CN106250656A - The complicated landform wind field design platform of the big data of a kind of combination and method - Google Patents
The complicated landform wind field design platform of the big data of a kind of combination and method Download PDFInfo
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Abstract
The invention discloses the complicated landform wind field design platform of the big data of a kind of combination, including analog platform, big data workstation and optimization layout platform；Described analog platform includes being sequentially connected mesoscale numerical model module, NO emissions reduction wind-resources model module, the wind field flow model module considering landform and the wake model module connect；Described data workstation includes that the big data platform of wind energy turbine set and data analysis model module, described optimization layout platform include that wind energy turbine set generated energy computation model module and wind energy turbine set optimize layout calculation model module；The present invention corrects generated energy model based on big data workstation, the method for operation impacting Fan Equipment and geographic factor is embodied in during generated energy calculates to reduce blower fan fatigue load rate, thus reduces maintenance cost, reasonably optimizing wind turbine layout.
Description
Technical field
The invention belongs to technical field of wind power, be specifically related to the complicated landform wind field design platform of the big data of a kind of combination
And method.
Background technology
Wind energy turbine set in early days build the place that wind energy resources is abundant, landform is relatively flat in more, but is as wind energy turbine set scale
Increasing, quantity gets more and more, and wind energy turbine set starts to build in complex topographic area territory.China's complexity wind energy turbine set optimization design at present
Key technology (include macroscopic view addressing, survey wind, microcosmic structure etc.) the weakest, carry out wind field design according to external experience
With the needs that control can not adapt to China's extreme terrain, wind regime and national conditions, from the point of view of built wind-power electricity generation project, wind-powered electricity generation
The design control aspect of field still suffers from bigger optimization space, the wind energy turbine set of especially complicated region, is mainly manifested in macroscopic view choosing
Location scheme is coarse, anemometer tower layout shortage scientific basis causes the basis survey wind data imperfections such as wind-resources, it is high to survey eolian, tail
The aspects such as flow model precision is low, the optimization not of blower fan position.
Improve it is critical only that of these problems and promote the science designing the enforcement of each step.In recent years, along with computer meter
Quickly improving and the further investigation of logarithm value calculating of calculation ability, computational fluid dynamics (CFD) obtains significant progress,
Based on a series of bases mechanism model that it provides, wind field flow field accurately can be simulated.Further, since fan operation mistake
Cheng Zhonghui is disturbed by multiple practical factor, and the wind turbine power generation amount that therefore mechanism calculates is generally and physical presence difference.Based on
The model alignment technique of big data is the focus of Recent study, but is not also used in the design optimization of wind field.Wind field data
Comprising the information affecting wind turbine power generation amount, extracting useful information from powerful data volume, to correct generated energy computation model permissible
Strengthen the predictive ability of model, thus promote microcosmic structure precision.
Summary of the invention
Present invention solves the problem in that complicated landform wind field design platform and the method that the big data of a kind of combination are provided,
The scientific rationality of complicated landform wind field design is promoted with data analysis by the way of Analysis on Mechanism based on model is combined,
Promote wind energy turbine set economic benefit, reduce maintenance cost.
The present invention is to be achieved through the following technical solutions:
The complicated landform wind field design platform of the big data of a kind of combination, including data workstation, analog platform and optimization
Layout platform；
Described analog platform includes being sequentially connected mesoscale numerical model module, the NO emissions reduction wind-resources pattern die connect
Block, the wind field flow model module considering landform and wake model module；Described mesoscale numerical model module is to NO emissions reduction
Wind-resources model module output wind-resources distribution situation and wind-resources reserves；NO emissions reduction wind-resources model module is to considering landform
Wind data is surveyed in the output of wind field flow model module；Wake model module receives initial wind turbine layout and considers the wind field flowing of landform
The wind field flow distribution of model module output；
Described data workstation includes the big data platform of wind energy turbine set and data analysis model module, Data Analysis Model module
Receive independent variable and dependent variable that the big data platform of wind energy turbine set sends, to optimizing the theoretical generated energy of layout platform output and blower fan cloth
Office's modifying factor；
Described optimization layout platform includes that wind energy turbine set generated energy computation model module and wind energy turbine set optimize layout calculation mould
Pattern block, wind energy turbine set generated energy computation model module receives the output of wake model module, and receives blower fan layout modifying factor,
The generated energy that aweather output of electric Field Optimization layout calculation model module is revised；Wind energy turbine set optimizes layout calculation model module output wind
Electric Field Optimization layout result.
Also wind field flow model module and wake model module to described consideration landform carries out depression of order；
Wake model module after described wind energy turbine set generated energy computation model and depression of order and the wind field flowing mould of consideration landform
Pattern block matches, and it is excellent with wind energy turbine set generated energy computation model module and heredity that described wind energy turbine set optimizes layout calculation model module
Change algorithm to match.
The input independent variable of described Data Analysis Model module is landform, actual wind turbine layout at wind regime, blower fan at blower fan
With theoretical generated energy etc., the dependent variable of model is actual power generation, fan operation state and blower fan layout modifying factor, blower fan cloth
Office's modifying factor is between 0～1.
A kind of complicated landform wind field design method of the big data of combination, including following operation:
1) using the meteorological data including atmospheric pressure, height above sea level, temperature, wind direction, wind speed as input, in utilization
Scale parameter value model module carries out high-resolution simulation and calculates；Obtain wind-resources distribution situation and the wind money in complex topographic area territory
Source reserves；
2) NO emissions reduction wind-resources model module obtains the result mesoscale data given by mesoscale numerical model module 6,
And using it as the boundary condition of NO emissions reduction hydrodynamic analogy, alternative wind field is carried out NO emissions reduction simulation, it is thus achieved that wind-resources
Distribution, coupling system access, road transport, environmental conservation are built field condition at interior, are set up System of Comprehensive Evaluation, instruct wind
Macroscopical addressing of field；
3) the wind-resources distribution be given based on NO emissions reduction wind-resources model module, divides representative region, determines anemometer tower cloth
Put scheme, the parameter including anemometer tower quantity, installation site, instrument for wind measurement setting height(from bottom), thus obtain survey wind data；
4) for complicated terrain generation high-quality body fitted grids, analyze software based on CFD and set up the wind field stream of consideration landform
Movable model module, calculates for boundary condition surveying wind data, and application simultaneously surveys wind data to turbulence model parameter used
Demarcate；Wherein consider the wind field flow model module of landform describe the quality of wind flow in design section, momentum, energy and
Air condition, the wind regime in output design section, wind speed, wind direction, the distributed in three dimensions of turbulivity；
5) to consider wind field flow distribution 14 and the initial wind turbine layout 15 that the wind field flow model module 8 of landform calculates
The initial condition calculated as wake model module 9, analyzes software based on CFD and sets up different typical case's landform lower tail flow model module
9；Wherein wake model describes air flow behavior change after barrier, wind regime, wind in certain limit after output barrier
Speed, wind direction, the distributed in three dimensions of turbulivity；
6) set up the big data platform of wind energy turbine set, application-dependent data analyze method obtain at blower fan landform at wind regime, blower fan,
Actual wind turbine layout dependency relation between interior factor and blower fan unit performance, obtains Data Analysis Model, determines blower fan
Unit performance is by the quantitative effect size of the factor such as landform, actual wind turbine layout at wind regime, blower fan at blower fan；Described blower fan machine
Group performance includes actual power generation and fan operation state；
7) according to wake model module (9) and the output data of wind field flow model module (8) considering landform, it is thus achieved that wind
The wind regime of machine position, and the generated energy of the input calculating blower fan as power of fan curve；Wind energy turbine set generated energy calculates
Model is as follows:
Wind energy turbine set generated energy computation model is as follows:
Wherein, viRepresent input vector, including wind regime, landform and wind turbine layout；P () represents wind turbine power generation amount；I represents
Blower fan is numbered；N represents maximum blower fan number；W represents wind energy turbine set general power；
Theoretical generated energy (21) is carried out by blower fan layout modifying factor (22) exported based on Data Analysis Model module (5)
Revise；
8) the relevant optimized algorithm of application sets up wind energy turbine set optimization layout calculation model, and using revised generated energy as wind
The input of electric Field Optimization layout calculation model, optimizes placement scheme through optimizing the wind energy turbine set obtained under complicated landform；Wherein, institute
Stating optimized algorithm is genetic algorithm, ant group algorithm or simulated annealing.
With blower fan layout modifying factor as correction conditions, its mathematical expression formula is
Wherein, viRepresent input vector, including wind regime, landform and wind turbine layout；E () represents blower fan layout modifying factor
Son；P () represents wind turbine power generation amount；I represents blower fan numbering；N represents maximum blower fan number；W represents wind energy turbine set general power.
Compared with prior art, the present invention has a following useful technique effect:
1) macroscopic view addressing precision is improved.At present, at home macroscopic view addressing Main Basis locality meteorological department the conception of history
Survey data and country wind energy resources scattergram, precision high shortcoming low, uncertain is existed for complicated landform.Originally set
During meter method is passed through, minute yardstick simulation be obtained in that high-precision wind-resources distributed data, advantageously in instructing the grand of wind field
See addressing.
2) improve the representativeness of survey wind data, reduce eolian of survey.In complex topographic area territory, wind regime is with topography variation
Relatively big, the data that the most single anemometer tower is measured can only reflect the wind regime of limited region.To obtain whole complicated region
Wind-resources distribution situation, the anemometer tower quantity of needs may be greatly increased so that the front current cost of Wind Power Generation increases.The design
Method divides pathogenic wind by Analysis on Mechanism means and waits similar area, scientifically determine anemometer tower quantity and position, it is possible to increase
Survey the representativeness of wind data, reduce and survey eolian.
3) wind-resources distribution and the degree of accuracy of wake flow calculating are promoted.The commercialization software for calculation that microcosmic structure is main at present is equal
From abroad, wind regime model, turbulence model and the wake model etc. used all are developed for level terrain.It is applied to multiple
During the wind field design of miscellaneous lineament, there is limitation.The design method sets up accurate wind field fluid by CFD software
Kinetic model and wake model, it is possible to accurately obtain wind-resources distribution and the wake flow size of wind field, for accurately calculating generated energy
And the configuration of reasonably optimizing blower fan provides the foundation.
4) reasonably optimizing wind turbine layout, reduces maintenance cost.Owing to can be done by many factors during fan operation
Disturbing (such as turbulent flow), therefore the wind turbine power generation amount of Theoretical Calculation is generally and physical presence difference.Wind field packet is sent out containing affecting blower fan
All information of electricity, the design method corrects generated energy model based on wind-powered electricity generation service data, will impact Fan Equipment
The method of operation and geographic factor be embodied in during generated energy calculates to reduce blower fan fatigue load rate, thus reduce maintenance cost,
Reasonably optimizing wind turbine layout.
Accompanying drawing explanation
Fig. 1 is the complicated landform wind field design platform structure schematic diagram of the present invention；
Wherein, 1 is data workstation；2 is analog platform；3 for optimizing layout platform；4 is the big data platform of wind energy turbine set；5
For Data Analysis Model module；6 is mesoscale numerical model module；7 is NO emissions reduction wind-resources model module；8 for considering landform
Wind field flow model module；9 is wake model module；10 is generated energy computation model module；11 for optimizing layout calculation mould
Pattern block；12 is mesoscale data；13 are distributed for wind-resources；14 is wind field flow distribution；15 is initial wind turbine layout；16 is wind
Wind regime at machine；17 is landform at blower fan；18 is actual wind turbine layout；19 is actual power generation；20 is fan operation state；21 are
Theoretical generated energy；22 is that blower fan layout modifying factor 23 optimizes placement scheme for wind energy turbine set；24 is anemometer tower arrangement；25 are
Survey wind data；26 is revised generated energy.
Detailed description of the invention
Below in conjunction with specific embodiment, the present invention is described in further detail, described in be explanation of the invention and
It not to limit.
The complicated landform wind field design platform of the big data of a kind of combination, including data workstation 1, analog platform 2 and excellent
Change layout platform 3；
Described analog platform 2 includes being sequentially connected mesoscale numerical model module 6, the NO emissions reduction wind-resources pattern die connect
Block 7, the wind field flow model module 8 considering landform and wake model module 9；Described mesoscale numerical model module 6 is to fall
Yardstick wind-resources model module 7 exports wind-resources distribution situation and wind-resources reserves；NO emissions reduction wind-resources model module 7 is to consideration
Wind data is surveyed in wind field flow model module 8 output of landform；Wake model module 9 receives initial wind turbine layout and considers landform
The wind field flow distribution of wind field flow model module 8 output；
Described data workstation 1 includes the big data platform of wind energy turbine set 4 and data analysis model module 5, Data Analysis Model
Module 5 receives independent variable and the dependent variable that wind energy turbine set big data platform 4 sends, and exports actual power generation to optimizing layout platform 3
With blower fan layout modifying factor；
Described optimization layout platform 3 includes that wind energy turbine set generated energy computation model module 10 and wind energy turbine set optimize layout calculation
Model module 11, wind energy turbine set generated energy computation model module 10 receives the output of wake model module 9, and receives blower fan layout and repair
Positive divisor, the generated energy that aweather electric Field Optimization layout calculation model module 11 output is revised；Wind energy turbine set optimizes layout calculation model
Module 11 exports wind energy turbine set and optimizes layout result.
According to the preferred embodiment of the invention, it is used for promoting setting of complicated landform leeward electric field both macro and micro addressing precision
Meter platform structure composition is as it is shown in figure 1, mainly include data workstation 1, analog platform 2 and optimize layout platform 3.Described data
The big data platform of wind energy turbine set 4 runed equipped with certain large enterprise in work station and data analysis model module 5, for running
The data of wind energy turbine set are analyzed, and export blower fan layout modifying factor.
The independent variable of wherein said Data Analysis Model module 5 is landform 17, actual blower fan at wind regime 16, blower fan at blower fan
Layout 18 and theoretical generated energy 21 etc., the dependent variable of model is that actual power generation 19, fan operation state 20 and blower fan layout are repaiied
Positive divisor 22, blower fan layout modifying factor is between 0～1.
Described analog platform 2 comprises mesoscale numerical model module 6, NO emissions reduction wind-resources based on Fluent software development
Model module 7, the wind field flow model module 8 considering landform and wake model module 9.
Described optimization layout platform 3 comprises wind energy turbine set generated energy computation model 10 and wind energy turbine set optimizes layout calculation model
11。
Wind field flow model module 8 and wake model module 9 owing to considering landform are complex, therefore drop it
Rank, optimize precision and the requirement of real-time to meet simultaneously.Wake flow after described wind energy turbine set generated energy computation model and depression of order
The wind field flow model module 8 of model module 9 and consideration landform matches, and described wind energy turbine set optimizes layout calculation model module 11
Match with wind energy turbine set generated energy computation model module 10 and genetic Optimization Algorithm.
Method for designing based on above-mentioned design platform comprises the steps:
Step 1, using the meteorological data including atmospheric pressure, height above sea level, temperature, wind direction, wind speed as input, profit
Carry out high-resolution simulation by mesoscale numerical model module 6 to calculate；Obtain the wind-resources distribution situation in complex topographic area territory
And wind-resources reserves；
Step 2, NO emissions reduction wind-resources model module 7 obtains the result mesoscale given by mesoscale numerical model module 6
Data 12, and using it as the boundary condition of NO emissions reduction hydrodynamic analogy, alternative wind field is carried out NO emissions reduction simulation, it is thus achieved that
Wind-resources distribution 13；Coupling system access, road transport, environmental conservation build field condition at interior, set up comprehensive evaluation index body
System, instructs macroscopical addressing of wind field；
Concrete, using Mesoscale Numerical Simulation result mesoscale data 12 as the border of NO emissions reduction hydrodynamic analogy
Condition, carries out NO emissions reduction simulation to alternative wind field.
Step 3, the wind-resources distribution 13 obtained based on NO emissions reduction hydrodynamic analogy, divide representative region, determine survey
Wind tower arrangement 24, the parameter such as including anemometer tower (or windfinding radar) quantity, installation site, instrument for wind measurement setting height(from bottom), and
Obtain and survey wind data 25.
Step 4, for complicated terrain generation high-quality body fitted grids, sets up the wind field stream considering landform based on CFD software
Movable model module 8, calculates for boundary condition surveying wind data 25, and application simultaneously surveys wind data 25 to turbulence model used
Parameter is demarcated；Wherein consider the wind field flow model module 8 of landform describe the quality of wind flow in design section, momentum,
Energy and air condition, the wind regime in output design section, wind speed, wind direction, the distributed in three dimensions of turbulivity；
Step 5, to consider wind field flow distribution 14 that the wind field flow model module 8 of landform calculates and initial blower fan cloth
Put 15 initial condition calculated as wake model module 9, analyze software based on CFD and set up different typical case's landform lower tail flow model
Module 9；Wherein wake model describes air flow behavior change after barrier, certain limit endogenous wind after output barrier
Condition, wind speed, wind direction, the distributed in three dimensions of turbulivity；
Step 6, sets up the big data platform of wind energy turbine set 4, and application-dependent data is analyzed method and obtained wind regime 16, blower fan at blower fan
Place the factor such as landform 17, actual wind turbine layout 18 and blower fan unit performance include actual power generation 19, fan operation state 20 it
Between the most described Data Analysis Model of dependency relation 5, determine that blower fan unit performance includes actual power generation 19, fan operation state
20 by the quantitative effect size of the factor such as landform 17, actual wind turbine layout 18 at wind regime at blower fan 16, blower fan.
Step 7, sets up different typical case's landform lower tail flow model module 9 based on CFD, to consider the wind field flow model of landform
Wind field flow distribution 14 that module 8 calculates and the initial condition that initial wind turbine layout 15 calculates as wake model 9.
Wind field flow model 8 based on wake model module 9 and consideration landform sets up wind energy turbine set generated energy computation model 10
For the calculating of wind energy turbine set theory generated energy, and theory is sent out by blower fan layout modifying factor 22 based on Data Analysis Model output
Electricity 21 is modified.
Wind energy turbine set generated energy computation model is as follows:
Wherein, viRepresent input vector, including wind regime, landform and wind turbine layout；P () represents wind turbine power generation amount；I represents
Blower fan is numbered；N represents maximum blower fan number；W represents wind energy turbine set general power；
Step 8, applies relevant optimized algorithm to set up wind energy turbine set and optimizes layout calculation model 11, and by revised generated energy
26 optimize the input of layout calculation model as wind energy turbine set, optimize placement scheme through optimizing the wind energy turbine set obtained under complicated landform
23。
With blower fan layout modifying factor 22 as correction conditions, its mathematical expression formula is:
Wherein, viRepresent input vector, including wind regime, landform and wind turbine layout；E () represents blower fan layout modifying factor
Son；P () represents wind turbine power generation amount；I represents blower fan numbering；N represents maximum blower fan number；W represents wind energy turbine set general power.
The method for designing realized based on the design platform is with in place of the main difference of conventional design method:
1) macroscopic view addressing and survey wind are more scientific and reasonable.Due in have employed, the numerical computations of minute yardstick, to wind-resources
Assessment is more accurate, and the division to similar wind regime region is the most reasonable.
2) computational accuracy of complicated landform leeward resource distribution and wake flow improves.Owing to applying CFD software, it is possible to from machine
In reason, the flowing to wind is analyzed, and the factor such as landform, roughness that comprehensively considers is on wind flow and the impact of wake flow.
3) layout optimization scheme is more reasonable.It is analyzed by service data long to multiple Wind turbines, obtains
The factor such as landform, wind regime information that wind turbine power generation amount is affected, and with the form correction generated energy of modifying factor (such as at certain
Planting under landform, wind regime, blower fan can be in turbulent area for a long time, thus causes operation conditions poor, may when carrying out Theoretical Calculation
This impact can be ignored.By the correction of modifying factor, the wind turbine power generation amount being under similar landform and wind regime is made to reduce, thus
Reduce wind turbine layout probability under such landform and wind regime), obtain generated energy value of calculation more accurately, so that
Final layout optimization scheme is more reasonable.
The technology of the present invention is applied to certain complicated landform wind field design, than the same type wind-powered electricity generation not applying the technology of the present invention
Field generated energy improves more than 5%, and operation and maintenance cost reduces by more than 10%.
Example given above is to realize the present invention preferably example, the invention is not restricted to above-described embodiment.This area
Technical staff made according to the technical characteristic of technical solution of the present invention any nonessential interpolation, replacement, belong to this
The protection domain of invention.
Claims (5)
1. the complicated landform wind field design platform combining big data, it is characterised in that include data workstation (1), mould
Intend platform (2) and optimize layout platform (3)；
Described analog platform (2) includes being sequentially connected mesoscale numerical model module (6), the NO emissions reduction wind-resources pattern die connect
Block (7), wind field flow model module (8) considering landform and wake model module (9)；Described mesoscale numerical model module
(6) to NO emissions reduction wind-resources model module (7) output wind-resources distribution situation and wind-resources reserves；NO emissions reduction wind-resources pattern die
Block (7) surveys wind data to wind field flow model module (8) output considering landform；Wake model module (9) receives initial blower fan
Arrange and consider the wind field flow distribution that wind field flow model module (8) of landform exports；
Described data workstation (1) includes the big data platform of wind energy turbine set (4) and data analysis model module (5), data analysis mould
Pattern block (5) receives independent variable and the dependent variable that the big data platform of wind energy turbine set (4) sends, and to optimizing, layout platform (3) output is real
Border generated energy and blower fan layout modifying factor；
Described optimization layout platform (3) includes that wind energy turbine set generated energy computation model module (10) and wind energy turbine set optimize layout calculation
Model module (11), wind energy turbine set generated energy computation model module (10) receives the output of wake model module (9), and receives blower fan
Layout modifying factor, the generated energy that aweather electric Field Optimization layout calculation model module (11) output is revised；Wind energy turbine set optimizes layout
Computation model module (11) output wind energy turbine set optimizes layout result.
Combine the complicated landform wind field design platform of big data the most as claimed in claim 1, it is characterised in that also to described
Wind field flow model module (8) of consideration landform and wake model module (9) carry out depression of order；
Wake model module (9) after described wind energy turbine set generated energy computation model and depression of order and the wind field flow model of consideration landform
Module (8) matches, and described wind energy turbine set optimizes layout calculation model module (11) and wind energy turbine set generated energy computation model module
(10) match with genetic Optimization Algorithm.
Combine the complicated landform wind field design platform of big data the most as claimed in claim 1, it is characterised in that described data
Analyze the input independent variable of model module (5) be landform (17) at wind regime (16), blower fan at blower fan, actual wind turbine layout (18) and
Theoretical generated energy (21) etc., the dependent variable of model is actual power generation (19), fan operation state (20) and blower fan layout correction
The factor (22), blower fan layout modifying factor is between 0～1.
4. the complicated landform wind field design method combining big data, it is characterised in that include following operation:
1) using the meteorological data including atmospheric pressure, height above sea level, temperature, wind direction, wind speed as input, mesoscale is utilized
Numerical model module (6) carries out high-resolution simulation and calculates；Obtain wind-resources distribution situation and the wind money in complex topographic area territory
Source reserves；
2) NO emissions reduction wind-resources model module (7) obtains the result mesoscale data given by mesoscale numerical model module (6)
(12), and using it as the boundary condition of NO emissions reduction hydrodynamic analogy, alternative wind field is carried out NO emissions reduction simulation, it is thus achieved that wind
Resource distribution (13)；Coupling system access, road transport, environmental conservation build field condition at interior, set up comprehensive evaluation index body
System, instructs macroscopical addressing of wind field；
3) wind-resources distribution (13) be given based on NO emissions reduction wind-resources model module (7), divides representative region, determines anemometer tower
Arrangement (24), the parameter including anemometer tower quantity, installation site, instrument for wind measurement setting height(from bottom), thus obtain survey wind
Data (25)；
4) for complicated terrain generation high-quality body fitted grids, analyze software based on CFD and set up the wind field flowing mould of consideration landform
Pattern block (8), is that boundary condition calculates to survey wind data (25), and application simultaneously surveys wind data (25) to turbulent flow mould used
Shape parameter is demarcated；Wherein consider that wind field flow model module (8) of landform describes the quality of wind flow in design section, moves
Amount, energy and air condition, the wind regime in output design section, wind speed, wind direction, the distributed in three dimensions of turbulivity；
5) to consider wind field flow distribution (14) that wind field flow model module (8) of landform calculates and initial wind turbine layout
(15) initial condition calculated as wake model module (9), analyzes software based on CFD and sets up different typical case's landform lower tail stream mould
Pattern block (9)；Wherein wake model describes air flow behavior change after barrier, after output barrier in certain limit
Wind regime, wind speed, wind direction, the distributed in three dimensions of turbulivity；
6) the big data platform of wind energy turbine set (4) is set up, ground at wind regime (16), blower fan at application-dependent data analysis method acquisition blower fan
Shape (17), the actual wind turbine layout (18) dependency relation between interior factor and blower fan unit performance, obtain data analysis mould
Pattern block (5), determines that blower fan unit performance is by landform (17), actual wind turbine layout (18) etc. at wind regime at blower fan (16), blower fan
The quantitative effect size of factor；Described blower fan unit performance includes actual power generation (19) and fan operation state (20)；
7) according to wake model module (9) and the output data of wind field flow model module (8) considering landform, it is thus achieved that blower fan position
Put the wind regime at place, and the generated energy of the input calculating blower fan as power of fan curve；Wind energy turbine set generated energy computation model
As follows:
Wherein, viRepresent input vector, including wind regime, landform and wind turbine layout；P () represents wind turbine power generation amount；I represents blower fan
Numbering；N represents maximum blower fan number；W represents wind energy turbine set general power；
Theoretical generated energy (21) is repaiied by blower fan layout modifying factor (22) exported based on Data Analysis Model module (5)
Just；
8) optimizing application algorithm sets up wind energy turbine set optimization layout calculation model (11), and using revised generated energy (26) as wind
The input of electric Field Optimization layout calculation model, optimizes placement scheme (23) through optimizing the wind energy turbine set obtained under complicated landform；Its
In, described optimized algorithm is genetic algorithm, ant group algorithm or simulated annealing.
Combine the complicated landform wind field design method of big data the most as claimed in claim 4, it is characterised in that with blower fan cloth
Office's modifying factor (22) is correction conditions, and its mathematical expression formula is:
Wherein, viRepresent input vector, including wind regime, landform and wind turbine layout；E () represents blower fan layout modifying factor；p
() represents wind turbine power generation amount；I represents blower fan numbering；N represents maximum blower fan number；W represents wind energy turbine set general power.
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