Calculation Method for Annual Power Generation of Offshore Wind Farms Considering the Influence of Atmospheric Stability

Abstract

The present invention relates to a method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability, which is applicable to the technical field of wind power generation. The technical solution adopted by the present invention is as follows: determining the classification of atmospheric stability corresponding to each time period; determining the basic wind conditions corresponding to each time period under each classification of atmospheric stability; considering the influence of the wind direction vertical shear coefficient in the statistical value of the environmental flow field characteristics on the wind turbine wake, and determining the wind speed loss and additional turbulence intensity; determining the inflow wind speed based on the wind speed vertical shear coefficient; determining the turbulence intensity based on the turbulence intensity and the vertical shear coefficient of the turbulence intensity; determining the effective wind speed and effective turbulence intensity of the wind turbine based on the inflow wind speed and the turbulence intensity, in combination with the wind speed loss and additional turbulence intensity; determining the power generation of each wind turbine based on the effective wind speed of each wind turbine; and determining the annual power generation of the representative year based on the power generation of each wind turbine.

Description

Technical Field

[0001] The present invention relates to a method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability, which is applicable to the technical field of wind power generation. Background Art

[0002] The assessment of wind energy resources is of great significance for the development of wind power projects. As an important environmental flow field parameter among them, atmospheric stability has an impact that cannot be ignored. Long-term statistical data shows that on a daily time scale, atmospheric stability will show alternating cyclic changes. However, the current wind power engineering practice shows particular inadequacy in considering this important factor. When calculating the power generation of a wind farm, the dynamic changes of atmospheric stability are often ignored, and it is simply considered that the wind farm is always operating under neutral atmosphere.

[0003] Taking the widely used MeteodynWT and WAsP software in the industry as examples, they both calculate the power generation by the Park model, which only contains one input parameter, namely the wake decay coefficient, used to adjust the recovery rate of the velocity loss in the wake area of the wind turbine according to the field environment, without considering, let alone reflecting, the influence of the change of atmospheric stability on the wake. Even in the latest academic research, the influence of atmospheric stability is only simply attributed to "the difference in the recovery rate of the wind speed loss in the wake area due to the difference in turbulence intensity", ignoring the influence of other key inflow characteristic quantities that change with atmospheric stability on the evolution of the wind turbine wake.

[0004] In fact, as the atmospheric stability increases, in addition to the decrease in turbulence intensity, the vertical shear of the wind speed and wind direction profiles also increases, which will affect the wake wind field behind the wind turbine disk surface, and further affect the power generation of the downstream wind turbine. Therefore, ignoring the influence of other key inflow characteristic quantities on the evolution of the wind turbine wake in the prior art will seriously affect the accuracy of power generation calculation. Summary of the Invention

[0005] The technical problem to be solved by the present invention is: in view of the above problems, to provide a method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability.

[0006] The technical solution adopted by the present invention is: a method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability, including:

[0007] Obtain the information of the wind farm and the representative annual wind resource dataset at the representative height, where the representative annual wind resource dataset includes the wind speed, wind direction and environmental flow field characteristic quantities at each time period within the representative year, and the environmental flow field characteristic quantities include the turbulence intensity, and the vertical shear coefficients of the wind speed, wind direction and turbulence intensity;

[0008] Judge the classification of atmospheric stability corresponding to each time period, and determine the statistical values of the environmental flow field characteristic quantities under each atmospheric stability classification;

[0009] Divide the basic wind conditions based on wind speed and wind direction, determine the corresponding basic wind conditions for each time period under each atmospheric stability classification, and determine the representative wind speed and representative wind direction at the representative height for each basic wind condition;

[0010] Based on the wind farm information and the representative wind direction, considering the influence of the wind direction vertical shear coefficient in the statistical value of the environmental flow field characteristic quantity on the wind turbine wake, determine the wind speed loss and additional turbulence intensity at each discrete point on the wind turbine disk surface;

[0011] Based on the wind speed vertical shear coefficient in the statistical value of the environmental flow field characteristic quantity, combined with the representative wind speed at the representative height, determine the inflow wind speed at the vertical height where each discrete point is located; based on the turbulence intensity and turbulence intensity vertical shear coefficient in the statistical value of the environmental flow field characteristic quantity, determine the turbulence intensity at the vertical height where each discrete point is located;

[0012] Based on the inflow wind speed and turbulence intensity at the vertical height where each discrete point on the wind turbine disk surface is located, combined with the wind speed loss and additional turbulence intensity at each discrete point, determine the effective wind speed and effective turbulence intensity of the wind turbine;

[0013] Based on the effective wind speed of each wind turbine, determine the power generation of each wind turbine in each basic wind condition under each atmospheric stability classification;

[0014] Based on the power generation of each wind turbine, determine the power generation of each basic wind condition under each atmospheric stability classification, and further determine the power generation of each atmospheric stability classification and the annual power generation of the representative year.

[0015] The determination of the atmospheric stability classification corresponding to each time period includes:

[0016] Based on the temperature difference and flow wind speed difference between multiple different preset heights within each time period, calculate the flux Richardson number corresponding to each time period, and judge the atmospheric stability classification of each time period based on the flux Richardson number.

[0017] The determination of the statistical value of the environmental flow field characteristic quantity under each atmospheric stability classification includes:

[0018] Calculate the arithmetic mean of the environmental flow field characteristic quantity at the representative height for all time periods within each atmospheric stability classification, and use it as the statistical value of the environmental flow field characteristic quantity for this atmospheric stability classification.

[0019] The division of the basic wind conditions based on wind speed and wind direction includes:

[0020] Based on the wind speed - aerodynamic parameter list of each wind turbine model in the wind farm, determine the maximum and minimum values of the cut - in wind speed and cut - out wind speed, and divide multiple wind speed intervals between the maximum and minimum values;

[0021] Divide the 0-360° wind direction angle evenly and cut out multiple wind direction sectors;

[0022] Combine the wind speed intervals and wind direction sectors in pairs to form multiple basic wind conditions.

[0023] The representative wind direction and representative wind speed are the median values of the corresponding wind direction sectors and wind speed intervals of the corresponding basic wind conditions.

[0024] Based on the wind farm information and the representative wind direction, considering the influence of the wind direction vertical shear coefficient in the statistical value of the environmental flow field characteristics on the wake of the wind turbine, determine the wind speed loss and additional turbulence intensity at each discrete point on the wind turbine disk surface, including:

[0025]

[0026] Among them, is the wind speed loss at the discrete point m on the wind turbine disk surface of wind turbine i affected by the wake of the upwind wind turbine j; and D j are the effective wind speed and rotor diameter of wind turbine j respectively, and the parameter The calculation formula of is:

[0027]

[0028] Among them, H' j is the hub height of wind turbine j, y' i-m and z' i-m successively refer to the ordinate and vertical coordinate of the discrete point m of wind turbine i in the relative coordinate system with the representative wind direction as the positive x-axis direction, refers to the lateral offset of the center point of the velocity loss profile in the isolated wake of wind turbine j relative to the mid-vertical plane passing through the center point of the wind turbine j disk surface at the discrete point m on the wind turbine i disk surface, and the calculation formula is:

[0029]

[0030] Among them, x' j and x' i-m respectively represent the abscissas of wind turbine j and the discrete point m on the wind turbine i disk surface in the relative coordinate system, θ(z' i-m )-θ(H′ j ) represents the change in the wind direction angle at the vertical height z' i-m where the discrete point m is located relative to the wind direction angle at the vertical height H' j where the center point of the wind turbine j disk surface is located, and is estimated by the following formula:

[0031] θ(z′ i-m )-θ(H′ j )=Δ x (z′ i-m-H′ j )

[0032] where, Δ x the vertical wind shear coefficient under the atmospheric stability classification x;

[0033] the peak of the velocity loss profile, determined by the following formula:

[0034]

[0035] where, C Tj the thrust coefficient of wind turbine j, is the standard deviation of the Gaussian function used to describe the velocity loss profile, and the calculation formula is:

[0036]

[0037] where, k j is called the wake expansion coefficient.

[0038] Based on the wind farm information and the representative wind direction, considering the influence of the vertical wind shear coefficient in the statistical value of the environmental flow field characteristics on the wind turbine wake, determining the wind speed loss and additional turbulence intensity at each discrete point on the wind turbine disk surface, including:

[0039]

[0040] In the formula, is the additional turbulence intensity at the discrete point m on the wind turbine disk surface of wind turbine i affected by the wake of the upwind wind turbine j; is the peak of the additional turbulence intensity profile, and the calculation formula is:

[0041]

[0042] where, I j is the turbulence intensity at wind turbine j;

[0043] is the double-peak Gaussian function used to describe the additional turbulence intensity, and the calculation formula is:

[0044]

[0045] where, is the standard deviation of the additional turbulence intensity profile:

[0046]

[0047] where, is the standard deviation of the Gaussian function used to describe the velocity loss profile;

[0048] Refers to the distance between the peak point and the center point of the additional turbulence intensity profile, and is estimated by the following formula

[0049]

[0050] Where, D j Is the rotor diameter of wind turbine j;

[0051] Is used to correct the additional turbulence intensity in the area below the hub height of wind turbine j to simulate the asymmetry of its vertical distribution. The calculation formula is:

[0052]

[0053] Where, y' i-n And z' i-m Successively refer to the ordinate and vertical coordinate of the discrete point m of wind turbine i in the relative coordinate system with the representative wind direction being the positive x-axis direction, Refers to the lateral offset of the center point of the velocity loss profile in the isolated wake of wind turbine j relative to the central longitudinal plane passing through the center point of the disk of wind turbine j at the discrete point m within the disk of wind turbine i. H' j Is the hub height of wind turbine j.

[0054] Determining the inflow wind speed at the vertical height where each discrete point is located based on the vertical wind shear coefficient in the statistical value of the environmental flow field characteristic quantity and combining with the representative wind speed at the representative height includes:

[0055]

[0056] In the formula, Is the inflow wind speed at the vertical height where the discrete point m on wind turbine i is located; Is the representative wind speed corresponding to the basic wind condition Wr r ; z' i-n Refers to the vertical coordinate of the discrete point m of wind turbine i in the relative coordinate system with the representative wind direction being the positive x-axis direction; H ref Is the representative height, determined based on the hub height of the wind turbines in the wind farm; S x Is the vertical wind shear coefficient under the atmospheric stability classification x.

[0057] Determining the turbulence intensity at the vertical height where each discrete point is located based on the turbulence intensity and the vertical turbulence shear coefficient in the statistical value of the environmental flow field characteristic quantity includes:

[0058]

[0059] Where, Is the turbulence intensity at the vertical height where the discrete point m on wind turbine i is located; is the turbulence intensity under the atmospheric stability classification x; z' i-m is the vertical coordinate of the discrete point m representing the wind turbine i in the relative coordinate system with the positive x-axis as the representative wind direction; H ref is the representative height, determined based on the hub height of the wind turbine; C x is the vertical shear coefficient of the turbulence intensity under the atmospheric stability classification x.

[0060] Determining the effective wind speed and effective turbulence intensity of the wind turbine based on the inflow wind speed and turbulence intensity at the vertical heights where each discrete point on the wind turbine disk is located, and combining the wind speed loss and additional turbulence intensity at each discrete point, includes:

[0061]

[0062] Among them, is the effective wind speed of the wind turbine i, N i is the total number of discrete points belonging to the target wind turbine i, Δu i-m and I +i-m respectively represent the wind speed loss and additional turbulence intensity after considering the wake effects of all upwind wind turbines at the m-th discrete point, and successively refer to the inflow wind speed and turbulence intensity at the vertical height z' i-m where the m-th discrete point is located.

[0063] Determining the power generation of each wind turbine in each basic wind condition under each atmospheric stability classification based on the effective wind speed of each wind turbine, includes:

[0064] Based on the effective wind speed of the wind turbine, and combining with the wind speed-aerodynamic parameter list of the wind turbine model to which the wind turbine belongs, through interpolation calculation, the power generation of each wind turbine is obtained;

[0065] The wind speed-aerodynamic parameter list of each model is supplemented with aerodynamic parameters in the wind speed intervals below the cut-in wind speed and above the cut-out wind speed. In the wind speed interval below the cut-in wind speed, the thrust coefficient value is supplemented with a large value close to 1, and the power value is 0; in the wind speed interval above the cut-out wind speed, the thrust coefficient value is supplemented with a small value close to 0, and the power value is 0.

[0066] Determining the power generation of each basic wind condition under each atmospheric stability classification based on the power generation of each wind turbine, and then determining the power generation of each atmospheric stability classification and the annual power generation of the representative year, includes:

[0067] Based on the power generation of each wind turbine in the wind farm, determine the power generation of the wind farm in each basic wind condition under each atmospheric stability classification;

[0068] Based on the power generation of the wind farm under each basic wind condition for each atmospheric stability classification, and combining with the proportion of each basic wind condition under each atmospheric stability classification, determine the power generation for each atmospheric stability classification;

[0069] Based on the power generation for each atmospheric stability classification, and combining with the proportion of each atmospheric stability classification in the representative year, determine the annual power generation of the representative year;

[0070] The proportion of each basic wind condition under each atmospheric stability classification is determined based on the ratio of the time period corresponding to each basic wind condition to the time period corresponding to the respective atmospheric stability classification;

[0071] The proportion of each atmospheric stability classification in the representative year is determined based on the ratio of the time period corresponding to each atmospheric stability classification to the time period within the representative year.

[0072] A calculation device for the annual power generation of an offshore wind farm considering the influence of atmospheric stability includes:

[0073] An information acquisition module for acquiring wind farm information and a representative-year wind resource data set at the representative height, where the representative-year wind resource data set includes wind speed, wind direction, and environmental flow field characteristic quantities for each time period within the representative year, and the environmental flow field characteristic quantities include turbulence intensity, as well as the vertical shear coefficient of wind speed, wind direction, and turbulence intensity;

[0074] A stability classification module for judging the atmospheric stability classification corresponding to each time period and determining the statistical values of the environmental flow field characteristic quantities for each atmospheric stability classification;

[0075] A wind condition division module for dividing basic wind conditions based on wind speed and wind direction, determining the basic wind conditions corresponding to each time period under each atmospheric stability classification, and determining the representative wind speed and representative wind direction at the representative height for each basic wind condition;

[0076] A first calculation module for determining the wind speed loss and additional turbulence intensity at each discrete point on the wind turbine disk based on the wind farm information and the representative wind direction, considering the influence of the wind direction vertical shear coefficient in the statistical values of the environmental flow field characteristic quantities on the wind turbine wake;

[0077] A second calculation module for determining the inflow wind speed at the vertical height where each discrete point is located based on the wind speed vertical shear coefficient in the statistical values of the environmental flow field characteristic quantities and combining with the representative wind speed at the representative height; for determining the turbulence intensity at the vertical height where each discrete point is located based on the turbulence intensity and the turbulence intensity vertical shear coefficient in the statistical values of the environmental flow field characteristic quantities;

[0078] A third calculation module for determining the effective wind speed and effective turbulence intensity of the wind turbine based on the inflow wind speed and turbulence intensity at the vertical height where each discrete point on the wind turbine disk is located, combining with the wind speed loss and additional turbulence intensity at each discrete point;

[0079] A fourth calculation module, configured to determine the power generation of each wind turbine in each basic wind condition under each atmospheric stability classification based on the effective wind speed of each wind turbine;

[0080] A fifth calculation module, configured to determine the power generation of each basic wind condition under each atmospheric stability classification based on the power generation of each wind turbine, and further determine the power generation of each atmospheric stability classification and the annual power generation of the representative year.

[0081] A storage medium, on which a computer program executable by a processor is stored, and when the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability are implemented.

[0082] An offshore wind farm annual power generation calculation device, having a memory and a processor, and a computer program executable by the processor is stored on the memory, and when the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability are implemented.

[0083] The beneficial effects of the present invention are as follows:

[0084] Based on the differences in atmospheric stability and the basic wind conditions with different wind speeds and wind directions, the present invention divides the wind resource data at each time period within the representative year at the representative height, forms several data subsets, and when calculating the power generation under each data subset, comprehensively considers the turbulence intensity under the corresponding atmospheric stability, as well as the influence of key environmental flow field characteristic quantities such as the vertical shear of the wind speed, wind direction, and turbulence intensity profiles on the wake evolution of the wind turbine. Furthermore, the power generation of the wind farm under each subset is summarized and calculated to obtain the annual power generation of the wind farm.

[0085] The present invention makes a refined distinction based on atmospheric stability and basic wind conditions, and quantitatively targets the refined distinction results, which can make the calculation results better reflect the wind energy resource distribution in the field area while greatly reducing the calculation amount, and significantly improves the calculation accuracy of the annual power generation of the offshore wind farm.

[0086] The present invention considers the influence of the vertical changes of multiple key environmental characteristic quantities on the effective wind speed of the wind turbine in the power generation calculation, makes the effective wind speed of the wind turbine closer to the actual situation, and further makes the power generation calculation better reflect the actual power generation situation of the wind turbine, improving the calculation accuracy of the power generation.

[0087] The present invention determines the wind speed range based on the wind speed - aerodynamic parameter list of each wind turbine model in the wind farm, enabling each type of wind turbine in the wind farm to find the corresponding basic wind conditions. Moreover, the present invention determines the power generation of each wind turbine by separately calculating the effective wind speed of each wind turbine, and then determines the power generation of the wind farm and the annual power generation. Therefore, in addition to the single - model scenarios commonly seen in current engineering practices, the present invention is also applicable to the situation where multiple types of models are arranged in a mixed manner in the wind farm area, thus greatly expanding the scope of application of the present invention. Description of the Drawings

[0088] Figure 1 It is a flowchart of the calculation method for the annual power generation of an offshore wind farm considering the influence of atmospheric stability in the embodiment.

[0089] Figure 2 It is a flowchart of the power generation calculation of the wind farm under the basic wind conditions in the embodiment.

[0090] Figure 3 It is a schematic diagram of the discretization of the wind turbine disk plane in the embodiment.

[0091] Figure 4 It is a schematic diagram of the correspondence between the annual power generation of the wind farm considering the influence of atmospheric stability and the wind resource data set in the embodiment.

[0092] Figure 5 It is a schematic diagram of the calculation device for the annual power generation of an offshore wind farm considering the influence of atmospheric stability in the embodiment.

[0093] Figure 6 It is the vertical profiles of the incoming flow direction, wind direction, and turbulence intensity under three different atmospheric stabilities in Example 1 of the embodiment, corresponding to (a), (b), and (c) in the sub - figures respectively.

[0094] Figure 7 It is the wake velocity and additional turbulence intensity cloud maps of the NREL 5MW wind turbine under stable atmosphere in Example 1 of the embodiment, corresponding to (a) and (b) in the sub - figures respectively.

[0095] Figure 8 It is the wake velocity loss and additional turbulence intensity cloud maps of the NREL 5MW wind turbine under neutral atmosphere in Example 1 of the embodiment, corresponding to (a) and (b) in the sub - figures respectively.

[0096] Figure 9 It is the wake velocity loss and additional turbulence intensity cloud maps of the NREL 5MW wind turbine under unstable atmosphere in Example 1 of the embodiment, corresponding to (a) and (b) in the sub - figures respectively. Detailed Embodiment

[0097] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present invention and should not be construed as limiting the present invention. For the step numbers in the following embodiments, they are only set for the convenience of description and illustration, and no limitation is imposed on the order between steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0098] In the description of the present invention, "a plurality" means two or more. If the first and second are described, it is only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence of the indicated technical features. In addition, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art of this technology.

[0099] Embodiment 1: As Figure 1 shown, this embodiment is a method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability, which specifically includes the following steps:

[0100] S100. Obtain the wind farm information and the representative annual wind resource dataset at the representative height.

[0101] In this embodiment, the wind farm information includes the wind farm layout, the models of each wind turbine built-in, the rotor diameter, hub height, wind speed-aerodynamic parameter list, etc. of the models to which they belong. The wind speed-aerodynamic parameter list consists of each typical wind speed value between the cut-in wind speed and the cut-out wind speed and the corresponding power and thrust coefficients.

[0102] In this example, the representative annual wind resource datasets at multiple preset heights are obtained by processing the wind measurement data of the wind farm, where the wind measurement data should cover the wind speed, wind direction, and turbulence intensity at multiple different wind measurement heights and multiple time periods.

[0103] The processing of the wind measurement data in this embodiment includes the integrity check, rationality check of the data, as well as the elimination, interpolation, extension, and representative year correction of unreasonable data and missing measurement data.

[0104] In this example, one of the multiple preset heights that is closest to the average value of the hub heights of all models in the wind farm is used as the representative height H ref . This embodiment divides the representative annual wind resource dataset into hourly time periods, a total of 8760 time periods. The wind resource data corresponding to each time period should cover the wind speed, wind direction, and environmental flow field characteristic quantities. The environmental flow field characteristic quantities include the turbulence intensity, as well as the vertical shear coefficients of the wind speed, wind direction, and turbulence intensity.

[0105] In this example, the vertical shear coefficient of the wind speed can be obtained by fitting an exponential function based on the wind speed difference between two different vertical heights z1 and z2:

[0106]

[0107] where v1 and v2 respectively represent the wind speed magnitudes at the corresponding heights z1 and z2.

[0108] In this embodiment, the vertical shear coefficient of the wind direction can be calculated by a linear fitting method based on the wind direction difference between two different heights z1 and z2:

[0109]

[0110] where θ1 and θ2 are respectively the wind direction angles at the corresponding heights z1 and z2.

[0111] The vertical shear coefficient of the turbulence intensity can be calculated by an exponential fitting method based on the turbulence intensity difference between two different heights z1 and z2:

[0112]

[0113] where I 01 and I 02 are respectively the turbulence intensities at the corresponding heights z1 and z2.

[0114] For the heights z1 and z2, to ensure the reliability and representativeness of the data fitting results, it is recommended to select two heights from the aforementioned multiple different heights that satisfy the following constraint conditions:

[0115] z1 < H ref < z2 (4)

[0116] z1 < min(H1, H2, …, H t , …, H T ) (5)

[0117] z2 > max(H1, H2, …, H t , …, H T ) (6)

[0118] where T represents the number of turbine models in the wind farm, and H t is the hub height of the t-th turbine model.

[0119] It should be noted that in this embodiment, only the exponential fitting and linear fitting methods are used as examples, and other data fitting methods that can be used to describe the vertical profile changes of wind speed, wind direction, and turbulence intensity are also within the protection scope of the present invention.

[0120] S200. Determine the atmospheric stability classification corresponding to each time period, and determine the statistical values of the environmental flow field characteristic quantities under each atmospheric stability classification.

[0121] S210. In this embodiment, based on the temperature difference and the flow direction wind speed difference between multiple different preset heights within each time period, calculate the flux Richardson number corresponding to each time period, and judge the atmospheric stability classification of each time period based on the flux Richardson number. The atmospheric stability classification includes stable, neutral, and unstable atmospheres.

[0122] The judgment of the atmospheric stability classification of each time period based on the flux Richardson number is specifically as follows: When the flux Richardson number R i > 0, it corresponds to a stable atmosphere; R i = 0, corresponding to a neutral atmosphere; when R i < 0, it corresponds to an unstable atmosphere.

[0123] The flux Richardson number R i , can be calculated according to the temperature difference and the wind speed difference between two different heights. The calculation formula is:

[0124]

[0125] where g is the acceleration due to gravity, average absolute temperature, ΔT and are the temperature difference and the flow direction wind speed difference between heights z3 and z4 respectively, and γ d dry adiabatic lapse rate.

[0126] In this embodiment, according to the atmospheric stability classification corresponding to each time period, the representative annual wind resource data set at the representative height is divided into 3 data sets, corresponding to stable, neutral, and unstable atmospheres respectively. Within each data set, the data under each time period is consistent with that in the representative annual wind resource data set, and all include the wind speed, wind direction, turbulence intensity at the representative height, and the vertical shear coefficients of wind speed, wind direction, and turbulence intensity.

[0127] S220. Based on the data set divided according to the atmospheric stability classification, calculate the ratio of the number of time periods included in the data set corresponding to each atmospheric stability classification to the number of time periods in the representative annual wind resource data set, and determine the proportion of each atmospheric stability classification in the representative year.

[0128] For the convenience of distinction, in this embodiment, it is uniformly represented by f s , f n and f u to represent the proportions of stable, neutral, and unstable atmospheres. s, n, and u represent stable, neutral, and unstable atmospheres respectively. According to the definition, obviously: f s + f n + f u = 1.

[0129] S230. In this embodiment, by calculating the arithmetic mean of each environmental flow field characteristic quantity in all time periods of the data subset corresponding to each atmospheric stability classification, the statistical values of each environmental flow field characteristic quantity under each atmospheric stability classification are obtained, including the statistical value of the turbulence intensity, and the statistical values of the vertical shear coefficients of the wind speed, wind direction, and turbulence intensity.

[0130] For convenience of distinction, in this embodiment, it is uniformly represented by the statistical values of the turbulence intensity at the representative height under stable, neutral, and unstable atmospheres, as well as the vertical shear coefficients of the wind speed, wind direction, and turbulence intensity.

[0131] S300. Based on the wind speed and wind direction, the basic wind conditions are divided, the basic wind conditions corresponding to each time period under each atmospheric stability classification are determined, and the representative wind speed and representative wind direction at the representative height under each basic wind condition are determined.

[0132] S310. Based on the wind speed-aerodynamic parameter list of each wind turbine model in the wind farm, the maximum and minimum values of the cut-in wind speed and cut-out wind speed are determined, and multiple wind speed intervals are segmented between the maximum and minimum values.

[0133] Traverse the wind speed-aerodynamic parameter list of each model in the wind farm obtained in step S100 to determine the minimum value V min and the maximum value V max of the wind speed data therein, and perform floor(V min ) and ceil(V max ) processing on them respectively. Then, taking floor(V min ) and ceil(V max ) as the lower and upper limits, multiple distinct wind speed intervals are segmented according to the set wind speed calculation interval ΔV. According to the definition, the total number N ws of the wind speed intervals = (ceil(V max ) - floor(V min )) / ΔV, where the p-th wind speed interval can be expressed as [floor(V min ) + (p - 1)·ΔV, floor(V min ) + p·ΔV].

[0134] It is recommended that the wind speed calculation interval ΔV does not exceed the difference between adjacent wind speeds in the wind speed-aerodynamic parameter list of any model.

[0135] S320. According to the set number N wd of wind direction sectors, the 0-360° wind direction angle is evenly divided to segment multiple distinct wind direction sectors.

[0136] According to the definition, the size of each wind direction sector is Δθ = 360° / Nwd 。If 0° is taken as the middle value of the first wind direction sector, the q-th wind direction sector can be expressed as: [(q - 0.5)·Δθ, (q + 0.5)·Δθ]; referring to the conventional practice in wind power engineering, this embodiment recommends that N wd takes a value of 12 or 16.

[0137] S330. Combine the respective wind speed intervals and wind direction sectors obtained by dividing in steps S310 and S320 pairwise, thereby obtaining a plurality of distinct basic wind conditions. According to the definition, the total number of basic wind conditions is N wr = N ws ·N wd , and the corresponding number sequence can be expressed as where WR r refers to the r-th basic wind condition.

[0138] S340. Continuing with the data sets for each atmospheric stability classification in step S200, based on the wind speed and wind direction of each time period in the data sets for each atmospheric stability classification, and comparing with the wind speed and wind direction corresponding to the basic wind conditions in step S330, determine the basic wind conditions to which each time period belongs under each atmospheric stability classification.

[0139] S350. Based on the number of time periods of each basic wind condition under each atmospheric stability classification, determine the proportion of each basic wind condition under each atmospheric stability classification.

[0140] By statistically calculating the ratio of the number of time periods within each basic wind condition to the number of time periods within the data subset, the proportion of each basic wind condition under different atmospheric stabilities can be obtained, and the corresponding sequence can be expressed as where, refers to the proportion of the r-th basic wind condition WR r under the atmospheric stability corresponding to the superscript x.

[0141] It should be particularly mentioned that since the power generation of the wind turbine is 0 when the wind speed is lower than the cut-in wind speed or higher than the cut-out wind speed, there may be some time periods in each data subset corresponding to different atmospheric stabilities that do not belong to all the basic wind conditions listed in step S330. This means that when summing the proportions of each basic wind condition under a certain atmospheric stability, the sum value may be less than 1, that is, there is Nevertheless, as mentioned before, this result is reasonable.

[0142] S360. Based on the middle values of the wind direction sectors and wind speed intervals corresponding to each basic wind condition, determine the representative wind direction and representative wind speed

[0143] S400. Based on the wind farm information, combined with the representative wind speeds, representative wind directions of each basic wind condition under each atmospheric stability classification, and the statistical values of each environmental flow field characteristic quantity, calculate the power generation of each basic wind condition under each atmospheric stability classification, and then calculate the power generation of each atmospheric stability classification and the annual power generation.

[0144] For each basic wind condition obtained by the division in step S300, considering the differences in atmospheric stability classification, select one of them and calculate the power generation of the wind farm. Here, take the basic wind condition WR with the number r r For example, Figure 2 The flowchart for calculating the power generation of the wind farm when the atmospheric stability is x (x ∈ [s, n, u]) is given as follows:

[0145] S410. For the wind speed-aerodynamic parameter list of each wind turbine model in the wind farm obtained in step S100, supplement the aerodynamic parameters in the wind speed intervals below the cut-in wind speed and above the cut-out wind speed.

[0146] When the wind speed is lower than the cut-in wind speed or higher than the cut-out wind speed, the wind turbine does not operate. Therefore, in wind power engineering practice, referring to the data provided by the whole machine manufacturer, the wind speed-aerodynamic parameter list of each model obtained in step S100 usually only covers the aerodynamic parameters at each typical wind speed between the cut-in wind speed and the cut-out wind speed. When there are multiple types of models in the wind farm, for different models, their cut-in wind speeds and cut-out wind speeds often vary, which may cause the wind speeds sensed by some models in some of the basic wind conditions obtained by the division in step 4 to be outside the wind speed interval covered by the wind speed-aerodynamic parameter list obtained in step S100. Affected by this, in subsequent steps, when performing interpolation calculations of aerodynamic parameters based on the wind speed magnitude, calculation overflow errors will occur.

[0147] In view of this, for the wind speed-aerodynamic parameter list corresponding to each model obtained in step S100, it is necessary to supplement the aerodynamic parameters in the wind speed intervals below the cut-in wind speed and above the cut-out wind speed. In this embodiment, it is recommended that in the wind speed interval below the cut-in wind speed, the thrust coefficient takes a large value close to 1, such as 0.9999, and the power takes 0; while in the wind speed interval above the cut-out wind speed, the thrust coefficient takes a small value close to 0, such as 0.0001, and the power takes 0.

[0148] S420. Integrate the inflow data of each basic wind condition under each atmospheric stability classification. The inflow data includes the representative wind direction and representative wind speed as well as the statistical values of the environmental flow field characteristic quantities under the corresponding atmospheric stability classification.

[0149] S430. According to the along the representative wind direction According to the front - rear order, number each wind turbine in the wind farm. Among them, set the number of the first wind turbine as 1, and the numbers of other down - wind wind turbines increase sequentially one by one.

[0150] In this embodiment, assume that the total number of wind turbines in the wind farm is N wt , then the number sequence can be expressed as 1, 2, …, j, …, i, …, N wt}}.

[0151] In this embodiment, according to the representative wind direction, rotate the earth coordinate system so that in the new relative coordinate system, the positive direction of the x - axis of the relative coordinate system points to the representative wind direction. According to the coordinates of each wind turbine in the wind farm in the earth coordinate system and the transformation matrix, calculate their coordinates in the relative coordinate system, and then determine the front - rear order along the representative wind direction by comparing the abscissa values in the relative coordinate system.

[0152] For the earth coordinate system, take any point in the wind farm as the coordinate origin, the due - east direction (corresponding to the wind direction angle of 270°) as the positive direction of the x - axis, and the due - north direction (corresponding to the wind direction angle of 180°) as the positive direction of the y - axis to establish a two - dimensional rectangular coordinate system.

[0153] For the transformation matrix, the calculation formula is:

[0154]

[0155] z' = z (9)

[0156] Among them, x, y, z and x', y', z' represent the abscissa, ordinate and vertical coordinate in the earth coordinate system and the relative coordinate system in sequence.

[0157] According to the wind farm layout obtained in step S100, the coordinates of each wind turbine in the established earth coordinate system can be determined. After transformation processing, corresponding to their number sequence, the following coordinate sequence containing the coordinate values of each wind turbine in the relative coordinate system can be integrated Among them, x' i , y' i , H' i respectively represent the abscissa, ordinate and vertical coordinate with the value of the hub height of the wind turbine numbered i in the relative coordinate system.

[0158] S440: Use the inflow data in step S420 as the input of the analysis model, and calculate the effective wind speed and thrust coefficient of each wind turbine in turn according to the order of the numbers from small to large in S430.

[0159] Since the velocity loss in the wake area of an upwind wind turbine will directly affect the wind speed perceived by the downstream wind turbine, and the additional turbulence intensity generated by the operation of the wind turbine will indirectly affect the former by influencing the recovery of the velocity loss in the wake area. Therefore, when evaluating the wake effect and calculating the power generation of a wind farm based on an analytical model, accurately simulating the above two key wake characteristic quantities is the core and key.

[0160] In the analytical model used in this embodiment, the influence of multiple key inflow characteristic quantities (turbulence intensity, and the vertical shear of wind speed, wind direction, and turbulence intensity) varying with atmospheric stability on wake evolution is scientifically quantified.

[0161] S441. As shown in Figure 3 , discretize the wind turbine disk of the target wind turbine i to generate a number of discrete points located on the wind turbine disk, and calculate the coordinates of each discrete point in the relative coordinate system according to the transformation matrices in equations (8) and (9). Let the total number of discrete points belonging to the target wind turbine i be N i , then the discrete point coordinate set in the following form can be integrated

[0162]

[0163] where, (x' i-1 , y' i-1 , z' i-1 ) represents the coordinates of discrete point 1 on wind turbine i. Similarly, (x' i-m , y' i-m , z' i-m ) represents the coordinates of discrete point m on wind turbine i.

[0164] S442. Based on the wind farm information and the representative wind direction, considering the influence of the vertical shear coefficient of the wind direction in the statistical values of the environmental flow field characteristics on the wind turbine wake, determine the wind speed loss and additional turbulence intensity at each discrete point on the wind turbine disk.

[0165] The following takes the wind turbine numbered i in the wind farm as an example:

[0166] When the number i of the target wind turbine is 1, since there is no other wind turbine upwind, the wind speed loss and additional turbulence increment caused by wake interference at each discrete point in its wind turbine disk are both 0. Taking the discrete point numbered m as an example,

[0167] The calculation formula for wind speed loss is:

[0168] Δu i-m = 0 (10)

[0169] The calculation formula for additional turbulence increment is:

[0170] I +i-m= 0 (11)

[0171] When the number of the target wind turbine is i > 1, the interference effect of the wake of the upwind wind turbine needs to be considered. Compared with the "top hat distribution" assumption commonly used in current wind power projects, in this embodiment, based on a large number of measured data and high-precision CFD simulation data, the more realistic Gaussian function and double-peak Gaussian function are respectively used to describe the velocity loss and additional turbulence intensity in the wake area of the wind turbine. Furthermore, considering the turbulence intensity varying with atmospheric stability, as well as multiple key environmental flow field characteristic quantities such as wind speed, wind direction, and vertical shear of turbulence intensity on the wake evolution described in step S300, calculate the velocity loss and additional turbulence increment at each discrete point in the rotor disk plane of the target wind turbine i for the isolated wake of any upwind wind turbine j (j < i). Here, still taking the discrete point numbered m as an example.

[0172] When the number of the target wind turbine i > 1, the wind speed loss and additional turbulence intensity at each discrete point on the rotor disk are calculated as follows:

[0173] ① The velocity loss is determined by the following formula:

[0174]

[0175] Among them, and D j are the effective wind speed and rotor diameter of wind turbine j respectively. Considering that the wind direction is the most important external driver affecting the wake propagation direction, and combining with the different degrees of vertical wind shear in the inflow under different atmospheric stabilities, the parameter is calculated by the formula:

[0176]

[0177] Among them, H' j is the hub height of wind turbine j, y' i-m and z' i-m successively refer to the ordinate and vertical coordinate of the discrete point m of wind turbine i in the relative coordinate system described in step 5.3. refers to the lateral offset of the center point of the velocity loss profile in the isolated wake of wind turbine j relative to the mid-longitudinal plane passing through the center point of the rotor disk of wind turbine j at the discrete point m in the rotor disk plane of wind turbine i, and the calculation formula is:

[0178]

[0179] Among them, x' j and x' i-m respectively represent the abscissas of the discrete point m in the rotor disk planes of wind turbine j and wind turbine i in the relative coordinate system, θ(z' i-m ) - θ(H′ j ) represents the vertical height z' where the discrete point m is located.i-m The wind direction angle at j relative to the vertical height H' of the center point of the wind turbine j's rotor disk

[0180] θ(z' i-m ) - θ(H′ j ) = Δ x (z' i-m - H' j ) (15)

[0181] where, Δ x with the superscript x referring to the atmospheric stability, which can be correspondingly selected from Δ s , Δ n , Δ u described in step 3.

[0182] In formula (12), is the peak value of the velocity loss profile, and its threshold is limited according to the one-dimensional momentum theorem. In this embodiment, it is determined by the following formula:

[0183]

[0184] where, C Tj is the thrust coefficient of wind turbine j, is the standard deviation of the Gaussian function used to describe the velocity loss profile, and the calculation formula is:

[0185]

[0186] where, k j is called the wake expansion coefficient. Research shows that its value is positively correlated with the turbulence intensity at wind turbine j (when j = 1, only the turbulence intensity in the inflow can be considered, and when j > 1, it includes both the turbulence intensity in the inflow and the additional turbulence intensity generated by the operation of the upwind wind turbine). When the turbulence intensity is greater, due to the more intense momentum exchange between the wake and the ambient flow field, as the distance from the rotor disk increases, the outward expansion rate of the wake influence area and the recovery rate of the wind speed loss inside it are also greater. Correspondingly, the value of k j should also be greater.

[0187] ② The additional turbulence intensity is determined by the following formula:

[0188]

[0189] In formula (20), is the peak value of the additional turbulence intensity profile, and the calculation formula is:

[0190]

[0191] where, Ij is the turbulence intensity at wind turbine j.

[0192] In Equation (20), is a bimodal Gaussian function used to describe the additional turbulence intensity, and its calculation formula is:

[0193]

[0194] where is the standard deviation of the additional turbulence intensity profile. At the same downstream position behind the rotor disk plane, it satisfies the following relationship with the standard deviation of the velocity loss profile in Equation (17):

[0195]

[0196] In Equation (23), refers to the distance between the peak point and the center point of the additional turbulence intensity profile. Since the tip vortex is an important driver for inducing the additional turbulence intensity, in the near wake region close to the rotor disk plane, the value of is approximately equal to the rotor radius. Further considering the influence of the wake expansion effect on the position of the peak point of the profile in the far wake region, in this embodiment, the following formula is used to estimate

[0197]

[0198] In Equation (20), is used to correct the additional turbulence intensity in the area below the hub height of wind turbine j to simulate the asymmetry of its vertical distribution. The calculation formula is:

[0199]

[0200] In this embodiment, based on the velocity loss and additional turbulence intensity at the discrete point m on wind turbine i caused by the isolated wakes of the upwind wind turbines, the wind speed loss and additional turbulence increment at the discrete point m on wind turbine i are calculated.

[0201] When its number is i > 1 and there are wind turbines upwind, to quantify the superimposed influence of the wake interference of multiple upwind wind turbines, in this embodiment, the linear superposition method and the maximum value method are respectively used to calculate the velocity loss and additional turbulence intensity in the wake overlap region, and the wind speed loss and additional turbulence increment at each discrete point within the rotor disk plane of the target wind turbine i are estimated therefrom. Here, still taking the discrete point numbered m as an example,

[0202] The calculation formula for the wind speed loss is:

[0203]

[0204] The calculation formula for the additional turbulence increment is:

[0205]

[0206] Among them, and respectively represent the velocity loss and additional turbulence intensity of the isolated wake of wind turbine j at the m-th discrete point.

[0207] S443. Based on the vertical wind speed shear coefficient in the statistical value of the environmental flow field characteristics, combined with the representative wind speed at the representative height, determine the inflow wind speed at the vertical height where each discrete point is located; based on the turbulence intensity and the vertical wind speed shear coefficient of the turbulence intensity in the statistical value of the environmental flow field characteristics, determine the turbulence intensity at the vertical height of each discrete point.

[0208]

[0209] Among them, and successively refer to the inflow wind speed and turbulence intensity at the vertical height z' i-m where the m-th discrete point is located, is the representative wind speed WR r corresponding to the target basic wind condition, S x is the vertical wind speed shear coefficient under the atmospheric stability classification x, is the turbulence intensity under the atmospheric stability classification x, C x is the vertical wind speed shear coefficient of the turbulence intensity under the atmospheric stability classification x.

[0210] S444. Based on the inflow wind speed and turbulence intensity at the vertical height of each discrete point on the wind turbine disk surface, combined with the wind speed loss and additional turbulence intensity at each discrete point, determine the effective wind speed and effective turbulence intensity of the wind turbine.

[0211] Considering the vertical shear effect of the wind speed and turbulence intensity in the inflow, determine the wind speed and turbulence intensity of each discrete point in the wind turbine disk surface of the target wind turbine i, and then through calculating the average value, the effective wind speed and effective turbulence intensity I i can be obtained:

[0212]

[0213] Among them, N i is the total number of discrete points belonging to the target wind turbine i, Δu i-m and I +i-m respectively represent the wind speed loss and additional turbulence intensity after considering the wake effects of all upwind wind turbines at the m-th discrete point, referring to step S442.

[0214] S445. According to the effective wind speed Combined with the wind speed - aerodynamic parameter list of its corresponding model, through interpolation calculation, the thrust coefficient C of the target wind turbine i can be obtained Ti :

[0215]

[0216] wherein, and respectively correspond to the two wind speeds in the wind speed - aerodynamic parameter list of the model to which the target wind turbine i belongs that are closest to , satisfying and C Tp and C Tq are the thrust coefficients corresponding to and in the list

[0217] Considering that there is a strong correlation between the turbulence intensity at the wind turbine and the expansion rate of the wake influence range and the recovery rate of wind speed loss behind its disk, in this embodiment, according to the effective turbulence intensity I i at the target wind turbine i, the expansion coefficient k i used for the wake calculation of this wind turbine is determined with reference to the following formula

[0218] k i = k a I i + k b (36)

[0219] wherein, k a and k b are adjustable parameters. Referring to past research, the recommended values in this embodiment are 0.38 and 0.004

[0220] S450. Based on the effective wind speeds of each wind turbine, determine the power generation of each wind turbine in each basic wind condition under each atmospheric stability classification

[0221] According to the effective wind speeds of each wind turbine, combined with the wind speed - aerodynamic parameter list of their respective models, through interpolation calculation, the power generation of each wind turbine can be obtained

[0222]

[0223] wherein, P i is the power generation of the wind turbine numbered i, and respectively correspond to the two wind speeds in the wind speed - aerodynamic parameter list of the model to which the wind turbine i belongs that are closest to , satisfying and P p and P q are the corresponding and Power.

[0224] S460. Determine the power generation of each basic wind condition under each atmospheric stability classification based on the power generation of each wind turbine, and then determine the power generation of each atmospheric stability classification and the annual power generation of the representative year.

[0225] S461. Determine the wind farm power generation of each basic wind condition under each atmospheric stability classification based on the power generation of each wind turbine in the wind farm.

[0226] In this embodiment, based on the target basic wind condition WR r The power generation of each wind turbine in the wind farm under the target basic wind condition WR when the atmospheric stability is x can be obtained by summing. r The wind farm power generation under

[0227]

[0228] Among them, N wt is the total number of wind turbines in the wind farm, and P i is the power generation of the wind turbine numbered i.

[0229] S462. Determine the power generation of each atmospheric stability classification by combining the wind farm power generation of each basic wind condition under each atmospheric stability classification with the proportion of each basic wind condition under each atmospheric stability classification.

[0230] Figure 4 The corresponding relationship between atmospheric stability, basic wind condition, and wind farm power generation is given. Among them, the average power generation of each time period of the wind farm under stable, neutral, and unstable atmospheres can be calculated by the following formulas respectively:

[0231]

[0232] Among them, and successively represent the proportion of the rth basic wind condition under stable, neutral, and unstable atmospheres and the corresponding wind farm power generation.

[0233] S463. Determine the annual power generation of the representative year by combining the power generation of each atmospheric stability classification with the proportion of each atmospheric stability classification in the representative year.

[0234] The annual power generation P of the wind farm is calculated according to the following formula tot :

[0235]

[0236] Among them, A is the number of time periods in the representative year. In this example, A = 8760, f s , fn and f u represent the proportions of stable, neutral, and unstable atmospheres within a year respectively, and f s + f n + f u = 1.

[0237] Example 2: As Figure 5 shown, this example is a device for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability, including an information acquisition module, a stability classification module, a wind condition division module, and first to fifth calculation modules.

[0238] In this example, the information acquisition module is used to acquire wind farm information and the representative annual wind resource dataset at the representative height. This representative annual wind resource dataset includes the wind speed, wind direction, and environmental flow field characteristic quantities at each time period within the representative year. Among them, the environmental flow field characteristic quantities include the turbulence intensity, as well as the vertical shear coefficients of the wind speed, wind direction, and turbulence intensity.

[0239] The stability classification module is used to judge the atmospheric stability classification corresponding to each time period and determine the statistical values of the environmental flow field characteristic quantities under each atmospheric stability classification.

[0240] The wind condition division module is used to divide the basic wind conditions based on the wind speed and wind direction, determine the basic wind conditions corresponding to each time period under each atmospheric stability classification, and determine the representative wind speed and representative wind direction at the representative height under each basic wind condition.

[0241] The first calculation module is used to consider the influence of the wind direction vertical shear coefficient in the statistical values of the environmental flow field characteristic quantities on the wind turbine wake based on the wind farm information and the representative wind direction, and determine the wind speed loss and additional turbulence intensity at each discrete point on the wind turbine disk.

[0242] The second calculation module is used to determine the inflow wind speed at the vertical height where each discrete point is located based on the wind speed vertical shear coefficient in the statistical values of the environmental flow field characteristic quantities and combine it with the representative wind speed at the representative height; it is used to determine the turbulence intensity at the vertical height where each discrete point is located based on the turbulence intensity and the turbulence intensity vertical shear coefficient in the statistical values of the environmental flow field characteristic quantities.

[0243] The third calculation module is used to determine the effective wind speed and effective turbulence intensity of the wind turbine based on the inflow wind speed and turbulence intensity at the vertical height where each discrete point on the wind turbine disk is located, and combine the wind speed loss and additional turbulence intensity at each discrete point.

[0244] The fourth calculation module is used to determine the power generation of each wind turbine in each basic wind condition under each atmospheric stability classification based on the effective wind speed of each wind turbine.

[0245] The fifth calculation module is used to determine the power generation of each basic wind condition under each atmospheric stability classification based on the power generation of each wind turbine, and further determine the power generation of each atmospheric stability classification and the annual power generation of the representative year.

[0246] Embodiment 3: This embodiment is a storage medium on which a computer program executable by a processor is stored. When the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability in Embodiment 1 are implemented.

[0247] Embodiment 4: This embodiment is an offshore wind farm annual power generation calculation device, which has a memory and a processor. A computer program executable by the processor is stored on the memory. When the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm considering the influence of atmospheric stability in Embodiment 1 are implemented.

[0248] The following is illustrated with a specific example:

[0249] Example 1: The wake effect is a decisive factor affecting the power generation of an offshore wind farm, and the accurate calculation of the wake of any isolated operating wind turbine in the field is the core and key among them. In Example 1, a single NREL 5MW wind turbine was used as the research object. Under the wind conditions with representative wind speeds and directions of 8 m / s and 270° respectively, the wind turbine wake simulation data based on high-precision CFD simulation was used as the reference benchmark to test the reliability of using the model method of the present invention for calculating the wind turbine wake wind field under stable, neutral, and unstable atmospheres. Since in real wind farms such as Horns Rev I and Nysted, which are commonly used as standard models, the distance between adjacent rows of wind turbines is about 7 times the rotor diameter (hereinafter referred to as D by D), a vertical section 7D behind the rotor disk plane was also selected as the representative section here, and the model calculation results under different atmospheric stabilities were compared with the CFD simulation data.

[0250] Figure 6 The vertical profiles of the incoming flow wind speed, wind direction, and turbulence intensity under three different atmospheric stabilities obtained based on CFD simulation are shown, and the calculation results of their vertical shear coefficients are summarized in Table 1.

[0251] Table 1

[0252] Atmospheric stability Stable Neutral Unstable Turbulence intensity at the representative height 0.046 0.06 0.084 Vertical shear coefficient of wind speed 0.257 0.133 0.031 Vertical shear coefficient of wind direction -0.072 -0.019 -0.003 Vertical shear coefficient of turbulence intensity -0.406 -0.227 -0.199

[0253] In view of the fact that the mainstream commercial calculation software in current wind power projects, such as WAsP, MeteodynWT, etc., all use the Park model as the development kernel and use the IEC model to calculate the additional turbulence intensity of wind turbines, so Figures 7 - 9Among them, in addition to the model method of the present invention, the calculation results of the above two representative models are also compared. As can be seen from the figure, regardless of how the atmospheric stability changes, the present invention can accurately simulate the spatial distributions of the two key characteristic quantities, namely the wind speed and the additional turbulence intensity, in the wake area of the wind turbine, which is in good agreement with the high-precision CFD simulation results used as a reference, and the calculation accuracy is significantly higher than that of the commonly used model methods.

[0254] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order mentioned in the operation diagrams. For example, depending on the functions / operations involved, two consecutive blocks shown may actually be executed substantially simultaneously or the above-mentioned blocks can sometimes be executed in the reverse order. In addition, the embodiments presented and described in the flowcharts of the present invention are provided by way of example for the purpose of providing a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented herein. Alternative embodiments are foreseeable, in which the order of various operations is changed and the sub-operations described as part of a larger operation are executed independently.

[0255] Furthermore, although the present invention has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the above functions and / or features may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It can also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. More precisely, considering the attributes, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the modules will be understood within the ordinary skills of an engineer. Therefore, those skilled in the art can implement the present invention as set forth in the claims without undue experimentation. It can also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0256] If the above functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the above-mentioned methods in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs, Read-Only Memories), random access memories (RAMs, Random Access Memories), magnetic disks, or optical discs.

[0257] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or used in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0258] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection part with one or more wirings (electronic device), a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the above program can be printed, because the above program can be obtained electronically, for example, by optically scanning the paper or other media, then editing, interpreting, or otherwise processing it as appropriate, and then storing it in a computer memory.

[0259] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0260] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0261] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the claims and their equivalents.

[0262] The above is a specific description of the preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present invention, and these equivalent deformations or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability, characterized in that: include: Obtain wind farm information and a representative annual wind resource data set at a representative height, wherein the representative annual wind resource data set includes wind speed, wind direction and environmental flow field characteristic quantities representing each period of the year, wherein the environmental flow field characteristic quantities include turbulence intensity and vertical shear coefficients of wind speed, wind direction and turbulence intensity; Determine the atmospheric stability classification corresponding to each time period, and determine the statistical value of the environmental flow field characteristic quantity under each atmospheric stability classification; Divide the basic wind conditions based on wind speed and wind direction, determine the basic wind conditions corresponding to each period under each atmospheric stability classification, and determine the representative wind speed and representative wind direction at the representative height under each basic wind condition; Based on wind farm information and representative wind direction, the wind speed loss and additional turbulence intensity at each discrete point on the wind rotor disk are determined by considering the influence of the vertical shear coefficient of wind direction in the statistical value of the characteristic quantity of the environmental flow field on the wind turbine wake. Based on the vertical shear coefficient of wind speed in the statistical value of the characteristic quantity of the environmental flow field and the representative wind speed at the representative height, the inflow wind speed at the vertical height of each discrete point is determined; Based on the turbulence intensity and the vertical shear coefficient of turbulence intensity in the statistical values ​​of the characteristic quantities of the environmental flow field, the turbulence intensity at the vertical height of each discrete point is determined; Based on the inflow wind speed and turbulence intensity at the vertical height of each discrete point on the wind rotor disk, combined with the wind speed loss and additional turbulence intensity at each discrete point, the effective wind speed and effective turbulence intensity of the wind turbine are determined; Based on the effective wind speed of each wind turbine, determine the power generation of each wind turbine in each basic wind condition under each atmospheric stability classification; Based on the power generation of each wind turbine, determine the power generation of each basic wind condition under each atmospheric stability classification, and then determine the power generation of each atmospheric stability classification and the annual power generation of a representative year; The method is based on wind farm information and representative wind direction, taking into account the influence of the vertical shear coefficient of wind direction in the statistical value of the characteristic quantity of the environmental flow field on the wind turbine wake, and determining the wind speed loss and additional turbulence intensity at each discrete point on the wind rotor disk surface, including: in, is the wind speed loss at discrete point m on the rotor disk of wind turbine i affected by the wake of upwind wind turbine j; and D j are the effective wind speed and rotor diameter of wind turbine j respectively, and the parameters The calculation formula is: Among them, H' j is the hub height of wind turbine j, y' i-m and z' i-m The ordinate and vertical coordinates of the discrete point m of wind turbine i in the relative coordinate system with the wind direction as the positive direction of the x-axis are respectively referred to as: It refers to the lateral displacement of the center point of the velocity loss profile in the isolated wake of wind turbine j at the discrete point m within the disk of wind turbine i relative to the mid-longitudinal plane passing through the center point of the disk of wind turbine j. y' is the ordinate of wind turbine j in the relative coordinate system. The calculation formula is: Among them, x' j and x' i-m represents the horizontal coordinates of the discrete point m in the disk of wind turbine j and wind turbine i in the relative coordinate system, θ(z' i-m )-θ(H' j ) represents the vertical height z' of the discrete point m i-m The wind direction angle at the wind turbine j is relative to the vertical height H' of the center point of the wind turbine rotor disk. j The change in wind direction angle at is estimated by the following formula: θ(z′ i-m )-θ(H′ j )=D x (z′ i-m -H′ j ); Among them, Δ x is the vertical shear coefficient of wind direction under atmospheric stability classification x; is the peak value of the velocity loss profile, determined by the following formula: Among them, C Tj is the thrust coefficient of wind turbine j, is the standard deviation of the Gaussian function used to describe the velocity loss profile, D j is the rotor diameter of wind turbine j, and the calculation formula is: Among them, k j It is called the wake expansion coefficient.

2. The method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1, characterized in that: The atmospheric stability classification corresponding to each time period is determined, including: Based on the temperature difference and flow direction wind speed difference between multiple different preset heights in each time period, the flux Richardson number corresponding to each time period is calculated, and the atmospheric stability classification of each time period is determined based on the flux Richardson number.

3. The method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1 or 2, characterized in that: The method of determining the statistical value of the environmental flow field characteristic quantity under each atmospheric stability classification includes: The arithmetic mean of the environmental flow field characteristic quantities at the representative heights of all time periods in each atmospheric stability classification is calculated as the statistical value of the environmental flow field characteristic quantities of the atmospheric stability classification.

4. The method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1, characterized in that: The basic wind conditions divided based on wind speed and wind direction include: Based on the wind speed-aerodynamic parameter list of each wind turbine model in the wind farm, the maximum and minimum values ​​of the cut-in wind speed and the cut-out wind speed are determined, and multiple wind speed intervals are divided between the maximum and minimum values; Evenly divide the wind direction angle from 0 to 360° and divide it into multiple wind direction sectors; The wind speed ranges and wind direction sectors are combined in pairs to form multiple basic wind conditions.

5. The method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 4, characterized in that: The representative wind direction and representative wind speed are the middle values ​​of the wind direction sector and wind speed range corresponding to the corresponding basic wind conditions.

6. The method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1, characterized in that: The method is based on wind farm information and representative wind direction, taking into account the influence of the vertical shear coefficient of wind direction in the statistical value of the characteristic quantity of the environmental flow field on the wind turbine wake, and determining the wind speed loss and additional turbulence intensity at each discrete point on the wind rotor disk surface, including: In the formula, is the additional turbulence intensity at discrete point m on the rotor disk of wind turbine i affected by the wake of upwind wind turbine j; is the peak value of the additional turbulence intensity profile, calculated as: Among them, I j Turbulence intensity at wind turbine j; The double-peaked Gaussian function used to describe the additional turbulence intensity is calculated as: in, is the standard deviation of the additional turbulence intensity profile: in, is the standard deviation of the Gaussian function used to describe the velocity loss profile; It refers to the distance between the peak point and the center point of the additional turbulence intensity profile, which is estimated by the following formula: Among them, D j is the rotor diameter of wind turbine j; It is used to correct the additional turbulence intensity in the area below the hub height of the wind turbine j to simulate its asymmetry in vertical distribution. The calculation formula is: Among them, y' i-m and z' i-m The ordinate and vertical coordinates of the discrete point m of wind turbine i in the relative coordinate system with the wind direction as the positive direction of the x-axis are respectively referred to as: H′ refers to the lateral displacement of the center point of the velocity loss profile in the isolated wake of wind turbine j at discrete point m within the disk of wind turbine i relative to the mid-longitudinal plane passing through the center point of the disk of wind turbine j. j is the hub height of wind turbine j.

7. The method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1, characterized in that: The method of determining the inflow wind speed at the vertical height of each discrete point based on the wind speed vertical shear coefficient in the statistical value of the characteristic quantity of the environmental flow field and the representative wind speed at the representative height includes: In the formula, is the inflow wind speed at the vertical height of discrete point m on wind turbine i; The basic wind condition WR r The corresponding representative wind speed; z' i-m is the vertical coordinate of the discrete point m of wind turbine i in the relative coordinate system where the wind direction is the positive direction of the x-axis; H ref is the representative height, which is determined based on the hub height of the wind turbine in the wind farm; S x is the vertical shear coefficient of wind speed under atmospheric stability classification x.

8. The method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1, characterized in that: The method of determining the turbulence intensity at the vertical height of each discrete point based on the turbulence intensity and the turbulence intensity vertical shear coefficient in the statistics of the characteristic quantity of the environmental flow field comprises: in, is the turbulence intensity at the vertical height of discrete point m on wind turbine i; is the turbulence intensity under atmospheric stability classification x; z' i-m is the vertical coordinate of the discrete point m of wind turbine i in the relative coordinate system where the wind direction is the positive direction of the x-axis; H ref is the representative height, determined based on the wind turbine hub height; C x is the vertical shear coefficient of turbulence intensity under atmospheric stability classification x.

9. The method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1, characterized in that: The effective wind speed and effective turbulence intensity of the wind turbine are determined based on the inflow wind speed and turbulence intensity at the vertical height of each discrete point on the wind rotor disk surface, combined with the wind speed loss and additional turbulence intensity at each discrete point, including: in, is the effective wind speed of wind turbine i, N i is the total number of discrete points belonging to the target wind turbine i, Δu i-m and I +i-m They represent the wind speed loss and additional turbulence intensity at the mth discrete point after considering the wake effects of all upwind wind turbines, and Refers to the vertical height z' of the mth discrete point in turn i-m Inflow wind speed and turbulence intensity at .

10. The method for calculating annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1, characterized in that: The method of determining the power generation of each wind turbine in each basic wind condition under each atmospheric stability classification based on the effective wind speed of each wind turbine comprises: Based on the effective wind speed of the wind turbine, combined with the wind speed-aerodynamic parameter list of the model to which the wind turbine belongs, the power generation of each wind turbine is obtained through interpolation calculation; The wind speed-aerodynamic parameter list of each model is supplemented with aerodynamic parameters for wind speed intervals below the cut-in wind speed and above the cut-out wind speed. In the wind speed interval below the cut-in wind speed, the supplementary thrust coefficient takes a large value close to 1, and the power takes a value of 0; in the wind speed interval above the cut-out wind speed, the supplementary thrust coefficient takes a small value close to 0, and the power takes a value of 0.

11. The method for calculating annual power generation of an offshore wind farm taking into account the influence of atmospheric stability according to claim 1, characterized in that: The power generation of each basic wind condition under each atmospheric stability classification is determined based on the power generation of each wind turbine, and then the power generation of each atmospheric stability classification and the annual power generation of the representative year are determined, including: Based on the power generation of each wind turbine in the wind farm, determine the power generation of the wind farm under each basic wind condition under each atmospheric stability classification; Based on the wind farm power generation under each basic wind condition under each atmospheric stability classification, combined with the proportion of each basic wind condition under each atmospheric stability classification, determine the power generation under each atmospheric stability classification; Based on the power generation of each atmospheric stability classification and the proportion of each atmospheric stability classification in the representative year, the annual power generation of the representative year is determined; The proportion of each basic wind condition under each atmospheric stability classification is determined based on the proportion of the number of time periods corresponding to each basic wind condition to the number of time periods corresponding to the corresponding atmospheric stability classification; The proportion of each atmospheric stability classification in the representative year is determined based on the ratio of the number of time periods corresponding to each atmospheric stability classification to the number of time periods in the representative year.

12. A device for calculating annual power generation of an offshore wind farm taking into account the influence of atmospheric stability, characterized in that: include: An information acquisition module is used to acquire wind farm information and a representative annual wind resource data set at a representative height, wherein the representative annual wind resource data set includes wind speed, wind direction and environmental flow field characteristic quantities representing each period of the year, wherein the environmental flow field characteristic quantities include turbulence intensity and vertical shear coefficients of wind speed, wind direction and turbulence intensity; The stability classification module is used to determine the atmospheric stability classification corresponding to each time period based on the representative annual wind resource data set at multiple preset heights, and determine the statistical value of the environmental flow field characteristic quantity under each atmospheric stability classification; The wind condition classification module is used to classify the basic wind conditions based on wind speed and wind direction, determine the basic wind conditions corresponding to each time period under each atmospheric stability classification, and determine the representative wind speed and representative wind direction at the representative height under each basic wind condition; The first calculation module is used to determine the wind speed loss and additional turbulence intensity at each discrete point on the wind rotor disk surface based on the wind farm information and the representative wind direction, taking into account the influence of the vertical shear coefficient of the wind direction in the statistical value of the environmental flow field characteristic quantity on the wind turbine wake; The second calculation module is used to determine the inflow wind speed at the vertical height where each discrete point is located based on the wind speed vertical shear coefficient in the statistical value of the environmental flow field characteristic quantity and the representative wind speed at the representative height; It is used to determine the turbulence intensity at the vertical height of each discrete point based on the turbulence intensity and the vertical shear coefficient of turbulence intensity in the statistical value of the characteristic quantity of the environmental flow field; The third calculation module is used to determine the effective wind speed and effective turbulence intensity of the wind turbine based on the inflow wind speed and turbulence intensity at the vertical height of each discrete point on the wind rotor disk surface, combined with the wind speed loss and additional turbulence intensity at each discrete point; A fourth calculation module is used to determine the power generation of each wind turbine in each basic wind condition under each atmospheric stability classification based on the effective wind speed of each wind turbine; The fifth calculation module is used to determine the power generation of each basic wind condition under each atmospheric stability classification based on the power generation of each wind turbine, and further determine the power generation of each atmospheric stability classification and the annual power generation of the representative year.

13. A storage medium having stored thereon a computer program executable by a processor, characterized in that: When the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability as described in any one of claims 1 to 11 are implemented.

14. An offshore wind farm annual power generation calculation device, comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, characterized in that: When the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability as described in any one of claims 1 to 11 are implemented.

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