measures; Taking into account multiple evaluation indicators such as key generation rate, bit error rate and key randomness, the weighted average method is used to calculate the comprehensive performance score of the quantum key distribution system; Generate system safety and reliability assessment reports and compare them with historical assessment results to identify long-term trends in system performance; If the evaluation results do not meet the expected goals, the optimization plan is iteratively adjusted and steps 6-8 are repeated until the system performance meets the safety and reliability requirements; The lessons learned during the optimization process are entered into the expert knowledge base to provide a reference for future system upgrades and maintenance.

4. The method according to claim 1, characterized in that The calculation of electromagnetic compatibility index, temperature adaptability index and space layout efficiency index forms the overall environmental adaptability evaluation of the quantum key distribution system through comprehensive calculation, including: Acquire electromagnetic environment strength data inside the substation, compare the electromagnetic environment strength data with a preset anti-interference capability threshold of the quantum key distribution system, and obtain an electromagnetic compatibility index; Acquire key generation rate data and quantum bit error rate data under different temperature conditions, compare the key generation rate data with a key generation rate reference value under a preset standard temperature, and obtain a temperature adaptability index; According to the electromagnetic compatibility index and the temperature adaptability index, judging whether the quantum key distribution system meets the adaptability requirements of the substation environment; If the quantum key distribution system does not meet the adaptability requirements of the substation environment, the distance between the actual layout position of the quantum key distribution device and the electromagnetic interference source is obtained, and the optimal layout distance of the quantum key distribution device is determined by a particle swarm optimization algorithm in combination with the electromagnetic interference intensity data to obtain a spatial layout efficiency index; Using the analytic hierarchy process, according to the importance of the electromagnetic compatibility index, the temperature adaptability index and the spatial layout efficiency index, the weight of each index is calculated through a pairwise comparison matrix, and the overall environmental adaptability score of the quantum key distribution system is obtained through weighted calculation; Acquire real-time operation data of the quantum key distribution system, compare the real-time operation data with simulation data in a pre-built digital twin system, calculate the mean square error, and if the mean square error exceeds a preset threshold, adjust the parameters of the digital twin model through an optimization algorithm to achieve adaptive calibration of the digital twin model; According to the calibrated digital twin system, simulate the operation of the quantum key distribution system under different environmental conditions, predict the environmental adaptability of the quantum key distribution system, and generate optimization suggestions; Using a support vector machine algorithm, based on historical operation data and environmental monitoring data, a prediction model for the environmental adaptability of the quantum key distribution system is established to achieve a dynamic evaluation of the adaptability of the quantum key distribution system; The overall environmental adaptability evaluation result of the quantum key distribution system is compared with a preset benchmark. If the evaluation result is lower than the preset benchmark, the parameter configuration of the quantum key distribution system is optimized by a genetic algorithm to improve the environmental adaptability of the quantum key distribution system.

5. The method according to claim 1, characterized in that The evaluation of single photon source intensity, single photon source pulse frequency, quantum state intensity consistency, detection efficiency, dark count rate, quantum bit error rate and count rate according to preset thresholds includes: Acquiring light source safety assessment data, wherein the light source safety assessment data includes light intensity, spectrum, polarization degree and beam quality factor; Determine whether the light intensity is greater than 30 dB, if so, the light intensity score is 50 points, otherwise, the light intensity score is 0 points; Determine whether the spectrum satisfies the single frequency and line width less than 1 nm. If so, the spectrum score is 50 points, otherwise, the spectrum score is 0 points; Determine whether the polarization degree is greater than 100:1, if so, the polarization degree score is 50 points, otherwise, the polarization degree score is 0 points; Determine whether the beam quality factor is less than 1.1, if so, the beam quality factor score is 50 points, otherwise, the beam quality factor score is 0 points; Calculate the light source safety score based on the light intensity score, spectrum score, polarization score and beam quality factor score; Acquiring detection safety assessment data, wherein the detection safety assessment data includes detection efficiency and dark count rate; Determine whether the detection efficiency is greater than 80%, if so, the detection efficiency score is 50 points, otherwise, the detection efficiency score is 0 points; Determine whether the dark count rate is less than 100 cps, if so, the dark count rate score is 50 points, otherwise, the dark count rate score is 0 points; The detection safety score is calculated based on the detection efficiency score and the dark count rate score; Acquiring decoyed state protocol compliance evaluation data, wherein the decoyed state protocol compliance evaluation data includes a quantum bit error rate and a counting rate; Determine whether the quantum bit error rate is less than 5%, if so, the quantum bit error rate score is 50 points, otherwise, the quantum bit error rate score is 0 points; Determine whether the counting rate is greater than 1 kHz, if so, the counting rate score is 50 points, otherwise, the counting rate score is 0 points; Calculate the decoy state protocol compliance score based on the quantum bit error rate score and the count rate score; A weighted average algorithm is used to combine the light source safety score, the detection safety score and the decoy state protocol compliance score according to a preset weight coefficient to obtain an overall safety assessment score, wherein the weight coefficient includes the light source safety weight, the detection safety weight and the decoy state protocol compliance weight; comparing the overall safety assessment score with a preset threshold; If the overall security assessment score is greater than or equal to the preset threshold, it is determined that the security of the quantum key distribution system meets the requirements; If the overall security assessment score is less than the preset threshold, it is determined that the security of the quantum key distribution system does not meet the standards.

6. The method according to claim 1, characterized in that The decision tree model is constructed, and the nodes include environmental factors such as electromagnetic interference and temperature fluctuations. The weight of each evaluation index is dynamically adjusted according to real-time environmental data, including: Obtain initial data on electromagnetic compatibility, temperature adaptability and space layout efficiency; According to the initial data, a mapping relationship between the electromagnetic compatibility, temperature adaptability and spatial layout efficiency and light source safety, detection safety and decoy state protocol compliance is established using a linear proportional function and an inverse proportional function; Setting initial values ​​of the light source safety weight, detection safety weight, and deception state protocol compliance weight, wherein the initial values ​​are all in the range of 0 to 1; According to the mapping relationship function, the initial weight is adjusted to obtain an adjusted weight; Normalizing the adjusted weight to obtain a normalized weight, wherein the normalized weight satisfies that the sum of the light source safety weight, the detection safety weight, and the decoy state protocol compliance weight is 1; Constructing a loss function, wherein the loss function is defined as a weighted square sum of the normalized weight and a preset tolerance; Minimize the loss function using the gradient descent method, iteratively update the weights until the loss function value converges, and use the weights at the convergence as new weights; Real-time collection of electromagnetic interference and temperature data of substations; According to a pre-built decision tree model, the electromagnetic interference level and temperature state are determined by taking the electromagnetic interference and temperature data as input; Obtaining a weight adjustment coefficient output by the decision tree model, and multiplying the weight adjustment coefficient by the new weight to obtain a dynamically adjusted weight; The dynamically adjusted weights are substituted into the preset substation QKD protocol interference consistency evaluation formula to calculate the overall score, which is used as a quantitative indicator for evaluating the security of the substation QKD system.

7. The method according to claim 1, characterized in that The digital twin environment simulates various typical substation environments, generates virtual test data, and experimentally verifies various indicators of the quantum key distribution system, including: Obtain the actual layout data of the substation, use LiDAR scanning to collect point cloud data, build a 3D model of the substation in 3D modeling software, and extract spatial layout data; Use the game engine to build a digital twin environment containing all QKD system-related equipment in the substation to reproduce the real scene; Configure environmental parameters in the digital twin environment, load an electromagnetic field simulation module and a temperature control model, the electromagnetic field simulation module uses Ansys HFSS software to simulate electromagnetic field distribution, sets high electromagnetic interference as a benchmark scenario, and the temperature control model simulates typical temperature fluctuations of actual substation operation data in the digital twin environment by writing scripts; Using Ansys HFSS to perform electromagnetic field simulation at different locations in the digital twin environment, analyzing the relationship between electromagnetic field strength and the distance between devices, and generating an electromagnetic compatibility distribution map; In the digital twin environment, different temperature gradient changes are applied through a temperature control model, a data acquisition system is used to measure the changing trends of the key generation rate and bit error rate of the QKD system at different temperatures, and a mathematical model of the relationship between temperature and QKD performance is established using a linear regression method; Run the photon transmission simulation, use the Monte Carlo method to randomly simulate the photon transmission trajectory and detection behavior, and obtain the detection efficiency and dark count rate in the simulation environment; Simulating the decoyed state protocol communication in the digital twin environment, and outputting the quantum bit error rate and count rate data of the decoyed state protocol execution process; Synchronizing the electromagnetic compatibility distribution map in the digital twin environment with the key generation rate, bit error rate data of the QKD system and the quantum bit error rate and count rate data of the decoy state protocol communication; The synchronized data is combined with the weighted average method to calculate the scores of various safety indicators, and the classification decision tree model is used to judge the electromagnetic compatibility and temperature environment level, and the weight distribution is dynamically adjusted; The overall evaluation score of the QKD system in the current simulation environment is obtained based on the final weight distribution combined with the weighted average method; Determine whether the overall evaluation score is higher than a threshold. If it is lower than the threshold, trigger the genetic algorithm to improve the overall evaluation score of the simulation experiment by adjusting the digital twin environment layout parameters or equipment parameters to meet the set threshold and generate optimization adjustment suggestions; Establish a calibration model for key parameters in the real environment and virtual environment, correct the digital twin environment parameters, adjust the accuracy of virtual scene parameters, and approach the real operating environment; Re-run the photonic quantum transmission simulation and continuously update the virtual scene library.

8. The method according to claim 1, characterized in that The multi-level scoring model is used to perform weighted scoring on the light source safety, detection safety, decoy state protocol compliance and other levels, including: Obtaining operation data of the quantum communication system in the substation, the operation data including single photon source intensity, single photon source pulse frequency, quantum state intensity consistency, detection efficiency, dark count rate, quantum bit error rate and count rate; According to the preset scoring criteria, the scores of the single-photon source light intensity, the single-photon source pulse frequency and the quantum state light intensity consistency are calculated, and weighted according to the preset weights to obtain the score of the light source safety level, wherein the preset scoring criteria include the single-photon source light intensity scoring criteria, the single-photon source pulse frequency scoring criteria and the quantum state light intensity consistency scoring criteria, and the preset weights include the weight of the single-photon source light intensity, the weight of the single-photon source pulse frequency and the weight of the quantum state light intensity consistency; According to a preset scoring standard, the scores of the detection efficiency and the dark count rate are calculated, and weighted according to a preset weight to obtain a score of the detection safety level, wherein the preset scoring standard includes a detection efficiency scoring standard and a dark count rate scoring standard, and the preset weight includes a weight of the detection efficiency and a weight of the dark count rate; According to a preset scoring standard, the scores of the quantum bit error rate and the counting rate are calculated, and weighted according to a preset weight to obtain a score of the compliance level of the entrapped state protocol, wherein the preset scoring standard includes a quantum bit error rate scoring standard and a counting rate scoring standard, and the preset weight includes a weight of the quantum bit error rate and a weight of the counting rate; The overall security and performance evaluation score of the substation quantum communication system is calculated by using a weighted average method, comprehensively considering the score of the light source security level, the score of the detection security level and the score of the decoy state protocol compliance level, and combining the preset weights of each level, wherein the preset weights of each level include the light source security level weight, the detection security level weight and the decoy state protocol compliance level weight; Using simulation software to simulate different operating scenarios in a virtual environment to verify the overall safety and performance evaluation scores; According to the result of the verification, the scoring criteria and the weights are adjusted, the multi-level scoring model is optimized, and the accuracy and reliability of the evaluation are improved.

9. The method according to claim 1, characterized in that: The dynamic weights output by the decision tree model are combined with the scores at each level to calculate the overall security and performance evaluation scores of the quantum key distribution system, including: Obtain the light source safety weight, detection safety weight and decoy state protocol compliance weight output by the decision tree model; According to the scores and weights of single-photon source intensity, single-photon source pulse frequency and quantum state intensity consistency, the hierarchical analysis method is used to calculate the hierarchical score of light source safety; According to the scores of detection efficiency and dark count rate and their weights, the detection safety hierarchical score is calculated by using the analytic hierarchy process; According to the scores and weights of the quantum bit error rate and count rate, the hierarchical analysis method is used to calculate the hierarchical score of the decoy state protocol compliance; Obtaining electromagnetic compatibility indicators, temperature adaptability indicators, and spatial layout efficiency indicators, and using a support vector machine to determine whether the indicators all reach preset thresholds; If so, the data is determined to be valid; Otherwise, the data is determined to be invalid; If the data is valid, the overall security and performance evaluation score of the quantum key distribution system is calculated by combining the light source security level score, the detection security level score and the decoy state protocol compliance level score and their weights through the weighted average method; Obtain simulation and experimental verification results of the digital twin environment, compare the consistency of virtual data with real data through the Pearson correlation coefficient, and dynamically adjust the design parameters of the equipment's anti-interference and temperature adaptability; Get early warning information from real-time monitoring systems to identify potential problems; Based on the classification results of digital twin simulation and decision tree model, personalized optimization suggestions are generated and optimization reports are output.

10. A substation quantum key distribution system environmental adaptation and security assessment system, characterized in that: The system is configured to: Obtain basic data such as light intensity, pulse frequency, detection efficiency, dark count rate, etc. of key components of quantum encryption communication systems such as light sources and detectors in substations, and collect electromagnetic field intensity and temperature change data at the same time; Perform pre-processing such as filtering, smoothing, and outlier removal on the collected raw data, and synchronize all data to a unified time axis; Calculate electromagnetic compatibility index, temperature adaptability index and space layout efficiency index, and form the overall environmental adaptability evaluation of the quantum key distribution system through comprehensive calculation; Evaluate single-photon source intensity, single-photon source pulse frequency, quantum state intensity consistency, detection efficiency, dark count rate, quantum bit error rate and count rate according to preset thresholds; Construct a decision tree model with nodes including environmental factors such as electromagnetic interference and temperature fluctuations, and dynamically adjust the weight of each evaluation indicator based on real-time environmental data; Simulate various typical substation environments in the digital twin environment, generate virtual test data, and experimentally verify various indicators of the quantum key distribution system; A multi-level scoring model is used to perform weighted scoring on light source safety, detection safety, decoy state protocol compliance, etc. Based on the dynamic weights output by the decision tree model and combined with the scores at each level, the overall security and performance evaluation scores of the quantum key distribution system are calculated.

Images