Offshore wind plant annual energy output calculation method considering atmospheric stability influence

Abstract

The invention relates to a method for calculating annual energy production of an offshore wind plant by considering atmospheric stability influence. The invention is applicable to the technical field of wind power generation. According to the technical scheme adopted by the invention, the method comprises the following steps: judging atmospheric stability classification corresponding to each time period; determining a basic wind condition corresponding to each time period under each atmospheric stability classification; considering the influence of a wind direction vertical shear coefficient in an environmental flow field characteristic quantity statistical value on the fan wake flow, and determining wind speed loss and additional turbulence intensity; based on the wind speed vertical shear coefficient, the inflow wind speed is determined; determining the turbulence intensity based on the turbulence intensity and the turbulence intensity vertical shear coefficient; based on the inflow wind speed and the turbulence intensity, the effective wind speed and the effective turbulence intensity of the wind turbine are determined by combining the wind speed loss and the additional turbulence intensity; determining the generating capacity of each wind turbine based on the effective wind speed of each wind turbine; based on the generating capacity of each wind turbine, the annual generating capacity representative of the year is determined.

Description

Technical Field

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

[0002] Wind energy resource assessment is of great significance to the development of wind power projects. As an important environmental flow field parameter, atmospheric stability has an impact that cannot be ignored. Long-term statistical data show that atmospheric stability will show alternating cyclic changes on a daily time scale. However, current wind power engineering practices are particularly insufficient in considering this important factor. When calculating the power generation of wind farms, the dynamic changes of atmospheric stability are often ignored, and it is simply assumed that wind farms always operate in a neutral atmosphere.

[0003] Take the widely used Meteodyn WT and WAsP software in the industry as examples. They both calculate power generation using the Park model, which contains only one required input parameter, the wake attenuation coefficient, which is used to adjust the recovery rate of speed loss in the wake area of ​​the wind turbine according to the site environment, without considering or reflecting the impact of changes in atmospheric stability on the wake. Even in the latest academic research, the impact of atmospheric stability is simply attributed to "the difference in wind speed loss recovery rate in the wake area due to differences in turbulence intensity", ignoring the impact of other key inflow characteristics that change with atmospheric stability on the evolution of wind turbine wakes.

[0004] In fact, as the atmospheric stability increases, in addition to the decrease in turbulence intensity, the vertical shear of wind speed and wind direction profiles increases, which will affect the wake wind field behind the wind rotor disk and further affect the power generation of the downwind wind turbine. Therefore, the existing technology ignores the influence of other key inflow characteristic quantities on the evolution of wind turbine wake, which 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-mentioned problems, a method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability is provided.

[0006] The technical solution adopted by the present invention is: a method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability, comprising: 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, combined with 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 value of the characteristic quantity 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, the power generation of each basic wind condition under each atmospheric stability classification is determined, and then the power generation of each atmospheric stability classification and the annual power generation of the representative year are determined.

[0007] 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.

[0008] 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.

[0009] 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.

[0010] 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.

[0011] 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 are the effective wind speed and rotor diameter of wind turbine j respectively, and the parameters The calculation formula is: ; in, is the hub height of wind turbine j, and 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 discrete point m within the disk of wind turbine i relative to the median longitudinal plane passing through the center point of the disk of wind turbine j. The calculation formula is: ; in, and They represent the horizontal coordinates of discrete point m on the disk of wind turbine j and wind turbine i in the relative coordinate system, Indicates the vertical height of the discrete point m The wind direction angle at j is relative to the vertical height of the center point of the wind turbine rotor disk. The change in wind direction angle at is estimated by the following formula: ; in, is the vertical shear coefficient of wind direction under atmospheric stability classification x; The peak value of the velocity loss profile is determined by the following formula: ; in, The thrust coefficient of wind turbine j, is the standard deviation of the Gaussian function used to describe the velocity loss profile, calculated as: ; ; ; in, It is called the wake expansion coefficient.

[0012] 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: ; ; in, is the turbulence intensity at wind turbine j; is a double-peaked Gaussian function used to describe the additional turbulence intensity, and the calculation formula is: ; 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: : ; in, 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: ; ; ; in, and 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 discrete point m within the disk of wind turbine i relative to the median longitudinal plane passing through the center point of the disk of wind turbine j, is the hub height of wind turbine j.

[0013] 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; Basic wind conditions The corresponding representative wind speed; is the vertical coordinate of the discrete point m representing wind turbine i in the relative coordinate system where the wind direction is the positive direction of the x-axis; is the representative height, determined based on the hub height of the wind turbines in the wind farm; is the vertical shear coefficient of wind speed under atmospheric stability classification x.

[0014] 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; is the vertical coordinate of the discrete point m representing wind turbine i in the relative coordinate system where the wind direction is the positive direction of the x-axis; is the representative height, determined based on the wind turbine hub height; is the vertical shear coefficient of turbulence intensity under atmospheric stability classification x.

[0015] 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, is the total number of discrete points belonging to the target wind turbine i, and Respectively represent The wind speed loss and additional turbulence intensity after the influence of the wake of all upwind wind turbines are considered at each discrete point. and Refers to the first The vertical height of the discrete points Inflow wind speed and turbulence intensity at .

[0016] 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.

[0017] 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 a 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.

[0018] A device for calculating annual power generation of an offshore wind farm taking into account the influence of atmospheric stability, comprising: 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 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 vertical shear coefficient of the wind speed in the statistical value of the characteristic quantity of the environmental flow field and the representative wind speed at the representative height; and is used to determine the turbulence intensity at the vertical height where each discrete point is located based on the turbulence intensity and the vertical shear coefficient of the 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.

[0019] A storage medium stores a computer program executable by a processor, wherein the computer program, when executed, implements the steps of the method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability.

[0020] An offshore wind farm annual power generation calculation device comprises a memory and a processor. The memory stores a computer program executable by the processor. When the computer program is executed, the steps of the offshore wind farm annual power generation calculation method taking into account the influence of atmospheric stability are implemented.

[0021] The beneficial effects of the present invention are: The present invention divides the wind resource data of each period of the year at a representative height based on the difference in atmospheric stability and the basic wind conditions with different wind speeds and wind directions to form a number of data subsets. When calculating the power generation under each data subset, the turbulence intensity under the corresponding atmospheric stability, as well as the key environmental flow field characteristics such as wind speed, wind direction and vertical shear of turbulence intensity profile on the evolution of wind turbine wake are comprehensively considered. Then, the power generation of the wind farm under each subset is summarized and calculated to obtain the annual power generation of the wind farm.

[0022] The present invention makes a fine distinction based on atmospheric stability and basic wind conditions, and quantifies the results of the fine distinction in a targeted manner. This can greatly reduce the amount of calculation and make the calculation results more reflective of the distribution of wind energy resources in the site, thereby significantly improving the calculation accuracy of the annual power generation of the offshore wind farm.

[0023] The present invention takes into account the influence of vertical changes of multiple key environmental characteristic quantities on the effective wind speed of the wind turbine in the power generation calculation, so that the effective wind speed of the wind turbine is closer to reality, and the power generation calculation can better reflect the actual power generation situation of the wind turbine, thereby improving the calculation accuracy of the power generation.

[0024] 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, so that each type of wind turbine in the wind farm can find the corresponding basic wind condition, and the present invention determines the power generation of each wind turbine by calculating the effective wind speed of each wind turbine separately, and then determines the power generation and annual power generation of the wind farm. Therefore, in addition to the single model scenario commonly seen in current engineering practice, the present invention is also applicable to the situation where multiple types of models may be mixed and arranged in the site, thereby greatly expanding the scope of application of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of the method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability in an embodiment.

[0026] Figure 2 This is a flow chart of calculating the power generation of a wind farm under basic wind conditions in an embodiment.

[0027] Figure 3 Schematic diagram of the discretization of the wind wheel surface in the embodiment.

[0028] Figure 4 It is a schematic diagram of the corresponding relationship between the annual power generation of a wind farm and a wind resource data set taking into account the influence of atmospheric stability in the embodiment.

[0029] Figure 5 It is a schematic diagram of a device for calculating annual power generation of an offshore wind farm taking into account the influence of atmospheric stability in an embodiment.

[0030] Figure 6 The vertical profiles of inflow wind direction, wind direction and turbulence intensity under three different atmospheric stabilities in Example 1 of the embodiment correspond to (a), (b) and (c) in the sub-figures respectively.

[0031] Figure 7 The cloud diagrams of the wake velocity and additional turbulence intensity of the NREL 5MW wind turbine in a stable atmosphere in Example 1 of the embodiment correspond to (a) and (b) in the sub-figures, respectively.

[0032] Figure 8 The cloud diagrams of the wake velocity loss and additional turbulence intensity of the NREL 5MW wind turbine in the neutral atmosphere in Example 1 of the embodiment correspond to (a) and (b) in the sub-figures, respectively.

[0033] Fig. 9The cloud diagrams of the wake velocity loss and additional turbulence intensity of the NREL 5MW wind turbine in the unstable atmosphere in Example 1 of the embodiment correspond to (a) and (b) in the sub-figures, respectively. DETAILED DESCRIPTION

[0034] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limitations of the present invention. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0035] In the description of the present invention, the meaning of "a plurality" is two or more than two. If there is a description of "a first" or "a second", it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features. In addition, unless otherwise defined, all technical and scientific terms used in this document have the same meaning as those commonly understood by those skilled in the art.

[0036] Example 1: Figure 1 As shown, this embodiment is a method for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability, which specifically includes the following steps: S100: Obtain wind farm information and a representative annual wind resource data set at a representative height.

[0037] In this embodiment, the wind farm information includes the wind farm layout, the models of each built-in wind turbine and the rotor diameter, hub height, wind speed-aerodynamic parameter list of each model, etc., wherein the wind speed-aerodynamic parameter list consists of typical wind speed values ​​between the cut-in wind speed and the cut-out wind speed and the corresponding power and thrust coefficients.

[0038] In this example, the representative annual wind resource data sets at multiple preset heights are obtained by processing the wind measurement data of the wind farm, wherein the wind measurement data should cover the wind speed, wind direction and turbulence intensity at multiple different wind measurement heights and multiple time periods.

[0039] The processing of wind measurement data in this embodiment includes data integrity check, rationality check, elimination, interpolation, extension of unreasonable data and missing data, representative year correction, etc.

[0040] In this example, the one among multiple preset heights that is closest to the average hub height of all turbines in the wind farm is used as the representative height. In this embodiment, the wind resource data set representing the year is divided into 8760 time periods by hour, wherein the wind resource data corresponding to each time period should cover wind speed, wind direction and environmental flow field characteristics, and the environmental flow field characteristics include turbulence intensity and vertical shear coefficients of wind speed, wind direction and turbulence intensity.

[0041] The vertical shear coefficient of wind speed in this example can be calculated based on two different vertical heights. and The wind speed difference between the two is obtained by fitting the exponential function: (1) in, and Respectively refer to the corresponding height and The wind speed at the location.

[0042] The vertical shear coefficient of the wind direction in this embodiment can be calculated based on two different heights: and The wind direction difference between the two is calculated by linear fitting method: (2) in, and The corresponding heights are and The wind direction angle.

[0043] The vertical shear coefficient of the turbulence intensity can be calculated based on two different heights. and The turbulence intensity difference between the two is calculated by exponential fitting method: (3) in, and The corresponding heights are and The turbulence intensity at .

[0044] The height and To ensure the reliability and representativeness of the data fitting results, it is recommended to select two heights that meet the following constraints from the aforementioned multiple different heights: (4) (5) (6) in, Represents the number of models in the wind farm, For the The wheel hub height of each model.

[0045] It should be noted that in this embodiment, only exponential fitting and linear fitting methods are used as examples, and other data fitting methods that can be used to describe the changes in the vertical profile of wind speed, wind direction and turbulence intensity are also within the protection scope of the present invention.

[0046] S200, determining the atmospheric stability classification corresponding to each time period, and determining the statistical value of the environmental flow field characteristic quantity under each atmospheric stability classification.

[0047] S210. In this embodiment, 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. The atmospheric stability classification includes stable, neutral and unstable atmosphere.

[0048] The atmospheric stability classification for each period is determined based on the flux Richardson number, specifically: when the flux Richardson number >0, corresponding to a stable atmosphere; =0, corresponding to a neutral atmosphere; when When <0, it corresponds to an unstable atmosphere.

[0049] The flux Richardson number , can be calculated based on the temperature difference and wind speed difference between two different heights. The calculation formula is: (7) in, is the acceleration due to gravity, Mean absolute temperature, and Height and The temperature difference and wind speed difference between Dry adiabatic cooling rate.

[0050] 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 three data sets, corresponding to stable, neutral and unstable atmospheres, respectively. In each data set, the data in each time period is consistent with the representative annual wind resource data set, including wind speed, wind direction, turbulence intensity at the representative height, and the vertical shear coefficient of wind speed, wind direction and turbulence intensity.

[0051] 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 year wind resource data set, and determine the proportion of each atmospheric stability classification in the representative year.

[0052] For the convenience of distinction, in this embodiment, , and Refers to the proportion of stable, neutral and unstable atmospheres. Represent stable, neutral and unstable atmospheres respectively. According to the definition, it is obvious that: .

[0053] S230. In this embodiment, by calculating the arithmetic mean of the environmental flow field characteristic quantities in all time periods in 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 turbulence intensity statistical value, and the vertical shear coefficient statistical value of wind speed, wind direction and turbulence intensity.

[0054] For the convenience of distinction, in this embodiment, { , , , },{ , , , },{ , , , } refers to the statistical values ​​of turbulence intensity at representative heights in stable, neutral and unstable atmospheres, as well as wind speed, wind direction and vertical shear coefficient of turbulence intensity.

[0055] S300, dividing basic wind conditions based on wind speed and wind direction, determining basic wind conditions corresponding to each time period under each atmospheric stability classification, and determining representative wind speed and representative wind direction at a representative height under each basic wind condition.

[0056] S310, 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 the cut-out wind speed, and divide a plurality of wind speed intervals between the maximum and minimum values.

[0057] Traverse the wind speed-aerodynamic parameter list of each model in the wind farm obtained in step S100, and determine the minimum value of the wind speed data and maximum value , and round them down respectively and round up Processing, and then and As lower and upper limits, the interval is calculated according to the set wind speed , dividing the wind speed into multiple different intervals. According to the definition, the total number of wind speed intervals , among which, The wind speed interval can be expressed as .

[0058] The wind speed calculation interval It is recommended that the value should not exceed the difference between adjacent wind speeds in the wind speed-aerodynamic parameter list of any model.

[0059] S320, according to the set number of wind direction sectors , evenly divide the wind direction angle from 0 to 360°, and cut out multiple different wind direction sectors.

[0060] According to the definition, the size of each wind direction sector is If As the middle value of the first wind direction sector, The wind direction sector can be expressed as: ; Referring to the conventional practices in wind power projects, this embodiment recommends The value is 12 or 16.

[0061] S330, combining each wind speed interval and wind direction sector obtained in steps S310 and S320 in pairs, thereby obtaining a plurality of mutually different basic wind conditions. According to the definition, the total number of basic wind conditions is , the corresponding numbering sequence can be expressed as ,in Refers to Basic wind conditions.

[0062] S340, following the data sets of each atmospheric stability classification in step S200, according to the wind speed and wind direction of each time period in each atmospheric stability classification data set, and comparing the wind speed and wind direction corresponding to the basic wind condition in step S330, determine the basic wind condition belonging to each time period under each atmospheric stability classification.

[0063] S350: Determine the proportion of each basic wind condition under each atmospheric stability classification based on the number of time periods of each basic wind condition under each atmospheric stability classification.

[0064] By counting the ratio of the number of time periods in each basic wind condition to the number of time periods in the data subset, the proportion of each basic wind condition under different atmospheric stability can be obtained. The corresponding sequence can be expressed as ,in, Refers to superscript Under the corresponding atmospheric stability, Basic wind conditions % of.

[0065] One point that needs to be mentioned in particular is that when the wind speed is lower than the cut-in wind speed or higher than the cut-out wind speed, the wind turbine power generation is 0. Therefore, in each data subset corresponding to different atmospheric stability, there may be some time periods that do not belong to all the basic wind conditions listed in step S330. This means that when the proportion of each basic wind condition under a certain atmospheric stability is summed, the sum may be less than 1, that is, Nonetheless, as mentioned above, this result is reasonable.

[0066] S360: Determine the representative wind direction of each basic wind condition based on the middle value of the wind direction sector and wind speed interval corresponding to each basic wind condition. and represents wind speed .

[0067] S400. Based on the wind farm information, combined with the representative wind speed and representative wind direction of each basic wind condition under each atmospheric stability classification, and the statistical values ​​of each environmental flow field characteristic quantity, the power generation of each basic wind condition under each atmospheric stability classification is calculated, and then the power generation and annual power generation of each atmospheric stability classification are calculated.

[0068] For each basic wind condition obtained in step S300, taking into account the difference in atmospheric stability classification, one is selected to calculate the power generation of the wind farm. example, Figure 2 The calculation of atmospheric stability when x is given The wind farm power generation flow chart is as follows: 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 of wind speed intervals below the cut-in wind speed and above the cut-out wind speed.

[0069] 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 the practice of wind power engineering, referring to the information 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 speed and cut-out wind speed often have differences, and this will result in that under some basic wind conditions divided in step 4, the wind speed perceived by some models may not be within the wind speed range covered by the wind speed-aerodynamic parameter list obtained in step S100. Affected by this, in the subsequent steps, when the interpolation calculation of aerodynamic parameters is performed according to the wind speed, a calculation overflow error will occur.

[0070] 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 of the wind speed interval 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 a value of 0; and 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 a value of 0.

[0071] S420, integrating the inflow data of each basic wind condition under each atmospheric stability classification, the inflow data including the representative wind direction under the corresponding basic wind condition Represents wind speed As well as the statistical values ​​of environmental flow field characteristics under the corresponding atmospheric stability classification.

[0072] S430, according to the wind direction along the The wind turbines in the wind farm are numbered in sequence, wherein the first wind turbine is numbered 1, and the numbers of the other downwind wind turbines are incremented one by one in sequence.

[0073] In this embodiment, the total number of wind turbines in the wind farm is The numbering sequence can be expressed as In this embodiment, the geodetic coordinate system is rotated according to the representative wind direction, 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 geodetic coordinate system and the conversion matrix, their coordinates in the relative coordinate system are calculated, and then the front and rear order along the representative wind direction is determined by comparing the horizontal coordinates in the relative coordinate system.

[0074] The geodetic coordinate system takes any point in the wind farm as the origin of the coordinate system, and the east direction (corresponding to Wind direction angle) is the positive direction of the x-axis, due north (corresponding to A two-dimensional rectangular coordinate system is established with the wind direction angle) as the positive direction of the y-axis.

[0075] The conversion matrix is ​​calculated as follows: (8) (9) in, and They represent the horizontal coordinate, vertical coordinate and perpendicular coordinate in the geodetic coordinate system and the relative coordinate system respectively.

[0076] According to the wind farm layout obtained in step S100, the coordinates of each wind turbine in the geodetic coordinate system established above can be determined. After conversion, the corresponding numbering sequences can be integrated to obtain the following coordinate sequence containing the coordinate values ​​of each wind turbine in the relative coordinate system: ,in, They respectively represent the horizontal coordinate, vertical coordinate and the vertical coordinate of the hub height of the wind turbine numbered i in the relative coordinate system.

[0077] S440, using the inflow data of step S420 as the input of the analytical model, and calculating the effective wind speed and thrust coefficient of each wind turbine in sequence according to the order from small to large in the numbering in S430.

[0078] Considering that the speed loss in the wake area of ​​the 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 affecting the recovery of the speed loss in the wake area, when evaluating the wake effect of a wind farm and calculating the power generation based on the analytical model, the accurate simulation of the above two key wake characteristic quantities is the core and key.

[0079] In the analytical model used in this embodiment, the influence of multiple key inflow characteristics (turbulence intensity, and wind speed, wind direction and vertical shear of turbulence intensity) that change with atmospheric stability on the wake evolution is scientifically quantified.

[0080] S441, such as Figure 3 As shown in the figure, the wind rotor disk surface of the target wind turbine i is discretized to generate a number of discrete points on the wind rotor disk surface. According to the transformation matrix in equations (8) and (9), the coordinates of each discrete point in the relative coordinate system are calculated. Suppose the total number of discrete points belonging to the target wind turbine i is , then the discrete point coordinate set can be integrated to obtain the following form ,in, Represents the coordinates of discrete point 1 on wind turbine i. Similarly Represents the coordinates of discrete point m on wind turbine i.

[0081] S442. Based on the 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 the wind direction in the statistical value of the environmental flow field characteristic quantity on the wind turbine wake.

[0082] The following is an example of a wind turbine numbered i in a wind farm: When the target wind turbine is numbered i=1, since there are no other wind turbines in the upwind direction, the wind speed loss and additional turbulence increment caused by wake interference at each discrete point within its wind rotor disk are both 0. Taking the discrete point numbered m as an example, The calculation formula for wind speed loss is: (10) The calculation formula for the additional turbulence increment is: (11) 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 amount 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. Further considering the influence of multiple key environmental flow field characteristic quantities such as the turbulence intensity varying with atmospheric stability, and the vertical shear of wind speed, wind direction and turbulence intensity on the wake evolution, the velocity loss and additional turbulence increment at each discrete point in the rotor disk plane of the target wind turbine i caused by the isolated wake of any upwind wind turbine j (j < i) are calculated. Here, the discrete point numbered m is still taken as an example.

[0083] When the number i of the target wind turbine is greater than 1, the wind speed loss and additional turbulence intensity at each discrete point on the rotor disk are calculated as follows: ① The velocity loss is determined by the following formula: (12) Where, and are the effective wind speed and rotor diameter of wind turbine j respectively. Considering that the wind direction is the most important external driving force affecting the wake propagation direction, and combining the different degrees of vertical wind shear in the inflow under different atmospheric stabilities, the parameter is calculated by the following formula: (13) Where, is the hub height of wind turbine j, and successively represent the ordinate and vertical coordinate of the discrete point m of wind turbine i in the relative coordinate system described in step 5.3. represents 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: (14) Where, and 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 respectively, represents the vertical height where the discrete point m is located The change in the wind direction angle at the vertical height where the discrete point m is located relative to the wind direction angle at the vertical height (15) Where, The superscript of refers to the atmospheric stability, which can be obtained from step 3 Make the corresponding selection.

[0084] In formula (12), is the peak value of the velocity loss profile. Its threshold is defined according to the one-dimensional momentum theorem. In this embodiment, it is determined by the following formula: (16) in, is the thrust coefficient of wind turbine j, is the standard deviation of the Gaussian function used to describe the velocity loss profile, calculated as: (17) (18) (19) in, It is called the wake expansion coefficient. Studies have shown that its value is positively correlated with the turbulence intensity at the wind turbine j (when j=1, only the turbulence intensity in the inflow can be taken into account, and when j>1, it includes 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, the momentum exchange between the wake and the ambient flow field is more intense. Therefore, as it moves away from the wind rotor disk, the outward expansion rate of the wake influence area and the recovery rate of the internal wind speed loss are also greater. Correspondingly, The value of should be larger.

[0085] ② The additional turbulence intensity is determined by the following formula: (20) In formula (20), is the peak value of the additional turbulence intensity profile, calculated as: (twenty one) (twenty two) in, is the turbulence intensity at wind turbine j.

[0086] In formula (20), is a double-peaked Gaussian function used to describe the additional turbulence intensity, and the calculation formula is: (twenty three) in, is the standard deviation of the additional turbulence intensity profile. At the same downstream position behind the wind rotor disk, it satisfies the following relationship with the standard deviation of the velocity loss profile in equation (17): (twenty four) In formula (23), The distance between the peak point and the center point of the additional turbulence intensity profile is denoted as the tip vortex, which is an important driver for inducing additional turbulence intensity. Therefore, in the near wake area close to the rotor disk, The value of is approximately equal to the rotor radius. Further considering the influence of the wake expansion effect in the far wake region on the position of the profile peak point, in this embodiment, the following formula is used to estimate : (25) In formula (20), 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: (26) (27) (28) In this embodiment, the wind speed loss and additional turbulence increment at discrete point m on wind turbine i are calculated based on the speed loss and additional turbulence intensity of the isolated wakes of each upwind wind turbine at discrete point m on wind turbine i.

[0087] When its number is i>1 and there is a wind turbine in the upwind direction, in order to quantify the superposition effect of the wake interference of multiple wind turbines in the upwind direction, in this embodiment, the linear superposition method and the maximum value method are used to calculate the speed loss and additional turbulence intensity in the wake overlap area, and the wind speed loss and additional turbulence increment at each discrete point in the wind rotor disk of the target wind turbine i are estimated. Here, the discrete point numbered m is still used as an example, The calculation formula for wind speed loss is: (29) The calculation formula for the additional turbulence increment is: (30) in, and represent the velocity loss and additional turbulence intensity of the isolated wake of wind turbine j at the mth discrete point respectively.

[0088] S443, based on the wind speed vertical shear coefficient in the environmental flow field characteristic quantity statistics, combined with the representative wind speed at the representative height, determine the inflow wind speed at the vertical height of each discrete point; based on the turbulence intensity and the turbulence intensity vertical shear coefficient in the environmental flow field characteristic quantity statistics, determine the turbulence intensity at the vertical height of each discrete point; (31) (32) in, and Refers to the first The vertical height of the discrete points The inflow wind speed and turbulence intensity at Target base wind condition The corresponding representative wind speed is is the vertical shear coefficient of wind speed under atmospheric stability classification x, is the turbulence intensity under atmospheric stability classification x, is the vertical shear coefficient of turbulence intensity under atmospheric stability classification x.

[0089] S444. 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, determine the effective wind speed and effective turbulence intensity of the wind turbine.

[0090] Considering the vertical shear effect of wind speed and turbulence intensity in the inflow, the wind speed and turbulence intensity of each discrete point on the rotor disk of target wind turbine i are determined, and then the effective wind speed of target wind turbine i is obtained by calculating the average value. and effective turbulence intensity : (33) (34) in, is the total number of discrete points belonging to the target wind turbine i, and Respectively represent The wind speed loss and additional turbulence intensity after the influence of the wake of all upwind wind turbines are considered at each discrete point, refer to step S442.

[0091] S445, based on the effective wind speed of the target wind turbine i , combined with the wind speed-aerodynamic parameter list of the model to which it belongs, the thrust coefficient of the target wind turbine i can be obtained through interpolation calculation : (35) in, and Corresponding to the target wind turbines The wind speed of the model is closest to the list of aerodynamic parameters The two wind speeds meet ,and For the list and The corresponding thrust coefficient.

[0092] Considering that there is a strong correlation between the turbulence intensity at the wind turbine and the expansion rate of the wake influence range behind the disk and the recovery rate of wind speed loss, in this embodiment, according to the effective turbulence intensity at the target wind turbine i , refer to the following formula to determine the expansion coefficient used for the wind turbine wake calculation : (36) in, and It is an adjustable parameter. Referring to previous studies, this embodiment recommends values ​​of 0.38 and 0.004.

[0093] S450: 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.

[0094] According to the effective wind speed of each wind turbine, combined with the wind speed-aerodynamic parameter list of their respective models, the power generation of each wind turbine can be obtained through interpolation calculation: (37) in, For the number The wind turbine power generation, and Corresponding to wind turbines The closest wind speed to the model in the aerodynamic parameter list The two wind speeds meet ,and For the corresponding and of power.

[0095] S460. 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.

[0096] S461. 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.

[0097] In this embodiment, based on the target basic wind condition The wind turbine power generation of each wind turbine in the wind farm can be summed to obtain the target basic wind condition when the atmospheric stability is x. Wind farm power generation under .

[0098] (38) in, is the total number of wind turbines in the wind farm, For the number of wind turbine power generation.

[0099] S462. Determine the power generation of each atmospheric stability classification based on the wind farm power generation of each basic wind condition under each atmospheric stability classification and the proportion of each basic wind condition under each atmospheric stability classification.

[0100] Figure 4 The corresponding relationship between atmospheric stability, basic wind conditions and wind farm power generation is given, among which the average power generation of wind farms in each period under stable, neutral and unstable atmospheres is shown. , , Can be calculated by the following formula: (39) (40) (41) in, , , and , , Refers to the stable, neutral and unstable atmospheres respectively. The proportion of basic wind conditions and the corresponding wind farm power generation.

[0101] S463. Determine the annual power generation in the representative year based on the power generation of each atmospheric stability classification and the proportion of each atmospheric stability classification in the representative year.

[0102] The annual power generation of the wind farm can be calculated according to the following formula : (42) Among them, A represents the number of time periods in a year. In this example, A=8760. , and Represent the proportion of stable, neutral and unstable atmosphere in a year, .

[0103] Example 2: Figure 5 As shown, this embodiment is a device for calculating the annual power generation of an offshore wind farm taking into account the influence of atmospheric stability, including an information acquisition module, a stability classification module, a wind condition classification module, and first to fifth calculation modules.

[0104] In this embodiment, the information acquisition module is used to obtain wind farm information and a representative annual wind resource data set at a representative height, wherein the representative annual wind resource data set contains wind speed, wind direction and environmental flow field characteristics representing each period of the year, wherein the environmental flow field characteristics include turbulence intensity, and the vertical shear coefficient of wind speed, wind direction and turbulence intensity.

[0105] The stability classification module is used to determine the atmospheric stability classification corresponding to each time period and determine the statistical values ​​of the environmental flow field characteristics under each atmospheric stability classification.

[0106] The wind condition classification module is used to classify 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.

[0107] 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 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 environmental flow field characteristic quantity on the wind turbine wake.

[0108] The second calculation module is used to determine the inflow wind speed at the vertical height of each discrete point based on the vertical shear coefficient of wind speed in the statistical value of the environmental flow field characteristic quantity, combined with the representative wind speed at the representative height; and 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 environmental flow field characteristic quantity.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] Embodiment 3: This embodiment is a storage medium on which a computer program that can be executed 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 taking into account the influence of atmospheric stability in Embodiment 1 are implemented.

[0113] Embodiment 4: This embodiment is an offshore wind farm annual power generation calculation device, which has a memory and a processor. The memory stores a computer program that can be executed by the processor. When the computer program is executed, the steps of the offshore wind farm annual power generation calculation method taking into account the influence of atmospheric stability in Embodiment 1 are implemented.

[0114] The following is a specific example: Example 1: The wake effect is a decisive factor affecting the power generation of offshore wind farms, and the accurate calculation of the wake of any isolated wind turbine in the field is the core and key. In Example 1, a single NREL 5MW wind turbine is used as the research object. Under the wind conditions with a representative wind speed and wind direction of 8 m / s and 270°, the wind turbine wake simulation data based on high-precision CFD simulation is used as a reference benchmark to verify the reliability of the model method of the present invention for the calculation of wind turbine wake wind field under stable, neutral and unstable atmospheres. Because in the real wind farms commonly used as standard models such as Horns Rev I and Nysted, the spacing between adjacent rows of wind turbines is about 7 times the diameter of the wind rotor (hereinafter referred to as D for the wind rotor diameter), the vertical section at 7D behind the wind rotor disk is also selected as a representative section, and the model calculation results under different atmospheric stabilities are compared with the CFD simulation data.

[0115] Figure 6 The vertical profiles of inflow wind speed, wind direction and turbulence intensity under three different atmospheric stability conditions obtained based on CFD simulation are shown, and the calculation results of their vertical shear coefficients are summarized in Appendix 1; Table 1

[0116] In view of the fact that the mainstream commercial computing software in current wind power engineering, such as WAsP, Meteodyn WT, etc., all use the Park model as the development kernel and use the IEC model to calculate the additional turbulence intensity of wind turbines, Figure 7-Figure 9 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, no matter how the atmospheric stability changes, the present invention can accurately simulate the spatial distribution of the two key characteristic quantities, wind speed and 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 method.

[0117] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the above-mentioned boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part for which is described as a larger operation is performed independently.

[0118] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise specified to the contrary, one or more of the above-mentioned functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present invention. More specifically, in view of the properties, functions and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional skills of the engineer. Therefore, those skilled in the art can implement the present invention set forth in the claims without excessive experimentation using ordinary techniques. It is also 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.

[0119] If the above functions are implemented in the form of software functional 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, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the above methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0120] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0121] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the above-mentioned program is printed, since the above-mentioned program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or processing in other suitable ways as necessary, and then stored in a computer memory.

[0122] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned 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, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0123] 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 conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0124] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0125] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in 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, the power generation of each basic wind condition under each atmospheric stability classification is determined, and then the power generation of each atmospheric stability classification and the annual power generation of the representative year are determined.

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, 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 are the effective wind speed and rotor diameter of wind turbine j respectively, and the parameters The calculation formula is: ； in, is the hub height of wind turbine j, and 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 discrete point m within the disk of wind turbine i relative to the median longitudinal plane passing through the center point of the disk of wind turbine j. The calculation formula is: ； in, and They represent the horizontal coordinates of discrete point m on the disk of wind turbine j and wind turbine i in the relative coordinate system, Indicates the vertical height of the discrete point m The wind direction angle at j is relative to the vertical height of the center point of the wind turbine rotor disk. The change in wind direction angle at is estimated by the following formula: ； in, 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: ； in, is the thrust coefficient of wind turbine j, is the standard deviation of the Gaussian function used to describe the velocity loss profile, calculated as: ； ； ； in, It is called the wake expansion coefficient.

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 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: ； ； in, is the 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: : ； in, 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: ； ； ； in, and 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 discrete point m within the disk of wind turbine i relative to the median longitudinal plane passing through the center point of the disk of wind turbine j, is the hub height of wind turbine j.

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 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; Basic wind conditions The corresponding representative wind speed; is the vertical coordinate of the discrete point m representing wind turbine i in the relative coordinate system where the wind direction is the positive direction of the x-axis; is the representative height, determined based on the hub height of the wind turbines in the wind farm; is the vertical shear coefficient of wind speed 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 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; is the vertical coordinate of the discrete point m representing wind turbine i in the relative coordinate system where the wind direction is the positive direction of the x-axis; is the representative height, determined based on the wind turbine hub height; is the vertical shear coefficient of turbulence intensity under atmospheric stability classification x.

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 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, is the total number of discrete points belonging to the target wind turbine i, and Respectively represent The wind speed loss and additional turbulence intensity after the influence of the wake of all upwind wind turbines are considered at each discrete point. and Refers to the first The vertical height of the discrete points Inflow wind speed and turbulence intensity at .

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 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.

12. 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 a 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.

13. A device for calculating the 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.

14. 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 12 are implemented.

15. 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 12 are implemented.

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