CN114837902A - Health degree evaluation method, system, equipment and medium for wind turbine generator - Google Patents
Health degree evaluation method, system, equipment and medium for wind turbine generator 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
- F03D—WIND MOTORS
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Abstract
The invention relates to a method, a system, equipment and a medium for evaluating the health degree of a wind turbine generator, which comprises the following steps: preprocessing the acquired original operation data of the wind turbine generator to obtain optimal characteristic data of the wind turbine generator; based on the obtained optimal characteristic data of the wind turbine generator, carrying out quantitative evaluation on the health degree of the wind turbine generator; and visually displaying the obtained health degree quantitative evaluation result of the wind turbine generator, and outputting an evaluation suggestion. The method obtains the current running health state of the fan from the whole view, quantifies the current running health state of the fan, positions hidden dangers and intelligently recommends operation and maintenance decision suggestions according to the health levels of different indexes in a health degree evaluation system, and can be widely applied to the technical field of operation and maintenance of wind turbine generators.
Description
Technical Field
The invention belongs to the technical field of operation and maintenance of wind turbine generators, and particularly relates to a method, a system, equipment and a medium for evaluating the health degree of a wind turbine generator.
Background
With the proposal of the double-carbon target, the installed capacity of wind power in China is exponentially increased, and the problem of mismatching between the increase of the installed capacity and the increase of the operation and maintenance capacity exists, so that higher challenges are provided for the operation and maintenance capacity of the wind power plant. At present, the operation and maintenance work development process of the wind turbine generator is that after a SCADA system is subjected to data acquisition and monitoring control and alarm or shutdown information is reported in real time, a technical worker of a wind power plant takes a series of maintenance actions. The operation and maintenance mode cannot arrange corresponding maintenance or prepare spare parts for work by sensing the health state of the wind turbine generator in advance, and the process of waiting for the spare parts can reach one or two months due to sudden damage of most parts such as a gear box, a generator and the like, so that serious power generation loss is caused.
For wind power owners, the evaluation and the mastering of the integrity of the operation quality of the wind turbine generator are very important. Under the large background of wind power flat price internet surfing, owners want to obtain more profits, the construction cost and the operation and maintenance cost need to be reduced, and the wind power competitiveness is improved. Meanwhile, the modification, upgrading and decommissioning of the old wind power plant is a main means for reducing the construction cost and the operation and maintenance cost, however, how to evaluate whether the old wind power plant needs to be modified by upgrading and how to determine the direction of the upgrading and the modification need to be solved urgently.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a method, a system, a device, and a medium for evaluating health degree of a wind turbine generator, which on one hand acquire and quantify a health state of a fan from a whole view, and on the other hand locate hidden dangers and intelligently recommend operation and maintenance decision suggestions according to health levels of different indexes in a health degree evaluation system.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the invention provides a health degree evaluation method for a wind turbine generator, which comprises the following steps:
preprocessing the acquired original operation data of the wind turbine generator to obtain optimal characteristic data of the wind turbine generator;
based on the obtained optimal characteristic data of the wind turbine generator, carrying out quantitative evaluation on the health degree of the wind turbine generator;
and visually displaying the obtained health degree quantitative evaluation result of the wind turbine generator, and outputting an evaluation suggestion.
Further, the obtained original operation data of the wind turbine generator includes: sensor data and event data, the sensor data including vibration data, temperature, pressure, humidity, current, voltage; the event data includes events occurring on the wind turbine components and events performed by service technicians.
Further, the method for quantitatively evaluating the health degree of the wind turbine generator based on the obtained optimal characteristic data of the wind turbine generator comprises the following steps:
establishing a health degree evaluation system;
and calculating to obtain the complete machine health degree of the wind turbine generator based on the established health degree evaluation system and the acquired optimal characteristic data of the wind turbine generator.
Further, the health degree evaluation system comprises a statistical index system and a trend index system;
the statistical index system comprises reliability and real output indexes;
the trend index system comprises performance degradation identification, fault early warning and sensor abnormal indexes.
Further, the method for obtaining the overall health degree of the wind turbine generator through calculation based on the established health degree evaluation system and the acquired optimal characteristic data of the wind turbine generator comprises the following steps:
calculating to obtain each index value in a health degree evaluation system based on the acquired optimal characteristic data of the wind turbine generator and standardizing;
and calculating to obtain the health degree of the whole machine based on the preset weight coefficient and the normalized index value.
Further, the calculation formula of the whole health degree is as follows:
wherein S is i Scoring the ith index; w i Is the ith index weight.
Further, the method for visually displaying the health quantitative evaluation result of the wind turbine generator and outputting the evaluation suggestion comprises the following steps:
finding out a problem wind turbine generator according to the obtained health degree quantitative evaluation result of the health group of the wind turbine generator;
and obtaining a tree diagram corresponding to the problem wind turbine generator according to the health degree evaluation system, searching and positioning a problem source, and giving suggestions to arrangement of spare parts and maintenance activities of the wind power plant.
In a second aspect, the present invention provides a health degree evaluation system for a wind turbine generator, which includes:
the data acquisition module is used for preprocessing the acquired original operation data of the wind turbine generator to obtain the optimal characteristic data of the wind turbine generator;
the health degree evaluation module is used for quantitatively evaluating the health degree of the wind turbine generator based on the obtained optimal characteristic data of the wind turbine generator;
and the result output module is used for visually displaying the obtained health degree quantitative evaluation result of the wind turbine generator and outputting an evaluation suggestion.
In a third aspect, the present invention provides a processing device, where the processing device at least includes a processor and a memory, where the memory stores a computer program, and the processor executes the computer program when executing the computer program to implement the steps of the wind turbine health assessment method.
In a fourth aspect, the present invention provides a computer storage medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to implement the steps of the wind turbine health assessment method.
Due to the adoption of the technical scheme, the invention has the following advantages:
1. the health degree evaluation system of the wind turbine generator, provided by the invention, comprises a statistical index system and a trend index system, and not only considers the state performance of the wind turbine generator in a period of historical time, but also considers the current state identification and the future state development trend change of the wind turbine generator. The current state and future trend of the whole unit are understood and mastered macroscopically, and the comprehensive management of the asset running condition is facilitated. In addition, in the design of specific indexes, the testability and the representativeness of the selected evaluation indexes are fully considered, and the scientificity and the effectiveness of a health degree system are ensured.
2. The health degree evaluation system of the wind turbine generator system not only supports quantification of the health degree of equipment, but also supports problem tracing: for equipment with low overall health scores, specific problem sources can be located. Therefore, the problem is killed in the bud state, the sub-health condition of the component is sensed in advance, maintenance or technical improvement is arranged, the service life is prolonged, the shutdown time is shortened, the power generation loss is reduced, and the increase of large operation and maintenance cost caused by the replacement of a large component due to the thorough damage of the large component is avoided.
3. According to the method, historical operation data of a large number of wind turbine generators are collected, the relation expressed between different wind field health degrees is observed, and the difference and influence factors (such as operation time and fan brands) between the different wind field health degrees are known, so that the operation rule of the fan is revealed in a larger range. And evaluating the health degree of the old units, and knowing the life cycle stage of the old wind field, thereby providing a reference basis for whether the old wind field is upgraded and modified and the upgrading and modifying direction.
Therefore, the method can be widely applied to the technical field of operation and maintenance of the wind turbine generator.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. In the drawings:
FIG. 1 is a flow chart of a health degree evaluation method for a wind turbine generator according to an embodiment of the present invention;
FIG. 2 is a health degree evaluation system of a wind turbine generator provided by the embodiment of the invention;
FIG. 3 is a calculation result of the health of the whole machine in the embodiment of the present invention;
FIG. 4 is a tree diagram of the overall health of the number 4 unit in the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the described embodiments of the invention, are within the scope of the invention.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
For a wind power owner, the evaluation and the mastering of the integrity of the operation quality of the wind generation set are very important, the evaluation of the health degree of the whole wind generation set can macroscopically understand and master the current state and the future trend of the whole wind generation set, and the comprehensive management of the asset operation condition is facilitated. Therefore, in some embodiments of the present invention, a method for evaluating health of a wind turbine is provided, including: preprocessing the acquired original operation data of the wind turbine generator to obtain optimal characteristic data of the wind turbine generator; and quantitatively evaluating the health degree of the wind turbine generator based on the obtained optimal characteristic data of the wind turbine generator. According to the invention, when the health degree of the wind turbine generator is evaluated, the state performance of the wind turbine generator in a period of historical time is considered, and the current state identification and the future state development trend change of the wind turbine generator are considered. The current state and future trend of the whole unit are understood and mastered macroscopically, and the comprehensive management of the asset running condition is facilitated.
Correspondingly, in other embodiments of the invention, a wind turbine health assessment system, equipment and medium are provided.
Example 1
As shown in fig. 1, the method for evaluating health degree of a wind turbine provided in this embodiment mainly includes data acquisition, data preprocessing, evaluation of health degree of a wind turbine, decision assistance and resource management, and specifically includes the following steps:
1) data acquisition and preprocessing: and preprocessing the acquired original operation data of the wind turbine generator to obtain the optimal characteristic data of the wind turbine generator.
Specifically, the acquired wind turbine generator operation data includes Sensor Data (SD) and Event Data (ED). The SD is measured data of a sensor installed on the wind turbine generator, and comprises vibration data, temperature, pressure, humidity, current, voltage and the like. The ED includes events occurring on the wind turbine components, such as faults, damages, replacements, etc., and events performed by service technicians, such as information on maintenance, repair, cleaning, and adding lubricating oil, etc., and further includes oil sample detection data, etc.
The method for preprocessing the original operation data of the wind turbine generator is a technology known by the technical personnel in the field, and the invention is not described herein again.
2) Evaluating the health degree of the wind turbine generator: and quantitatively evaluating the health degree of the wind turbine generator based on the obtained optimal characteristic data of the wind turbine generator.
Specifically, the method comprises the following steps:
2.1) establishing a health degree evaluation system.
As shown in fig. 2, in this embodiment, the established health degree evaluation system includes a statistical index system for counting states of the wind turbine generator in a preset historical time period and a trend index system for identifying a current state of the wind turbine generator and predicting a fault occurrence condition in a future time period. In a health degree evaluation system, the more indexes are selected, the better the indexes are, the more typical indexes which can reflect the state of equipment are selected as much as possible, and the testability, completeness, independence, objectivity, sensitivity and consistency of each index are ensured.
2.1.1) statistical index System
The statistical index system is used for quantitatively analyzing whether the equipment runs healthily or not within a period of historical time and comprises two aspects of wind turbine generator reliability and real output evaluation.
(ii) reliability
The reliability of the wind turbine generator is evaluated by the failure frequency and the Mean Time To Repair (MTTR). The lower the failure frequency is, the shorter the average failure time is, which indicates that the reliability of the wind turbine generator is higher.
② real output
The real output condition of the wind turbine is evaluated by the Power-based availability (PBA). The higher the energy availability, the better the real output condition of the wind turbine generator.
2.1.2) Trend indicator System
The trend index system is used for quantitatively analyzing whether the equipment is in a healthy running state at present and in a period of time in the future, and a wind turbine running state identification model and a fault early warning model are established by a big data mining method, so that the healthy running state of the wind turbine at present and in a period of time in the future can be estimated. The trend index system mainly considers three aspects: performance degradation identification, fault early warning, and sensor anomalies.
Performance degradation recognition
The performance degradation identification is an evaluation of the degree of performance degradation of the actual power generation capacity of the wind power plant as compared to the expected normal power generation capacity. The performance degradation does not cause abnormal alarm and shutdown of the wind turbine, but the actual power generation performance degradation causes power generation loss, which is specifically represented by wind power curve deviation, namely, the actual power generation capacity is reduced compared with the expected normal power generation capacity at the same wind speed.
② fault early warning
The fault early warning is that according to the running rule of the equipment or the possibility precursor obtained by observation, before the equipment really breaks down, the abnormal condition of the equipment is forecasted in time, and corresponding measures such as arranging and repairing and maintaining the equipment, preparing spare parts and the like are taken, so that the loss caused by the equipment failure is reduced to the maximum extent.
③ abnormality of sensor
The sensor abnormality is caused by sensor electrical signal abnormality, communication failure and the like, and time sequence data shows the phenomena of out-of-limit, dead value, fluctuation range abnormality and the like.
And 2.2) calculating to obtain the complete machine health degree of the wind turbine generator based on the established health degree evaluation system and the acquired optimal characteristic data of the wind turbine generator.
The method comprises the following steps:
2.2.1) calculating to obtain each index value in the health degree evaluation system based on the acquired optimal characteristic data of the wind turbine generator and standardizing.
Various indexes in the health degree evaluation system are firstly scored, because different evaluation indexes often have different dimensions and dimension units, the data analysis result is influenced under the condition, and in order to eliminate the dimension influence among the indexes, the different evaluation indexes are standardized to a [0,100] interval according to the scoring rule so as to solve the comparability among the data indexes.
2.2.2) calculating to obtain the health degree of the whole machine based on the preset weight coefficient and the normalized index value.
The calculation formula of the whole health degree H is as follows:
wherein S is i Scoring the ith index; w i Is the ith index weight.
And evaluating the overall health degree of the fan according to different requirements, wherein the index weight modes are different. And various index weight modes are given through expert thinking, so that corresponding evaluation schemes are provided for different health evaluation requirements.
3) Visual display: and visually displaying the obtained health degree quantitative evaluation result of the wind turbine generator through a human-computer interaction interface.
4) Auxiliary decision and resource management: and finding out the problem set according to the health degree quantitative evaluation result of the health group of the wind turbine generator, searching and positioning a problem source through the tree diagram, and providing reasonable suggestions for arranging spare parts and adopting active maintenance activities for the wind power plant.
Example 2
For better understanding of the present invention, the present embodiment selects a 5-ten thousand kW wind farm operating for 11 years as an example for calculating the health degree.
As shown in fig. 3, in this embodiment, a set of weight modes is given for assisting decision and resource management according to needs, and the trend index is used for identifying the current state of the wind turbine and early warning the future state of the wind turbine, so that the weight of the trend index system is 0.8, the weight of the statistical index system is 0.2, the overall health of 53 wind turbines in an old wind farm is calculated, the full score of each wind turbine is 100, the higher the score is, the healthier the wind turbine is, and the overall health scores of the wind turbines No. 4, 10 and 24 are obviously lower through the transverse comparison among the wind turbines.
As shown in fig. 4, a tree diagram of the problem unit No. 4 is obtained according to a health degree evaluation system, and is used for problem tracing, and by drilling downwards, it is finally found that zero errors exist in the wind vane of the problem unit No. 4, the power generation performance of the unit is reduced, the energy availability is low, and the unit is in a sub-health operation state. To address this issue, a wind farm recommendation is given: and (4) zero offset of the wind vane, and tower climbing correction is recommended. And the wind turbine generator 4 is inspected by a wind power plant maintainer, and the wind turbine generator is found to have the problem of zero offset of a wind vane and is corrected. After the correction is completed, the health degree of the wind turbine generator is recovered to be normal, and the effectiveness and the practicability of the health degree evaluation system provided by the invention are verified.
Example 3
The embodiment 1 provides a wind turbine health degree evaluation method, and correspondingly, the embodiment provides a wind turbine health degree evaluation system. The system provided by this embodiment may implement the method for evaluating health degree of a wind turbine generator in embodiment 1, and the system may be implemented by software, hardware, or a combination of software and hardware. For example, the system may comprise integrated or separate functional modules or functional units to perform the corresponding steps in the methods of embodiment 1. Since the system of this embodiment is substantially similar to the method embodiment, the description process of this embodiment is relatively simple, and reference may be made to part of the description of embodiment 1 for relevant points.
The health degree evaluation system for the wind turbine generator provided by the embodiment comprises:
the data acquisition and preprocessing module is used for preprocessing the acquired original operation data of the wind turbine generator to obtain optimal characteristic data of the wind turbine generator;
the health degree evaluation module of the wind turbine generator is used for quantitatively evaluating the health degree of the wind turbine generator based on the obtained optimal characteristic data of the wind turbine generator;
the visual display module is used for visually displaying the obtained health degree quantitative evaluation result of the wind turbine generator through a human-computer interaction interface;
and the auxiliary decision and resource management module is used for arranging spare parts and taking active maintenance activities to give reasonable suggestions according to the obtained health degree quantitative evaluation result of the health group of the wind turbine generator.
Example 4
This embodiment provides a processing device corresponding to the method for evaluating health of a wind turbine generator set provided in embodiment 1, where the processing device may be a processing device for a client, such as a mobile phone, a notebook computer, a tablet computer, a desktop computer, and the like, to execute the method of embodiment 1.
The processing equipment comprises a processor, a memory, a communication interface and a bus, wherein the processor, the memory and the communication interface are connected through the bus so as to complete mutual communication. The memory stores a computer program capable of running on the processor, and the processor executes the wind turbine health assessment method provided by embodiment 1 when running the computer program.
In some embodiments, the Memory may be a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory, such as at least one disk Memory.
In other embodiments, the processor may be various general-purpose processors such as a Central Processing Unit (CPU), a Digital Signal Processor (DSP), and the like, and is not limited herein.
Example 5
The wind turbine health assessment method according to embodiment 1 may be embodied as a computer program product, and the computer program product may include a computer readable storage medium on which computer readable program instructions for executing the wind turbine health assessment method according to embodiment 1 are loaded.
The computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any combination of the foregoing.
It should be noted that the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s).
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
The above embodiments are only used for illustrating the present invention, and the structure, connection mode, manufacturing process, etc. of the components may be changed, and all equivalent changes and modifications performed on the basis of the technical solution of the present invention should not be excluded from the protection scope of the present invention.
Claims (10)
1. A health degree assessment method for a wind turbine generator is characterized by comprising the following steps:
preprocessing the acquired original operation data of the wind turbine generator to obtain optimal characteristic data of the wind turbine generator;
based on the obtained optimal characteristic data of the wind turbine generator, carrying out quantitative evaluation on the health degree of the wind turbine generator;
and visually displaying the obtained health degree quantitative evaluation result of the wind turbine generator, and outputting an evaluation suggestion.
2. The wind turbine generator health assessment method according to claim 1, characterized in that: the obtained original operation data of the wind turbine generator comprises the following steps: sensor data and event data, the sensor data including vibration data, temperature, pressure, humidity, current, voltage; the event data includes events occurring on the wind turbine components and events performed by service technicians.
3. The wind turbine generator health assessment method according to claim 1, characterized in that: the method for quantitatively evaluating the health degree of the wind turbine generator based on the obtained optimal characteristic data of the wind turbine generator comprises the following steps:
establishing a health degree evaluation system;
and calculating to obtain the complete machine health degree of the wind turbine generator based on the established health degree evaluation system and the acquired optimal characteristic data of the wind turbine generator.
4. The wind turbine generator health assessment method according to claim 3, characterized in that: the health degree evaluation system comprises a statistical index system and a trend index system;
the statistical index system comprises reliability and real output indexes;
the trend index system comprises performance degradation identification, fault early warning and sensor abnormal indexes.
5. The wind turbine generator health assessment method according to claim 3, characterized in that: the method for calculating the complete machine health degree of the wind turbine generator based on the established health degree evaluation system and the collected optimal characteristic data of the wind turbine generator comprises the following steps:
calculating to obtain each index value in a health degree evaluation system based on the acquired optimal characteristic data of the wind turbine generator and standardizing;
and calculating to obtain the health degree of the whole machine based on the preset weight coefficient and the normalized index value.
6. The wind turbine generator health assessment method according to claim 3, characterized in that: the calculation formula of the whole health degree is as follows:
wherein S is i Scoring the ith index; w i Is the ith index weight.
7. The wind turbine generator health assessment method according to claim 1, characterized in that: the method for visually displaying the obtained quantitative evaluation result of the health degree of the wind turbine generator and outputting the evaluation suggestion comprises the following steps of:
finding out a problem wind turbine generator according to the obtained health degree quantitative evaluation result of the health group of the wind turbine generator;
and obtaining a tree diagram corresponding to the problem wind turbine generator according to the health degree evaluation system, searching and positioning a problem source, and giving suggestions to arrangement of spare parts and maintenance activities of the wind power plant.
8. A health degree evaluation system of a wind turbine generator is characterized by comprising:
the data acquisition module is used for preprocessing the acquired original operation data of the wind turbine generator to obtain the optimal characteristic data of the wind turbine generator;
the health degree evaluation module is used for quantitatively evaluating the health degree of the wind turbine generator based on the obtained optimal characteristic data of the wind turbine generator;
and the result output module is used for visually displaying the obtained health degree quantitative evaluation result of the wind turbine generator and outputting an evaluation suggestion.
9. A processing device comprising at least a processor and a memory, the memory having stored thereon a computer program, characterized in that the processor executes, when executing the computer program, the steps of the wind turbine health assessment method according to any of claims 1 to 7.
10. A computer storage medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to implement the steps of the wind turbine health assessment method according to any one of claims 1 to 7.
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| CN115564298A (en) * | 2022-10-29 | 2023-01-03 | 北京远舢智能科技有限公司 | Production line equipment health degree evaluation method and system, intelligent terminal and storage medium |
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