CN113051845A - Method, system, equipment and storage medium for visually evaluating real-time wind resources of in-service mountain wind power plant - Google Patents
Method, system, equipment and storage medium for visually evaluating real-time wind resources of in-service mountain wind power plant Download PDFInfo
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Abstract
The invention discloses a visual assessment method, a system, equipment and a storage medium for real-time wind resources of an in-service mountain wind power plant, wherein the method is used for acquiring the spatial position, real-time wind direction and wind speed data of the existing wind measuring equipment of the in-service mountain wind power plant; finding out related wind speed data under a corresponding wind direction sector in the wind resource offline data set; performing online calculation on the wind vector of the corresponding ground clearance height layer by using an internal interpolation method to obtain the wind resource distribution of the current full wind power plant; and carrying out real-time wind resource assessment on the in-service mountain wind power plant in a visual map mode. The method is based on the wind resource offline data set, combines the evaluation thinking of wind direction sector classification and wind speed interpolation of field wind measurement data, ensures the simulation precision, avoids the online calculation with longer working hours, saves the allocation of software and hardware resources in an operation and maintenance system, realizes the visual output of the whole field of real-time wind resources, and provides theoretical reference and data analysis basis for the energy efficiency evaluation of the wind turbine generator.
Description
Technical Field
The invention belongs to the technical field of wind power plant wind energy resource calculation, and particularly relates to a method, a system, equipment and a storage medium for visually evaluating the real-time wind resources of an in-service mountain wind power plant based on a wind resource offline data set.
Background
In recent years, onshore wind power is mainly and vigorously developed aiming at geographical positions with excellent wind energy resources and better construction conditions, so that large centralized site resources represented by flat terrains tend to be limited. At present, the development environment of onshore wind power is gradually turned to a complex mountain area with relatively rich wind resources and large volatility from a flat terrain. The air flow above the wind farm in mountainous regions is influenced by complex landforms, local wind direction change, intermittent wind fluctuation and regional strong turbulence often occur, and the wind condition directly influences the wind energy utilization rate and the generating capacity of the whole farm.
Because the area range that the wind power prediction anemometer tower equipped with in-service mountain wind power station can represent is limited, it is difficult to accurately evaluate the distribution of wind energy resources in the whole field. Therefore, the real-time evaluation of the wind energy resources of the wind power plant in the in-service mountain region can enable operation and maintenance personnel of the wind power plant to better know the wind conditions of all regions in the plant, so that the generated energy of the wind turbine generator can be rechecked, whether the actual operation index of the wind power plant reaches the target determined in the project design or not is determined, the method is an important link of the intelligent operation and maintenance technology of the current wind power plant, and theoretical reference and data analysis basis can be provided for follow-up operation and maintenance management and unit maintenance. The method is mainly used for visually and vividly recording and dynamically displaying the wind speed and the wind direction of each wind turbine point position in an intelligent operation and maintenance system of a remote centralized control center according to current refined wind condition data obtained by calculating a wind power plant region.
At present, the evaluation of wind energy resources of a wind power plant is generally used in an early exploration and design stage, and the flow characteristics of wind in a target area are scientifically predicted and calculated by combining field wind measurement data or mesoscale weather data and utilizing a numerical simulation method, so that the wind resource prediction of the whole plant continuity is obtained. For wind resource numerical simulation of a complex mountain wind farm, a nonlinear Computational Fluid Dynamics (CFD) mode is generally required to be adopted to generate a spatial grid with high resolution to analyze irregular landforms, so that wind condition prediction with high reliability is obtained. However, as the land occupation and installed capacity of the mountain wind farm site are continuously increased, the number of grids required by the calculation domain is multiplied, so that the solution time required by the numerical simulation is continuously increased under the condition that the cost of the operation resources is not increased.
However, after the mountain wind farm is put into production and operated, the visual evaluation of the wind resource flow field is used as a functional module of the whole intelligent operation and maintenance system, and due to the limitation of the allocation of the computing and processing hardware resources, it is difficult to embed the refined wind resource calculation based on the CFD method into the real-time evaluation link of the wind resources in an online manner. For online evaluation of wind resources of an in-service mountain wind power plant, the online evaluation is still in an exploration phase at present. For example, the invention patent with application number 202010550705.6, application date 2020.06.16, published as 2020.09.25 discloses a wind power plant wind resource calculation method using unit SCADA data, wherein a cabin transfer function of one unit in a wind power plant is obtained through calculation, the cabin wind speed of each representative unit is corrected by using the transfer function relation, and then wind resource simulation is performed by using the corrected wind speed. The method is based on the premise that the influence of topographic changes on the unit cabin transfer function can be ignored, the single unit is adopted in the cabin transfer function of the wind power plant, the wind resource conditions of the positions of the units are reflected in real time, the method is mostly suitable for wind resource evaluation of the wind power plant with low topographic complexity, and for the situation of complex mountainous regions, the influence factors of terrains in different regions on the cabin transfer function need to be researched. Meanwhile, although the invention utilizes virtual wind measurement data obtained by SCADA real-time data of a plurality of units to perform CFD calculation so as to obtain the whole-field wind speed distribution corresponding to each time point and even the whole-field annual average wind speed distribution, the result does not relate to the real-time visual evaluation of the wind condition during the operation and maintenance of the wind power plant.
Disclosure of Invention
Aiming at the difficult problems mentioned in the background art, the invention aims to provide a method, a system, equipment and a storage medium for visually evaluating the real-time wind resources of an on-service mountain wind power plant based on a wind resource offline data set.
In order to achieve the purpose, the invention adopts the technical scheme that:
a real-time wind resource visual assessment method for an in-service mountain wind power plant comprises the following steps:
acquiring the spatial position, real-time wind direction and real-time wind speed data of the existing wind measuring equipment of the in-service mountain wind power plant;
finding out related wind speed data under a corresponding wind direction sector in the wind resource offline data set; performing online calculation on the wind vector of the corresponding ground clearance height layer by using an internal interpolation method to obtain the wind resource distribution of the current full wind power plant;
and carrying out real-time wind resource assessment on the in-service mountain wind power plant in a visual map mode.
As a further improvement of the invention, the wind resource offline data set adopts a lead numerical simulation mode, and calculates the wind conditions of the area where the wind power plant is located by taking a symbolic inflow wind speed sequence under each inflow wind direction sector as a drive, so as to establish the wind resource offline data set under different drive wind speeds in each wind direction sector; the method specifically comprises the following steps:
determining a target calculation domain of the mountain wind power plant according to the geographic position coordinates of the field wind measuring equipment of the target mountain wind power plant and each wind turbine generator, acquiring a high-precision digital elevation model of the terrain of the region, and establishing and generating a hexahedral space calculation domain and a grid to be subjected to wind resource CFD numerical simulation;
formulating a wind resource refinement numerical simulation scheme based on a CFD (computational fluid dynamics) mode; each symbolic driving wind speed is adopted, and CFD numerical simulation is carried out on the whole wind electric field area;
sampling the wind direction and the wind speed at the hub height position of the point position in the simulation result according to the position coordinates of the on-site wind measuring equipment based on the wind resource simulation result corresponding to each group of driving wind conditions to serve as the driving wind conditions of the wind measuring point position;
and constructing a wind resource offline data set framework based on the obtained driving wind conditions of each group of wind measuring point positions.
As a further improvement of the present invention, the formulating a wind resource refinement numerical simulation scheme based on the CFD mode specifically includes:
dividing an incoming flow wind direction sector;
determining the height of a hub at the corresponding inlet boundary under each incoming flow wind direction sector, wherein the height can be used for driving a numerical simulation symbolic incoming flow wind speed sequence;
setting necessary operation parameters related to numerical simulation of boundary conditions, time and space discrete formats, turbulence models, a coupling iterative algorithm for solving a flow control equation and the like in each direction based on a wind resource evaluation method;
and (3) carrying out CFD numerical simulation on the whole wind electric field area by adopting each symbolic driving wind speed under each incoming flow wind direction sector until the simulation result corresponding to each group of driving wind conditions is converged and the stability is maintained.
As a further improvement of the invention, the building of the wind resource offline data set framework comprises the following steps:
establishing a first layer of incoming flow wind direction data set according to the incoming flow wind direction sectors, wherein the incoming flow wind direction data set comprises first subsets with the number corresponding to the number of the incoming flow wind direction sectors, and each first subset corresponds to the central angle value of the incoming flow sector corresponding to the driving wind direction of the wind measuring point;
establishing a second layer wind speed dataset under each subset of the incoming flow wind direction dataset;
the wind speed data set comprises second subsets with the number corresponding to the driving wind speed of the wind measuring point, and each second subset corresponds to the driving wind speed of the wind measuring point;
under a second subset of the second layer of wind speed data sets, establishing a third layer of different ground clearance level data sets based on the impeller wind sweeping height; the data set of different ground clearance height layers consists of a plurality of third subsets, and the third subsets correspond to the values of the wind turbine blade minimum wind-sweeping height, the hub height and the wind turbine blade maximum wind-sweeping height.
As a further improvement of the present invention, the finding of the relevant wind speed data in the corresponding wind direction sector in the wind resource offline data set specifically includes the following steps:
determining the central angle of the wind direction sector according to the angle range of the real-time wind direction data in the incoming flow sector, and entering a corresponding incoming flow wind direction data set in the wind resource offline data set;
entering a wind speed data set in an incoming flow wind direction data set, and searching two wind speed values adjacent to the wind speed data value;
and respectively entering different ground clearance layer data sets corresponding to two adjacent wind speed data sets of the wind speed data, and simultaneously reading the whole field wind vector data in a folder of the same ground clearance layer.
As a further improvement of the present invention, the online calculation of the wind vector of the corresponding terrain clearance layer by using an internal interpolation method to obtain the wind resource distribution of the current full wind farm specifically includes the following steps:
performing internal interpolation calculation on the wind speed data and two adjacent wind speed values to obtain an interpolated scale factor, and calculating the whole field wind vector data based on the current wind direction data and the wind speed data by utilizing interpolation in combination with the read wind vector data with the same ground clearance corresponding to the two adjacent wind speeds;
reading wind vector data at the same spatial position in the folders of the same ground clearance height layer in two adjacent wind speed data sets,
calculating the wind speed components in the directions of x, y and z corresponding to each spatial coordinate point in the ground clearance layer based on the current wind direction data and the wind speed data by utilizing interpolation;
and after the wind speed component calculation is carried out on each space point position in sequence, the wind resource distribution data of the current full wind farm is obtained.
As a further improvement of the method, the real-time wind resource assessment of the in-service mountain wind power plant in the form of the visual map specifically comprises the following steps:
based on the current actually measured wind direction data and the whole field wind vector data with different ground heights obtained under the wind speed data, obtaining visual display of a current field wind speed slice cloud picture and a current field wind speed flow line through a visual tool;
and counting the wind speed of the point positions of each wind turbine set, and rechecking the theoretical power and the actual power of each wind turbine set through a wind speed-power curve.
A real-time wind resource visual assessment system for an in-service mountain wind power plant comprises:
the acquiring module is used for acquiring the spatial position of the existing wind measuring equipment of the in-service mountain wind power plant, and real-time wind direction and wind speed data;
the calculation module is used for finding out related wind speed data under a corresponding wind direction sector in the wind resource offline data set; performing online calculation on the wind vector of the corresponding ground clearance height layer by using an internal interpolation method to obtain the wind resource distribution of the current full wind power plant;
and the evaluation module is used for evaluating the real-time wind resources of the in-service mountain wind power plant in a visual map mode.
An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the in-service mountain wind farm real-time wind resource visualization evaluation method when executing the computer program.
A computer-readable storage medium, which stores a computer program that, when being executed by a processor, carries out the steps of the method for the visual assessment of real-time wind resources of an in-service mountain wind farm.
Compared with the prior art, the method has the beneficial effects that:
the invention provides a real-time wind resource visual assessment method for an in-service mountain wind power plant based on a wind resource offline data set, which adopts a pilot numerical simulation mode, takes a symbolic inflow wind speed sequence under each inflow wind direction sector as a drive, and calculates the wind condition of the area where the wind power plant is located, so as to establish a full-field wind resource offline data set under different drive wind speeds in each wind direction sector; in the actual operation and maintenance process, based on real-time wind direction and wind speed data acquired by existing wind measuring equipment in a field, a related wind speed data set corresponding to a wind direction sector is found in a wind resource off-line data set, so that an internal interpolation method is used for carrying out on-line calculation on a wind vector of a corresponding ground clearance layer, the wind resource distribution of the current full wind power plant is obtained, and the evaluation is carried out in an intelligent operation and maintenance system in a visual map mode. The method is based on the wind resource offline data set, combines the evaluation thinking of wind direction sector classification and wind speed interpolation of field wind measurement data, ensures the simulation precision, avoids the online calculation with longer working hours, saves the allocation of software and hardware resources in an operation and maintenance system, realizes the visual output of the whole field of real-time wind resources, and provides theoretical reference and data analysis basis for the energy efficiency evaluation of the wind turbine generator. The common CFD refined wind resource simulation is used for establishing a full-field wind resource off-line data set corresponding to different driving wind speeds under each incoming flow sector in a pre-prediction mode, CFD parameters related to calculation debugging in numerical simulation are effectively set and an iterative solution link is effectively carried out, and before the CFD refined wind resource simulation is used on line in an intelligent operation and maintenance system of a wind power plant, the convergence and the stability of calculation results under each driving wind condition are ensured.
Furthermore, by utilizing real-time wind direction and wind speed data acquired by on-site wind measuring equipment, wind direction sector classification and wind speed internal interpolation calculation are carried out on wind resource off-line data in a centralized manner to obtain the on-line assessment idea of the wind condition of the whole field, so that the on-line numerical simulation with longer working hours is avoided, and the allocation of software and hardware resources in an operation and maintenance system is saved;
furthermore, the real-time wind condition data of the wind power plant obtained by wind direction sector classification and wind speed internal interpolation method can be stored and output in a space coordinate-wind vector format based on the requirements of different terrain clearance layers above the wind power plant, and the display and evaluation of atmospheric flow characteristics such as wind speed slice cloud pictures, flow lines and the like can be realized through flow field visualization software/plug-ins compatible and matched with an operation and maintenance system.
Furthermore, by acquiring and displaying wind speed scalar data and a cloud chart of a hub height layer of the whole field region, the wind speed calculated at each unit point position can be compared and analyzed with an engine room anemometer, and meanwhile, the energy efficiency of the unit is evaluated through a wind speed-power curve.
Drawings
FIG. 1 is a flow chart of a real-time wind resource visual assessment method for an in-service mountain wind farm based on a wind resource offline data set according to the present invention;
FIG. 2 is a schematic diagram of an offline data set structure of wind resources in a wind farm;
FIG. 3 is a wind speed distribution cloud chart at a height of 90m of the whole field under driving wind conditions (270 degrees and 8m/s) of a wind measuring point position, namely, under wind speed conditions (270 degrees and 8m/s) of an incoming flow wind direction (positive west wind) and 8m/s of the wind measuring point position (wherein a dot represents a wind turbine unit point position, and a rectangular tip bar represents a wind measuring tower position);
FIG. 4 is a flow chart of the whole field at a height of 90m under driving wind conditions (270 degrees and 8m/s) at the wind measuring point, namely, under an incoming wind direction (normal west wind) at 270 degrees and a wind speed of 8m/s at the wind measuring point;
FIG. 5 is a schematic structural diagram of a real-time wind resource visual evaluation system of an in-service mountain wind farm of the present invention;
FIG. 6 is a schematic structural diagram of an electronic device according to the present invention.
Detailed Description
In order to make the objects and technical solutions of the present invention clearer and easier to understand. The present invention will be described in further detail with reference to the following drawings and examples.
As shown in fig. 1, a first object of the present invention is to provide a method for visually evaluating the real-time wind resources of an in-service mountain wind farm based on a wind resource offline data set, which includes applying a computational fluid dynamics mode to an area where the wind farm is located, and performing numerical simulation of the wind condition of the whole farm by using different representative wind speeds in each incoming wind direction sector as driving, thereby establishing a full-field wind resource offline data set in each wind direction sector at different driving wind speeds; secondly, based on the spatial position of the existing wind measuring equipment of the in-service mountain wind power plant and the collected real-time wind direction and wind speed data, finding out relevant wind speed data under a corresponding wind direction sector in the wind resource off-line data set by using an internal interpolation method, and thus, performing on-line calculation on the wind vector of the corresponding ground clearance layer by using the internal interpolation method to obtain the wind resource distribution of the current full wind power plant and evaluating the wind vector in the intelligent operation and maintenance system in the form of a visual map.
Specifically, the method for visually evaluating the real-time wind resources of the in-service mountain wind power plant based on the wind resource offline data set comprises the following steps:
a first part: and (4) establishing a wind resource offline data set (comprising the steps one to five).
Determining a target calculation domain of a mountain wind power plant according to geographical position coordinates of field wind measuring equipment of the target mountain wind power plant and wind generating sets, acquiring a high-precision Digital Elevation Model (DEM) of the terrain of the region, and establishing and generating a hexahedron space calculation domain and a grid to be subjected to wind resource CFD numerical simulation;
step two, formulating a wind resource refinement numerical simulation scheme based on the CFD mode, which specifically comprises the following steps:
2.1) dividing the wind direction sector of the incoming flow. Selecting sixteen directions to flow according to classical wind direction rose diagram, wherein each direction represents wind direction sector central angle Di(where i is 1 to 16), and the angle ranges of the incoming flow sectors represented by the angles are shown in table 1;
wind direction sector center angle and sector angle range corresponding to incoming wind direction of meter 116 azimuth
2.2) determining the corresponding inlet boundary hub height under each incoming wind direction sector, wherein the corresponding inlet boundary hub height can be used for driving a numerical simulation symbolic incoming wind speed sequence, and particularly the cut-in wind speed (V) of the wind turbine setin) Cut-out wind speed (V)out) Incremental selection of the symbolic driving wind speed is carried out in the interval;
wind turbine generator system cut-in wind speed V in the present embodimentinCut-out wind speed V of 2.5m/sout20m/s, the rated operation wind speed of the unit is 13m/s, and the driving wind speed sequence with the desired index is Vj＝[2.5m/s，7.0m/s，10.m/s，13m/s，20m/s]Wherein j is 1 to 5.
2.3) based on available wind resource evaluation commercial software or professional fluid mechanics simulation software, reasonably setting necessary operation parameters related to numerical simulation such as boundary conditions, time and space discrete formats, turbulence models, coupled iterative algorithms for solving flow control equations and the like in all directions;
2.4) in each incoming flow direction sector (D)i) Next, each index driving wind speed (V) is adoptedj) CFD numerical simulations were performed on the entire wind field area (total 16 × 5-80 groups) until each group driven wind condition (D)i，Vj) The corresponding simulation result is converged and the stability is maintained;
step three, based on step twoMiddle and each group of driving wind conditions (D)i，Vj) Corresponding wind resource simulation results are obtained, according to the position coordinates of the field wind measuring equipment, the wind direction at the hub height position of the point in the simulation results
With wind speed
Sampling as wind-measuring point to drive wind condition
It should be noted here that the wind-sensing point drives the wind direction due to the spatial variation of the wind condition vector of the flow field
With wind speed
Driving wind direction D corresponding to inlet boundaryiWith wind speed VjClose, but with some differences;
step four, driving wind conditions of each group of wind measuring point positions obtained based on the step three
A wind resource offline data set framework is constructed, and a structural framework of the wind resource offline data set framework is shown in fig. 2, and specifically comprises the following steps:
4.1) establishing a first layer of 'incoming flow wind direction file set' according to the incoming flow wind direction sectors in the step 2.1.
The 'incoming flow wind direction file set' is composed of folders with the number corresponding to that of incoming flow wind direction sectors, and the folders at the level drive the wind direction by wind measuring point positions
Corresponding to the central angle value (D) of the incoming flow sectori) Naming;
in this embodiment, the "incoming flow wind direction file set" includes 16 folders with names: "0 °", "22.5 °", "45 °", …, "315 °", "337.5 °".
4.2) establishing a second layer of "wind speed filesets" under each folder in the "incoming wind direction fileset" in step 4.1.
The wind speed file set drives the wind speed by the wind measuring point position
The folders of the hierarchy drive the wind speed numerical value by the wind measuring point position
Naming;
for example, in this embodiment, under the folder "45 °" under the first layer "incoming wind direction file set", the second layer "wind speed file set" is established to contain 5 folders with names: "2.65 m/s", "7.35 m/s", "10.4 m/s", "13.5 m/s", "20.62 m/s". (it is explained here that a slight acceleration effect is produced at the point of anemometry when the wind blows from the northeast sector)
4.3) establishing a third layer of file sets with different ground clearance heights based on the wind sweeping height of the impeller under each folder in the wind speed file set in the step 4.2.
The file set of the layers with different ground heights is composed of 3 folders (can be increased or decreased according to analysis requirements), and the folders (taking 3 as an example) of the level are named by numerical values of the lowest wind sweeping point height of the wind wheel blade, the hub height and the highest wind sweeping point height of the wind wheel blade;
for example, in this embodiment, in a second tier of "10.4 m/s" (wind speed) folders under the first tier of "45 °" (wind direction) folders, a third tier of "different terrain height tier file sets" is created that contains 3 folders, each named: "20 m AGL", "90 m AGL", "160 m AGL". (the minimum wind sweeping height of the wind wheel blades is 20m, the hub height is 90m, and the maximum wind sweeping height of the wind wheel blades is 160 m.)
Step five, based on each wind measuring point position in step threeDriving wind condition
And performing slice extraction on the full-field wind data at the lowest wind sweeping position of the wind wheel blades, the hub and the highest wind sweeping position of the wind wheel blades according to the corresponding whole-field numerical simulation result to form space wind vector data files with different Ground heights (AGL), and storing the space wind vector data files in corresponding folders in the path of the 'incoming wind direction file set' → 'wind speed file set' → 'different Ground height layer file set' in the fourth step, wherein the files are named as 'Dxxx (wind direction) -Vyyyy (wind speed) -AGLzz (height layer). dat', so as to construct a wind resource offline data set.
For example, in this embodiment, in the "45 °" wind direction folder, the spatial wind vector data file stored in the "90 m AGL" folder under the "10.4 m/s" wind speed folder is: D45-V10.4-AGL90. dat.
The data structure of the space wind vector data files with different ground clearance heights is composed of 7 columns, and the space wind vector data files are respectively used for calculating east-west (x) direction coordinates, south-north (y) direction coordinates, vertical (z) direction coordinates and x direction wind speed components V corresponding to each coordinate point position (x, y, z)xY-direction wind speed component VyZ-direction wind speed component Vz。
A second part: a real-time wind resource visualization evaluation method for an in-service mountain wind power plant (comprising the steps six to nine).
Step six, acquiring real-time (10-minute average) wind direction data D on the basis of the hub height layer of the target mountain wind power plant field wind measuring equipmentmWith wind speed data VmAnd in the wind resource offline data set established in the step five, positioning and searching corresponding data files are carried out, and the method specifically comprises the following steps:
6.1) according to DmThe angle range of the incoming flow sector falling in Table 1 determines the center angle D of the wind direction sectoriEntering a lower folder D of a corresponding 'incoming flow wind direction file set' in the first layer of the wind resource offline data seti；
In this example, if Dm275 deg. it is locatedThe angular range of the incoming flow sector is 270 degrees plus or minus 11.25 degrees, and the central angle of the wind direction sector is 270 degrees, so that the '270 degrees' folder is entered.
6.2) entering folder DiThe "wind speed File set" (wind resource offline dataset second level) below, find two wind speed folders (and read their corresponding wind speed values) that are adjacent to the Vm value
And
)
in this embodiment, if VmThe two wind speed folders adjacent to it are "7.35 m/s" and "10.4 m/s", where,
6.3) entering respectively with VmUnder two adjacent wind speed folders, reading the whole field wind vector data file in the same file folder of the ground clearance height layer (the third layer of the wind resource offline data set) correspondingly;
in this embodiment, the "90 m AGL" folder under the "7.35 m/s" and "10.4 m/s" folders is entered, respectively, while the whole wind vector data files "D270-V7.35-AGL 90. dat" and "D270-V10.4-AGL 90. dat" are read.
Step seven, mixing VmTwo wind speed values adjacent to the one in step 6.2
Performing internal interpolation to obtain an interpolated scale factor (IF), combining the wind vector data of the same ground clearance corresponding to the two adjacent wind speeds read in step 6.3, and calculating based on the current D by using the IF interpolationmAnd VmThe following whole field wind vector data are specifically as follows:
7.1) computing the interpolated scale factor (IF)
In this embodiment of the present invention,
7.2) reading
And
under the folder, wind vector data at the same spatial position in the folder of the same ground clearance layer are calculated by utilizing IF interpolation and are based on the current DmAnd VmLower, x-direction wind speed component corresponding to each coordinate point in space in the terrain clearance layer
Component of wind speed in y direction
Component of wind speed in z direction
Wherein the content of the first and second substances,
are respectively as
Wind speed components in the x direction, the y direction and the z direction corresponding to a certain space point position under the folder; accordingly, the number of the first and second electrodes,
are respectively as
And wind speed components in the x direction, the y direction and the z direction corresponding to the same space point position under the folder.
In this embodiment, a set of wind vector data corresponding to the same spatial position coordinate in "D270-V7.35-AGL90. dat" and "D270-V10.4-AGL90. dat" are read
And
calculating the current actually measured wind direction data D by combining the formula (2)mWith wind speed data VmLower, wind vector (V) at the spatial position coordinatex m，Vy m，Vz m)。
7.3) carrying out sequential wind speed component calculation at each space point according to the method in the step 7.2), and storing the obtained result in a new data file.
In this embodiment, the wind speed components of all spatial points are calculated in sequence, and the obtained result is stored in the file "D270-V8.00-AGL90. dat".
Step eight, based on the step seven (current measured wind direction data D)mWith wind speed data VmNext), obtaining the whole field wind vector data with different ground clearance heights, and obtaining visual display of a current 10-minute field wind speed slice cloud picture and a streamline through flow field visual software/plug-in compatible and matched with an operation and maintenance system;
in this embodiment, the wind direction data D is based on the current measured wind directionm275 ° from the wind speed data VmThe wind vector data in the 20m, 90m, 160m terrain layer at 8m/s are "D270-V8.00-agll 20. dat", "D270-V8.00-agll 90. dat", "D270-V8.00-agll 160. dat". The cloud chart and the line chart of the flow field wind speed obtained by the open source visualization software in the document D270-V8.00-AGL90.dat are respectively shown in fig. 3 and fig. 4.
Step nine, based on the step seven (current measured wind direction data D)mWith wind speed data VmNext), the wind speed of each wind turbine set point position is counted according to the obtained whole field wind vector data with different ground clearance heights, and the theoretical power and the actual power of each wind turbine set are rechecked through a wind speed-power curve.
As shown in FIG. 5, a second object of the present invention is to provide a real-time wind resource visualization evaluation system for an in-service mountain wind farm, comprising:
the acquiring module is used for acquiring the spatial position of the existing wind measuring equipment of the in-service mountain wind power plant, and real-time wind direction and wind speed data;
the calculation module is used for finding out related wind speed data under a corresponding wind direction sector in the wind resource offline data set; performing online calculation on the wind vector of the corresponding ground clearance height layer by using an internal interpolation method to obtain the wind resource distribution of the current full wind power plant;
and the evaluation module is used for evaluating the real-time wind resources of the in-service mountain wind power plant in a visual map mode.
As shown in fig. 6, a third object of the present invention is to provide an electronic device, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the method for visually evaluating the active mountain wind farm real-time wind resources.
A fourth object of the present invention is to provide a computer-readable storage medium, which stores a computer program, which when executed by a processor, implements the steps of the method for visually evaluating the real-time wind resources of an in-service mountain wind farm.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A real-time wind resource visual assessment method for an in-service mountain wind power plant is characterized by comprising the following steps:
acquiring the spatial position, real-time wind direction and real-time wind speed data of the existing wind measuring equipment of the in-service mountain wind power plant;
finding out related wind speed data under a corresponding wind direction sector in the wind resource offline data set; performing online calculation on the wind vector of the corresponding ground clearance height layer by using an internal interpolation method to obtain the wind resource distribution of the current full wind power plant;
and carrying out real-time wind resource assessment on the in-service mountain wind power plant in a visual map mode.
2. The method for visually evaluating the real-time wind resources of an in-service mountain wind farm according to claim 1, wherein the wind resource offline data set adopts a pilot numerical simulation mode, and is driven by a symbolic inflow wind speed sequence under each inflow wind direction sector to calculate the wind condition of the area where the wind farm is located, so that wind resource offline data sets under different driving wind speeds in each wind direction sector are established; the method specifically comprises the following steps:
determining a target calculation domain of the mountain wind power plant according to the geographic position coordinates of the field wind measuring equipment of the target mountain wind power plant and each wind turbine generator, acquiring a high-precision digital elevation model of the terrain of the region, and establishing and generating a hexahedral space calculation domain and a grid to be subjected to wind resource CFD numerical simulation;
formulating a wind resource refinement numerical simulation scheme based on a CFD (computational fluid dynamics) mode; each symbolic driving wind speed is adopted, and CFD numerical simulation is carried out on the whole wind electric field area;
sampling the wind direction and the wind speed at the hub height position of the point position in the simulation result according to the position coordinates of the on-site wind measuring equipment based on the wind resource simulation result corresponding to each group of driving wind conditions to serve as the driving wind conditions of the wind measuring point position;
and constructing a wind resource offline data set framework based on the obtained driving wind conditions of each group of wind measuring point positions.
3. The method for visually evaluating the real-time wind resources of an in-service mountain wind farm according to claim 2, wherein the formulating of the wind resource refinement numerical simulation scheme based on the CFD mode specifically comprises:
dividing an incoming flow wind direction sector;
determining the height of a hub at the corresponding inlet boundary under each incoming flow wind direction sector, wherein the height can be used for driving a numerical simulation symbolic incoming flow wind speed sequence;
setting necessary operation parameters related to numerical simulation of boundary conditions, time and space discrete formats, turbulence models, a coupling iterative algorithm for solving a flow control equation and the like in each direction based on a wind resource evaluation method;
and (3) carrying out CFD numerical simulation on the whole wind electric field area by adopting each symbolic driving wind speed under each incoming flow wind direction sector until the simulation result corresponding to each group of driving wind conditions is converged and the stability is maintained.
4. The method for visually evaluating real-time wind resources of an in-service mountain wind farm according to claim 2, wherein the constructing of the wind resource offline dataset framework comprises:
establishing a first layer of incoming flow wind direction data set according to the incoming flow wind direction sectors, wherein the incoming flow wind direction data set comprises first subsets with the number corresponding to the number of the incoming flow wind direction sectors, and each first subset corresponds to the central angle value of the incoming flow sector corresponding to the driving wind direction of the wind measuring point;
establishing a second layer wind speed dataset under each subset of the incoming flow wind direction dataset;
the wind speed data set comprises second subsets with the number corresponding to the driving wind speed of the wind measuring point, and each second subset corresponds to the driving wind speed of the wind measuring point;
under a second subset of the second layer of wind speed data sets, establishing a third layer of different ground clearance level data sets based on the impeller wind sweeping height; the data set of different ground clearance height layers consists of a plurality of third subsets, and the third subsets correspond to the values of the wind turbine blade minimum wind-sweeping height, the hub height and the wind turbine blade maximum wind-sweeping height.
5. The method for visually evaluating real-time wind resources of an in-service mountain wind farm according to claim 1, wherein the step of finding relevant wind speed data under a corresponding wind direction sector in the wind resource offline data set specifically comprises the following steps:
determining the central angle of the wind direction sector according to the angle range of the real-time wind direction data in the incoming flow sector, and entering a corresponding incoming flow wind direction data set in the wind resource offline data set;
entering a wind speed data set in an incoming flow wind direction data set, and searching two wind speed values adjacent to the wind speed data value;
and respectively entering different ground clearance layer data sets corresponding to two adjacent wind speed data sets of the wind speed data, and simultaneously reading the whole field wind vector data in a folder of the same ground clearance layer.
6. The in-service mountain wind farm real-time wind resource visualization evaluation method according to claim 1, wherein the wind vectors of the corresponding terrain clearance layer are calculated online by using an internal interpolation method to obtain the wind resource distribution of the current full wind farm, and the method specifically comprises the following steps:
performing internal interpolation calculation on the wind speed data and two adjacent wind speed values to obtain an interpolated scale factor, and calculating the whole field wind vector data based on the current wind direction data and the wind speed data by utilizing interpolation in combination with the read wind vector data with the same ground clearance corresponding to the two adjacent wind speeds;
reading wind vector data at the same spatial position in the folders of the same ground clearance height layer in two adjacent wind speed data sets,
calculating the wind speed components in the directions of x, y and z corresponding to each spatial coordinate point in the ground clearance layer based on the current wind direction data and the wind speed data by utilizing interpolation;
and after the wind speed component calculation is carried out on each space point position in sequence, the wind resource distribution data of the current full wind farm is obtained.
7. The method for visually evaluating the real-time wind resources of the on-service mountain wind farm according to claim 1, wherein the evaluation of the real-time wind resources of the on-service mountain wind farm in the form of a visual map specifically comprises the following steps:
based on the current actually measured wind direction data and the whole field wind vector data with different ground heights obtained under the wind speed data, obtaining visual display of a current field wind speed slice cloud picture and a current field wind speed flow line through a visual tool;
and counting the wind speed of the point positions of each wind turbine set, and rechecking the theoretical power and the actual power of each wind turbine set through a wind speed-power curve.
8. The real-time wind resource visual assessment system for the in-service mountain wind power plant is characterized by comprising the following components:
the acquiring module is used for acquiring the spatial position of the existing wind measuring equipment of the in-service mountain wind power plant, and real-time wind direction and wind speed data;
the calculation module is used for finding out related wind speed data under a corresponding wind direction sector in the wind resource offline data set; performing online calculation on the wind vector of the corresponding ground clearance height layer by using an internal interpolation method to obtain the wind resource distribution of the current full wind power plant;
and the evaluation module is used for evaluating the real-time wind resources of the in-service mountain wind power plant in a visual map mode.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the in-service mountain wind farm real-time wind resource visualization evaluation method of any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, which stores a computer program that, when being executed by a processor, carries out the steps of the method for the visual assessment of the real-time wind resources of an active mountain wind farm according to any one of claims 1 to 7.
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