A power failure management method and system based on cloud edge combination

Abstract

This invention discloses a cloud-edge integrated power outage management method and system. An edge controller is installed at the power plant site to collect operating status parameters of on-site equipment and auxiliary start-up system equipment, enabling rapid anomaly detection and failure rate calculation. A digital twin module is deployed on the cloud server in the control center. Based on the operating equipment and steps included in the power outage operation in the plant scheduling plan, combined with the real-time operating status parameters of on-site equipment and on-duty personnel information during the simulated power outage operation, the power outage operation is simulated and rehearsed. The probability of a plant-wide power outage risk is determined based on the simulation results, thereby managing and controlling the power outage operation. By integrating multi-dimensional risk factors such as equipment failure rate, failure rate of operation-related equipment, personnel error rate, and the health status of auxiliary start-up system equipment, dynamic judgment is achieved, enabling more accurate and realistic prediction of power plant outage risks and reducing the number of plant-wide power outages.

Description

Technical Field

[0001] This invention relates to the field of automated power plant planned power outage dispatch management methods, and in particular to a power outage management method and system based on cloud-edge integration. Background Technology

[0002] As the source of the power system, the operational reliability of power plants directly affects grid security and social power supply stability. Plant-wide blackouts remain one of the main risks threatening safe operation. Power plant blackout management involves switching plant power or isolating equipment according to the plant's dispatch plan. During this process, it is crucial to ensure the safety of plant power (the power plant's own power, lighting, and control power) to prevent plant-wide blackouts. Even in the event of a plant-wide blackout, rapid power restoration must be guaranteed. Traditional planned blackout processes rely on pre-set logic and on-site judgment by operators, limiting their ability to respond to emergencies. The shutdown process requires multiple operators to monitor screens and manually execute hundreds of steps, making them highly susceptible to human error or misjudgment, potentially leading to a plant-wide blackout. Furthermore, the causes of plant-wide blackouts are complex and diverse, typically involving the coupling effects of equipment failure, human error, grid disturbances, and environmental factors. From a system perspective, plant-wide blackouts are often not caused by a single factor but rather a chain reaction triggered by the superposition of multiple risk factors under specific operating conditions. For example, excessive vibration of a feedwater pump (equipment factor), combined with the operator switching the pump group (operational factor), and the fatigue of the on-duty personnel (personnel factor), may lead to water supply interruption, which in turn triggers the boiler fire suppression protection and ultimately causes a power outage throughout the plant.

[0003] While some power plants have implemented outage risk management systems, such as deploying sensors for vibration, temperature, and pressure to collect real-time equipment operating data and using threshold alarms or machine learning algorithms for fault warnings, or strictly enforcing operation permit and work permit systems to standardize operator behavior and reduce the risk of misoperation, and in recent years, some power plants have also begun to explore the application of digital twin technology to build virtual models of equipment for state mapping and fault simulation, most existing power plant outage risk management methods only focus on the equipment itself, ignoring operational disturbances and human factors. These methods cannot respond to changes in operating conditions in real time and are difficult to accurately predict internal power outage risks. Summary of the Invention

[0004] Therefore, it is necessary to propose a cloud-edge integrated power outage management method and system to address the aforementioned technical issues. This involves setting up an edge controller at the power plant site to collect operational status parameters of on-site equipment and auxiliary start-up system equipment, enabling rapid anomaly detection and failure rate calculation for both operating and auxiliary start-up system equipment. A digital twin module is deployed on the cloud server in the control center. Based on the operating equipment and steps included in the power outage operation in the plant's scheduling plan, combined with the real-time operational status parameters of on-site equipment and information of on-duty operators during the simulated power outage operation, the power outage operation is simulated and rehearsed. The simulation results determine the probability of a plant-wide power outage risk, thereby enabling management and control of the power outage operation. By integrating multi-dimensional risk factors such as equipment failure rate, failure rate of operation-related equipment, personnel error rate, and the health status of auxiliary start-up system equipment, dynamic judgment is achieved. This allows for a more accurate and realistic reflection of predicted power plant outage risks, reducing the number of plant-wide power outages.

[0005] This invention provides a power outage management method based on cloud-edge integration, the power outage management method specifically including:

[0006] The edge controller collects real-time operating status parameters of the plant's field equipment and the status parameters of the auxiliary start-up system equipment in real time, and determines whether the equipment is abnormal based on the real-time operating status parameters; if there is no abnormality, the real-time operating status parameters and the status parameters of the auxiliary start-up system equipment are stored in the database.

[0007] The edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start system equipment, and historical maintenance records stored in the database according to a preset cycle, calculates the failure rate of field equipment and the health status of auxiliary start system equipment, and uploads them to the cloud server of the control center.

[0008] The control center cloud server parses the received plant scheduling plan. If the plant scheduling plan includes a power outage operation, within a preset time before the power outage operation is executed, the digital twin module parses and extracts the operation steps and operating equipment included in the power outage operation. It also extracts the field equipment failure rate and auxiliary start-up system equipment health of the corresponding operating equipment and the equipment associated with the operation steps. Combined with the real-time operating status parameters of the field equipment and the information of the on-duty operators during the simulated power outage operation, the power outage operation is simulated and rehearsed. Based on the simulation and rehearsal results, the probability of a power outage risk for the entire plant is determined.

[0009] The control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage.

[0010] Accordingly, in one embodiment, the digital twin module simulates and rehearses the power outage operation, specifically including:

[0011] The digital twin module predicts and simulates the real-time operating status of field equipment during a power outage operation based on the real-time operating status parameters of the field equipment at the start of the simulation, and calculates the probability G of plant operation failure. 场 ;

[0012] The digital twin module analyzes the power outage operation, extracts the operating equipment involved in each operation step, and extracts the execution field equipment associated with the operating equipment and operation steps according to the built-in knowledge graph. It also extracts the failure rate G of the operating equipment from the database. 操 and the failure rate G of the field equipment 执 According to the failure rate G of the operating equipment in each operating step 操 and the failure rate G of the field equipment 执 Calculate the probability G of power outage operation risk 综停 ;

[0013] The digital twin module determines the operator error rate G based on the on-duty operator information during the power outage operation. 误 ;

[0014] The simulation and pre-run module is based on the plant operation failure probability G. 场 The probability G of the power outage operation risk 综停 Operator error rate G 误 And the health status of the auxiliary startup system devices (G) 辅 Determine the probability G of a plant-wide power outage. 全停 ;

[0015] The The The probability of power outage operation risk G 综停 The weights, the Operator error rate G 误 The weights; Weights for assisting in the startup system equipment failure rate.

[0016] In another corresponding embodiment, the digital twin module also predicts the associated failure rate G of the field equipment during the simulated power outage operation based on the real-time operating status parameters of the field equipment at the start of the simulation. 关1 ;

[0017] The association weight R between the field device and the operating device or operating step is calculated based on the knowledge graph, and then the overall associated failure rate G of the field device is calculated. 综 ;

[0018] ;

[0019] Then, based on the failure rate G of the operating equipment in each operating step...操 and the failure rate G of the field equipment 执 Calculate the probability G of power outage operation risk 综停 Specifically, it includes:

[0020] ; i is the i-th step in the power outage operation, the The m represents the total number of operation steps in the power outage operation; The failure rate of the operating equipment in step i. The overall associated failure rate of the field equipment executing the i-th step operation;

[0021] .

[0022] Accordingly, the control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage, specifically including:

[0023] If the probability of a plant-wide power outage is G 全停 If the value is less than the first threshold, output a prompt indicating the current and next steps to be performed;

[0024] If the probability of a plant-wide power outage is G 全停 If the failure rate is greater than or equal to the first threshold, the control center determines the part with the highest failure rate during the simulation and pre-run, queries and reasons about replacement schemes based on the knowledge graph, and outputs corresponding operation prompts for operators to choose from when executing operation steps;

[0025] If the probability of a plant-wide power outage is G 全停 If the risk steps in the simulation are greater than or equal to the second threshold, the control center will push the risk steps in the simulation to the dispatch center, so that the dispatchers can modify the power outage operation according to the risk step prompts and reissue it.

[0026] Accordingly, the digital twin module calculates the probability G of plant operation failure. 场 Specifically, it includes:

[0027] A neural network prediction model is constructed based on the historical operating status parameters of field equipment in the database. The neural network prediction model takes the real-time operating status parameters of the field equipment at the start of the simulation as input, uses the preset time as the time window, and predicts the operating status of the field equipment at each time node within the preset time period. The digital twin model calculates the probability G of plant operation failure based on the operating status of the field equipment at each time node. 场 Within the preset time period, time nodes are set as integer multiples of the operating status parameter acquisition cycle.

[0028] Accordingly, the edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start-up system equipment, and historical maintenance records stored in the database according to a preset cycle, and calculates the failure rate of field equipment and the health status of auxiliary start-up system equipment, specifically including:

[0029] The edge controller constructs a set of historical operating curves for field devices under different external environmental parameters based on the historical operating status parameters of field devices and field external environmental parameters stored in the database. It also extracts the operating status parameters of field devices and field external environmental parameters within the current period, queries and compares them with the set of historical operating curves to determine the current health status of the field devices, and calculates the failure rate of the field devices by combining them with historical maintenance records.

[0030] The edge controller determines the health status of the auxiliary start system equipment based on the equipment's operational duration and status parameters stored in the database, combined with historical maintenance records.

[0031] Accordingly, the digital twin module determines the operator error rate G based on the on-duty operator information during the power outage operation. 误 Specifically, it includes:

[0032] The digital twin model extracts the operation log of the on-duty operator during the power outage operation and the operator's continuous on-duty hours before the power outage operation plan; the operation log includes the operator's length of service and the operator's error rate when operating a certain operation step or equipment based on all actual operations and simulated pre-operations.

[0033] The digital twin model, based on the extracted and analyzed operation steps and equipment, identifies the operator's error rate when performing the operation on the specified equipment and steps, calculates the overall error rate of the power outage operation, and then combines this with the operator's length of service and continuous shift duration to comprehensively calculate the operator's error rate G. 误 .

[0034] Accordingly, the digital twin module predicts the associated failure rate G of the field equipment during the power outage operation based on the real-time operating status parameters of the field equipment at the start of the simulation, which is related to the operation equipment and operation steps. 关1 Specifically, it includes:

[0035] The digital twin module performs N operation simulations within the preset time period. From all simulation results, it obtains the number of times n, associated with the execution site equipment, fails during the execution of the operation equipment and operation steps. The ratio of this number to the total number of simulations N is used as the simulation-associated failure rate G. 关1 The aforementioned .

[0036] Secondly, the present invention also provides a power outage management system based on cloud-edge integration, the power outage management system including field devices, edge controllers, control center, database and dispatch center;

[0037] The edge controller collects real-time operating status parameters of the plant's field equipment and the status parameters of the auxiliary start-up system equipment in real time, and determines whether the equipment is abnormal based on the real-time operating status parameters; if there is no abnormality, the real-time operating status parameters and the status parameters of the auxiliary start-up system equipment are stored in the database.

[0038] The edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start system equipment, and historical maintenance records stored in the database according to a preset cycle, calculates the failure rate of field equipment and the health status of auxiliary start system equipment, and uploads them to the cloud server of the control center.

[0039] The control center cloud server parses the received plant scheduling plan. If the plant scheduling plan includes a power outage operation, within a preset time before the power outage operation is executed, the digital twin module parses and extracts the operation steps and operating equipment included in the power outage operation. It also extracts the field equipment failure rate and auxiliary start-up system equipment health of the operating equipment corresponding to the operation steps and the equipment associated with the operation steps. Combined with the real-time operating status parameters of the field equipment and the information of the on-duty operators during the simulated power outage operation, the power outage operation is simulated and rehearsed. The probability of a plant-wide power outage risk is determined based on the simulation and rehearsal results. The control center then determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage risk.

[0040] The dispatch center is used to compile plant and station scheduling plans and upload them to the control center's cloud server, as well as to receive operation feedback from the control center.

[0041] Accordingly, the control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage, specifically including:

[0042] If the probability of a plant-wide power outage is G 全停 If the value is less than the first threshold, output a prompt indicating the current and next steps to be performed;

[0043] If the probability of a plant-wide power outage is G 全停 If the failure rate is greater than or equal to the first threshold, the control center determines the part with the highest failure rate during the simulation and pre-run, queries and reasons about replacement schemes based on the knowledge graph, and outputs corresponding operation prompts for operators to choose from when executing operation steps;

[0044] If the probability of a plant-wide power outage is G 全停If the risk steps in the simulation are greater than or equal to the second threshold, the control center will push the risk steps in the simulation to the dispatch center, so that the dispatchers can modify the power outage operation according to the risk step prompts and reissue it.

[0045] The beneficial effects of this invention are as follows: 1. An edge controller is set up at the power plant site to collect on-site equipment operating status parameters, and a neural network prediction module is deployed to realize rapid detection of equipment anomalies and calculation of failure rates, thereby reducing the computing pressure on the cloud.

[0046] 2. Deploy a digital twin module in the cloud server of the control center. Based on the operating equipment and steps included in the power outage operation in the plant scheduling plan, and combined with the real-time operating status parameters of the field equipment and the information of the on-duty operators during the simulated power outage operation, simulate the power outage operation. Based on the simulation results, determine the probability of power outage risk for the entire plant, and then carry out dynamic predictive management and control of the power outage operation, thereby improving the initiative and accuracy of power outage management of the power plant.

[0047] 3. The digital twin module integrates multiple risk factors, including equipment failure rate, operation-related equipment failure rate, personnel error rate, and auxiliary start-up system equipment health status, to achieve dynamic judgment. This enables a comprehensive assessment of power outage risks. Equipment failure rate reflects the health status of the equipment itself; operation-related equipment failure rate quantifies the disturbance impact of operational behavior on related equipment; personnel error rate reflects human-caused reliability; and auxiliary start-up system equipment health status reflects the plant's self-healing ability after operational errors. By integrating multiple factors, the system can more accurately and realistically reflect and predict power outage risks at power plants, reducing the number of plant-wide power outages. Even if a plant-wide power outage occurs during operation, the auxiliary start-up system can restore plant power in a very short time, improving plant operating efficiency and safety.

[0048] 4. When calculating equipment failure rate, operation-related equipment failure rate and personnel error rate, the digital twin module also combines multi-source information such as equipment operating status and power plant environment to calculate the probability value of a plant-wide power outage within a preset time window, providing operators with more accurate situational awareness.

[0049] 5. The digital twin module also dynamically adjusts the weights of each risk factor based on the current operating conditions during the simulation. For example, when an important equipment switching operation is performed, the weight of "operation-related failure rate" is automatically increased to improve the accuracy of prediction. Attached Figure Description

[0050] Figure 1 A flowchart illustrating the steps of a cloud-edge integrated power outage management method;

[0051] Figure 2 This is a schematic diagram of the structure of a cloud-edge integrated power outage management system. Detailed Implementation

[0052] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the following description.

[0053] This invention provides a power outage management method based on cloud-edge integration, the power outage management method specifically including:

[0054] The edge controller collects real-time operating status parameters of the plant's field equipment and the status parameters of the auxiliary start-up system equipment in real time, and determines whether the equipment is abnormal based on the real-time operating status parameters; if there is no abnormality, the real-time operating status parameters and the status parameters of the auxiliary start-up system equipment are stored in the database.

[0055] Specifically, the edge controller has a built-in anomaly detection model. After collecting and receiving real-time operating status parameters of field devices and status parameters of auxiliary start-up system devices, it determines whether the device is abnormal based on preset trigger thresholds and judgment conditions.

[0056] If there are no abnormalities, the real-time operating status parameters and auxiliary start system device status parameters are stored in the database;

[0057] If the equipment malfunctions, it will check whether its preset control logic can handle the malfunction. If it can, it will directly output control commands according to the preset control logic and report the malfunction and the handling record. If it cannot handle the malfunction, it will report the malfunction to the control center. The control center's cloud server will call the knowledge base and automatically generate detailed handling suggestions and send them to the edge controller so that the edge controller can control the field equipment to perform the handling.

[0058] The edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start-up system equipment, and historical maintenance records stored in the database according to a preset cycle, calculates the failure rate of field equipment and the health status of auxiliary start-up system equipment, and uploads them to the cloud server of the control center.

[0059] The control center cloud server parses the received plant scheduling plan. If the plant scheduling plan includes a power outage operation, within a preset time before the power outage operation is executed, the digital twin module parses and extracts the operation steps and operating equipment included in the power outage operation. It also extracts the field equipment failure rate and auxiliary start-up system equipment health of the corresponding operating equipment and the equipment associated with the operation steps. Combined with the real-time operating status parameters of the field equipment and the information of the on-duty operators during the simulated power outage operation, the power outage operation is simulated and rehearsed. Based on the simulation and rehearsal results, the probability of a power outage risk for the entire plant is determined.

[0060] The control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage.

[0061] Accordingly, in one embodiment, the digital twin module simulates and rehearses the power outage operation, specifically including:

[0062] The digital twin module predicts and simulates the real-time operating status of field equipment during a power outage operation based on the real-time operating status parameters of the field equipment at the start of the simulation, and calculates the probability G of plant operation failure. 场 ;

[0063] Specifically, a neural network prediction model is constructed based on the historical operating status parameters of field equipment in the database. The neural network prediction model takes the real-time operating status parameters of the field equipment at the start of the simulation as input, uses the preset time as a time window, and predicts and outputs the operating status of the field equipment at each time node within the preset time period. The digital twin model calculates the probability G of plant operation failure based on the operating status of the field equipment at each time node. 场 Within the preset time period, time nodes are set as integer multiples of the operating status parameter acquisition cycle.

[0064] The digital twin module analyzes the power outage operation, extracts the operating equipment involved in each operation step, and extracts the execution field equipment associated with the operating equipment and operation steps according to the built-in knowledge graph. It also extracts the failure rate G of the operating equipment from the database. 操 and the failure rate G of the field equipment 执 According to the failure rate G of the operating equipment in each operating step 操 and the failure rate G of the field equipment 执 Calculate the probability G of power outage operation risk 综停 ;

[0065] Specifically, the digital twin module also predicts the associated failure rate G of the field equipment during the power outage operation based on the real-time operating status parameters of the field equipment at the start of the simulation. 关1 ;

[0066] The inferred associated failure rate is the probability of the impact of operating device A on associated device B. In one embodiment, for example, if a water pump is shut down, the associated water pump will be overloaded and fail due to the shutdown of the water pump. The inferred associated failure rate can be determined based on the associated failure relationship between devices in the established fault tree model.

[0067] Alternatively, the failure rate G can be determined based on the number of times associated equipment malfunctions during the total number of simulations: the digital twin module performs N operation simulations within the preset time period, obtains the number of times n, the associated execution site equipment malfunctions during the execution of the operation equipment and operation steps from all simulation results, and uses the ratio of this number n to the total number of simulations N as the simulation-related failure rate G. 关1 The aforementioned ;

[0068] The association weight R between the field device and the operating device or operating step is calculated based on the knowledge graph, and then the overall associated failure rate G of the field device is calculated. 综 ;

[0069] ;

[0070] Existing calculations of associated failure rates for operation tickets mostly rely solely on equipment relationships to determine the probability of associated failures, neglecting to consider the equipment's own failure factors. This leads to projections that do not accurately reflect the actual operating scenarios of the plant system. Therefore, the comprehensive associated failure rate G of the execution site equipment is... 综 It not only includes the inferred associated failure rate, but also takes into account the failure probability of the equipment itself. Only in this way can the calculated associated execution field equipment failure rate more accurately reflect the risk impact based on operation in the actual operation scenario of the plant.

[0071] Accordingly, based on the failure rate G of the operating equipment in each operating step... 操 and the failure rate G of the field equipment 执 Calculate the probability G of power outage operation risk 综停 Specifically, it includes:

[0072] ; i is the i-th step in the power outage operation, the The m represents the total number of operation steps in the power outage operation; The failure rate of the operating equipment in step i. The overall associated failure rate of the field equipment executing the i-th step operation;

[0073] ;

[0074] Furthermore, G can be defined for each operational step in the power outage operation. i停 Assign the corresponding weight value w i When the i-th step is a critical operation in the power outage operation, the efficiency of this step G can be increased. i停 weight value w i ,

[0075] ;

[0076] The digital twin module determines the operator error rate G based on the on-duty operator information during the power outage operation. 误 ;

[0077] Specifically, the digital twin model extracts the operation log of the on-duty operator during the power outage operation and the operator's continuous on-duty time before the power outage operation plan; the operation log includes the operator's length of service and the operator's error rate when operating a certain operation step or equipment based on all actual operations and simulated pre-operations; when there are multiple on-duty operators, the operation log and continuous on-duty time of each operator are extracted and calculated separately;

[0078] The digital twin model, based on the extracted and analyzed operation steps and equipment, identifies the operator's error rate when performing the operation on the specified equipment and steps, calculates the overall error rate of the power outage operation, and then combines this with the operator's length of service and continuous shift duration to comprehensively calculate the operator's error rate G. 误 For example, if the longer the on-duty operator's tenure, the higher the error rate G. 误 The smaller the weight of the error rate G, the lower the error rate should be; conversely, the longer the continuous shift of the operator, the lower the weight of the error rate G. 误 The weight of this component should be dynamically adjusted upwards.

[0079] Since each operator on duty has different years of experience and different levels of proficiency, their proficiency in each type of operation step is also different. Since power outage operations usually involve multiple operation steps and different types of equipment, it is necessary to calculate the overall error rate of the power outage operation based on the error rate of the operator on duty when performing each operation step. The overall error rate can be set as the sum of the error rates of the operator on duty when performing each operation step, or only the error rate of important operation steps in the power outage operation.

[0080] The simulation and pre-run module is based on the plant operation failure probability G. 场 The probability G of the power outage operation risk 综停 Operator error rate G 误 And the health status of the auxiliary startup system devices (G) 辅 Determine the probability G of a plant-wide power outage. 全停 ;

[0081] The The The probability of power outage operation risk G 综停 The weights, the Operator error rate G 误 The weights; Weights for assisting in the startup system equipment failure rate;

[0082] In another embodiment, a Monte Carlo simulation model can also be set up to obtain G. 全停 .

[0083] Accordingly, the control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage, specifically including:

[0084] If the probability of a plant-wide power outage is G 全停 If the value is less than the first threshold, output a prompt indicating the current and next steps to be performed;

[0085] If the probability of a plant-wide power outage is G 全停 If the failure rate is greater than or equal to the first threshold, the control center determines the part with the highest failure rate during the simulation and pre-run, queries and reasons about replacement schemes based on the knowledge graph, and outputs corresponding operation prompts for operators to choose from when executing operation steps;

[0086] If the probability of a plant-wide power outage is G 全停 If the risk steps in the simulation are greater than or equal to the second threshold, the control center will push the risk steps in the simulation to the dispatch center, so that the dispatchers can modify the power outage operation according to the risk step prompts and reissue it.

[0087] In another embodiment, in order to achieve rapid judgment in the control center and save the computing power of the control center processor, the following configuration can be provided:

[0088] The ;

[0089] Furthermore, the control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage, specifically including:

[0090] If the probability of a plant-wide power outage is G ’ 全停 If the value is less than the first threshold, output a prompt indicating the current and next steps to be performed;

[0091] If the probability of a plant-wide power outage is G ’ 全停 If the value is greater than or equal to the first threshold, the control center will further calculate the rate G. ’ 全停 and If the sum of values ​​is less than the third threshold, the control center determines the part with the highest failure rate during the simulation, queries and reasons about replacement schemes based on the knowledge graph, and outputs corresponding operation prompts for operators to choose from when executing operation steps; if the sum of values ​​is greater than or equal to the third threshold, the control center pushes the risk steps in the simulation to the dispatch center, so that the dispatchers can modify the power outage operation according to the risk step prompts and reissue it.

[0092] If the probability of a plant-wide power outage is G ’ 全停If the risk steps in the simulation are greater than or equal to the second threshold, the control center will push the risk steps in the simulation to the dispatch center, so that the dispatchers can modify the power outage operation according to the risk step prompts and reissue it.

[0093] In this example, the control center only considers the probability G of a plant-wide power outage. ’ 全停 Only when the health status (G) of the auxiliary startup system device is greater than or equal to the first threshold will it be considered. 辅 A comprehensive judgment is made. If the sum is less than the third threshold, it means that even if a plant-wide power outage occurs during the simulation, the plant can be restored as soon as possible by combining the high health of the auxiliary start-up system, ensuring the normal operation of the plant. Therefore, the power outage operation can continue. If the sum is greater than or equal to the third threshold, it means that even with the self-healing capability of the auxiliary start-up system, there is still a high risk of a plant-wide power outage, and the power outage operation needs to be modified and adjusted.

[0094] In G ’ 全停 When the value is less than the first threshold, it indicates that the predicted risk of power outage operation is relatively small, and the operation can be carried out directly.

[0095] In G ’ 全停 If the value is greater than or equal to the second threshold, it indicates that the predicted risk of power outage operation is relatively high. Even without considering the self-healing capability of the auxiliary start-up system, there is still a significant risk of a plant-wide power outage. This indicates that the operation steps in the power outage operation are incorrectly set and need to be modified and adjusted.

[0096] In this example, only the probability of a plant-wide power outage G ’ 全停 Only when the health status (G) of the auxiliary startup system device is greater than or equal to the first threshold will it be considered. 辅 To perform a comprehensive judgment by summation calculation, one can first directly use G. ’ 全停 The system assesses the approximate risk of power outages, enabling rapid response and control without requiring summation calculations across all judgment conditions. This also reduces the computational burden on the control center processor and improves system real-time performance.

[0097] Accordingly, the edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start-up system equipment, and historical maintenance records stored in the database according to a preset cycle, and calculates the failure rate of field equipment and the health status of auxiliary start-up system equipment, specifically including:

[0098] The edge controller constructs a set of historical operating curves for field devices under different external environmental parameters based on the historical operating status parameters of field devices and field external environmental parameters stored in the database. It also extracts the operating status parameters of field devices and field external environmental parameters within the current period, queries and compares them with the set of historical operating curves to determine the current health status of the field devices, and calculates the failure rate of the field devices by combining them with historical maintenance records.

[0099] The edge controller determines the health status of the auxiliary start system equipment based on the equipment's operational duration and status parameters stored in the database, combined with historical maintenance records.

[0100] For example, when calculating and determining the failure rate of field equipment and the health status of auxiliary start-up system equipment by combining historical maintenance records, the following can be specifically included: if the equipment has just undergone maintenance, the failure rate should be dynamically reduced, that is, the health status should be dynamically increased.

[0101] Specifically, the length of the preset time window should be less than the length of the preset period, so as to avoid deviations in the simulation results due to the updating calculation of the failure rate of on-site equipment during the simulation process;

[0102] Accordingly, the control center records the actual power outage operation results and, based on these results, assesses the probability G of a plant-wide power outage risk. 全停 The fault weight values ​​of each part in the calculation formula are adjusted based on feedback.

[0103] Secondly, the present invention also provides a power outage management system based on cloud-edge integration, the power outage management system including field devices, edge controllers, control center, database and dispatch center;

[0104] The edge controller collects real-time operating status parameters of the plant's field equipment and the status parameters of the auxiliary start-up system equipment in real time, and determines whether the equipment is abnormal based on the real-time operating status parameters; if there is no abnormality, the real-time operating status parameters and the status parameters of the auxiliary start-up system equipment are stored in the database.

[0105] The edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start system equipment, and historical maintenance records stored in the database according to a preset cycle, calculates the failure rate of field equipment and the health status of auxiliary start system equipment, and uploads them to the cloud server of the control center.

[0106] The control center cloud server parses the received plant scheduling plan. If the plant scheduling plan includes a power outage operation, within a preset time before the power outage operation is executed, the digital twin module parses and extracts the operation steps and operating equipment included in the power outage operation. It also extracts the field equipment failure rate and auxiliary start-up system equipment health of the operating equipment corresponding to the operation steps and the equipment associated with the operation steps. Combined with the real-time operating status parameters of the field equipment and the information of the on-duty operators during the simulated power outage operation, the power outage operation is simulated and rehearsed. The probability of a plant-wide power outage risk is determined based on the simulation and rehearsal results. The control center then determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage risk.

[0107] The dispatch center is used to compile plant and station scheduling plans and upload them to the control center's cloud server, as well as to receive operation feedback from the control center.

[0108] Accordingly, the control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage, specifically including:

[0109] If the probability of a plant-wide power outage is G 全停 If the value is less than the first threshold, output a prompt indicating the current and next steps to be performed;

[0110] If the probability of a plant-wide power outage is G 全停 If the failure rate is greater than or equal to the first threshold, the control center determines the part with the highest failure rate during the simulation and pre-run, queries and reasons about replacement schemes based on the knowledge graph, and outputs corresponding operation prompts for operators to choose from when executing operation steps;

[0111] If the probability of a plant-wide power outage is G 全停 If the risk steps in the simulation are greater than or equal to the second threshold, the control center will push the risk steps in the simulation to the dispatch center, so that the dispatchers can modify the power outage operation according to the risk step prompts and reissue it.

[0112] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, ROM, RAM, etc.

[0113] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0114] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A power outage management method based on cloud-edge integration, characterized in that, The power outage management method specifically includes: The edge controller collects real-time operating status parameters of the plant's field equipment and the status parameters of the auxiliary start-up system equipment in real time, and determines whether the equipment is abnormal based on the real-time operating status parameters; if there is no abnormality, the real-time operating status parameters and the status parameters of the auxiliary start-up system equipment are stored in the database. The edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start system equipment, and historical maintenance records stored in the database according to a preset cycle, calculates the failure rate of field equipment and the health status of auxiliary start system equipment, and uploads them to the cloud server of the control center. The control center cloud server parses the received plant scheduling plan. If the plant scheduling plan includes a power outage operation, within a preset time before the power outage operation is executed, the digital twin module parses and extracts the operation steps and operating equipment included in the power outage operation. It also extracts the field equipment failure rate and auxiliary start-up system equipment health of the corresponding operating equipment and the equipment associated with the operation steps. Combined with the real-time operating status parameters of the field equipment and the information of the on-duty operators during the simulated power outage operation, the power outage operation is simulated and rehearsed. Based on the simulation and rehearsal results, the probability of a power outage risk for the entire plant is determined. The control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage.

2. The power outage management method based on cloud-edge integration as described in claim 1, characterized in that, The digital twin module simulates and rehearses power outage operations, specifically including: The digital twin module predicts and simulates the real-time operating status of field equipment during a power outage operation based on the real-time operating status parameters of the field equipment at the start of the simulation, and calculates the probability G of plant operation failure. 场 ; The digital twin module analyzes the power outage operation, extracts the operating equipment involved in each operation step, and extracts the execution field equipment associated with the operating equipment and operation steps according to the built-in knowledge graph. It also extracts the failure rate G of the operating equipment from the database. 操 and the failure rate G of the field equipment 执 According to the failure rate G of the operating equipment in each operating step 操 and the failure rate G of the field equipment 执 Calculate the probability G of power outage operation risk 综停 ; The digital twin module determines the operator error rate G based on the on-duty operator information during the power outage operation. 误 ; The simulation and pre-run module is based on the plant operation failure probability G. 场 The probability G of the power outage operation risk 综停 Operator error rate G 误 And the health status of the auxiliary startup system devices (G) 辅 Determine the probability G of a plant-wide power outage. 全停 ; The The The probability of power outage operation risk G 综停 The weights, the Operator error rate G 误 The weights; Weights for assisting in the startup system equipment failure rate.

3. The power outage management method based on cloud-edge integration as described in claim 2, characterized in that, The digital twin module also predicts the associated failure rate G of the field equipment during the power outage operation based on the real-time operating status parameters of the field equipment at the start of the simulation. 关1 ; The association weight R between the field device and the operating device or operating step is calculated based on the knowledge graph, and then the overall associated failure rate G of the field device is calculated. 综 ; ； Then, based on the failure rate G of the operating equipment in each operating step... 操 and the failure rate G of the field equipment 执 Calculate the probability G of power outage operation risk 综停 Specifically, it includes: ; i is the i-th step in the power outage operation, the The m represents the total number of operation steps in the power outage operation; The failure rate of the operating equipment in step i. The overall associated failure rate of the field equipment executing the i-th step operation; 。 4. The power outage management method based on cloud-edge integration as described in claim 1, characterized in that, The control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage, specifically including: If the probability of a plant-wide power outage is G 全停 If the value is less than the first threshold, output a prompt indicating the current and next steps to be performed; If the probability of a plant-wide power outage is G 全停 If the failure rate is greater than or equal to the first threshold, the control center determines the part with the highest failure rate during the simulation and pre-run, queries and reasons about replacement schemes based on the knowledge graph, and outputs corresponding operation prompts for operators to choose from when executing operation steps; If the probability of a plant-wide power outage is G 全停 If the risk steps in the simulation are greater than or equal to the second threshold, the control center will push the risk steps in the simulation to the dispatch center, so that the dispatchers can modify the power outage operation according to the risk step prompts and reissue it.

5. The power outage management method based on cloud-edge integration as described in claim 2, characterized in that, The digital twin module calculates the probability G of plant operation failure. 场 Specifically, it includes: A neural network prediction model is constructed based on the historical operating status parameters of field equipment in the database. The neural network prediction model takes the real-time operating status parameters of the field equipment at the start of the simulation as input, uses the preset time as the time window, and predicts the operating status of the field equipment at each time node within the preset time period. The digital twin model calculates the probability G of plant operation failure based on the operating status of the field equipment at each time node. 场 Within the preset time period, time nodes are set as integer multiples of the operating status parameter acquisition cycle.

6. The power outage management method based on cloud-edge integration as described in claim 1, characterized in that, The edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start-up system equipment, and historical maintenance records stored in the database according to a preset cycle, and calculates the failure rate of field equipment and the health status of auxiliary start-up system equipment, specifically including: The edge controller constructs a set of historical operating curves for field devices under different external environmental parameters based on the historical operating status parameters of field devices and field external environmental parameters stored in the database. It also extracts the operating status parameters of field devices and field external environmental parameters within the current period, queries and compares them with the set of historical operating curves to determine the current health status of the field devices, and calculates the failure rate of the field devices by combining them with historical maintenance records. The edge controller determines the health status of the auxiliary start system equipment based on the equipment's operational duration and status parameters stored in the database, combined with historical maintenance records.

7. The power outage management method based on cloud-edge integration as described in claim 2, characterized in that, The digital twin module determines the operator error rate G based on the on-duty operator information during the power outage operation. 误 Specifically, it includes: The digital twin model extracts the operation log of the on-duty operator during the power outage operation and the operator's continuous on-duty hours before the power outage operation plan; the operation log includes the operator's length of service and the operator's error rate when operating a certain operation step or equipment based on all actual operations and simulated pre-operations. The digital twin model, based on the extracted and analyzed operation steps and equipment, identifies the operator's error rate when performing the operation on the specified equipment and steps, calculates the overall error rate of the power outage operation, and then combines this with the operator's length of service and continuous shift duration to comprehensively calculate the operator's error rate G. 误 .

8. The power outage management method based on cloud-edge integration as described in claim 3, characterized in that, The digital twin module predicts the associated failure rate G of the field equipment during a power outage operation based on the real-time operating status parameters of the field equipment at the start of the simulation, which is related to the operating equipment and operation steps. 关1 Specifically, it includes: The digital twin module performs N operation simulations within the preset time period. From all simulation results, it obtains the number of times n, associated with the execution site equipment, fails during the execution of the operation equipment and operation steps. The ratio of this number to the total number of simulations N is used as the simulation-associated failure rate G. 关1 The aforementioned .

9. A power outage management system based on cloud-edge integration, characterized in that, The power outage management system includes field devices, edge controllers, a control center, a database, and a dispatch center; The edge controller collects real-time operating status parameters of the plant's field equipment and the status parameters of the auxiliary start-up system equipment, and determines whether the equipment is abnormal based on the real-time operating status parameters. If there are no abnormalities, the real-time operating status parameters and auxiliary start system device status parameters are stored in the database; The edge controller extracts historical operating status parameters of field equipment, status parameters of auxiliary start system equipment, and historical maintenance records stored in the database according to a preset cycle, calculates the failure rate of field equipment and the health status of auxiliary start system equipment, and uploads them to the cloud server of the control center. The control center cloud server parses the received plant scheduling plan. If the plant scheduling plan includes a power outage operation, within a preset time before the power outage operation is executed, the digital twin module parses and extracts the operation steps and operating equipment included in the power outage operation, and extracts the field equipment failure rate and auxiliary start-up system equipment health of the corresponding operating equipment and the equipment associated with the operation steps. Combined with the real-time operating status parameters of the field equipment and the information of the on-duty operators during the simulated power outage operation, the power outage operation is simulated and rehearsed, and the probability of a power outage risk for the entire plant is determined based on the simulation and rehearsal results. The control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage; The dispatch center is used to compile plant and station scheduling plans and upload them to the control center's cloud server, as well as to receive operation feedback from the control center.

10. A cloud-edge integrated power outage management system as described in claim 9, characterized in that, The control center determines whether to execute the power outage operation based on the determined probability of a plant-wide power outage, specifically including: If the probability of a plant-wide power outage is G 全停 If the value is less than the first threshold, output a prompt indicating the current and next steps to be performed; If the probability of a plant-wide power outage is G 全停 If the failure rate is greater than or equal to the first threshold, the control center determines the part with the highest failure rate during the simulation and pre-run, queries and reasons about replacement schemes based on the knowledge graph, and outputs corresponding operation prompts for operators to choose from when executing operation steps; If the probability of a plant-wide power outage is G 全停 If the risk steps in the simulation are greater than or equal to the second threshold, the control center will push the risk steps in the simulation to the dispatch center, so that the dispatchers can modify the power outage operation according to the risk step prompts and reissue it.

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