CN116502558B - Wind energy resource simulation method, device, equipment and medium - Google Patents
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Abstract
The application relates to the technical field of computers, and provides a wind energy resource simulation method, a device, equipment and a medium, wherein the method comprises the following steps: acquiring wind speed data and average wind speed deviation data of a plurality of wind direction sectors in a target wind power field; dividing wind speed data of each wind direction sector to obtain a plurality of wind speed sections and the number of samples corresponding to each wind speed section, and constructing a first matrix; according to the wind speed data and the average wind speed deviation data, obtaining turbulence intensity, and constructing a second matrix according to a plurality of wind speed sections and the turbulence intensity; removing values which do not meet a preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix; transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module so as to perform numerical simulation on the wind energy resources of the target wind power plant area, improve the accuracy of wind flow simulation and reduce the uncertainty of the wind energy resources of the target wind power plant area.
Description
Technical Field
The application relates to the technical field of computers, in particular to a wind energy resource simulation method, a wind energy resource simulation device, a wind energy resource simulation equipment and a wind energy resource simulation medium.
Background
With the increasing prominence of energy and environmental problems, wind energy is increasingly valued as a clean and renewable energy source, and the most basic condition for constructing a wind power plant is to have energy-rich wind energy resources and select a proper site, however, the advantages and disadvantages of site selection are directly related to the economy of the wind power plant.
Wind energy resource assessment has been developed to the stage of numerical simulation technology, and currently mainstream CFD (Computational Fluid Dynamics ) can perform wind resource assessment under complex terrain, so as to reduce assessment uncertainty under complex terrain conditions. When wind resource evaluation is carried out, the environmental turbulence intensity obtained by carrying out directional calculation on the wind field distribution of the standard initial wind field and different wind directions is obtained by CFD calculation, and the accuracy of wind flow simulation can be improved by using turbulence correction. Turbulence correction there are two ways, directional turbulence correction and turbulence matrix correction, which is generally employed. However, when the turbulence matrix is manufactured, the turbulence matrix cannot be directly used due to fewer samples or missing data, is often filled through artificial experience, has high uncertainty and long time consumption, and also has low accuracy of wind flow simulation.
Therefore, how to increase the generation rate of the turbulence matrix and the accuracy of wind flow simulation is a problem to be solved.
Disclosure of Invention
In view of the above problems in the prior art, the present application aims to provide a wind energy resource simulation method, device, equipment and medium, so as to at least solve the technical problems of how to increase the generation rate of a turbulence matrix and the accuracy of wind flow simulation.
To achieve the above and other related objects, the present application provides a wind energy resource simulation method, the method comprising:
acquiring wind speed data and average wind speed deviation data of a plurality of wind direction sectors in a target wind power field;
dividing wind speed data of each wind direction sector according to a preset wind speed interval to obtain a plurality of wind speed sections and the number of samples corresponding to each wind speed section, and constructing a first matrix according to the plurality of wind speed sections and the number of samples;
obtaining turbulence intensity according to the wind speed data and the average wind speed deviation data, and constructing a second matrix according to the wind speed sections and the turbulence intensity;
removing values which do not meet a preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix;
Transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module to perform numerical simulation on wind energy resources of the target wind farm area.
In an embodiment of the present application, transmitting the target turbulence matrix to a preconfigured wind energy resource assessment module to perform numerical simulation on wind energy resources of the target wind farm area, including:
Transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module;
Obtaining topographic data, roughness data, a preset drawing area, preset wind measuring points and result points of the target wind farm area and wind measuring tower observation results;
obtaining a plurality of initial wind fields and wind field distribution of each initial wind field according to the topographic data, the roughness data, the preset drawing area, the preset wind measuring points and the result points;
Correcting the wind field distribution of the initial wind fields according to the target turbulence matrix to obtain wind field distribution of the target wind fields;
And obtaining wind energy parameters at the result points according to the plurality of target wind fields, wind field distribution of each target wind field and the observation result of the wind measuring tower so as to realize numerical simulation of wind energy resources of the target wind field area.
In an embodiment of the application, obtaining turbulence intensity according to wind speed data and the average wind speed deviation data comprises:
according to the wind speed data, average wind speed data in a preset time interval is obtained;
and obtaining the turbulence intensity according to the ratio between the average wind speed data and the average wind speed deviation data.
In an embodiment of the present application, before obtaining the wind speed data and the average wind speed deviation data of a plurality of wind direction sectors in the target wind farm, the method further includes:
Acquiring wind direction data in the target wind power field area;
And dividing the wind direction in the wind direction data into a plurality of wind direction sectors according to a preset wind direction division difference value.
In an embodiment of the present application, removing values in the first matrix and the second matrix that do not satisfy a preset threshold range to obtain a reserved value, and performing matrix interpolation on the second matrix according to the reserved value to obtain a target turbulence matrix, including:
Removing a wind speed section smaller than a preset sample quantity threshold value in the first matrix and the sample quantity corresponding to the wind speed section to obtain a first reserved value;
Removing a wind speed section smaller than the sample quantity threshold value in the second matrix and turbulence intensity corresponding to the wind speed section to obtain a second reserved value;
Obtaining a corresponding relation between the wind speed section and the turbulence intensity according to the first reserved value and the second reserved value;
if the average wind speed effective value of the target wind speed section in the second reserved value is smaller than a preset interpolation average wind speed effective value threshold value, interpolating turbulence intensity corresponding to a previous wind speed section of the target wind speed section into turbulence intensity of the target wind speed section to obtain the target turbulence matrix;
If the average wind speed effective value of the target wind speed section is larger than the interpolation average wind speed effective value threshold value, obtaining interpolation turbulence intensity corresponding to the target wind speed section according to the corresponding relation between the wind speed section and the turbulence intensity, and interpolating the second reserved value according to the target wind speed section and the interpolation turbulence intensity to obtain the target turbulence matrix.
In an embodiment of the present application, the representation of the correspondence between the wind speed segment and the turbulence intensity includes:
lnTi＝klnVhub+m
wherein Ti is the turbulence intensity, V hub is the average wind speed of the wind speed section, k is the slope, and m is the intercept.
In one embodiment of the present application, the interpolation turbulence intensity is expressed by:
Wherein Ti' is the interpolation turbulence intensity, V hub is the average wind speed of the wind speed section, k is the slope, and m is the intercept.
In an embodiment of the present application, there is also provided a wind energy resource simulation device, the device including:
The data acquisition module is used for acquiring wind speed data and average wind speed deviation data of a plurality of wind direction sectors in a target wind power field;
The first matrix construction module is used for dividing wind speed data of each wind direction sector according to a preset wind speed interval to obtain a plurality of wind speed sections and the number of samples corresponding to each wind speed section, and constructing a first matrix according to the plurality of wind speed sections and the number of samples;
the second matrix construction module is used for obtaining turbulence intensity according to the wind speed data and the average wind speed deviation data and constructing a second matrix according to the wind speed sections and the turbulence intensity;
the matrix interpolation module is used for removing the values which do not meet the preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix;
and the simulation module is used for transmitting the target turbulence matrix to a pre-configured wind energy resource evaluation module so as to perform numerical simulation on the wind energy resources of the target wind power plant area.
In an embodiment of the present application, there is further provided a computer readable storage medium, including a stored computer program, wherein the computer program executes the wind energy resource simulation method described above.
In an embodiment of the application, there is also provided an electronic device comprising a memory and a processor, the memory having stored therein a computer program, the processor being arranged to perform the wind energy resource simulation method described above by means of the computer program.
The invention has the beneficial effects that:
Firstly, acquiring wind speed data and average wind speed deviation data of a plurality of wind direction sectors in a target wind power field; dividing wind speed data of each wind direction sector according to a preset wind speed interval to obtain a plurality of wind speed sections and the number of samples corresponding to each wind speed section, and constructing a first matrix according to the wind speed sections and the number of samples; obtaining turbulence intensity according to the wind speed data and the average wind speed deviation data, and constructing a second matrix according to the wind speed sections and the turbulence intensity; removing values which do not meet a preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix; and finally, transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module so as to perform numerical simulation on wind energy resources of the target wind power plant area. According to the application, the target turbulence matrix is generated in a standard mode, so that the generation rate of the target turbulence matrix is improved, and the problem of insufficient data accuracy caused by filling data by artificial experience is avoided; in addition, the wind energy resources in the target wind power plant area are subjected to numerical simulation through the target turbulence matrix, so that the accuracy of wind flow simulation can be further improved, and the uncertainty of the wind energy resources in the target wind power plant area can be reduced.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a schematic view of an application environment of a wind energy resource simulation method shown in an exemplary embodiment of the application;
FIG. 2 is a flow chart of a wind energy resource simulation method shown in an exemplary embodiment of the application;
FIG. 3 is a schematic diagram of turbulence matrix correction for a first sector, shown in accordance with an exemplary embodiment of the present application;
FIG. 4 is a schematic diagram of turbulence matrix correction for a second sector, shown in accordance with an exemplary embodiment of the present application;
FIG. 5 is a schematic view of a wind energy resource simulation device shown in accordance with an exemplary embodiment of the present application;
Fig. 6 is a schematic structural view of an electronic device according to an exemplary embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Before describing the embodiments of the present application, technical terms related to the embodiments of the present application will be described herein:
CFD, computational fluid dynamics (Computational Fluid Dynamics). Along with the increasingly perfect performance of CFD universal software, the application range is also continuously expanded, and the CFD universal software is also widely applied to the related fields of chemical industry, metallurgy, construction, environment and the like. Modern hydrodynamic research methods include three aspects, theoretical analysis, numerical calculation and experimental research. These methods are studied for different angles, complementary to each other. The theoretical analysis research can express the parameter influence form, and provides effective guidance for numerical calculation and experimental research; the test is an effective means for understanding objective reality, and verifies the correctness of theoretical analysis and numerical calculation; computational fluid dynamics complements the theoretical and experimental vacancies by providing an economical means of simulating true flow.
Turbulence, which often occurs in analytical reports such as fan gearbox damage, blade cracking, foundation cracking, and substandard power generation, is within the wind power industry. Turbulence, also known as turbulence, refers to the non-uniform flow of fluid. Turbulence is generated mainly for two reasons, one is that the air flow is rubbed or retarded by the roughness of the floor when flowing, and the other is that the air flow moves vertically due to the difference in air density and the difference in atmospheric temperature. Generally, both of the above reasons tend to simultaneously cause turbulence to occur. The environmental turbulence of the anemometer tower is the turbulence intensity actually measured at the anemometer tower. The environmental turbulence at the machine location is calculated from the CFD orientation and corrected for the measured environmental turbulence at the anemometer tower, without being affected by the wake of other fans or obstacles.
IEC, the international electrotechnical commission (International Electrotechnical Commission), is mainly dedicated to the establishment of safety standards and technical studies of electronic and electrical products, and industry professionals in excess of 20000+ worldwide serve this organization. In the wind power field IECA, namely the turbulence level A, the high turbulence characteristic is designated; IECB, namely a turbulence level B, specifying medium turbulence characteristics; the IECC, i.e. turbulence class C, specifies low turbulence characteristics. The magnitude of the turbulence intensity not only affects the generated energy, but also affects the fatigue load of the unit.
In an embodiment of the present application, a wind energy resource simulation method is provided, alternatively, as an alternative implementation, the wind energy resource simulation method may be applied, but not limited to, in the environment as shown in fig. 1. FIG. 1 is a schematic diagram of an application environment of a wind energy resource simulation method according to an exemplary embodiment of the present application, referring to FIG. 1, a wind energy resource simulation terminal 101 may be, but is not limited to, a host computer, a desktop computer, a notebook computer, etc. having a local computing capability, the wind energy resource simulation terminal 101 may be, but is not limited to, in communication with a data acquisition terminal 102, a server 103 via a network, and the server 103 may be, but is not limited to, performing an operation on a database, such as a data writing operation or a data reading operation. The wind energy resource simulation terminal 101 may include, but is not limited to, a human-machine interaction screen, a processor, and a memory. The man-machine interaction screen described above may be used, but is not limited to, for displaying the results of wind energy resource simulations. The processor may be, but is not limited to, configured to perform a corresponding operation in response to the man-machine interaction operation, or generate a corresponding instruction, and send the generated instruction to the server 103. The memory is used for storing relevant stored data, such as wind energy resource simulation information and the like.
Alternatively, the data may be collected by the data collection terminal 102, for example, collecting and preprocessing wind speed data, average wind speed deviation data, of a plurality of wind direction sectors within a target wind farm.
As an alternative, the following steps in the wind energy resource simulation method may be performed on the wind energy resource simulation terminal 101:
acquiring wind speed data and average wind speed deviation data of a plurality of wind direction sectors in a target wind power field;
dividing wind speed data of each wind direction sector according to a preset wind speed interval to obtain a plurality of wind speed sections and the number of samples corresponding to each wind speed section, and constructing a first matrix according to the plurality of wind speed sections and the number of samples;
obtaining turbulence intensity according to the wind speed data and the average wind speed deviation data, and constructing a second matrix according to the wind speed sections and the turbulence intensity;
removing values which do not meet a preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix;
Transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module to perform numerical simulation on wind energy resources of the target wind farm area.
As an alternative, the server 103 may acquire wind energy resource simulation values transmitted by the wind energy resource simulation terminal 101 and then analyze them.
Based on the mode, the target turbulence matrix is generated in a standard mode, so that the generation rate of the target turbulence matrix is improved, and the problem of insufficient data accuracy caused by filling data by artificial experience is solved; in addition, the wind energy resources in the target wind power plant area are subjected to numerical simulation through the target turbulence matrix, so that the accuracy of wind flow simulation can be further improved, and the uncertainty of the wind energy resources in the target wind power plant area can be reduced.
Alternatively, in the present embodiment, the wind energy resource simulation terminal 101 may be a terminal device configured with a target client, and may include, but is not limited to, at least one of the following: notebook computers, tablet computers, palm computers, PADs, desktop computers, and the like. The target client may be a video client, instant messaging client, browser client, educational client, etc. that supports providing wind energy resource simulation applications. The network may include, but is not limited to: a wired network, a wireless network, wherein the wired network comprises: local area networks, metropolitan area networks, and wide area networks, the wireless network comprising: bluetooth, WIFI, and other networks that enable wireless communications. The server may be a single server, a server cluster composed of a plurality of servers, or a cloud server. The above is merely an example, and is not limited in any way in the present embodiment.
As an alternative example, the implementation subject of the wind energy resource simulation method is not limited, and some or all of the steps of the wind energy resource simulation method may be implemented on the wind energy resource simulation terminal 101, and may be implemented on a desktop computer, for example, in the case where the wind energy resource simulation terminal 101 is a desktop computer.
In one embodiment of the application, a wind energy resource simulation method is provided. FIG. 2 is a flow chart of a wind energy resource simulation method according to an exemplary embodiment of the application, see FIG. 2, comprising the steps as described in S210 to S250:
In step S210, wind speed data and average wind speed deviation data of a plurality of wind direction sectors in the target wind farm are acquired.
It should be noted that, the wind speed data obtained in the embodiment of the application is the wind speed time series data of 10 minutes interval measured by the whole year anemometer tower; the average wind speed deviation data are the average wind speed deviation time series data of 10 minute intervals measured by the whole year anemometer tower.
In step S220, according to a preset wind speed interval, wind speed data of each wind direction sector is divided to obtain a plurality of wind speed segments and the number of samples corresponding to each wind speed segment, and a first matrix is constructed according to the plurality of wind speed segments and the number of samples.
It should be noted that, in the embodiment of the present application, the first matrix is Occurrences matrices, that is, co-occurrence matrices. In Occurrences matrix, the wind speed section is represented by horizontal data, and the number of samples is represented by vertical data.
For example, the number of wind speed samples under 16 sectors is counted, and a plurality of wind speed segments under 16 sectors and the number of samples corresponding to each wind speed segment are obtained according to a wind speed interval of 1m/s, where the wind speed segments may be: v is more than or equal to 0m/s and less than 1m/s, V is more than or equal to 1m/s and less than or equal to 2m/s, V is more than or equal to 2m/s and less than or equal to 3m/s, and V is more than or equal to 3m/s and less than or equal to 4m/s.
In step S230, turbulence intensity is obtained according to the wind speed data and the average wind speed deviation data, and a second matrix is constructed according to the plurality of wind speed segments and the turbulence intensity.
The turbulence intensity (abbreviated as TI) refers to the random variation amplitude of the wind speed within 10 minutes, is the ratio of the standard deviation of the average wind speed within 10 minutes to the average wind speed in the same period, is the normal fatigue load born by the wind turbine generator during operation, and is important to the safety of the wind turbine. In the embodiment of the application, the second matrix is the TI matrix, the transverse data of the TI matrix is a wind speed section, and the longitudinal data of the TI matrix is the average turbulence intensity of the sector.
In step S240, values in the first matrix and the second matrix that do not satisfy the preset threshold range are removed, so as to obtain a reserved value, and matrix interpolation is performed on the second matrix according to the reserved value, so as to obtain a target turbulence matrix.
In step S250, the target turbulence matrix is transmitted to a preconfigured wind energy resource assessment module to numerically simulate wind energy resources of the target wind farm area.
By adopting the embodiment provided by the application, the target turbulence matrix is generated in a standard mode, so that the generation rate of the target turbulence matrix is improved, and the problem of insufficient data accuracy caused by filling data by artificial experience is avoided; in addition, the wind energy resources in the target wind power plant area are subjected to numerical simulation through the target turbulence matrix, so that the accuracy of wind flow simulation can be further improved, and the uncertainty of the wind energy resources in the target wind power plant area can be reduced.
In an embodiment of the present application, in the above wind energy resource simulation method, in step S250, the transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module to perform numerical simulation on the wind energy resource of the target wind farm area includes:
Transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module;
Obtaining topographic data, roughness data, a preset drawing area, preset wind measuring points and result points of the target wind farm area and wind measuring tower observation results;
obtaining a plurality of initial wind fields and wind field distribution of each initial wind field according to the topographic data, the roughness data, the preset drawing area, the preset wind measuring points and the result points;
Correcting the wind field distribution of the initial wind fields according to the target turbulence matrix to obtain wind field distribution of the target wind fields;
And obtaining wind energy parameters at the result points according to the plurality of target wind fields, wind field distribution of each target wind field and the observation result of the wind measuring tower so as to realize numerical simulation of wind energy resources of the target wind field area.
In the wind energy resource evaluation module, the wind field distribution of a plurality of initial wind fields and each initial wind field, namely, the directional calculation result is obtained by loading the topographic data, the roughness data, the preset drawing area, the preset wind measuring points and the result points and orienting according to the wind speed profile. And correcting the wind field distribution of the initial wind fields according to the target turbulence matrix to obtain the wind field distribution of the target wind fields. And finally, calculating wind energy parameters at a result point according to the statistical relationship between the observation result of the wind measuring tower and the directional calculation result at the same position in the calculation area, thereby obtaining the wind flow condition of the whole wind power plant.
In an embodiment of the present application, the wind energy resource simulation method, according to the wind speed data and the average wind speed deviation data, obtains turbulence intensity in step S230, includes:
according to the wind speed data, average wind speed data in a preset time interval is obtained;
and obtaining the turbulence intensity according to the ratio between the average wind speed data and the average wind speed deviation data.
Exemplary, the calculation formula of TI is
Wherein sigma i is the average wind speed deviation at the moment i, and the unit is m/s; u i is the average wind speed at time i in m/s.
In an embodiment of the present application, the wind energy resource simulation method further includes, before acquiring wind speed data and average wind speed deviation data of a plurality of wind direction sectors in the target wind farm in step S210:
Acquiring wind direction data in the target wind power field area;
And dividing the wind direction in the wind direction data into a plurality of wind direction sectors according to a preset wind direction division difference value.
Illustratively, according to the wind direction time sequence file of the measured 10 minute intervals of the N whole year anemometer towers, the wind direction is divided into 16 sectors according to the wind direction division difference value, and the 16 sectors are divided into the following table. Referring to table 1, table 1 shows wind direction division results of 16 sectors and wind direction expression relations of each sector, where D represents wind direction in ° for the wind direction division of 16 sectors.
TABLE 1 wind direction division for 16 sectors
In an embodiment of the present application, in the wind energy resource simulation method, removing values in the first matrix and the second matrix that do not satisfy a preset threshold range in step S240 to obtain a reserved value, and performing matrix interpolation on the second matrix according to the reserved value to obtain a target turbulence matrix, including:
Removing a wind speed section smaller than a preset sample quantity threshold value in the first matrix and the sample quantity corresponding to the wind speed section to obtain a first reserved value;
Removing a wind speed section smaller than the sample quantity threshold value in the second matrix and turbulence intensity corresponding to the wind speed section to obtain a second reserved value;
Obtaining a corresponding relation between the wind speed section and the turbulence intensity according to the first reserved value and the second reserved value;
if the average wind speed effective value of the target wind speed section in the second reserved value is smaller than a preset interpolation average wind speed effective value threshold value, interpolating turbulence intensity corresponding to a previous wind speed section of the target wind speed section into turbulence intensity of the target wind speed section to obtain the target turbulence matrix;
If the average wind speed effective value of the target wind speed section is larger than the interpolation average wind speed effective value threshold value, obtaining interpolation turbulence intensity corresponding to the target wind speed section according to the corresponding relation between the wind speed section and the turbulence intensity, and interpolating the second reserved value according to the target wind speed section and the interpolation turbulence intensity to obtain the target turbulence matrix.
For example, since there are partial sectors of sample data volume that are uneven and insufficient, and there are partial sectors of Occurrences matrix and TI matrix that are missing, interpolation is needed to interpolate the data. Traversing Occurrences the matrix and the TI matrix, deleting the corresponding values when the number of samples in the Occurrences matrix and the TI matrix is smaller than 10, reserving the effective values when the number of samples is larger than or equal to 10 and TI is not 0, and obtaining a first reserved value and a second reserved value. According to the wind speed distribution rule, the values of the high wind speed section with smaller data quantity and larger turbulence and the representativeness are low in the case of accidents, so the deletion process is generally performed.
It should be noted that, according to 2005 edition IEC61400-1, the normal turbulence model specified in the third edition is as follows:
σ1＝Iref(0.75×Vhub+b)
Wherein b=5.6 m/s, I ref is the reference wind speed.
Thus, the first and second substrates are bonded together,
Referring to Table 2, table 2 shows reference wind speeds for different turbulence levels specified by IEC.
TABLE 2 reference wind speeds for different turbulence classes
| IEC-A | IEC-B | IEC-C | IEC-S | |
| 0.16 | 0.14 | 0.12 | Custom |
As can be seen from Table 2, I ref is constant at different turbulence levels, and thus is specific to The ln functions on both sides are obtained, and the change shows that lnTi and lnV hub have a unitary linear function relationship.
And if the V hub effective value of the TI matrix is smaller than 3, the value of the TI matrix interpolated by the sector is the minimum value of the TI value corresponding to the previous wind speed section.
And if the effective value of V hub of the TI matrix is more than or equal to 3, obtaining the interpolation turbulence intensity corresponding to the target wind speed section according to the corresponding relation between the wind speed section and the turbulence intensity.
In an embodiment of the present application, the representation of the correspondence between the wind speed segment and the turbulence intensity includes:
lnTi＝klnVhub+m
wherein Ti is the turbulence intensity, V hub is the average wind speed of the wind speed section, k is the slope, and m is the intercept.
In one embodiment of the present application, the interpolation turbulence intensity is expressed by:
Wherein Ti' is the interpolation turbulence intensity, V hyb is the average wind speed of the wind speed section, k is the slope, and m is the intercept.
Illustratively, the TI is filled in the empty sector (column) and the wind speed (row) by using the representation mode of the interpolation turbulence intensity to obtain a target turbulence matrix. And storing the target turbulence matrix output by the method as a text file with the suffix of txt, and importing the text file into CFD mode software for comprehensive calculation.
In an embodiment of the present application, referring to fig. 3 and 4, fig. 3 is a schematic diagram of turbulence matrix correction of a first sector shown in an exemplary embodiment of the present application, and fig. 4 is a schematic diagram of turbulence matrix correction of a second sector shown in an exemplary embodiment of the present application. As can be seen from fig. 3 and 4, the wind field distribution of the initial wind fields and the wind field distribution of each initial wind field are corrected by the target turbulence matrix, so that the data accuracy is improved.
According to the embodiment, the target turbulence matrix is generated in a standard mode, so that the generation rate of the target turbulence matrix is improved, and the problem of insufficient data accuracy caused by filling data by artificial experience is avoided; in addition, the wind energy resources in the target wind power plant area are subjected to numerical simulation through the target turbulence matrix, so that the accuracy of wind flow simulation can be further improved, and the uncertainty of the wind energy resources in the target wind power plant area can be reduced.
In an embodiment of the application, a wind energy resource simulation device is also provided. FIG. 5 is a schematic view of a wind energy resource simulation device according to an exemplary embodiment of the application, see FIG. 5, comprising:
The data acquisition module 501 is configured to acquire wind speed data and average wind speed deviation data of a plurality of wind direction sectors in a target wind power field;
The first matrix construction module 502 is configured to divide wind speed data of each wind direction sector according to a preset wind speed interval, obtain a plurality of wind speed segments and a sample number corresponding to each wind speed segment, and construct a first matrix according to the plurality of wind speed segments and the sample number;
a second matrix construction module 503, configured to obtain turbulence intensity according to wind speed data and the average wind speed deviation data, and construct a second matrix according to the wind speed segments and the turbulence intensity;
The matrix interpolation module 504 is configured to remove values in the first matrix and the second matrix that do not satisfy a preset threshold range, obtain a reserved value, and perform matrix interpolation on the second matrix according to the reserved value, so as to obtain a target turbulence matrix;
The simulation module 505 is configured to transmit the target turbulence matrix to a preconfigured wind energy resource assessment module, so as to perform numerical simulation on the wind energy resource of the target wind farm area.
According to the wind energy resource simulation device, the target turbulence matrix is generated in a standard mode, so that the generation rate of the target turbulence matrix is improved, and the problem of insufficient data accuracy caused by filling data by artificial experience is solved; in addition, the wind energy resources in the target wind power plant area are subjected to numerical simulation through the target turbulence matrix, so that the accuracy of wind flow simulation can be further improved, and the uncertainty of the wind energy resources in the target wind power plant area can be reduced.
The specific embodiments of the wind energy resource simulation device according to the present application may refer to examples shown in the wind energy resource simulation method, and in this example, the description thereof will not be repeated here.
In an embodiment of the present application, an electronic device for implementing the wind energy resource simulation method is also provided. The electronic device comprises a memory in which a computer program is stored, and a processor arranged to execute the wind energy resource simulation method described above by means of the computer program
Referring to fig. 6, fig. 6 is a schematic structural view of an electronic device according to an exemplary embodiment of the present application. The computer system 600 includes a central processing unit (Central Processing Unit, CPU) 601 that can perform various appropriate actions and processes, such as performing the methods described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 602 or a program uploaded from a storage portion 608 into a random access Memory (Random Access Memory, RAM) 603. In the RAM 603, various programs and data required for system operation are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An Input/Output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a Liquid crystal display (Liquid CRYSTAL DISPLAY, LCD), and a speaker, etc.; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN (Local Area Network ) card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. When executed by a Central Processing Unit (CPU) 601, performs the various functions defined in the system of the present application.
It should be noted that, the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-Only Memory (ROM), an erasable programmable read-Only Memory (Erasable Programmable Read Only Memory, EPROM), a flash Memory, an optical fiber, a portable compact disc read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with a computer-readable computer program embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Where each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be provided in a processor. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
In another aspect, the application also provides a computer readable storage medium, which comprises a stored computer program, wherein the computer program executes the wind energy resource simulation method. The computer-readable storage medium may be included in the electronic device described in the above embodiment or may exist alone without being incorporated in the electronic device.
Another aspect of the application also provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the wind energy resource simulation method provided in the above embodiments.
The above embodiments are merely illustrative of the principles of the present invention and its effectiveness, and are not intended to limit the invention. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the invention. It is therefore intended that all equivalent modifications and changes made by those skilled in the art without departing from the spirit and technical spirit of the present invention shall be covered by the appended claims.
Claims (7)
1. A method of wind energy resource simulation, the method comprising:
acquiring wind speed data and average wind speed deviation data of a plurality of wind direction sectors in a target wind power field;
dividing wind speed data of each wind direction sector according to a preset wind speed interval to obtain a plurality of wind speed sections and the number of samples corresponding to each wind speed section, and constructing a first matrix according to the plurality of wind speed sections and the number of samples;
obtaining turbulence intensity according to the wind speed data and the average wind speed deviation data, and constructing a second matrix according to the wind speed sections and the turbulence intensity;
removing values which do not meet a preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix;
Transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module to perform numerical simulation on wind energy resources of the target wind power plant area;
Removing the values which do not meet the preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix, wherein the method comprises the following steps of:
Removing a wind speed section smaller than a preset sample quantity threshold value in the first matrix and the sample quantity corresponding to the wind speed section to obtain a first reserved value;
Removing a wind speed section smaller than the sample quantity threshold value in the second matrix and turbulence intensity corresponding to the wind speed section to obtain a second reserved value;
Obtaining a corresponding relation between the wind speed section and the turbulence intensity according to the first reserved value and the second reserved value;
if the average wind speed effective value of the target wind speed section in the second reserved value is smaller than a preset interpolation average wind speed effective value threshold value, interpolating turbulence intensity corresponding to a previous wind speed section of the target wind speed section into turbulence intensity of the target wind speed section to obtain the target turbulence matrix;
If the average wind speed effective value of the target wind speed section is larger than the interpolation average wind speed effective value threshold value, obtaining interpolation turbulence intensity corresponding to the target wind speed section according to the corresponding relation between the wind speed section and the turbulence intensity, and interpolating the second reserved value according to the target wind speed section and the interpolation turbulence intensity to obtain the target turbulence matrix;
the representation mode of the correspondence between the wind speed section and the turbulence intensity comprises the following steps:
lnTi＝klnVhub+m
Wherein Ti is the turbulence intensity, V hub is the average wind speed of the wind speed section, k is the slope, and m is the intercept;
The representation of the interpolated turbulence intensity includes:
Wherein Ti' is the interpolation turbulence intensity, V hub is the average wind speed of the wind speed section, k is the slope, and m is the intercept.
2. The wind energy resource simulation method of claim 1, wherein transmitting the target turbulence matrix to a preconfigured wind energy resource assessment module to numerically simulate wind energy resources of the target wind farm area comprises:
Transmitting the target turbulence matrix to a preconfigured wind energy resource evaluation module;
Obtaining topographic data, roughness data, a preset drawing area, preset wind measuring points and result points of the target wind farm area and wind measuring tower observation results;
obtaining a plurality of initial wind fields and wind field distribution of each initial wind field according to the topographic data, the roughness data, the preset drawing area, the preset wind measuring points and the result points;
Correcting the wind field distribution of the initial wind fields according to the target turbulence matrix to obtain wind field distribution of the target wind fields;
And obtaining wind energy parameters at the result points according to the plurality of target wind fields, wind field distribution of each target wind field and the observation result of the wind measuring tower so as to realize numerical simulation of wind energy resources of the target wind field area.
3. The wind energy resource simulation method according to claim 1, wherein deriving turbulence intensity from wind speed data and said average wind speed deviation data comprises:
according to the wind speed data, average wind speed data in a preset time interval is obtained;
and obtaining the turbulence intensity according to the ratio between the average wind speed data and the average wind speed deviation data.
4. The wind energy resource simulation method according to claim 1, further comprising, before acquiring the wind speed data and the average wind speed deviation data of the plurality of wind direction sectors in the target wind farm:
Acquiring wind direction data in the target wind power field area;
And dividing the wind direction in the wind direction data into a plurality of wind direction sectors according to a preset wind direction division difference value.
5. A wind energy resource simulation device, the device comprising:
The data acquisition module is used for acquiring wind speed data and average wind speed deviation data of a plurality of wind direction sectors in a target wind power field;
The first matrix construction module is used for dividing wind speed data of each wind direction sector according to a preset wind speed interval to obtain a plurality of wind speed sections and the number of samples corresponding to each wind speed section, and constructing a first matrix according to the plurality of wind speed sections and the number of samples;
the second matrix construction module is used for obtaining turbulence intensity according to the wind speed data and the average wind speed deviation data and constructing a second matrix according to the wind speed sections and the turbulence intensity;
the matrix interpolation module is used for removing the values which do not meet the preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix;
The simulation module is used for transmitting the target turbulence matrix to a pre-configured wind energy resource evaluation module so as to perform numerical simulation on wind energy resources of the target wind power plant area;
Removing the values which do not meet the preset threshold range in the first matrix and the second matrix to obtain reserved values, and performing matrix interpolation on the second matrix according to the reserved values to obtain a target turbulence matrix, wherein the method comprises the following steps of:
Removing a wind speed section smaller than a preset sample quantity threshold value in the first matrix and the sample quantity corresponding to the wind speed section to obtain a first reserved value;
Removing a wind speed section smaller than the sample quantity threshold value in the second matrix and turbulence intensity corresponding to the wind speed section to obtain a second reserved value;
Obtaining a corresponding relation between the wind speed section and the turbulence intensity according to the first reserved value and the second reserved value;
if the average wind speed effective value of the target wind speed section in the second reserved value is smaller than a preset interpolation average wind speed effective value threshold value, interpolating turbulence intensity corresponding to a previous wind speed section of the target wind speed section into turbulence intensity of the target wind speed section to obtain the target turbulence matrix;
If the average wind speed effective value of the target wind speed section is larger than the interpolation average wind speed effective value threshold value, obtaining interpolation turbulence intensity corresponding to the target wind speed section according to the corresponding relation between the wind speed section and the turbulence intensity, and interpolating the second reserved value according to the target wind speed section and the interpolation turbulence intensity to obtain the target turbulence matrix;
the representation mode of the correspondence between the wind speed section and the turbulence intensity comprises the following steps:
lnTi＝klnVhub+m
Wherein Ti is the turbulence intensity, V hub is the average wind speed of the wind speed section, k is the slope, and m is the intercept;
The representation of the interpolated turbulence intensity includes:
Wherein Ti' is the interpolation turbulence intensity, V hub is the average wind speed of the wind speed section, k is the slope, and m is the intercept.
6. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, performs the wind energy resource simulation method of any of the claims 1 to 4.
7. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the wind energy resource simulation method according to any of the claims 1 to 4 by means of the computer program.
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| CN111400852A (en) * | 2018-12-30 | 2020-07-10 | 北京金风科创风电设备有限公司 | Method and device for determining turbulence intensity parameters of wind power plant |
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| CN111400852A (en) * | 2018-12-30 | 2020-07-10 | 北京金风科创风电设备有限公司 | Method and device for determining turbulence intensity parameters of wind power plant |
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