CN116335893A - Method and system for classifying running states of wind generating set - Google Patents
Method and system for classifying running states of wind generating set Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention provides a classification method and a classification system for the running state of a wind generating set, wherein the classification method comprises the following steps: acquiring operation parameter information of a wind generating set in a target time period; determining a plurality of event types of the wind generating set and the time for entering each event type based on the operation parameter information; inputting a plurality of event types of a target time period into a fan state statistical analysis model, and outputting running states of a plurality of time intervals by the model, wherein the method comprises the following steps of: classifying event types to obtain available event types and unavailable event types; merging adjacent event types with the same classification to obtain running states of a plurality of time intervals; the running state comprises an available state and an unavailable state; the method can automatically identify the event of the pushing equipment, improve the accuracy and the authenticity of the counted index data, enable the wind generating set to adapt to the centralized management of a large-scale installation, and better cope with various complex equipment working conditions in actual operation.
Description
Technical Field
The invention relates to the technical field of wind generating sets, in particular to a method and a system for classifying the running states of a wind generating set.
Background
The new energy power station is often built in a remote area, geographical environment and climate conditions are bad, and when a generator set is built, the power transmission and transformation equipment and a control room related to the construction are required to be matched, and remote monitoring and management are realized by means of an information acquisition and processing technology. With the coming explosive growth of new energy industry. Digitization, intensification, and intellectualization are the necessary demands for managing new energy projects of such growing scale. In recent years, each new energy power generation group realizes a hierarchical equipment management system from top to bottom in an enterprise through being put into a construction area centralized control center and a group supervision center. The method is influenced by the characteristics of new energy power generation equipment (single machine capacity is small, power generation equipment is numerous), long-time running conditions of the equipment are difficult to control and manage from the global by only relying on operators and monitoring systems, and most of management modes of enterprises in the industry at present are based on the running conditions of manual reporting equipment and rely on report statistics and related indexes are calculated. Therefore, the data quality is difficult to ensure, and the index statistics and the production and management decisions are affected.
In view of the above, the invention provides a method and a system for classifying the running state of a wind generating set, so that the event of pushing equipment can be automatically identified, the accuracy and the authenticity of the counted index data are improved, the wind generating set is suitable for centralized management of a large-scale installation, and various complex equipment working conditions in actual running can be better dealt with.
Disclosure of Invention
The invention aims to provide a classification method of the running state of a wind generating set, which comprises the following steps: acquiring operation parameter information of a wind generating set in a target time period; determining a plurality of event types of the wind generating set and a time for entering each event type based on the operation parameter information; inputting a plurality of event types of the target time period into a fan state statistical analysis model, and outputting running states of a plurality of time intervals by the model; wherein obtaining the running states of the time intervals includes: classifying the event types to obtain available event types and unavailable event types; merging adjacent event types with the same classification to obtain running states of a plurality of time intervals; the operational states include an available state and an unavailable state.
Further, the method further comprises the following steps: outputting the state type and state information of the unavailable running state; the status information includes a unit name, an unavailable event type, a start time, an end time, and a duration of each unavailable event of the operating status.
Further, the method further comprises the following steps: acquiring existing report system data of a power plant; and comparing the information in the report system data with the unit name, the unavailable event type, the starting time, the ending time and the duration time, and determining the accuracy of report filling.
Further, the accuracy comprises a correlation condition accuracy rate and a consistency rate; wherein the association condition correctness is related to the type of the unavailable event of the unit; the rate of coincidence is related to the start time, end time, and duration of the unit.
Further, determining a consistency rate of the filled report includes: acquiring the filling start time and the filling end time of the failure of the wind generating set from the report system data; obtaining standard starting time and standard ending time of the failure of the wind generating set; comparing the filling duration between the filling start time and the filling end time with the standard duration between the standard start time and the standard end time to obtain a coincident time interval of the filling duration and the standard duration; and taking the ratio of the sum of the overlapping time intervals of all the wind generating sets to the sum of the standard duration as the consistency rate of the report.
Further, the event types include a normal operation state, a standby state, an overhaul state, a fault state, a power limit state, and an off-line state.
Further, classifying the normal operation state, the standby state, and the electricity limiting state as the available event type; classifying the service status, the fault status, and the offline status as the unavailable event type.
Further, the merging the adjacent event types with the same classification includes: judging whether the duration of each event type is longer than a preset duration; if not, changing the classification of the event type; based on the modified classification, neighboring event types of the same classification are merged.
Further, the operation parameter information comprises an original state of the wind generating set and a set operation parameter; the set operation parameters comprise current, voltage, temperature, angle and wind speed when the wind generating set is operated.
The invention aims to provide a classification system of the running state of a wind generating set, which comprises an acquisition module, a determination module and a classification module; the acquisition module is used for acquiring the operation parameter information of the wind generating set in the target time period; the determining module is used for determining a plurality of event types of the wind generating set and the time for entering each event type based on the operation parameter information; the classification module is used for inputting a plurality of event types of the target time period into a fan state statistical analysis model, and the model outputs the running states of a plurality of time intervals; wherein obtaining the running states of the time intervals includes: classifying the event types to obtain available event types and unavailable event types; merging adjacent event types with the same classification to obtain running states of a plurality of time intervals; the operational states include an available state and an unavailable state.
The technical scheme of the embodiment of the invention has at least the following advantages and beneficial effects:
by applying the fan state statistical analysis model, the automatic statistical analysis of the running event of the wind generating set is realized, the method of data docking with a report system widely applied to power generation enterprises in the current stage is supported, good implementation compatibility is provided, and the management needs of the current new energy power generation enterprises are more met.
Because the fan state statistical analysis model has the advantage of large-scale calculation performance, the problem of processing mass operation data of wind power equipment is solved by determining the operation states of a plurality of time intervals by using the fan state statistical analysis model, and a general scheme for monitoring the operation quality of the equipment in the future centralized large-scale installation background is provided.
Drawings
FIG. 1 is an exemplary flow chart of a method for classifying operational states of a wind turbine generator set according to some embodiments of the present invention;
FIG. 2 is an exemplary flow chart of a classification system for wind turbine generator system operating conditions according to some embodiments of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
FIG. 1 is an exemplary flow chart of a method for classifying operational states of a wind turbine generator set according to some embodiments of the present invention. In some embodiments, the process 100 may be performed by the system 200. As shown in fig. 1, the process 100 includes the following:
The target time period may refer to a time period in which the operational state of the genset needs to be classified. The target time period may be determined according to actual requirements. The operating parameter information includes the original state of the wind turbine and the turbine operating parameters. The raw state may refer to a state of a fan set by the power plant. The unit operating parameters may be related to the state of the unit as it operates. For example, the unit operating parameters may include current, voltage, temperature, angle, wind speed, etc. of the wind turbine unit when operating. In some embodiments, the wind generating set can realize the operation control of the set through a Programmable Logic Controller (PLC), and the PLC outputs the operation parameter information of the set.
The event type may refer to a type of event related to an operational state of the wind park. The event type may be determined according to specific needs. In some embodiments, event types include normal operating conditions, standby conditions, overhaul conditions, fault conditions, electricity limiting conditions, and offline conditions. The normal running state refers to a state corresponding to grid-connected power generation of the wind generating set. The standby state refers to that the wind generating set has no faults and routine maintenance, but the wind speed is lower than the cut-in wind speed or higher than the cut-out wind speed, and the set is in a ready-to-start state or a waiting grid-connected state. The overhauling state refers to a state corresponding to the condition that the wind generating set enters a service (maintenance and manual shutdown) mode. The fault state refers to a state corresponding to a fault stop code reported by the PLC of the wind generating set, or the fault stop of the wind generating set caused by other reasons. The electricity limiting state refers to a state in which the wind turbine generator set is power-limited to generate electricity or shut down due to a scheduling command. The offline state refers to the communication interruption or power failure between the wind generating set and the monitoring background. At any moment, according to the original PLC state of the fan, and through logic judgment, the real-time running states of different types of wind turbines can be collected into one of the 6 real-time states (only one of the states can be used at the same moment).
In some embodiments, the time at which the operating parameter changes to the next event type may be taken as the time at which the event type is entered.
And 130, inputting a plurality of event types of the target time period into a fan state statistical analysis model, and outputting the running states of a plurality of time intervals by the model.
A fan state statistical analysis (WTSA) model is used to classify and merge event types for wind turbines. For example, the WTSA model further classifies 6 event types of wind turbines into 2 categories. The fan state statistical analysis model can be realized through a program. For example, by the Python language (including numpy, etc. modules). In some embodiments, the WTSA model is written and packaged in Python language as an executable program, so that statistical analysis is performed on historical unit data stored in a high-capacity time sequence library, and the unavailable state event record of each wind turbine in a specified time is supported to be output in a table form. According to the report system data, the program can automatically compare the identification result with the filling information (comprising the time consistency rate of the unit event type and the event occurrence), and output the complete evaluation result.
According to the state classification rule of the WTSA model, unit state events can be divided into two main categories:
an unavailable status event: starting with one segment of the unavailable state, the next segment of the available state (which may be maintained for a certain period of time) is terminated, during which successive individual state intervals are combined into one unavailable state event.
Available status event: events outside the unavailable state are all counted as available state events.
The fan state statistical analysis model outputs running states of a plurality of time intervals, and the fan state statistical analysis model comprises the following steps:
and loading unit state data for a period of time, wherein the data comprises real-time state of the unit and time corresponding to the state. The format is as follows:
and recording and storing the moment of each change of the real-time state in the time period.
The event types are classified to obtain available event types and unavailable event types.
In some embodiments, event types may be classified based on whether wind turbines are available to divide event types into two categories: available event types (value 1) and unavailable event types (value 0). The available event type may refer to the unit being in a shutdown state when generating electricity or because the environmental conditions are not met (low wind standby or high wind cut-out). For example, the normal operation state, the standby state, and the electricity limiting state may be classified as available event types. The type of unusable event may refer to the equipment being out of line due to a malfunction or need for service or maintenance, a shutdown condition occurring, or the equipment being in an offline condition. For example, the overhaul status, the fault status, and the offline status may be classified as unusable event types.
For example, for a certain continuous target time period, the wind turbine generator is in a standby state in a first time interval, and the duration is 1.2h; in the second time interval, the wind generating set is in an operating state, and the duration time is 1.5h; in the third time interval, the wind generating set is in a power limiting state, and the duration time is 0.6h; in the fourth time interval, the wind generating set is in a normal running state, and the duration time is 3.2h; in the fifth time interval, the wind generating set is in a fault state, and the duration time is 1.1h; in the sixth time interval, the wind generating set is in an overhauling state, and the duration time is 3h; in the seventh interval, the wind generating set is in an offline state, and the duration time is 1.2h; in the eighth time interval, the wind generating set is in an overhauling state, and the duration time is 1.3h; and in the ninth time interval, the wind generating set is in a normal running state, and the duration time is 2.8h. The first time interval, the second time interval, the third time interval, the fourth time interval, the fifth time interval, the sixth time interval, the seventh time interval, the eighth time interval, and the ninth time interval are consecutive time intervals with the adjacent time intervals. Classifying event types of the nine time intervals to obtain available event types including a first time interval, a second time interval, a third time interval, a fourth time interval and a ninth time interval; the resulting unusable event types include a fifth time interval, a sixth time interval, a seventh time interval, and an eighth time interval.
Merging adjacent event types with the same classification to obtain running states of a plurality of time intervals; the operational states include an available state and an unavailable state.
For example, the plurality of available event types and the plurality of unavailable event types obtained above may be classified: because the first time interval, the second time interval, the third time interval and the fourth time interval are all available event types and are adjacent intervals, the first time interval, the second time interval, the third time interval and the fourth time interval can be combined to obtain an available running state with the duration of 6.5 hours. Similarly, the fifth time interval, the sixth time interval, the seventh time interval, and the eighth time interval may be combined to obtain an unavailable state having a duration of 6.6 hours. The ninth time interval alone is an available operating state with a duration of 2.8 hours.
In some embodiments, merging neighboring event types that are classified the same includes: judging whether the duration time of each event type is longer than a preset duration time; if not, changing the classification of the event type; based on the modified classification, neighboring event types of the same classification are merged.
The preset duration may refer to a preset minimum duration of the event type. When the duration of the event type is less than the preset duration, the event type can be ignored, and the running state of the event type is determined according to the running states of the event types before and after the event type. For example, when the first event type is an unavailable event type, the second event type is an available event type, the third event type is an unavailable event type, and the duration of the first event type and the third event type is greater than a preset duration and the duration of the second event type is less than the preset duration, the second event type may be determined to be an unavailable event type. Thus, the first event type, the second event type, and the third event type may be merged into an unavailable state.
In some embodiments, further comprising outputting state types and state information for unavailable operating states; the status information includes the unit name (number) of each unavailable event, the type of unavailable event, the start time, the end time, and the duration of the operating status.
In some embodiments, the state type takes the state of the first event type within the unavailable run state. In the time dimension, the set running event is reflected by the combination of continuous set real-time state changes, and the first state of the set state event represents the state of the whole event. For example, if a unit fails at a certain time, a manual maintenance state is changed to be processed after the machine is stopped, and operation is resumed after a period of time, then a "failure" state event is generated in the section.
In some embodiments, further comprising: acquiring existing report system data of a power plant; and comparing the information in the report system data with the unit name, the type of the unavailable event, the starting time, the ending time and the duration, and determining the accuracy of the report.
The report system data can refer to the existing report data of the power generation enterprises, and the unavailable state and the unavailable time length of the wind generating set are recorded. In some embodiments, the reporting system data may be obtained by manual filling.
In some embodiments, the accuracy rate includes an association case accuracy rate and a consistency rate; wherein the association condition correctness is related to the type of the unavailable event of the unit. For example, whether the type of unavailable event of the crew is properly filled.
The rate of coincidence is related to the start time, end time, and duration of the unit. In some embodiments, determining the consistency rate of the filled report includes: acquiring the filling start time and the filling end time of the failure of the wind generating set from the report system data; obtaining standard starting time and standard ending time of failure of a wind generating set; comparing the filling duration time from the filling start time to the filling end time with the standard duration time between the standard start time and the standard end time to obtain a coincident time interval of the filling duration time and the standard duration time; and taking the ratio of the sum of the overlapping time intervals of all the wind generating sets to the sum of the standard duration as the consistency rate of the report.
The fill start time may refer to a start time of the fan in an unavailable state recorded in the report system data. The end time of the filling may refer to the end time of the fan in the unavailable state recorded in the report system data.
The standard start time may refer to a start time of the fan in an unavailable state calculated by the fan state statistical model. The standard end time may refer to an end time of the fan in an unavailable state calculated by the fan state statistical model. In some embodiments, the start time of the first unavailable event in the unavailable state may be taken as the fill start time, and the end time of the last unavailable event in the unavailable state may be taken as the fill end time.
FIG. 2 is an exemplary flow chart of a classification system for wind turbine generator system operating conditions according to some embodiments of the invention. As shown in fig. 2, system 200 includes an acquisition module 210, a determination module 220, and a classification module 230.
The obtaining module 210 is configured to obtain operation parameter information of a wind generating set in a target period. For more on the acquisition module 210, see FIG. 1 and its associated description.
The determination module 220 is configured to determine a plurality of event types and a time to enter each event type for the wind turbine generator set based on the operating parameter information. For more details on the determination module 220, see FIG. 1 and its associated description.
The classification module 230 is configured to input a plurality of event types of a target time period into a fan state statistical analysis model, and the model outputs running states of a plurality of time intervals; wherein obtaining the running states of the plurality of time intervals includes: classifying event types to obtain available event types and unavailable event types; merging adjacent event types with the same classification to obtain running states of a plurality of time intervals; the operational states include an available state and an unavailable state. For more details on classification module 230, see FIG. 1 and its associated description.
According to the classification method and system for the running states of the wind generating set, provided by the invention, the real running conditions of the equipment can be completely obtained from the dimension of the real-time data by designing the fan state statistical analysis model aiming at the real-time data of the equipment, and the events such as equipment faults, overhaul and the like are accurately and automatically counted, so that the management efficiency and the management quality are improved. The program analysis process is completely based on the unit operation state data, so that the statistical result is more objective and reliable.
The classification method and the classification system for the running state of the wind generating set also support matching report form filling data, and provide high compatibility with the management mode of the current new energy power generation enterprise in the management dimension. The production manager can compare the identification result with the filling information through the program, analyze and judge the result, find out potential problems of each link such as equipment maintenance, operation monitoring and the like, thereby making targeted treatment measures and improving the operation quality of the equipment.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for classifying an operational state of a wind turbine generator system, comprising:
acquiring operation parameter information of a wind generating set in a target time period;
determining a plurality of event types of the wind generating set and a time for entering each event type based on the operation parameter information;
inputting a plurality of event types of the target time period into a fan state statistical analysis model, and outputting running states of a plurality of time intervals by the model; wherein obtaining the running states of the time intervals includes:
classifying the event types to obtain available event types and unavailable event types;
merging adjacent event types with the same classification to obtain running states of a plurality of time intervals;
the operational states include an available state and an unavailable state.
2. The method of classifying an operational state of a wind turbine generator set according to claim 1, further comprising: outputting the state type and state information of the unavailable running state; the status information includes a unit name, an unavailable event type, a start time, an end time, and a duration of each unavailable event of the operating status.
3. The method of classifying an operational state of a wind turbine generator set according to claim 2, further comprising:
acquiring existing report system data of a power plant;
and comparing the information in the report system data with the unit name, the unavailable event type, the starting time, the ending time and the duration time, and determining the accuracy of report filling.
4. A method of classifying an operational state of a wind turbine generator system according to claim 3, wherein the accuracy rate comprises a correlation condition accuracy rate and a coincidence rate; wherein the association condition correctness is related to the type of the unavailable event of the unit; the rate of coincidence is related to the start time, end time, and duration of the unit.
5. The method of classifying an operational state of a wind turbine generator system of claim 4, wherein determining a consistency rate of the filled report comprises:
acquiring the filling start time and the filling end time of the failure of the wind generating set from the report system data;
obtaining standard starting time and standard ending time of the failure of the wind generating set; comparing the filling duration between the filling start time and the filling end time with the standard duration between the standard start time and the standard end time to obtain a coincident time interval of the filling duration and the standard duration;
and taking the ratio of the sum of the overlapping time intervals of all the wind generating sets to the sum of the standard duration as the consistency rate of the report.
6. The method of classifying an operational state of a wind turbine generator set according to claim 1, wherein the event types include a normal operational state, a standby state, a maintenance state, a fault state, a power limit state, and an offline state.
7. A method of classifying an operating state of a wind park according to claim 6, wherein the normal operating state, the standby state and the electricity limiting state are classified as the available event type; classifying the service status, the fault status, and the offline status as the unavailable event type.
8. The method of classifying an operational state of a wind turbine generator set according to claim 1, wherein said merging adjacent event types of the same classification comprises:
judging whether the duration of each event type is longer than a preset duration;
if not, changing the classification of the event type;
based on the modified classification, neighboring event types of the same classification are merged.
9. The method for classifying an operational state of a wind turbine generator set according to claim 1, wherein the operational parameter information includes an original state of the wind turbine generator set and a set operational parameter; the set operation parameters comprise current, voltage, temperature, angle and wind speed when the wind generating set is operated.
10. The classification system of the running state of the wind generating set is characterized by comprising an acquisition module, a determination module and a classification module;
the acquisition module is used for acquiring the operation parameter information of the wind generating set in the target time period; the determining module is used for determining a plurality of event types of the wind generating set and the time for entering each event type based on the operation parameter information;
the classification module is used for inputting a plurality of event types of the target time period into a fan state statistical analysis model, and the model outputs the running states of a plurality of time intervals; wherein obtaining the running states of the time intervals includes: classifying the event types to obtain available event types and unavailable event types; merging adjacent event types with the same classification to obtain running states of a plurality of time intervals; the operational states include an available state and an unavailable state.
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| CN202310323418.5A CN116335893A (en) | 2023-03-29 | 2023-03-29 | Method and system for classifying running states of wind generating set |
| JP2023003252U JP3244451U (en) | 2023-03-29 | 2023-09-07 | Wind generator operating status classification system |
| DE202023105458.7U DE202023105458U1 (en) | 2023-03-29 | 2023-09-19 | A classification system for the operating status of wind turbines |
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