Post-evaluation method of wind power project power generation based on measured data from operating wind tower

Abstract

The invention discloses a post-evaluation method for power generation of a wind power project based on measured data of an operating wind tower, and proposes a calculation step for the degree of deviation between the wind speed and power generation at each machine position of the wind power project and the calculation results at the project design stage; the post-evaluation of wind energy resources is based on the measured data of the operating wind tower and its reference meteorological data, and the multi-year average wind speed at the operating wind tower is obtained through data interpolation and correction, and then the wind speed at each machine position is deduced, and finally the degree of deviation of the actual wind speed at each machine position from the wind speed calculated at the design stage is obtained; the post-evaluation of power generation is based on the SCADA data of the wind turbine, and the wind speed before the impeller of each wind turbine is deduced through the measured data of the operating wind tower, and then the actual power curve of each wind turbine is calculated, and compared with the bid power curve of the wind turbine manufacturer and the SCADA power curve of each wind turbine, and at the same time, the degree of deviation of the power generation of each machine position from the calculation results at the design stage is obtained.

Description

Technical Field

[0001] The invention belongs to the technical field of wind power project management, and in particular relates to a post-evaluation method for power generation of a wind power project based on measured data of an operating wind tower. Background Art

[0002] With the development and construction of wind power projects in my country, the operation data of wind power projects has gradually become richer. How to use the operation data of wind power projects that have been put into operation to compare and analyze the actual power generation after the project is completed and put into operation with the power generation calculated in the project design stage and conduct a comprehensive evaluation has become a hot issue in wind power project management research. According to the requirements of the power grid dispatching agency, all wind power projects that have been put into operation must install wind power prediction wind towers. In addition, some wind power projects are also equipped with operating wind towers specifically used for post-evaluation of wind power projects for intensive wind measurement. Through the analysis of the measured data of wind power prediction wind towers or operating wind towers of wind power projects that have been put into operation, as well as the operation data of wind turbines, post-evaluation of wind power project power generation is a problem faced by project investment and operation management and participating units (including survey and design units).

[0003] Post-evaluation of wind power project power generation is conducted after the wind power project is completed and accepted and put into operation for a period of time. In the industry, it is usually conducted after the project is completed and accepted for one year. At present, there is no scientific, systematic and standardized post-evaluation method for wind power project power generation in the industry. Third-party post-evaluation agencies are often unable to conduct fair and objective evaluations on the project power generation calculation results proposed by the survey and design units and the compliance of the equipment power curve provided by the wind turbine equipment manufacturers. Summary of the invention

[0004] In order to overcome the above problems, the present invention provides a post-evaluation method for power generation of a wind power project based on measured data of an operating wind tower.

[0005] The technical solution adopted by the present invention is:

[0006] The post-evaluation method of wind power project power generation based on the measured data of the operating wind tower includes the following steps:

[0007] Step 1: Based on the measured data of the project's operating wind tower and its reference meteorological data, obtain the measured data of a complete wind measurement year through data interpolation. If the average wind speed of the complete wind measurement year cannot reflect the multi-year average wind speed level at the wind tower, further long-term representative correction is performed to obtain the multi-year average wind speed at the operating wind tower;

[0008] Step 2: Based on the measured data of the wind tower and the wind speed data of the SCADA recorder at the corresponding time of the wind turbine with the best representativeness, a linear regression equation is established with the instantaneous wind speed of the SCADA recorder as the independent variable and the instantaneous wind speed measured by the wind tower as the dependent variable;

[0009] Step 3: Use the aforementioned linear regression equation, take the wind speed of the SCADA recorder of each other fan as the independent variable, and calculate the instantaneous wind speed in front of the impeller of each other fan. According to the long-term representativeness of the complete wind measurement year selected above, through the long-term representativeness correction, further obtain the multi-year average wind speed at each fan;

[0010] Step 4: Count the deviation of the multi-year average wind speed at each wind turbine from the wind speed calculated in the design stage;

[0011] Step 5: Draw the SCADA power curve of each fan according to the wind speed and active power data of the SCADA recorder behind each fan impeller;

[0012] Step 6: Draw the actual operating power curve of each fan according to the instantaneous wind speed in front of the impeller of each fan and the active power data of the SCADA recorder at the corresponding time;

[0013] Step 7: Count the deviation of the actual operating power generation of each wind turbine from the calculated power generation of the corresponding wind turbine in the design phase.

[0014] Among them, the linear regression equation is established in step 2:

[0015]

[0016] Where i represents the time when the wind speed is recorded; v 测风塔，i It represents the instantaneous wind speed of the operating wind tower at the i-th moment; It represents the instantaneous wind speed of the wind turbine at the i-th moment that is best represented by the running wind tower. Since the running wind tower is the best representative of the wind speed of the wind turbine, it is considered that the instantaneous wind speed of the running wind tower at the i-th moment is equal to the instantaneous wind speed in front of the impeller of the wind turbine at the i-th moment. a is the regression coefficient of the linear regression equation; b is the constant of the linear regression equation.

[0017] Among them, in step 3, the linear regression equation is used to calculate the instantaneous wind speed in front of each fan impeller, and the following formula is used for calculation:

[0018]

[0019] Wherein, t represents the wind turbine number; i represents the time of wind speed recording; It represents the instantaneous wind speed in front of the impeller of the t-th fan at the i-th moment, that is, the wind speed actually available to the fan; represents the instantaneous wind speed when the SCADA recorder is located behind the impeller of the tth wind turbine at the i-th moment; a and b are the coefficients in the linear regression equation in step 2.

[0020] The deviation between the actual annual average wind speed at each wind turbine in step 4 and the annual average wind speed calculated in the design stage is calculated using the following formula:

[0021]

[0022] Wherein, t represents the fan number; represents the average wind speed of the impeller of the tth fan in the previous year; It represents the annual average wind speed at the t-th wind turbine calculated in the design stage; It indicates the degree of deviation of the annual average wind speed of the impeller of the tth fan from the annual average wind speed calculated in the design stage, expressed as a percentage.

[0023] The deviation between the actual operating power generation of each wind turbine in step 7 and the calculated power generation of the corresponding wind turbine in the design stage is calculated using the following formula:

[0024]

[0025] Wherein, t represents the fan number; represents the actual operating power generation of the tth wind turbine; represents the calculated power generation of the t-th wind turbine; It indicates the degree of deviation between the actual operating power generation of the tth wind turbine and the calculated power generation, expressed as a percentage.

[0026] The advantages of the present invention are as follows:

[0027] 1. For the first time, a method is proposed to estimate the wind speed in front of each wind turbine impeller (i.e., the wind speed actually available to the wind turbine) by establishing a linear regression equation based on the measured data of the operating wind tower and the instantaneous wind speed data of the wind turbine operating SCADA recorder (located behind the impeller); this method avoids the huge amount of calculation required by the third-party assessment agency to re-establish the site CFD model and solve it when conducting post-evaluation of wind power project power generation, which can effectively improve the efficiency of post-evaluation of wind power project power generation.

[0028] 2. This method maximizes the value of operating data, uses the measured data of the operating wind tower and the wind speed data of the fan SCADA to estimate the wind speed in front of the fan impeller, and further obtains the degree of deviation of the multi-year average wind speed at each fan from the wind speed calculated in the design stage; compared with the traditional method of using the measured data of the wind tower and establishing a CFD model for simulation calculation, this method regards the SCADA recorder installed on each fan as an independent wind tower, so the data used in this method are all measured data, and the results obtained can effectively verify the rationality of the CFD model established by the survey and design unit in the design stage.

[0029] 3. The actual operating environment of the wind turbine is different from the experimental environment. The wind speed recorded by the SCADA recorder is the wind speed behind the impeller, which is somewhat different from the wind speed in front of the wind turbine impeller. At the same time, the time-varying nature of wind speed, wind direction and other factors of the wind turbine will produce actions such as pitch or yaw, which will directly affect the output of the wind turbine. Therefore, compared with the traditional method of simply comparing the bid power curve with the SCADA recorded power curve, this method uses the wind speed in front of the wind turbine impeller and the active power data sequence recorded at the same time to fit the actual power curve of the wind turbine, and compares the actual power curve with the bid power curve. This method is more objective and fair, and can more truly reflect the actual output level of the wind turbine and the compliance of the power curve.

[0030] In summary, the present invention proposes for the first time a method for estimating the wind speed in front of each wind turbine impeller based on the measured data of the operating wind tower and the SCADA wind speed data of the wind turbine operation by establishing a linear regression equation; and fitting the actual power curve of the wind turbine based on the wind speed in front of each wind turbine impeller and the SCADA active power data, and comparing it with the bid power curve of the wind turbine manufacturer, which is more objective and fair; this method maximizes the value of operating data, and uses statistical methods to post-evaluate the power generation of wind power projects, which is a powerful supplement to the CFD model method of wind farms. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is a flow chart of the present invention;

[0032] Figure 2 is a representative situation diagram of the wind speed of the weather station corresponding to the evaluation period selected in the embodiment in the long sequence;

[0033] Figure 3 is a bar graph showing the degree of deviation of the actual wind speed at each position in the embodiment from the calculated wind speed at each position in the design stage;

[0034] Figure 4 It is a scatter diagram of actual wind speed-active power and a fitting diagram of actual operating power curve in the embodiment;

[0035] Figure 5 It is a comparison diagram of the bidding power curve, SCADA power curve and actual operation power curve in the embodiment;

[0036] Figure 6 It is a bar graph showing the degree of deviation of the actual operating power generation of each unit in the embodiment from the calculated power generation of each unit in the design stage. DETAILED DESCRIPTION

[0037] The present invention will be further described below, but the present invention is not limited to these contents.

[0038] Example

[0039] like Figure 1As shown, the present invention provides a post-evaluation method for wind power project power generation based on measured data of an operating wind tower, comprising the following steps:

[0040] Step 1: Based on the measured data of the project's operating wind tower and its reference meteorological data, obtain the measured data of a complete wind measurement year through data interpolation. If the average wind speed of the complete wind measurement year cannot reflect the multi-year average wind speed level at the wind tower, further long-term representative correction is performed to obtain the multi-year average wind speed at the operating wind tower;

[0041] Step 2: Based on the measured data of the wind tower and the wind speed data of the SCADA recorder at the corresponding time of the wind turbine with the best representativeness, a linear regression equation is established with the instantaneous wind speed of the SCADA recorder as the independent variable and the instantaneous wind speed measured by the wind tower as the dependent variable;

[0042] Step 3: Use the aforementioned linear regression equation, take the wind speed of the SCADA recorder of each other fan as the independent variable, and calculate the instantaneous wind speed in front of the impeller of each other fan. According to the long-term representativeness of the complete wind measurement year selected above, through the long-term representativeness correction, further obtain the multi-year average wind speed at each fan;

[0043] Step 4: Count the deviation of the multi-year average wind speed at each wind turbine from the wind speed calculated in the design stage;

[0044] Step 5: Draw the SCADA power curve of each fan according to the wind speed and active power data of the SCADA recorder behind each fan impeller;

[0045] Step 6: Draw the actual operating power curve of each fan according to the instantaneous wind speed in front of the impeller of each fan and the active power data of the SCADA recorder at the corresponding time;

[0046] Step 7: Count the deviation of the actual operating power generation of each wind turbine from the calculated power generation of the corresponding wind turbine in the design phase.

[0047] Example: There is a wind power project that has been in operation for one year. It has 50 wind turbines with a single unit capacity of 2MW, a wind turbine hub height of 80m, and a total installed capacity of 100MW. There is an operating wind measurement tower within the site area, with a tower height of 80m. A set of anemometers and a set of wind vanes are installed at a height of 80m. The operating wind measurement tower is 154m away from the T42 wind turbine. The altitude, terrain, landform and wind conditions are similar to those of the T42 machine position. Therefore, the wind speed at the height of 80m of the operating wind measurement tower can basically represent the wind speed in front of the T42 wind turbine impeller.

[0048] (1) This post-evaluation of power generation collected 10-minute wind speed and wind direction data from January 2017 to December 2017 at an operating wind tower at a height of 80m, of which 52,560 wind speed data records should be measured, and 50,813 records were measured; 52,560 wind direction data records should be measured, and 50,741 records were measured. At the same time, hourly wind speed and wind direction data from January 2017 to December 2017 were collected from the reference meteorological station, of which 8,760 wind speed data records should be measured, and 8,760 records were measured; 8,760 wind direction data records should be measured, and 8,760 records were measured. According to the method recommended in the Wind Energy Resource Assessment Method for Wind Farms (GB / T 18710-2002), the measured data of the operating wind tower were interpolated into a data sequence of a complete wind measurement year.

[0049] According to the meteorological data of the reference meteorological station, the average annual wind speed of the reference meteorological station in the same period was 1.420m / s, and the cumulative annual average wind speed was 1.421m / s, with a difference of 0.001m / s, and a deviation of 0.07% from the cumulative annual average wind speed, which is a small deviation. According to the judgment method and long-term representative correction method recommended in the "Wind Energy Resource Assessment Method for Wind Farms" (GB / T 18710-2002), the selected wind measurement period is a normal wind year, which can represent the average wind speed level of the region for many years, so there is no need to make a long-term representative correction. The annual average wind speed of the reference meteorological data is as follows: Figure 2 shown.

[0050] (2) Based on the measured data of the wind tower and the wind speed data of the SCADA recorder at the corresponding time of the wind turbine with the best representativeness, the linear regression equation is established with the SCADA wind speed instantaneous wind speed as the independent variable and the measured instantaneous wind speed of the wind tower as the dependent variable:

[0051]

[0052] Where i represents the time when the wind speed is recorded, v 测风塔，i represents the instantaneous wind speed of the operating wind tower at the i-th moment, It represents the instantaneous wind speed of the wind turbine with the best representativeness in the running wind measurement tower at the i-th moment.

[0053] According to the wind speed data of the SCADA recorders of other wind turbines, the instantaneous wind speed in front of the impeller of each wind turbine is calculated using the aforementioned linear regression equation:

[0054]

[0055] Where t is the wind turbine number, i is the wind speed recording time, represents the instantaneous wind speed in front of the impeller of the t-th fan at the i-th moment, It represents the instantaneous wind speed of the SCADA recorder (behind the impeller) of the tth wind turbine at the i-th moment.

[0056] (3) The degree of deviation of the annual average wind speed at each wind turbine from the wind speed calculated in the design stage is calculated, as shown in the following table. Based on the degree of deviation of the wind speed before the impeller calculated by the SCADA recorder at each turbine position from the wind speed in the design stage, a bar graph is drawn showing the degree of deviation of the actual wind speed at each turbine position from the wind speed calculated at the design stage, as shown in the following table: Figure 3 shown.

[0057]

[0058]

[0059] (4) Based on the estimated wind speed in front of each fan impeller and the active power data sequence of the SCADA at the corresponding time, draw a scatter plot of the actual wind speed-active power of each fan; according to the method recommended in IEC61400-12-1, divide the actual wind speed into several intervals at intervals of 0.5m / s, and the center value of each interval is an integer multiple of 0.5m / s. At the same time, calculate the average active power corresponding to each interval, and draw a fitting diagram of the actual operating power curve. This embodiment gives a scatter plot of the actual wind speed-active power and a fitting diagram of the actual operating power curve of the T42 machine position, as shown in FIG. Figure 4 shown.

[0060] (5) Draw the SCADA power curve of each wind turbine based on the wind speed and active power data of the SCADA recorder behind each wind turbine impeller; draw the actual operating power curve of each wind turbine based on the instantaneous wind speed in front of each wind turbine impeller and the active power data of the SCADA recorder at the corresponding time; and compare it with the guaranteed power curve provided by the wind turbine manufacturer during the project bidding, such as Figure 5 shown.

[0061] (6) The deviation degree of the actual operating power generation of each wind turbine from the calculated power generation of the corresponding wind turbine in the design stage is counted, as shown in the following table. According to the deviation degree of the actual operating annual power generation of each wind turbine from the calculated annual power generation of each wind turbine in the design stage, a bar graph of the deviation degree of the actual operating annual power generation at each wind turbine location from the calculated annual power generation of each wind turbine in the design stage is drawn, as shown in the following table: Figure 6 shown.

[0062]

[0063]

[0064] It can be seen from the results of the project survey and design that the actual wind speed and power generation of the T1-T23 wind turbines in this project are smaller than the results calculated in the design stage, the actual wind speed and power generation of the T25-T33 wind turbines are basically consistent with the results calculated in the design stage, and the actual wind speed and power generation of the T34-T50 wind turbines are larger than the results calculated in the design stage; the actual operating power generation of each wind turbine deviates more from the results calculated in the design stage than the wind speed results. From the operation of the project wind turbines, the wind energy utilization efficiency of the wind turbines has basically reached the level of the bidding stage, but there are still cases where the actual operating power generation of some wind turbines is inconsistent with the measured wind speed. This situation is mostly caused by abnormal equipment operation, and these wind turbines need to be analyzed separately.

[0065] It is pointed out that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A post-evaluation method for wind power project power generation based on measured data from an operating wind tower, characterized in that: The steps include: Step 1: Based on the measured data of the project's operating wind tower and its reference meteorological data, obtain the measured data of a complete wind measurement year through data interpolation. If the average wind speed of the complete wind measurement year cannot reflect the multi-year average wind speed level at the wind tower, further long-term representative correction is performed to obtain the multi-year average wind speed at the operating wind tower; Step 2: Based on the measured data of the wind tower and the wind speed data of the SCADA recorder at the corresponding time of the wind turbine with the best representativeness, a linear regression equation is established with the instantaneous wind speed of the SCADA recorder as the independent variable and the instantaneous wind speed measured by the wind tower as the dependent variable; Step 3: Use the aforementioned linear regression equation, take the wind speed of the SCADA recorder of each other fan as the independent variable, and calculate the instantaneous wind speed in front of the impeller of each other fan. According to the long-term representativeness of the complete wind measurement year selected above, through the long-term representativeness correction, further obtain the multi-year average wind speed at each fan; Step 4: Count the deviation of the multi-year average wind speed at each wind turbine from the wind speed calculated in the design stage; Step 5: Draw the SCADA power curve of each fan according to the wind speed and active power data of the SCADA recorder behind each fan impeller; Step 6: Draw the actual operating power curve of each fan according to the instantaneous wind speed in front of the impeller of each fan and the active power data of the SCADA recorder at the corresponding time; Step 7: Count the deviation of the actual operating power generation of each wind turbine from the calculated power generation of the corresponding wind turbine in the design phase.

2. The post-evaluation method for wind power project power generation based on measured data from an operating wind tower according to claim 1, characterized in that: In the step 2, a linear regression equation is established: Where i represents the time when the wind speed is recorded; v 测风塔,i It represents the instantaneous wind speed of the operating wind tower at the i-th moment; It represents the instantaneous wind speed of the wind turbine at the i-th moment that is best represented by the running wind tower. Since the running wind tower is the best representative of the wind speed of the wind turbine, it is considered that the instantaneous wind speed of the running wind tower at the i-th moment is equal to the instantaneous wind speed in front of the impeller of the wind turbine at the i-th moment. a is the regression coefficient of the linear regression equation; b is the constant of the linear regression equation.

3. The post-evaluation method for wind power project power generation based on measured data from an operating wind tower according to claim 1, characterized in that: In step 3, a linear regression equation is used to calculate the instantaneous wind speed in front of each fan impeller, using the following formula: Wherein, t represents the wind turbine number; i represents the time of wind speed recording; It represents the instantaneous wind speed in front of the impeller of the t-th fan at the i-th moment, that is, the wind speed actually available to the fan; represents the instantaneous wind speed when the SCADA recorder is located behind the impeller of the tth wind turbine at the i-th moment; a and b are the coefficients in the linear regression equation in step 2.

4. The post-evaluation method for wind power project power generation based on measured data from an operating wind tower according to claim 1, characterized in that: The degree of deviation between the actual annual average wind speed at each wind turbine in step 4 and the annual average wind speed calculated in the design stage is calculated using the following formula: Wherein, t represents the fan number; represents the average wind speed of the impeller of the tth fan in the previous year; It represents the annual average wind speed at the t-th wind turbine calculated in the design stage; It indicates the degree of deviation of the annual average wind speed of the impeller of the tth fan from the annual average wind speed calculated in the design stage, expressed as a percentage.

5. The post-evaluation method for wind power project power generation based on measured data from an operating wind tower according to claim 1, characterized in that: The deviation degree between the actual operating power generation of each wind turbine in step 7 and the calculated power generation of the corresponding wind turbine in the design stage is calculated using the following formula: Wherein, t represents the fan number; represents the actual operating power generation of the tth wind turbine; represents the calculated power generation of the t-th wind turbine; It indicates the degree of deviation between the actual operating power generation of the tth wind turbine and the calculated power generation, expressed as a percentage.

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