CN113761713A - Method, device and system for simulating operation impact load of wind generating set - Google Patents
Method, device and system for simulating operation impact load of wind generating set Download PDFInfo
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Abstract
The invention discloses a method, a device and a system for simulating an operation impact load of a wind generating set. The method comprises the following steps: acquiring historical fault data of the wind generating set; processing the historical fault data to obtain the shutdown times of the wind power generation set at different fault levels; determining a mathematical model coefficient value of the wind generating set according to the environmental information of the wind power plant and the attribute information of the fan; and determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times. By using the method, the operation impact load of the wind generating set can be effectively simulated, operation and maintenance personnel can master the operation state of the wind generating set, and the danger of major equipment accidents is reduced.
Description
Technical Field
The embodiment of the invention relates to the technical field of wind power generation, in particular to a method, a device and a system for simulating a running impact load of a wind generating set.
Background
The wind generating set is a high-technology intensive product which absorbs wind energy through blades, converts the wind energy into rotating mechanical energy of a wind wheel, converts the mechanical energy into electric energy through a generator and inputs the electric energy into a power grid. The wind turbine generator system is required to bear loads generated by alternating stress in the operation process.
The load on the wind generating set mainly comprises the pneumatic thrust of the incoming wind, the inertia force and the self structural force acting on the blades. For a large wind generating set, except for the pneumatic load generated by blades, in the operation process of the wind generating set, the fluctuation of the load of the set structure and components can be caused by actions such as braking, yawing, variable pitch, net dropping and the like, so that how to determine the operation impact load of the wind generating set is a technical problem to be solved urgently at present.
Disclosure of Invention
The embodiment of the invention provides a method, a device and a system for simulating the operation impact load of a wind generating set, which can effectively simulate the operation impact load of the wind generating set, help operation and maintenance personnel to master the operation state of the wind generating set and reduce the risk of major equipment accidents.
In a first aspect, an embodiment of the present invention provides a method for simulating an operation impact load of a wind turbine generator system, including:
acquiring historical fault data of the wind generating set;
processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels;
determining a mathematical model coefficient value of the wind generating set according to the environmental information of the wind power plant and the attribute information of the fan;
and determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
In a second aspect, an embodiment of the present invention further provides a device for simulating an operational impact load of a wind turbine generator system, including:
the acquisition module is used for acquiring historical fault data of the wind generating set;
the processing module is used for processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels;
the first determination module is used for determining the mathematical model coefficient value of the wind generating set according to the wind power plant environment information and the fan attribute information;
and the second determination module is used for determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
In a third aspect, an embodiment of the present invention further provides a computing server, including:
one or more processors;
storage means for storing one or more programs;
the one or more programs are executed by the one or more processors to cause the one or more processors to implement the method of simulating a running impact load as described in any embodiment of the invention.
In a fourth aspect, embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for simulating an operational impact load according to any of the embodiments of the present invention.
In a fifth aspect, an embodiment of the present invention further provides a monitoring system for simulating an operation impact load of a wind turbine generator system, including: the system comprises a database server, a calculation server and a website server, wherein the calculation server is respectively connected with the database server and the website server;
the database server is used for acquiring historical fault data of the wind generating set and sending the historical fault data to the computing server;
the calculation server is used for determining the total simulated operation impact load of the wind generating set based on the historical fault data and sending the total simulated operation impact load to the website server;
and the website server is used for displaying the total simulated operation impact load to a user through a user browser so as to realize the monitoring of the user on the simulated operation impact load of the wind generating set.
The embodiment of the invention provides a method, a device and a system for simulating an operation impact load of a wind generating set, which comprises the steps of firstly, acquiring historical fault data of the wind generating set; then processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels; determining a mathematical model coefficient value of the wind generating set according to the environmental information of the wind power plant and the attribute information of the fan; and finally, determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times. By utilizing the technical scheme, the operation impact load of the wind generating set can be effectively simulated, operation and maintenance personnel can master the operation state of the wind generating set, and the danger of major equipment accidents is reduced.
Drawings
Fig. 1 is a schematic flow chart of a method for simulating an operational impact load of a wind turbine generator system according to a first embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for simulating an operational impact load of a wind turbine generator system according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a device for simulating an operational impact load of a wind turbine generator system according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a monitoring system for simulating an operation impact load of a wind turbine generator system according to a fourth embodiment of the present invention;
fig. 5 is a scene schematic diagram of a monitoring system for simulating an operation impact load of a wind turbine generator system according to a fourth embodiment of the present invention;
fig. 6 is a schematic structural diagram of a computing server according to a fifth embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and the embodiments of the present invention are illustrative only and are not intended to limit the scope of the present invention.
It should be understood that the various steps recited in the method embodiments of the present invention may be performed in a different order and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the invention is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present invention are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in the present invention are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that reference to "one or more" unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present invention are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Example one
Fig. 1 is a schematic flow chart of a method for simulating an operational impact load of a wind turbine generator system according to an embodiment of the present invention, where the method is applicable to a situation of simulating an operational impact load of a wind turbine generator system, and the method may be performed by an apparatus for simulating an operational impact load, where the apparatus may be implemented by software and/or hardware, and is generally integrated on a computing server, and the computing server is one of the servers.
As shown in fig. 1, a method for simulating an operational impact load of a wind turbine generator system according to a first embodiment of the present invention includes the following steps:
and S110, acquiring historical fault data of the wind generating set.
The number of the wind generating sets can be multiple, and the number of the wind generating sets is not particularly limited. The historical fault data is fault data generated when the wind generating set actually operates in any time period before the current time, and for example, historical fault data in one year can be obtained in the step. The historical fault data may include a wind turbine generator set's machine number, fault code, fault description, fault start time, fault end time, and fault class. Wherein the current time can be regarded as the time of the current simulated operation impact load.
In this embodiment, the method for obtaining the historical fault Data of the wind turbine generator system is not limited, And the historical fault Data of the wind turbine generator system may be collected in any one method, for example, the historical fault Data may be derived from a Supervisory Control And Data Acquisition (SCADA) system in a wind farm, And the derivation time period may be freely selected, And the historical fault Data of one year may be derived by general selection.
It should be noted that each wind turbine generator set has corresponding historical fault data, and the historical fault data corresponding to each wind turbine generator set can be correspondingly derived from the wind farm SCADA system.
And S120, processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels.
In this embodiment, processing the historical fault data may include performing data cleansing on the historical fault data to check the validity of the data; screening effective historical fault data to screen out a first fault occurring in the same time period; and counting the shutdown times of each shutdown level of the wind generating set according to the fault levels in the historical fault data table. Wherein, the data cleaning comprises checking data consistency and processing invalid values and missing values.
In the embodiment, a historical fault data table can be obtained by performing data cleaning and statistics on the number, the fault code, the fault description, the fault start time, the fault end time and the fault level data of the wind generating set in the historical fault data.
Table 1 is a historical fault data table provided in the first embodiment of the present invention, as shown in table 1, table 1 records historical fault data of a wind turbine generator set with a fan number of 1 in 1 month in 2020, and the first fault occurring in the corresponding time period of the wind turbine generator set in 1 month in 2020 includes a safety chain fault, a hydraulic fault, a pitch system fault, and a yaw fault. For example, the first fault corresponding to the first wind generating set from 33 point 2 at 1/16/2/2021 to 35 point 2 at 1/16/2/2021 is a safety chain fault, the corresponding fault code is 8007, and the fault level corresponding to the safety chain fault is emergency shutdown.
Blower fan number | Fault code | Description of faults | Time of failure onset | End of fault time | Failure class |
1 | 800070 | Failure of safety chain | 2020/1/9 11:08 | 2020/1/9 11:08 | Emergency shutdown |
1 | 800070 | Failure of safety chain | 2020/1/11 8:07 | 2020/1/11 8:07 | Emergency shutdown |
1 | 800070 | Failure of safety chain | 2020/1/16 2:33 | 2020/1/16 2:35 | Emergency shutdown |
1 | 50030 | Hydraulic breakdown | 2020/1/17 20:18 | 2020/1/17 20:18 | Quick stop |
1 | 300709 | Pitch system failure | 2020/1/20 5:30 | 2020/1/20 5:30 | Emergency shutdown |
1 | 800070 | Failure of safety chain | 2020/1/20 7:46 | 2020/1/20 7:47 | Emergency shutdown |
1 | 60010 | Yaw fault | 2020/1/21 10:38 | 2020/1/21 10:40 | Normal shutdown |
1 | 80070 | Failure of safety chain | 2020/1/22 14:28 | 2020/1/22 14:28 | Emergency shutdown |
TABLE 1
It should be further explained that table 1 only records the historical fault data table corresponding to the wind generating set with the fan number 1, and the wind generating set with each fan number may correspond to one historical fault data table. And counting the historical fault data table corresponding to the wind generating set of each fan number to obtain the shutdown times of different shutdown grades of the wind generating set of each fan number. The shutdown levels may include, among others, a normal shutdown, a fast shutdown, and an emergency shutdown.
Table 2 is a statistical table of the shutdown level failure times of the wind turbine generator system, and table 2 can visually display the normal shutdown times, the rapid shutdown times and the emergency shutdown times corresponding to the wind turbine generator systems with different fan numbers.
TABLE 2
And S130, determining a mathematical model coefficient value of the wind generating set according to the wind power plant environment information and the fan attribute information.
The wind power plant environment information can be understood as information of a wind power plant site environment where the wind generating set is located. The wind turbine attribute information may be understood as attribute information of the wind turbine generator system, and the wind turbine attribute information may include a wind turbine tower height, a blade length, and a wind turbine capacity.
In the embodiment, the electric field coefficient value and the shutdown coefficient value of the wind generating set are determined according to the wind farm environment information and the fan attribute information. The electric field coefficient value can be a coefficient value corresponding to a complete machine mathematical model established according to the wind power plant environment, and the shutdown coefficient value can be a coefficient value corresponding to a complete machine pneumatic model established according to the height of a tower barrel of the fan, the length of the blade and the capacity of the fan.
Specifically, the mathematical model coefficient value includes an electric field coefficient value and a shutdown coefficient value, and the mathematical model coefficient value of the wind turbine generator system is determined according to the wind farm environment information and the fan attribute information, and includes: determining a corresponding electric field coefficient value of the wind generating set according to the environmental information of the wind power plant; and determining a shutdown coefficient value corresponding to the wind generating set according to the fan attribute information.
In this embodiment, the method for determining the electric field coefficient value corresponding to the wind generating set according to the wind farm environment information may be as follows: and determining the type of the wind power plant according to the environment information of the wind power plant, and determining the electric field coefficient according to the type of the wind power plant. The mode of determining the corresponding shutdown coefficient value of the wind generating set can be that the corresponding shutdown coefficient value is obtained through table lookup according to the diameter of the wind wheel of the wind generating set.
Further, the determining a wind farm coefficient value corresponding to the wind generating set according to the wind farm environment information includes: determining the type of the wind power plant where the wind generating set is located according to the environment information of the wind power plant; and obtaining a wind power plant coefficient value corresponding to the wind generating set according to the wind power plant type.
The wind farm types can include plain wind farms, offshore wind farms, hilly wind farms, and mountain wind farms, among others. In this embodiment, it is not limited in which way the wind farm type where the wind turbine generator set is located is determined, nor how to obtain the corresponding wind farm coefficient according to the wind farm type. If the type of the wind power plant is a plain wind power plant, the corresponding wind power plant coefficient is 1; if the type of the wind power plant is an offshore wind power plant, the corresponding wind power plant coefficient is 1.5; if the type of the wind power plant is a hill wind power plant, the corresponding wind power plant coefficient is 2; and if the type of the wind power plant is a mountainous wind power plant, the corresponding wind power plant coefficient is 3.
Further, the shutdown coefficient value comprises a normal shutdown coefficient value, a rapid shutdown coefficient value and an emergency shutdown coefficient value, the fan attribute information comprises a fan tower height, a fan blade length and a fan capacity, and the shutdown coefficient value is acquired in a manner that: determining the diameter of a wind wheel of a wind generating set by inquiring a parameter table of the wind generating set; and determining a normal shutdown coefficient value, a quick shutdown coefficient value and an emergency shutdown coefficient value corresponding to each wind generating set by inquiring a shutdown coefficient table according to the diameter of the wind wheel.
Table 3 is a parameter table of the wind turbine generator system according to the first embodiment of the present invention, as shown in table 3, main parameters of the wind turbine generator system in a certain wind farm are recorded in table 3, and the main parameters include a model of the wind turbine generator system, a rated power of the wind turbine generator system, a height of a hub, a cut-in wind speed, a rated wind speed, a cut-out wind speed, a maximum wind speed, a diameter of a wind wheel, and a model version of remote monitoring software.
TABLE 3
It should be further explained that each wind generating set can correspond to a wind generating set parameter table, and the wind turbine diameter of the wind generating set is recorded in the wind generating set parameter table corresponding to each wind generating set.
Table 4 is a shutdown coefficient table according to the first embodiment of the present invention, and as shown in table 4, the normal shutdown coefficient value, the fast shutdown coefficient value, and the emergency shutdown coefficient value corresponding to different wind wheel diameters are recorded in table 4.
Serial number | Diameter of wind wheel | Normal shutdown coefficient value | Fast shutdown coefficient value | Value of emergency shutdown coefficient |
1 | 77 | 1.16 | 14.0 | 93 |
2 | 82 | 1.32 | 15.8 | 105 |
3 | 87 | 1.48 | 17.8 | 119 |
4 | 93 | 1.70 | 20.0 | 135 |
5 | 97 | 1.85 | 22.2 | 148 |
6 | 100 | 1.96 | 23.5 | 157 |
7 | 105 | 2.16 | 25.9 | 173 |
8 | 110 | 2.37 | 28.5 | 190 |
9 | 116 | 2.64 | 31.7 | 211 |
10 | 120 | 2.83 | 33.9 | 226 |
11 | 140 | 3.85 | 46.2 | 308 |
TABLE 4
The values of normal shutdown coefficients, fast shutdown coefficients and emergency shutdown coefficients corresponding to different diameters of the wind turbine can be inquired through the table 4. Illustratively, if the wind wheel diameter is 93m, the corresponding normal shutdown coefficient value is 1.7, the fast shutdown coefficient value is 20, and the emergency shutdown coefficient value is 135.
And S140, determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
The shutdown times can be shutdown times corresponding to different shutdown levels, and the shutdown times can include normal shutdown times, rapid shutdown times and emergency shutdown times.
In this embodiment, based on the mathematical model coefficient value and the shutdown number, the method for determining the total simulated operation impact load of each wind turbine generator set may be: determining a normal shutdown simulation load according to the normal shutdown times and the normal shutdown coefficient value; determining a rapid shutdown simulation load according to the rapid shutdown times and the rapid shutdown coefficient value; determining an emergency stop simulation load according to the emergency stop times and the emergency stop coefficient value; and determining the total simulated operation impact load according to the normal shutdown simulation load, the rapid shutdown simulation load, the emergency shutdown simulation load and the electric field coefficient value.
Further, the different levels of shutdown times include normal shutdown times, rapid shutdown times and emergency shutdown times, and the determining of the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the different levels of shutdown times includes: determining the product of the number of normal stops and the normal stop coefficient value as a normal stop simulation load; determining the product of the rapid shutdown times and the rapid shutdown coefficient value as a rapid shutdown simulation load; determining the product of the emergency shutdown times and the emergency shutdown coefficient value as the determined emergency shutdown simulation load; and determining the product of the total shutdown simulation load and the electric field coefficient value as a total simulation operation impact load, wherein the total shutdown simulation load is the sum of the normal shutdown simulation load, the rapid shutdown simulation load and the emergency shutdown simulation load.
Illustratively, the total simulated operational impact load ═ α (normal shutdown simulated load + rapid shutdown simulated load + emergency shutdown simulated load); wherein,
normal shutdown simulation load is the normal shutdown times and the normal shutdown coefficient value;
a rapid shutdown simulation load (PRF) — number of rapid shutdown times — (rapid shutdown coefficient value);
emergency stop simulation load (PRE) ═ emergency stop times × emergency stop coefficient value.
Table 5 shows the wind turbine shutdown simulation load table provided in the first embodiment of the present invention, and as shown in table 5, the wind turbine generator sets of different wind turbine numbers correspond to the normal shutdown simulation load, the fast shutdown simulation load, the emergency shutdown simulation load, and the total simulated operation impact load.
TABLE 5
The method for simulating the operation impact load of the wind generating set provided by the embodiment of the invention comprises the steps of firstly, acquiring historical fault data of the wind generating set; then processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels; determining a mathematical model coefficient value of the wind generating set according to the environmental information of the wind power plant and the attribute information of the fan; and finally determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times. By the method, the operation impact load of the wind generating set can be effectively simulated, operation and maintenance personnel can master the operation state of the wind generating set, and the danger of major equipment accidents is reduced.
Example two
Fig. 2 is a schematic flow chart of a method for simulating an operation impact load of a wind turbine generator system according to a second embodiment of the present invention, and the second embodiment is optimized based on the above embodiments. In this embodiment, the processing the historical fault data to obtain the shutdown times of the wind power generation group at different levels is further embodied as: checking the validity of the historical fault data and determining valid historical fault data; screening out first fault data of the wind generating set in a plurality of preset time periods from the effective historical fault data; generating a historical fault data table according to each initial fault data, wherein the historical fault data table comprises shutdown grades corresponding to each initial fault data; and counting the times of different shutdown grades in the historical fault data table to obtain the shutdown times of the wind generating set at different shutdown grades. Please refer to the first embodiment for a detailed description of the present embodiment.
As shown in fig. 2, a method for simulating an operational impact load of a wind turbine generator system according to a second embodiment of the present invention includes the following steps:
and S210, acquiring historical fault data of the wind generating set.
S220, checking the validity of the historical fault data and determining effective historical fault data.
In the embodiment, the consistency of the historical fault data is checked, and invalid values and missing values are processed to obtain valid historical data.
S230, screening out first-occurring fault data of the wind generating set in a plurality of preset time periods from the effective historical fault data.
In this embodiment, the valid historical fault data may include the wind turbine generator set's machine number, fault code, fault description, fault start time, fault end time, and fault class data. The preset time period may include a fault start time and a fault end time, and the first fault data may be understood as the first fault data occurring within a certain preset time period.
And S240, generating a historical fault data table according to each initial fault data, wherein the historical fault data table comprises fault grades corresponding to each initial fault data.
In this embodiment, the historical fault data table records the fault start time, the fault end time, the fault description and the corresponding fault level corresponding to the first-sent fault data. The failure levels may include emergency shutdown, rapid shutdown, and normal shutdown.
And S250, counting the occurrence frequency of different fault levels in the historical fault data table to obtain the shutdown frequency of the wind generating set at different fault levels.
According to the historical fault data table, the times of emergency shutdown, the times of normal shutdown and the times of rapid shutdown can be counted.
And S260, determining a mathematical model coefficient value of the wind generating set according to the wind power plant environment information and the fan attribute information.
And S270, determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
The method for simulating the operation impact load of the wind generating set provided by the embodiment of the invention embodies the purpose that the stop times of the wind generating set at different levels are obtained by processing the historical fault data. By the method, operation and maintenance personnel can be helped to master the running state of the wind generating set, the condition that parts such as a main shaft bearing, a gear box, a tower bolt of a front frame of an engine room and the like are possibly damaged is predicted, and the risk of major equipment accidents is reduced by reducing high-level shutdown faults and inspection tests.
EXAMPLE III
Fig. 3 is a schematic structural diagram of an apparatus for simulating an operational impact load of a wind turbine generator system according to a third embodiment of the present invention, where the apparatus is applicable to a situation of simulating an operational impact load of a wind turbine generator system, and the apparatus may be implemented by software and/or hardware and is generally integrated on a computing server.
As shown in fig. 3, the apparatus includes: an acquisition module 310, a processing module 320, a first determination module 330, and a second determination module 340.
An obtaining module 310, configured to obtain historical fault data of the wind turbine generator system;
the processing module 320 is used for processing the historical fault data to obtain the shutdown times of the wind power generation set at different fault levels;
the first determining module 330 is configured to determine a mathematical model coefficient value of the wind turbine generator set according to the wind farm environment information and the fan attribute information;
and the second determining module 340 is used for determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
In the embodiment, the device firstly acquires historical fault data of the wind generating set through an acquisition module 310; then, the historical fault data is processed through a processing module 320, and the shutdown times of the wind power generation set at different fault levels are obtained; then, determining a mathematical model coefficient value of the wind generating set through a first determining module 330 according to the environmental information of the wind power plant and the attribute information of the wind turbine; and finally, determining the total simulated operation impact load of each wind generating set through a second determination module 340 based on the mathematical model coefficient value and the shutdown times.
The embodiment provides a device for simulating wind generating set operation impact load, can effectively simulate wind generating set's operation impact load, helps operation and maintenance personnel to master wind generating set's running state, reduces the danger of taking place major equipment accident.
Further, the processing module 320 is specifically configured to: checking the validity of the historical fault data and determining valid historical fault data; screening out first fault data of the wind generating set in a plurality of preset time periods from the effective historical fault data; generating a historical fault data table according to each initial fault data, wherein the historical fault data table comprises fault grades corresponding to each initial fault data; and counting the occurrence times of different fault levels in the historical fault data table to obtain the shutdown times of the wind generating set at different fault levels.
Further, the mathematical model coefficient values include a wind farm coefficient value and a shutdown coefficient value, and the first determining module 330 is specifically configured to: determining a wind power plant coefficient value corresponding to the wind generating set according to the wind power plant environment information; and determining a shutdown coefficient value corresponding to the wind generating set according to the fan attribute information.
Further, the determining a wind farm coefficient value corresponding to the wind generating set according to the wind farm environment information includes: determining the type of the wind power plant where the wind generating set is located according to the environment information of the wind power plant; and obtaining a wind power plant coefficient value corresponding to the wind generating set according to the wind power plant type.
Further, the shutdown coefficient value comprises a normal shutdown coefficient value, a rapid shutdown coefficient value and an emergency shutdown coefficient value, the fan attribute information comprises a fan tower height, a fan blade length and a fan capacity, and the shutdown coefficient value is acquired in a manner that: determining the diameter of a wind wheel of a wind generating set by inquiring a parameter table of the wind generating set; and determining a normal shutdown coefficient value, a quick shutdown coefficient value and an emergency shutdown coefficient value corresponding to each wind generating set by inquiring a shutdown coefficient table according to the diameter of the wind wheel.
Further, the shutdown times of different levels include a normal shutdown time, a fast shutdown time, and an emergency shutdown time, and the second determining module 340 is specifically configured to: determining the product of the number of normal stops and the normal stop coefficient value as a normal stop simulation load; determining the product of the rapid shutdown times and the rapid shutdown coefficient value as a rapid shutdown simulation load; determining the product of the emergency shutdown times and the emergency shutdown coefficient value as the determined emergency shutdown simulation load; and determining the product of the total shutdown simulation load and the electric field coefficient value as a total simulation operation impact load, wherein the total shutdown simulation load is the sum of the normal shutdown simulation load, the rapid shutdown simulation load and the emergency shutdown simulation load.
The device for simulating the operation impact load of the wind generating set can execute the method for simulating the operation impact load of the wind generating set provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 4 is a schematic structural diagram of a system for monitoring an operational impact load of a simulated wind turbine generator system according to a fourth embodiment of the present invention, where the system is applicable to monitoring an operational impact load of a simulated wind turbine generator system, and the system may be implemented by software and/or hardware.
As shown in fig. 4, the system includes a database server 410, a computation server 420 and a website server 430, wherein the computation server 420 is connected to the database server 410 and the website server 430 respectively; the database server 410 is used for acquiring historical fault data of the wind generating set and sending the historical fault data to the computing server 420; the calculation server 420 is used for determining the total simulated operation impact load of the wind generating set based on the historical fault data and sending the total simulated operation impact load to the website server 430; and the website server 430 is configured to display the total simulated operation impact load to a user through a user-side browser, so as to enable the user to monitor the simulated operation impact load of the wind turbine generator system.
In this embodiment, the number of the wind generating sets is not particularly limited, and historical fault data corresponding to at least one wind generating set may be obtained.
For example, the database server 410 may derive historical fault data of the wind turbine generator set within the wind farm SCADA system and send the historical fault data of the wind turbine generator set to the calculation server so that the calculation server can obtain the historical fault data of the wind turbine generator set.
In the present embodiment, after receiving the historical fault data of the wind generating set sent by the database server 410, the calculation server 420 determines the total simulated operation impact load of the wind generating set based on the historical fault data. If historical fault data of a plurality of wind generating sets is received, the total simulated operation impact load of the corresponding generating set can be determined according to the historical fault data of each generating set.
Specifically, the method for determining the total simulated operation impact load of the wind turbine generator system based on the historical fault data may be as follows: processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels; determining a mathematical model coefficient value of the wind generating set according to the environmental information of the wind power plant and the attribute information of the fan; and determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
Further, the processing of the historical fault data to obtain the shutdown times of the wind power generation set at different levels includes: checking the validity of the historical fault data to determine valid historical fault data; screening first fault data of the wind generating set in a plurality of preset time periods from the effective historical fault data; generating a historical fault data table according to each initial fault data, wherein the historical fault data table comprises fault grades corresponding to each initial fault data; and counting the occurrence times of different fault levels in the historical fault data table to obtain the shutdown times of the wind generating set at different fault levels.
Further, the mathematical model coefficient value includes a wind farm coefficient value and a shutdown coefficient value, and the determining the mathematical model coefficient value of the wind turbine generator set according to the wind farm environment information and the fan attribute information includes: determining a wind power plant coefficient value corresponding to the wind generating set according to the wind power plant environment information; and determining a shutdown coefficient value corresponding to the wind generating set according to the fan attribute information.
Further, the determining a wind farm coefficient value corresponding to the wind generating set according to the wind farm environment information includes: determining the type of the wind power plant where the wind generating set is located according to the environment information of the wind power plant; and obtaining a wind power plant coefficient value corresponding to the wind generating set according to the wind power plant type.
Further, the shutdown coefficient value comprises a normal shutdown coefficient value, a rapid shutdown coefficient value and an emergency shutdown coefficient value, the fan attribute information comprises a fan tower height, a fan blade length and a fan capacity, and the shutdown coefficient value is acquired in a manner that: determining the diameter of a wind wheel of a wind generating set by inquiring a parameter table of the wind generating set; and determining a normal shutdown coefficient value, a quick shutdown coefficient value and an emergency shutdown coefficient value corresponding to each wind generating set by inquiring a shutdown coefficient table according to the diameter of the wind wheel.
Further, the different levels of shutdown times include normal shutdown times, rapid shutdown times and emergency shutdown times, and the determining of the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the different levels of shutdown times includes: determining the product of the number of normal stops and the normal stop coefficient value as a normal stop simulation load; determining the product of the rapid shutdown times and the rapid shutdown coefficient value as a rapid shutdown simulation load; determining the product of the emergency shutdown times and the emergency shutdown coefficient value as the determined emergency shutdown simulation load; and determining the product of the total shutdown simulation load and the electric field coefficient value as a total simulation operation impact load, wherein the total shutdown simulation load is the sum of the normal shutdown simulation load, the rapid shutdown simulation load and the emergency shutdown simulation load.
In this embodiment, after the calculation server 520 determines the total simulated operation impact load corresponding to the wind generating set, the total simulated operation impact load corresponding to the wind generating set may be sent to the website server 530, so that the website server 530 may display the total simulated operation impact load corresponding to the wind generating set to a user through a user-side browser, that is, the user may view the total simulated operation impact load corresponding to the wind generating set through the user-side browser, so that the user may monitor the result of the simulated operation impact load of each wind generating set.
According to the monitoring system for simulating the impact load of the wind generating set in the fourth embodiment of the invention, the total simulated operation impact load of the wind generating set is calculated by the calculation server 420, and the total simulated operation impact load of the wind generating set is displayed on the browser at the user end by the website server 430, so that the monitoring of the user on the impact load of the wind generating set in the simulated operation can be effectively realized.
Fig. 5 is a schematic view of a scene of a monitoring system for simulating an operational impact load of a wind turbine generator system according to a fourth embodiment of the present invention, and as shown in fig. 5, a database server is connected to a calculation server, and sends acquired historical fault data of the wind turbine generator system to the calculation server; after receiving historical fault data of the wind generating set, the calculation server can determine total simulated operation impact load of the wind generating set based on the historical fault data, and sends the total simulated operation impact load of the wind generating set to the web server, and the web server displays the total simulated operation impact load of the wind generating set to a user through a user browser.
EXAMPLE five
Fig. 6 is a schematic structural diagram of a computing server according to a fifth embodiment of the present invention. As shown in fig. 6, a computing server provided in the fifth embodiment of the present invention includes: one or more processors 61 and storage 62; the processor 61 in the computing server may be one or more, and one processor 61 is taken as an example in fig. 6; storage 62 is used to store one or more programs; the one or more programs are executed by the one or more processors 61, so that the one or more processors 61 implement the method for simulating the operation impact load of the wind generating set according to any one of the embodiments of the present invention.
The computing server may further include: an input device 63 and an output device 64.
The processor 61, the storage device 62, the input device 63 and the output device 64 in the computing server may be connected by a bus or other means, and fig. 6 illustrates an example of a connection by a bus.
The storage device 62 in the computing server is used as a computer readable storage medium for storing one or more programs, which may be software programs, computer executable programs, and modules, and program instructions/modules corresponding to the method for simulating wind generating set operation impact load according to one or two embodiments of the present invention (for example, the modules in the device for simulating wind generating set operation impact load shown in fig. 3 include an obtaining module 310, a processing module 320, a first determining module 330, and a second determining module 340). The processor 61 executes various functional applications and data processing of the computing server by running software programs, instructions and modules stored in the storage device 62, namely, the method for simulating the operation impact load of the wind generating set in the above method embodiment is realized.
The storage device 62 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the calculation server, and the like. Further, the storage device 62 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the storage device 62 may further include memory located remotely from the processor 61, which may be connected to the device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 63 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the computing server. The output device 64 may include a display device such as a display screen.
And, when the one or more programs included in the above-mentioned computing server are executed by the one or more processors 61, the programs perform the following operations:
acquiring historical fault data of the wind generating set;
processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels;
determining a mathematical model coefficient value of the wind generating set according to the environmental information of the wind power plant and the attribute information of the fan;
and determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
EXAMPLE five
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, is configured to perform a method for simulating an operational impact load of a wind turbine generator system, where the method includes:
acquiring historical fault data of the wind generating set;
processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels;
determining a mathematical model coefficient value of the wind generating set according to the environmental information of the wind power plant and the attribute information of the fan;
and determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
Optionally, the program, when executed by the processor, may be further configured to perform a method for simulating an operational impact load of a wind turbine generator system according to any embodiment of the present invention.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a flash Memory, an optical fiber, a portable CD-ROM, an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. A computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take a variety of forms, including, but not limited to: an electromagnetic signal, an optical signal, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, Radio Frequency (RF), etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for simulating an operational impact load of a wind turbine generator system, the method comprising:
acquiring historical fault data of the wind generating set;
processing the historical fault data to obtain the shutdown times of the wind power generation set at different shutdown levels;
determining a mathematical model coefficient value of the wind generating set according to the environmental information of the wind power plant and the attribute information of the fan;
and determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
2. The method of claim 1, wherein said processing said historical fault data to obtain a number of shutdowns of said wind power generation group at different levels comprises:
checking the validity of the historical fault data and determining valid historical fault data;
screening out first fault data of the wind generating set in a plurality of preset time periods from the effective historical fault data;
generating a historical fault data table according to each initial fault data, wherein the historical fault data table comprises fault grades corresponding to each initial fault data;
and counting the occurrence times of different fault levels in the historical fault data table to obtain the shutdown times of the wind generating set at different fault levels.
3. The method of claim 1, wherein the mathematical model coefficient values comprise a wind farm coefficient value and a shutdown coefficient value, and wherein determining the mathematical model coefficient values for the wind turbine generator set based on the wind farm environmental information and the wind turbine attribute information comprises:
determining a wind power plant coefficient value corresponding to the wind generating set according to the wind power plant environment information;
and determining a shutdown coefficient value corresponding to the wind generating set according to the fan attribute information.
4. The method of claim 3, wherein determining the wind farm coefficient value corresponding to the wind turbine generator set according to the wind farm environment information comprises:
determining the type of the wind power plant where the wind generating set is located according to the environment information of the wind power plant;
and obtaining a wind power plant coefficient value corresponding to the wind generating set according to the wind power plant type.
5. The method of claim 3, wherein the shutdown coefficient values include a normal shutdown coefficient value, a fast shutdown coefficient value, and an emergency shutdown coefficient value, the wind turbine attribute information includes a wind turbine tower height, a wind turbine blade length, and a wind turbine capacity, and the shutdown coefficient values are obtained by:
determining the diameter of a wind wheel of a wind generating set by inquiring a parameter table of the wind generating set;
and determining a normal shutdown coefficient value, a quick shutdown coefficient value and an emergency shutdown coefficient value corresponding to each wind generating set by inquiring a shutdown coefficient table according to the diameter of the wind wheel.
6. The method of claim 5, wherein the different levels of shutdown include a normal shutdown, a fast shutdown, and an emergency shutdown, and wherein determining the total simulated operational impact load for each wind turbine generator set based on the mathematical model coefficient values and the different levels of shutdown includes:
determining the product of the number of normal stops and the normal stop coefficient value as a normal stop simulation load;
determining the product of the rapid shutdown times and the rapid shutdown coefficient value as a rapid shutdown simulation load;
determining the product of the emergency shutdown times and the emergency shutdown coefficient value as the determined emergency shutdown simulation load;
and determining the product of the total shutdown simulation load and the electric field coefficient value as a total simulation operation impact load, wherein the total shutdown simulation load is the sum of the normal shutdown simulation load, the rapid shutdown simulation load and the emergency shutdown simulation load.
7. A device for simulating operation impact load of a wind generating set is characterized by comprising:
the acquisition module is used for acquiring historical fault data of the wind generating set;
the processing module is used for processing the historical fault data to obtain the shutdown times of the wind power generation set at different fault levels;
the first determination module is used for determining the mathematical model coefficient value of the wind generating set according to the wind power plant environment information and the fan attribute information;
and the second determination module is used for determining the total simulated operation impact load of each wind generating set based on the mathematical model coefficient value and the shutdown times.
8. A computing server, comprising:
one or more processors;
storage means for storing one or more programs;
the one or more programs are executable by the one or more processors to cause the one or more processors to perform the method of simulating operational impact loads of any of claims 1-6.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method of simulating a running impact load according to any one of claims 1 to 6.
10. A monitoring system for simulating the operation impact load of a wind generating set is characterized by comprising a database server, a calculation server and a website server, wherein the calculation server is respectively connected with the database server and the website server;
the database server is used for acquiring historical fault data of the wind generating set and sending the historical fault data to the computing server;
the calculation server is used for determining the total simulated operation impact load of the wind generating set based on the historical fault data and sending the total simulated operation impact load to the website server;
and the website server is used for displaying the total simulated operation impact load to a user through a user browser so as to realize the monitoring of the user on the simulated operation impact load of the wind generating set.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104810860A (en) * | 2015-02-06 | 2015-07-29 | 华北水利水电大学 | Power distribution method and power distribution device in wind power plant |
CN108074197A (en) * | 2016-11-11 | 2018-05-25 | 河北新天科创新能源技术有限公司 | The control method of fan trouble data analysis system |
CN108615086A (en) * | 2016-12-12 | 2018-10-02 | 北京金风科创风电设备有限公司 | The failure optimization method and device of wind power generating set |
CN112611584A (en) * | 2020-05-18 | 2021-04-06 | 北京金风慧能技术有限公司 | Fatigue failure detection method, device, equipment and medium for wind generating set |
CN112686403A (en) * | 2020-12-30 | 2021-04-20 | 福建海电运维科技有限责任公司 | Intelligent fan file operation and maintenance method and system |
-
2021
- 2021-08-05 CN CN202110896245.7A patent/CN113761713A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104810860A (en) * | 2015-02-06 | 2015-07-29 | 华北水利水电大学 | Power distribution method and power distribution device in wind power plant |
CN108074197A (en) * | 2016-11-11 | 2018-05-25 | 河北新天科创新能源技术有限公司 | The control method of fan trouble data analysis system |
CN108615086A (en) * | 2016-12-12 | 2018-10-02 | 北京金风科创风电设备有限公司 | The failure optimization method and device of wind power generating set |
CN112611584A (en) * | 2020-05-18 | 2021-04-06 | 北京金风慧能技术有限公司 | Fatigue failure detection method, device, equipment and medium for wind generating set |
CN112686403A (en) * | 2020-12-30 | 2021-04-20 | 福建海电运维科技有限责任公司 | Intelligent fan file operation and maintenance method and system |
Non-Patent Citations (1)
Title |
---|
燕妮;齐蓓;蒋程;: "考虑多因素影响的风电机组故障率计算方法", 电气应用, no. 09, 5 May 2015 (2015-05-05), pages 88 - 91 * |
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