Wind turbine generator set power limiting judgment method based on real-time power and average wind speed

Abstract

The application provides a wind turbine unit power limiting judgment method based on real-time power and average wind speed, which can reduce unnecessary maintenance cost. The method comprises the following steps: a. A fault analysis program is set in a host computer in advance, the fault analysis program is connected to all wind turbine data acquisition systems, different groups of wind farms correspond to different wind farm data codes, and different wind turbines in each group of wind farms correspond to different wind turbine number data codes; b. The calculation method of different types of wind turbines is set in the fault analysis program in advance, the wind turbines are matched with the corresponding calculation method, the average wind speed, the theoretical power and the corresponding holding time calculated by the real-time data calculation after the wind farm operation data under normal working conditions and cleaning are obtained; c. The fault analysis program identifies each power limiting wind turbine according to the average wind speed, the theoretical power and the corresponding holding time calculated by the corresponding wind turbine, and obtains the power limiting wind turbine whose real-time power is much lower than the corresponding power under the same wind speed.

Description

Technical Field

[0001] This invention relates to the technical field of wind turbine fault diagnosis, specifically a method for determining power outages in wind turbine generator sets based on real-time power and average wind speed. Background Technology

[0002] Wind turbines (hereinafter referred to as wind turbines) are the basic production unit of wind power companies. Large-scale wind power consumption is a global challenge. On the one hand, wind resources are concentrated and large-scale, far from load centers, and the market size in these resource areas is small, making local consumption difficult. On the other hand, wind power itself has characteristics such as volatility and intermittency, requiring the construction of peak-shaving power sources for grid connection; this phenomenon is also known as "wind curtailment." Therefore, to solve this problem, it is necessary to first distinguish the curtailment status of wind turbines.

[0003] In existing technologies, wind turbines that are under power restrictions are often misjudged as faulty wind turbines, which leads to unnecessary maintenance costs for repairing wind turbines under power restrictions. Therefore, there is an urgent need to develop a method that can accurately determine the power restriction status of wind turbines. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides a method for determining power curtailment of wind turbine generators based on real-time power and average wind speed. This method can accurately identify wind turbines in a power curtailment state based on their real-time power and average wind speed, thereby reducing unnecessary maintenance costs.

[0005] A method for determining power curtailment of wind turbine generators based on real-time power and average wind speed, characterized by comprising the following steps:

[0006] A fault analysis program is pre-set inside the host. The fault analysis program is connected to all wind turbine data acquisition systems. The data collected by the wind turbine data acquisition system includes the real-time power, real-time wind speed, rotational speed and grid-side voltage of each wind turbine in each group of wind farms. Different groups of wind farms have different wind farm data codes, and different wind turbines in each group of wind farms have different wind turbine number data codes.

[0007] b. The calculation methods for different types of wind turbines are pre-set in the fault analysis program. After matching the wind turbine with the corresponding calculation method, the average wind speed, theoretical power and corresponding holding time are calculated from the wind farm operation data under normal working conditions and the real-time data after cleaning.

[0008] The fault analysis program identifies each power-limited fan based on the calculated average wind speed, theoretical power, and corresponding hold-up time. It identifies the power-limited fans whose real-time power is significantly lower than the expected power at the same wind speed and sets the corresponding fan status to power-limited state.

[0009] Its further features are:

[0010] In step b, the fault analysis program calculates the 1-minute average wind speed, theoretical power, and the duration of operation of the corresponding fan.

[0011] In step c, it is checked whether the wind turbine has been running for more than 5 minutes within 10 minutes. Only if it has been running for more than 5 minutes can it be determined that the wind turbine is in a normal power generation state. Then, it is determined that the wind turbine is in a normal power generation state and the average wind speed per minute is greater than 6 meters. Then, it is further determined that the real-time power / theoretical power is less than 0.6 for 15 minutes. If the above conditions are met, a power-limited wind turbine with a real-time power significantly lower than the expected power at the same wind speed is obtained, and the corresponding wind turbine status is set to power-limited state.

[0012] By adopting this invention, the average calculation methods are pre-set according to different wind turbine manufacturers and models. The fault analysis program has a pre-set average parameter calculation method. The summarized real-time wind turbine data is uploaded to the wind turbine data acquisition system. Then, the fault analysis program matches the wind turbine with the corresponding calculation method and calculates the average wind speed, theoretical power, and corresponding holding time calculated from the wind farm operation data under normal operating conditions and the real-time data after cleaning. Afterwards, the fault analysis program identifies each power-canceling wind turbine based on the average wind speed, theoretical power, and corresponding holding time calculated for the corresponding wind turbine. It identifies the power-canceling wind turbines whose real-time power is significantly lower than the expected power at the same wind speed and sets the corresponding wind turbine status to power-canceling state. It can accurately determine the wind turbine in the power-canceling state based on the real-time power and average wind speed, reducing unnecessary maintenance costs. Attached Figure Description

[0013] Figure 1 This is a flowchart illustrating the operation of the method of the present invention. Detailed Implementation

[0014] Wind turbine status is standardized into six categories: "Operating," "Standby," "Fault," "Maintenance," "Power Curtailment," and "Offline." Power curtailment refers to insufficient power generation from the wind turbine. Maintenance refers to the wind turbine being manually shut down. While fault status requires subsequent maintenance, power curtailment status does not. Power curtailment includes wind power abandonment, which refers to the phenomenon where, in the early stages of wind power development, wind turbines are shut down due to insufficient local grid capacity, mismatched construction schedules, and inherent instability of wind power, even when they are operating normally.

[0015] A method for determining power curtailment of wind turbine generators based on real-time power and average wind speed, see [link to relevant documentation]. Figure 1 It includes the following steps:

[0016] A fault analysis program is pre-set inside the host. The fault analysis program is connected to all wind turbine data acquisition systems. The data collected by the wind turbine data acquisition system includes the real-time power, real-time wind speed, rotational speed and grid-side voltage of each wind turbine in each group of wind farms. Different groups of wind farms have different wind farm data codes, and different wind turbines in each group of wind farms have different wind turbine number data codes.

[0017] b. The calculation methods for different types of wind turbines are pre-set in the fault analysis program. After matching the wind turbine with the corresponding calculation method, the average wind speed, theoretical power and corresponding holding time are calculated from the wind farm operation data under normal working conditions and the real-time data after cleaning.

[0018] The fault analysis program identifies each power-limited fan based on the calculated average wind speed, theoretical power, and corresponding hold-up time. It identifies the power-limited fans whose real-time power is significantly lower than the expected power at the same wind speed and sets the corresponding fan status to power-limited state.

[0019] The wind turbine data acquisition system establishes communication with the wind turbine's main control PLC and stores the data transmitted by the PLC in the database. The data collected by the wind turbine data acquisition system is disorganized and needs to be organized. The organization process is called data cleaning. Only after cleaning can the operating data of each wind turbine under normal operating conditions be obtained.

[0020] In a specific embodiment, the specific steps formed by combining steps b and c are as follows:

[0021] Step 1: Detect real-time data from the wind turbine;

[0022] Step 2: Calculate the 1-minute average wind speed, theoretical power, and the duration of operation.

[0023] Step 3: The fan remained running for more than 5 minutes within the 10-minute timeframe;

[0024] Step 4: The wind turbine is in normal power generation condition and the average wind speed per minute is greater than 6 meters.

[0025] Step 5: The real-time power / theoretical power ratio remains less than 0.6 for 15 minutes.

[0026] If the conditions in steps 3-5 are met, then the power-limited wind turbines with real-time power significantly lower than the required power at the same wind speed are obtained, and the corresponding wind turbine status is set to power-limited state.

[0027] During the derivation and verification process, it was found that some wind turbines would meet the power limiting judgment method during start-up and shutdown. Therefore, step 3 was added to exclude the situation of normal wind turbine shutdown or start-up. During the derivation and verification process, it was found that the real-time power of the wind turbines fluctuated. Therefore, the duration of step 5 was added to exclude the situation of unstable data.

[0028] The system pre-sets average calculation methods for different wind turbine manufacturers and models. The fault analysis program internally calculates corresponding average parameters and uploads the aggregated real-time wind turbine data to the wind turbine data acquisition system. Then, the fault analysis program matches the wind turbine to the corresponding calculation method, calculating the average wind speed, theoretical power, and corresponding hold-up time based on the wind farm's operating data under normal conditions and the real-time data after cleaning. Subsequently, based on the calculated average wind speed, theoretical power, and corresponding hold-up time for each wind turbine, the fault analysis program identifies the wind turbines that are experiencing significantly lower real-time power than their expected power at the same wind speed, and sets the corresponding wind turbines to a power-limited state. It can accurately determine wind turbines in a power-limited state based on their real-time power and average wind speed, reducing unnecessary maintenance costs.

[0029] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0030] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A wind turbine generator set power limiting judgment method based on real-time power and average wind speed, characterized in that, It comprises the following steps: a. A fault analysis program is set in advance in the host, and the fault analysis program is connected to all fan data acquisition systems respectively. The data collected by the fan data acquisition system includes real-time power, real-time wind speed, rotating speed and grid-side voltage of each fan in each group of wind farms. Different groups of wind farms correspond to different wind farm data codes, and different fans in each group of wind farms correspond to different fan number data codes; b. The calculation method of different types of fans is set in advance in the fault analysis program. After the fans are matched with the corresponding calculation method, the average wind speed, theoretical power and corresponding retention time calculated by the real-time data of the wind farm running data under normal working condition and after cleaning are obtained; c. The fault analysis program identifies each power-limited fan according to the average wind speed, theoretical power and corresponding retention time calculated for the corresponding fan, obtains the power-limited fan whose real-time power is much lower than the power that should be generated under the same wind speed, and sets the state of the corresponding fan to power-limited state; In step b, the fault analysis program calculates the 1-minute average wind speed, theoretical power and retention time of the running state of the corresponding fan; In step c, it is detected whether the fan has been in the running state for more than 5 minutes within 10 minutes. Only when it has been in the running state for more than 5 minutes can it be determined that the fan is in a normal power-generating state. Then it is determined that the fan is in a normal power-generating state and the 1-minute average wind speed is greater than 6 meters. Then it is continuously determined that the real-time power / theoretical power is less than 0.6 for 15 minutes. If the above conditions are met, the power-limited fan whose real-time power is much lower than the power that should be generated under the same wind speed is obtained, and the state of the corresponding fan is set to power-limited state.

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