Method and system for testing wind energy capture performance of offshore direct-current wind power plant

Abstract

The invention discloses a method and a system for testing the wind energy capture performance of an offshore direct-current wind power plant. The method comprises the following steps: acquiring incoming flow wind speed data of a first exhaust fan of an offshore direct-current wind power plant; acquiring operation state data of different fans in an inner field of the offshore wind power plant, and performing time mark synchronization, dimension unification and other processing operations on the data; wind energy capture performance evaluation indexes, including average wind energy capture efficiency and electromagnetic torque fatigue load, of the offshore direct-current wind power plant are constructed from the two aspects of power generation efficiency and unit health state; performing weighted average on the two indexes to obtain a single-valued index representing the wind energy capture performance of the offshore direct-current wind power plant; and changing the test time period, carrying out multiple tests under different working conditions, and carrying out statistics to obtain corresponding wind energy capture performance indexes of the offshore direct-current wind power plant. The method and the system provided by the invention are oriented to the field test of the wind energy capture performance of the actual offshore direct current wind power plant, and provide a solid technical basis for accurately evaluating and improving the wind energy capture performance of the offshore wind power plant.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind turbines, and in particular to a method and system for testing the wind energy capture performance of an offshore DC wind farm. Background Art

[0002] Offshore wind power, a clean, renewable, green energy source, is gaining widespread attention and development amidst the broader energy transition and upgrade. By 2023, offshore wind power capacity will have increased by approximately 11 GW, a 17.2% growth rate, and is increasingly being deployed in deep-sea locations. Currently, numerous offshore wind power bases with capacity exceeding 10 million kilowatts have been established in Jiangsu, Guangdong, and Fujian.

[0003] The operating environment of offshore wind farms is complex, with frequent changes in environmental factors such as wind speed, wind direction, temperature, and humidity. This places higher demands on the performance and stability of wind turbines, and also increases the difficulty of testing the wind energy capture performance of offshore DC wind turbines and wind farms. Compared with AC collection methods, DC collection methods have the characteristics of low power loss, controllability, and high reliability, and are becoming a potential way to achieve power collection in offshore wind farms. Since most of the current offshore wind turbines use AC wind turbines, their power collection method is naturally AC collection. There is a lack of research on testing technology for offshore DC wind turbines and wind farms using DC collection methods. On the other hand, current technologies mainly focus on performance testing of individual equipment in offshore wind power systems, such as separate testing of wind turbine rectifiers, inverters, transformers, etc., rather than exploring the testing of wind energy capture operating performance of offshore wind farms from the perspective of the entire system.

[0004] This makes it difficult for current performance tests targeting individual equipment to comprehensively evaluate the actual operating performance of offshore DC wind farms in complex marine environments. This leads to inaccurate assessments of the output of offshore DC wind farms, which in turn affects the rationality of dispatching instructions issued by the dispatching department and ultimately affects the performance of offshore DC wind farms integrated into the power grid. Therefore, there is an urgent need for a wind energy capture performance test method and system specifically for offshore DC wind farms to accurately evaluate the wind energy capture performance of offshore DC wind farms in complex marine environments, provide accurate test data, and provide a basis for the optimization and control of offshore wind farms. Summary of the Invention

[0005] The purpose of the present invention is to address the problems existing in the above-mentioned prior art and provide a method and system for testing the wind energy capture performance of an offshore DC wind farm. The method obtains the wind speed of the first row of wind turbines in the wind farm, and uses the wind energy contained therein as a benchmark for calculating the wind energy capture performance index. The operating status data of each wind turbine in the field is obtained through communication between the test system and the offshore DC wind turbine main control system, thereby calculating the wind energy capture performance index of the offshore DC wind farm, providing a basis for subsequent performance evaluation and performance improvement of the offshore DC wind farm.

[0006] The technical solution for achieving the purpose of the present invention is: a method for testing the wind energy capture performance of an offshore DC wind farm, the method comprising the following steps:

[0007] Step 1: Obtain the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm;

[0008] Step 2: establishing communication between the offshore DC wind farm wind energy capture performance test system and the offshore DC wind turbine master control system to obtain operating status data of different wind turbines within the offshore wind farm;

[0009] Step 3: Post-process the incoming wind speed data and operating status data collected from different wind turbines to achieve normalization;

[0010] Step 4: Based on the data processed in step 3, construct and calculate the wind energy capture performance evaluation index of the offshore DC wind farm during the current test period from the two aspects of power generation efficiency and unit health status;

[0011] Step 5: Fusing the two indicators obtained in step 4 to obtain a single-value indicator characterizing the wind energy capture performance of the offshore DC wind farm;

[0012] Step 6: Change the test period and conduct tests under different working conditions according to the methods of steps 1 to 5. Statistically obtain the final wind energy capture performance evaluation index, analyze the impact of wind speed fluctuation characteristics on wind energy capture performance indicators, and establish a relationship curve between average wind speed, turbulence intensity and offshore wind farm wind energy capture performance evaluation indicators.

[0013] Furthermore, in step 1, the incoming wind speed data of the first row of wind turbines of the offshore DC wind farm is obtained by using a wind speed measuring instrument;

[0014] Assume that the wind turbine layout topology in the offshore DC wind farm is m*n, the incoming wind speed of the first row of wind turbines is v0, the rotor radius of the offshore DC wind turbine is R, and the wind power P contained in the incoming wind speed of the first row of wind turbines is W for:

[0015]

[0016] Where ρ is the air density.

[0017] Furthermore, the communication protocol is the Modbus TCP protocol, and the communication cycle is 20ms.

[0018] Furthermore, in step 2, the operating status data at least includes the DC voltage U i , DC current I i and electromagnetic torque T gi , i=1,2,3,……,N, N is the number of wind turbines in the offshore wind farm.

[0019] Furthermore, the post-processing operation in step 3 includes:

[0020] Time-scale synchronization: The operating status data collected by each wind turbine's main control system is marked with a unified time-scale through the Beidou timing system;

[0021] Dimensional unification: This includes unifying the DC voltage dimension to volts (V), the DC current dimension to amperes (A), the wind speed dimension to meters per second (m / s), and the fan speed dimension to radians per second (rad / s);

[0022] Unify data precision: Unify data precision to 2 decimal places.

[0023] Furthermore, in step 4, in terms of power generation efficiency, the wind energy capture performance evaluation index of the offshore DC wind farm is the average wind energy capture efficiency: the ratio of the integral of the output power of all wind turbines in the wind farm during the test period, i.e., the total electric energy, to the integral of the wind power during the test period, i.e., the total wind energy, i.e.:

[0024]

[0025] Where, η is the wind energy capture performance evaluation index of offshore DC wind farm, U i (t), I i P (t) are the DC voltage and DC current of the i-th wind turbine in the offshore wind farm at time t during the test period, N is the number of wind turbines in the offshore wind farm, and T is the test period; W (t) is the wind power contained in the incoming wind speed of the first row of wind turbines at time t;

[0026] In terms of unit health status, the wind energy capture performance evaluation index of offshore DC wind farms is the electromagnetic torque fatigue load index: the range of the average electromagnetic torque of all wind turbines in the wind farm. and the range of the standard deviation

[0027]

[0028] Where, is the average value of the electromagnetic torque of the i-th fan in the time range [T0, T0+T], that is, the current test period, is the standard deviation of the electromagnetic torque of the i-th fan in the time range [T0, T0+T]; Take the time range [T0, T0+T] respectively The maximum and minimum values ​​of Take the time range [T0, T0+T] respectively The maximum and minimum values ​​of .

[0029] Furthermore, the fusion formula in step 5 is:

[0030]

[0031] Where a and b are the weight coefficients of the average wind energy capture efficiency and electromagnetic torque fatigue load index, respectively. The value of a ranges from 1 to 10, and the value of b ranges from 0.00001 to 0.0001.

[0032] In another aspect, a wind energy capture performance testing system for an offshore DC wind farm is provided, the system comprising:

[0033] The first module is used to achieve: obtaining the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm;

[0034] The second module is used to achieve: establishing communication between the offshore DC wind farm wind energy capture performance test system and the offshore DC wind turbine master control system, and obtaining operating status data of different wind turbines in the offshore wind farm;

[0035] The third module is used to implement: post-processing operations on the incoming wind speed data and operating status data collected from different wind turbines to achieve normalization;

[0036] The fourth module is used to implement: based on the data processed by the third module, construct and calculate the wind energy capture performance evaluation index of the offshore DC wind farm in the current test period from the two aspects of power generation efficiency and unit health status;

[0037] The fifth module is used to achieve: fusing the two indicators obtained in the fourth module to obtain a single-value indicator characterizing the wind energy capture performance of the offshore DC wind farm;

[0038] The sixth module is used to achieve the following: changing the test period, conducting tests under different working conditions in the manner of the first to fifth modules, statistically obtaining the final wind energy capture performance evaluation index, analyzing the impact of wind speed fluctuation characteristics on wind energy capture performance indicators, and establishing a relationship curve between average wind speed, turbulence intensity and offshore wind farm wind energy capture performance evaluation indicators.

[0039] On the other hand, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the offshore DC wind farm wind energy capture performance testing method when executing the computer program.

[0040] On the other hand, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the offshore DC wind farm wind energy capture performance testing method is implemented.

[0041] Compared with the prior art, the present invention has the following significant advantages:

[0042] (1) Aiming at actual offshore DC wind farms, the present invention proposes a wind energy capture performance test and system for offshore DC wind farms, which avoids the need for a large number of wind speed measuring instruments and is a practical and cost-effective wind energy capture performance testing solution.

[0043] (2) The proposed offshore DC wind farm wind energy capture performance test and system takes into account the wake effect within the wind farm, reflecting the impact of the wind turbine control strategy on the wake effect and the overall wind energy capture performance. Furthermore, the wind farm health status assessment index, which considers the differences in electromagnetic torque fatigue loads of wind turbines, can avoid downtime maintenance caused by excessive fatigue loads on a few units. This provides a reference for improving wind energy capture performance at the wind farm level.

[0044] The present invention is further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of the wind energy capture performance testing method for an offshore DC wind farm according to the present invention.

[0046] Figure 2 This is the distribution topology of wind turbines in an offshore DC wind farm. DETAILED DESCRIPTION

[0047] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention, in conjunction with the accompanying drawings. Obviously, the described embodiments are only a portion of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0048] It should be noted that if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0049] In one embodiment, combined Figure 1 , provides a method for testing wind energy capture performance of an offshore DC wind farm, the method comprising the following steps:

[0050] Step 1: Obtain the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm;

[0051] Step 2: establishing communication between the offshore DC wind farm wind energy capture performance test system and the offshore DC wind turbine master control system to obtain operating status data of different wind turbines within the offshore wind farm;

[0052] Step 3: Post-process the incoming wind speed data and operating status data collected from different wind turbines to achieve normalization;

[0053] Step 4: Based on the data processed in step 3, construct and calculate the wind energy capture performance evaluation index of the offshore DC wind farm during the current test period from the two aspects of power generation efficiency and unit health status;

[0054] Step 5: Fusing the two indicators obtained in step 4 to obtain a single-value indicator characterizing the wind energy capture performance of the offshore DC wind farm;

[0055] Step 6: Change the test period and conduct tests under different working conditions according to the methods of steps 1 to 5. Statistically obtain the final wind energy capture performance evaluation index, analyze the impact of wind speed fluctuation characteristics on wind energy capture performance indicators, and establish a relationship curve between average wind speed, turbulence intensity and offshore wind farm wind energy capture performance evaluation indicators.

[0056] Furthermore, in one embodiment, in step 1, wind speed data of the first row of wind turbines in the offshore DC wind farm is obtained by an anemometer; the wind energy contained therein is used as a benchmark for calculating the wind energy capture performance index of the offshore DC wind farm;

[0057] like Figure 2 As shown, the wind turbine layout topology in the offshore DC wind farm is m*n, the incoming wind speed of the first row of wind turbines is v0, the rotor radius of the offshore DC wind turbine is R, and the wind power P contained in the incoming wind speed of the first row of wind turbines is W for:

[0058]

[0059] Where ρ is the air density.

[0060] Furthermore, in one embodiment, in step 2, the communication protocol is the Modbus TCP protocol, and the communication cycle is 20 ms.

[0061] Furthermore, in one embodiment, in step 2, the operating status data at least includes the DC voltage U of the (i-th wind turbine group) i , DC current I i and electromagnetic torque T gi , i=1,2,3,……,N, N is the number of wind turbines in the offshore wind farm.

[0062] Furthermore, in one embodiment, the post-processing operation in step 3 includes:

[0063] Time-scale synchronization: The operating status data collected by each wind turbine's main control system is marked with a unified time-scale through the Beidou timing system;

[0064] Dimensional unification: This includes unifying the DC voltage dimension to volts (V), the DC current dimension to amperes (A), the wind speed dimension to meters per second (m / s), and the fan speed dimension to radians per second (rad / s);

[0065] Unify data precision: Unify data precision to 2 decimal places.

[0066] Furthermore, in one embodiment, in step 4, in terms of power generation efficiency, the wind energy capture performance evaluation index of the offshore DC wind farm is the average wind energy capture efficiency: the ratio of the integral of the output power of all wind turbines in the wind farm during the test period, i.e., the total electric energy, to the integral of the wind power during the test period, i.e., the total wind energy, that is:

[0067]

[0068] Where, η is the wind energy capture performance evaluation index of offshore DC wind farm, U i (t), I i P (t) are the DC voltage and DC current of the i-th wind turbine in the offshore wind farm at time t during the test period, N is the number of wind turbines in the offshore wind farm, and T is the test period; W (t) is the wind power contained in the incoming wind speed of the first row of wind turbines at time t;

[0069] In terms of unit health status, the wind energy capture performance evaluation index of offshore DC wind farms is the electromagnetic torque fatigue load index: the range of the average electromagnetic torque of all wind turbines in the wind farm. and the range of the standard deviation

[0070]

[0071]

[0072] Where, is the average value of the electromagnetic torque of the i-th fan in the time range [T0, T0+T], that is, the current test period, is the standard deviation of the electromagnetic torque of the i-th fan in the time range [T0, T0+T]; Take the time range [T0, T0+T] respectively The maximum and minimum values ​​of Take the time range [T0, T0+T] respectively The maximum and minimum values ​​of ; T is the time interval; T0 is a certain moment.

[0073] This indicator reflects the difference in electromagnetic torque fatigue loads between wind turbines in an offshore DC wind farm. It can quickly detect units with excessive electromagnetic torque fatigue loads and avoid shutdown and maintenance of such units.

[0074] Furthermore, in one embodiment, the fusion formula in step 5 is:

[0075]

[0076] Where a and b are the weight coefficients of the average wind energy capture efficiency and electromagnetic torque fatigue load index, respectively. The value of a ranges from 1 to 10, and the value of b ranges from 0.00001 to 0.0001.

[0077] In one embodiment, a wind energy capture performance testing system for an offshore DC wind farm is provided, the system comprising:

[0078] The first module is used to achieve: obtaining the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm;

[0079] The second module is used to achieve: establishing communication between the offshore DC wind farm wind energy capture performance test system and the offshore DC wind turbine master control system, and obtaining operating status data of different wind turbines in the offshore wind farm;

[0080] The third module is used to implement: post-processing operations on the incoming wind speed data and operating status data collected from different wind turbines to achieve normalization;

[0081] The fourth module is used to implement: based on the data processed by the third module, construct and calculate the wind energy capture performance evaluation index of the offshore DC wind farm in the current test period from the two aspects of power generation efficiency and unit health status;

[0082] The fifth module is used to achieve: fusing the two indicators obtained in the fourth module to obtain a single-value indicator characterizing the wind energy capture performance of the offshore DC wind farm;

[0083] The sixth module is used to achieve the following: changing the test period, conducting tests under different working conditions in the manner of the first to fifth modules, statistically obtaining the final wind energy capture performance evaluation index, analyzing the impact of wind speed fluctuation characteristics on wind energy capture performance indicators, and establishing a relationship curve between average wind speed, turbulence intensity and offshore wind farm wind energy capture performance evaluation indicators.

[0084] The specific limitations of the offshore DC wind farm wind energy capture performance test system can be found in the limitations of the offshore DC wind farm wind energy capture performance test method described above and will not be repeated here. Each module in the aforementioned offshore DC wind farm wind energy capture performance test system can be implemented in whole or in part through software, hardware, or a combination thereof. Each of the aforementioned modules can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in a computer device in software form, so that the processor can call and execute the operations corresponding to each of the aforementioned modules.

[0085] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following is achieved:

[0086] Step 1: Obtain the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm;

[0087] Step 2: establishing communication between the offshore DC wind farm wind energy capture performance test system and the offshore DC wind turbine master control system to obtain operating status data of different wind turbines within the offshore wind farm;

[0088] Step 3: Post-process the incoming wind speed data and operating status data collected from different wind turbines to achieve normalization;

[0089] Step 4: Based on the data processed in step 3, construct and calculate the wind energy capture performance evaluation index of the offshore DC wind farm during the current test period from the two aspects of power generation efficiency and unit health status;

[0090] Step 5: Fusing the two indicators obtained in step 4 to obtain a single-value indicator characterizing the wind energy capture performance of the offshore DC wind farm;

[0091] Step 6: Change the test period and conduct tests under different working conditions according to the methods of steps 1 to 5. Statistically obtain the final wind energy capture performance evaluation index, analyze the impact of wind speed fluctuation characteristics on wind energy capture performance indicators, and establish a relationship curve between average wind speed, turbulence intensity and offshore wind farm wind energy capture performance evaluation indicators.

[0092] For the specific limitations of each step, please refer to the limitations of the test method for wind energy capture performance of offshore DC wind farms mentioned above, which will not be repeated here.

[0093] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the computer program implements:

[0094] Step 1: Obtain the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm;

[0095] Step 2: establishing communication between the offshore DC wind farm wind energy capture performance test system and the offshore DC wind turbine master control system to obtain operating status data of different wind turbines within the offshore wind farm;

[0096] Step 3: Post-process the incoming wind speed data and operating status data collected from different wind turbines to achieve normalization;

[0097] Step 4: Based on the data processed in step 3, construct and calculate the wind energy capture performance evaluation index of the offshore DC wind farm during the current test period from the two aspects of power generation efficiency and unit health status;

[0098] Step 5: Fusing the two indicators obtained in step 4 to obtain a single-value indicator characterizing the wind energy capture performance of the offshore DC wind farm;

[0099] Step 6: Change the test period and conduct tests under different working conditions according to the methods of steps 1 to 5. Statistically obtain the final wind energy capture performance evaluation index, analyze the impact of wind speed fluctuation characteristics on wind energy capture performance indicators, and establish a relationship curve between average wind speed, turbulence intensity and offshore wind farm wind energy capture performance evaluation indicators.

[0100] For the specific limitations of each step, please refer to the limitations of the test method for wind energy capture performance of offshore DC wind farms mentioned above, which will not be repeated here.

[0101] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention, and such changes and modifications fall within the scope of the invention as claimed.

Claims

1. A method for testing wind energy capture performance of an offshore DC wind farm, characterized in that: The method comprises the following steps: Step 1: Obtain the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm; Step 2: establishing communication between the offshore DC wind farm wind energy capture performance test system and the offshore DC wind turbine master control system to obtain operating status data of different wind turbines within the offshore wind farm; Step 3: Post-process the incoming wind speed data and operating status data collected from different wind turbines to achieve normalization; Step 4: Based on the data processed in step 3, construct and calculate the wind energy capture performance evaluation index of the offshore DC wind farm during the current test period from the two aspects of power generation efficiency and unit health status; Step 5: Fusing the two indicators obtained in step 4 to obtain a single-value indicator characterizing the wind energy capture performance of the offshore DC wind farm; Step 6: Change the test period and conduct tests under different working conditions according to the methods of steps 1 to 5. Statistically obtain the final wind energy capture performance evaluation index, analyze the impact of wind speed fluctuation characteristics on wind energy capture performance indicators, and establish a relationship curve between average wind speed, turbulence intensity and offshore wind farm wind energy capture performance evaluation indicators.

2. The offshore DC wind farm wind energy capture performance testing method according to claim 1, characterized in that: In step 1, the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm is obtained by using a wind speed measuring instrument; Assume that the wind turbine layout topology in the offshore DC wind farm is m*n, the incoming wind speed of the first row of wind turbines is v0, the rotor radius of the offshore DC wind turbine is R, and the wind power P contained in the incoming wind speed of the first row of wind turbines is W for: Where ρ is the air density.

3. The offshore DC wind farm wind energy capture performance testing method according to claim 1, characterized in that: In step 2, the communication protocol is modbusTCP protocol, and the communication cycle is 20ms.

4. The offshore DC wind farm wind energy capture performance testing method according to claim 1, characterized in that: In step 2, the operating status data at least includes the DC voltage U i , DC current I i and electromagnetic torque T gi , i=1,2,3,……,N, N is the number of wind turbines in the offshore wind farm.

5. The offshore DC wind farm wind energy capture performance testing method according to claim 1, characterized in that: The post-processing operations in step 3 include: Time-scale synchronization: The operating status data collected by each wind turbine's main control system is marked with a unified time-scale through the Beidou timing system; Dimensional unification: This includes unifying the DC voltage dimension to volts (V), the DC current dimension to amperes (A), the wind speed dimension to meters per second (m / s), and the fan speed dimension to radians per second (rad / s); Unify data precision: Unify data precision to 2 decimal places.

6. The offshore DC wind farm wind energy capture performance testing method according to claim 1, characterized in that: In step 4, in terms of power generation efficiency, the wind energy capture performance evaluation index of the offshore DC wind farm is the average wind energy capture efficiency: the ratio of the integral of the output power of all wind turbines in the wind farm during the test period, i.e., the total electric energy, to the integral of the wind power during the test period, i.e., the total wind energy, i.e.: Where, η is the wind energy capture performance evaluation index of offshore DC wind farm, U i (t), I i P (t) are the DC voltage and DC current of the i-th wind turbine in the offshore wind farm at time t during the test period, N is the number of wind turbines in the offshore wind farm, and T is the test period; W (t) is the wind power contained in the incoming wind speed of the first row of wind turbines at time t; In terms of unit health status, the wind energy capture performance evaluation index of offshore DC wind farms is the electromagnetic torque fatigue load index: the range of the average electromagnetic torque of all wind turbines in the wind farm. and the range of the standard deviation Where, is the average value of the electromagnetic torque of the i-th fan in the time range [T0, T0+T], that is, the current test period, is the standard deviation of the electromagnetic torque of the i-th fan in the time range [T0, T0+T]; Take the time range [T0, T0+T] respectively The maximum and minimum values ​​of Take the time range [T0, T0+T] respectively The maximum and minimum values ​​of .

7. The offshore DC wind farm wind energy capture performance testing method according to claim 6, characterized in that: The fusion formula in step 5 is: Where a and b are the weight coefficients of the average wind energy capture efficiency and electromagnetic torque fatigue load index, respectively. The value of a ranges from 1 to 10, and the value of b ranges from 0.00001 to 0.0001.

8. An offshore DC wind farm wind energy capture performance testing system based on the method according to any one of claims 1 to 7, characterized in that: The system comprises: The first module is used to achieve: obtaining the incoming wind speed data of the first row of wind turbines in the offshore DC wind farm; The second module is used to achieve: establishing communication between the offshore DC wind farm wind energy capture performance test system and the offshore DC wind turbine master control system, and obtaining operating status data of different wind turbines in the offshore wind farm; The third module is used to implement: post-processing operations on the incoming wind speed data and operating status data collected from different wind turbines to achieve normalization; The fourth module is used to implement: based on the data processed by the third module, construct and calculate the wind energy capture performance evaluation index of the offshore DC wind farm in the current test period from the two aspects of power generation efficiency and unit health status; The fifth module is used to achieve: fusing the two indicators obtained in the fourth module to obtain a single-value indicator characterizing the wind energy capture performance of the offshore DC wind farm; The sixth module is used to achieve the following: changing the test period, conducting tests under different working conditions in the manner of the first to fifth modules, statistically obtaining the final wind energy capture performance evaluation index, analyzing the impact of wind speed fluctuation characteristics on wind energy capture performance indicators, and establishing a relationship curve between average wind speed, turbulence intensity and offshore wind farm wind energy capture performance evaluation indicators.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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