An edge computing method and device suitable for online evaluation of a wind farm

Abstract

The application relates to an edge computing method and device suitable for online evaluation of a wind power plant, which comprises the following steps: S1, collecting voltage and current instantaneous values in real time; S2, performing simple calculation on the collected instantaneous values, and performing variable sampling rate caching on the instantaneous values and the simple calculation results in three different sampling rates according to needs; S3, performing feature quantity calculation and logic trigger recording based on the cached data in different sampling rates; and S4, performing communication transmission on the feature quantity calculation and logic trigger recording results. The application can comprehensively perceive key grid-connected performance information in wind turbine operation data, provide a data channel for a large amount of single-machine fault original data, improve the wind turbine state monitoring capability, be favorable to unit fault early warning and operation and maintenance, and support wind power plant grid-connected characteristic analysis and fault deduction, so that the application reduces the calculation amount of an upper online evaluation system, improves a control strategy, and improves the power grid friendliness.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy access and control technology, in particular to an edge computing method and device suitable for online evaluation of a wind farm. BACKGROUND

[0002] Under the background of building a new power system mainly based on new energy, new energy represented by wind power will continue to develop rapidly. Unlike traditional thermal power units, wind turbine has small inertia, serious power electronics, strong random fluctuation, and other characteristics, combined with small scale, multiple types and various access methods of power generation units, which requires real-time monitoring method to obtain wind power grid performance to serve the dispatching decision. The wind farm can use online evaluation system to monitor wind turbine and grid connection point online, and realize online evaluation of operation state and control margin.

[0003] The granted invention patent 201410773583.1 provides a wind farm grid connection characteristic online evaluation system, mainly including data communication unit, online evaluation algorithm module and function management module, based on real-time performance information of grid connection point and operation state signal of wind turbine, the evaluation of active power change rate, voltage deviation, voltage and frequency adaptability, active power regulation, reactive voltage regulation and low voltage ride through capability can be realized. Although the grid connection point information can reflect the real-time grid connection performance of the wind farm, the operation process of the wind turbine also contains a large amount of operation information, which not only helps to evaluate the real-time grid connection performance of the wind farm, but also can estimate the control margin, analyze and accurately locate the fault. Only collecting wind turbine state signal of grid connection point cannot provide sufficient basis for large-scale wind power consumption and power system dispatching.

[0004] The operation data of wind turbine is currently mainly sent to the supervisory control and data acquisition system (SCADA) through the optical fiber ring network by the main control system. On the one hand, the data is usually low-resolution second-level information, and mainly focuses on the healthy operation state of the wind turbine, and pays little attention to the grid connection performance. On the other hand, the voltage, current and power electrical quantity information required to be collected at the unit port has high resolution, up to 1kHz or more, and in the fault state, it is necessary to record and store the transient process. These data or information are difficult to upload under the current communication mode and bandwidth.

[0005] Therefore, there is no edge computing method and device in the current wind farm online evaluation method and system that can perceive the key grid connection information of wind turbine and solve the following problems

[0006] (1) It can perceive the key grid connection performance information in the wind turbine operation data, and meet the relevant standards;

[0007] (2) A large number of single machine fault original data cannot be uploaded. SUMMARY

[0008] In view of the deficiencies of the prior art, the present application provides an edge computing method and device suitable for online evaluation of a wind farm.

[0009] In a first aspect, the present application provides an edge computing method suitable for online evaluation of a wind farm, comprising the following steps:

[0010] Step S1: Real-time acquisition of voltage and current instantaneous values;

[0011] Step S2: Simple calculation of the acquired instantaneous values, and variable sampling rate caching of the instantaneous values and the results of the simple calculation at three different sampling rates as needed;

[0012] Step S3: Feature quantity calculation and logic triggered recording based on the cached data at different sampling rates;

[0013] Step S4: Communication transmission of the results of the feature quantity calculation and the logic triggered recording.

[0014] Further, the real-time acquisition in step S1 is the acquisition of three-phase voltage and three-phase current instantaneous values.

[0015] Further, the real-time acquisition in step S1 has a sampling rate of 10 kHz.

[0016] Further, the three different sampling rates in step S2 are 10 kHz, 2 kHz and 10 Hz.

[0017] Further, in step S2, the three-phase phase voltage and current effective values, the positive and negative sequence voltage and current effective values are obtained through the simple calculation, and the active power and reactive power are further calculated.

[0018] Further, the step S2 further comprises real-time communication transmission of the results of the simple calculation.

[0019] Further, the method of the simple calculation is to obtain the three-phase phase voltage and current effective values through a sliding window method, and to obtain the positive and negative sequence voltage and current effective values through a positive and negative sequence separation method.

[0020] Further, the feature quantity calculation of step S3 is based on the 10 kHz original value cache and the 2 kHz simple calculation result cache, and the logic triggered recording is based on the 10 kHz original value cache and the 2 kHz original value cache.

[0021] Further, the feature quantity calculation mainly includes power quality feature quantity calculation, grid adaptability feature quantity calculation, fault ride-through feature quantity calculation, power feature quantity calculation, and fast frequency and reactive voltage regulation response feature quantity calculation.

[0022] Furthermore, the power quality characteristic quantity calculation includes the average active power over 10 minutes, long-term flicker value, harmonic current, total harmonic distortion rate of current, and maximum value of interharmonic voltage.

[0023] Furthermore, the calculation of the power grid adaptability characteristics includes power grid frequency, unbalance, voltage deviation, and operating status.

[0024] Furthermore, the fault ride-through characteristic calculation includes high / low ride-through type flag, fault ride-through type flag, and voltage change amplitude.

[0025] Furthermore, the calculation of the electrical energy characteristic quantities includes the cumulative electricity consumption and the equivalent utilization hours.

[0026] Furthermore, the calculation of the rapid frequency and reactive power regulation response characteristics includes adjustment time and power change amplitude.

[0027] Furthermore, the characteristic calculation results are transmitted in real time at a sampling rate of 10Hz, and the logic-triggered waveform recording is transmitted in file format.

[0028] Furthermore, the communication transmission is based on Modbus TCP / IP for real-time uploading and on FTP functionality for file uploading.

[0029] Furthermore, the logic-triggered waveform recording includes manually triggered waveform recording and self-triggered waveform recording.

[0030] Furthermore, the triggering conditions for the self-triggered waveform recording include: voltage exceeding the limit and frequency exceeding the limit, requiring preset threshold values ​​for effective voltage amplitude and frequency change.

[0031] Secondly, the present invention provides an edge computing device suitable for online evaluation of wind farms, characterized in that the edge computing device mainly includes a data acquisition module, a computing function module, a storage module and a communication function module;

[0032] The data acquisition module is used to implement instantaneous data acquisition and variable sampling rate buffering functions.

[0033] The calculation function module is used to calculate the feature quantity and transmit the calculation result to the online evaluation system through the communication function transmission module.

[0034] The storage module is used to implement logic-triggered waveform recording, store it in file form, and transmit it to the online evaluation system through the communication function module.

[0035] The communication function module implements data transmission through a universal protocol.

[0036] Furthermore, the data acquisition module is also used to perform simple calculations on instantaneous data.

[0037] Furthermore, the data acquisition module is also used to transmit the results of simple calculations to the online evaluation system through the communication function transmission module.

[0038] Furthermore, the data acquisition module has a voltage input range of 0–690V, a current input range of 0–1A, and a sampling rate of not less than 10kHz.

[0039] Furthermore, the computing module employs a dual-core industrial-grade processor.

[0040] Furthermore, the storage module is equipped with industrial-grade flash memory.

[0041] Furthermore, the communication module meets the Modbus TCP / IP communication protocol and FTP file transfer function.

[0042] Thirdly, the present invention provides an online evaluation platform suitable for wind farms, the platform including a business terminal, an online evaluation system, and the aforementioned edge computing device suitable for online evaluation of wind farms.

[0043] Furthermore, the service terminal and the edge computing device can be one or more.

[0044] Furthermore, the business terminal is used to send an online evaluation request to the online evaluation system and send the request to the edge computing device suitable for online evaluation of wind farms; the online evaluation system is used to receive the request, perform online evaluation and analysis based on the request and the data calculated by the edge computing device, obtain the evaluation result, and send the obtained evaluation result to the business terminal.

[0045] Furthermore, the online evaluation system is set up in a distributed server.

[0046] Furthermore, the distributed server is a cloud server.

[0047] Furthermore, the distributed server is an edge server.

[0048] Compared with the prior art, the present invention has the following obvious substantive features and significant advantages:

[0049] (1) Based on the instantaneous voltage and current data with high sampling rate, key grid connection information is mined and a data channel is provided for the original data, which is conducive to supporting the analysis of grid connection characteristics and fault inference of wind farms;

[0050] (2) As an edge computing device, it can collect grid-connected voltage and current data to realize the preprocessing of key features of the grid-connected characteristics of the unit, which greatly reduces the amount of computation required for the application of the upper-level online evaluation system.

[0051] (3) Based on the grid connection characteristic data of wind turbine units, the status monitoring capability of wind turbine units can be improved, which is conducive to the early warning of unit faults and operation and maintenance; based on the grid connection characteristic analysis of wind turbine units, grid friendliness can be improved by improving control strategies. Attached Figure Description

[0052] Figure 1 A schematic diagram of the edge computing method for online evaluation of wind farms provided by the present invention;

[0053] Figure 2 A schematic diagram of an edge computing device suitable for online evaluation of wind farms provided by the present invention. Detailed Implementation

[0054] To make the objectives, 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 accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] Firstly, this invention proposes an edge computing method suitable for online evaluation of wind farms, such as... Figure 1 As shown, the method includes the following steps:

[0056] Step S1: Real-time acquisition of instantaneous voltage and current values;

[0057] Step S2: Perform a simple calculation on the collected instantaneous value, and cache the instantaneous value and the result of the simple calculation at three different sampling rates as needed;

[0058] Step S3: Calculate feature quantities and trigger waveform recording based on buffered data with different sampling rates;

[0059] Step S4: Transmit the results of the characteristic quantity calculation and logic trigger waveform recording via communication.

[0060] In step S1, real-time acquisition involves collecting the instantaneous values ​​of the three-phase voltage and three-phase current at the grid connection point of the wind turbine generator. The collected instantaneous data has a sampling rate of 10kHz.

[0061] Preferably, the three-phase voltage is obtained by direct acquisition, and the three-phase current is obtained by current clamping.

[0062] The variable sampling rate buffer in step S2 is as follows: the instantaneous values ​​of the three-phase phase voltage and current enter the variable sampling rate buffer. At this time, the instantaneous value data collected has 10kHz. According to the requirements, the raw value of 10kHz is buffered for subsequent characteristic quantity calculation and artificial triggering of waveform recording. If necessary, 10kHz can also be reduced to 2kHz to obtain a raw value buffer of 2kHz, which is used for self-triggering waveform recording.

[0063] Furthermore, during the variable sampling rate buffering process, it is necessary to perform simple calculations on the original 10kHz values ​​to obtain the effective values ​​of the three-phase phase voltage and current, the effective values ​​of the positive and negative sequence voltage and current, and further calculate the active power and reactive power.

[0064] Preferably, the simple calculation is to obtain the effective values ​​of the three-phase phase voltage and current through the sliding window method, and to calculate the effective values ​​of the positive and negative sequence voltage and current respectively through the positive and negative sequence separation method.

[0065] The buffer sampling rate for the calculated data values ​​entering the feature quantity calculation step is reduced to 2kHz.

[0066] The buffer sampling rate for the calculated data values ​​entering the real-time communication transmission step is reduced to 10Hz.

[0067] As can be seen, the variable sampling rate buffering step forms three types of buffers with different resolutions: 10kHz, 2kHz, and 10Hz.

[0068] The characteristic quantity calculation in step S3 mainly includes the calculation of power quality characteristic quantity, grid adaptability characteristic quantity, fault ride-through characteristic quantity, power characteristic quantity, fast frequency and reactive power voltage regulation response characteristic quantity, etc.

[0069] The power quality characteristics are calculated as follows: average active power over 10 minutes, long-term flicker, harmonic current, total harmonic distortion of current, and maximum interharmonic voltage. Instantaneous voltage and current values ​​are stored in a 10kHz buffer, with each 10-minute data packet used for calculation. Simultaneously, the average active power is calculated using the active power data from a 2kHz buffer within the same 10-minute period.

[0070] The calculation of the grid adaptability characteristics includes grid frequency, unbalance, voltage deviation, and operating status. The grid frequency is calculated using the A-phase voltage in a 10kHz buffer, and the effective voltage value in a 2kHz buffer is used to calculate the unbalance and voltage deviation. Specifically, threshold ranges are set for grid frequency, unbalance, and voltage deviation. When these thresholds are exceeded, the active power in the 2kHz buffer is continuously monitored during operation outside the threshold range, and it is determined whether the active power becomes zero or below. If it becomes zero or below, the operating status value is set to 0. After a 1-hour delay, the active power is checked again. When the active power is positive, the operating status value is restored to 1.

[0071] The fault ride-through characteristic calculation includes high / low ride-through type flags, fault ride-through type flags, and voltage change amplitude. The calculation is performed using a 2kHz buffered positive-sequence voltage and the effective values ​​of the three-phase voltages, with the normal voltage amplitude set to U. n When the positive sequence voltage U < 0.9U n When U is in the low-voltage ride-through type, the high / low ride-through type flag is set to 0. n When the fault ride-through type is high voltage ride-through, the flag bit is set to 1. Calculate the three-phase voltage imbalance. When it is greater than 4%, the fault ride-through type is an asymmetrical fault, and the fault ride-through type flag bit is set to 1; otherwise, it is a symmetrical fault, and is set to 0. At the same time, calculate the voltage change amplitude ΔU(t), as shown in formula (1). The maximum voltage change amplitude calculated during the voltage drop is the characteristic quantity.

[0072]

[0073] In the formula, U pos (t) represents the positive sequence voltage value during the fault.

[0074] The calculation of electrical energy characteristics includes cumulative electricity generation and equivalent utilization hours. Power generation is calculated by integrating the active power with a 2kHz buffer, and the equivalent utilization hours are calculated as the quotient of the calculated power generation and the rated capacity of the wind turbine.

[0075] The calculation of rapid frequency and reactive power voltage regulation response characteristics includes adjustment time and power change amplitude. Using the grid frequency result calculated in the grid adaptability characteristic calculation, the grid frequency changes are tracked. When the frequency change is greater than 0.1Hz, a timestamp and the active power value at that time are marked. Simultaneously, the active power value cached at 2kHz is used to determine the active power change amplitude and adjustment time. When the active power change rate approaches zero or a set threshold, a timestamp and the active power value are marked, and these are subtracted from the timestamp and active power value marked at the initial moment of the frequency change to obtain the adjustment time and active power change amplitude, respectively. Similarly, using the effective voltage value cached at 2kHz, voltage changes are tracked. When the voltage change rate is greater than a set threshold, a timestamp and the reactive power value at that time are marked. Simultaneously, the reactive power value cached at 2kHz is used to determine the reactive power change amplitude and adjustment time. When the reactive power change rate approaches zero or a set threshold, a timestamp and the active power value are marked, and these are subtracted from the timestamp and reactive power value marked at the initial moment of the voltage change to obtain the adjustment time and reactive power change amplitude, respectively.

[0076] In step S3, the logic-triggered waveform recording is achieved by setting preset trigger conditions to record fault waveforms, which are then saved in file form and transmitted via communication.

[0077] Preferably, based on the type of triggering, waveform recording can be divided into manual triggering and self-triggering.

[0078] The manually triggered waveform recording uses 10kHz buffered instantaneous voltage and current data to achieve buffered storage 1 second before the trigger command and data storage 10 minutes after the manual trigger command is issued. The self-triggered waveform recording uses 2kHz buffered instantaneous voltage and current data to achieve buffered storage 1 second before the trigger command is issued and data storage 1 minute after the command is issued.

[0079] Preferably, the triggering conditions for the self-triggered waveform recording include: voltage exceeding limits and frequency exceeding limits. Preset thresholds for the effective voltage amplitude and frequency variation are required.

[0080] The communication transmission achieves rapid data output through a general protocol. Specifically, it completes real-time data transmission of the data values ​​calculated in the variable sampling buffer step at a sampling rate of 10Hz; it completes real-time data transmission of the power quality characteristics, grid adaptability characteristics, fault ride-through characteristics, power characteristics, fast frequency and reactive power regulation response characteristics calculated in the characteristic calculation step at a sampling rate of 10Hz; and it completes the transmission of the waveform recording file formed in the logic trigger waveform recording step.

[0081] Preferably, the communication transmission is based on Modbus TCP / IP to achieve 10Hz real-time feature upload.

[0082] Preferably, the communication transmission utilizes the FTP function to achieve autonomous uploading of 10kHz 10min active waveform recording files and 2kHz 1min automatic waveform recording files.

[0083] Secondly, this invention provides an edge computing device suitable for online evaluation of wind farms, mainly comprising a data acquisition module, a computing function module, a storage module, and a communication function module, such as... Figure 2 As shown.

[0084] The data acquisition module is used to realize instantaneous data acquisition and variable sampling rate caching functions. Part of the acquired data is transmitted in real time and directly uploaded to the online evaluation system, part is passed to the calculation function module, and part is stored in the storage module.

[0085] The calculation module calculates the feature values ​​and transmits them to the communication module for uploading to the online evaluation system.

[0086] The storage module implements a logic-triggered waveform recording function, and the stored files will be uploaded to the online evaluation system through the communication function module.

[0087] The communication module enables rapid data output through a common protocol, uploading data or files to the online evaluation system.

[0088] Preferably, the data acquisition module has a voltage input range of 0–690V, a current input range of 0–1A, and a sampling rate of not less than 10kHz.

[0089] Preferably, the computing module uses a dual-core industrial-grade processor with ECC-protected cache and 64-bit 1GB RAM.

[0090] Preferably, the storage module is equipped with 4G industrial-grade flash memory.

[0091] Preferably, the communication module meets the Modbus TCP / IP communication protocol and FTP file transfer function.

[0092] Thirdly, the present invention provides an online evaluation platform suitable for wind farms, the platform including a business terminal, an online evaluation system, and the aforementioned edge computing device suitable for online evaluation of wind farms.

[0093] Preferably, the service terminal and the edge computing device can be one or more.

[0094] The business terminal is used to send an online evaluation request to the online evaluation system and send the request to the edge computing device suitable for online evaluation of wind farms; the online evaluation system is used to receive the request, perform online evaluation analysis based on the request and the data output by the edge computing device, obtain the evaluation result, and send the obtained evaluation result to the business terminal.

[0095] Preferably, the online evaluation system is set up in a distributed server.

[0096] Preferably, the distributed server is a cloud server.

[0097] Preferably, the distributed server is an edge server.

[0098] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0099] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An edge computing method suitable for online evaluation of wind farms, characterized in that, Includes the following steps: Step S1: Real-time acquisition of instantaneous voltage and current values; Step S2: Perform a simple calculation on the collected instantaneous value, and cache the instantaneous value and the result of the simple calculation at three different sampling rates as needed; Step S3: Calculate feature quantities and trigger waveform recording based on buffered data with different sampling rates; The characteristic quantity calculation in step S3 is based on a 10kHz raw value cache and a 2kHz cache of the result after simple calculation, and the logic-triggered waveform recording is based on a 10kHz raw value cache and a 2kHz raw value cache. The characteristic quantity calculation mainly includes power quality characteristic quantity calculation, grid adaptability characteristic quantity calculation, fault ride-through characteristic quantity calculation, power characteristic quantity calculation, fast frequency and reactive power voltage regulation response characteristic quantity calculation; Step S4: Transmit the results of the characteristic quantity calculation and logic trigger waveform recording via communication.

2. The method as described in claim 1, characterized in that, The real-time acquisition in step S1 involves acquiring the instantaneous values ​​of three-phase voltage and three-phase current.

3. The method as described in claim 1, characterized in that, The real-time acquisition in step S1 has a sampling rate of 10 kHz.

4. The method as described in claim 1, characterized in that, The three different sampling rates in step S2 are 10kHz, 2kHz and 10Hz.

5. The method as described in claim 1, characterized in that, In step S2, the effective values ​​of the three-phase phase voltage and current, the effective values ​​of the positive and negative sequence voltage and current are obtained through the simple calculation, and the active power and reactive power are further calculated.

6. The method as described in claim 4, characterized in that, Step S2 also includes transmitting the results obtained from simple calculations in real time via communication.

7. The method as described in claim 5, characterized in that, The simple calculation method is to obtain the effective values ​​of the three-phase phase voltage and current through the sliding window method, and to obtain the effective values ​​of the positive and negative sequence voltage and current through the positive and negative sequence separation method.

8. The method as described in claim 1, characterized in that, The power quality characteristics are calculated, including the average active power over 10 minutes, long-term flicker, harmonic current, total harmonic distortion rate of current, and maximum value of interharmonic voltage.

9. The method as described in claim 1, characterized in that, The calculation of the power grid adaptability characteristics includes power grid frequency, unbalance, voltage deviation, and operating status.

10. The method as described in claim 1, characterized in that, The fault ride-through characteristic quantity calculation includes high / low ride-through type flag, fault ride-through type flag, and voltage change amplitude.

11. The method as described in claim 1, characterized in that, The calculation of electrical energy characteristics includes cumulative electricity consumption and equivalent utilization hours.

12. The method as described in claim 1, characterized in that, The calculation of the rapid frequency and reactive power regulation response characteristics includes adjustment time and power change amplitude.

13. The method as described in claim 1, characterized in that, The characteristic calculation results are transmitted in real time via communication at a sampling rate of 10Hz, and the logic-triggered waveform recording is transmitted via communication in file format.

14. The method as described in claim 13, characterized in that, The communication transmission is based on Modbus TCP / IP for real-time uploading and on FTP functionality for file uploading.

15. The method as described in claim 1, characterized in that, The logic-triggered waveform recording includes manually triggered waveform recording and self-triggered waveform recording.

16. The method as described in claim 15, characterized in that, The triggering conditions for the self-triggered waveform recording include: voltage exceeding the limit and frequency exceeding the limit, and the effective voltage amplitude threshold and frequency change threshold need to be preset.

17. An edge computing device suitable for online evaluation of wind farms, characterized in that, The edge computing device mainly includes a data acquisition module, a computing function module, a storage module, and a communication function module; The data acquisition module is used to implement instantaneous data acquisition and variable sampling rate buffering functions. The calculation function module is used to calculate the feature quantity and transmit the calculation result to the online evaluation system through the communication function transmission module. The characteristic quantity calculation mainly includes power quality characteristic quantity calculation, grid adaptability characteristic quantity calculation, fault ride-through characteristic quantity calculation, power characteristic quantity calculation, fast frequency and reactive power voltage regulation response characteristic quantity calculation; The storage module is used to implement logic-triggered waveform recording, store it in file form, and transmit it to the online evaluation system through the communication function module. The characteristic quantity calculation is based on a 10kHz raw value buffer and a 2kHz buffer of the result after simple calculation; the logic-triggered waveform recording is based on a 10kHz raw value buffer and a 2kHz raw value buffer. The communication function module implements data transmission through a universal protocol.

18. The apparatus as claimed in claim 17, characterized in that, The data acquisition module is also used to perform simple calculations on instantaneous data.

19. The apparatus as claimed in claim 18, characterized in that, The data acquisition module is also used to transmit the results of simple calculations to the online evaluation system through the communication function transmission module.

20. The apparatus as claimed in claim 17, characterized in that, The data acquisition module has a voltage input range of 0~690V, a current input range of 0~1A, and a sampling rate of not less than 10kHz.

21. The apparatus as claimed in claim 17, characterized in that, The computing module uses a dual-core industrial-grade processor.

22. The apparatus as claimed in claim 17, characterized in that, The storage module is equipped with industrial-grade flash memory.

23. The apparatus as claimed in claim 17, characterized in that, The communication function module meets the Modbus TCP / IP communication protocol and FTP file transfer function.

24. An online evaluation platform for wind farms, the platform comprising a business terminal, an online evaluation system, and an edge computing device for online evaluation of wind farms as described in any one of claims 17-23.

25. The platform as described in claim 24, characterized in that, The service terminal and edge computing device can be one or more.

26. The platform as described in claim 24, characterized in that, The business terminal is used to send an online evaluation request to the online evaluation system and send the request to the edge computing device suitable for online evaluation of wind farms; The online evaluation system is used to receive requests, perform online evaluation and analysis based on the requests and the data calculated by the edge computing device, obtain evaluation results, and send the evaluation results to the business terminal.

27. The platform as described in claim 24, characterized in that, The online evaluation system is set up on a distributed server.

28. The platform as described in claim 27, characterized in that, The distributed server is a cloud server.

29. The platform as described in claim 27, characterized in that, The distributed server is an edge server.

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