A direct current power export grid fault control optimization method

Abstract

The application provides a DC external power grid fault control optimization method, and belongs to the technical field of power systems, which comprises the following steps: constructing a DC external power grid fault analysis model according to the fault type, formulating a corresponding fault treatment scheme, and then constructing a fault safety control model; obtaining DC external power grid operation information, analyzing the operation information, judging the existing fault and the existing fault type of the DC external power grid, and outputting the existing fault treatment scheme from the fault safety control model; randomly combining the existing fault treatment scheme, simulating the random combination result, screening the random combination result, and obtaining an optimal treatment scheme and a backup treatment scheme; and using the optimal treatment scheme to treat the existing fault, and judging the execution mode of the backup treatment scheme according to the treatment result, which realizes systematic analysis and treatment scheme formulation for different fault types, enhances the pertinence and effectiveness of fault treatment, and improves the ability to deal with complex faults.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to an optimization method for fault control of DC transmission power grids. Background Technology

[0002] With the rapid development of renewable energy and the increase in electricity demand, DC power transmission networks, as an efficient and low-loss power transmission method, are gradually gaining attention. However, DC power transmission networks may encounter various faults during operation, leading to system instability or outages. Traditional methods often lack systematicity and flexibility, and are inefficient in handling complex faults.

[0003] Therefore, the present invention provides an optimization method for fault control of DC power transmission grids. Summary of the Invention

[0004] This invention provides a fault control optimization method for DC power transmission networks. By constructing a fault analysis model and a safety control model, it systematically identifies and analyzes fault types in the DC power transmission network. After obtaining operational information, the model judges the fault and outputs a handling plan. The handling plans are randomly combined and simulated to select the optimal and backup plans. The optimal plan is implemented to handle the fault, and the backup plan is executed based on the handling results. This improves fault recovery efficiency and system reliability, realizes systematic analysis and handling plan formulation for different fault types, enhances the pertinence and effectiveness of fault handling, and improves the ability to cope with complex faults.

[0005] This invention provides a method for optimizing fault control in a DC power transmission network, comprising:

[0006] Step 1: Construct a fault analysis model for the DC power transmission network based on the fault type. At the same time, formulate corresponding fault handling schemes based on the fault types, and construct a fault safety control model for the DC power transmission network based on the fault handling schemes.

[0007] Step 2: Obtain the DC power transmission network operation information, analyze the operation information based on the fault analysis model, determine the existing faults in the DC power transmission network and the corresponding fault types, and output the fault handling plan from the fault safety control model;

[0008] Step 3: Randomly combine the existing fault handling solutions, simulate the random combination results, filter the random combination results based on the simulation results, and obtain the optimal handling solution and the backup handling solution.

[0009] Step 4: Use the optimal solution to handle the fault, and determine the execution method of the backup solution based on the processing results.

[0010] This invention provides a method for optimizing fault control in a DC power transmission network. The method involves constructing a fault analysis model of the DC power transmission network based on fault types, formulating corresponding fault handling schemes based on the fault types, and constructing a fault safety control model for the DC power transmission network based on the fault handling schemes. The method includes:

[0011] Analyze the historical fault records of the DC power transmission network, classify the historical fault records, determine the fault types, and identify the type characteristics and type impact of each fault type;

[0012] Based on the aforementioned type characteristics and type impacts, statistical analysis is performed on the corresponding fault types to identify the occurrence frequency, duration, and loss impact of each fault type, resulting in a statistical analysis set. Based on the aforementioned type characteristics and type impacts, trend analysis is performed to identify the occurrence time pattern of each fault type.

[0013] A fault analysis model for DC power transmission networks is constructed by integrating statistical analysis sets of all fault types and occurrence time patterns.

[0014] Based on the output of the fault analysis model, a preliminary handling plan is formulated for each fault type. The preliminary handling plan is evaluated, and the preliminary handling plan is optimized based on the evaluation results to obtain the fault handling plan.

[0015] A fault-safe control model is constructed by integrating all fault handling solutions.

[0016] This invention provides a fault control optimization method for DC power transmission networks, which integrates all fault handling schemes to construct a fault safety control model, including:

[0017] Based on the fault handling plan, the optimization target is determined, and the initial field layer, initial area layer and initial central layer are set based on the optimization target.

[0018] Based on the initial field layer, initial area layer, and initial central layer, the control topology is set to obtain the field control layer, area control layer, and central control layer.

[0019] By integrating fault handling schemes based on the field control layer, regional control layer, and central control layer, a fault safety control model is derived.

[0020] This invention provides a method for optimizing fault control in a DC power transmission network. Based on the initial field layer, initial regional layer, and initial central layer, a control topology is set to derive a field control layer, a regional control layer, and a central control layer, including:

[0021] Obtain the field devices and corresponding device functions of the DC power transmission network, and perform field topology on the initial field layer based on the field devices and corresponding device functions to obtain the field control layer;

[0022] Acquire field data and corresponding control commands corresponding to multiple field control layers and integrate them into the initial area layer. Divide the field control layer into multiple sub-areas according to the field devices and their corresponding device functions. Configure an area controller for each sub-area. Select the corresponding data integration mechanism from the characteristic-integration mechanism table according to the data characteristics of the initial area layer. Integrate the data of all sub-areas to perform area topology on the initial area layer and obtain the area control layer.

[0023] Based on the data characteristics of the regional control layer, the corresponding decision algorithm is selected from the characteristic-decision algorithm table to establish a decision support mechanism, thereby deriving the central control layer.

[0024] This invention provides a fault control optimization method for DC power transmission networks. The method acquires DC power transmission network operation information, analyzes the operation information based on a fault analysis model, determines the existence of faults in the DC power transmission network and their corresponding types, and outputs fault handling schemes from a fault safety control model, including:

[0025] Based on the fault analysis model, the existing faults and their corresponding types in the operation information are determined, and the fault handling solutions and corresponding optimization objectives are determined based on the fault types.

[0026] The existing optimization objectives are analyzed using a fault-tolerant control model, and corresponding fault handling solutions are output based on the analysis results.

[0027] This invention provides a fault control optimization method for DC power transmission networks, which involves randomly combining existing fault handling schemes, simulating the random combination results, filtering the random combination results based on the simulation results, and obtaining the optimal handling scheme and backup handling schemes, including:

[0028] A random combination algorithm is set according to all fault types to randomly combine the existing fault handling solutions and obtain the random combination result.

[0029] A simulation environment is built based on the fault safety control model. The random combination results are simulated and processed. A first processing threshold is set on the simulation results according to the user's first requirement. The random combination results are filtered using the first processing threshold to obtain the optimal processing solution.

[0030] Based on the user's second requirement, a second processing threshold is set for the simulation results. The remaining random combination results are then filtered using the second processing threshold to obtain alternative processing solutions.

[0031] This invention provides a method for optimizing fault control in a DC power transmission network, comprising the following formulas for setting a first processing threshold and a second processing threshold:

[0032] , in, T1 represents the optimal control input at time t under the user's first requirement; T1 represents the first processing threshold. The dynamic equation representing the progress of fault recovery at time t; The dynamic equation representing the failure loss at time t; The dynamic equation represents the fault recovery time; a represents the recovery time weighting coefficient under the user's primary demand; b represents the fault loss weighting coefficient under the user's primary demand. Represents the dynamic variables for fault recovery under optimal control input and time variations; The Lagrange multiplier represents the state constraint; u represents the control input variable under the user's primary requirement; Represents the fault recovery state variable at time t; argmin represents the independent function that minimizes the function within the parentheses.

[0033] Similarly, a second processing threshold is determined based on the user's second requirement.

[0034] This invention provides a fault control optimization method for DC power transmission networks, which uses an optimal handling scheme to deal with existing faults and determines the execution mode of a backup handling scheme based on the handling results, including:

[0035] After implementing the optimal treatment plan, key performance indicators are evaluated based on the treatment results;

[0036] The power grid status is determined based on the key performance indicators. If both the power grid status and the key performance indicators return to normal, monitoring continues. If the power grid status fails to return to normal, or the key performance indicators fail to reach the corresponding standard values, the evaluation of the backup plan is initiated, and the execution method of the backup plan is determined based on the evaluation results.

[0037] Compared with existing technologies, the beneficial effects of this application are as follows: By constructing a fault analysis model and a safety control model, the fault types of DC power transmission networks are systematically identified and analyzed. After obtaining operational information, the model judges the fault and outputs a handling plan. The handling plans are randomly combined and simulated to select the optimal and backup plans. The optimal plan is implemented to handle the fault, and the backup plan is executed based on the handling results. This improves the fault recovery efficiency and system reliability, realizes the systematic analysis and handling plan formulation for different fault types, enhances the pertinence and effectiveness of fault handling, and improves the ability to cope with complex faults.

[0038] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0039] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0040] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0041] Figure 1 This is a flowchart illustrating a DC power grid fault control optimization method provided in an embodiment of the present invention. Detailed Implementation

[0042] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0043] Example 1:

[0044] This invention provides an optimization method for fault control in a DC power transmission grid, such as... Figure 1 As shown, it includes:

[0045] Step 1: Construct a fault analysis model for the DC power transmission network based on the fault type. At the same time, formulate corresponding fault handling schemes based on the fault types, and construct a fault safety control model for the DC power transmission network based on the fault handling schemes.

[0046] Step 2: Obtain the DC power transmission network operation information, analyze the operation information based on the fault analysis model, determine the existing faults in the DC power transmission network and the corresponding fault types, and output the fault handling plan from the fault safety control model;

[0047] Step 3: Randomly combine the existing fault handling solutions, simulate the random combination results, filter the random combination results based on the simulation results, and obtain the optimal handling solution and the backup handling solution.

[0048] Step 4: Use the optimal solution to handle the fault, and determine the execution method of the backup solution based on the processing results.

[0049] In this embodiment, the fault type is a classification of fault events based on fault characteristics, such as identifying short-circuit faults, open-circuit faults, overload faults, and equipment faults.

[0050] In this embodiment, the fault analysis model is a model built based on statistical analysis sets and time patterns, used to predict and analyze faults. For example, a model built using machine learning algorithms can predict future fault types and their probabilities. The input is equipment operation data, and the output is fault type, type characteristics, statistical analysis sets, occurrence time patterns, etc. The number of training iterations is 1000.

[0051] In this embodiment, the fault-tolerant control model is a model constructed by integrating all optimization schemes, used for real-time monitoring and control of faults. For example, it is a control system that integrates real-time data monitoring and automatic response mechanisms. The inputs are fault type, type characteristics, statistical analysis set, occurrence time pattern, etc., and the output is a preliminary handling scheme for each fault type. The number of training iterations is 1000.

[0052] In this embodiment, by analyzing historical fault records of the DC power transmission network, the characteristics and impacts of fault types are classified and identified, their occurrence frequency, duration and losses are statistically analyzed, and then a fault analysis model is constructed. Based on the model output, a preliminary handling plan is formulated for each fault and evaluated and optimized, ultimately forming a fault safety control model.

[0053] In this embodiment, optimization is to improve the initial processing plan to enhance its effectiveness, such as by adding redundant equipment to reduce the impact of short-circuit faults; the fault handling plan is the processing plan after evaluation and improvement, such as the optimized short-circuit fault handling plan including automatic monitoring and rapid response mechanisms.

[0054] In this embodiment, the operating information includes real-time monitoring of current, voltage, equipment status, load conditions, etc. The existence of faults and the types of faults are the results obtained by the fault analysis model after analyzing the operating information, and the fault handling scheme is the output result of the fault safety control model.

[0055] In this embodiment, the processing result refers to the specific feedback and data obtained after executing the scheme, which will be used to evaluate key performance indicators and grid status.

[0056] In this embodiment, a random combination algorithm is set to randomly combine fault handling schemes to generate multiple possible handling schemes. These schemes are simulated in the simulation environment of the fault safety control model, and the optimal handling scheme and backup handling scheme are selected according to the user's needs by setting the processing threshold.

[0057] In this embodiment, the execution method is the specific implementation steps or strategies determined after the evaluation of the backup handling scheme. For example, Scheme A: If the equipment status is "faulty", immediately replace the faulty equipment and start the backup power supply; Scheme B: If the recovery progress is less than 50%, increase the monitoring frequency and conduct manual inspection; Scheme C: If the load exceeds the safe range, dispatch the backup generator to balance the load.

[0058] In this embodiment, after implementing the optimal processing scheme, the key performance indicators are evaluated based on the processing results to determine the power grid status. If the power grid status and performance indicators return to normal, monitoring continues; if they do not return to normal, the effectiveness of the backup processing scheme is evaluated, and its execution method is determined.

[0059] The working principle and beneficial effects of the above technical solution are as follows: By constructing a fault analysis model and a safety control model, the fault types of the DC power transmission network are systematically identified and analyzed. After obtaining the operating information, the model judges the fault and outputs a handling plan. The handling plans are randomly combined and simulated to select the optimal and backup plans. The optimal plan is implemented to handle the fault, and the backup plan is executed based on the handling results. This improves the fault recovery efficiency and system reliability, realizes the systematic analysis and handling plan formulation for different fault types, enhances the pertinence and effectiveness of fault handling, and improves the ability to cope with complex faults.

[0060] Example 2:

[0061] This invention provides a method for optimizing fault control in a DC power transmission network. The method involves constructing a fault analysis model of the DC power transmission network based on fault types, developing corresponding fault handling schemes based on the fault types, and constructing a fault safety control model for the DC power transmission network based on the fault handling schemes. The method includes:

[0062] Analyze the historical fault records of the DC power transmission network, classify the historical fault records, determine the fault types, and identify the type characteristics and type impact of each fault type;

[0063] Based on the aforementioned type characteristics and type impacts, statistical analysis is performed on the corresponding fault types to identify the occurrence frequency, duration, and loss impact of each fault type, resulting in a statistical analysis set. Based on the aforementioned type characteristics and type impacts, trend analysis is performed to identify the occurrence time pattern of each fault type.

[0064] A fault analysis model for DC power transmission networks is constructed by integrating statistical analysis sets of all fault types and occurrence time patterns.

[0065] Based on the output of the fault analysis model, a preliminary handling plan is formulated for each fault type. The preliminary handling plan is evaluated, and the preliminary handling plan is optimized based on the evaluation results to obtain the fault handling plan.

[0066] A fault-safe control model is constructed by integrating all fault handling solutions.

[0067] In this embodiment, historical fault records are detailed records of fault events that have occurred in the past. For example, all fault events recorded by a power grid in the past three years, including the date, time, location and type of the fault.

[0068] In this embodiment, the type feature is the unique performance characteristic of each fault type. For example, a short-circuit fault may be characterized by a sudden surge in current, while an open-circuit fault may be characterized by a rapid drop in voltage.

[0069] In this embodiment, the type impact refers to the effect of each fault type on the operation of the power grid. For example, a short-circuit fault can cause equipment damage and power outages, while an open-circuit fault can lead to a power supply interruption.

[0070] In this embodiment, statistical analysis involves analyzing data on fault types to identify their characteristics, such as analyzing the frequency of occurrence of each fault type and its impact on the system over the past year.

[0071] In this embodiment, the statistical analysis set is a dataset generated based on statistical analysis, such as a data table containing the frequency of occurrence, duration, and impact of loss for each type of failure.

[0072] In this embodiment, the frequency of occurrence is the number of times a certain type of fault occurs within a specific time period. For example, short circuit faults occurred 10 times in the past year. The duration is the time required for a fault to recover from its occurrence. For example, the duration of an open circuit fault is 2 hours. The loss impact is the economic loss or service impact of the fault on the operation of the power grid. For example, the economic loss caused by a short circuit fault is 50,000 yuan.

[0073] In this embodiment, trend analysis is to analyze the occurrence patterns of fault types to identify changing trends. For example, it is found that short-circuit faults occur more frequently in winter.

[0074] In this embodiment, the occurrence time pattern is the distribution pattern of fault types over time. For example, open circuit faults are more likely to occur on weekends than on weekdays.

[0075] In this embodiment, the preliminary handling plan is a preliminary response measure formulated for each fault type. For example, the preliminary handling plan for a short circuit fault includes quickly disconnecting the faulty part of the circuit.

[0076] In this embodiment, the evaluation result is an assessment of the effectiveness of the preliminary treatment plan. For example, the evaluation finds that the preliminary treatment plan is effective in 90% of cases.

[0077] The working principle and beneficial effects of the above technical solution are as follows: by analyzing the historical fault records of the DC power transmission network, classifying and identifying the characteristics and impacts of fault types, statistically analyzing their occurrence frequency, duration and losses, and then constructing a fault analysis model, based on the model output, formulating preliminary handling plans for each fault and evaluating and optimizing them, and finally forming a fault safety control model, which improves the accuracy of fault identification and the effectiveness of handling plans, and enhances the safety and stability of the power grid.

[0078] Example 3:

[0079] This invention provides a fault control optimization method for DC power transmission networks, which integrates all fault handling schemes to construct a fault safety control model, including:

[0080] Based on the fault handling plan, the optimization target is determined, and the initial field layer, initial area layer and initial central layer are set based on the optimization target.

[0081] Based on the initial field layer, initial area layer, and initial central layer, the control topology is set to obtain the field control layer, area control layer, and central control layer.

[0082] By integrating fault handling schemes based on the field control layer, regional control layer, and central control layer, a fault safety control model is derived.

[0083] In this embodiment, the optimization objective is a specific goal set to improve fault handling efficiency and power grid security, such as reducing fault recovery time to within 1 hour and reducing economic losses caused by faults by 20%.

[0084] In this embodiment, the initial field layer refers to the preliminary setup for equipment and operators in the actual operation site of the power grid. For example, setting up field monitoring equipment in substations to ensure real-time collection of current, voltage, and temperature data.

[0085] In this embodiment, the initial area layer refers to the control and management settings within a specific area, which typically encompasses multiple field layers. For example, within a power distribution area, an area monitoring center is set up to coordinate and manage the operation of multiple substations.

[0086] In this embodiment, the initial central layer refers to the overall management and control center of the power grid, which is responsible for overall decision-making and strategy formulation. For example, the power grid dispatch center is responsible for monitoring the operating status of the entire power grid and formulating emergency response plans.

[0087] In this embodiment, the control topology refers to how to effectively connect and configure the field layer, regional layer and central layer in the fault handling scheme. For example, a hierarchical control architecture is adopted, in which the field layer reports data through the regional control layer, and the regional control layer then summarizes the information to the central control layer.

[0088] In this embodiment, the field control layer refers to the layer that performs real-time control and monitoring directly on-site. It typically includes automated equipment and sensors. For example, the field controller automatically adjusts the substation's operating parameters based on real-time data.

[0089] In this embodiment, the regional control layer is responsible for coordinating and managing multiple field control layers, performing data analysis and decision support. For example, the regional control center analyzes data from different substations to determine whether load adjustments are needed.

[0090] In this embodiment, the central control layer is responsible for overall strategy formulation and resource allocation to ensure the overall stability of the power grid. For example, the central dispatch center formulates a fault emergency response plan for the entire network based on data from the regional layer.

[0091] In this embodiment, integration refers to combining the control and management functions of each layer to form a unified fault-tolerant control model. For example, by integrating the information flow and control strategies of the field, regional and central control layers, rapid response and handling of faults can be achieved.

[0092] In this embodiment, the control topology is constructed by acquiring the field equipment and functions of the DC power grid, forming a field control layer, integrating the data and control commands of multiple field control layers, dividing sub-regions and configuring area controllers, and constructing area control layers and central control layers by selecting appropriate data integration mechanisms and decision algorithms.

[0093] The working principle and beneficial effects of the above technical solution are as follows: by determining the optimization target, an initial field layer, regional layer and central layer are constructed to form a control topology. Then, field, regional and central control layers are set. Based on these control layers, fault handling schemes are integrated to finally form a fault safety control model. This enhances the hierarchy and coordination of fault handling, improves the system's response speed and processing efficiency, ensures that the safe operation of the power grid can be restored quickly and effectively when a fault occurs, and reduces potential losses.

[0094] Example 4:

[0095] This invention provides a method for optimizing fault control in a DC power transmission network. Based on the initial field layer, initial regional layer, and initial central layer, a control topology is set to derive a field control layer, a regional control layer, and a central control layer, including:

[0096] Obtain the field devices and corresponding device functions of the DC power transmission network, and perform field topology on the initial field layer based on the field devices and corresponding device functions to obtain the field control layer;

[0097] Acquire field data and corresponding control commands corresponding to multiple field control layers and integrate them into the initial area layer. Divide the field control layer into multiple sub-areas according to the field devices and their corresponding device functions. Configure an area controller for each sub-area. Select the corresponding data integration mechanism from the characteristic-integration mechanism table according to the data characteristics of the initial area layer. Integrate the data of all sub-areas to perform area topology on the initial area layer and obtain the area control layer.

[0098] Based on the data characteristics of the regional control layer, the corresponding decision algorithm is selected from the characteristic-decision algorithm table to establish a decision support mechanism, thereby deriving the central control layer.

[0099] In this embodiment, the equipment function refers to the specific role or task of various equipment in the power grid. For example, transformer: voltage conversion and power transmission; converter: converting direct current to alternating current, or vice versa, to realize power transmission and distribution; protection relay: monitoring equipment status and cutting off power in case of failure.

[0100] In this embodiment, field topology refers to the spatial layout and connection relationship of field devices, such as the layout and electrical connection relationship diagram of transformers, switches, protection devices, etc. in a substation.

[0101] In this embodiment, field equipment refers to equipment that is actually installed and used at the power grid operation site, such as transformers, switches, measuring instruments, control panels, etc. in a substation.

[0102] In this embodiment, a sub-region is a smaller area that divides field equipment according to function or geographical location to facilitate management and control. For example, a large substation can be divided into a high-voltage area, a low-voltage area, and a control area.

[0103] In this embodiment, the area controller is a control system responsible for managing and controlling the equipment within a specific sub-area. For example, a controller configured in a certain sub-area is responsible for monitoring and adjusting the operating status of the equipment within that area.

[0104] In this embodiment, the feature-integration mechanism table is a mapping table that lists different data features and corresponding data integration methods. For example, the table may list the integration mechanism for "real-time data" as "weighted average method" and the mechanism for "historical data" as "time series analysis".

[0105] In this embodiment, the data characteristics of the initial region layer refer to the type, format, and features of the data collected in the region layer, such as real-time current data, historical fault records, and equipment status data.

[0106] In this embodiment, the region topology refers to the layout and connection relationship of devices within the region layer. For example, a device connection diagram of multiple sub-regions shows how each sub-region is interconnected through the region controller.

[0107] In this embodiment, the data integration mechanism refers to the methods and techniques used in the data processing process, such as using the "aggregation" method to integrate data from multiple sites into a single regional report.

[0108] In this embodiment, the data characteristics of the regional control layer refer to the type and features of the data collected and processed at the regional control layer, such as real-time monitoring data of current, voltage, temperature, etc. from different sub-regions.

[0109] In this embodiment, the feature-decision algorithm table is a mapping table that lists different data features and corresponding decision algorithms. For example, the table may list "random forest" as the decision algorithm corresponding to "fault prediction" and "linear regression" as the algorithm corresponding to "load prediction".

[0110] In this embodiment, the decision algorithm is an algorithm used to analyze data and make decisions. For example, machine learning algorithms (such as support vector machines and decision trees) are used for fault prediction and load management.

[0111] In this embodiment, the decision support mechanism refers to a system or method that provides support and suggestions during the decision-making process, such as providing fault response suggestions to the dispatcher based on the analysis results of real-time and historical data.

[0112] The working principle and beneficial effects of the above technical solution are as follows: by acquiring the field equipment and functions of the DC power grid, constructing the field topology, forming a field control layer, integrating the data and control commands of multiple field control layers, dividing the area into sub-regions and configuring area controllers, and constructing the area control layer and central control layer by selecting appropriate data integration mechanisms and decision-making algorithms, the efficiency and accuracy of data processing are improved, the synergy between control layers is enhanced, thereby optimizing fault response capability and system stability.

[0113] Example 5:

[0114] This invention provides a method for optimizing fault control in a DC power transmission network. The method involves acquiring DC power transmission network operation information, analyzing the operation information based on a fault analysis model, determining the presence of faults in the DC power transmission network and their corresponding types, and outputting fault handling solutions from a fault safety control model. The method includes:

[0115] Based on the fault analysis model, the existing faults and their corresponding types in the operation information are determined, and the fault handling solutions and corresponding optimization objectives are determined based on the fault types.

[0116] The existing optimization objectives are analyzed using a fault-tolerant control model, and corresponding fault handling solutions are output based on the analysis results.

[0117] In this embodiment, a fault refers to a specific problem or abnormal state detected in the actual operation of the power grid that may affect the normal operation of the system. For example, transformer overheating: the transformer temperature exceeds the safe range due to excessive load or cooling system failure; converter failure: the converter cannot work properly, resulting in the DC current not being able to be converted into AC current; communication failure: communication between the monitoring system and the control center is interrupted.

[0118] In this embodiment, the existence of fault types is a standard for classifying specific faults, which facilitates identification and handling. For example, equipment faults include mechanical faults of transformers or switching equipment; electrical faults include electrical problems such as short circuits and overloads; and system faults include communication interruptions and control system failures.

[0119] In this embodiment, the optimization objective is a specific goal set for the identified fault, such as reducing fault recovery time: reducing the transformer fault recovery time from 4 hours to less than 1 hour; improving equipment reliability: increasing the uptime of the converter and reducing the fault rate by 20%; and improving communication stability: ensuring that the communication availability of the monitoring system reaches 99.9%.

[0120] In this embodiment, the fault handling scheme is a specific measure or plan formulated to achieve the optimization goal. For example, equipment upgrade: replace old transformers and adopt new high-efficiency equipment; increase redundancy: add backup lines in critical communication links to ensure communication reliability; and regular maintenance plan: formulate detailed equipment maintenance and inspection plans to reduce the occurrence of faults.

[0121] The working principle and beneficial effects of the above technical solution are as follows: by identifying faults and their types in the operation information through a fault analysis model, the corresponding fault handling schemes and objectives are determined. The fault safety control model is used to conduct in-depth analysis of the optimization objectives, and finally outputs the corresponding fault handling schemes. This ensures the accuracy of fault identification and the pertinence of the handling schemes, improves the fault recovery efficiency of the power grid, reduces power outage time and economic losses, and enhances the stability and security of the system.

[0122] Example 6:

[0123] This invention provides a method for optimizing fault control in a DC power transmission network. The method involves randomly combining existing fault handling schemes, simulating the results of these combinations, filtering the results based on the simulation, and determining the optimal and backup handling schemes. The method includes:

[0124] A random combination algorithm is set according to all fault types to randomly combine the existing fault handling solutions and obtain the random combination result.

[0125] A simulation environment is built based on the fault safety control model. The random combination results are simulated and processed. A first processing threshold is set on the simulation results according to the user's first requirement. The random combination results are filtered using the first processing threshold to obtain the optimal processing solution.

[0126] Based on the user's second requirement, a second processing threshold is set for the simulation results. The remaining random combination results are then filtered using the second processing threshold to obtain alternative processing solutions.

[0127] In this embodiment, the random combination algorithm is an algorithm for generating fault handling solutions. It explores multiple possible solutions by randomly selecting different fault handling measures for combination. For example, assuming the following fault handling measures are available: A: replace equipment, B: add a monitoring system, C: perform regular maintenance, the random combination algorithm may generate the following combinations: combination 1: A+B, combination 2: B+C, combination 3: A+C, combination 4: A+B+C.

[0128] In this embodiment, the random combination result is all possible fault handling schemes generated by the random combination algorithm. For example, the random combination results generated by the above algorithm are: Scheme 1: Replace the transformer + increase monitoring, Scheme 2: Increase monitoring + regular maintenance, Scheme 3: Replace the transformer + regular maintenance, Scheme 4: Replace the transformer + increase monitoring + regular maintenance.

[0129] In this embodiment, the simulation environment is a virtual test platform used to test and evaluate the effectiveness of random combination results. For example, a simulation environment can be built using software tools (such as MATLAB, Simulink, etc.) to simulate the operation of the power grid under different fault handling schemes and evaluate the effectiveness of each scheme.

[0130] In this embodiment, simulation processing is used to test the random combination results and analyze their performance under specific conditions. For example, the random combination results are run in a simulation environment to observe the impact of each scheme on indicators such as power grid stability and fault recovery time.

[0131] In this embodiment, the user's primary requirement is the user's first requirement for the fault handling solution, which is usually related to efficiency, safety or economy. For example, the user hopes to restore the normal operation of the power grid as soon as possible after a fault occurs, and the set requirement is "fault recovery time is less than 1 hour".

[0132] In this embodiment, the first processing threshold is a standard used to filter the simulation processing results to ensure that the solution meets the user's primary needs.

[0133] In this embodiment, the optimal solution is the best fault handling solution that can meet the user's primary needs after screening. For example, after simulation processing and threshold screening, the optimal solution is "replacing the transformer + adding monitoring", with a recovery time of 45 minutes.

[0134] In this embodiment, the user's second requirement is the user's requirement for a backup solution, which is usually related to suboptimal choice or risk management. For example, the user wants to have a backup solution when the main solution fails, and the requirement is that "the backup solution can restore the power grid within 2 hours".

[0135] In this embodiment, the second processing threshold is a standard used to filter the remaining random combination results to meet the user's second requirement.

[0136] In this embodiment, the backup solution is a fault handling solution that can meet the user's second requirement after screening. For example, after a second screening, the backup solution is "increase monitoring + regular maintenance", with a recovery time of 90 minutes.

[0137] The working principle and beneficial effects of the above technical solution are as follows: by setting a random combination algorithm to randomly combine fault handling schemes, multiple possible handling schemes are generated. In the simulation environment of the fault safety control model, these schemes are simulated and processed. According to the user's needs, the processing threshold is set to select the optimal handling scheme and the backup handling scheme. This improves the flexibility and adaptability of fault handling, ensures rapid response under different needs, optimizes the fault recovery strategy, and reduces potential risks and losses.

[0138] Example 7:

[0139] This invention provides a method for optimizing fault control in a DC power transmission network, comprising the following formulas for setting a first processing threshold and a second processing threshold:

[0140] , in, T1 represents the optimal control input at time t under the user's first requirement; T1 represents the first processing threshold. The dynamic equation representing the progress of fault recovery at time t; The dynamic equation representing the failure loss at time t; The dynamic equation represents the fault recovery time; a represents the recovery time weighting coefficient under the user's primary demand; b represents the fault loss weighting coefficient under the user's primary demand. Represents the dynamic variables for fault recovery under optimal control input and time variations; The Lagrange multiplier represents the state constraint; u represents the control input variable under the user's primary requirement; Represents the fault recovery state variable at time t; argmin represents the independent function that minimizes the function within the parentheses.

[0141] Similarly, a second processing threshold is determined based on the user's second requirement.

[0142] In this embodiment, the optimal control input is the best control strategy or input required for fault handling under the user's primary needs. For example, it is assumed that when a fault occurs, the optimal control input is "increase the monitoring frequency".

[0143] In this embodiment, the dynamic equation for the fault recovery progress is an equation describing the change of the fault recovery process over time, which is usually expressed as the relationship between recovery progress and time.

[0144] In this embodiment, the dynamic equation for fault loss is an equation describing how the loss caused by the fault changes over time.

[0145] In this embodiment, the dynamic equation for fault recovery time is an equation describing how the time required for fault recovery changes over time.

[0146] In this embodiment, the fault recovery dynamic variable is a dynamic variable that describes the fault recovery state under the condition of optimal control input and time variation.

[0147] The working principle and beneficial effects of the above technical solution are as follows: the fault recovery progress, loss and recovery time are described by dynamic equations, and the control input is optimized to minimize the fault recovery loss by combining the processing threshold set by the user's needs. The optimal control strategy under specific constraints is determined by using the Lagrange multiplier method and weighting coefficients. The processing threshold is adjusted according to the user's second requirement to adapt to different recovery objectives, thereby improving the efficiency and pertinence of fault recovery and ensuring that the best recovery effect can be achieved under different conditions.

[0148] Example 8:

[0149] This invention provides a method for optimizing fault control in a DC power transmission network. The method uses an optimal handling scheme to address existing faults and determines the execution mode of a backup handling scheme based on the handling results. The method includes:

[0150] After implementing the optimal treatment plan, key performance indicators are evaluated based on the treatment results;

[0151] The power grid status is determined based on the key performance indicators. If both the power grid status and the key performance indicators return to normal, monitoring continues. If the power grid status fails to return to normal, or the key performance indicators fail to reach the corresponding standard values, the evaluation of the backup plan is initiated, and the execution method of the backup plan is determined based on the evaluation results.

[0152] In this embodiment, key performance indicators are quantitative indicators used to evaluate the operation effect of the power grid, which typically include recovery time, fault loss, system stability, etc. For example, recovery time: the time required for the system to return to normal operation after a fault occurs, with an expected value of 1 hour; fault loss: the economic loss of the power grid during the fault, with an expected value of no more than 10,000 yuan; system stability: the range of power grid frequency and voltage fluctuations, with an expected value of frequency between 49.5 Hz and 50.5 Hz and voltage within ±5%.

[0153] In this embodiment, the power grid status is a status variable that reflects the current operating status of the power grid. It usually includes recovery progress, equipment status, load status, etc. For example, recovery progress: indicates the percentage of fault recovery completed, such as 70%; equipment status: the working status of key equipment (such as transformers and switches), which may be "normal", "faulty" or "awaiting maintenance"; load status: whether the current load of the power grid is within the safe range, such as 80% (within the normal range).

[0154] In this embodiment, the standard value is the expected or allowable range of key performance indicators and power grid status, used to determine whether the power grid is operating normally. For example, the standard value of recovery time is ≤1 hour, the standard value of fault loss is ≤10,000 yuan, and the standard value of power grid frequency is 49.5Hz ≤ frequency ≤50.5Hz.

[0155] The working principle and beneficial effects of the above technical solution are as follows: After implementing the optimal treatment plan, the key performance indicators are evaluated based on the treatment results to determine the power grid status. If the power grid status and performance indicators return to normal, monitoring continues; if they do not return, the effectiveness of the backup treatment plan is evaluated, and its execution method is determined, thus ensuring the stability and security of the power grid after fault recovery. Through dynamic monitoring and evaluation mechanisms, the treatment strategy is adjusted in a timely manner, improving the reliability and response capability of the power grid.

[0156] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing fault control in a DC power transmission network, characterized in that, include: Step 1: Construct a fault analysis model for the DC power transmission network based on the fault type. At the same time, formulate corresponding fault handling schemes based on the fault types, and construct a fault safety control model for the DC power transmission network based on the fault handling schemes. Step 2: Obtain the DC power transmission network operation information, analyze the operation information based on the fault analysis model, determine the existing faults in the DC power transmission network and the corresponding fault types, and output the fault handling plan from the fault safety control model; Step 3: Randomly combine existing fault handling solutions, simulate the random combination results, and filter the random combination results based on the simulation results to obtain the optimal handling solution and backup handling solutions. This includes: setting a random combination algorithm based on all fault types to randomly combine existing fault handling solutions to obtain random combination results; building a simulation environment based on the fault safety control model to simulate the random combination results; setting a first processing threshold for the simulation results based on the user's first requirement; using the first processing threshold to filter the random combination results to obtain the optimal handling solution; setting a second processing threshold for the simulation results based on the user's second requirement; using the second processing threshold to filter the remaining random combination results to obtain backup handling solutions. Step 4: Use the optimal solution to handle the fault, and determine the execution method of the backup solution based on the processing results.

2. The DC power grid fault control optimization method according to claim 1, characterized in that, A fault analysis model for the DC transmission network is constructed based on the fault type. Simultaneously, corresponding fault handling schemes are formulated according to the fault type. Based on these fault handling schemes, a fault safety control model for the DC transmission network is constructed, including: Analyze the historical fault records of the DC power transmission network, classify the historical fault records, determine the fault types, and identify the type characteristics and type impact of each fault type; Based on the aforementioned type characteristics and type impacts, statistical analysis is performed on the corresponding fault types to identify the occurrence frequency, duration, and loss impact of each fault type, resulting in a statistical analysis set. Based on the aforementioned type characteristics and type impacts, trend analysis is performed to identify the occurrence time pattern of each fault type. A fault analysis model for DC power transmission networks is constructed by integrating statistical analysis sets of all fault types and occurrence time patterns. Based on the output of the fault analysis model, a preliminary handling plan is formulated for each fault type. The preliminary handling plan is evaluated, and the preliminary handling plan is optimized based on the evaluation results to obtain the fault handling plan. A fault-safe control model is constructed by integrating all fault handling solutions.

3. The DC power grid fault control optimization method according to claim 1, characterized in that, A fault-safe control model is constructed by integrating all fault handling solutions, including: Based on the fault handling plan, the optimization target is determined, and the initial field layer, initial area layer and initial central layer are set based on the optimization target. Based on the initial field layer, initial area layer, and initial central layer, the control topology is set to obtain the field control layer, area control layer, and central control layer. By integrating fault handling schemes based on the field control layer, regional control layer, and central control layer, a fault safety control model is derived.

4. The DC power grid fault control optimization method according to claim 3, characterized in that, Based on the initial field layer, initial regional layer, and initial central layer, the control topology is set, resulting in the field control layer, regional control layer, and central control layer, including: Obtain the field devices and corresponding device functions of the DC power transmission network, and perform field topology on the initial field layer based on the field devices and corresponding device functions to obtain the field control layer; Acquire field data and corresponding control commands corresponding to multiple field control layers and integrate them into the initial area layer. Divide the field control layer into multiple sub-areas according to the field devices and their corresponding device functions. Configure an area controller for each sub-area. Select the corresponding data integration mechanism from the characteristic-integration mechanism table according to the data characteristics of the initial area layer. Integrate the data of all sub-areas to perform area topology on the initial area layer and obtain the area control layer. Based on the data characteristics of the regional control layer, the corresponding decision algorithm is selected from the characteristic-decision algorithm table to establish a decision support mechanism, thereby deriving the central control layer.

5. The DC power grid fault control optimization method according to claim 4, characterized in that, Obtain operational information of the DC power transmission network, analyze the operational information based on a fault analysis model, determine the existing faults in the DC power transmission network and their corresponding types, and output fault handling solutions from the fault safety control model, including: Based on the fault analysis model, the existing faults and their corresponding types in the operation information are determined, and the fault handling solutions and corresponding optimization objectives are determined based on the fault types. The existing optimization objectives are analyzed using a fault-tolerant control model, and corresponding fault handling solutions are output based on the analysis results.

6. The DC power grid fault control optimization method according to claim 1, characterized in that, The formulas for setting the first processing threshold and the second processing threshold include: ， in, T1 represents the optimal control input at time t under the user's first requirement; T1 represents the first processing threshold. The dynamic equation representing the progress of fault recovery at time t; The dynamic equation representing the failure loss at time t; The dynamic equation represents the fault recovery time; a represents the recovery time weighting coefficient under the user's primary demand; b represents the fault loss weighting coefficient under the user's primary demand. Represents the dynamic variables for fault recovery under optimal control input and time variations; The Lagrange multiplier represents the state constraint; u represents the control input variable under the user's primary requirement; Represents the fault recovery state variable at time t; argmin represents the independent function that minimizes the function within the parentheses. Similarly, a second processing threshold is determined based on the user's second requirement.

7. The DC power grid fault control optimization method according to claim 1, characterized in that, The optimal handling solution is used to address the existing fault. Based on the handling results, the execution method of the backup handling solution is determined, including: After implementing the optimal treatment plan, key performance indicators are evaluated based on the treatment results; The power grid status is determined based on the key performance indicators. If both the power grid status and the key performance indicators return to normal, monitoring continues. If the power grid status fails to return to normal, or the key performance indicators fail to reach the corresponding standard values, the evaluation of the backup plan is initiated, and the execution method of the backup plan is determined based on the evaluation results.

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