Power grid control safety system and method based on digital twinning

Abstract

The invention relates to the technical field of power grid safety management, in particular to a digital twinning-based power grid control safety system and method.The digital twinning-based power grid control safety system comprises a power grid model unit, an intelligent recognition unit, a strategy making unit and a block chain cooperation unit. The method improves the operation safety and reliability of a power grid, optimizes the resource configuration of the power grid, reduces the energy consumption, provides detailed safety reports and risk assessment for the operation of the power grid, dynamically recognizes potential safety threats and abnormal behaviors, automatically generates a response strategy in real time, improves the overall safety of the system, and improves the safety of the system through the introduction of a block chain technology and the combination with digital twinning. According to the method, transparent information sharing and collaborative management among each level and each region of the power grid are realized, and through decentralized data storage and security guarantee, the power distribution networks in different regions can be ensured to be efficiently collaborative when facing network attacks or faults, and the response efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid security management, and in particular to a power grid control security system and method based on digital twins. Background Art

[0002] A digital twin is a digitized model of a physical entity that reflects its state and behavior in real time. Digital twin technology has seen significant applications in industries such as industry, transportation, and healthcare. In power grid systems, digital twins can provide more accurate simulations and predictions, supporting optimized system management.

[0003] The patent application number is 201510261055.2, and its description states that "the present invention relates to a security protection method and system for a distribution network control system. By judging the data type of the message, when the data type of the message is an application data type, the messages with the distribution network communication protocol number are screened out, and the messages without the distribution network communication protocol number are discarded. The screened messages with the distribution network communication protocol number are further subjected to protocol detection to screen out the messages that meet the distribution network communication protocol, discard the messages that do not meet the distribution network communication protocol, and then forward the messages that meet the communication protocol. The screened messages are safe, ensuring that the distribution terminals and the master station will not receive any messages other than the distribution network communication protocol, avoiding the risk of the entire distribution network control system being attacked by hackers and causing large-scale power outages, thereby ensuring the information security of the distribution network control system." The above technology mainly relies on static rules to judge the legitimacy of messages and cannot dynamically adapt to new attack modes or abnormal behaviors. In addition, when facing large-scale failures or attacks, the collaboration between the various levels may be insufficient, resulting in low response efficiency.

[0004] To sum up, the development of a power grid control safety system and method based on digital twins is still a key issue that needs to be urgently addressed in the field of power grid safety management technology. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem in the prior art that the above-mentioned technology mainly relies on static rules to judge the legitimacy of messages and cannot dynamically adapt to new attack patterns or abnormal behaviors. In addition, when facing large-scale failures or attacks, the collaboration between various levels may be insufficient, resulting in low response efficiency. The present invention provides a power grid control safety system and method based on digital twins.

[0006] To achieve the above object, the present invention provides the following technical solutions: The present invention provides a power grid control safety system based on digital twins, comprising: A power grid model unit, configured to preset a basic digital virtual model, simultaneously obtain power grid operation data in real time, and dynamically update the basic digital virtual model according to the operation data; An intelligent identification unit, configured to analyze the operating data, identify potential safety issues, and generate a safety report based on the potential safety issues; A policy formulation unit, which introduces predefined rules and artificial intelligence algorithms to automatically generate response strategies in real time based on the security reports; The blockchain collaboration unit is used to achieve data collaborative management among various levels and regions of the power grid according to the response strategy.

[0007] Furthermore, the power grid model unit includes: The data acquisition module presets a basic digital virtual model and uses sensors and monitoring equipment to obtain real-time grid operation data, including but not limited to voltage, current, and frequency operating parameters; A digital virtual model dynamically updates the basic digital virtual model based on the grid's operating data to reflect the grid's real-time status, provides a visual interface to display grid operation and performance indicators, and uses the Internet of Things to connect grid devices and transmit data; The intelligent recognition unit includes: Artificial intelligence module, which uses deep learning algorithms to analyze power grid operation data and identify potential safety issues in the data; The processing module generates a safety report based on potential safety issues in the power grid's operating data and notifies relevant personnel in real time to take countermeasures.

[0008] Furthermore, the policy formulation unit includes: Simulation system, simulating the effects of response strategies under different situations, providing feasibility analysis of response strategy implementation, and optimizing response strategies; The decision-making system introduces predefined rules and artificial intelligence algorithms to automatically generate response strategies in real time based on the safety report and feasibility analysis. It also supports manual intervention, allowing operators to adjust strategies based on actual conditions and records all decision-making processes for subsequent auditing and analysis. The blockchain collaboration unit includes: Decentralized module, which uses decentralized data storage and management to achieve real-time synchronization and transparent data sharing between various levels and regions of the power grid when executing the response strategy; The automatic execution module receives the response strategy, automatically executes predefined protocols and rules, monitors abnormal transactions on the blockchain in real time based on the real-time synchronization and data transparent sharing mechanism, and records all data transactions and changes.

[0009] Furthermore, the workflow of the power grid model unit is as follows: The data acquisition module installs sensors and monitoring equipment at key nodes of the power grid to obtain real-time grid operation data. It uses the power flow calculation formula to calculate the power status of the grid to help determine changes in grid load. Through the Internet of Things technology, the real-time grid operation data is transmitted to the central processing system, which stores the real-time grid operation data and performs preliminary preprocessing. At the same time, the load forecasting model predicts future load changes of the grid based on historical data, using the power flow calculation formula: ,in is the active power, is the voltage, is the current, is the phase difference between voltage and current, load forecasting model formula: ,in is the load at the current moment, , , is the weight coefficient of historical load, is a random error; The digital virtual model is used to preset a basic digital virtual model, obtain the operation data of the power grid in real time, and dynamically update the basic digital virtual model according to the operation data to reflect the real-time state changes of the power grid. The power flow of each node in the power grid is calculated according to the power flow equation formula, and the stability of the power grid is monitored, thereby continuously updating the power grid state. The state space model formula is: ,in is the system status, is the state transition matrix, is the control input, is the process noise, and the power flow equation is: ,in is a node The active power, is the node voltage, , is the admittance between nodes.

[0010] Furthermore, the workflow of the intelligent recognition unit is as follows: The AI module uses deep learning formulas to train a neural network model to identify potential safety issues in real-time grid operation data. It uses anomaly detection formulas to standardize real-time grid operation data to identify outliers that deviate from the normal range, thereby establishing a baseline for identifying potential safety issues. Each time a new safety issue is identified, the model parameters are optimized to improve the accuracy of future identifications. The deep learning formula is as follows: ,in is the output, are input features, are model parameters, is the weight matrix, is the bias, Is the activation function, anomaly detection formula: ,in is the normalized value, is a data point, is the mean, is the standard deviation; The processing module automatically generates a detailed security report based on the identified security issues. It uses the fault diagnosis model formula to quantitatively evaluate the faults in the power grid, generate a fault report, quantify the identified security threats and potential risks, and then uses the risk assessment formula to generate a security report that describes the security threats and potential risks. When abnormal behavior or security threats are identified, it triggers an early warning in real time, notifies relevant operators to take countermeasures, provides analysis and suggestions on the identification results, and helps operators make more effective response decisions. The fault diagnosis model formula is: ,in is the fault diagnosis score, is the feature weight, is the fault characteristic data, and the risk assessment formula is: ,in is the risk value, is the probability of the event occurring, The impact of the event.

[0011] Furthermore, the workflow of the strategy formulation unit is as follows: The simulation system builds a simulation environment for multiple response strategies based on different risk scenarios, including but not limited to sudden increases in power load and equipment failures. It simulates the effects of response strategies in different situations and evaluates the effects of different response strategies based on the strategy effect evaluation formula to assess their feasibility and effectiveness. It then uses the dynamic programming formula to simulate the benefit evaluation of different strategies, optimize the decision-making process, and help decision makers choose the best strategy. During the simulation process, the strategy parameters are dynamically adjusted according to real-time data or environmental changes. The strategy effect evaluation formula is: ,in is the strategy effect evaluation percentage, is the system status after implementation, is the system state before implementation, dynamic programming formula: ,in Is in state The maximum profit under is the current decision benefit; The decision-making system generates response strategies in real time based on predefined security rules and artificial intelligence algorithms, allowing operators to manually adjust automatically generated strategies in critical situations. It optimizes the decision-making process in real time through the decision optimization model formula, and then uses the linear programming model formula to optimize strategy generation under multiple constraints to select the best response strategy and ensure that the strategy meets actual operational needs. At the same time, it records all decision-making processes and execution status. The decision optimization model formula is as follows: ,in is the objective function, is the payoff of each decision variable, Is the decision variable, the linear programming model formula: ,in is the objective function, is the profit vector, is the constraint matrix, It's a resource limitation.

[0012] Furthermore, the workflow of the blockchain collaborative unit is as follows: The decentralized module uses decentralized blockchain technology to achieve data storage and management between various levels and regions of the power grid. The consistency and security of blockchain data are ensured through the data consistency formula. At the same time, the consensus algorithm formula is used to calculate the probability of reaching consensus in the blockchain network, improve data consistency, avoid tampering, and transparently share data between various levels and regions, so that data between regions are synchronized in real time, with collaborative management and collaborative operations capabilities. The data consistency formula is: ,in is the block hash value, It is the data in the block. is a random number, and the consensus algorithm formula is: ,in is the probability of accepting the consensus, is the number of nodes that agree, is the total number of nodes; The automatic execution module uses the smart contract activation formula to monitor the triggering conditions of the contract to automatically execute predefined protocols and rules in real time to ensure the effective implementation of various tasks and strategies. When the agreement is automatically executed according to the agreement execution logic formula, the transaction results and data changes on the blockchain are monitored in real time. The agreement execution logic formula: ,in is the total transaction value, is the value of each transaction, Is the execution status of the transaction, the smart contract activation formula: ,in is the number of activated contracts, is the trigger condition for each contract, is the trigger threshold.

[0013] On the other hand, the present invention also provides a power grid control security method based on digital twin, which includes the following steps: Step S1, presetting a basic digital virtual model, acquiring the operation data of the power grid in real time, and dynamically updating the basic digital virtual model according to the operation data; Step S2: analyzing the operating data to obtain potential safety issues, and generating a safety report based on the potential safety issues; Step S3, introducing predefined rules and artificial intelligence algorithms to automatically generate a response strategy in real time based on the security report; Step S4: Implementing collaborative data management among various levels and regions of the power grid according to the response strategy.

[0014] Furthermore, in step S1, the operation data of the power grid is acquired in real time, and a method for establishing a digital twin model of the power grid is as follows: Preset basic digital virtual models and use sensors and monitoring equipment to obtain real-time grid operation data, including but not limited to voltage, current, and frequency operating parameters; Dynamically update the basic digital virtual model based on the operation data of the power grid to reflect the real-time status of the power grid, provide a visual interface to display the operation status and performance indicators of the power grid, and use the Internet of Things to achieve the connection and data transmission of power grid equipment; In step S2, the operating data is analyzed to obtain potential safety issues, and a safety report is generated based on the potential safety issues as follows: Use deep learning algorithms to analyze power grid operation data and identify potential safety issues in the data; Generate security reports based on potential security issues in the power grid's operating data, and notify relevant personnel in real time to take countermeasures.

[0015] Furthermore, in step S3, predefined rules and artificial intelligence algorithms are introduced to automatically generate a response strategy in real time according to the security report: Simulate the effects of response strategies under different circumstances, provide feasibility analysis of response strategy implementation, and optimize response strategies; Predefined rules and artificial intelligence algorithms are introduced to automatically generate response strategies in real time based on the security report and feasibility analysis. Manual intervention is also supported, allowing operators to adjust strategies based on actual conditions. All decision-making processes are recorded to facilitate subsequent audits and analysis. In step S4, according to the response strategy, the method for achieving data collaborative management between various levels and regions of the power grid is as follows: Decentralized data storage and management are used to achieve real-time synchronization and transparent data sharing between all levels and regions of the power grid when executing the response strategy; Receive the response strategy, automatically execute predefined protocols and rules, monitor abnormal transactions on the blockchain in real time based on real-time synchronization and data transparent sharing mechanism, and record all data transactions and changes.

[0016] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects: When used, the present invention is conducive to combining digital twins with artificial intelligence, improving the safety and reliability of power grid operation, optimizing power grid resource allocation, reducing energy consumption, and providing detailed security reports and risk assessments for power grid operation, dynamically identifying potential security threats and abnormal behaviors, and automatically generating response strategies in real time to improve the overall security of the system. By introducing blockchain technology and combining it with digital twins, transparent information sharing and collaborative management between all levels and regions of the power grid can be achieved. Through decentralized data storage and security guarantees, it is ensured that distribution networks in different regions can efficiently collaborate when facing network attacks or failures, thereby improving response efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a system diagram of a power grid control safety system based on digital twins of the present invention; Figure 2 This is a flow chart of a power grid control safety method based on digital twins of the present invention. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0019] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0020] The present invention is described in further detail below with reference to the accompanying drawings: Example 1: like Figure 1 As shown, the present invention provides a power grid control safety system based on digital twins, comprising: a power grid model unit, configured to preset a basic digital virtual model, simultaneously acquire power grid operation data in real time, and dynamically update the basic digital virtual model according to the operation data; Furthermore, the data acquisition module presets a basic digital virtual model and uses sensors and monitoring equipment to obtain real-time operation data of the power grid, including but not limited to voltage, current, and frequency operation parameters; Furthermore, the digital virtual model dynamically updates the basic digital virtual model according to the operation data of the power grid to reflect the real-time status of the power grid, provides a visual interface to display the operation status and performance indicators of the power grid, and uses the Internet of Things to realize the connection and data transmission of power grid equipment; Furthermore, the workflow of the power grid model unit is as follows: The data acquisition module installs sensors and monitoring equipment at key nodes of the power grid to obtain real-time grid operation data. It uses the power flow calculation formula to calculate the power status of the grid to help determine changes in grid load. Through the Internet of Things technology, the real-time grid operation data is transmitted to the central processing system, which stores the real-time grid operation data and performs preliminary preprocessing. At the same time, the load forecasting model predicts future load changes of the grid based on historical data, using the power flow calculation formula: ,in is the active power, is the voltage, is the current, is the phase difference between voltage and current, load forecasting model formula: ,in is the load at the current moment, , , is the weight coefficient of historical load, is a random error; The digital virtual model is used to preset a basic digital virtual model, obtain the operation data of the power grid in real time, and dynamically update the basic digital virtual model according to the operation data to reflect the real-time state changes of the power grid. The power flow of each node in the power grid is calculated according to the power flow equation formula, and the stability of the power grid is monitored, thereby continuously updating the power grid state. The state space model formula is: ,in is the system status, is the state transition matrix, is the control input, is the process noise, and the power flow equation is: ,in is a node The active power, is the node voltage, , is the admittance between nodes.

[0021] Specifically, the data acquisition module installs sensors at key nodes of the power grid to collect real-time operation data of the power grid, obtain power status, monitor load changes, and use Internet of Things technology to transmit data to the central processing system for storage and preliminary preprocessing. The digital virtual model builds a digital twin model based on the real-time data obtained by the data acquisition module, dynamically simulates the operation status of the power grid, and continuously updates the power grid status and monitors its stability, which is conducive to improving operational safety and reliability, optimizing power grid resource allocation, reducing energy consumption, and making it easier for operators to grasp the operation status of the power grid in real time.

[0022] An intelligent identification unit, configured to analyze the operating data, identify potential safety issues, and generate a safety report based on the potential safety issues; Furthermore, the artificial intelligence module uses deep learning algorithms to analyze the power grid's operating data and identify potential safety issues in the power grid's operating data; Furthermore, the processing module generates a safety report based on potential safety issues in the grid’s operational data, and notifies relevant personnel in real time to take countermeasures; Furthermore, the workflow of the intelligent recognition unit is as follows: The AI module uses deep learning formulas to train a neural network model to identify potential safety issues in real-time grid operation data. It uses anomaly detection formulas to standardize real-time grid operation data to identify outliers that deviate from the normal range, thereby establishing a baseline for identifying potential safety issues. Each time a new safety issue is identified, the model parameters are optimized to improve the accuracy of future identifications. The deep learning formula is as follows: ,in is the output, are input features, are model parameters, is the weight matrix, is the bias, Is the activation function, anomaly detection formula: ,in is the normalized value, is a data point, is the mean, is the standard deviation; The processing module automatically generates a detailed security report based on the identified security issues. It uses the fault diagnosis model formula to quantitatively evaluate the faults in the power grid, generate a fault report, quantify the identified security threats and potential risks, and then uses the risk assessment formula to generate a security report that describes the security threats and potential risks. When abnormal behavior or security threats are identified, it triggers an early warning in real time, notifies relevant operators to take countermeasures, provides analysis and suggestions on the identification results, and helps operators make more effective response decisions. The fault diagnosis model formula is: ,in is the fault diagnosis score, is the feature weight, is the fault characteristic data, and the risk assessment formula is: ,in is the risk value, is the probability of the event occurring, The impact of the event.

[0023] Specifically, artificial intelligence modules are used to train neural networks, analyze power grid data, identify potential safety issues, standardize data, and identify outliers that deviate from the normal range. The processing module automatically generates safety reports based on the safety issues identified by the artificial intelligence module, quantitatively assesses power grid failures and generates fault reports, describes security threats and their potential risks, triggers early warnings in real time, notifies relevant operators to take countermeasures, and provides analysis and suggestions on the identification results, which is conducive to improving the safety of power grid operation, providing detailed safety reports and risk assessments, and gradually improving the accuracy of safety issue identification.

[0024] A policy formulation unit, which introduces predefined rules and artificial intelligence algorithms to automatically generate response strategies in real time based on the security reports; Furthermore, the simulation system simulates the effects of response strategies under different situations, provides feasibility analysis of response strategy implementation, and optimizes response strategies; Furthermore, the decision-making system introduces predefined rules and artificial intelligence algorithms to automatically generate response strategies in real time based on the safety report and feasibility analysis. It also supports manual intervention, allowing operators to adjust strategies based on actual conditions, and records all decision-making processes for subsequent audit and analysis. Furthermore, the workflow of the strategy formulation unit is as follows: The simulation system builds a simulation environment for multiple response strategies based on different risk scenarios, including but not limited to sudden increases in power load and equipment failures. It simulates the effects of response strategies in different situations and evaluates the effects of different response strategies based on the strategy effect evaluation formula to assess their feasibility and effectiveness. It then uses the dynamic programming formula to simulate the benefit evaluation of different strategies, optimize the decision-making process, and help decision makers choose the best strategy. During the simulation process, the strategy parameters are dynamically adjusted according to real-time data or environmental changes. The strategy effect evaluation formula is: ,in is the strategy effect evaluation percentage, is the system status after implementation, is the system state before implementation, dynamic programming formula: ,in Is in state The maximum profit under is the current decision benefit; The decision-making system generates response strategies in real time based on predefined security rules and artificial intelligence algorithms, allowing operators to manually adjust automatically generated strategies in critical situations. It optimizes the decision-making process in real time through the decision optimization model formula, and then uses the linear programming model formula to optimize strategy generation under multiple constraints to select the best response strategy and ensure that the strategy meets actual operational needs. At the same time, it records all decision-making processes and execution status. The decision optimization model formula is as follows: ,in is the objective function, is the payoff of each decision variable, Is the decision variable, the linear programming model formula: ,in is the objective function, is the profit vector, is the constraint matrix, It's a resource limitation.

[0025] Specifically, the simulation system constructs a simulation environment for response strategies for different risk scenarios, evaluates the strategy effects and the feasibility and effectiveness of different strategies, until a certain strategy is found to be most effective in restoring power supply. The decision-making system automatically generates response strategies in real time based on this evaluation result and predefined safety rules and artificial intelligence algorithms, and optimizes strategy generation through decision optimization models and linear programming models to ensure that the strategies meet actual needs. At the same time, all decision-making processes are recorded for subsequent audits and analysis, which is conducive to rapid response to power grid changes and security incidents, assists decision makers in selecting the best strategy, improves the scientificity and effectiveness of decision-making, and improves management transparency.

[0026] A blockchain collaboration unit, configured to implement collaborative data management among various levels and regions of the power grid according to the response strategy; Furthermore, the decentralized module adopts decentralized data storage and management to achieve real-time synchronization and transparent data sharing between various levels and regions of the power grid when executing the response strategy; Furthermore, the automatic execution module receives the response strategy, automatically executes predefined protocols and rules, monitors abnormal transactions on the blockchain in real time based on the real-time synchronization and data transparent sharing mechanism, and records all data transactions and changes; Furthermore, the workflow of the blockchain collaborative unit is as follows: The decentralized module uses decentralized blockchain technology to achieve data storage and management between various levels and regions of the power grid. The consistency and security of blockchain data are ensured through the data consistency formula. At the same time, the consensus algorithm formula is used to calculate the probability of reaching consensus in the blockchain network, improve data consistency, avoid tampering, and transparently share data between various levels and regions, so that data between regions are synchronized in real time, with collaborative management and collaborative operations capabilities. The data consistency formula is: ,in is the block hash value, It is the data in the block. is a random number, and the consensus algorithm formula is: ,in is the probability of accepting the consensus, is the number of nodes that agree, is the total number of nodes; The automatic execution module uses the smart contract activation formula to monitor the triggering conditions of the contract to automatically execute predefined protocols and rules in real time to ensure the effective implementation of various tasks and strategies. When the agreement is automatically executed according to the agreement execution logic formula, the transaction results and data changes on the blockchain are monitored in real time. The agreement execution logic formula: ,in is the total transaction value, is the value of each transaction, Is the execution status of the transaction, the smart contract activation formula: ,in is the number of activated contracts, is the trigger condition for each contract, is the trigger threshold.

[0027] Specifically, by deploying a blockchain collaboration unit at a power grid dispatch center, grid data from various regions is synchronized in real time through a decentralized module, ensuring transparent information sharing at all levels. The automated execution module, through smart contracts, automatically executes predefined adjustment protocols when a key indicator exceeds a threshold, adjusting power distribution in a timely manner. The entire process is recorded on the blockchain, ensuring data integrity and traceability, providing a reliable basis for subsequent analysis and decision-making. This facilitates transparent data sharing across all levels and regions, improving collaborative management capabilities. Decentralized storage reduces the risk of data tampering, ensures data consistency, and contributes to improved security and stability, while also reducing manual intervention and increasing efficiency.

[0028] Example 2: like Figure 2 As shown, embodiment 2 provides a power grid control security method based on digital twins, which includes the following steps: Step S1, presetting a basic digital virtual model, acquiring the operation data of the power grid in real time, and dynamically updating the basic digital virtual model according to the operation data; Step S2: analyzing the operating data to obtain potential safety issues, and generating a safety report based on the potential safety issues; Step S3, introducing predefined rules and artificial intelligence algorithms to automatically generate a response strategy in real time based on the security report; Step S4: Implementing collaborative data management among various levels and regions of the power grid according to the response strategy.

[0029] Furthermore, in step S1, the operation data of the power grid is acquired in real time, and a method for establishing a digital twin model of the power grid is as follows: Preset basic digital virtual models and use sensors and monitoring equipment to obtain real-time grid operation data, including but not limited to voltage, current, and frequency operating parameters; Dynamically update the basic digital virtual model based on the operation data of the power grid to reflect the real-time status of the power grid, provide a visual interface to display the operation status and performance indicators of the power grid, and use the Internet of Things to achieve the connection and data transmission of power grid equipment; In step S2, the operating data is analyzed to obtain potential safety issues, and a safety report is generated based on the potential safety issues as follows: Use deep learning algorithms to analyze power grid operation data and identify potential safety issues in the data; Generate security reports based on potential security issues in the power grid's operating data, and notify relevant personnel in real time to take countermeasures.

[0030] Furthermore, in step S3, predefined rules and artificial intelligence algorithms are introduced to automatically generate a response strategy in real time according to the security report: Simulate the effects of response strategies under different circumstances, provide feasibility analysis of response strategy implementation, and optimize response strategies; Predefined rules and artificial intelligence algorithms are introduced to automatically generate response strategies in real time based on the security report and feasibility analysis. Manual intervention is also supported, allowing operators to adjust strategies based on actual conditions. All decision-making processes are recorded to facilitate subsequent audits and analysis. In step S4, according to the response strategy, the method for achieving data collaborative management between various levels and regions of the power grid is as follows: Decentralized data storage and management are used to achieve real-time synchronization and transparent data sharing between all levels and regions of the power grid when executing the response strategy; Receive the response strategy, automatically execute predefined protocols and rules, monitor abnormal transactions on the blockchain in real time based on real-time synchronization and data transparent sharing mechanism, and record all data transactions and changes.

[0031] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A power grid control safety system based on digital twins, characterized by: include: A power grid model unit, configured to preset a basic digital virtual model, simultaneously obtain power grid operation data in real time, and dynamically update the basic digital virtual model according to the operation data; An intelligent identification unit, configured to analyze the operating data, identify potential safety issues, and generate a safety report based on the potential safety issues; A policy formulation unit, which introduces predefined rules and artificial intelligence algorithms to automatically generate response strategies in real time based on the security reports; The blockchain collaboration unit is used to achieve data collaborative management among various levels and regions of the power grid according to the response strategy.

2. A digital twin-based power grid control safety system according to claim 1, characterized in that: The power grid model unit includes: The data acquisition module presets a basic digital virtual model and uses sensors and monitoring equipment to obtain real-time grid operation data, including but not limited to voltage, current, and frequency operating parameters; A digital virtual model dynamically updates the basic digital virtual model based on the grid's operating data to reflect the grid's real-time status, provides a visual interface to display grid operation and performance indicators, and uses the Internet of Things to connect grid devices and transmit data; The intelligent recognition unit includes: Artificial intelligence module, which uses deep learning algorithms to analyze power grid operation data and identify potential safety issues in the data; The processing module generates a safety report based on potential safety issues in the power grid's operating data and notifies relevant personnel in real time to take countermeasures.

3. A digital twin-based power grid control safety system according to claim 2, characterized in that: The Strategy Development Unit includes: Simulation system, simulating the effects of response strategies under different situations, providing feasibility analysis of response strategy implementation, and optimizing response strategies; The decision-making system introduces predefined rules and artificial intelligence algorithms to automatically generate response strategies in real time based on the safety report and feasibility analysis. It also supports manual intervention, allowing operators to adjust strategies based on actual conditions and records all decision-making processes for subsequent auditing and analysis. The blockchain collaboration unit includes: Decentralized module, which uses decentralized data storage and management to achieve real-time synchronization and transparent data sharing between various levels and regions of the power grid when executing the response strategy; The automatic execution module receives the response strategy, automatically executes predefined protocols and rules, monitors abnormal transactions on the blockchain in real time based on the real-time synchronization and data transparent sharing mechanism, and records all data transactions and changes.

4. A digital twin-based power grid control safety system according to claim 3, characterized in that: The workflow of the power grid model unit: The data acquisition module installs sensors and monitoring equipment at key nodes of the power grid to obtain real-time grid operation data. It uses the power flow calculation formula to calculate the power status of the grid to help determine changes in grid load. Through the Internet of Things technology, the real-time grid operation data is transmitted to the central processing system, which stores the real-time grid operation data and performs preliminary preprocessing. At the same time, the load forecasting model predicts future load changes of the grid based on historical data, using the power flow calculation formula: ,in is the active power, is the voltage, is the current, is the phase difference between voltage and current, load forecasting model formula: ,in is the load at the current moment, , , is the weight coefficient of historical load, is a random error; The digital virtual model is used to preset a basic digital virtual model, obtain the operation data of the power grid in real time, and dynamically update the basic digital virtual model according to the operation data to reflect the real-time state changes of the power grid. The power flow of each node in the power grid is calculated according to the power flow equation formula, and the stability of the power grid is monitored, thereby continuously updating the power grid state. The state space model formula is: ,in is the system status, is the state transition matrix, is the control input, is the process noise, and the power flow equation is: ,in is a node The active power, is the node voltage, , is the admittance between nodes.

5. A digital twin-based power grid control safety system according to claim 4, characterized in that: The workflow of the intelligent recognition unit: The AI module uses deep learning formulas to train a neural network model to identify potential safety issues in real-time grid operation data. It uses anomaly detection formulas to standardize real-time grid operation data to identify outliers that deviate from the normal range, thereby establishing a baseline for identifying potential safety issues. Each time a new safety issue is identified, the model parameters are optimized to improve the accuracy of future identifications. The deep learning formula is as follows: ,in is the output, are input features, are model parameters, is the weight matrix, is the bias, Is the activation function, anomaly detection formula: ,in is the normalized value, is a data point, is the mean, is the standard deviation; The processing module automatically generates a detailed security report based on the identified security issues. It uses the fault diagnosis model formula to quantitatively evaluate the faults in the power grid, generate a fault report, quantify the identified security threats and potential risks, and then uses the risk assessment formula to generate a security report that describes the security threats and potential risks. When abnormal behavior or security threats are identified, it triggers an early warning in real time, notifies relevant operators to take countermeasures, provides analysis and suggestions on the identification results, and helps operators make more effective response decisions. The fault diagnosis model formula is: ,in is the fault diagnosis score, is the feature weight, is the fault characteristic data, and the risk assessment formula is: ,in is the risk value, is the probability of the event occurring, The impact of the event.

6. A digital twin-based power grid control safety system according to claim 5, characterized in that: The workflow of the strategy formulation unit: The simulation system builds a simulation environment for multiple response strategies based on different risk scenarios, including but not limited to sudden increases in power load and equipment failures. It simulates the effects of response strategies in different situations and evaluates the effects of different response strategies based on the strategy effect evaluation formula to assess their feasibility and effectiveness. It then uses the dynamic programming formula to simulate the benefit evaluation of different strategies, optimize the decision-making process, and help decision makers choose the best strategy. During the simulation process, the strategy parameters are dynamically adjusted according to real-time data or environmental changes. The strategy effect evaluation formula is: ,in is the strategy effect evaluation percentage, is the system status after implementation, is the system state before implementation, dynamic programming formula: ,in Is in state The maximum profit under is the current decision benefit; The decision-making system generates response strategies in real time based on predefined security rules and artificial intelligence algorithms, allowing operators to manually adjust automatically generated strategies in critical situations. It optimizes the decision-making process in real time through the decision optimization model formula, and then uses the linear programming model formula to optimize strategy generation under multiple constraints to select the best response strategy and ensure that the strategy meets actual operational needs. At the same time, it records all decision-making processes and execution status. The decision optimization model formula is as follows: ,in is the objective function, is the payoff of each decision variable, Is the decision variable, the linear programming model formula: ,in is the objective function, is the profit vector, is the constraint matrix, It's a resource limitation.

7. A digital twin-based power grid control safety system according to claim 6, characterized in that: The workflow of the blockchain collaborative unit: The decentralized module uses decentralized blockchain technology to achieve data storage and management between various levels and regions of the power grid. The consistency and security of blockchain data are ensured through the data consistency formula. At the same time, the consensus algorithm formula is used to calculate the probability of reaching consensus in the blockchain network, improve data consistency, avoid tampering, and transparently share data between various levels and regions, so that data between regions are synchronized in real time, with collaborative management and collaborative operations capabilities. The data consistency formula is: ,in is the block hash value, It is the data in the block. is a random number, and the consensus algorithm formula is: ,in is the probability of accepting the consensus, is the number of nodes that agree, is the total number of nodes; The automatic execution module uses the smart contract activation formula to monitor the triggering conditions of the contract to automatically execute predefined protocols and rules in real time to ensure the effective implementation of various tasks and strategies. When the agreement is automatically executed according to the agreement execution logic formula, the transaction results and data changes on the blockchain are monitored in real time. The agreement execution logic formula: ,in is the total transaction value, is the value of each transaction, Is the execution status of the transaction, the smart contract activation formula: ,in is the number of activated contracts, is the trigger condition for each contract, is the trigger threshold.

8. A digital twin-based power grid control safety method, based on a digital twin-based power grid control safety system according to any one of claims 1 to 7, characterized in that: The following steps are involved: Step S1, presetting a basic digital virtual model, acquiring the operation data of the power grid in real time, and dynamically updating the basic digital virtual model according to the operation data; Step S2: analyzing the operating data to obtain potential safety issues, and generating a safety report based on the potential safety issues; Step S3, introducing predefined rules and artificial intelligence algorithms to automatically generate a response strategy in real time based on the security report; Step S4: Implementing collaborative data management among various levels and regions of the power grid according to the response strategy.

9. A digital twin-based power grid control safety method according to claim 8, characterized in that: In step S1, the operation data of the power grid is acquired in real time, and the method for establishing a digital twin model of the power grid is as follows: Preset basic digital virtual models and use sensors and monitoring equipment to obtain real-time grid operation data, including but not limited to voltage, current, and frequency operating parameters; Dynamically update the basic digital virtual model based on the operation data of the power grid to reflect the real-time status of the power grid, provide a visual interface to display the operation status and performance indicators of the power grid, and use the Internet of Things to achieve the connection and data transmission of power grid equipment; In step S2, the operating data is analyzed to obtain potential safety issues, and a safety report is generated based on the potential safety issues as follows: Use deep learning algorithms to analyze power grid operation data and identify potential safety issues in the data; Generate security reports based on potential security issues in the power grid's operating data, and notify relevant personnel in real time to take countermeasures.

10. A digital twin-based power grid control safety method according to claim 9, characterized in that: In step S3, the method of introducing predefined rules and artificial intelligence algorithms to automatically generate a response strategy in real time based on the security report is as follows: Simulate the effects of response strategies under different circumstances, provide feasibility analysis of response strategy implementation, and optimize response strategies; Predefined rules and artificial intelligence algorithms are introduced to automatically generate response strategies in real time based on the security report and feasibility analysis. Manual intervention is also supported, allowing operators to adjust strategies based on actual conditions. All decision-making processes are recorded to facilitate subsequent audits and analysis. In step S4, according to the response strategy, the method for achieving data collaborative management between various levels and regions of the power grid is as follows: Decentralized data storage and management are used to achieve real-time synchronization and transparent data sharing between all levels and regions of the power grid when executing the response strategy; Receive the response strategy, automatically execute predefined protocols and rules, monitor abnormal transactions on the blockchain in real time based on real-time synchronization and data transparent sharing mechanism, and record all data transactions and changes.

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