An intelligent management system for single converter operation

Abstract

The present invention discloses an intelligent management system for the operation of a single-unit converter, which belongs to the technical field of power operation supervision. It is used to solve the technical problems of poor autonomous supervision of abnormal operation of single-unit converters and poor autonomous management of operation and maintenance expansion in existing solutions. It performs data monitoring, statistics, processing and screening on the abnormal states of different single-unit converters in different production batches. From the production batch dimension, the abnormal data corresponding to all abnormal single-unit converters are integrated, calculated and analyzed to determine the overall state of the production batch corresponding to the production batch, and further perform an expansion analysis of the degree of abnormal impact of the abnormal overall state of the production batch obtained by analysis. By performing data integration, calculation and data analysis on the abnormal type dimension, the overall type of impact of different abnormal types on the operation of the single-unit converter is determined, and the subsequent operation and maintenance of the single-unit converter can be dynamically managed based on the analysis results.

Description

Technical Field

[0001] The present invention relates to the technical field of power operation supervision, and in particular to an intelligent management system for the operation of a single converter. Background Art

[0002] A single-cell converter is a device in the field of power electronics. In wind power systems, single-cell converters are typically used to convert the AC power generated by wind turbines into DC power, or to convert DC power back into AC power for use in the transmission network.

[0003] When implemented, the existing single-cell converter operation management solution cannot monitor and classify the different anomalies that occur in different single-cell converters in different batches, conduct anomaly impact assessment based on the classification results, and adaptively and dynamically manage the operation of different batches of single-cell converters. This results in poor autonomous supervision of single-cell converter operation anomalies and poor autonomous management of operation and maintenance expansion. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent management system for the operation of a single converter, which is used to solve the technical problems of poor autonomous supervision of abnormal operation of single converters and poor autonomous management of operation and maintenance expansion in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A single-unit converter operation intelligent management system, comprising:

[0007] The operation abnormality monitoring and statistical processing module is used to monitor the operation of all single converters in real time, conduct targeted abnormality sorting and screening for the single converters with abnormal monitoring, and update the screening results to the operation abnormality monitoring diagram in real time;

[0008] An operational anomaly integrated assessment management module is configured to perform integrated calculations and data analysis of the impact of abnormalities on the corresponding production batch based on real-time updates of the operational anomaly monitoring graph corresponding to the production batch, and to perform a first dynamic management of the operational maintenance of other single converters corresponding to the production batch based on the analysis results;

[0009] The operation anomaly expansion assessment management module is used to perform integrated calculations and data analysis on the impact of different anomaly types based on the real-time updates of different production batches in the operation anomaly monitoring diagram, and to perform secondary dynamic management of the subsequent operation and maintenance of the single converter based on the analysis results.

[0010] Preferably, the abnormality type corresponding to the single converter in the abnormal state is obtained, and the obtained abnormality type is digitally processed to obtain a corresponding abnormality identifier;

[0011] When implementing targeted abnormal sorting and screening of the single converters with abnormal monitoring according to the abnormal identification, analyze the abnormal identification;

[0012] If the sample exception type that is the same as the exception type does not exist in the exception type identification table, the exception identification corresponding to the obtained exception type is set to 0;

[0013] If there is a sample exception type that is the same as the exception type in the exception type identification table, the exception identification corresponding to the sample exception type that matches the same exception type is associated with the obtained exception type.

[0014] Preferably, the production batch corresponding to the single converter in the abnormal state is obtained according to the abnormal flag with a non-zero value, and the total number of abnormalities is increased by one;

[0015] Obtain the production batch, operation coordinates, abnormal identification, and abnormal occurrence time corresponding to the abnormal single converter, and sort and combine them to obtain the operation abnormality monitoring sequence corresponding to the abnormal single converter;

[0016] According to the production batches in the operation abnormality monitoring sequence, they are added to the corresponding sample production batches in the operation abnormality monitoring chart for real-time update.

[0017] Preferably, when there is data update for a production batch in the operation abnormality monitoring diagram, an integration instruction is generated, and according to the integration instruction, the updated production batch is marked as a target production batch, and the total number N of single converters in normal use and the total number N' of single converters with abnormalities in the target production batch are counted; data integration calculation is performed using a production batch identification piecewise function, and an impact status identifier corresponding to the target production batch is output;

[0018] The impact status flag contains a value of 0 or non-zero, indicating that the overall status of the production batch corresponding to the target production batch is normal or the overall status of the production batch is abnormal;

[0019] The impact status identifier of the calculated output is analyzed to determine the abnormal impact status corresponding to the target production batch.

[0020] Preferably, the expression of the production batch identification piecewise function is ; In the formula, SS is the impact status identifier; A is the standard impact value.

[0021] Preferably, if the value of the impact status indicator is 0, the target production batch is associated with the overall status of the production batch as normal;

[0022] If the value of the impact status identifier is not 0, an abnormal tracing instruction is generated and the impact degree identification piecewise function is used to perform data integration calculation and output the impact degree identifier corresponding to the target production batch;

[0023] Among them, the expression of the influence degree identification piecewise function is: ; In the formula, YS is the impact degree identifier; Ybi is the abnormality identifier corresponding to the single converter with abnormality; i is the different single converters with abnormality; i=1, 2, 3, ..., N´; B is the standard degree value;

[0024] The impact level identifier includes a value of 1 or 2, which respectively indicates that the impact level of the abnormality corresponding to the target production batch is a slight abnormality in the overall state of the production batch or a severe abnormality in the overall state of the production batch.

[0025] Preferably, the corresponding target production batch is marked as a low-impact production batch or a high-impact production batch according to the impact degree identifier with a value of 1 or 2;

[0026] When the first dynamic management is carried out on the operation and maintenance of other single converters corresponding to the target production batch, a targeted enhanced operation and maintenance plan will be subsequently implemented for other single converters operating normally in the low-impact production batch, and a targeted operation and maintenance after-sales plan will be implemented for other single converters operating normally in the high-impact production batch.

[0027] Preferably, all abnormal identifications j with non-zero values ​​and the corresponding abnormal identification values ​​Bj and the total number of occurrences Nj are obtained; j=1, 2, 3, ..., n; n is a positive integer; and the type impact values ​​corresponding to different abnormal types are calculated by the type abnormality impact formula; the type abnormality impact formula is Where, YYj is the type impact value corresponding to different abnormality types; NZ1 is the total number of single converters put into use corresponding to all production batches; NZ2 is the total number of abnormality types with non-zero values;

[0028] When performing the second dynamic management on the subsequent operation and maintenance of the single converter, data analysis is performed on the type impact values ​​corresponding to different abnormality types.

[0029] Preferably, if the type impact value is 0, the existing operation and maintenance plan corresponding to the corresponding exception type is maintained;

[0030] If the type impact value is 1, the existing operation and maintenance plan corresponding to the exception type is adjusted to implement targeted operation and maintenance optimization management.

[0031] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0032] The present invention monitors, collects, processes and filters data on abnormal states of different single converters in different production batches, and can provide reliable multi-dimensional data support for subsequent analysis and management of the operating states of the single converters in different dimensions.

[0033] The present invention integrates and calculates the abnormal data corresponding to all abnormal single-unit converters from the production batch dimension, determines the overall status of the production batch corresponding to the production batch, and further performs an extended analysis of the degree of abnormal impact of the abnormal overall status of the production batch obtained through analysis, thereby improving the diversity and active supervision effect of the monitoring data processing and extended analysis of abnormal single-unit converters in the production batch dimension.

[0034] The present invention determines the overall type of impact of different abnormality types on the operation of single-unit converters by performing data integration calculation and data analysis on the abnormality type dimension, and can dynamically manage the subsequent operation and maintenance of the single-unit converter based on the analysis results, thereby improving the autonomous supervision effect of the abnormality type dimension and the autonomous management effect of operation and maintenance expansion. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention will be further described below with reference to the accompanying drawings.

[0036] Figure 1 This is a module block diagram of a single-unit converter operation intelligent management system of the present invention.

[0037] Figure 2 This is a flowchart of the present invention for implementing targeted abnormality sorting and screening for single converters with abnormal monitoring.

[0038] Figure 3 This is a flowchart of analyzing the impact status identifier output by the calculation to determine the abnormal impact status corresponding to the target production batch in the present invention. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0040] like Figure 1 As shown, the present invention is an intelligent management system for the operation of a single converter, comprising an operation abnormality monitoring and statistical processing module, an operation abnormality expansion assessment management module and an operation abnormality integration assessment management module;

[0041] The operation abnormality monitoring and statistical processing module is used to monitor the operation of all single converters in real time, conduct targeted abnormality sorting and screening for single converters with abnormal monitoring, and update the screening results to the operation abnormality monitoring diagram in real time; it includes:

[0042] When a single converter in an abnormal state is detected, a tracing instruction is generated, and the abnormal type corresponding to the single converter in the abnormal state is obtained according to the tracing instruction. The obtained abnormal type is digitized, and the abnormal type is traversed and matched with the abnormal type identification table to obtain the corresponding abnormal identification;

[0043] It should be noted that the abnormality type corresponding to the abnormal state can be obtained by existing automated monitoring technology, or can be determined in combination with staff investigation;

[0044] In addition, the abnormality type includes self-abnormality type and non-self-abnormality type; the non-self-abnormality type may be an abnormality in the operation of a single converter caused by external factors;

[0045] Specifically, the abnormality type includes but is not limited to electrical fault type, mechanical fault type, control circuit fault type, etc.;

[0046] The abnormality type identification table pre-stores several different sample abnormality types and their corresponding abnormality identifications. The abnormality identification is used to digitally and differentially represent the impact of a single abnormality corresponding to the sample abnormality type. The specific value of the abnormality identification can be determined by professionals in this field based on the degree of the corresponding negative impact, or it can be determined by the total number of corresponding abnormalities in the history of single converter operation.

[0047] like Figure 2 As shown, when implementing targeted abnormal sorting and screening of the single converters with abnormal monitoring according to the abnormal identification, the abnormal identification is analyzed;

[0048] If the sample exception type that is the same as the exception type does not exist in the exception type identification table, the exception identification corresponding to the obtained exception type is set to 0;

[0049] If there is a sample exception type that is the same as the exception type in the exception type identification table, the exception identification corresponding to the matching sample exception type is associated with the obtained exception type;

[0050] Obtain the production batch corresponding to the single converter in the abnormal state according to the abnormal flag with a non-zero value and increase the total number of abnormalities by one;

[0051] It is worth noting that, in the embodiment of the present invention, by implementing targeted abnormality sorting and screening for the single converters with abnormal monitoring, the reliability of subsequent monitoring, analysis and management of different abnormality types can be improved;

[0052] Obtain the production batch, operation coordinates, abnormality identification, and abnormality occurrence time corresponding to the single converter in the abnormal state, sort and combine them, and obtain the operation abnormality monitoring sequence corresponding to the single converter in the abnormal state; the operation coordinates are the position coordinates corresponding to the single converter in the abnormal state;

[0053] According to the production batches in the operation abnormality monitoring sequence, they are added to the corresponding sample production batches in the operation abnormality monitoring chart for real-time update;

[0054] The operation anomaly monitoring graph stores operation anomaly monitoring sequences updated for different production batches and at different time points; the operation anomaly monitoring graph is used to record and store all abnormal data corresponding to different production batches; in addition, in the embodiment of the present invention, it is assumed that different production batches correspond to the same manufacturer;

[0055] In the embodiment of the present invention, by monitoring, collecting statistics, processing and screening the abnormal status of different single converters in different production batches, reliable multi-dimensional data support can be provided for subsequent analysis and management of the operating status of the single converters in different dimensions.

[0056] The operation anomaly integrated assessment management module is used to perform integrated calculation and data analysis of the impact of the anomaly on the corresponding production batch based on the real-time update of the operation anomaly monitoring diagram corresponding to the production batch, and to perform a first dynamic management of the operation and maintenance of other single converters corresponding to the production batch based on the analysis results; it includes:

[0057] When data is updated for a production batch in the abnormality monitoring graph, an integration instruction is generated. Based on the integration instruction, the updated production batch is marked as the target production batch. The total number of single converters in normal use (N) and the total number of single converters experiencing abnormalities (N´) in the target production batch are counted. The data integration calculation is performed using a production batch identification piecewise function, and the impact status identifier corresponding to the target production batch is output.

[0058] Among them, the expression of the production batch identification piecewise function is Where SS is the impact status identifier; A is the standard impact value, which can be determined based on the design requirement data corresponding to the single converter;

[0059] In addition, the impact status indicator includes a value of 0 or non-0, indicating that the overall status of the production batch corresponding to the target production batch is normal or the overall status of the production batch is abnormal;

[0060] like Figure 3 As shown, the impact status identifier of the calculated output is analyzed to determine the abnormal impact status corresponding to the target production batch;

[0061] If the value of the impact status indicator is 0, the overall status of the target production batch is associated with the production batch as normal;

[0062] It should be noted that in the embodiment of the present invention, the impact status corresponding to the target production batch with an abnormality is digitally processed and analyzed by using the production batch identification piecewise function. When the analysis result shows that the overall status of the production batch is abnormal, further extended analysis is required to determine the degree of abnormality corresponding to the target production batch.

[0063] If the value of the impact status identifier is not 0, an abnormal tracing instruction is generated and the impact degree identification piecewise function is used to perform data integration calculation and output the impact degree identifier corresponding to the target production batch;

[0064] Among them, the expression of the influence degree identification piecewise function is: Where, YS is the impact level identifier; Ybi is the abnormality identifier corresponding to the abnormal single converter; i is the different single converters with abnormalities; i = 1, 2, 3, ..., N´; B is the standard level value, which can be determined according to the design requirement data corresponding to the single converter;

[0065] In addition, the impact level indicator includes a value of 1 or 2, which respectively indicates that the impact level of the abnormality corresponding to the target production batch is a slight abnormality in the overall state of the production batch or a severe abnormality in the overall state of the production batch;

[0066] According to the impact level indicator with a value of 1 or 2, the corresponding target production batch is marked as a low-impact production batch or a high-impact production batch;

[0067] When conducting the first dynamic management of the operation and maintenance of other single converters corresponding to the target production batch, a targeted enhanced operation and maintenance plan will be subsequently implemented for other normally operating single converters in the low-impact production batch, and a targeted operation and maintenance after-sales plan will be implemented for other normally operating single converters in the high-impact production batch;

[0068] The enhanced O&M solution can add O&M services corresponding to all types of anomalies based on the existing O&M solution. The O&M after-sales solution can have professional technicians in the field assess whether the individual converters in the production batch need to be replaced, or provide unified after-sales maintenance services corresponding to all types of anomalies.

[0069] In the embodiment of the present invention, the abnormal data corresponding to all abnormal single converters that appear are integrated and calculated and analyzed from the production batch dimension to determine the overall status of the production batch corresponding to the production batch, and the abnormal overall status of the production batch obtained by analysis is further analyzed to determine the degree of abnormal impact. This improves the diversity of monitoring data processing and extended analysis of abnormal single converters in the production batch dimension and the proactive supervision effect.

[0070] The operational anomaly expansion assessment management module is used to perform integrated calculations and data analysis on the impact of different anomaly types based on real-time updates of different production batches in the operational anomaly monitoring diagram. This module also provides secondary dynamic management of subsequent operational maintenance of individual converters based on the analysis results. This module includes:

[0071] Get all abnormal identification j with non-zero values ​​and the corresponding abnormal identification values ​​Bj and the total number of occurrences Nj; j = 1, 2, 3, ..., n; n is a positive integer; and calculate the type impact value corresponding to different abnormal types through the type abnormal impact formula; the type abnormal impact formula is Where, YYj is the type impact value corresponding to different abnormality types; NZ1 is the total number of single converters put into use corresponding to all production batches; NZ2 is the total number of abnormality types with non-zero values;

[0072] It should be noted that the type impact value is used to integrate the impact data of different aspects of the abnormal type to digitally represent its overall type impact;

[0073] When performing the second dynamic management of subsequent operation and maintenance of the single converter, data analysis is performed on the type impact values ​​corresponding to different abnormality types;

[0074] If the type impact value is 0, the existing operation and maintenance plan corresponding to the exception type is maintained;

[0075] If the type impact value is 1, the existing operation and maintenance plan corresponding to the exception type is adjusted to implement targeted operation and maintenance optimization management.

[0076] In an embodiment of the present invention, data integration calculation and data analysis are performed on the abnormality type dimension to determine the overall type of impact of different abnormality types on the operation of the single-unit converter, and the subsequent operation and maintenance of the single-unit converter can be dynamically managed based on the analysis results, thereby improving the autonomous supervision effect of the abnormality type dimension and the autonomous management effect of operation and maintenance expansion.

[0077] In addition, the formulas involved in the above are all calculated by removing dimensions and taking their numerical values. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it through simulation software.

[0078] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the embodiments of the invention described above are merely illustrative. For example, the division of modules is only a logical function division, and other division methods may be used in actual implementation.

[0079] Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of these modules may be selected to achieve the objectives of this embodiment based on actual needs.

[0080] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing module, each module may exist physically separately, or two or more modules may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or hardware plus software functional modules.

[0081] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, but that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent management system for single converter operation, characterized in that: include: The operation abnormality monitoring and statistical processing module is used to monitor the operation of all single converters in real time, conduct targeted abnormality sorting and screening for the single converters with abnormal monitoring, and update the screening results to the operation abnormality monitoring diagram in real time; The operational anomaly integrated assessment management module is used to perform integrated calculations and data analysis on the impact of abnormalities on the corresponding production batches based on real-time updates of the operational anomaly monitoring graph. Based on the analysis results, it also performs the first dynamic management of the operation and maintenance of other single converters corresponding to the production batch, improving the diversity of monitoring data processing and extended analysis of abnormal single converters in the production batch dimension and the effectiveness of proactive supervision. When there is a data update for a production batch in the abnormality monitoring diagram, an integration instruction is generated. According to the integration instruction, the updated production batch is marked as the target production batch. The total number N of single converters in normal use in the target production batch and the total number N´ of single converters with abnormalities are counted. The data integration calculation is performed using the production batch identification piecewise function, and the impact status identifier corresponding to the target production batch is output. The expression of the production batch identification piecewise function is: ; In the formula, SS is the impact status identifier; A is the standard impact value; Analyze the impact status identifier of the calculated output to determine the abnormal impact status corresponding to the target production batch; If the value of the impact status indicator is 0, the overall status of the target production batch is associated with the production batch as normal; If the value of the impact status identifier is not 0, an abnormal tracing instruction is generated and the impact degree identification piecewise function is used to perform data integration calculation and output the impact degree identifier corresponding to the target production batch; Among them, the expression of the influence degree identification piecewise function is: ; In the formula, YS is the impact degree identifier; Ybi is the abnormality identifier corresponding to the single converter with abnormality; i is the different single converters with abnormality; i=1, 2, 3, ..., N´; B is the standard degree value; According to the impact level indicator with a value of 1 or 2, the corresponding target production batch is marked as a low-impact production batch or a high-impact production batch; The operational anomaly expansion assessment management module is used to perform integrated calculations and data analysis on the impact of different anomaly types based on real-time updates of different production batches in the operational anomaly monitoring diagram. This module also provides secondary dynamic management of subsequent operation and maintenance of individual converters based on the analysis results, improving the autonomous supervision of anomaly types and the autonomous management of operational expansion. Among them, obtain all abnormal identifications j with non-zero values ​​and the corresponding abnormal identification values ​​Bj and the total number of occurrences Nj; j = 1, 2, 3, ..., n; n is a positive integer; and calculate the type impact value corresponding to different abnormal types through the type abnormal impact formula; the type abnormal impact formula is Where, YYj is the type impact value corresponding to different abnormality types; NZ1 is the total number of single converters put into use corresponding to all production batches; NZ2 is the total number of abnormality types with non-zero values; When performing the second dynamic management of subsequent operation and maintenance of the single converter, data analysis is performed on the type impact values ​​corresponding to different abnormality types; If the type impact value is 0, the existing operation and maintenance plan corresponding to the exception type is maintained; If the type impact value is 1, the existing operation and maintenance plan corresponding to the exception type is adjusted to implement targeted operation and maintenance optimization management.

2. The intelligent management system for single converter operation according to claim 1, characterized in that: Obtaining an abnormality type corresponding to the single converter in the abnormal state, and digitally processing the obtained abnormality type to obtain a corresponding abnormality identifier; When implementing targeted abnormal sorting and screening of the single converters with abnormal monitoring according to the abnormal identification, analyze the abnormal identification; If the sample exception type that is the same as the exception type does not exist in the exception type identification table, the exception identification corresponding to the obtained exception type is set to 0; If there is a sample exception type that is the same as the exception type in the exception type identification table, the exception identification corresponding to the sample exception type that matches the same exception type is associated with the obtained exception type.

3. The intelligent management system for single converter operation according to claim 2, characterized in that: Obtain the production batch corresponding to the single converter in the abnormal state according to the abnormal flag with a non-zero value and increase the total number of abnormalities by one; Obtain the production batch, operation coordinates, abnormal identification, and abnormal occurrence time corresponding to the abnormal single converter, and sort and combine them to obtain the operation abnormality monitoring sequence corresponding to the abnormal single converter; According to the production batches in the operation abnormality monitoring sequence, they are added to the corresponding sample production batches in the operation abnormality monitoring chart for real-time update.

4. The intelligent management system for single converter operation according to claim 3, characterized in that: When the first dynamic management is carried out on the operation and maintenance of other single converters corresponding to the target production batch, a targeted enhanced operation and maintenance plan will be subsequently implemented for other single converters operating normally in the low-impact production batch, and a targeted operation and maintenance after-sales plan will be implemented for other single converters operating normally in the high-impact production batch.

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