Calculation method for annual power generation of offshore wind farms applicable to wind and solar power co-location

Abstract

The present invention relates to a method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar panels are in the same field. It is applicable to the field of integrated energy technology. The present invention makes a photovoltaic panel unit equivalent to a small wind turbine, introduces the wind farm equivalent roughness calculation model in the Frandsen model into the calculation of the equivalent roughness of the photovoltaic panel array, realizes the approximate calculation of the equivalent roughness of the photovoltaic panel array, corrects the hub height wind speed in the inflow based on the equivalent roughness of the photovoltaic panel array, and corrects the wake attenuation coefficient, so as to introduce the influence of the photovoltaic panel into the calculation of the inflow wind field and the evolution of the wind turbine wake, so that it can better reflect the actual situation of the situation where wind and solar panels are in the same field. The introduction of a virtual wind turbine is used to quantify the influence of the wake reflection caused by the photovoltaic panel on the wake interference between wind turbines. The virtual wind turbine and the real wind turbine are about a mirror symmetric plane, and the mirror symmetric plane is determined based on the equivalent roughness of the photovoltaic panel array to accurately reflect the actual situation of the wake reflection.

Description

Technical Field

[0001] The present invention relates to a method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field, and is applicable to the field of comprehensive energy technology. Background Art

[0002] Wind energy and solar energy have natural complementary characteristics. There is sufficient solar energy during the day, while the wind is often stronger at night. The development of wind and solar power on the same site can effectively improve the stability and reliability of energy output, thereby enhancing the grid's ability to accept clean energy, while helping to improve the comprehensive utilization efficiency of the sea area and achieve "multiple uses of one site". For this reason, in recent years, the development of wind and solar power on the same site has received more and more attention and has achieved vigorous development.

[0003] However, it is worth noting that the current mainstream commercial wind farm design software (such as WAsP, WT, etc.) is only applicable to the scenario where the wind farm itself exists. It does not consider and cannot reflect the impact of adding photovoltaic panels on the site on the power generation performance of wind turbines. The calculation results cannot reflect the actual situation, which reduces the reliability of the project investment return evaluation results and increases the investment risk of the development unit.

[0004] Especially in the scenario of wind and solar power co-development at sea, due to the low roughness of the sea surface, the turbulence intensity in the inflow is relatively weak, and the relatively regular layout of the wind farm is superimposed, the degree of wake interference between units is significantly enhanced compared with that on land. In this case, the photovoltaic panels installed between wind turbines, as an additional external disturbance source, will inevitably have an unignorable impact on the inflow wind field and the evolution of the wind turbine wake. When calculating the power generation of the wind farm, it is necessary to take this into account and scientifically quantify it. 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 applicable to the situation where wind and solar power are on the same field 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 applicable to the situation where wind and solar power are in the same field, comprising:

[0007] Obtain wind turbine installation location information and wind turbine structural parameters of each wind turbine in the wind farm, and obtain photovoltaic panel installation location information and photovoltaic panel structural parameters of each photovoltaic panel unit in a photovoltaic panel array arranged in the same field;

[0008] Determine multiple representative heights based on wind turbine structural parameters and photovoltaic panel structural parameters, and obtain a representative annual wind resource data set at the representative heights;

[0009] The sea surface roughness is calculated based on the center height of the photovoltaic panel surface in the photovoltaic panel structural parameters and the representative annual wind resource data set at the height;

[0010] Based on the sea surface roughness, photovoltaic panel installation location information, panel center height, and representative annual wind resource data set at the panel center height, the photovoltaic panel array equivalent roughness calculation model is used to calculate the photovoltaic panel array equivalent roughness;

[0011] The total roughness is determined based on the sea surface roughness and the equivalent roughness of the photovoltaic panel array, and the wind speed at the hub height of the wind turbine in the representative annual wind resource dataset is updated according to the total roughness, and the wake attenuation coefficient of the Park model is determined according to the total roughness;

[0012] Calculate the annual power generation of the offshore wind farm based on the wind turbine installation location information, wind turbine structural parameters, updated wind speed at wind turbine hub height and determined wake attenuation coefficient;

[0013] The photovoltaic panel array equivalent roughness calculation model includes:

[0014] ,

[0015] ,

[0016] in, is the equivalent roughness of the photovoltaic panel array, is the center height of the photovoltaic panel surface, is the von Karman constant, and They represent the equivalent geometric spacing between photovoltaic panel units along the wind direction during period t and perpendicular to the wind direction during period t, and They respectively refer to the sea surface roughness and the thrust coefficient of the photovoltaic panel unit during period t.

[0017] The method of calculating the sea surface roughness based on the center height of the photovoltaic panel surface in the photovoltaic panel structural parameters and the representative annual wind resource data set at the height includes:

[0018] ,

[0019] in, is the sea surface roughness at time period t, is the von Karman constant, It is the average wind speed at the center height of the panel during the t period in the annual wind resource dataset.

[0020] The photovoltaic panel unit thrust coefficient during the t period Calculations include:

[0021] Based on the maximum and minimum wind speeds at the center height of the panel in the representative annual wind resource data set, multiple typical wind speeds are divided between the maximum and minimum values;

[0022] The structural modeling is carried out based on the structural parameters of the photovoltaic panel, and the panel thrust of the photovoltaic panel unit under various typical wind speeds is calculated with the help of CFD flow field simulation software;

[0023] Based on the panel thrust and panel area of ​​the photovoltaic panel unit, the thrust coefficient of the photovoltaic panel unit under each typical wind speed is calculated, and a list of corresponding relationships between typical wind speed and thrust coefficient is constructed;

[0024] Based on the wind speed at the center height of the panel in the representative annual wind resource data set for period t , determine the wind speed Typical wind speeds approaching above and below and , and based on and The corresponding thrust coefficient determines the wind speed The corresponding thrust coefficient is used as the thrust coefficient of the photovoltaic panel unit during period t .

[0025] The basis and The corresponding thrust coefficient determines the wind speed The corresponding thrust coefficients include:

[0026] based on and Corresponding thrust coefficient, using interpolation to determine typical wind speed and Wind speed between The corresponding thrust coefficient.

[0027] The method of determining the total roughness based on the sea surface roughness and the photovoltaic panel array equivalent roughness comprises:

[0028] ,

[0029] in, is the total roughness, They respectively refer to the sea surface roughness and the equivalent roughness of the photovoltaic panel array at time period t.

[0030] The updating of the wind speed at the wind turbine hub height in the representative annual wind resource dataset according to the total roughness comprises:

[0031] ,

[0032] ,

[0033] ,

[0034] in, is the updated wind speed at the hub height of the wind turbine during period t, is the friction speed, is the von Karman constant, is the wind turbine hub height, is the total roughness size during period t, is the drag coefficient, is the wind speed at the center of the panel during period t.

[0035] Determining the wake attenuation coefficient of the Park model according to the total roughness includes:

[0036] ,

[0037] in, is the wake attenuation coefficient during period t, is the von Karman constant, is the wind turbine hub height, is the total roughness size during period t.

[0038] The calculation of the annual power generation of the offshore wind farm based on the wind turbine installation location information, the wind turbine structural parameters, the updated wind speed at the wind turbine hub height and the determined wake attenuation coefficient includes:

[0039] Based on wind speed and wind direction, the basic wind conditions are divided, and the representative values ​​of wind direction, wind speed, equivalent roughness of photovoltaic panel array, and wake attenuation coefficient are determined for each basic wind condition;

[0040] Based on the updated wind speed at the hub height of the wind turbine and the wind direction at that height, the proportion of each basic wind condition is calculated;

[0041] A mirror symmetry plane is determined based on the representative value of the equivalent roughness of the photovoltaic panel array, and a virtual wind turbine symmetrical to the wind turbine configuration in the wind farm is configured based on the mirror symmetry plane. The virtual wind turbine has the same wind turbine structural parameters and the same wake evolution law as its corresponding wind turbine.

[0042] Considering the wake effect of each wind turbine in the upwind direction and the virtual wind turbine, calculate the power generation of each wind turbine in the wind farm under each basic wind condition;

[0043] Based on the power generation of each wind turbine in the wind farm under each basic wind condition, the power generation of the wind farm under each basic wind condition is calculated, and combined with the proportion of each basic wind condition, the annual power generation of the wind farm is calculated.

[0044] The basic wind conditions are divided based on wind speed and wind direction, including:

[0045] Based on the wind speed-aerodynamic parameter list of each type of wind turbine in the wind farm, the maximum and minimum values ​​of the wind speed data are determined, and multiple wind speed intervals are divided between the maximum and minimum values;

[0046] Evenly divide the wind direction angle from 0 to 360° and divide it into multiple wind direction sectors;

[0047] The wind speed ranges and wind direction sectors are combined in pairs to form multiple basic wind conditions.

[0048] The determination of the representative value of wind direction, the representative value of wind speed, the representative value of the equivalent roughness of the photovoltaic panel array, and the representative value of the wake attenuation coefficient of each basic wind condition includes:

[0049] The central values ​​of the wind direction sectors and wind speed intervals corresponding to each basic wind condition are taken as the representative values ​​of wind direction and wind speed;

[0050] The average values ​​of the equivalent roughness of the photovoltaic panel array and the wake attenuation coefficient under all time periods belonging to each basic wind condition are calculated as the representative values ​​of the equivalent roughness of the photovoltaic panel array and the wake attenuation coefficient, respectively.

[0051] The proportion of each basic wind condition is calculated based on the updated wind speed at the wind turbine hub height and the wind direction at the height, including:

[0052] Based on the wind direction at the wind turbine hub height and the updated wind speed at each time period in the representative annual wind resource data set, the basic wind conditions assigned to each time period are determined;

[0053] Based on the number of time periods assigned to each basic wind condition and the total number of time periods corresponding to the representative year, the proportion of each basic wind condition is calculated.

[0054] The method of determining the mirror symmetric plane based on the representative value of the equivalent roughness of the photovoltaic panel array includes:

[0055] ,

[0056] in, is the vertical height of the mirror symmetry plane, A is an adjustable parameter, is the representative value of the equivalent roughness of the photovoltaic panel array.

[0057] The calculation of the power generation of each wind turbine in the wind farm under each basic wind condition by considering the wake influence of each wind turbine in the upwind direction and the virtual wind turbine includes:

[0058] Based on the representative wind direction value under basic wind conditions, the wind turbines in the wind farm are sorted and numbered;

[0059] The representative value of the attenuation coefficient is used as the input of the Park model. The effective wind speed at each wind turbine after considering the influence of all upwind wind turbines and the corresponding virtual wind turbine wake is calculated in order of wind turbine numbers from small to large, and then the thrust coefficient and power generation are calculated.

[0060] The attenuation coefficient representative value is used as the input of the Park model, and the effective wind speed after the influence of all upwind wind turbines and the corresponding virtual wind turbine wake is calculated at each wind turbine in order of wind turbine numbers from small to large, including:

[0061] ,

[0062] When i=1, ,

[0063] When i>1, ,

[0064] in, is the wind speed representative value of the basic wind condition m; For wind turbines i The effective wind speed; For wind turbines i The wind speed loss due to the influence of the wake of the upwind wind turbine; and Refers to the upwind wind turbine Virtual Wind Turbine The isolated wake of the target wind turbine i The wind speed loss caused by the location is calculated by the Park model; i,j All are wind turbine numbers. For wind turbines j The corresponding virtual wind turbine number.

[0065] An offshore wind farm annual power generation calculation device applicable to the situation where wind and solar power are in the same field, comprising:

[0066] An information acquisition module is used to obtain the wind turbine installation position information and wind turbine structural parameters of each wind turbine in the wind farm, and to obtain the photovoltaic panel installation position information and photovoltaic panel structural parameters of each photovoltaic panel unit in the photovoltaic panel array arranged in the same field;

[0067] A data acquisition module, used to determine a plurality of representative heights based on wind turbine structural parameters and photovoltaic panel structural parameters, and to acquire a representative annual wind resource data set at the representative heights;

[0068] Roughness calculation module I is used to calculate the sea surface roughness based on the center height of the photovoltaic panel surface in the photovoltaic panel structure parameters and the representative annual wind resource data set at this height;

[0069] Roughness calculation module II is used to calculate the equivalent roughness of the photovoltaic panel array based on the sea surface roughness, photovoltaic panel installation location information, panel center height, and representative annual wind resource data set at the panel center height, using the photovoltaic panel array equivalent roughness calculation model;

[0070] A data updating module is used to determine the total roughness based on the sea surface roughness and the equivalent roughness of the photovoltaic panel array, and to update the wind speed at the hub height of the wind turbine in the representative annual wind resource data set according to the total roughness, and to determine the wake attenuation coefficient of the Park model according to the total roughness;

[0071] A power generation calculation module, used to calculate the annual power generation of the offshore wind farm based on the wind turbine installation location information, wind turbine structural parameters, updated wind speed at the wind turbine hub height and the determined wake attenuation coefficient;

[0072] The photovoltaic panel array equivalent roughness calculation model includes:

[0073] ,

[0074] ,

[0075] in, is the equivalent roughness of the photovoltaic panel array, is the center height of the photovoltaic panel surface, is the von Karman constant, and They represent the equivalent geometric spacing between photovoltaic panel units along the wind direction during period t and perpendicular to the wind direction during period t, and They respectively refer to the sea surface roughness and the thrust coefficient of the photovoltaic panel unit during period t.

[0076] A storage medium stores a computer program that can be executed by a processor, and when the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are on the same field are implemented.

[0077] A device for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field, comprising a memory and a processor, wherein the memory stores a computer program that can be executed by the processor, and when the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field are implemented.

[0078] The beneficial effects of the present invention are as follows: the present invention makes the photovoltaic panel unit equivalent to a small wind turbine, thereby introducing the wind farm equivalent roughness calculation model in the Frandsen model into the photovoltaic panel array equivalent roughness calculation, realizing the approximate calculation of the photovoltaic panel array equivalent roughness, and correcting the hub height wind speed in the inflow based on the photovoltaic panel array equivalent roughness, and correcting the wake attenuation coefficient, thereby realizing the introduction of the influence of the photovoltaic panel into the inflow wind field and the wind turbine wake evolution calculation, so that it can better reflect the actual situation of the wind and solar power in the same field.

[0079] The present invention introduces a virtual wind turbine to quantify the influence of wake reflection caused by photovoltaic panels on wake interference between wind turbines. The virtual wind turbine and the real wind turbine are about a mirror symmetry plane, which is determined based on the equivalent roughness of the photovoltaic panel array to reflect the actual situation of wake reflection as accurately as possible.

[0080] The present invention breaks through the functional limitation that commercial software can only be used for power generation calculation when the wind farm itself exists, and provides a more scientific and practical technical path for the power generation calculation of offshore wind farms in the same wind and solar farms and the profit evaluation based on this. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 A flowchart of an embodiment.

[0082] Figure 2 This is a schematic diagram of a "virtual wind turbine" in the case of offshore wind and solar power in the same field in the embodiment. Figure 2 (a) is the front view. Figure 2 (b) is a side view.

[0083] Figure 3 This is a flow chart for calculating the annual power generation of an offshore wind farm taking into account the impact of photovoltaic panels in an embodiment.

[0084] Figure 4 Schematic diagram of the comparison of the evolution of the wind turbine wake with and without photovoltaic panels in Example 1 of the embodiment, wherein (a) corresponds to the case without photovoltaic panels, and (b) corresponds to the case with photovoltaic panels.

[0085] Figure 5 This is a schematic diagram comparing the wind speed loss of the rear wind turbine disk with and without photovoltaic panels in Example 1 of the embodiment, wherein (a) corresponds to the case without photovoltaic panels, and (b) corresponds to the case with photovoltaic panels. DETAILED DESCRIPTION

[0086] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0087] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0088] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0089] Example 1: Figure 1 As shown, this embodiment is a method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field, which specifically includes the following steps:

[0090] S100, obtaining wind turbine installation position information and wind turbine structural parameters of each wind turbine in the wind farm, and obtaining photovoltaic panel installation position information and photovoltaic panel structural parameters of each photovoltaic panel unit in a photovoltaic panel array arranged in the same field.

[0091] In this embodiment, the wind turbine structural parameters include the model of each wind turbine in the wind farm and the key basic parameters of the model, including the rotor diameter, hub height, wind speed-aerodynamic parameter list, etc.; the photovoltaic panel structural parameters include the panel area of ​​each photovoltaic panel unit in the photovoltaic panel array and the height of the support pole under the photovoltaic panel, etc.

[0092] In this example, the photovoltaic panel unit comprises a support rod and a photovoltaic panel mounted on the upper end of the support rod, and the center position of the photovoltaic panel is connected to the upper end of the support rod.

[0093] S200: Determine multiple representative heights based on wind turbine structural parameters and photovoltaic panel structural parameters, and obtain a representative annual wind resource data set at the representative heights.

[0094] In this embodiment, wind measurement data (including wind speed and wind direction information of all monitoring periods at multiple wind measurement heights) are obtained, and the wind measurement data are processed, including data integrity check, rationality check, and elimination, interpolation, extension of unreasonable data and missing data, representative year correction, etc. The goal is to obtain a representative annual wind resource data set that can reflect the long-term average level of the wind farm area.

[0095] In this embodiment, the representative height includes at least the center height of the panel surface (equal to the height of the support rod below the photovoltaic panel ) and wind turbine hub height .

[0096] A full year contains 365*24=8760 hours. In this embodiment, one hour is used as a period, and the full year is divided into 8760 periods. Taking the representative annual wind resource data set at the center height of the panel (the height of the photovoltaic panel support pole) as an example, the format is as follows:

[0097]

[0098] in, is the average wind speed in the t period in the annual wind resource data set at the center height of the panel (the height of the photovoltaic panel support pole); is the average wind direction in period t in the annual wind resource dataset at the center height of the panel (the height of the photovoltaic panel support pole).

[0099] In this embodiment, the representative annual wind resource data set at the height of the wind turbine hub is in the same form as the representative annual wind resource data set at the height of the photovoltaic panel support pole, and will not be described in detail.

[0100] S300, calculating the sea surface roughness based on the photovoltaic panel surface center height in the photovoltaic panel structural parameters and a representative annual wind resource data set at the height.

[0101] Traverse all time periods in the annual wind resource data set representing the height of the photovoltaic panel support pole and calculate the sea surface roughness in each time period;

[0102] Taking the period numbered t as an example, the corresponding sea surface roughness is Calculated by the following formula:

[0103] ,

[0104] in, is the von Karman constant; is the average wind speed at the height of the photovoltaic panel support pole during period t in the annual wind resource dataset.

[0105] S400, based on the sea surface roughness, the photovoltaic panel installation location information, the panel center height, and the representative annual wind resource data set at the panel center height, the photovoltaic panel array equivalent roughness calculation model is used to calculate the photovoltaic panel array equivalent roughness.

[0106] In this embodiment, all time periods in the annual wind resource data set representing the height of the photovoltaic panel support pole are traversed to calculate the equivalent roughness of the photovoltaic panel array in each time period.

[0107] In this embodiment, the photovoltaic panel unit composed of the photovoltaic panel and the support pole is equivalent to a small wind turbine, and the equivalent roughness calculation model of the wind farm in the Frandsen model commonly used in current wind power engineering is used to quantify the equivalent roughness of the photovoltaic panel array in the field.

[0108] Taking the period numbered t as an example, the equivalent roughness of the photovoltaic panel array is Calculated by the following formula:

[0109] ,

[0110] ,

[0111] in, is the height of the support pole of the photovoltaic panel; is the von Karman constant; and They represent the equivalent geometric spacing between photovoltaic panel units along the wind direction during period t and perpendicular to the wind direction during period t respectively; , They respectively refer to the sea surface roughness and the thrust coefficient of the photovoltaic panel unit during period t.

[0112] In this embodiment and The photovoltaic panel installation position information of each photovoltaic panel unit is determined, specifically including:

[0113] , ,

[0114] ,in ,

[0115] In the above formula, the superscript I represents the first group of two adjacent rows of photovoltaic panel units; m represents the number of groups of two adjacent rows of photovoltaic panel units; n represents the number of wind turbines within the range sandwiched by the adjacent straight lines, n≥2; L represents the distance between two adjacent photovoltaic panel units within the range sandwiched by the adjacent straight lines; It indicates the number of adjacent straight lines without photovoltaic panel units within the range between two adjacent rows of photovoltaic panel units; the subscripts j and k indicate the numbers of two adjacent photovoltaic panel units within the range between the adjacent straight lines.

[0116] In this embodiment It is the average diameter of the small wind turbine rotor equivalent to each photovoltaic panel unit in the photovoltaic panel array.

[0117] In this example, the rotor diameter D of the small wind turbine equivalent to the photovoltaic panel unit is determined based on the wind direction and the corresponding photovoltaic panel surface area. The calculation formula is as follows:

[0118] ,

[0119] in, is the projection area of ​​the corresponding photovoltaic panel surface on the plane perpendicular to the wind direction, and D is the rotor diameter of the small wind turbine equivalent to the photovoltaic panel unit.

[0120] In this embodiment, the thrust coefficient of the photovoltaic panel unit during the period t The calculation includes: based on the average wind speed during period t Compare to the typical wind speed-thrust coefficient table for photovoltaic panel units, such as Corresponding to one of the typical wind speeds, the thrust coefficient corresponding to the typical wind speed is taken as Otherwise, take the closest Two wind speeds and ,satisfy , and In the list and The corresponding thrust coefficient is based on and The corresponding thrust coefficient determines the wind speed The corresponding thrust coefficient is used as the thrust coefficient of the photovoltaic panel unit during period t .

[0121] In this example, interpolation is used to calculate the thrust coefficient of the photovoltaic panel unit. :

[0122] ,

[0123] It should be noted that this example only uses a linear interpolation method as an example, and other available interpolation calculation methods are also within the protection scope of the present invention.

[0124] The method used in this example to construct a table of typical wind speed-thrust coefficients for photovoltaic panel units includes:

[0125] ① Based on the maximum and minimum wind speeds at the center height of the panel in the representative annual wind resource data set, multiple typical wind speeds are divided between the maximum and minimum values.

[0126] Traverse the representative annual wind resource data set at the height of the photovoltaic panel support pole and determine the minimum value of the wind speed data in each period and maximum value , and respectively and Perform rounding down and rounding up, and convert the result after the above processing and Used as lower and upper limits, combined with the set wind speed calculation interval , multiple typical wind speeds are divided and then integrated to form a sequence, which is expressed as follows:

[0127] ,

[0128] Obviously, according to the above segmentation method, the total number of data elements in the sequence (given by It is represented by the number of typical wind speeds. Refers to the sth typical wind speed in the sequence and is determined by the following formula:

[0129] ,

[0130] ②. Structural modeling is performed based on the structural parameters of the photovoltaic panel, and the thrust coefficient of the photovoltaic panel unit under various typical wind speeds is calculated with the help of CFD flow field simulation software.

[0131] Based on the structural parameters of the photovoltaic panel unit, the structure model is built, and with the help of CFD flow field simulation software such as FLUENT and Star CCM+, the panel thrust of the photovoltaic panel unit under each typical wind speed is calculated. Referring to the following formula, the thrust coefficient is obtained:

[0132] ,

[0133] in, is the thrust coefficient of the photovoltaic panel unit at the sth typical wind speed, is the air density, is the panel area of ​​the photovoltaic panel unit, and They respectively refer to the sth typical wind speed and the panel thrust at this typical wind speed.

[0134] Integrate the calculation results to construct a list of typical wind speed-thrust coefficients for photovoltaic panel units in the following form:

[0135]

[0136] S500, determining the total roughness based on the sea surface roughness and the equivalent roughness of the photovoltaic panel array, updating the wind speed at the hub height of the wind turbine in the representative annual wind resource data set according to the total roughness, and determining the wake attenuation coefficient of the Park model according to the total roughness.

[0137] S510, based on the sea surface roughness and the equivalent roughness of the photovoltaic panel array in period t, the total roughness of period t is calculated using the following formula: :

[0138] ,

[0139] in, They respectively refer to the sea surface roughness and the equivalent roughness of the photovoltaic panel array at time period t.

[0140] S520, traverse each time period in the data set representing the annual wind resource at the height of the wind turbine hub, and update the wind speed in each time period according to the total roughness.

[0141] Taking the time period numbered t as an example, the updated wind speed is calculated by the following formula: :

[0142] ,

[0143] in, is the total roughness size during period t, is the friction speed, is the von Karman constant, calculated as:

[0144] ,

[0145] in, is the resistance coefficient, which can be calculated by the following formula:

[0146] ,

[0147] S530: Calculate the attenuation coefficient of the Park model according to the total roughness in each time period.

[0148] The Park model is a mathematical model that describes the wake of wind turbines in wind farms. Its principle is: it is assumed that the wake formed after the airflow passes through the wind turbine impeller is axisymmetric along the center line of the wind turbine, and the wake width increases linearly with the increase of the downwind distance r, but the speed attenuation gradually recovers.

[0149] The core of Park's model is to represent the linear expansion of the wake by defining the wake attenuation coefficient. The wake attenuation coefficient is related to the environmental turbulence and ground roughness. Usually, the wake attenuation coefficient increases with the increase of the environmental turbulence intensity. Different values ​​of the wake attenuation coefficient will directly affect the calculation results of the wake loss and the total power generation.

[0150] The wake attenuation coefficient is the only input parameter that needs to be specified in the Park model. It is used to describe the outward expansion rate of the wake influence area and the recovery of wind speed loss in the wake area as the distance from the wind rotor disk increases.

[0151] According to existing research, the rougher the environment of the wind farm area, the more severe the disturbance of the external flow field to the wind turbine wake. Correspondingly, the outward expansion of the wake influence range and the recovery of wind speed loss are accelerated. In view of this, in this embodiment, referring to the empirical calculation formula commonly used in wind power engineering, according to the total roughness of the time period t , the wake attenuation coefficient at time t is estimated by the following formula: :

[0152] ,

[0153] in, is the von Karman constant, is the wind turbine hub height.

[0154] S600, based on the wind turbine installation location information, wind turbine structural parameters, and the updated wind speed at the wind turbine hub height and the determined wake attenuation coefficient, calculate the annual power generation of the offshore wind farm, see Figure 3 .

[0155] S610. Divide the basic wind conditions based on wind speed and wind direction, determine the representative value of wind direction, representative value of wind speed, representative value of equivalent roughness of photovoltaic panel array, representative value of wake attenuation coefficient of each basic wind condition, and count the proportion of each basic wind condition based on the updated wind speed at the height of the wind turbine hub and the wind direction at that height.

[0156] S611. Based on the wind speed-aerodynamic parameter list of each type of wind turbine in the wind farm, determine the maximum and minimum values ​​of the wind speed data, and divide multiple wind speed intervals between the maximum and minimum values; evenly divide the wind direction angle of 0-360° to divide multiple wind direction sectors; combine the wind speed intervals and wind direction sectors in pairs to form multiple basic wind conditions.

[0157] Based on the wind speed-aerodynamic parameter list of each type of wind turbine in the wind farm, determine the minimum value of the wind speed data and maximum value (corresponding to the minimum cut-in wind speed and the maximum cut-out wind speed of the wind turbines in the wind farm, respectively), and round them down respectively and round up Processing, and then and As lower and upper limits, combined with the set wind speed calculation interval , dividing into multiple different wind speed intervals, the corresponding number of wind speed intervals is , specifically, No. The wind speed interval can be expressed as: .

[0158] According to the set number of wind direction sectors , evenly divide the wind direction angle from 0 to 360°, and divide the wind direction calculation interval into There are multiple wind direction sectors with different wind directions. As the center value of the first wind direction sector, The wind direction sector can be expressed as: .

[0159] Any wind direction sector and any wind speed interval are combined in pairs to obtain multiple different basic wind conditions. The total number of corresponding basic wind conditions is

[0160] S612, classify each time period into the corresponding basic wind condition according to the wind speed and wind direction of each time period in the updated representative annual wind resource data set at the hub height of the wind turbine; after completing the above operation, further count the ratio of the number of time periods under each basic wind condition to the number of time periods in the representative annual wind resource data set, and obtain the proportion of each basic wind condition. Specifically, the proportion of the mth basic wind condition can be calculated by the following formula:

[0161] ,

[0162] in, is the number of time periods classified under the basic wind condition m, and 8760 is the number of time periods in the representative annual wind resource dataset.

[0163] Here, it is important to mention that if the proportion of each basic wind condition is summed up, the sum value is It may be less than 1 because: the wind speed in the annual wind resource dataset is less than and wind speed greater than The period of time is not included in the statistics. This is because when the wind speed is lower than the cut-in wind speed Or higher than the cut-out wind speed When the wind turbine is in shutdown state, even if these time periods are included in the statistics and the basic wind conditions are additionally divided for this purpose, the corresponding wind turbine power generation result is 0, which has no practical significance. In view of this, in order to improve the calculation efficiency, in this embodiment, it is chosen to eliminate these invalid time periods when dividing the basic wind conditions.

[0164] S613. Take the center values ​​of the wind direction sectors and wind speed intervals that constitute each basic wind condition as the representative values ​​of wind direction and wind speed, respectively, and calculate the average values ​​of the equivalent roughness height and wake attenuation coefficient of the photovoltaic panel in all time periods belonging to each basic wind condition, and use them as the representative values ​​of the equivalent roughness and wake attenuation coefficient of the photovoltaic panel array.

[0165] S620. Determine a mirror symmetry plane based on a representative value of the equivalent roughness of the photovoltaic panel array, and configure a virtual wind turbine symmetrical to the wind turbine in the wind farm based on the mirror symmetry plane. The virtual wind turbine and its corresponding wind turbine have the same wind turbine structural parameters and the same wake evolution law.

[0166] Compared with the conventional scenario where only the wind farm exists, when photovoltaic panels are installed in the site, several key points must be considered when calculating the power generation of the wind farm:

[0167] (1) Changes in inflow wind conditions. Specifically, when a photovoltaic array is installed, the environmental roughness of the site increases. According to a large number of existing studies, with the increase in environmental roughness, the vertical shear (also known as wind shear) of the inflow wind profile will become more severe, which will affect the free wind speed at the height of the wind turbine hub.

[0168] (2) The greater environmental roughness caused by the addition of photovoltaic panels will enhance the disturbance of the external environmental flow field to the wind turbine wake, so the parameter values ​​in the analytical model used to describe the wind turbine wake need to be adjusted accordingly.

[0169] (3) As the wind turbine moves away from the rotor disk, its wake continuously exchanges momentum with the external environment flow field, so the range of its influence area expands outward. Under certain wind directions, the expanding wake will contact the photovoltaic panel surface and be reflected, thereby affecting the wind speed and power generation of the downwind wind turbine.

[0170] In contrast to the key points mentioned in the above analysis, the greater environmental roughness caused by the addition of photovoltaic panels, which in turn causes the change in wind speed at the height of the wind turbine hub and the impact on the evolution of the wind turbine wake, has been solved in steps S100 to S500. In order to quantify the impact of the "wake reflection" phenomenon, as shown in Figure 2 As shown, the concept of "virtual wind turbine" is introduced in this embodiment, referring to the equivalent roughness height of the photovoltaic panel array of the basic working condition m , determine the mirror symmetry plane for all Each wind turbine is equipped with a corresponding virtual wind turbine.

[0171] like Figure 2 As shown, the virtual wind turbine has the same geometric features as the corresponding real wind turbine, such as the rotor diameter and the hub height. In addition, the wake evolution law of the two is the same. In this embodiment, when the wake calculation is performed based on the Park model, the same attenuation coefficient will be shared.

[0172] In this embodiment, the expanded wake will contact the photovoltaic panel surface and thus be reflected. Therefore, when the photovoltaic panels are completely distributed around the wind turbine, the horizontal plane where the photovoltaic panel support pole height (the center height of the photovoltaic panel) is located is selected as the mirror symmetry plane, that is, .

[0173] However, in the practice of wind power projects, in order to meet the requirements of ship navigation, operation and maintenance accessibility, and to avoid the influence of light and shadow effects of wind farms, photovoltaic panel units are usually not distributed throughout the entire site. There is a certain distance between them, and the distance between them in different projects may not be the same. In view of this, the center height of the panel cannot accurately represent the height of the wake reflection surface.

[0174] In order to accurately represent the height of the wake reflection surface as much as possible, this embodiment determines the vertical height of the mirror symmetry plane based on the equivalent roughness of the photovoltaic panel array related to the arrangement spacing between photovoltaic panel units. :

[0175] ,

[0176] Among them, A is an adjustable parameter. The accurate value of A can be determined by conducting a series of CFD simulations under multiple typical wind conditions.

[0177] S630, considering the wake influence of each wind turbine in the upwind direction and the virtual wind turbine, calculate the power generation of each wind turbine in the wind farm under each basic wind condition.

[0178] S631. Sort and number the wind turbines in the wind farm based on the representative value of wind direction under basic wind conditions.

[0179] According to the representative value of wind direction along the basic working condition m The relative positions of the wind turbines in the wind farm are The wind turbines are sorted and numbered from 1, and the corresponding numbering sequence can be expressed as .

[0180] In this embodiment, the representative value along the wind direction The front and rear relative positions can be obtained by comparing the sizes of the horizontal coordinates of each wind turbine in the relative coordinate system. Specifically, when the horizontal coordinate is larger, the wind turbine is located further back.

[0181] The relative coordinate system shares the same origin with the geodetic coordinate system and is obtained by rotating the geodetic coordinate system so that in the relative coordinate system, the x-axis points to the wind direction. The geodetic coordinate system is a two-dimensional rectangular coordinate system established by taking any point in the wind farm as the origin of the coordinate system, with the east direction as the positive direction of the x-axis (corresponding to a wind direction angle of 270°) and the north direction as the positive direction of the y-axis (corresponding to a wind direction angle of 180°).

[0182] In this embodiment, the horizontal coordinate in the relative coordinate system is calculated by the following formula, taking the wind turbine numbered i as an example:

[0183] ,

[0184] in, and are the horizontal and vertical coordinates of wind turbine i in the geodetic coordinate system and the relative coordinate system, respectively.

[0185] S632. Using the representative value of the attenuation coefficient as the input of the Park model, the effective wind speed after the influence of the wake of all upwind wind turbines and the corresponding virtual wind turbine is calculated at each wind turbine in order of wind turbine numbers from small to large, and then the thrust coefficient and power generation are calculated.

[0186] Taking the wind turbine numbered i as an example, the details are as follows:

[0187] When i=1, it means that there is no other wind turbine upwind of the target wind turbine i, and it is not affected by the wake interference. The corresponding wind speed loss is ;

[0188] When i>1, the target wind turbine i operates under the influence of the wakes of multiple wind turbines in the upwind direction. In this embodiment, the wake calculation method of WAsP, a commonly used design software in wind power engineering, is referred to, and the overlapping effect of the wakes of multiple wind turbines is processed by square sum superposition, that is, the wind speed loss at the target wind turbine i under the influence of the wakes of multiple wind turbines is calculated by the following formula:

[0189] ,

[0190] in, and Refers to the upwind wind turbine Virtual Wind Turbine The wind speed loss caused by the isolated wake of at the target wind turbine i is calculated by the Park model.

[0191] For ease of understanding, the Park model is briefly described as follows. It is the most widely used wind turbine wake calculation model in current wind power engineering practice and is used as the development kernel by commercial software such as WAsP and WT. In this model, it is assumed that at each downstream position behind the wind rotor disk, the wake influence area is circular, and within this circular domain, the velocity loss is a constant. The center point of the wind rotor disk is taken as the center of the circle. As the wake propagates downstream, the diameter of the aforementioned circular wake influence area expands linearly, and at the wind rotor position, the wake diameter is taken as the wind rotor diameter. Based on the above, it can be calculated by the following formulas respectively and :

[0192] ,

[0193] ,

[0194] in, For wind turbines The wind wheel area, and Respectively represent wind turbines The isolated wake of the target wind turbine The velocity loss magnitude and circular impact area at the wind turbine As mentioned above, the Park model ignores the spanwise change of velocity loss in the wake region relative to the center of the wind rotor disk, and considers it to be only related to the flow spacing. and The same size, the calculation formula is:

[0195] ,

[0196] ,

[0197] in, , and Wind turbine The effective wind speed, thrust coefficient and rotor diameter, It is the representative attenuation coefficient under the target basic wind condition m. and are the horizontal coordinates of wind turbine i and wind turbine j in the relative coordinate system, respectively, because the x-axis direction of the relative coordinate system represents the wind direction , so represents the flow distance between wind turbine i and wind turbine j along the wind direction, is the diameter of the circular wake influence area of ​​the isolated wake of wind turbine j at wind turbine i.

[0198] Loss according to wind speed , the effective wind speed of the target wind turbine i can be calculated by the following formula: :

[0199] ,

[0200] in, That is the representative wind speed of the target basic wind condition m.

[0201] The effective wind speed calculated above is , combined with the wind speed-aerodynamic parameter list of the target wind turbine i, the thrust coefficient and power generation are obtained through interpolation calculation. The calculation formula is:

[0202] ,

[0203] ,

[0204] in, and The closest wind speed-aerodynamic coefficient in the list of the corresponding model The two wind speeds meet , and , and The wind speeds in the list and Corresponding thrust coefficient and power.

[0205] By summing the output power of each wind turbine, the wind farm power generation under the target basic wind condition m is obtained: , the calculation formula is:

[0206] ,

[0207] Among them, i is the wind turbine serial number, and its value range is , It represents the power generation of wind turbine with serial number i under the target basic wind condition m.

[0208] S640. Calculate the power generation of the wind farm under each basic wind condition based on the power generation of each wind turbine in the wind farm under each basic wind condition, and calculate the annual power generation of the wind farm in combination with the proportion of each basic wind condition.

[0209] Traversing all basic wind conditions, the annual power generation of the wind farm is calculated by the following formula :

[0210] ,

[0211] Among them, m refers to the basic wind condition number, ranging from , and represents the proportion of the mth basic wind condition and the wind farm power generation calculated in step S630 in turn.

[0212] The following is a specific example of this embodiment:

[0213] Example 1: Take the example of arranging a photovoltaic panel array between two wind turbines. Figure 4 The normalized velocity loss cloud diagram in the wake area of ​​the front row wind turbines with / with photovoltaic panels is shown. Figure 5 The wind speed loss at the rear wind turbines with and without photovoltaic panels is further compared, where the white circle represents the wind rotor disk of the rear wind turbines. More specifically, in the above two figures, sub-figure (a) corresponds to the case without photovoltaic panels, and sub-figure (b) corresponds to the case with photovoltaic panels. It can be seen that after the photovoltaic panels are added, the wake of the front wind turbines is restored faster, and at the same downstream position behind the wind rotor disk, the normalized wind speed loss in the wake area is significantly reduced; in addition, Figure 5 As can be seen from (b) in the figure, due to the wake reflection caused by the photovoltaic panels, the wind speed loss in the area below the wind rotor disk of the rear wind turbine increases compared to when there are no photovoltaic panels.

[0214] Embodiment 2: This embodiment is an offshore wind farm annual power generation calculation device applicable to the situation where wind and solar power are in the same field, including: an information acquisition module, a data acquisition module, a roughness calculation module I, a roughness calculation module II, a data update module and a power generation calculation module, etc.

[0215] In this example, the information acquisition module is used to obtain the wind turbine installation location information and wind turbine structural parameters of each wind turbine in the wind farm, and to obtain the photovoltaic panel installation location information and photovoltaic panel structural parameters of each photovoltaic panel unit in the photovoltaic panel array arranged in the same field.

[0216] The data acquisition module is used to determine multiple representative heights based on wind turbine structural parameters and photovoltaic panel structural parameters, and to acquire representative annual wind resource data sets at the representative heights.

[0217] In this embodiment, the roughness calculation module I is used to calculate the sea surface roughness based on the photovoltaic panel surface center height in the photovoltaic panel structure parameters and the representative annual wind resource data set at the height.

[0218] Roughness calculation module II is used to calculate the equivalent roughness of the photovoltaic panel array based on the sea surface roughness, photovoltaic panel installation location information, panel center height, and representative annual wind resource data set at the panel center height, using the photovoltaic panel array equivalent roughness calculation model.

[0219] The calculation model of the equivalent roughness of photovoltaic panel array includes:

[0220] ,

[0221] ,

[0222] in, is the equivalent roughness of the photovoltaic panel array; is the center height of the photovoltaic panel surface; is the von Karman constant; and They represent the equivalent geometric spacing between photovoltaic panel units along the wind direction during period t and perpendicular to the wind direction during period t, respectively, and are determined based on the photovoltaic panel installation location information; and They respectively refer to the sea surface roughness and the thrust coefficient of the photovoltaic panel unit during period t.

[0223] In this embodiment, the data updating module is used to determine the total roughness based on the sea surface roughness and the equivalent roughness of the photovoltaic panel array, and to update the wind speed at the hub height of the wind turbine in the representative annual wind resource data set according to the total roughness, and to determine the wake attenuation coefficient of the Park model according to the total roughness.

[0224] In this embodiment, the power generation calculation module is used to calculate the annual power generation of the offshore wind farm based on the wind turbine installation location information, wind turbine structural parameters, updated wind speed at the wind turbine hub height and the determined wake attenuation coefficient.

[0225] 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 applicable to the situation where wind and solar power are on the same field in Embodiment 1 are implemented.

[0226] Embodiment 4: This embodiment is a device for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field, comprising a memory and a processor, wherein the memory stores a computer program that can be executed by the processor, and when the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field in Embodiment 1 are implemented.

Claims

1. A method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field, characterized in that: include: Obtain wind turbine installation location information and wind turbine structural parameters of each wind turbine in the wind farm, and obtain photovoltaic panel installation location information and photovoltaic panel structural parameters of each photovoltaic panel unit in a photovoltaic panel array arranged in the same field; Determine multiple representative heights based on wind turbine structural parameters and photovoltaic panel structural parameters, and obtain a representative annual wind resource data set at the representative heights; The sea surface roughness is calculated based on the center height of the photovoltaic panel surface in the photovoltaic panel structural parameters and the representative annual wind resource data set at the height; Based on the sea surface roughness, photovoltaic panel installation location information, panel center height, and representative annual wind resource data set at the panel center height, the photovoltaic panel array equivalent roughness calculation model is used to calculate the photovoltaic panel array equivalent roughness; The total roughness is determined based on the sea surface roughness and the equivalent roughness of the photovoltaic panel array, and the wind speed at the hub height of the wind turbine in the representative annual wind resource dataset is updated according to the total roughness, and the wake attenuation coefficient of the Park model is determined according to the total roughness; Calculate the annual power generation of the offshore wind farm based on the wind turbine installation location information, wind turbine structural parameters, updated wind speed at wind turbine hub height and determined wake attenuation coefficient; The photovoltaic panel array equivalent roughness calculation model includes: ， ， in, is the equivalent roughness of the photovoltaic panel array, is the center height of the photovoltaic panel surface, is the von Karman constant, and They represent the equivalent geometric spacing between photovoltaic panel units along the wind direction during period t and perpendicular to the wind direction during period t, and They respectively refer to the sea surface roughness and the thrust coefficient of the photovoltaic panel unit during period t.

2. The method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field according to claim 1 is characterized in that: The method of calculating the sea surface roughness based on the center height of the photovoltaic panel surface in the photovoltaic panel structural parameters and the representative annual wind resource data set at the height includes: ， in, is the sea surface roughness at time period t, is the von Karman constant, It is the average wind speed at the center height of the panel during the t period in the annual wind resource dataset.

3. The method for calculating annual power generation of an offshore wind farm applicable to wind and solar power co-existing in the same field according to claim 1 is characterized in that: The photovoltaic panel unit thrust coefficient during the t period Calculations include: Based on the maximum and minimum wind speeds at the center height of the panel in the representative annual wind resource data set, multiple typical wind speeds are divided between the maximum and minimum values; The structural modeling is carried out based on the structural parameters of the photovoltaic panel, and the panel thrust of the photovoltaic panel unit under various typical wind speeds is calculated with the help of CFD flow field simulation software; Based on the panel thrust and panel area of ​​the photovoltaic panel unit, the thrust coefficient of the photovoltaic panel unit under each typical wind speed is calculated, and a list of corresponding relationships between typical wind speed and thrust coefficient is constructed; Based on the wind speed at the center height of the panel in the representative annual wind resource data set for period t , determine the wind speed Typical wind speeds approaching above and below and , and based on and The corresponding thrust coefficient determines the wind speed The corresponding thrust coefficient is used as the thrust coefficient of the photovoltaic panel unit during period t .

4. The method for calculating annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field according to claim 3 is characterized in that: The basis and The corresponding thrust coefficient determines the wind speed The corresponding thrust coefficients include: based on and Corresponding thrust coefficient, using interpolation to determine typical wind speed and Wind speed between The corresponding thrust coefficient.

5. The method for calculating annual power generation of an offshore wind farm applicable to wind and solar power co-existing in the same field according to claim 1 is characterized in that: The method of determining the total roughness based on the sea surface roughness and the photovoltaic panel array equivalent roughness comprises: ， in, is the total roughness, They respectively refer to the sea surface roughness and the equivalent roughness of the photovoltaic panel array at time period t.

6. The method for calculating annual power generation of an offshore wind farm applicable to wind and solar power co-existing in the same field according to claim 1 is characterized in that: The updating of the wind speed at the wind turbine hub height in the representative annual wind resource dataset according to the total roughness comprises: ， ， ， in, is the updated wind speed at the hub height of the wind turbine during period t, is the friction speed, is the von Karman constant, is the wind turbine hub height, is the total roughness size during period t, is the drag coefficient, is the wind speed at the center of the panel during period t.

7. The method for calculating annual power generation of an offshore wind farm applicable to wind and solar power co-existing in the same field according to claim 1 is characterized in that: Determining the wake attenuation coefficient of the Park model according to the total roughness includes: ， in, is the wake attenuation coefficient during period t, is the von Karman constant, is the wind turbine hub height, is the total roughness size during period t.

8. The method for calculating annual power generation of an offshore wind farm applicable to wind and solar power co-existing in the same field according to claim 1 is characterized in that: The calculation of the annual power generation of the offshore wind farm based on the wind turbine installation location information, the wind turbine structural parameters, the updated wind speed at the wind turbine hub height and the determined wake attenuation coefficient includes: Based on wind speed and wind direction, the basic wind conditions are divided, and the representative values ​​of wind direction, wind speed, equivalent roughness of photovoltaic panel array, and wake attenuation coefficient are determined for each basic wind condition; Based on the updated wind speed at the hub height of the wind turbine and the wind direction at that height, the proportion of each basic wind condition is calculated; A mirror symmetry plane is determined based on the representative value of the equivalent roughness of the photovoltaic panel array, and a virtual wind turbine symmetrical to the wind turbine configuration in the wind farm is configured based on the mirror symmetry plane. The virtual wind turbine has the same wind turbine structural parameters and the same wake evolution law as its corresponding wind turbine. Considering the wake effect of each wind turbine in the upwind direction and the virtual wind turbine, calculate the power generation of each wind turbine in the wind farm under each basic wind condition; Based on the power generation of each wind turbine in the wind farm under each basic wind condition, the power generation of the wind farm under each basic wind condition is calculated, and combined with the proportion of each basic wind condition, the annual power generation of the wind farm is calculated.

9. The method for calculating annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field according to claim 8 is characterized in that: The basic wind conditions are divided based on wind speed and wind direction, including: Based on the wind speed-aerodynamic parameter list of each type of wind turbine in the wind farm, the maximum and minimum values ​​of the wind speed data 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.

10. The method for calculating annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field according to claim 9 is characterized in that: The determination of the representative value of wind direction, the representative value of wind speed, the representative value of the equivalent roughness of the photovoltaic panel array, and the representative value of the wake attenuation coefficient of each basic wind condition includes: The central values ​​of the wind direction sectors and wind speed intervals corresponding to each basic wind condition are taken as the representative values ​​of wind direction and wind speed; The average values ​​of the equivalent roughness of the photovoltaic panel array and the wake attenuation coefficient under all time periods belonging to each basic wind condition are calculated as the representative values ​​of the equivalent roughness of the photovoltaic panel array and the wake attenuation coefficient, respectively.

11. The method for calculating annual power generation of an offshore wind farm applicable to wind and solar power co-existing in the same field according to claim 8, characterized in that: The calculation of the proportion of each basic wind condition based on the updated wind speed at the wind turbine hub height and the wind direction at the height includes: Based on the wind direction at the height of the wind turbine hub in each period in the representative annual wind resource data set and the updated wind speed at the height, the basic wind conditions assigned to each period are determined; Based on the number of time periods assigned to each basic wind condition and the total number of time periods corresponding to the representative year, the proportion of each basic wind condition is calculated.

12. The method for calculating annual power generation of an offshore wind farm applicable to wind and solar power co-existing in the same field according to claim 8, characterized in that: The method of determining the mirror symmetric plane based on the representative value of the equivalent roughness of the photovoltaic panel array comprises: ， in, is the vertical height of the mirror symmetry plane, A is an adjustable parameter, is the representative value of the equivalent roughness of the photovoltaic panel array under the basic wind condition m.

13. The method for calculating annual power generation of an offshore wind farm applicable to wind and solar power co-existing in the same field according to claim 8, characterized in that: The calculation of the power generation of each wind turbine in the wind farm under each basic wind condition by considering the wake influence of each wind turbine in the upwind direction and the virtual wind turbine includes: Based on the representative wind direction value under basic wind conditions, the wind turbines in the wind farm are sorted and numbered; The representative value of the attenuation coefficient is used as the input of the Park model. The effective wind speed at each wind turbine after considering the influence of all upwind wind turbines and the corresponding virtual wind turbine wake is calculated in order of wind turbine numbers from small to large, and then the thrust coefficient and power generation are calculated.

14. The method for calculating annual power generation of an offshore wind farm applicable to the situation where wind and solar power are in the same field according to claim 13, characterized in that: The attenuation coefficient representative value is used as the input of the Park model, and the effective wind speed after the influence of all upwind wind turbines and the corresponding virtual wind turbine wake is calculated at each wind turbine in order of wind turbine numbers from small to large, including: ， When i=1, , When i>1, , in, is the wind speed representative value of the basic wind condition m; For wind turbines i The effective wind speed; For wind turbines i The wind speed loss due to the influence of the wake of the upwind wind turbine; and Refers to the upwind wind turbine Virtual Wind Turbine The isolated wake of the target wind turbine i The wind speed loss caused by the location is calculated by the Park model; i,j All are wind turbine numbers. For wind turbines j The corresponding virtual wind turbine number.

15. An offshore wind farm annual power generation calculation device applicable to wind and solar power co-existing in the same field, characterized in that: include: An information acquisition module is used to obtain the wind turbine installation position information and wind turbine structural parameters of each wind turbine in the wind farm, and to obtain the photovoltaic panel installation position information and photovoltaic panel structural parameters of each photovoltaic panel unit in the photovoltaic panel array arranged in the same field; A data acquisition module, used to determine a plurality of representative heights based on wind turbine structural parameters and photovoltaic panel structural parameters, and to acquire a representative annual wind resource data set at the representative heights; Roughness calculation module I is used to calculate the sea surface roughness based on the center height of the photovoltaic panel surface in the photovoltaic panel structure parameters and the representative annual wind resource data set at this height; Roughness calculation module II is used to calculate the equivalent roughness of the photovoltaic panel array based on the sea surface roughness, photovoltaic panel installation location information, panel center height, and representative annual wind resource data set at the panel center height, using the photovoltaic panel array equivalent roughness calculation model; A data updating module is used to determine the total roughness based on the sea surface roughness and the equivalent roughness of the photovoltaic panel array, and to update the wind speed at the hub height of the wind turbine in the representative annual wind resource data set according to the total roughness, and to determine the wake attenuation coefficient of the Park model according to the total roughness; A power generation calculation module, used to calculate the annual power generation of the offshore wind farm based on the wind turbine installation location information, wind turbine structural parameters, updated wind speed at the wind turbine hub height and the determined wake attenuation coefficient; The photovoltaic panel array equivalent roughness calculation model includes: ， ， in, is the equivalent roughness of the photovoltaic panel array, is the center height of the photovoltaic panel surface, is the von Karman constant, and They represent the equivalent geometric spacing between photovoltaic panel units along the wind direction during period t and perpendicular to the wind direction during period t, and They respectively refer to the sea surface roughness and the thrust coefficient of the photovoltaic panel unit during period t.

16. 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 applicable to the situation where wind and solar power are on the same site as described in claims 1 to 14 are implemented.

17. An offshore wind farm annual power generation calculation device applicable to the situation where wind and solar power are in the same field, comprising a memory and a processor, wherein a computer program executable by the processor is stored in the memory, and wherein: When the computer program is executed, the steps of the method for calculating the annual power generation of an offshore wind farm applicable to the situation where wind and solar power are on the same site as described in claims 1 to 14 are implemented.

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