Substation safety control method and system based on informatization management

Abstract

The invention discloses a transformer substation safety control method and system based on informatization management, and relates to the technical field of transformer substations. S1, comprehensive input data of the operation state of a transformer substation is formed; s2, preprocessing the collected comprehensive input data; s3, constructing a comprehensive characteristic model of the operation state of the transformer substation; s4, performing optimization calculation on the comprehensive characteristic model of the operation state of the transformer substation based on a bitter fish optimization algorithm, and performing adaptive optimization on a safety control strategy of the transformer substation by adopting the bitter fish optimization algorithm; s5, generating a dynamic substation safety control strategy based on an optimization calculation result of the bitter fish optimization algorithm; and S6, issuing a dynamic substation safety control strategy to the substation control terminal through the remote control interface, and executing an equipment load optimization scheduling strategy, a fault response strategy and a safety protection strategy. According to the invention, load distribution can be adjusted in advance or local isolation can be carried out to reduce the influence of faults on the operation of the whole power grid.

Description

Technical Field

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

[0002] With the development of smart grid technology, substations, as important hubs of the power system, have a direct impact on the reliable operation of the entire power grid due to their safety and stability. Traditional substation safety control mainly relies on fixed rules, manual inspections and preset thresholds. When the actual operating status changes, the existing control schemes often cannot be adjusted in time, resulting in increased safety hazards.

[0003] At present, substation safety control mainly adopts rule-based automatic control system, combined with manual inspection and remote monitoring to ensure that the equipment works within the normal operating range. However, the existing methods have the following defects: First, the safety control response is not timely and there is a lack of 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 adapt quickly, resulting in a delayed system response. In the case of large load fluctuations, the existing load optimization scheduling strategy is difficult to adjust power distribution in real time, which can easily lead to equipment overload or local load imbalance.

[0004] Secondly, the equipment maintenance model is backward and it is difficult to predict failures. The current equipment maintenance of substations usually adopts regular inspections or passive fault handling methods, that is, repairing the equipment after a failure occurs, rather than predicting and preventing it in advance. This maintenance model is difficult to adaptively adjust according to the actual operating status of the equipment, which may lead to excessive maintenance of the equipment when no failure occurs, increasing operation and maintenance costs; or failing to discover hidden dangers in time before potential failures occur, causing system failures to spread, seriously affecting the safe and stable operation of the power grid.

[0005] Thirdly, the security protection strategy is single and difficult to cope with complex external interference. The existing substation security protection methods mainly rely on fixed threshold judgments. Substation safety issues are often affected by a combination of multiple external factors. A single threshold strategy is difficult to accurately identify the risk level, resulting in excessive triggering or insufficient response of security protection measures.

[0006] In summary, the existing technologies have significant deficiencies in substation safety control, including delayed safety control response, insufficient fault prediction capabilities, and rigid safety protection strategies. They are unable to meet the requirements of modern smart grids for high efficiency, intelligence, and real-time safety management of substations. Summary of the invention

[0007] One object of the present invention is to provide a substation safety control method and system based on information management, which can adjust load distribution or perform local isolation in advance to reduce the impact of faults on the overall power grid operation.

[0008] A substation safety control method based on information management according to an embodiment of the present invention includes the following steps: 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.

[0009] Optionally, the S1 includes 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 , the substation environmental status data is stored in the environmental database , the external interference factor data is stored in the interference database , the databases are associated with each other using indexes to satisfy the following storage structure: ; in, 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.

[0010] Optionally, 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.

[0011] Optionally, S3 includes the following steps: S31. Unify and integrate the pre-processed comprehensive input data to form a comprehensive data set ,in Represents a standardized data set consisting of equipment operation data, environmental status data, and interference factor data; S32. Comprehensive Dataset Perform multidimensional association analysis and calculate the correlation matrix between each data category: ; in, It represents the correlation coefficient between the i-th category data and the j-th category data in the comprehensive data set, and is calculated using the following formula: ; in, Represents a comprehensive dataset 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 The comprehensive characteristic model M of substation operation status is constructed based on the analysis results: ; in, Represents comprehensive input data The transposed matrix of M represents the comprehensive characteristic model of substation operation status. is the weight vector, each component According to the autocorrelation coefficient of the corresponding data category Determine by the following formula: .

[0012] Optionally, S4 includes 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: ; in, represents the i-th optimization variable in the substation safety control strategy, n represents the total number of optimization variables, and each optimization variable The value range of is limited by the safe operation constraints of the substation and meets the following requirements: ; in, and They are substation safety control variables The lower and upper safety limits; S42, initialize the bitter fish population in the optimization search space, set the number of bitter fish individuals , randomly initialized within the optimization variable set X Bitter fish individuals constitute the initial population P: ; in, 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 are randomly distributed within the allowable range, and each bitter fish is given a dynamic adjustment weight , used to enhance the ability to adapt to different security operating environments: ; in, Represents individual bitter fish In optimizing goals The adaptive adjustment weight on 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. , load dispatch balance , minimize energy consumption and security response time , the fitness function is expressed as follows: ; in, It represents the failure rate of substation equipment under the optimization strategy X. The smaller the value, the higher the equipment stability. 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. The amount of loss caused by unreasonable scheduling of energy consumption during the operation of the substation. The optimization goal is to reduce ineffective energy consumption. The response time of the substation to sudden safety incidents. , , , To optimize the weight coefficient; S44, based on the collaborative foraging behavior of bitter fish optimization algorithm, the positions of individual bitter fish are adjusted, and the information interaction mechanism is set so that individuals consider group information when searching for the optimal control strategy. 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: ; in, is the neighborhood individual set of bitter fish i, which represents the individuals that exchange information with each other during the search process of substation safety control strategy. Represents the strategy difference between bitter fish i and j. The smaller the value, the more similar the control schemes of the two individuals are. It is a pheromone guidance factor. 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 values ​​of all individuals are calculated. , 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 parameters are output .

[0013] Optionally, S5 includes the following steps: S51, based on substation safety control strategy parameters Constructing an adaptive dynamic substation safety control strategy , the safety control strategy includes equipment load optimization scheduling strategy , Fault Response Strategy and security protection strategies : ; Multi-level intelligent load adjustment is performed based on the comprehensive characteristic model M of the substation operation status. Combine historical fault data, fault propagation path analysis and intelligent decision-making models to trigger rapid response. 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. , and define the load dynamic scheduling objective function: ; in, is the load power of the ith device in the substation at time t, is the ideal load distribution value for substation equipment, is the response factor of the equipment load adjustment. Different equipment has different response capabilities. 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: Introducing the fault propagation path prediction model to build an intelligent fault response strategy , a fault propagation prediction matrix is ​​established based on a multi-level impact assessment mechanism: ; in, is a historical fault data set that records the fault distribution under different operating conditions. is the current abnormal status data, Adjust parameters for system status, , , is the adaptive weight of each indicator. Exceeding the set threshold 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 , calculate the safety risk index of the substation under external interference : ; in, is the external interference factor data, is the impact factor function, which is used to describe the impact of different interference factors on substation safety. 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 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 security control strategy based on feedback adaptive mechanism , the substation operation status comprehensive characteristic model M and the optimized safety control strategy are stored in the information management system.

[0014] A substation safety control system based on information management, used to execute a substation safety control method based on information management, 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.

[0015] The beneficial effects of the present invention are: (1) The present invention adopts an improved bitter fish optimization algorithm with topology adaptation. By introducing a dynamic topology search mechanism, a pheromone guidance strategy and adaptive weight adjustment, the optimization algorithm can dynamically adjust the search path according to the real-time changes in the substation operation status, thereby improving the optimization capability of the substation safety control strategy. The topology adaptive search strategy enables the bitter fish optimization algorithm to dynamically adjust the search direction under the influence of load fluctuations, fault conditions and external interference factors, thereby ensuring that the optimization process is more efficient and stable.

[0016] (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 active protection measures before the fault occurs. It uses 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 fault propagation trends. When it is predicted that the fault may spread to key load equipment, the system can adjust the load distribution or perform local isolation in advance to reduce the impact of the fault on the overall power grid operation.

[0017] (3) The present invention adopts a multi-modal fusion security protection strategy, game theory optimization and fuzzy hierarchical analysis to construct a dynamic security protection mechanism for external interference factors. The existing substation security protection system is usually based on a fixed threshold strategy, which is difficult to make accurate judgments under complex environmental interference and easily leads to false alarms or omissions of security measures. By integrating 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 The present invention provides a flow chart of a substation safety control method and system based on information management. DETAILED DESCRIPTION

[0019] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0020] refer to Figure 1 , a substation safety control method based on information management, comprising the following steps: 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.

[0021] In this implementation, S1 includes the following steps: S11. Deploy smart sensors and data acquisition terminals near key nodes of substation equipment, environmental monitoring areas and external interference sources. 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 , the substation environmental status data is stored in the environmental database , the external interference factor data is stored in the interference database , the databases are associated with each other using indexes to satisfy the following storage structure: ; in, 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.

[0022] In this embodiment, 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.

[0023] In this implementation, S3 includes the following steps: S31. Unify and integrate the pre-processed comprehensive input data to form a comprehensive data set ,in Represents a standardized data set consisting of equipment operation data, environmental status data, and interference factor data; S32. Comprehensive Dataset Perform multidimensional association analysis and calculate the correlation matrix between each data category: ; in, It represents the correlation coefficient between the i-th category data and the j-th category data in the comprehensive data set, and is calculated using the following formula: ; in, Represents a comprehensive dataset 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 The comprehensive characteristic model M of substation operation status is constructed based on the analysis results: ; in, Represents comprehensive input data The transposed matrix of M represents the comprehensive characteristic model of substation operation status. is the weight vector, each component According to the autocorrelation coefficient of the corresponding data category Determine as follows: .

[0024] In this implementation, S4 includes 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: ; in, represents the i-th optimization variable in the substation safety control strategy, n represents the total number of optimization variables, and each optimization variable The value range of is limited by the safe operation constraints of the substation and meets the following requirements: ; in, and They are substation safety control variables The lower and upper safety limits; S42, initialize the bitter fish population in the optimization search space, set the number of bitter fish individuals , randomly initialized within the optimization variable set X Bitter fish individuals constitute the initial population P: ; in, 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 are randomly distributed within the allowable range, and each bitter fish is given a dynamic adjustment weight , used to enhance the ability to adapt to different security operating environments: ; in, Represents individual bitter fish In optimizing goals The adaptive adjustment weight on 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. , load dispatch balance , minimize energy consumption and security response time , the fitness function is expressed as follows: ; in, It represents the failure rate of substation equipment under the optimization strategy X. The smaller the value, the higher the equipment stability. 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. The amount of loss caused by unreasonable scheduling of energy consumption during the operation of the substation. The optimization goal is to reduce ineffective energy consumption. The response time of the substation to sudden safety incidents. , , , To optimize the weight coefficient; S44, based on the collaborative foraging behavior of bitter fish optimization algorithm, the positions of individual bitter fish are adjusted, and the information interaction mechanism is set so that individuals consider group information when searching for the optimal control strategy. 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: ; in, is the neighborhood individual set of bitter fish i, which represents the individuals that exchange information with each other during the search process of substation safety control strategy. Represents the strategy difference between bitter fish i and j. The smaller the value, the more similar the control schemes of the two individuals are. It is a pheromone guidance factor. 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 values ​​of all individuals are calculated. , 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 parameters are output .

[0025] In this implementation, S5 includes the following steps: S51, based on substation safety control strategy parameters Constructing an adaptive dynamic substation safety control strategy , the safety control strategy includes equipment load optimization scheduling strategy , Fault Response Strategy and security protection strategies : ; Multi-level intelligent load adjustment is performed based on the comprehensive characteristic model M of the substation operation status. Combine historical fault data, fault propagation path analysis and intelligent decision-making models to trigger rapid response. 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. , and define the load dynamic scheduling objective function: ; in, is the load power of the ith device in the substation at time t, is the ideal load distribution value for substation equipment, is the response factor of the equipment load adjustment. Different equipment has different response capabilities. 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: Introducing the fault propagation path prediction model to build an intelligent fault response strategy , a fault propagation prediction matrix is ​​established based on a multi-level impact assessment mechanism: ; in, is a historical fault data set that records the fault distribution under different operating conditions. is the current abnormal status data, Adjust parameters for system status, , , is the adaptive weight of each indicator. Exceeding the set threshold 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 , calculate the safety risk index of the substation under external interference : ; in, is the external interference factor data, is the impact factor function, which is used to describe the impact of different interference factors on substation safety. 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 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 security control strategy based on feedback adaptive mechanism , the substation operation status comprehensive characteristic model M and the optimized safety control strategy are stored in the information management system.

[0026] A substation safety control system based on information management, used to execute a substation safety control method based on information management, includes the following modules: Data acquisition and monitoring module, 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; The safety control strategy generation module is used to generate a dynamic substation safety control strategy based on the optimal substation safety control strategy parameters of the optimization calculation module. The safety control strategy includes equipment load optimization scheduling strategy, fault response strategy and safety protection strategy. The equipment load optimization scheduling strategy is used to adjust the 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 results of the fault propagation path. The safety protection strategy is used to implement different levels of safety protection measures based on the multi-modal 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 the 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.

[0027] 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 was as high as 37.5°C, the air humidity was 68%, and a thunderstorm weather warning was in effect. The substation undertook the power supply task of multiple industrial parks and residential areas, and the instantaneous load was close to 230MW. The substation was operating at a high load state.

[0028] At 14:25, the information management system detected that the load of main transformer 1 had reached 228.6MW, close to the rated upper limit, and the temperature of the GIS switch equipment 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 may be overloaded or equipment failure may be caused by lightning strike, the system entered the safety warning mode.

[0029] At 14:27, the substation SCADA system automatically enabled the load dispatching strategy based on the bitter fish optimization algorithm to calculate the current optimal load distribution plan. During the optimization process, the system dynamically adjusted the load distribution of main transformer 1 and main transformer 2 to reduce the operating pressure of main transformer 1.

[0030] The calculation results are as follows: Optimizing front load (14:26): Main transformer 1: 228.6MW, main transformer 2: 140.2MW, standby power supply: 42.0MW; Optimizing Afterload (14:28): Main transformer 1: 205.0MW (↓10.3%), main transformer 2: 160.8MW (↑14.7%), backup power supply: 47.6MW (↑13.3%); At 14:29, the SCADA system successfully executed load scheduling, and the load of main transformer 1 dropped to a safe range. At the same time, the scheduling capacity of the backup power supply was optimized.

[0031] At 14:33, the temperature sensor of the GIS equipment recorded an accelerated temperature rise rate, from 62.5°C to 67.2°C in the past 5 minutes. The system detected that this trend was abnormal. According to the fault propagation path prediction model, if the GIS temperature continues to rise for 5 minutes, it may cause insulation breakdown and affect the 110kV busbar.

[0032] The system automatically performs the following preventive measures: Forced cooling of GIS equipment: Start the air cooling system and reduce the load distributed to the switch circuit of GIS equipment.

[0033] 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 increase.

[0034] Triggering remote inspection: The SCADA system automatically notifies the operation and maintenance center and dispatches technicians to complete the remote inspection within 10 minutes.

[0035] At 14:36, the GIS temperature stabilized at 65.1°C, which did not reach the danger threshold, and the fault expansion was successfully avoided. In this case, the traditional system may require at least 15 minutes of manual intervention, while the method of the present invention completes the early warning and response within 3 minutes, improving the fault response speed.

[0036] At 14:40, the impact of thunderstorms intensified, the lightning intensity reached 24.2kA, and the SCADA system received an alarm from the environmental monitoring sensor. Through the multi-modal fusion security protection strategy, the system evaluated the external environmental risks and implemented the following preventive measures: Adjust the arrester status: improve the grounding resistance adjustment capability and optimize the current discharge to the backup grounding device.

[0037] Dynamically adjust the transformer operation mode: reduce the impact load on the high-voltage side and avoid secondary overvoltage caused by current overshoot.

[0038] Intelligent load transfer: Reduce the load supply in areas with high lightning risk and transfer part of the load to lines far away from the impact of thunderstorms.

[0039] At 14:45, the system successfully adjusted the transformer grounding mode, reducing the voltage fluctuations caused by lightning strikes. All key equipment remained in normal operation without tripping or equipment damage.

[0040] The experimental comparison data is as follows:

[0041] The method of the invention significantly improves the load dispatching efficiency, reduces the risk of equipment overload, and improves the safety protection capability in thunderstorm weather under high-load operation environment. Through intelligent optimization, the load adjustment response time is shortened by 80%, and the fault response time is shortened by 65.2%, avoiding economic losses of more than 850,000 yuan, providing a more reliable safety control solution for substations.

[0042] The present invention adopts a topology-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 substation operating status, thereby improving the optimization capability 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 conditions and external interference factors, thereby ensuring that the optimization process is more efficient and stable.

[0043] The present invention combines the 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 active protection measures before the fault occurs. It uses 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 fault propagation trends. When it is predicted that the fault may spread to key load equipment, the system can adjust the load distribution or perform local isolation in advance to reduce the impact of the fault on the overall power grid operation.

[0044] The present invention uses multimodal fusion security protection strategies, game theory optimization and fuzzy hierarchical analysis to construct a dynamic security protection mechanism for external interference factors. The existing substation security protection system is usually based on a fixed threshold strategy, which is difficult to make accurate judgments under complex environmental interference and easily leads to false alarms or omissions of security measures. A dynamic security risk assessment model is constructed by integrating environmental monitoring data, equipment operation data and external threat data, and combined with a game theory optimization algorithm, so that the security protection system can adaptively adjust the protection strategy according to different risk levels.

[0045] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by 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.

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 , the substation environmental status data is stored in the environmental database , the external interference factor data is stored in the interference database , the databases are associated with each other using indexes to satisfy the following storage structure: ； in, 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 ,in Represents a standardized data set consisting of equipment operation data, environmental status data, and interference factor data; S32. Comprehensive Dataset Perform multidimensional association analysis and calculate the correlation matrix between each data category: ； in, represents the correlation coefficient between the i-th category data and the j-th category data in the comprehensive data set, For the matrix rows and columns, use the following formula to calculate: ； in, Represents a comprehensive dataset 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 The comprehensive characteristic model M of substation operation status is constructed based on the analysis results: ； in, Represents comprehensive input data The transposed matrix of M represents the comprehensive characteristic model of substation operation status. is the weight vector, each component According to the autocorrelation coefficient of the corresponding data category Determine by the following formula: 。 5. A substation safety control method based on information management according to claim 1, characterized in that: 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: ； Where n represents the total number of optimization variables; represents the i-th optimization variable in the substation safety control strategy. Each optimization variable The value range of is limited by the safe operation constraints of the substation and meets the following requirements: ； in, and They are substation safety control variables The lower and upper safety limits; S42, initialize the bitter fish population in the optimization search space, set the number of bitter fish individuals , randomly initialized within the optimization variable set X Bitter fish individuals constitute the initial population P: ； in, 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 are randomly distributed within the allowable range, and each bitter fish is given a dynamic adjustment weight , used to enhance the ability to adapt to different security operating environments: ； in, Represents individual bitter fish In optimizing goals The adaptive adjustment weight on 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. , load dispatch balance , minimize energy consumption and security response time , the fitness function is expressed as follows: ； in, It represents the failure rate of substation equipment under the optimization strategy X. The smaller the value, the higher the equipment stability. 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. The amount of loss caused by unreasonable scheduling of energy consumption during the operation of the substation. The optimization goal is to reduce ineffective energy consumption. The response time of the substation to sudden safety incidents. , , , To optimize the weight coefficient; S44, based on the collaborative foraging behavior of bitter fish optimization algorithm, the positions of individual bitter fish are adjusted, and the information interaction mechanism is set so that individuals consider group information when searching for the optimal control strategy. 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: ； in, is the neighborhood individual set of bitter fish i, which represents the individuals that exchange information with each other during the search process of substation safety control strategy. Represents the strategy difference between bitter fish i and j. The smaller the value, the more similar the control schemes of the two individuals are. It is a pheromone guidance factor. 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 values ​​of all individuals are calculated. , 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 parameters are output. .

6. A substation safety control method based on information management according to claim 1, characterized in that: The S5 comprises the following steps: S51, based on substation safety control strategy parameters Constructing an adaptive dynamic substation safety control strategy , the safety control strategy includes equipment load optimization scheduling strategy , Fault Response Strategy and security protection strategies : ； Multi-level intelligent load adjustment is performed based on the comprehensive characteristic model M of the substation operation status. Combine historical fault data, fault propagation path analysis and intelligent decision-making models to trigger rapid response. 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. , and define the load dynamic scheduling objective function: ； in, is the load power of the ith device in the substation at time t, is the ideal load distribution value for substation equipment, is the response factor of the equipment load adjustment. Different equipment has different response capabilities. 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: Introducing the fault propagation path prediction model to build an intelligent fault response strategy , a fault propagation prediction matrix is ​​established based on a multi-level impact assessment mechanism: ； in, is a historical fault data set that records the fault distribution under different operating conditions. is the current abnormal status data, Adjust parameters for system status, , , is the adaptive weight of each indicator. Exceeding the set threshold 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 , calculate the safety risk index of the substation under external interference : ； in, is the external interference factor data, is the impact factor function, which is used to describe the impact of different interference factors on substation safety. 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 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 security control strategy based on feedback adaptive mechanism , the substation operation status comprehensive characteristic model M and the optimized safety control strategy are stored in the information management system.

7. 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 6, 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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