Micro-siting method for wind farm based on micro-meteorology and micro-topography coupling

Abstract

This invention discloses a micro-site selection method for wind farms based on the coupling of micro-meteorology and micro-topography, relating to the field of wind power processing technology. The method includes: determining the annual total power generation model of the target wind farm, which is obtained by summing the target wake models of each wind turbine, used to calculate the annual power generation of each turbine; using the maximization of annual total power generation as the optimization objective, searching for the optimal location of each turbine in the annual total power generation model using the PSO algorithm to obtain the optimal location of each turbine in the target wind farm; the target wake model of each turbine is determined by the turbine parameters, altitude, moist air density, location, and turbine availability of each turbine. Through this technical solution, the influence of key physical factors such as altitude on wake and turbine output can be corrected, improving the accuracy and reliability of turbine location, and thus improving the accuracy and reliability of annual power generation prediction.

Description

Technical Field

[0001] This invention relates to the field of wind power processing technology, specifically to a wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography. Background Technology

[0002] High-altitude areas are rich in wind energy resources and are one of the strategic core areas for wind power development in my country. Micro-site selection is a crucial early step in wind farm development, and its core is to use wake models to accurately assess annual power generation and optimize turbine layout. The wake effect is the main source of energy loss within a wind farm, typically accounting for 10%-20% of total power generation loss. Therefore, the accuracy of the wake model directly determines the economic feasibility of the wind farm.

[0003] As the global energy structure shifts towards cleaner energy, wind power development is gradually expanding into high-altitude, complex mountainous areas. However, this unique and extreme environment presents significant technical challenges and places higher demands on the precise planning and reliable operation of wind farms. Using traditional wake models for micro-situation of wind farms is a common technique, but existing micro-situation strategies do not fully consider the specific characteristics of high-altitude environments. They are typically based solely on flat terrain or standard atmospheric conditions, failing to effectively couple the dynamic changes in air density and the strong topographic effects unique to high altitudes. Furthermore, current micro-situation processes largely focus on maximizing theoretical annual power generation, largely ignoring the actual operating conditions in high-altitude areas. High-altitude wind farms currently face harsh climate conditions, such as cold, icing, and complex terrain. The poor accessibility of operation and maintenance equipment and personnel leads to high turbine failure rates and short maintenance windows, which seriously affect the actual availability and operational efficiency of wind farms. This may also result in wind farm investment returns being far lower than expected, and even affect the stable supply of regional energy. If we continue to use methods based on flat terrain and standard atmospheric conditions for micro-site selection of wind farms, it will reduce the accuracy and reliability of the layout of wind turbines in the wind farm, thereby reducing the accuracy of the annual total power generation assessment of the wind farm. Summary of the Invention

[0004] The purpose of this invention is to provide a micro-site selection method for wind farms based on the coupling of micro-meteorology and micro-topography, so as to solve the technical problems existing in related technologies.

[0005] To achieve the above objectives, this invention provides a wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography, comprising:

[0006] A model for the total annual power generation of the target wind farm is determined, wherein the total annual power generation model is obtained by adding the target wake models of each wind turbine, and the target wake models are used to calculate the annual power generation of the wind turbines.

[0007] With the goal of maximizing the total annual power generation, the PSO algorithm is used to search for the optimal layout of each wind turbine in the annual total power generation model to obtain the optimal layout of each wind turbine in the target wind farm.

[0008] The target wake model of the wind turbine is determined by the wind turbine parameters, the wind turbine altitude, the humid air density at the location of the wind turbine, the layout of the wind turbine, and the wind turbine availability rate.

[0009] Optionally, the availability of the fan is determined by the following method:

[0010] Determine the composite failure factors of the wind turbine;

[0011] The synthetic fault impact factor is used as the quantitative benchmark for wind turbine fault status. The target random number is randomly sampled using the Monte Carlo simulation method, and the comparison result between the target random number and the synthetic fault impact factor is determined.

[0012] The status of the wind turbine is determined based on the comparison results. When the wind turbine is in normal operation, the availability rate is the first threshold; otherwise, the availability rate is the second threshold.

[0013] Optionally, the target wake model is expressed by the following calculation formula: ; ; ; in, The first of the downstream wind turbines The actual inflow velocity of the typhoon fan For downstream The free-inflow velocity of the typhoon fan. Topographical influencing factors For the downstream wind turbine A collection of upstream wind turbines affected by typhoons. For the upstream Typhoon generator and downstream Overlap area factor of typhoon generators Let be the thrust coefficient of the j-th wind turbine in the upstream wind turbines. The wake attenuation coefficient is... The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine Downwind distance between typhoon generators Let be the rotor diameter of the j-th wind turbine in the upstream wind turbine series. The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine The relative distance between the typhoon generators on the y-axis The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine The relative distance between the typhoon generators on the z-axis The first of the upstream wind turbines The wake of the typhoon is the first in the downstream wind turbine. The horizontal radius of the typhoon's spread. The first of the upstream wind turbines The wake of the typhoon is the first in the downstream wind turbine. The radius of diffusion in the vertical direction of the typhoon generator's location. This is the slope sensitivity coefficient. The slope angle, The terrain affects the height scale. The first of the downstream wind turbines The power generation of typhoon generators, The first of the downstream wind turbines The rotor sweep area of ​​a typhoon fan. The first of the downstream wind turbines The power factor of a typhoon turbine. The density of moist air. The first of the downstream wind turbines The availability rate of typhoon turbines. This is the difference between the wheel hub height and the reference point height.

[0014] Optionally, the density of the moist air This can be expressed by the following calculation formula: ; in, Atmospheric pressure. For water vapor partial pressure, For air temperature, The gas constant of water vapor. The gas constant for dry air. This represents the vertical temperature lapse rate. Altitude The molar mass of dry air, It is the acceleration due to gravity. Relative humidity, This is the universal gas constant. The saturated vapor pressure at the current temperature. Standard atmospheric pressure at sea level. This is the standard temperature.

[0015] Optionally, the upstream wind turbine of the first The wake of the typhoon is the first in the downstream wind turbine. The horizontal diffusion radius of the typhoon generator's location This can be expressed by the following calculation formula: ; in, The horizontal diffusion coefficient is... The length of the surface roughness. For Richardson's number;

[0016] The upstream wind turbine The wake of the typhoon is the first in the downstream wind turbine. The vertical diffusion radius of the typhoon generator's location This can be expressed by the following calculation formula: ; in, The vertical diffusion coefficient is... This refers to altitude.

[0017] Optionally, the upstream first Typhoon generator and downstream Overlap area factor of typhoon generators This can be expressed by the following calculation formula: ; ;

[0018] in, The first of the upstream wind turbines The rotor swept area of ​​the typhoon turbine ranks first among downstream wind turbines. The overlapping area of ​​the typhoon's wake cross-section perpendicular to the incoming flow direction. The first of the downstream wind turbines The location of the typhoon generator represents the angle of deflection of the equivalent inflow wind direction in the vertical plane relative to the horizontal plane. For the radius of the wind turbine, For the upstream Typhoon generators and downstream Spatial distance between typhoon generators. The first of the downstream wind turbines The typhoon turbine rotor sweep circle and the upstream turbine middle section The length of the chord formed by the intersection of the equivalent wake cross-section circles of a typhoon generator in a plane perpendicular to the direction of incoming flow. The distance from the center of the wake to the chord of the intersection of the two circles is denoted as . The first of the downstream wind turbines The vertical displacement of the typhoon fan. The first of the upstream wind turbines The vertical displacement of the typhoon fan. The first of the upstream wind turbines The displacement of the typhoon fan along the y-axis. The first of the downstream wind turbines The displacement of the typhoon fan along the y-axis; The first of the upstream wind turbines The typhoon generator is the first unit in the downstream section. The equivalent wake radius of a typhoon.

[0019] Optionally, the downstream wind turbine of the first The angle between the vertical and horizontal directions at the location of the typhoon generator This can be expressed by the following calculation formula: ; in, The first of the downstream wind turbines The horizontal wind direction angle of the terrain where the typhoon generator is located. The first of the downstream wind turbines The slope angle of the terrain where the typhoon generator is located. The first of the downstream wind turbines The terrain where the typhoon generator is located causes a change in wind direction. The first of the upstream wind turbines The wake of the typhoon caused the downstream wind turbine to... The direction of the wind deflection at the location of the typhoon generator The free-flow wind direction, after being corrected by topography and wake, affects the downstream first... The overall wind direction angle at the location of the typhoon generator. The free-flow wind direction angle represents the large-scale wind direction before entering the wind farm. The deflection attenuation length, The angle between the free-flow wind direction and the ridgeline. The first of the downstream wind turbines The altitude of the typhoon machine The first of the downstream wind turbines The typhoon generator is located in the spatial coordinates of the lateral direction of the wind. This is the deflection sensitivity coefficient.

[0020] Optionally, the synthetic failure impact factor is calculated using the following expression: ; in, The first of the downstream wind turbines Composite failure factors of typhoon generators The base failure rate used for correction. For maintenance accessibility factors, For the accessibility sensitivity coefficient of maintenance, The sensitivity coefficient for weather maintainability. Meteorological influencing factors, To maintain the accessibility slope attenuation coefficient, The first of the downstream wind turbines The slope of the location where the typhoon generator is located.

[0021] The above technical solution involves summing the target wake models of each wind turbine in the target wind farm to obtain the annual total power generation model. With maximizing the annual total power generation as the optimization objective, the PSO algorithm is used to search for the optimal layout location of each wind turbine in the annual total power generation model, thus obtaining the optimal layout location for each wind turbine in the target wind farm. The target wake model for each wind turbine is determined by its turbine parameters, altitude, humid air density at its location, layout location, and availability. Using the altitude, humid air density, and turbine layout location of the wind farm area to construct the target wake model ensures high computational efficiency and corrects for the impact of key physical factors such as altitude on the wake and turbine output, thereby improving the accuracy of the annual total power generation assessment. Using the turbine availability rate of the wind farm area to construct the target wake model improves the accuracy and reliability of the turbine layout location, thus enhancing the accuracy and reliability of the annual power generation prediction.

[0022] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0023] Figure 1 This is a schematic diagram illustrating a wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to an exemplary embodiment of the present invention.

[0024] Figure 2 This is a schematic diagram illustrating the process of constructing a target wake model according to an exemplary embodiment of the present invention. Detailed Implementation

[0025] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, so as to provide a better understanding of the concept of the present invention, the technical problem solved, the technical features constituting the technical solution, and the technical effects brought about.

[0026] In the first related technologies, high-precision computational fluid dynamics (CFD) or large eddy simulation (LES) methods are employed. The core idea is to accurately capture the fine structure of complex terrain flow fields, atmospheric stability, and wakes by solving fluid dynamics equations. CFD / LES methods can accurately assess terrain effects. Specifically, CFD can numerically simulate computational fluid motion, while LES can directly simulate large-scale eddies with high energy proportions in the flow field, and approximate small-scale eddies using sub-grid models. While these methods have advantages in theoretical analysis, their computational and time costs are extremely high. In micro-site selection, optimization algorithms such as PSO require iterative evaluation of thousands of layout schemes, and CFD / LES methods suffer from a "practicality bottleneck," making them difficult to directly apply to large-scale site selection optimization calculations.

[0027] In the second related technology, the most mainstream method currently used in industry for large-scale micro-site optimization is the analytical / semi-empirical model, such as the Jensen model and the Larsen model. These methods are based on momentum conservation and simplified physical assumptions, employing a "top-hat" velocity profile and linear wake extension, resulting in extremely high computational efficiency. However, the core assumptions of these models are flat terrain and standard atmospheric conditions. They fail to consider the dynamic changes in air density with air pressure, temperature, and humidity at high altitudes, and also fail to effectively handle the acceleration, deceleration, and deflection effects of complex mountainous terrain on airflow.

[0028] However, the inventors discovered that existing mainstream analytical wake models are developed based on flat terrain and standard atmospheric conditions, neglecting the key physical characteristics of high-altitude regions, namely micro-meteorological and micro-topographical factors. This leads to low model accuracy and large prediction bias. At high altitudes, air pressure is low, temperature varies greatly, and air density is significantly lower than at sea level and dynamically changing. Simultaneously, complex mountainous terrain has a significant acceleration and deflection effect on airflow. Existing analytical models ignore these two core factors, and their assumptions are severely inconsistent with actual conditions at high altitudes. This inevitably leads to distorted wake predictions, resulting in significant deviations in annual power generation assessments and a substantial overestimation of power generation potential. This severe overestimation greatly affects the reliability of project investment decisions.

[0029] Most existing micro-level site selection optimization models focus solely on maximizing theoretical annual power generation, neglecting the harsh operating conditions and maintenance constraints of high-altitude regions. This leads to insufficient actual operational efficiency and reliability of the site selection schemes. High-altitude areas suffer from harsh climates and complex terrain, resulting in high turbine failure rates, short maintenance windows, poor accessibility, and extremely high maintenance costs. Existing site selection strategies ignore the reduced unit availability caused by these factors, meaning that the optimized "layout" may fail to achieve the expected power generation benefits in actual operation due to frequent or prolonged outages. As related analyses show, neglecting failure rates leads to a significant overestimation of AEP (Annual Energy Production), reducing the robustness and reliability of the site selection scheme.

[0030] In view of this, the present invention provides a wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography to solve the technical problems existing in the above-mentioned related technologies.

[0031] like Figure 1 As shown, Figure 1 This is a schematic diagram illustrating a wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to an exemplary embodiment of the present invention, with reference to... Figure 1 The method includes;

[0032] S101: Determine the annual total power generation model of the target wind farm, wherein the annual total power generation model is obtained by adding the target wake models of each wind turbine, and the target wake models are used to calculate the annual power generation of the wind turbines.

[0033] S102: With the goal of maximizing the total annual power generation, the PSO algorithm is used to search for the layout location of each wind turbine in the total annual power generation model to obtain the optimal layout location of each wind turbine in the target wind farm.

[0034] The target wake model of the wind turbine is determined by the wind turbine parameters, the wind turbine altitude, the humid air density at the location of the wind turbine, the layout of the wind turbine, and the wind turbine availability rate.

[0035] The above technical solution involves summing the target wake models of each wind turbine in the target wind farm to obtain the annual total power generation model. With maximizing the annual total power generation as the optimization objective, the PSO algorithm is used to search for the optimal layout location of each wind turbine in the annual total power generation model, thus obtaining the optimal layout location for each wind turbine in the target wind farm. The target wake model for each wind turbine is determined by its turbine parameters, altitude, humid air density at its location, layout location, and availability. Using the altitude, humid air density, and turbine layout location of the wind farm area to construct the target wake model ensures high computational efficiency and corrects for the impact of key physical factors such as altitude on the wake and turbine output, thereby improving the accuracy of the annual total power generation prediction. Using the turbine availability rate of the wind farm area to construct the target wake model improves the accuracy and reliability of the turbine layout location, further enhancing the accuracy and reliability of the annual power generation prediction.

[0036] To enable those skilled in the art to better understand the wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography provided by the present invention, the above steps are illustrated in detail below.

[0037] For example, the target wind farm can be a wind farm in a high-altitude area and / or in a complex mountainous terrain; however, this embodiment of the invention does not specifically limit this. The annual total power generation model can be used to assess the total electricity that the target wind farm can generate over a year. In this embodiment, the target wind farm includes multiple wind turbines, and the electricity generated by each turbine can correspond to a target wake model. When calculating the annual total power generation model of the target wind farm, the target wake models corresponding to each wind turbine can be added together, that is, the annual power generation of each wind turbine is added together to obtain the annual total power generation model. The target wake model can be a mathematical model used to describe the low-speed, high-turbulence region (i.e., wake) downstream of the wind turbine due to energy extraction and its impact on subsequent wind turbines. In this embodiment, it can be used to quantify the impact of the low-speed turbulence region formed downstream after the wind turbine starts operating on other wind turbines. It can be used to assess and calculate the annual power generation of each wind turbine.

[0038] In this embodiment of the invention, the target wake model is determined by the turbine parameters of each wind turbine, the altitude of each wind turbine, the humid air density at the location of each wind turbine, the layout position of each wind turbine, and the availability rate of each wind turbine. The turbine parameters may include parameters such as the hub height and blade radius; the altitude can be the altitude corresponding to the geographical location of each wind turbine; and the availability rate is used to characterize whether each wind turbine has experienced a malfunction.

[0039] In the specific construction of the target wake model, such as Figure 2 As shown, the target wake model can be constructed as follows: Based on the computationally efficient classical Jensen model, this model comprehensively considers the coupling effects of altitude and mountainous terrain, as well as dynamic air density, and systematically improves the wake expansion, deflection, and superposition. The Jensen model is a classic, computationally efficient analytical wake model based on momentum conservation and the assumption of a linearly expanding wake profile. Addressing the problem of local wind speed acceleration caused by terrain in complex high-altitude mountainous areas, the model improves the free-inflow wind speed based on the traditional Jensen model. To quantify the impact of topography on inflow wind speed, the following adjustments are made: ; in, The slope sensitivity coefficient is set to 0.15~0.25. The slope angle, This is the difference between the wheel hub height and the reference point height. To account for the influence of topography on the height scale, half the mountain height is taken. The wind speed is the free-flow wind speed after terrain correction.

[0040] The long-term low temperature and low pressure in high-altitude areas result in thin air and a significant difference in air density compared to sea level. To make the model practical under high-altitude conditions, the assumption of fixed air density in traditional models is abandoned. Instead, the density of moist air is dynamically calculated based on parameters such as temperature, air pressure, and humidity. The calculation formula is as follows: ; in, Atmospheric pressure. For water vapor partial pressure, For air temperature, The gas constant of water vapor. , The gas constant for dry air. , This represents the vertical temperature lapse rate. Altitude The molar mass of dry air is 0.02897 kg / mol. The acceleration due to gravity is 9.80665 m / s². 2 , The relative humidity is 58%. The universal gas constant is 8.314 J / (mol·K). The saturated vapor pressure at the current temperature. The standard atmospheric pressure at sea level is 101325 Pa. Standard temperature .

[0041] In the classic Jensen model, the "top-hat" wake section assumption is adopted, which assumes that the velocity deficit inside the wake is uniform and expands linearly with distance. The velocity deficit formula is as follows: ;

[0042] This assumption limits the model's wake predictions to flat terrain and restricts its computational accuracy. In complex terrain, wind shear or topographical undulations can cause the wake centerline of wind turbines to shift, meaning downstream turbines may only intersect a portion of the upstream turbine's wake. To compensate for this deficiency, an overlap area factor is introduced. The velocity deficit of the wake section is described using the Gaussian distribution from turbulent diffusion theory combined with the Jensen model. The velocity deficit formula is corrected after considering the influence of external environmental factors, as follows: ; in, This represents the wind speed loss at the downstream wind turbine. For free-flow wind speed, The wake attenuation coefficient is... For the upstream Typhoon generator and downstream Overlap area factor of typhoon generators Let be the thrust coefficient of the j-th wind turbine in the upstream wind turbines. The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine Downwind distance between typhoon generators Let be the rotor diameter of the j-th wind turbine in the upstream wind turbine series. The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine The relative distance between the typhoon generators on the y-axis The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine The relative distance between the typhoon generators on the z-axis The first of the upstream wind turbines The wake of the typhoon is the first in the downstream wind turbine. The horizontal radius of the typhoon's spread. The first of the upstream wind turbines The wake of the typhoon is the first in the downstream wind turbine. The radius of diffusion in the vertical direction of the typhoon's location.

[0043] The upstream wind turbine The wake of the typhoon is the first in the downstream wind turbine. The horizontal diffusion radius of the typhoon generator's location This can be expressed by the following calculation formula: ; in, The horizontal diffusion coefficient is... The length of the surface roughness. For Richardson's number;

[0044] The upstream wind turbine The wake of the typhoon is the first in the downstream wind turbine. The vertical diffusion radius of the typhoon generator's location This can be expressed by the following calculation formula: ; in, The vertical diffusion coefficient is... This refers to altitude.

[0045] The upstream first Typhoon generator and downstream Overlap area factor of typhoon generators This can be expressed by the following formula: ; ; ; ; ; ; in, The first of the upstream wind turbines The rotor swept area of ​​the typhoon turbine ranks first among downstream wind turbines. The overlapping area of ​​the typhoon's wake cross-section perpendicular to the incoming flow direction. The first of the downstream wind turbines The location of the typhoon generator represents the angle of deflection of the equivalent inflow wind direction in the vertical plane relative to the horizontal plane. For the radius of the wind turbine, For the upstream Typhoon generators and downstream Spatial distance between typhoon generators. The first of the downstream wind turbines The typhoon turbine rotor sweep circle and the upstream turbine middle section The length of the chord formed by the intersection of the equivalent wake cross-section circles of a typhoon generator in a plane perpendicular to the direction of incoming flow. The distance from the center of the wake to the chord of the intersection of the two circles is denoted as . The first of the downstream wind turbines The vertical displacement of the typhoon fan. The first of the upstream wind turbines The vertical displacement of the typhoon fan. The first of the upstream wind turbines The displacement of the typhoon fan along the y-axis. The first of the downstream wind turbines The displacement of the typhoon fan along the y-axis; The first of the upstream wind turbines The typhoon generator is the first unit in the downstream section. The equivalent wake radius of a typhoon.

[0046] The aforementioned modifications refine the wake model's propagation path and influence range at the spatial geometry level, thus more accurately characterizing the physical effects of a single-unit wake. The ultimate goal of the wake model is to expand from single-unit effects to group effects at the wind farm scale. Since the inflow velocity of a single wind turbine is also affected by the wake effect of upstream turbines, identifying the upstream turbines that influence a particular turbine is crucial. For ease of and accuracy, this study uses the following conditions as criteria: distance condition: the wake influence is limited to within 10 times the diameter of the upstream turbine; if it exceeds this range, the wake dissipation is considered significant, and its influence can be ignored; relative orientation condition: if the target turbine is located within the wake diffusion range of another turbine, that turbine may influence the target turbine.

[0047] Therefore, the downstream wind turbine The angle between the vertical and horizontal directions at the location of the typhoon generator This can be expressed by the following calculation formula: ; in, The first of the downstream wind turbines The horizontal wind direction angle of the terrain where the typhoon generator is located. The first of the downstream wind turbines The slope angle of the terrain where the typhoon generator is located. The first of the downstream wind turbines The terrain where the typhoon generator is located causes a change in wind direction. The first of the upstream wind turbines The wake of the typhoon caused the downstream wind turbine to... The direction of the wind deflection at the location of the typhoon generator The free-flow wind direction, after being corrected by topography and wake, affects the downstream first... The overall wind direction angle at the location of the typhoon generator. For free-flow wind direction angle, = The deflection attenuation length, The angle between the free-flow wind direction and the ridgeline. The first of the downstream wind turbines The altitude of the typhoon machine The first of the downstream wind turbines The typhoon generator is located in the spatial coordinates of the lateral direction of the wind. The deflection sensitivity coefficient is positive when clockwise and negative when counterclockwise.

[0048] After successfully calculating wind direction changes, the impact of multiple upstream wind turbines on the wind speed of downstream turbines was synthesized. Using the root mean square method widely employed in the Jensen model, the sum of squares and square roots of the effective velocity deficits of all upstream wakes were taken to obtain the total effective velocity deficit of the downstream units, i.e.: ; in, The first of the downstream wind turbines All upstream wind turbines of the typhoon A set of.

[0049] The final target wake model is: ; ; ; in, The first of the downstream wind turbines The actual inflow velocity of the typhoon fan For downstream The free-inflow velocity of the typhoon fan. Topographical influencing factors For the downstream wind turbine A collection of upstream wind turbines affected by typhoons. The first of the downstream wind turbines The power generation of typhoon generators, The first of the downstream wind turbines The rotor sweep area of ​​a typhoon fan. The first of the downstream wind turbines The power factor of a typhoon turbine. The density of moist air. The first of the downstream wind turbines The availability rate of typhoon turbines.

[0050] In one possible manner, the availability of the fan is determined by the following method:

[0051] Determine the composite failure factors of the wind turbine;

[0052] The synthetic fault impact factor is used as the quantitative benchmark for wind turbine fault status. The target random number is randomly sampled using the Monte Carlo simulation method, and the comparison result between the target random number and the synthetic fault impact factor is determined.

[0053] The status of the wind turbine is determined based on the comparison results. When the wind turbine is in normal operation, the availability rate is the first threshold; otherwise, the availability rate is the second threshold.

[0054] It should be understood that the topography and climate of high-altitude areas not only affect inflow wind speed but also failure rate and maintenance accessibility. To quantify these effects, this invention defines a synthetic failure impact factor. ,Right now This is used to correct the base failure rate B, i.e., BaseFailure. This synthetic failure impact factor... Maintenance accessibility factor was taken into account. and meteorological influencing factors ,in, for , For WeatherWindowFactor, the calculation formula is as follows: ; in, For maintenance accessibility factors, The first of the downstream wind turbines The slope of the location where the typhoon generator is located. The slope attenuation coefficient for maintainability is set at 0.01 to 0.02, representing the percentage decrease in maintainability due to a 1° increase in slope. The meteorological impact factor is assigned based on the percentage of maintainable hours per year. Based on these influencing elements, the expression for the composite failure impact factor is: ; in, The first of the downstream wind turbines Composite failure factors of typhoon generators The baseline failure rate used for correction is 2.2. The accessibility sensitivity coefficient for maintenance is set to 0.4. The meteorological maintainability sensitivity coefficient is set to 0.6. Meteorological influencing factors, The first of the downstream wind turbines The slope of the location where the typhoon generator is located.

[0055] Then, the synthetic fault impact factor can be used as a quantitative benchmark for the wind turbine fault state. A target random number is randomly sampled using the Monte Carlo simulation method, and the comparison result between the target random number and the synthetic fault impact factor is determined. Based on the comparison result, the wind turbine's status is judged. When the wind turbine is in normal operating condition, the wind turbine availability rate is... The first threshold is set; otherwise, the wind turbine availability rate... The second threshold is defined as follows: the first threshold can be 1, and the second threshold can be 0. This embodiment of the invention does not impose specific limitations on this.

[0056] For example, after obtaining the annual total power generation model of the target wind farm, the optimization objective can be to maximize the annual total power generation of the target wind farm. The PSO (Particle Swarm Optimization) algorithm can be used to search for the optimal placement of wind turbines, ultimately obtaining the optimal placement location. This improves the evaluation of the annual total power generation of the wind farm. Specifically, when processing the annual total power generation model using the PSO algorithm, existing PSO algorithms can be employed. During the processing, the placement location of each wind turbine is treated as a particle, and iterative updates are performed continuously to obtain the optimal placement location of each wind turbine in the target wind farm. The annual total power generation of the target wind farm can then be calculated and evaluated based on the optimal placement location of each wind turbine.

[0057] By incorporating topographic influence factors and dynamic moist air density calculations into the target wake model, the above-mentioned technical solutions effectively correct the actual impact of complex terrain and thin air in high-altitude areas on wind speed and turbine output. Furthermore, dynamic moist air density calculations based on real-time air pressure, temperature, and humidity are introduced to correct the influence of low-density air at high altitudes on turbine output assessment. Refined wake calculations using Gaussian distribution and RSS (Root Sum of Squares) overlay significantly improve the model's AEP (Advanced Performance Estimation) accuracy in complex mountainous environments at high altitudes. This allows for more conservative and realistic predictions of annual total power generation, thereby improving the reliability of investment decisions for high-altitude wind power projects. By combining the basic failure rate of wind turbines with the unique operational and maintenance constraints of high-altitude areas, and by establishing maintenance accessibility factors and meteorological influence factors to correct for actual turbine failure rates and availability, and by quantitatively incorporating operational reliability into the AEP assessment model through Monte Carlo simulation, the AEP results obtained from the assessment more accurately reflect the actual benefits of wind farms and have stronger practical guiding significance. By incorporating availability into the target wake model and extending it to clusters that consider inter-field wakes, a comprehensive and accurate assessment of the power generation efficiency and operational stability of wind farms in complex high-altitude environments is achieved.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography, characterized in that, include: A model for the total annual power generation of the target wind farm is determined, wherein the total annual power generation model is obtained by adding the target wake models of each wind turbine, and the target wake models are used to calculate the annual power generation of the wind turbines. With the goal of maximizing the total annual power generation, the PSO algorithm is used to search for the optimal layout of each wind turbine in the annual total power generation model to obtain the optimal layout of each wind turbine in the target wind farm. The target wake model of the wind turbine is determined by the wind turbine parameters, the wind turbine altitude, the humid air density at the location of the wind turbine, the layout of the wind turbine, and the wind turbine availability rate.

2. The wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to claim 1, characterized in that, The availability rate of the fan is determined by the following method: Determine the composite failure factors of the wind turbine; The synthetic fault impact factor is used as the quantitative benchmark for wind turbine fault status. The target random number is randomly sampled using the Monte Carlo simulation method, and the comparison result between the target random number and the synthetic fault impact factor is determined. The status of the wind turbine is determined based on the comparison results. When the wind turbine is in normal operation, the availability rate is the first threshold; otherwise, the availability rate is the second threshold.

3. The wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to claim 1 or 2, characterized in that, The target wake model is expressed by the following calculation formula: ； ； ； in, The first of the downstream wind turbines The actual inflow velocity of the typhoon fan For downstream The free-inflow velocity of the typhoon fan. Topographical influencing factors For the downstream wind turbine A collection of upstream wind turbines affected by typhoons. For the upstream Typhoon generator and downstream Overlap area factor of typhoon generators Let be the thrust coefficient of the j-th wind turbine in the upstream wind turbines. The wake attenuation coefficient is... The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine Downwind distance between typhoon generators The first of the upstream wind turbines The rotor diameter of a typhoon generator The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine The relative distance between the typhoon generators on the y-axis The wind turbine is located in the upstream section of the wind turbine layout. The first of the typhoon turbine and downstream wind turbine The relative distance between the typhoon generators on the z-axis The first of the upstream wind turbines The wake of the typhoon is the first in the downstream wind turbine. The horizontal radius of the typhoon's spread. The first of the upstream wind turbines The wake of the typhoon is the first in the downstream wind turbine. The radius of diffusion in the vertical direction of the typhoon generator's location. This is the slope sensitivity coefficient. The slope angle, The terrain affects the height scale. The first of the downstream wind turbines The power generation of typhoon generators, The first of the downstream wind turbines The rotor sweep area of ​​a typhoon fan. The first of the downstream wind turbines The power factor of a typhoon turbine. The density of moist air. The first of the downstream wind turbines The availability rate of typhoon turbines. This is the difference between the wheel hub height and the reference point height.

4. The wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to claim 3, characterized in that, The density of moist air This can be expressed by the following calculation formula: ； in, Atmospheric pressure. For water vapor partial pressure, For air temperature, The gas constant of water vapor. The gas constant for dry air. This represents the vertical temperature lapse rate. Altitude The molar mass of dry air, It is the acceleration due to gravity. Relative humidity, This is the universal gas constant. The saturated vapor pressure at the current temperature. Standard atmospheric pressure at sea level. This is the standard temperature.

5. The wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to claim 3, characterized in that, The upstream wind turbine The wake of the typhoon is the first in the downstream wind turbine. The horizontal diffusion radius of the typhoon generator's location This can be expressed by the following calculation formula: ； in, The horizontal diffusion coefficient is... The length of the surface roughness. For Richardson's number; The upstream wind turbine The wake of the typhoon is the first in the downstream wind turbine. The vertical diffusion radius of the typhoon generator's location This can be expressed by the following calculation formula: ； in, The vertical diffusion coefficient is... This refers to altitude.

6. The wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to claim 3, characterized in that, The upstream first Typhoon generator and downstream Overlap area factor of typhoon generators This can be expressed by the following calculation formula: ； ； in, The first of the upstream wind turbines The rotor swept area of ​​the typhoon turbine ranks first among downstream wind turbines. The overlapping area of ​​the typhoon's wake cross-section perpendicular to the incoming flow direction. The first of the downstream wind turbines The location of the typhoon generator represents the angle of deflection of the equivalent inflow wind direction in the vertical plane relative to the horizontal plane. For the radius of the wind turbine, For the upstream Typhoon generators and downstream Spatial distance between typhoon generators. The first of the downstream wind turbines The typhoon turbine rotor sweep circle and the upstream wind turbine in the middle The length of the chord formed by the intersection of the equivalent wake cross-section circles of a typhoon generator in a plane perpendicular to the direction of incoming flow. The distance from the center of the wake to the chord of the intersection of the two circles is denoted as . The first of the downstream wind turbines The vertical displacement of the typhoon fan. The first of the upstream wind turbines The vertical displacement of the typhoon fan. The first of the upstream wind turbines The displacement of the typhoon fan along the y-axis. The first of the downstream wind turbines The displacement of the typhoon fan along the y-axis; The first of the upstream wind turbines The typhoon generator is the first unit in the downstream section. The equivalent wake radius of a typhoon.

7. The wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to claim 6, characterized in that, The downstream wind turbine The angle between the vertical and horizontal directions at the location of the typhoon generator This can be expressed by the following calculation formula: ； in, The first of the downstream wind turbines The horizontal wind direction angle of the terrain where the typhoon generator is located. The first of the downstream wind turbines The slope angle of the terrain where the typhoon generator is located. The first of the downstream wind turbines The terrain where the typhoon generator is located causes a change in wind direction. The first of the upstream wind turbines The wake of the typhoon caused the downstream wind turbine to... The direction of the wind deflection at the location of the typhoon generator The free-flow wind direction, after being corrected by topography and wake, affects the downstream first... The overall wind direction angle at the location of the typhoon generator. The free-flow wind direction angle represents the large-scale wind direction before entering the wind farm. The deflection attenuation length, The angle between the free-flow wind direction and the ridgeline. The first of the downstream wind turbines The altitude of the typhoon machine The first of the downstream wind turbines The typhoon generator is located in the spatial coordinates of the lateral direction of the wind. This is the deflection sensitivity coefficient.

8. The wind farm micro-site selection method based on the coupling of micro-meteorology and micro-topography according to claim 1 or 2, characterized in that, The synthetic fault impact factor is calculated using the following expression: ； in, The first of the downstream wind turbines Composite failure factors of typhoon generators The base failure rate used for correction. For maintenance accessibility factors, For the accessibility sensitivity coefficient of maintenance, The sensitivity coefficient for weather maintainability. Meteorological influencing factors, To maintain the accessibility slope attenuation coefficient, The first of the downstream wind turbines The slope of the location where the typhoon generator is located.

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