Wind power plant electric quantity calculation method considering coupling influence of additional turbulence and blocking effect

Abstract

The invention provides a wind power plant electric quantity calculation method considering additional turbulence and blocking effect coupling influence. The wind power plant electric quantity calculation method comprises the following steps: step 1, acquiring wind power plant information and inflow wind data; 2, numbering the wind turbines in the field according to a front-and-back sequence along the inflow wind direction; 3, quantizing wake flow loss by considering the additional turbulence influence, and calculating the effective wind speed and thrust coefficient of each wind turbine by combining the wind speed variation under the influence of the blocking effect; 4, taking the result of the step 3 as input, and calculating the wind speed variation caused by the blocking effect at each wind turbine; 5, updating the wind speed variation in the step 3 according to the result of the step 4, and obtaining an effective wind speed meeting a convergence standard through iterative calculation; and 6, calculating the generating capacity according to the effective wind speed in the step 5. Decoupling of the additional turbulence and the blocking effect is achieved, the generating capacity calculation method capable of efficiently and accurately simulating the common influence of the additional turbulence and the blocking effect is proposed for the first time, and the calculation precision is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a method for calculating the amount of electricity in a wind farm taking into account the coupling influence of additional turbulence and blocking effects. Background Art

[0002] Wind farms contain numerous turbines, each of which interacts with each other in complex ways during operation. Research has shown that in the wake of a wind turbine, in addition to the wind speed loss caused by wind energy absorption, the turbulence intensity is significantly higher than that of the inflow. This increased turbulence, known as "additional turbulence," affects the evolution of the wake behind the rotor disk, particularly the recovery of the aforementioned wind speed loss. Ignoring this effect can underestimate the wind speed at downwind turbines, affecting the accuracy of wind farm power calculations.

[0003] Furthermore, the "blocking effect" has garnered widespread attention in the field of wind power generation in recent years. Any isolated wind turbine has an induced velocity zone ahead of its disk, where wind speed decreases. Similarly, the inflow velocity in front of a wind farm is different from the free stream velocity and is smaller. This reduction in wind speed due to the wind farm itself stems from the "blocking effect." In wind power engineering practice, the "blocking effect" is particularly pronounced in the first row of wind turbines within a site. Although these turbines are not affected by the wakes of other turbines, their power generation is significantly different. When there are more downwind turbines, the power generation of the first row of wind turbines is lower. Numerous statistical data indicate that power losses due to the "blocking effect" can reach up to 3%. This is particularly true in stable atmospheres, where the impact of the "blocking effect" is further amplified by the strong interaction between the wind farm and the atmospheric turbulent boundary layer. Therefore, it is essential to consider the "blocking effect" when calculating wind farm power generation.

[0004] According to the above introduction, both "additional turbulence" and "blocking effect" have a significant impact on the power generation of wind farms. On the whole, the former tends to weaken the degree of wake interference between units and increase power generation, while the latter is the opposite. It reduces the incoming wind speed perceived by the wind turbines, resulting in a decrease in their power generation. The patent document with publication number CN 116720027 A discloses a method and device for calculating the power generation of a wind farm taking into account the "blocking effect" of wind turbines, wherein the influence area of ​​the "blocking effect" is defined with a preset distance as the radius. This processing method lacks a physical basis and may lead to the impact of the "blocking effect" being underestimated. More importantly, the method does not take into account the "additional turbulence" and its coupling with the "blocking effect", which will lead to a large deviation in the calculation of electricity, thereby affecting the reliability of the economic evaluation results of the wind power project.

[0005] In summary, there is still a gap in existing research on how to accurately quantify the complex nonlinear coupling effects of "additional turbulence" and "blocking effect", and efficient and reliable technical solutions are urgently needed. Summary of the Invention

[0006] The purpose of the present invention is to meet the actual needs of engineering and address the deficiencies of existing technologies, and to provide a wind farm power calculation method that takes into account the coupling effects of additional turbulence and blocking effects, so as to improve the accuracy of power calculation.

[0007] To this end, the present invention adopts the following technical solutions: The method for calculating the power of a wind farm taking into account the coupling effects of additional turbulence and blocking effects includes the following steps: Step 1: Obtain wind farm information and inflow wind data; Step 2: Number each wind turbine in the field in order of their orientation along the inflow wind direction; Step 3: Using the wake effect calculation model that considers the influence of additional turbulence on wake evolution, quantify the wind speed loss at each wind turbine in the field in ascending order, taking into account the additional turbulence and wake interference of other wind turbines. Combined with the wind speed change caused by the blocking effect, the effective wind speed of each wind turbine is obtained, and the thrust coefficient is obtained through interpolation calculation. Step 4: Using the effective wind speed and thrust coefficient obtained in step 3 as inputs to the blocking effect calculation model, the wind speed variation caused by the blocking effect at each wind turbine is quantified in descending order of numbers. Step 5: Based on the calculation results of step 4, update the wind speed change described in step 3 and perform iterative calculations until the difference between the wind speed changes at each wind turbine in the previous and subsequent calculations is less than the set threshold, and output the effective wind speed of each wind turbine at this time; Step 6: Based on the effective wind speed output in step 5, combined with the wind speed-aerodynamic parameter interpolation list of each wind turbine model, calculate the output power, and then obtain the wind farm power generation through summation calculation.

[0008] On the basis of adopting the above technical solutions, the present invention may also adopt the following further technical solutions, or use these further technical solutions in combination: In step 2, take any point in the wind farm as the coordinate origin and define the east direction as Axis positive direction, due north direction is Axis positive, establish a two-dimensional rectangular coordinate system, called the geodetic coordinate system, to determine the coordinates of each wind turbine in this coordinate system; Keep the coordinate origin fixed, follow the inflow wind direction in step 1, and rotate the coordinate system so that in the new coordinate system, that is, the relative coordinate system, The positive direction of the axis points to the inflow wind direction; According to the coordinate transformation matrix expressed by formula (1), the coordinates of each wind turbine in the relative coordinate system are calculated: (1) (2) in, and Represent the horizontal coordinate and vertical coordinate in the geodetic coordinate system and relative coordinate system respectively. is the inflow wind direction, is the angle between the inflow wind direction and the positive direction of the x-axis in the geodetic coordinate system. By comparing the horizontal coordinates of the wind turbines in the relative coordinate system, their relative positions can be determined, and they are sorted and numbered accordingly. The first wind turbine is numbered 1, and the numbers of the downwind wind turbines increase one by one in sequence. The total number of wind turbines in the wind farm is , then the numbering sequence is expressed as .

[0009] Step 3 includes the following specific steps: Step 3.1: Obtain the sequence of wind speed changes caused by the blocking effect , The corresponding numbers are The wind speed variation related to the blocking effect at each wind turbine; in the initial calculation, All values ​​are set to 0; Step 3.2: According to the order of wind turbine numbers from small to large in step 2, the wake effect calculation model that takes into account the influence of additional turbulence on wake evolution is used to quantify the wind speed loss of each wind turbine in the field after considering the influence of additional turbulence and wake interference of other wind turbines. Combined with the sequence described in step 3.1, middle The value of is used to reflect the influence of the blocking effect and calculate the effective wind speed at each wind turbine; Step 3.3: Based on the effective wind speed calculated in step 3.2, the thrust coefficient of each wind turbine is obtained by interpolation calculation based on the wind speed-aerodynamic parameter list of the corresponding wind turbine model. Step 3.4, integrate the calculation results of step 3.2 and step 3.3 to form the sequence and sequence , The corresponding numbers in the venue are The effective wind speed of the wind turbine, The corresponding numbers in the venue are The thrust coefficient of the wind turbine.

[0010] Step 4 includes the following specific steps: Step 4.1: Using the effective wind speed and thrust coefficient from step 3 as input, quantify the wind speed change due to the blocking effect at each wind turbine in the field in descending order using the blocking effect calculation model; Step 4.2: Integrate the calculation results of step 4.1 to form a new wind speed change sequence, expressed as , The corresponding numbers calculated in step 4.1 are The wind speed variation at each wind turbine.

[0011] Step 5 includes the following steps: Step 5.1, calculate the wind speed change sequence and The relative change of the data element at each position in the sequence is determined to be less than the set threshold value. If it is satisfied, the calculation is stopped and the process goes to step 5.2. If it is not satisfied, the sequence is Update Sequence , and repeat steps 3 and 4 until the convergence criteria are met; Step 5.2: Output the effective wind speed of each wind turbine in the field.

[0012] Step 6 includes the following specific steps: Step 6.1, based on the effective wind speed output in step 5, combined with the wind speed-aerodynamic parameter list of each wind turbine model, obtain their respective output powers through interpolation calculation; In step 6.2, the power generation of the wind farm is obtained by summing the output power of each wind turbine.

[0013] This invention is based on a careful analysis and decomposition of the mutual checks and balances among multiple factors that affect the evolution of the flow field in a wind farm. It uses the effective wind speed and thrust coefficient of each wind turbine in the field as an intermediate bridge to propose a decoupling calculation method. On this basis, it develops a wind farm power generation calculation method that can simultaneously and efficiently simulate the coupled effects of additional turbulence and blocking effects. Compared with the existing technology, the accuracy of power calculation is significantly improved, which can provide more scientific technical support for the engineering implementation of wind farm micro-site selection and field-level coordinated control based on this. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the specific embodiments of the present invention, some drawings required in the description of the specific embodiments will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0015] Figure 1 This is a flow chart of wind farm power calculation taking into account the coupling effects of additional turbulence and blocking effects according to the present invention; Figure 2Schematic diagram of wind turbine coordinate transformation; Figure 3 A schematic diagram of the complex coupling correlation of multiple key characteristic quantities that affect the evolution of wind farm flow fields; Figure 4 It is an iterative calculation flow chart; Figure 5(a) is a schematic diagram of the wind turbine rows in the wind farm used for power data analysis under the operating condition of the inflow wind direction angle θ=222° in Example 1. Figure 5(b) is the normalized power of each wind turbine row under the operating condition of the inflow wind direction angle θ=222°.

[0016] Figure 6(a) is a schematic diagram of the wind turbine rows in the wind farm used for power data analysis under the operating condition of the inflow wind direction angle θ=270° in Example 1. Figure 6(b) is the normalized power of each wind turbine row under the operating condition of the inflow wind direction angle θ=270°.

[0017] Figure 7(a) is a schematic diagram of the wind turbine rows in the wind farm used for power data analysis under the operating condition of the inflow wind direction angle θ=312° in Example 1. Figure 7(b) is the normalized power of each wind turbine row under the operating condition of the inflow wind direction angle θ=312°. DETAILED DESCRIPTION

[0018] The present invention provides a method for calculating the power of a wind farm taking into account the coupling effect of additional turbulence and blocking effects, such as Figure 1 As shown, the steps include: Step 1: Obtain wind farm information and inflow wind data; Step 2: Number each wind turbine in the field in order of their orientation along the inflow wind direction; Step 3: Using the wake effect calculation model that considers the influence of additional turbulence on wake evolution, quantify the wind speed loss at each wind turbine in the field in ascending order, taking into account the additional turbulence and wake interference of other wind turbines. Combined with the wind speed change caused by the blocking effect, the effective wind speed of each wind turbine is obtained, and the thrust coefficient is obtained through interpolation calculation. Step 4: Using the effective wind speed and thrust coefficient obtained in step 3 as inputs to the blocking effect calculation model, the wind speed variation caused by the blocking effect at each wind turbine is quantified in descending order of numbers. Step 5: Based on the calculation results of step 4, update the wind speed change described in step 3 and perform iterative calculations until the difference between the wind speed changes at each wind turbine in the previous and subsequent calculations is less than the set threshold, and output the effective wind speed of each wind turbine at this time; Step 6: Based on the effective wind speed output in step 5, combined with the wind speed-aerodynamic parameter interpolation list of each wind turbine model, calculate the output power, and then obtain the wind farm power generation through summation calculation.

[0019] In step 1, the wind farm information includes the location of each wind turbine in the wind farm, the model and the hub height, rotor diameter, and wind speed-aerodynamic parameter list of the corresponding model; the inflow wind data includes the wind speed, wind direction, and turbulence intensity at the hub height of the wind turbine.

[0020] In step 2, if Figure 2 As shown, take any point in the wind farm as the coordinate origin and define the east direction as The positive direction of the axis (corresponding to a wind direction angle of 270°) and the north direction are A two-dimensional rectangular coordinate system is established in the positive direction of the axis (the corresponding wind direction angle is 180°), called the geodetic coordinate system, and the point coordinates of each wind turbine in this coordinate system are determined.

[0021] Keep the coordinate origin fixed, follow the inflow wind direction described in step 1, and rotate the coordinate system so that in the new coordinate system, that is, the relative coordinate system, The positive direction of the axis points to the inflow wind direction.

[0022] According to the coordinate transformation matrix expressed by formula (1), the point coordinates of each wind turbine in the relative coordinate system are calculated: (1) (2) in, and Represent the horizontal coordinate and vertical coordinate in the geodetic coordinate system and relative coordinate system respectively. is the inflow wind direction, It is the angle between the inflow wind direction and the positive direction of the x-axis in the geodetic coordinate system.

[0023] By comparing the horizontal coordinates of each wind turbine in the relative coordinate system, their relative positions are determined, and they are sorted and numbered accordingly. The first wind turbine is numbered 1, and the numbers of each downwind wind turbine increase one by one in sequence. Assume that the total number of wind turbines in the wind farm is , then the numbering sequence can be expressed as .

[0024] For step 3, specifically: Step 3.1: Obtain the sequence of wind speed changes caused by the "blocking effect" , where each element is numbered The wind speed variation related to the “blocking effect” at each wind turbine. The values ​​of all data elements in are set to 0.

[0025] Step 3.2: In order of the wind turbine numbers from small to large, the wind speed loss under the influence of wake interference at each wind turbine in the field is quantified in turn using the "wake effect" calculation model that takes into account the influence of additional turbulence on wake evolution. Combined with the sequence described in step 3.1, The values ​​of the corresponding elements in are used to reflect the influence of the blocking effect and calculate the effective wind speed of each wind turbine. The following is an example of the calculation for wind turbine numbered j (1≤j≤N): When j=1, it is the first wind turbine along the inflow direction. Since there are no other units in front of it, it is not affected by the wake interference, so the wind speed loss associated with it is Only the inflow wind speed Based on the wind speed, subtract the wind speed change caused by the blocking effect , the effective wind speed it perceives can be determined: (3) When j>1, it is in the upwind direction. The wind turbines are operated in the wake area, assuming that the wind turbine in the upwind direction is numbered i. In this embodiment, the linear superposition method is used to calculate the velocity loss in the overlapping area of ​​the wakes of multiple wind turbines. The wind turbine velocity loss is calculated by the following formula: Wind speed loss under the influence of wake interference : (4) Furthermore, the wind speed variation caused by the “blocking effect” is superimposed , wind turbine Effective wind speed : (5) In formula (4) Indicates the number When the upwind wind turbine is operating in isolation, its wake The speed loss at , in formula (5) In this embodiment, the wake velocity loss threshold is defined according to the one-dimensional momentum theorem, and the modified Gaussian model is used to calculate : (6) (7) (8) (9) (10) in, 、 and Represent wind turbines The effective wind speed, thrust coefficient and rotor diameter, Refers to wind turbines With wind turbines The flow spacing, Relative to wind turbine Radial distance from the center axis of the wind wheel; parameter For quantifying wind turbines The velocity loss in the wake area and its impact range vary with downstream distance, and its value is similar to that of the wind turbine. Turbulence intensity at Positive correlation, calculated as: (11) (12) in, is the turbulence intensity in the inflow, For wind turbines The perceived additional turbulence intensity caused by the operation of the upwind wind turbine. When i=1, there is no other wind turbine in the upwind direction. , and when i>1, it is assumed that the wind turbine number on the upwind side is ,but It can be calculated by referring to the following formula: (13) in, For wind turbines The swept area of ​​the wind wheel, Representatives at wind turbines Upwind wind turbines The additional turbulence intensity generated by isolated operation is The size of the place, Indicates wind turbine Isolated wake and wind turbine The overlapping area of ​​the wind wheel disk.

[0026] Since the additional turbulence intensity profile in the hub height horizontal plane in the wake area of ​​the wind turbine is approximately a bimodal Gaussian distribution, it is calculated by the following formula: : (14) in, Represents the wind turbine used for fitting The standard deviation of the bimodal Gaussian function of the additional turbulence intensity profile in an isolated wake is The size of the place, Refers to wind turbines With wind turbines The flow spacing, Relative to wind turbine The radial distance from the central axis of the wind wheel; Representative wind turbine The additional turbulence intensity generated by isolated operation is In this embodiment, the peak value at is estimated using the empirical calculation formula proposed by Crespo et al., which is commonly used in wind power engineering practice: (15) (16) in, 、 and Represent wind turbines thrust coefficient, turbulence intensity and rotor diameter.

[0027] In formula (14) is a bimodal Gaussian function used to describe the additional turbulence intensity profile, and is calculated as follows: (17) in, Represents the distance between the peak point of the additional turbulence intensity profile and its center point. Existing studies have shown that the tip vortex is an important driver of the additional turbulence intensity. Therefore, near the wind wheel disk, the peak point appears approximately at the tip of the blade. As the wake propagates downstream, due to its continuous momentum exchange with the ambient flow field, the peak point gradually moves away from the center point of the profile and expands approximately linearly with the increase of downstream distance. This is called the wake expansion characteristic. In view of this, in this embodiment, the following formula is used to estimate : (18) In formula (17) and is the weight coefficient. Considering the influence of the aforementioned wake expansion characteristics, the calculation formula is: (19) It should be noted that in this embodiment, only the Gaussian model and the linear superposition method are used as examples to calculate the velocity loss in the wake area of ​​each isolated wind turbine and to quantify the overlapping effect of the wakes of multiple wind turbines in the upwind direction. Other commonly used calculation methods in this field are also within the scope of protection of the present invention, for example, the Park model and square sum superposition method embedded in wind resource calculation software such as WAsP and WindFarmer.

[0028] Similarly, to improve the calculation accuracy of additional turbulence, in this embodiment, a more realistic bimodal Gaussian function is used to describe the additional turbulence intensity in the wake area of the wind turbine, and the influence of the wake expansion characteristic on the spatial evolution of the additional turbulence intensity is considered. This is only an example, not a limitation. Other commonly used calculation models in this field are also within the protection scope of this invention. For example, the IEC model commonly used in the current wind power engineering field, etc.

[0029] Step 3.3: Based on the effective wind speeds of each wind turbine obtained in Step 3.2 and in combination with the wind speed-aerodynamic parameter list of the corresponding model, the thrust coefficient is obtained through interpolation calculation.

[0030] The interpolation calculation of the thrust coefficient is exemplified as follows: Assume that the effective wind speed of the wind turbine numbered is , and according to the data provided by the wind turbine manufacturer, the thrust coefficient of its corresponding model at the wind speed of is , and the thrust coefficient at the wind speed of is . Then the corresponding thrust coefficient can be obtained through linear interpolation calculation, and the calculation formula and result are

[0031] Similarly, in this embodiment, only the linear interpolation method is used as an example, not a limitation. Other commonly used interpolation calculation methods in this field are also within the protection scope of this invention.

[0032] Step 3.4: Integrate the calculation results of Step 3.2 and Step 3.3 to form a sequence , , where each element corresponds to the effective wind speed and thrust coefficient of the wind turbine numbered in sequence.

[0033] The specific steps of Step 4 are as follows: Step 4.1: Using the effective wind speed and thrust coefficient calculated in Step 3 as inputs, in the order of decreasing wind turbine numbers, the "blocking effect" calculation model is used to sequentially quantify the wind speed change caused by the "blocking effect" at each wind turbine in the field. The following is an example of the calculation for the wind turbine numbered j (1 ≤ j ≤ N): When j = N, it is the last wind turbine along the inflow wind direction. Since there are no other wind turbines downstream of it, it is not affected by the "blocking effect", and the corresponding wind speed change is .

[0034] When j < N, in this embodiment, the induced velocity of all downstream wind turbines at their positions is linearly superposed to quantify the wind speed change it perceives due to the "blocking effect" , and the calculation formula is: (20) in, For wind turbines The number of the downwind wind turbine, is the correction factor, the recommended value is 1.8, Refers to the location of the wind turbine Downwind wind turbine The induced velocity generated by isolated operation is In this embodiment, the size of the vortex column is calculated by the “vortex column” model: (twenty one) in, For wind turbines The vorticity is calculated as: (twenty two) in, and Represent wind turbines The effective wind speed and thrust coefficient.

[0035] In formula (21) Used to describe wind turbines The geometric factor of the induced velocity spatial distribution is calculated as: (twenty three) in, and denote the complete elliptic integrals of the first and third kind, respectively. Refers to wind turbines With wind turbines The flow spacing, For wind turbines The diameter of the wind wheel, Relative to wind turbines Radial distance from the center axis of the wind wheel, parameter Calculated by the following formula: (twenty four) In order to quantify the impact of the ground effect, the ground plane is used as a mirror plane, and it is assumed that there is a "virtual wind turbine" below it that is of the same type and symmetrically distributed as the wind turbine above the ground plane. The induced velocity of the latter can also be calculated with reference to equations (20)-(24).

[0036] As above, in this embodiment, the "vortex column" model is only used as an example to calculate the induced velocity of each wind turbine in the field, and is not intended to be limiting. Other related calculation models are also within the scope of protection of the present invention.

[0037] Step 4.2, integrate the calculation results of step 4.1 to form a wind speed change sequence, which is the same as the sequence described in step 3.1 To differentiate, the new sequence is expressed as , where each element is numbered The change in wind speed due to the “blocking effect” at each wind turbine.

[0038] For the specific explanation of step 5, we first summarize why it is necessary to solve iteratively in order to obtain the wind farm power that takes into account the coupling effects of additional turbulence and blocking effects. According to step 4, the induced speed of the wind turbine is closely related to its own effective wind speed and thrust coefficient, and affects the wind speed change at the upwind wind turbine through the blocking effect; and from step 3, it can be seen that for any wind turbine in the field, its perceived effective wind speed must be obtained by comprehensively considering the blocking effect and wake interference of other wind turbines. Among them, the additional turbulence determines the strength of the wake interference by affecting the evolution of the wind turbine's wake, and according to equations (14)-(16), the size of the additional turbulence depends on the thrust coefficient of the wind turbine, and the latter is a function of the effective wind speed of the wind turbine. It can be seen that there is an obvious nonlinear coupling relationship between the effective wind speed, thrust coefficient, additional turbulence and induced speed, such as Figure 3 Therefore, in order to realize the calculation of wind farm power under the coupling of additional turbulence and blocking effect, iterative solution is essential.

[0039] Based on the above analysis of the mutual checks and balances among multiple key characteristic quantities that affect the flow field evolution and power generation of wind farms, the present invention proposes the following iterative calculation method. The calculation process is detailed in Figure 4 , including the following steps: Step 5.1: Continue the wind speed change sequence caused by the "blocking effect" described in steps 3 and 4 and , calculate the relative change of the data elements at each position in the two sequences (in terms of For example, a wind turbine is used to calculate ), and judge whether it is less than the preset threshold S one by one. If it is satisfied, stop the calculation and go to step 5.2. If it is not satisfied, the sequence Update Sequence , and repeat steps 3 and 4 until the convergence criteria are met Step 5.2: Output the effective wind speed of each wind turbine in the field.

[0040] The step 6 is specifically as follows: Step 6.1, based on the effective wind speed output in step 5, combined with the wind speed-aerodynamic parameter interpolation list of each wind turbine model, calculate the output power of each wind turbine. An example is as follows: Assume the number is The effective wind speed of the wind turbine is , and according to the investment data of wind turbine manufacturers, the models they belong to are The output power at wind speed is , The output power at wind speed is , then the corresponding output power can be calculated by linear interpolation, the calculation formula and result are: .

[0041] Step 6.2: The power generation of the wind farm is obtained by summing up the output power of each wind turbine in step 6.1.

[0042] The effectiveness and reliability of the present invention are illustrated below by using specific examples: The Horns Rev I wind farm is used as the research object. It contains 80 Vestas 2MW wind turbines with a rotor diameter of D = 80 m and a hub height of H = 70 m. The turbines are arranged in a very regular pattern, with 8 rows in the north-south direction and 10 columns in the east-west direction. The row spacing and column spacing are both approximately 7D.

[0043] Under the inflow conditions of wind speed of 8 m / s and turbulence intensity of 0.077 at the hub height of the wind turbine, the technical path of the present invention is adopted, the threshold S in step 5 is set to 0.001, and the following calculations are made: θ The power generation under three typical inlet wind angles of 222°, 270° and 312° was compared with the measured data, CFD simulation data and the model calculation results when the influence of additional turbulence and blocking effects was ignored.

[0044] Specifically, referring to the processing method of wind turbine power generation in Horns Rev I wind farm when obtaining measured data and CFD simulation data, Figures 5(a), 6(a) and 7(a) respectively give θWind turbine rows for power data analysis at wind angles of 222°, 270°, and 312° are represented by black dashed lines connecting multiple adjacent solid black circles. Each solid black circle represents a wind turbine. As can be seen from the figure, the number of wind turbines within each row is identical at the same wind direction. For ease of distinction and illustration, the rows are numbered according to their order and are labeled in the figure using the character "R" followed by their sequence number. For example, in Figure 5(a), there are five wind turbine rows, designated R1, R2, R3, R4, and R5. Figures 5(b), 6(b), and 7(b) show the changes in normalized power for each of the wind turbine rows shown in Figures 5(a), 6(a), and 7(a), respectively. The normalized power is defined as the ratio of the actual power of each wind turbine row to the actual power of the first row of wind turbines at the same wind direction angle. Taking the result in Figure 5(b) as an example, the normalized power of the wind turbine row indicated by "R2" is the ratio of the actual power of the row to the actual power of the wind turbine row indicated by "R1".

[0045] According to Figures 5(b), 6(b) and 7(b), under the three working conditions tested, regardless of how the inlet wind direction angle changes, the normalized power of each wind turbine row calculated based on the technical solution of the present invention is in good agreement with the measured data and CFD simulation data used as a reference, and the accuracy is significantly higher than the model calculation results when the influence of additional turbulence and blocking effects is ignored.

[0046] The technical solutions of the present invention have been described above with reference to the accompanying drawings. It will be readily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent modifications or substitutions to the relevant technical features, and such modifications or substitutions will fall within the scope of protection of the present invention.

Claims

1. A method for calculating the power of a wind farm taking into account the coupling effect of additional turbulence and blocking effect, characterized in that: The following steps are involved: Step 1: Obtain wind farm information and inflow wind data; Step 2: Number each wind turbine in the field in order of their direction of incoming wind; Step 3: In order of increasing numbers, using the wake effect calculation model that takes into account the influence of additional turbulence on wake evolution, quantify the wind speed loss of each wind turbine in the field after considering the additional turbulence and wake interference of other wind turbines, and combine the wind speed change caused by the blocking effect to obtain the effective wind speed of each wind turbine, and obtain the thrust coefficient through interpolation calculation; Step 4, using the effective wind speed and thrust coefficient in step 3 as inputs of the blocking effect calculation model, and quantifying the wind speed change caused by the blocking effect at each wind turbine in descending order of numbers; Step 5: According to the calculation result of step 4, the wind speed change amount described in step 3 is updated, and iterative calculation is performed until the difference between the wind speed change amounts at each wind turbine in the previous and subsequent calculations is less than the set threshold value, and the effective wind speed of each wind turbine at this time is output; Step 6: According to the effective wind speed output in step 5, combined with the wind speed-aerodynamic parameter interpolation list of each wind turbine model, the output power is calculated, and then the wind farm power generation is obtained through summation calculation.

2. The method for calculating the power of a wind farm taking into account the coupling effect of additional turbulence and blocking effect as claimed in claim 1, characterized in that: In step 2, take any point in the wind farm as the coordinate origin and define the due east direction as Axis positive direction, due north direction is In the positive direction of the axis, a two-dimensional rectangular coordinate system is established, called the geodetic coordinate system, and the coordinates of each wind turbine in this coordinate system are determined; Keep the coordinate origin fixed, follow the inflow wind direction in step 1, and rotate the coordinate system so that in the new coordinate system, that is, the relative coordinate system, The positive direction of the axis points to the inflow wind direction; According to the coordinate transformation matrix expressed by formula (1), the coordinates of each wind turbine in the relative coordinate system are calculated: （1） (2) in, and Represent the horizontal and vertical coordinates in the geodetic coordinate system and relative coordinate system respectively. is the inflow wind direction, is the angle between the inflow wind direction and the positive direction of the x-axis in the geodetic coordinate system; by comparing the horizontal coordinates of each wind turbine in the relative coordinate system, their front and back relative positions can be determined, and they are sorted and numbered accordingly, where the first wind turbine is numbered 1, and the numbers of each downwind wind turbine increase one by one in sequence. Suppose the total number of wind turbines in the wind farm is , then the numbering sequence is expressed as .

3. The method for calculating the power of a wind farm taking into account the coupling effect of additional turbulence and blocking effect as claimed in claim 2, characterized in that: Step 3 includes the following specific steps: Step 3.1: Obtain the sequence of wind speed changes caused by the blocking effect , The corresponding numbers are The wind speed change related to the blocking effect at each wind turbine; in the initial calculation, All values ​​are set to 0; Step 3.2: According to the order of wind turbine numbers from small to large in step 2, the wind speed loss after considering the additional turbulence and wake interference of other wind turbines at each wind turbine in the field is quantified in turn by using the wake effect calculation model that considers the influence of additional turbulence on wake evolution. Combined with the sequence described in step 3.1, middle The value of is used to reflect the influence of the blocking effect and calculate the effective wind speed at each wind turbine; Step 3.3, following the effective wind speed calculated in step 3.2, combined with the wind speed-aerodynamic parameter list of the corresponding model, obtain the thrust coefficient of each wind turbine through interpolation calculation; Step 3.4, integrate the calculation results of step 3.2 and step 3.3 to form the sequence and sequence , The corresponding numbers in the venue are The effective wind speed of the wind turbine is The corresponding numbers in the venue are The thrust coefficient of the wind turbine.

4. The method for calculating the power of a wind farm taking into account the coupling effect of additional turbulence and blocking effect as claimed in claim 3, characterized in that: Step 4 includes the following specific steps: Step 4.1, using the effective wind speed and thrust coefficient in step 3 as input, and using the blocking effect calculation model to sequentially quantify the wind speed change caused by the blocking effect at each wind turbine in the field in descending order of wind turbine numbers; Step 4.2, integrate the calculation results of step 4.1 to form a new wind speed change sequence, expressed as , The corresponding numbers calculated in step 4.1 are The wind speed change at each wind turbine.

5. The method for calculating the power of a wind farm taking into account the coupling effect of additional turbulence and blocking effect as claimed in claim 4, characterized in that: Step 5 includes the following steps: Step 5.1, calculate the wind speed change sequence and The relative change of the data element at each position in the sequence is determined one by one to see whether it is less than the set threshold; if it is satisfied, the calculation is stopped and the process goes to step 5.2; if it is not satisfied, the sequence is Update Sequence , and repeat steps 3 and 4 until the convergence criteria are met; Step 5.2: Output the effective wind speed of each wind turbine in the field.

6. The method for calculating the power of a wind farm taking into account the coupling effect of additional turbulence and blocking effect as claimed in claim 5, characterized in that: Step 6 includes the following steps: Step 6.1, according to the effective wind speed output in step 5, combined with the wind speed-aerodynamic parameter list of each wind turbine model, obtain their respective output powers through interpolation calculation; Step 6.2, by summing the output power of each wind turbine, the power generation of the wind farm is obtained.

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