Substation safety control method and system based on information management

Abstract

The present invention discloses a substation safety control method and system based on information management, relating to the technical field of substations. S1, forming comprehensive input data of the substation operation state; S2, preprocessing the collected comprehensive input data; S3, constructing a comprehensive feature model of the substation operation state; S4, performing optimization calculation on the comprehensive feature model of the substation operation state based on the bitter fish optimization algorithm, and adaptively optimizing the substation safety control strategy by using the bitter fish optimization algorithm; S5, generating a dynamic substation safety control strategy based on the optimization calculation result of the bitter fish optimization algorithm; S6, sending the dynamic substation safety control strategy to the substation control terminal through a remote control interface, and executing the equipment load optimization scheduling strategy, the fault response strategy and the safety protection strategy. The present invention can adjust the load distribution in advance or perform local isolation to reduce the impact of faults on the overall power grid operation.

Description

Technical Field

[0001] The present invention relates to the technical field of substations, and particularly to a substation safety control method and system based on information management. Background Art

[0002] With the development of smart grid technology, as an important hub of the power system, the safety and stability of substations directly affect the reliable operation of the entire power grid. Traditional substation safety control mainly relies on fixed rules, manual inspections, and preset thresholds. When the actual operating state changes, the existing control schemes often cannot be adjusted in a timely manner, resulting in an increase in potential safety hazards.

[0003] Currently, substation safety control mainly adopts a rule-based automated control system, combined with manual inspections and remote monitoring means to ensure that equipment operates within the normal range. However, the existing methods have the following defects:

[0004] Firstly, the safety control response is not timely and lacks a dynamic adjustment mechanism. Most of the existing substation safety control strategies are based on preset rules or static thresholds. When emergencies occur, the fixed safety strategies cannot quickly adapt, resulting in a lag in system response. In the case of large load fluctuations, the existing load optimization scheduling strategies are difficult to adjust power distribution in real time, easily leading to equipment overload or local load imbalance.

[0005] Secondly, the equipment maintenance mode is backward and it is difficult to predict faults. Currently, the equipment maintenance of substations usually adopts regular inspections or passive fault handling methods, that is, repairing the equipment after a fault occurs, rather than predicting and preventing in advance. This maintenance mode is difficult to adaptively adjust according to the actual operating state of the equipment, which may lead to over-maintenance of the equipment when there is no fault, increasing the operation and maintenance costs; or failing to detect potential hazards in time before potential faults occur, resulting in the spread of system faults and seriously affecting the safe and stable operation of the power grid.

[0006] Thirdly, the safety protection strategy is single and it is difficult to cope with complex external interferences. The existing substation safety protection methods mainly rely on fixed threshold judgments. Substation safety problems are often affected by a variety of external factors comprehensively. The single threshold strategy is difficult to accurately identify the risk level, resulting in over-triggering or insufficient response of safety protection measures.

[0007] In summary, the existing technologies have significant deficiencies in substation safety control, including lagging safety control response, insufficient fault prediction ability, and rigid safety protection strategies, which are difficult to meet the requirements of high efficiency, intelligence, and real-time of modern smart grid for substation safety management. Summary of the Invention

[0008] An object of the present invention is to provide a substation safety control method and system based on information management. The present invention can adjust the load distribution in advance or perform local isolation to reduce the impact of faults on the overall power grid operation.

[0009] A substation safety control method based on information management according to an embodiment of the present invention includes the following steps:

[0010] S1. Construct a substation information management system, collect real-time operation data of substation equipment, substation environmental status data, and external interference factor data, and form comprehensive input data of the substation operation status;

[0011] S2. Perform outlier detection, data denoising, and data normalization processing on the collected comprehensive input data;

[0012] S3. Based on data fusion technology, perform multi-dimensional correlation analysis on the preprocessed comprehensive input data, and construct a comprehensive feature model of the substation operation status;

[0013] S4. Based on the bitter fish optimization algorithm, perform optimization calculation on the comprehensive feature model of the substation operation status, initialize the population of the bitter fish optimization algorithm, use the variables of the comprehensive feature model of the substation operation status as individual parameters in the optimization search space, and use the bitter fish optimization algorithm to adaptively optimize the substation safety control strategy;

[0014] S5. Generate a dynamic substation safety control strategy based on the optimization calculation result of the bitter fish optimization algorithm;

[0015] S6. Send the dynamic substation safety control strategy to the substation control terminal through the remote control interface, execute the equipment load optimization scheduling strategy, fault response strategy, and safety protection strategy, adjust the operation status of the substation equipment, and perform feedback analysis on the execution result. Based on the result of the feedback analysis, update the comprehensive feature model of the substation operation status in real time, and re-execute the bitter fish optimization algorithm to form a new optimization calculation result.

[0016] Optionally, S1 includes the following steps:

[0017] S11. Deploy intelligent sensors and data acquisition terminals at key nodes of substation equipment, environmental monitoring areas, and near external interference sources. The data acquisition terminals are used to collect and transmit operation data of substation equipment, substation environmental status data, and external interference factor data, and transmit the data to the supervisory control and data acquisition system;

[0018] S12. Integrate the Supervisory Control and Data Acquisition (SCADA) system and edge computing devices in the substation informatization management system. The SCADA system is used to receive, store, and perform preliminary processing on the operation data of substation equipment, the environmental status data of the substation, and the data of external interference factors. The edge computing devices are used to perform real-time calculations on the operation data of substation equipment at the data acquisition end.

[0019] S13. Perform data synchronization processing on the collected operation data of substation equipment, the environmental status data of the substation, and the data of external interference factors, and establish a unified time reference.

[0020] S14. Perform data formatting processing on the collected operation data of substation equipment, and convert the data of different sensors into a standard data format.

[0021] S15. Perform integrity verification on the operation data of substation equipment based on the SCADA system and edge computing devices.

[0022] S16. Perform data storage and classification management on the operation data of substation equipment, the environmental status data of the substation, and the data of external interference factors. Store the operation data of substation equipment in the equipment operation database , store the environmental status data of the substation in the environmental database , store the data of external interference factors in the interference database , and establish index associations between the databases to meet the following storage structure:

[0023] ;

[0024] Among them, is the comprehensive database in the substation informatization management system;

[0025] S17. Form the comprehensive input data of the substation operation status from the classified and stored operation data of substation equipment, the environmental status data of the substation, and the data of external interference factors.

[0026] Optionally, the operation data of substation equipment includes voltage data, current data, temperature data, and load data. The environmental status data of the substation includes temperature and humidity data and atmospheric pressure data. The data of external interference factors includes lightning strike probability data, electromagnetic interference data, and illegal intrusion alarm data.

[0027] Optionally, the S3 includes the following steps:

[0028] S31. Uniformly integrate the preprocessed comprehensive input data to form a comprehensive data set , where represents a standardized data set composed of equipment operation data, environmental status data, and interference factor data;

[0029] S32. Perform multi-dimensional correlation analysis on the comprehensive data set and calculate the correlation matrix between each data category:

[0030] ;

[0031] Among them, represents the correlation coefficient between the i-th type of data and the j-th type of data in the comprehensive data set, and is calculated using the following formula:

[0032] ;

[0033] Among them, represents the k-th sample value of the i-th type of data in the comprehensive data set , represents the average value of the i-th type of data, and N represents the total number of samples in the comprehensive data set;

[0034] S33. Based on the analysis results of the correlation matrix construct a comprehensive characteristic model M of the substation operation status:

[0035] ;

[0036] Among them, represents the transposed matrix of the comprehensive input data , M represents the comprehensive characteristic model of the substation operation status, is the weight vector, and each component is determined according to the autocorrelation coefficient of the corresponding data category using the following formula:

[0037] .

[0038] Optionally, the S4 includes the following steps:

[0039] S41. Perform optimization calculation based on the comprehensive characteristic model M of the substation operation status, construct an optimization search space for bitter fish for substation safety control, and set the optimization variable set X:

[0040] ;

[0041] Among them, represents the i-th optimization variable in the substation safety control strategy, n represents the total number of optimization variables, and each optimization variable is restricted by the substation safe operation constraints, satisfying:

[0042] ;

[0043] Among them, and are the safety lower limit and safety upper limit of the substation safety control variable, respectively;

[0044] S42. Initialize the bitter fish population within the optimized search space, set the number of bitter fish individuals , and randomly initialize bitter fish individuals within the optimized variable set X to form the initial population P:

[0045] ;

[0046] Among them, represents the current position of the i-th bitter fish, corresponding to a candidate substation safety control strategy. Initially, the control parameters of each bitter fish individual are randomly distributed within the allowable range, and at the same time, each bitter fish individual is given a dynamic adjustment weight to enhance the ability to adapt to different safe operating environments:

[0047] ;

[0048] Among them, represents the adaptive adjustment weight of the bitter fish individual on the optimization objective . m is the number of optimization objectives, enabling the substation safety control strategy to automatically adjust the optimization focus according to different safety events during operation;

[0049] S43. Define the fitness function F(X) for substation safety control to evaluate the effectiveness of the substation control strategy, comprehensively considering the equipment failure rate , load dispatch balance , energy consumption minimization and safety response time . The fitness function is expressed as follows:

[0050] ;

[0051] Among them, represents the substation equipment failure rate under the action of the optimization strategy X. The smaller the value, the higher the equipment stability. Evaluates the balance of load dispatch, making the power distribution between different load units of the substation reasonable and avoiding equipment damage caused by local overload. is the loss caused by unreasonable energy consumption dispatch during the operation of the substation. The optimization goal is to reduce ineffective energy consumption. is the response time of the substation to sudden safety events. , , , ​To optimize the weight coefficient;

[0052] S44. Adjust the positions of bitter fish individuals based on the cooperative foraging behavior of the bitter fish optimization algorithm, set up an information interaction mechanism, so that individuals consider group information when searching for the optimal control strategy, and make be the optimal individual in the current population. Combine the topological pheromone guidance mechanism to adjust the optimization search strategy of the bitter fish as follows:

[0053] ;

[0054] Among them, is the set of neighboring individuals of bitter fish i, indicating the individuals that exchange information with each other during the search process of the substation safety control strategy, represents the strategy difference degree between bitter fish i and j. The smaller the value, the more similar the control schemes of the two individuals are, is the pheromone guidance factor, is the random perturbation factor;

[0055] S45. Evaluate the fitness of the bitter fish population based on the improved dynamic hierarchical weight selection mechanism, and calculate the fitness values of all individuals , and use the non-dominated sorting method to screen out the individuals with better fitness to enter the next generation. When the convergence condition is met or the maximum number of iterations MaxIter is reached, the optimization process terminates, and the optimal substation safety control strategy parameters are output .

[0056] Optionally, the S5 includes the following steps:

[0057] S51. Based on the substation safety control strategy parameters construct an adaptive dynamic substation safety control strategy , and the safety control strategy includes the equipment load optimization scheduling strategy , the fault response strategy and the safety protection strategy :

[0058] ;

[0059] Perform multi-level intelligent load adjustment according to the comprehensive characteristic model M of the substation operation state, combine historical fault data, fault propagation path analysis and intelligent decision-making model to trigger rapid response, combine multi-modal data fusion and dynamic risk assessment technology to implement safety protection;

[0060] S52. Introduce a topology adaptive load migration mechanism on the basis of traditional balanced load optimization to optimize the load regulation ability of the substation under different operating conditions, and construct a multi-level dynamic load optimization scheduling strategy , and define the load dynamic scheduling objective function:

[0061] ;

[0062] Among them, is the load power of the i-th device in the substation at time t, is the ideal load distribution value of the substation equipment, is the response coefficient of equipment load adjustment. Different equipment has different response capabilities, is the load distribution stability weight. By solving the load dynamic scheduling objective function, the load distribution of different equipment in the substation is dynamically adjusted to achieve load optimization;

[0063] S53. Introduce a fault propagation path prediction model to construct an intelligent fault response strategy , and establish a fault propagation prediction matrix based on a multi-level impact assessment mechanism:

[0064] ;

[0065] Among them, is the historical fault data set, recording the fault distribution under different operating conditions, is the current abnormal state data, is the system state adjustment parameter, , , is the adaptive weight of each index. When exceeds the set threshold , a fault handling decision is triggered, and local isolation, load migration, and equipment protection are performed according to different fault propagation paths;

[0066] S54. Construct a multi-modal fusion security protection strategy , and calculate the security risk index of the substation under external interference :

[0067] ;

[0068] Among them, is the external interference factor data, is the influence factor function, used to describe the impact of different interference factors on the security of the substation, is the weight coefficient, reflecting the priority of different security risks, dynamically adjusted by the fuzzy analytic hierarchy process. When exceeds the set threshold , adjust the protection strategy:

[0069] Enhance equipment redundancy and reduce the risk of single-point failures;

[0070] Trigger the early warning mechanism and notify the operation and maintenance personnel to take intervention measures;

[0071] Adjust the operation mode of the substation to improve safety and stability;

[0072] S55. Update the safety control strategy based on the feedback adaptive mechanism , and store the comprehensive characteristic model M of the substation operation state and the optimized safety control strategy in the information management system.

[0073] A substation safety control system based on information management, used to execute the substation safety control method based on information management, includes the following modules:

[0074] The data acquisition and monitoring module is used to collect the operation data of substation equipment, the environmental state data of the substation, and the data of external interference factors in real time. The data acquisition and monitoring module includes intelligent sensors, data acquisition terminals, and a supervisory control and data acquisition system;

[0075] The data preprocessing and fusion module is used to perform standardization processing, outlier detection, data denoising, and data synchronization on the operation data of substation equipment, the environmental state data of the substation, and the data of external interference factors obtained by the data acquisition and monitoring module, and construct a comprehensive characteristic model of the substation operation state based on data fusion technology;

[0076] The optimization calculation module is used to perform optimization calculations on the comprehensive characteristic model of the substation operation state based on the bitter fish optimization algorithm. The optimization calculation module includes a bitter fish population initialization unit, a fitness evaluation unit, an individual update unit, and an optimization convergence determination unit. The bitter fish population initialization unit is used to randomly initialize bitter fish individuals in the optimization search space and assign each individual a dynamically adjusted weight. The fitness evaluation unit calculates the fitness of bitter fish individuals based on the substation equipment fault prediction model, the load balancing target, and the safety protection requirements. The individual update unit adjusts the positions of bitter fish individuals based on the adaptive optimization strategy to make them tend to the optimal substation safety control strategy. The optimization convergence determination unit is used to detect whether the optimization process meets the convergence conditions and output the optimized substation safety control strategy parameters when the conditions are met;

[0077] A safety control strategy generation module, which is used to generate a dynamic substation safety control strategy according to the optimal substation safety control strategy parameters of the optimization calculation module. The safety control strategy includes an equipment load optimization scheduling strategy, a fault response strategy, and a safety protection strategy. The equipment load optimization scheduling strategy is used to adjust the power grid load distribution when the load fluctuates or the equipment status changes. The fault response strategy is used to trigger a rapid emergency response based on the prediction result of the fault propagation path. The safety protection strategy is used to implement different levels of safety protection measures according to the multi-modal risk assessment result.

[0078] A safety control execution and feedback module, which is used to send the safety control strategy to the substation control terminal and monitor the execution situation of the safety control. The safety control execution and feedback module includes a remote control unit, a strategy execution unit, and a feedback adjustment unit. The remote control unit is used to transmit the optimized safety control strategy to the substation control terminal through a remote interface. The strategy execution unit adjusts the operation state of the substation according to the control instruction. The feedback adjustment unit is used to monitor the execution effect of the safety control strategy and store the execution feedback information in the information management system.

[0079] The beneficial effects of the present invention are as follows:

[0080] (1) The present invention adopts an improved bitter fish optimization algorithm with topology adaptability. By introducing a dynamic topology search mechanism, a pheromone guidance strategy, and an adaptive weight adjustment, the optimization algorithm can dynamically adjust the search path according to the real-time changes of the substation operation state, improving the optimization ability of the substation safety control strategy. Through the topology adaptive search strategy, the bitter fish optimization algorithm can dynamically adjust the search direction under the influence of load fluctuations, fault states, and external interference factors, ensuring that the optimization process is more efficient and stable.

[0081] (2) The present invention combines a fault propagation path prediction mechanism. By constructing a multi-level impact assessment model, it can accurately predict the propagation path of substation faults and take proactive protection measures before the faults occur. Using time series analysis combined with historical fault data, real-time abnormal data, and system adjustment status to construct a fault propagation prediction matrix to achieve intelligent prediction of the fault propagation trend. When it is predicted that the fault may spread to key load equipment, the system can adjust the load distribution in advance or perform local isolation to reduce the impact of the fault on the overall power grid operation.

[0082] (3) Through the multi-modal fusion security protection strategy, the present invention constructs a dynamic security protection mechanism for external interference factors by using game theory optimization and fuzzy analytic hierarchy process. The existing security protection system of substations usually has difficulty in making accurate judgments under complex environmental interferences based on fixed threshold strategies, which easily leads to false alarms or missed alarms of security measures. By fusing environmental monitoring data, equipment operation data, and external threat data, a dynamic security risk assessment model is constructed, and combined with the game theory optimization algorithm, the security protection system can adaptively adjust the protection strategy according to different risk levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, but do not constitute a limitation to the present invention. In the drawings:

[0084] Figure 1 It is a flowchart of a substation security control method and system based on information management proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0085] Now, the present invention will be further described in detail with reference to the drawings. These drawings are all simplified schematic diagrams, only showing the basic structure of the present invention in a schematic manner, so they only show the components related to the present invention.

[0086] Refer to Figure 1 , a substation security control method based on information management, includes the following steps:

[0087] S1. Construct a substation information management system, collect real-time operation data of substation equipment, substation environmental status data, and external interference factor data, and form comprehensive input data of the substation operation status;

[0088] S2. Perform outlier detection, data denoising, and data normalization processing on the collected comprehensive input data;

[0089] S3. Based on data fusion technology, perform multi-dimensional correlation analysis on the preprocessed comprehensive input data, and construct a comprehensive feature model of the substation operation status;

[0090] S4. Based on the bitter fish optimization algorithm, perform optimization calculation on the comprehensive feature model of the substation operation status, initialize the population of the bitter fish optimization algorithm, use the variables of the comprehensive feature model of the substation operation status as individual parameters in the optimization search space, and use the bitter fish optimization algorithm to adaptively optimize the substation security control strategy;

[0091] S5. Generate a dynamic substation security control strategy based on the optimization calculation results of the bitter fish optimization algorithm;

[0092] S6. Send the dynamic substation safety control strategy to the substation control terminal through the remote control interface, execute the equipment load optimization scheduling strategy, fault response strategy and security protection strategy, adjust the operation status of the substation equipment, and conduct feedback analysis on the execution results. Based on the results of the feedback analysis, update the comprehensive characteristic model of the substation operation status in real time, and re-execute the bitter fish optimization algorithm to form new optimization calculation results.

[0093] In this embodiment, S1 includes the following steps:

[0094] S11. Deploy intelligent sensors and data acquisition terminals near the key nodes of substation equipment, environmental monitoring areas and external interference sources. The data acquisition terminals are used to collect and transmit the operation data of substation equipment, the environmental status data of the substation and the data of external interference factors, and transmit the data to the supervisory control and data acquisition system;

[0095] S12. Integrate the supervisory control and data acquisition system and edge computing devices in the substation information management system. The supervisory control and data acquisition system is used to receive, store and preliminarily process the operation data of substation equipment, the environmental status data of the substation and the data of external interference factors. The edge computing device is used to perform real-time calculation on the operation data of substation equipment at the data acquisition end;

[0096] S13. Perform data synchronization processing on the collected operation data of substation equipment, the environmental status data of the substation and the data of external interference factors, and establish a unified time reference;

[0097] S14. Perform data formatting processing on the collected operation data of substation equipment, and convert the data of different sensors into a standard data format;

[0098] S15. Perform integrity verification on the operation data of substation equipment based on the supervisory control and data acquisition system and edge computing devices;

[0099] S16. Perform data storage and classification management on the operation data of substation equipment, the environmental status data of the substation and the data of external interference factors, and store the operation data of substation equipment in the equipment operation database The environmental status data of the substation is stored in the environmental database The data of external interference factors is stored in the interference database The databases are associated by indexes and meet the following storage structure:

[0100] ;

[0101] Among them, is the comprehensive database in the substation information management system;

[0102] S17. Form the comprehensive input data of the substation operation status from the substation equipment operation data, substation environment status data, and external interference factor data stored by classification.

[0103] In this embodiment, the substation equipment operation data includes voltage data, current data, temperature data, and load data. The substation environment status data includes temperature and humidity data and atmospheric pressure data. The external interference factor data includes lightning strike probability data, electromagnetic interference data, and illegal intrusion warning data.

[0104] In this embodiment, S3 includes the following steps:

[0105] S31. Uniformly integrate the preprocessed comprehensive input data to form a comprehensive data set , where represents the standardized data set composed of equipment operation data, environment status data, and interference factor data;

[0106] S32. Perform multi-dimensional correlation analysis on the comprehensive data set to calculate the correlation matrix between each data category:

[0107] ;

[0108] Among them, represents the correlation coefficient between the i-th type of data and the j-th type of data in the comprehensive data set, and is calculated using the following formula:

[0109] ;

[0110] Among them, represents the k-th sample value of the i-th type of data in the comprehensive data set , represents the average value of the i-th type of data, and N represents the total number of samples in the comprehensive data set;

[0111] S33. Construct the comprehensive characteristic model M of the substation operation status based on the analysis results of the correlation matrix :

[0112] ;

[0113] Among them, represents the transposed matrix of the comprehensive input data , M represents the comprehensive characteristic model of the substation operation status, is the weight vector, and each component is determined according to the autocorrelation coefficient of the corresponding data category using the following formula:

[0114] .

[0115] In this embodiment, S4 includes the following steps:

[0116] S41. Based on the comprehensive characteristic model M of the substation operation status, perform optimization calculations, construct an optimization search space for substation safety control, and set the optimization variable set X:

[0117] ;

[0118] Among them, represents the i-th optimization variable in the substation safety control strategy, n represents the total number of optimization variables, and each optimization variable is restricted by the substation safe operation constraints, and satisfies:

[0119] ;

[0120] Among them, and are respectively the safety lower limit and safety upper limit of the substation safety control variable ;

[0121] S42. Initialize the bitter fish population within the optimization search space, set the number of bitter fish individuals , and randomly initialize bitter fish individuals within the optimization variable set X to form the initial population P:

[0122] ;

[0123] Among them, represents the current position of the i-th bitter fish, corresponding to a candidate substation safety control strategy. Initially, the control parameters of each bitter fish individual are randomly distributed within the allowable range, and at the same time, each bitter fish individual is given a dynamic adjustment weight to enhance the ability to adapt to different safe operation environments:

[0124] ;

[0125] Among them, represents the adaptive adjustment weight of the bitter fish individual on the optimization objective , and m is the number of optimization objectives, so that the substation safety control strategy automatically adjusts the optimization focus according to different safety events during operation;

[0126] S43. Define the fitness function F(X) for substation safety control, evaluate the effectiveness of the substation control strategy, and comprehensively consider the equipment failure rate , load dispatch balance , energy consumption minimization and safety response time , the fitness function is expressed as follows:

[0127] ;

[0128] Among them, represents the failure rate of substation equipment under the action of the optimization strategy X. The smaller the value, the higher the equipment stability. Evaluates the balance of load dispatching, makes the power distribution reasonable among different load units of the substation, and avoids equipment damage caused by local overload. is the loss caused by unreasonable energy consumption dispatching during the operation of the substation. The optimization goal is to reduce the ineffective energy consumption. is the response time of the substation to sudden safety events. , , , is the optimization weight coefficient;

[0129] S44. Adjust the positions of bitter fish individuals based on the collaborative foraging behavior of the bitter fish optimization algorithm, set up an information interaction mechanism, so that individuals consider group information when searching for the optimal control strategy, and make be the optimal individual in the current population. Combining with the topological pheromone guidance mechanism, adjust the optimization search strategy of the bitter fish as follows:

[0130] ;

[0131] Among them, is the set of neighboring individuals of bitter fish i, representing the individuals that communicate with each other during the search for the substation safety control strategy. represents the strategy difference degree between bitter fish i and j. The smaller the value, the more similar the control schemes of the two individuals. is the pheromone guidance factor. is the random perturbation factor;

[0132] S45. Evaluate the fitness of the bitter fish population based on the improved dynamic hierarchical weight selection mechanism, and calculate the fitness values of all individuals , and use the non-dominated sorting method to screen out the individuals with better fitness to enter the next generation. When the convergence condition is satisfied or the maximum number of iterations MaxIter is reached, the optimization process terminates, and the optimal substation safety control strategy parameters are output.

[0133] In this embodiment, S5 includes the following steps:

[0134] S51. Based on the substation safety control strategy parameters construct an adaptive dynamic substation safety control strategy , the security control strategy includes the equipment load optimization scheduling strategy , the fault response strategy and the security protection strategy :

[0135] ;

[0136] Based on the multi-level intelligent load adjustment according to the comprehensive characteristic model M of the substation operation status, combined with the historical fault data, fault propagation path analysis and intelligent decision-making model to trigger a quick response, combined with multi-modal data fusion and dynamic risk assessment technology to implement security protection;

[0137] S52. On the basis of traditional balanced load optimization, introduce a topology adaptive load migration mechanism to optimize the load regulation ability of the substation under different operating conditions, and construct a multi-level dynamic load optimization scheduling strategy , and define the load dynamic scheduling objective function:

[0138] ;

[0139] Among them, is the load power of the i-th device of the substation at time t, is the ideal load distribution value of the substation equipment, is the response coefficient of equipment load adjustment, and different equipment has different response capabilities, is the load distribution stability weight. By solving the load dynamic scheduling objective function, the load distribution of different equipment in the substation is dynamically adjusted to achieve load optimization;

[0140] S53. Introduce a fault propagation path prediction model to construct an intelligent fault response strategy , and establish a fault propagation prediction matrix based on a multi-level impact assessment mechanism:

[0141] ;

[0142] Among them, is the historical fault data set, recording the fault distribution under different operating conditions, is the current abnormal state data, is the system state adjustment parameter, , , are the adaptive weights of each index. When exceeds the set threshold , trigger a fault handling decision, and according to different fault propagation paths, perform local isolation, load migration and equipment protection;

[0143] S54. Construct a multi-modal fusion security protection strategy , calculate the security risk index of the substation under external interference :

[0144] ;

[0145] Among them, is the data of external interference factors, is the influence factor function, which is used to describe the influence of different interference factors on the safety of the substation, is the weight coefficient, which reflects the priority of different security risks and is dynamically adjusted by using the fuzzy analytic hierarchy process. When exceeds the set threshold , adjust the protection strategy:

[0146] Enhance the equipment redundancy and reduce the risk of single-point failure;

[0147] Trigger the early warning mechanism and notify the operation and maintenance personnel to take intervention measures;

[0148] Adjust the operation mode of the substation to improve the safety and stability;

[0149] S55. Update the security control strategy based on the feedback adaptive mechanism , store the comprehensive characteristic model M of the substation operation state and the optimized security control strategy in the information management system.

[0150] A substation security control system based on information management is used to execute the substation security control method based on information management, and includes the following modules:

[0151] The data acquisition and monitoring module is used to collect the operation data of substation equipment, the environmental state data of the substation and the data of external interference factors in real time. The data acquisition and monitoring module includes intelligent sensors, data acquisition terminals and a supervisory control and data acquisition system;

[0152] The data preprocessing and fusion module is used to perform standardization processing, outlier detection, data denoising and data synchronization on the operation data of substation equipment, the environmental state data of the substation and the data of external interference factors obtained by the data acquisition and monitoring module, and construct a comprehensive characteristic model of the substation operation state based on data fusion technology;

[0153] Optimization calculation module, which is used to perform optimization calculation on the comprehensive feature model of the substation operation status based on the bitter fish optimization algorithm. The optimization calculation module includes a bitter fish population initialization unit, a fitness evaluation unit, an individual update unit, and an optimization convergence determination unit. The bitter fish population initialization unit is used to randomly initialize bitter fish individuals within the optimization search space and assign a dynamic adjustment weight to each individual. The fitness evaluation unit calculates the fitness of bitter fish individuals based on the substation equipment fault prediction model, the load balancing target, and the safety protection requirements. The individual update unit adjusts the positions of bitter fish individuals based on the adaptive optimization strategy to make them tend to the optimal substation safety control strategy. The optimization convergence determination unit is used to detect whether the optimization process meets the convergence condition and output the optimized substation safety control strategy parameters when the condition is met;

[0154] Safety control strategy generation module, which is used to generate a dynamic substation safety control strategy according to the optimal substation safety control strategy parameters of the optimization calculation module. The safety control strategy includes an equipment load optimization scheduling strategy, a fault response strategy, and a safety protection strategy. The equipment load optimization scheduling strategy is used to adjust the power grid load distribution when the load fluctuates or the equipment status changes. The fault response strategy is used to trigger a rapid emergency response based on the prediction result of the fault propagation path. The safety protection strategy is used to implement different levels of safety protection measures according to the multi-modal risk assessment results;

[0155] Safety control execution and feedback module, which is used to send the safety control strategy to the substation control terminal and monitor the safety control execution situation. The safety control execution and feedback module includes a remote control unit, a strategy execution unit, and a feedback adjustment unit. The remote control unit is used to transmit the optimized safety control strategy to the substation control terminal through a remote interface. The strategy execution unit adjusts the substation operation status according to the control instruction. The feedback adjustment unit is used to monitor the execution effect of the safety control strategy and store the execution feedback information into the information management system.

[0156] Example: At 14:20 on July 18, 2023, a 220kV substation in a coastal area was operating in a high-temperature and high-humidity environment. The temperature in the area reached 37.5°C that day, the air humidity was 68%, and the thunderstorm weather warning was in effect. The substation undertook the power supply tasks for multiple industrial parks and residential areas, and the instantaneous load had approached 230MW. The substation operation was in a high-load state.

[0157] At 14:25, the information management system detected that the load of main transformer 1 had reached 228.6MW, approaching the rated upper limit, and the temperature of the GIS switchgear continued to rise. At the same time, the environmental sensor recorded that the lightning intensity reached 22.7kA, exceeding the historical average level by 18%. Considering that the substation might experience overload or equipment failure caused by lightning strikes, the system entered the safety warning mode.

[0158] At 14:27, the substation SCADA system automatically activates the load scheduling strategy based on the bitter fish optimization algorithm to calculate the current optimal load distribution plan. During the optimization process, the system dynamically adjusts the load distribution between main transformer 1 and main transformer 2 to relieve the operating pressure on main transformer 1.

[0159] The calculation results are as follows:

[0160] Load before optimization (14:26):

[0161] Main transformer 1: 228.6 MW, main transformer 2: 140.2 MW, standby power supply: 42.0 MW;

[0162] Load after optimization (14:28):

[0163] Main transformer 1: 205.0 MW (↓10.3%), main transformer 2: 160.8 MW (↑14.7%), standby power supply: 47.6 MW (↑13.3%);

[0164] At 14:29, the SCADA system successfully executes the load scheduling, the load of main transformer 1 drops to the safe range, and at the same time, the scheduling capacity of the standby power supply is optimized.

[0165] At 14:33, the temperature sensor of the GIS equipment records an accelerated temperature rise rate, from 62.5°C to 67.2°C in the past 5 minutes. The system detects that this trend is abnormal. Through the calculation of the fault propagation path prediction model, if the GIS temperature continues to rise for 5 minutes, it may lead to insulation breakdown and affect the 110 kV busbar.

[0166] The system automatically executes the following preventive measures:

[0167] Forced cooling of GIS equipment: Start the air-cooling system and reduce the load distribution to the switch circuit of the GIS equipment.

[0168] Adjust the load in advance: Reduce the power output of the circuit where the GIS is located, lower the current density, and prevent further temperature rise.

[0169] Trigger remote inspection: The SCADA system automatically notifies the operation and maintenance center, and the dispatching technicians complete the remote inspection within 10 minutes.

[0170] At 14:36, the GIS temperature stabilizes at 65.1°C, does not reach the dangerous threshold, and successfully avoids the expansion of the fault. The traditional system may require at least 15 minutes of manual intervention in this situation, while the method of the present invention completes the early warning and response within 3 minutes, improving the fault response speed.

[0171] At 14:40, the impact of the thunderstorm weather intensified, and the lightning intensity reached 24.2 kA. The SCADA system received an alarm from the environmental monitoring sensors. Through the multi-modal fusion security protection strategy, the system evaluated the external environmental risks and implemented the following preventive measures:

[0172] Adjust the arrester status: Improve the grounding resistance adjustment ability and optimize the current discharge to the standby grounding device.

[0173] Dynamically adjust the transformer operation mode: Reduce the impact load on the high-voltage side and avoid secondary overvoltage caused by current overshoot.

[0174] Intelligent load transfer: Reduce the load supply in high lightning risk areas and transfer part of the load to lines far from the thunderstorm impact.

[0175] At 14:45, the system successfully adjusted the transformer grounding mode, reduced the voltage fluctuation caused by lightning strikes, and all key equipment remained in normal operation without tripping or equipment damage.

[0176] The experimental comparison data are as follows:

[0177]

[0178] The method of the present invention significantly improves the load dispatching efficiency, reduces the risk of equipment overload, and enhances the safety protection ability in thunderstorm weather in a high-load operation environment. Through intelligent optimization, the load adjustment response time is shortened by 80%, the fault response time is shortened by 65.2%, avoiding economic losses of more than 850,000 yuan, and providing a more reliable safety control scheme for the substation.

[0179] The present invention adopts a topologically adaptive bitter fish optimization algorithm. By introducing a dynamic topology search mechanism, a pheromone guidance strategy, and an adaptive weight adjustment, the optimization algorithm can dynamically adjust the search path according to the real-time changes in the operation state of the substation, improving the optimization ability of the substation safety control strategy. Through the topologically adaptive search strategy, the bitter fish optimization algorithm can dynamically adjust the search direction under the influence of load fluctuations, fault states, and external interference factors, ensuring that the optimization process is more efficient and stable.

[0180] The present invention combines a fault propagation path prediction mechanism. By constructing a multi-level impact assessment model, it can accurately predict the propagation path of substation faults and take proactive protection measures before the faults occur. Using time series analysis combined with historical fault data, real-time abnormal data, and system adjustment status to construct a fault propagation prediction matrix to achieve intelligent prediction of the fault propagation trend. When it is predicted that the fault may spread to key load equipment, the system can adjust the load distribution in advance or perform local isolation to reduce the impact of the fault on the overall power grid operation.

[0181] Through a multi-modal fusion security protection strategy, this invention constructs a dynamic security protection mechanism for external interference factors by using game theory optimization and fuzzy analytic hierarchy process. The existing security protection system of substations usually has difficulty in making accurate judgments under complex environmental interferences based on fixed threshold strategies, which easily leads to false alarms or missed alarms of security measures. By fusing environmental monitoring data, equipment operation data, and external threat data to construct a dynamic security risk assessment model and combining it with a game theory optimization algorithm, the security protection system can adaptively adjust the protection strategy according to different risk levels.

[0182] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes should be covered within the protection scope of the present invention.

Claims

1. A substation safety control method based on information management, characterized in that: The steps include: S1. Build a substation information management system to collect substation equipment operation data, substation environmental status data and external interference factor data in real time, and form comprehensive input data of substation operation status; S2, performing outlier detection, data denoising, and data normalization on the collected comprehensive input data; S3, based on data fusion technology, multi-dimensional correlation analysis is performed on the pre-processed comprehensive input data to build a comprehensive characteristic model of substation operation status; S4, optimizing and calculating the comprehensive characteristic model of the substation operation status based on the bitter fish optimization algorithm, initializing the bitter fish optimization algorithm population, taking the variables of the comprehensive characteristic model of the substation operation status as the individual parameters in the optimization search space, and using the bitter fish optimization algorithm to adaptively optimize the substation safety control strategy; S5. Generate a dynamic substation safety control strategy based on the optimization calculation results of the bitter fish optimization algorithm; S6. Send dynamic substation safety control strategies to substation control terminals through remote control interfaces, execute equipment load optimization scheduling strategies, fault response strategies and safety protection strategies, adjust the operating status of substation equipment, and conduct feedback analysis on the execution results. Based on the results of the feedback analysis, the comprehensive characteristic model of the substation operating status is updated in real time, and the bitter fish optimization algorithm is re-executed to form new optimization calculation results. The S4 comprises the following steps: S41. Perform optimization calculation based on the comprehensive characteristic model M of the substation operation status, construct a bitter fish optimization search space for substation safety control, and set the optimization variable set X: X={x1,x2,...,x n }; Where n represents the total number of optimization variables; x i represents the i-th optimization variable in the substation safety control strategy. Each optimization variable x i The value range of is limited by the safe operation constraints of the substation and meets the following requirements: x i,min ≤x i ≤x i,max ; Among them, x i,min and x i,max They are substation safety control variables x i The lower and upper safety limits; S42, initialize the bitter fish population in the optimization search space, and set the number of bitter fish individuals N f , randomly initialize N in the optimization variable set X f Bitter fish individuals constitute the initial population P: P={X1,X2,...,X Nf }; Among them, X i represents the current position of the i-th bitter fish, corresponding to a candidate substation safety control strategy. Initially, the control parameters of each bitter fish individual are randomly distributed within the allowable range, and each bitter fish individual is given a dynamic adjustment weight W i , used to enhance the ability to adapt to different security operating environments: IN i ={in i1 ,In i2 ,...,In im }; Among them, w ik Represents the bitter fish individual X i In the optimization objective f k (X) is the adaptive adjustment weight, m ​​is the number of optimization targets, so that the substation safety control strategy can automatically adjust the optimization focus according to different safety events during operation; S43. Define the fitness function F(X) for substation safety control, evaluate the effectiveness of substation control strategy, and comprehensively consider the equipment failure rate R fault (X), load dispatch balance P balance (X), energy consumption minimization E loss (X) and safety response time T response (X), the fitness function is expressed as follows: F(X)=w1R fault (X)+w2P balance (X)+w3E loss (X)+w4T response (X); Among them, R fault (X) represents the failure rate of substation equipment under the optimization strategy X. The smaller the value, the higher the equipment stability. balance (X) Evaluate the balance of load scheduling to make the power distribution between different load units of the substation reasonable and avoid equipment damage caused by local overload. loss (X) is the loss caused by unreasonable energy consumption scheduling during the operation of the substation. The optimization goal is to reduce the ineffective energy consumption, T response (X) is the response time of the substation to sudden safety events, w1, w2, w3, w4 are optimization weight coefficients; S44, based on the collaborative foraging behavior of bitter fish optimization algorithm, adjust the position of individual bitter fish, set up the information interaction mechanism, so that individuals consider group information when searching for the optimal control strategy, let X best For the best individual in the current population, combined with the topological pheromone guidance mechanism, the optimization search strategy of bitter fish is adjusted as follows: Among them, Ω(i) is the neighborhood individual set of bitter fish i, which represents the individuals who exchange information with each other during the search process of substation safety control strategy, d ij represents the difference in strategies between bitter fish i and j. The smaller the value, the more similar the control schemes of the two individuals are. α is the pheromone guidance factor, and β is the random disturbance factor. S45, based on the improved dynamic hierarchical weight selection mechanism, the fitness of the bitter fish population is evaluated and the fitness value F(X i ), the non-dominated sorting method is used to select individuals with better fitness to enter the next generation. When the convergence condition is met Or when the maximum number of iterations MaxIter is reached, the optimization process is terminated and the optimal substation safety control strategy parameter X is output. opt ; The S5 comprises the following steps: S51, based on substation safety control strategy parameters X opt Constructing an adaptive dynamic substation safety control strategy S control The safety control strategy includes the equipment load optimization scheduling strategy S load , Fault response strategy S fault and security protection strategy S security : S control ={S load ,S fault ,S security }; S load Multi-level intelligent load adjustment is performed based on the comprehensive characteristic model M of the substation operation status, S fault Combined with historical fault data, fault propagation path analysis and intelligent decision-making models to trigger rapid response, S security Implement security protection by combining multimodal data fusion and dynamic risk assessment technology; S52. Based on the traditional balanced load optimization, a topology adaptive load migration mechanism is introduced to optimize the load regulation capability of the substation under different operating conditions and build a multi-level dynamic load optimization dispatching strategy. load , and define the load dynamic scheduling objective function: in, is the load power of the ith device in the substation at time t, P ideal is the ideal load distribution value of the substation equipment, α i is the response coefficient of equipment load adjustment. Different equipment has different response capabilities. i Assign stability weights to the loads, dynamically adjust the load distribution of different equipment in the substation by solving the load dynamic scheduling objective function, and achieve load optimization; S53. Introduce fault propagation path prediction model to build intelligent fault response strategy S fault , a fault propagation prediction matrix is ​​established based on a multi-level impact assessment mechanism: R f =W p ·F history +W c ·F current +W s ·S state ; Among them, F history is a historical fault dataset, recording the fault distribution under different operating conditions. current is the current abnormal state data, S state is the system state adjustment parameter, W p ,W c ,W s is the adaptive weight of each indicator. f Exceeding the set threshold R th Fault handling decisions are triggered in real time, and local isolation, load migration and equipment protection are performed according to different fault propagation paths; S54. Constructing a multi-modal fusion security protection strategy security , calculate the safety risk index E of the substation under external interference risk : in, is the external interference factor data, g k (·) is the impact factor function, which is used to describe the impact of different interference factors on substation safety, λ k is the weight coefficient, reflecting the priority of different security risks, and is dynamically adjusted using the fuzzy hierarchical analysis method. Exceeding the set threshold E th When the protection strategy is adjusted: Enhance equipment redundancy and reduce the risk of single point failure; Trigger the early warning mechanism and notify the operation and maintenance personnel to take intervention measures; Adjust substation operation mode to improve safety and stability; S55. Update the security control strategy S based on feedback adaptive mechanism control , the substation operation status comprehensive characteristic model M and the optimized safety control strategy are stored in the information management system.

2. A substation safety control method based on information management according to claim 1, characterized in that: The S1 comprises the following steps: S11. Deploy smart sensors and data acquisition terminals near key equipment nodes, environmental monitoring areas and external interference sources in the substation. The data acquisition terminals are used to collect and transmit substation equipment operation data, substation environmental status data and external interference factor data, and transmit the data to the monitoring and data acquisition system; S12. Integrate a monitoring and data acquisition system and an edge computing device in the substation information management system. The monitoring and data acquisition system is used to receive, store and preliminarily process substation equipment operation data, substation environmental status data and external interference factor data. The edge computing device is used to perform real-time calculation of substation equipment operation data at the data acquisition end. S13, performing data synchronization processing on the collected substation equipment operation data, substation environmental status data and external interference factor data, and establishing a unified time reference; S14, formatting the collected substation equipment operation data, and converting the data from different sensors into a standard data format; S15. Perform integrity check on substation equipment operation data based on the monitoring and data acquisition system and edge computing equipment; S16. Data storage and classification management of substation equipment operation data, substation environmental status data and external interference factor data, and storage of substation equipment operation data in the equipment operation database DB eq , the substation environmental status data is stored in the environmental database DB env , the external interference factor data is stored in the interference database DB int , the databases are associated with each other using indexes to satisfy the following storage structure: DB total ={DB eq ,DB env ,DB int }; Among them, DB total It is a comprehensive database in the substation information management system; S17, forming comprehensive input data of the substation operation status by classifying and storing the substation equipment operation data, substation environment status data and external interference factor data.

3. A substation safety control method based on information management according to claim 1, characterized in that: The substation equipment operation data includes voltage data, current data, temperature data, and load data; the substation environmental status data includes temperature and humidity data and atmospheric pressure data; and the external interference factor data includes lightning strike probability data, electromagnetic interference data, and illegal intrusion alarm data.

4. A substation safety control method based on information management according to claim 1, characterized in that: The S3 comprises the following steps: S31. Unify and integrate the pre-processed comprehensive input data to form a comprehensive data set D total , where D total Represents a standardized data set consisting of equipment operation data, environmental status data, and interference factor data; S32. For the comprehensive data set D total Perform multidimensional association analysis and calculate the correlation matrix between each data category: in, It represents the correlation coefficient between the i-th type of data and the j-th type of data in the comprehensive data set. n×n is the row and column of the matrix and is calculated using the following formula: Among them, d i,k Denotes the comprehensive dataset D total The kth sample value of the i-th category data in , represents the average value of the i-th category data, and N represents the total number of samples in the comprehensive data set; S33, based on the correlation matrix R (3) The comprehensive characteristic model M of substation operation status is constructed based on the analysis results: in, Represents the comprehensive input data D total The transposed matrix of the substation, M represents the comprehensive characteristic model of substation operation status, W = [w1,w2,…,w n ] is the weight vector, each component w i According to the autocorrelation coefficient of the corresponding data category Determine as follows:

5. A substation safety control system based on information management, used to execute the substation safety control method based on information management according to any one of claims 1 to 4, characterized in that: Includes the following modules: A data acquisition and monitoring module is used to collect substation equipment operation data, substation environmental status data and external interference factor data in real time. The data acquisition and monitoring module includes intelligent sensors, data acquisition terminals and monitoring and data acquisition systems; The data preprocessing and fusion module is used to perform standardization, outlier detection, data denoising and data synchronization on the substation equipment operation data, substation environmental status data and external interference factor data obtained by the data acquisition and monitoring module, and to build a comprehensive characteristic model of the substation operation status based on data fusion technology; An optimization calculation module is used to optimize and calculate the comprehensive characteristic model of the substation operation status based on the bitter fish optimization algorithm. The optimization calculation module includes a bitter fish population initialization unit, a fitness evaluation unit, an individual update unit and an optimization convergence determination unit. The bitter fish population initialization unit is used to randomly initialize bitter fish individuals in the optimization search space and give each individual a dynamic adjustment weight. The fitness evaluation unit calculates the fitness of bitter fish individuals based on the substation equipment fault prediction model, load balancing objectives and safety protection requirements. The individual update unit adjusts the position of the bitter fish individuals based on an adaptive optimization strategy to make it tend to the optimal substation safety control strategy. The optimization convergence determination unit is used to detect whether the optimization process meets the convergence conditions, and output the optimized substation safety control strategy parameters when the conditions are met; A safety control strategy generation module is used to generate a dynamic substation safety control strategy according to the optimal substation safety control strategy parameters of the optimization calculation module. The safety control strategy includes an equipment load optimization scheduling strategy, a fault response strategy and a safety protection strategy. The equipment load optimization scheduling strategy is used to adjust the power grid load distribution when the load fluctuates or the equipment status changes. The fault response strategy is used to trigger a rapid emergency response based on the prediction result of the fault propagation path. The safety protection strategy is used to implement different levels of safety protection measures according to the multimodal risk assessment results. The safety control execution and feedback module is used to send the safety control strategy to the substation control terminal and monitor the safety control execution status. The safety control execution and feedback module includes a remote control unit, a strategy execution unit and a feedback adjustment unit. The remote control unit is used to transmit the optimized safety control strategy to the substation control terminal through a remote interface. The strategy execution unit adjusts the substation operation status according to the control instructions. The feedback adjustment unit is used to monitor the execution effect of the safety control strategy and store the execution feedback information in the information management system.

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