CN116882811A - Wind energy resource evaluation method and device, computer equipment and storage medium - Google Patents
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Abstract
The invention relates to the technical field of new energy, and discloses a wind energy resource evaluation method, a device, computer equipment and a storage medium, wherein wind energy resource data are acquired, qualitative index evaluation is carried out on the wind energy resource data, and qualitative index confidence is generated; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results; carrying out quantitative index evaluation on the wind energy resource data to generate quantitative index scores; the quantitative indexes comprise a hub height average wind speed index, an average wind power density index, an effective wind time index, a wind shear index, a turbulence intensity index and a wind power density grade index; and acquiring quantitative index weights, and determining the total score of the wind energy resource based on the qualitative index confidence level, the quantitative index score and the quantitative index weights. The method carries out comprehensive quantitative evaluation on the rationality and feasibility of the wind energy resource, realizes multidimensional evaluation on the wind energy resource, and improves the evaluation efficiency and the evaluation accuracy of the wind energy resource.
Description
Technical Field
The invention relates to the technical field of new energy, in particular to a wind energy resource evaluation method, a device, computer equipment and a storage medium.
Background
Related works related to new energy technology research and economic evaluation are developed at home and abroad, including research on aspects of resources, site selection, power generation cost, engineering geology, project economic benefit and the like, and a certain theoretical basis and practical reference are provided for development of new energy power generation industry and development and evaluation of new energy grid-connected projects.
However, the related evaluation technology does not comprehensively and quantitatively analyze the aspects of wind energy resources, and further does not have research on development of an automatic, digital and accurate decision-making auxiliary system. A complete and scientific index evaluation system is lacking for wind energy resource evaluation, and is used for transverse comparison of different projects, so that a quantitative, comprehensive and clear evaluation result cannot be given.
Disclosure of Invention
In view of the above, the invention provides a wind energy resource evaluation method, a device, computer equipment and a storage medium, so as to solve the problem that a complete and scientific index evaluation system is lacking in wind energy resource evaluation.
In a first aspect, the present invention provides a method for evaluating wind energy resources, comprising:
acquiring wind energy resource data, performing qualitative index evaluation on the wind energy resource data, and generating qualitative index confidence; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results;
carrying out quantitative index evaluation on the wind energy resource data to generate quantitative index scores; the quantitative indexes comprise a hub height average wind speed index, an average wind power density index, an effective wind time index, a wind shear index, a turbulence intensity index and a wind power density grade index;
and acquiring quantitative index weights, and determining the total score of the wind energy resource based on the qualitative index confidence level, the quantitative index score and the quantitative index weights.
According to the wind energy resource evaluation method provided by the invention, the wind energy resource data are subjected to qualitative index evaluation and quantitative index evaluation respectively, and the rationality and feasibility of the wind energy resource are comprehensively and quantitatively evaluated, so that the multi-dimensional evaluation of the wind energy resource is realized, the evaluation efficiency and evaluation accuracy of the wind energy resource are improved, and a theoretical basis is provided for decision making of project investors.
In an alternative embodiment, the qualitative index assessment of the wind energy resource data generates a qualitative index confidence comprising:
performing reliability judgment on wind resource assessment results in wind energy resource data through the resource measurement parameters, and generating a reliability index value of the wind resource assessment results;
performing stability judgment on wind resource data in the wind energy resource data through the long-sequence resource characteristic data, the monthly resource data and the quarterly resource data to generate a wind resource stability index value;
and determining the qualitative index confidence level based on the wind resource assessment result reliability index value and the wind resource stability index value.
According to the wind energy resource evaluation method provided by the invention, the feasibility evaluation of wind energy resources is realized by carrying out qualitative index evaluation on wind energy resource data, and a basis is provided for project decision.
In an alternative embodiment, the quantitative index assessment of the wind energy resource data generates a quantitative index score comprising:
determining a hub height average wind speed index value based on a wind speed observation sequence in wind energy resource data and the number of wind speed sequences in a target period;
determining an average wind power density index value based on the monthly average air density in the wind energy resource data, the wind speed sequence and the number of the wind speed sequences in the target period;
determining an effective wind time index value based on the effective time of the wind speed of the fan in the target period in the wind energy resource data;
determining a wind shear index value at a high speed based on the current wind speed and the wind speed in the wind energy resource data;
determining a turbulence intensity index value based on the pulsatile wind speed value and the average wind speed value in the wind energy resource data;
comparing the annual effective wind power density, the annual accumulated time of wind speed and the annual average wind speed in the wind energy resource data with preset thresholds respectively, and determining a wind power density grade index value;
respectively matching the hub height average wind speed index value, the average wind power density index value, the effective wind time index value, the wind shear index value, the turbulence intensity index value and the wind power density grade index value with a scoring rule database to generate a quantitative index score; the quantitative indicator scores include a hub altitude average wind speed indicator score, an average wind power density indicator score, an effective wind time index score, a wind shear index indicator score, a turbulence intensity indicator score, and a wind power density grade indicator score.
According to the wind energy resource evaluation method provided by the invention, the rationality evaluation of the wind energy resource is realized by carrying out quantitative index evaluation on the wind energy resource data, and a basis is provided for project decision.
In an alternative embodiment, the wind energy resource total score is determined based on the qualitative indicator confidence, the quantitative indicator score, and the quantitative indicator weight, and the wind energy resource total score is calculated as follows:
S＝C*∑(x 1 *w 1 +x 2 *w 2 +x 3 *w 3 +x 4 *w 4 +x 5 *w 5 +x 6 *w 6 )
wherein S represents the total score of the wind energy resource, C represents the confidence coefficient of the qualitative index, and x 1 Index score, w, representing hub altitude average wind speed 1 Indicating the weight of the index weight of the average wind speed of the hub height, x 2 Indicating the average wind power density index score, w 2 Indicating the weight of the average wind power density index, x 3 Index score indicating effective wind time, w 3 Indicating the index weight of effective wind time number, x 4 Index score, w, representing wind shear index 4 Indicating wind shear index weight, x 5 Indicating turbulence intensityMark score, w 5 Indicating the turbulence intensity index weight, x 6 Index score indicating wind power density level, w 6 Representing wind power density class indicator weights.
According to the wind energy resource evaluation method provided by the invention, the total score of the wind energy resource is determined based on the qualitative index confidence, the quantitative index score and the quantitative index weight, so that the wind energy resource evaluation process has more flexibility, and the accuracy of the wind energy resource evaluation result is improved.
In a second aspect, the present invention provides a wind energy resource assessment device comprising:
the first generation module is used for acquiring wind energy resource data, carrying out qualitative index evaluation on the wind energy resource data and generating qualitative index confidence coefficient; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results;
the second generation module is used for carrying out quantitative index evaluation on the wind energy resource data and generating quantitative index scores; the quantitative indexes comprise a hub height average wind speed index, an average wind power density index, an effective wind time index, a wind shear index, a turbulence intensity index and a wind power density grade index;
and the evaluation module is used for acquiring the quantitative index weight and determining the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score and the quantitative index weight.
In an alternative embodiment, the first generating module includes:
the first generation unit is used for judging the reliability of the wind resource assessment result in the wind energy resource data through the resource measurement and calculation parameters and generating a reliability index value of the wind resource assessment result;
the second generation unit is used for judging the stability of wind resource data in the wind energy resource data through the long-sequence resource characteristic data, the monthly resource data and the quarterly resource data, and generating a wind resource stability index value;
and the third generation unit is used for determining the qualitative index confidence level based on the wind resource assessment result reliability index value and the wind resource stability index value.
In an alternative embodiment, the second generating module includes:
the first determining unit is used for determining a hub height average wind speed index value based on a wind speed observation sequence in wind energy resource data and the number of wind speed sequences in a target period;
the second determining unit is used for determining an average wind power density index value based on the monthly average air density in the wind energy resource data, the wind speed sequence and the number of the wind speed sequences in the target period;
the third determining unit is used for determining an effective wind time index value based on the effective time of the wind speed of the fan in the target period of the wind energy resource data;
a fourth determining unit for determining a wind shear index value at a high speed based on the current wind speed and the wind speed in the wind energy resource data;
a fifth determining unit for determining a turbulence intensity index value based on the pulsating wind speed value and the average wind speed value in the wind energy resource data;
the sixth determining unit is used for comparing the annual effective wind power density, the annual accumulated time of wind speed and the annual average wind speed in the wind energy resource data with preset thresholds respectively to determine a wind power density grade index value;
the matching unit is used for respectively matching the hub height average wind speed index value, the average wind power density index value, the effective wind time index value, the wind shear index value, the turbulence intensity index value and the wind power density grade index value with the scoring rule database to generate quantitative index scores; the quantitative indicator scores include a hub altitude average wind speed indicator score, an average wind power density indicator score, an effective wind time index score, a wind shear index indicator score, a turbulence intensity indicator score, and a wind power density grade indicator score.
In an alternative embodiment, the evaluation module is specifically configured to determine a total wind energy resource score based on the qualitative indicator confidence, the quantitative indicator score, and the quantitative indicator weight, where a calculation formula of the total wind energy resource score is as follows:
S＝C*∑(x 1 *w 1 +x 2 *w 2 +x 3 *w 3 +x 4 *w 4 +x 5 *w 5 +x 6 *w 6 )
wherein S represents the total score of the wind energy resource, C represents the confidence coefficient of the qualitative index, and x 1 Index score, w, representing hub altitude average wind speed 1 Indicating the weight of the index weight of the average wind speed of the hub height, x 2 Indicating the average wind power density index score, w 2 Indicating the weight of the average wind power density index, x 3 Index score indicating effective wind time, w 3 Indicating the index weight of effective wind time number, x 4 Index score, w, representing wind shear index 4 Indicating wind shear index weight, x 5 Indicating turbulence intensity index score, w 5 Indicating the turbulence intensity index weight, x 6 Index score indicating wind power density level, w 6 Representing wind power density class indicator weights.
In a third aspect, the present invention provides a computer device comprising: the wind energy resource evaluation system comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions so as to execute the wind energy resource evaluation method according to the first aspect or any implementation mode corresponding to the first aspect.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon computer instructions for causing a computer to perform a wind energy resource assessment method according to the first aspect or any of its corresponding embodiments.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for evaluating wind energy resources according to an embodiment of the invention;
FIG. 2 is a schematic view of a wind energy resource assessment system according to an embodiment of the present invention;
FIG. 3 is a flow chart of another method for automated decision-making aided management of new energy technology assessment according to an embodiment of the present invention;
FIG. 4 is a flow chart of an automated decision-making aid management method for another new energy technology assessment according to an embodiment of the present invention;
FIG. 5 is a block diagram of a wind energy resource assessment device according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the invention provides a wind energy resource evaluation method, which achieves the effect of multi-dimensional evaluation of wind energy resources by evaluating qualitative indexes and quantitative indexes of the wind energy resources.
According to an embodiment of the present invention, there is provided an embodiment of a method for evaluating a wind energy resource, it being noted that the steps shown in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and that although a logical sequence is shown in the flowchart, in some cases the steps shown or described may be performed in a different order than what is shown herein.
In this embodiment, a wind energy resource evaluation method is provided, which may be used in the above mobile terminal, such as a mobile phone, a tablet computer, etc., fig. 1 is a flowchart of a wind energy resource evaluation method according to an embodiment of the present invention, and as shown in fig. 1-2, the flowchart includes the following steps:
step S101, acquiring wind energy resource data, and performing qualitative index evaluation on the wind energy resource data to generate qualitative index confidence; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results.
Step S102, carrying out quantitative index evaluation on wind energy resource data to generate quantitative index scores; the quantitative indexes comprise a hub height average wind speed index, an average wind power density index, an effective wind time index, a wind shear index, a turbulence intensity index and a wind power density grade index.
Step S103, obtaining quantitative index weight, and determining the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score and the quantitative index weight.
Specifically, the weight ratio is set according to the influence of each quantitative index on the investment benefit of the whole wind energy resource decision, and the weight sum of each quantitative index is 100%.
Further, the calculation formula of the total score of the wind energy resource is as follows:
S＝C*∑(x 1 *w 1 +x 2 *w 2 +x 3 *w 3 +x 4 *w 4 +x 5 *w 5 +x 6 *w 6 ) (1)
wherein S represents the total score of the wind energy resource, C represents the confidence coefficient of the qualitative index, and x 1 Index score, w, representing hub altitude average wind speed 1 Indicating the weight of the index weight of the average wind speed of the hub height, x 2 Indicating the average wind power density index score, w 2 Indicating the weight of the average wind power density index, x 3 Index score indicating effective wind time, w 3 Indicating the index weight of effective wind time number, x 4 Index score, w, representing wind shear index 4 Indicating wind shear index weight, x 5 Indicating turbulence intensity index score, w 5 Indicating the turbulence intensity index weight, x 6 Representing wind power density classIndex scoring, w 6 Representing wind power density class indicator weights.
Further, the total score of the wind energy resource is 0-10 minutes; the total score of the wind energy resources is below 60 points (including the wind energy resources) and is 'poor', which indicates that the part of the evaluation does not suggest passing; the score between 60 and 85 (inclusive) is "good", which means that the part of the evaluation passes the condition after the correction and optimization; more than 85 "excellent" indicates that the portion passed the evaluation.
According to the wind energy resource evaluation method, the wind energy resource data are subjected to qualitative index evaluation and quantitative index evaluation respectively, the rationality and feasibility of the wind energy resource are comprehensively and quantitatively evaluated, the multi-dimensional evaluation of the wind energy resource is realized, the evaluation efficiency and evaluation accuracy of the wind energy resource are improved, theoretical basis is provided for project investors to make decisions, and the total score of the wind energy resource is determined based on the qualitative index confidence level, the quantitative index score and the quantitative index weight, so that the wind energy resource evaluation process has more flexibility, and the accuracy of wind energy resource evaluation results is improved.
In this embodiment, a wind energy resource evaluation method is provided, which may be used in the above mobile terminal, such as a mobile phone, a tablet computer, etc., and fig. 3 is a flowchart of a wind energy resource evaluation method according to an embodiment of the present invention, as shown in fig. 3, where the flowchart includes the following steps:
step S301, obtaining wind energy resource data, and carrying out qualitative index evaluation on the wind energy resource data to generate qualitative index confidence; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results.
Specifically, the step S301 includes:
step S3011, reliability judgment is carried out on wind resource assessment results in wind energy resource data through the resource measurement parameters, and reliability index values of the wind resource assessment results are generated.
Specifically, the resource measurement parameters include: observing positions (coordinates), site photos, elevations, anemometry time periods, surrounding topography and landforms, anemometer device configuration, anemometry heights and maintenance records; mesoscale data, peripheral built project operation data; the method comprises the steps of observing the integrity rate of data, unreasonable data and processing method of missing measurement data, wind speed and wind power before and after data interpolation and wind direction frequency; wind shear index, wind speed calculation method at hub height and result; the sensors at the same height measure data versus graphs (wind speed, wind direction, turbulence, etc.).
And step S3012, judging the stability of wind resource data in the wind energy resource data according to the long-sequence resource characteristic data, the monthly resource data and the quarterly resource data, and generating a wind resource stability index value.
Specifically, the long-sequence resource feature data and the month resource data comprise many years of meteorological element features and resource features; the annual change rule of wind speed and the characteristic value of meteorological elements; counting freezing days in low-temperature and high-humidity areas in winter and stopping actual operation of peripheral wind power plants; the time-by-time wind speed correlation of the anemometer tower and the simultaneous section weather station, and the wind speed annual change of the anemometer tower and the simultaneous section long sequence, and the wind direction frequency distribution rule are consistent; long sequence wind speed observations.
Step S3013, determining the qualitative index confidence level based on the wind resource assessment result reliability index value and the wind resource stability index value.
Specifically, a confidence is given based on a qualitative index, wherein the stability of the resource is judged mainly by long-sequence resource characteristic data, month and quarter resource data; the reliability of the evaluation result is mainly determined by data quality, algorithm, key parameters and the like adopted in the resource measuring and calculating process, and the reliability of the evaluation result is given by the comprehensive resource stability and the reliability of the evaluation conclusion.
According to the wind energy resource evaluation method provided by the invention, the feasibility evaluation of wind energy resources is realized by carrying out qualitative index evaluation on wind energy resource data, and a basis is provided for project decision.
Step S302, carrying out quantitative index evaluation on wind energy resource data to generate quantitative index scores; the quantitative indexes comprise a hub height average wind speed index, an average wind power density index, an effective wind time index, a wind shear index, a turbulence intensity index and a wind power density grade index. Please refer to step S102 in the embodiment shown in fig. 1 in detail, which is not described herein.
Step S303, obtaining quantitative index weight, and determining the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score and the quantitative index weight. Please refer to step S103 in the embodiment shown in fig. 1 in detail, which is not described herein.
In this embodiment, a wind energy resource evaluation method is provided, which may be used in the above mobile terminal, such as a mobile phone, a tablet computer, etc., and fig. 4 is a flowchart of a wind energy resource evaluation method according to an embodiment of the present invention, as shown in fig. 4, where the flowchart includes the following steps:
step S401, obtaining wind energy resource data, and performing qualitative index evaluation on the wind energy resource data to generate qualitative index confidence; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results. Please refer to step S301 in the embodiment shown in fig. 3 in detail, which is not described herein.
Step S402, quantitative index evaluation is carried out on wind energy resource data, and quantitative index scores are generated.
Specifically, the step S402 includes:
step S4021, determining a hub height average wind speed index value based on a wind speed observation sequence in wind energy resource data and the number of wind speed sequences in a target period.
Specifically, the calculation formula of the numerical value of the hub height average wind speed index is as follows:
wherein V is E Indicating the index value of the average wind speed of the hub height, V i The wind speed observation sequence is represented, and n represents the number of wind speed sequences (namely the number of wind speed sequences in a target period) in the average wind speed calculation period (year and month).
Step S3022, determining an average wind power density index value based on the monthly average air density in the wind energy resource data, the wind speed sequence, and the number of wind speed sequences within the target period.
Specifically, the calculation formula of the average wind power density index value is as follows:
wherein D is WP Indicating the average wind power density index value, n k,i The number of observation hours for the kth month, k for month, k=1, 2 k Represents the average air density of the kth month, v k,i Represents the kth month wind speed sequence.
Step S4023, determining an effective wind time index value based on the effective time of the wind speed of the fan in the target period in the wind energy resource data.
Specifically, the number of hours between the wind speed of the fan being higher than the cut-in wind speed and lower than the cut-out wind speed in the target period is counted, and then the effective time number is determined.
Step S3024, determining a wind shear index value based on the current wind speed and the wind speed in the wind energy resource data.
Specifically, the wind shear index represents the variation degree of wind speed along with the height, and the large value of the index represents that wind energy increases rapidly along with the height, and the wind speed gradient is large; the small value of the wind energy represents that the wind energy is slowly increased along with the height, and the wind speed gradient is small.
Further, the calculation formula of the wind shear index value is as follows:
wherein alpha represents the index value of wind shear index, Z 1 And Z 2 Representing wind speed height, V 2 Representing Z 2 Corresponding wind speed, V 1 Representing Z 1 Corresponding wind speeds.
Step S4025, determining a turbulence intensity index value based on the pulsating wind speed value and the average wind speed value in the wind energy resource data.
Specifically, the calculation formula of the turbulence intensity index value is as follows:
wherein I represents the turbulence intensity index value, u' represents the pulsating wind speed value (sampling interval is less than or equal to 3 s),representing the average wind speed value.
Step S4026, comparing the annual effective wind power density, the annual cumulative time of wind speed and the annual average wind speed in the wind energy resource data with preset thresholds respectively, and determining the index value of the wind power density grade.
Specifically, the effective wind power density in the current year is more than 200W/m 3 The annual cumulative hours of the wind speed (watt per cubic meter) of 3-20 m/s (meter per second) is more than 5000h (hours), and the annual average wind speed is more than 6m/s, so that the current wind power area in the wind power resource is a wind power resource rich area, and the wind power density grade index value is 4.
Further, the effective wind power density in the current year is 200-150W/m 3 The annual cumulative hours of the wind speed of 3-20 m/s is 5000-4000 h, and when the annual average wind speed is about 5.5m/s, the current wind power area in the wind power resource is a secondary rich area of the wind power resource, and the wind power density grade index value is 3.
Further, the effective wind power density in the current year is 150-100W/m 3 The annual cumulative hours of the wind speed of 3-20 m/s is 4000-2000 hours, and when the annual average wind speed is about 5m/s, the current wind power area in the wind power resource is a wind power resource available area, and the wind power density grade index value is 2.
Further, the effective wind power density in the current year is less than 100W/m 3 The annual cumulative hours of the wind speed of 3-20 m/s is less than 2000h, the annual average wind speed is 4.5m/s, the current wind power area in the wind energy resource is a wind energy resource depletion area, and the wind power density grade index value is 1.
Step S4027, respectively matching the hub height average wind speed index value, the average wind power density index value, the effective wind time index value, the wind shear index value, the turbulence intensity index value and the wind power density grade index value with a scoring rule database to generate quantitative index scores; the quantitative indicator scores include a hub altitude average wind speed indicator score, an average wind power density indicator score, an effective wind time index score, a wind shear index indicator score, a turbulence intensity indicator score, and a wind power density grade indicator score.
Specifically, based on the quantitative index values, quantitative scoring is carried out by adopting a 0-10 minute system, so as to obtain quantitative index scores.
According to the wind energy resource evaluation method provided by the invention, the rationality evaluation of the wind energy resource is realized by carrying out quantitative index evaluation on the wind energy resource data, and a basis is provided for project decision.
Step S403, obtaining quantitative index weight, and determining the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score and the quantitative index weight. Please refer to step S303 in the embodiment shown in fig. 3 in detail, which is not described herein.
The following describes the process of a wind energy resource assessment method by means of a specific embodiment.
Example 1:
the full life cycle evaluation process of the wind power project mainly comprises the evaluation of the current period approval wholesale text, the evaluation of the feasibility study report, the evaluation of the preliminary design report, the evaluation of EPC recruitment, the evaluation of equipment quality and the operation evaluation of the post-production project.
The main evaluation indexes of the wind energy resources in the feasibility study, the preliminary design evaluation and the operation evaluation of the post-production project are shown in the following table 1:
table 1:
the main quantitative index and unit definition are shown in the following table 2:
table 2:
| numbering device | Index name | Unit (B) |
| 1 | Hub altitude average wind speed | m/s |
| 2 | Average wind power density | W/m 2 |
| 4 | Number of effective wind hours | h |
| 5 | Wind shear index | -- |
| 6 | Turbulence intensity | -- |
| 8 | Wind power density rating | -- |
The review scheme was designed as follows:
(1) Quantitative index: based on the actual quantization index data of the project, 0-10 minutes are adopted for quantization scoring.
(2) Qualitative index: giving confidence coefficient based on the qualitative index, wherein the stability of the resource is judged mainly by long-sequence resource characteristic data, month and quarter resource data; the reliability of the evaluation result is mainly judged by data quality, algorithm, key parameters and the like adopted in the resource measuring and calculating process, and the reliability of the evaluation result is given by the comprehensive resource stability and the reliability of the evaluation conclusion;
and setting a weight ratio (confidence value sigma (scoring weight)) for the final scoring result corresponding to the part of the evaluation content according to the part indexes to the investment benefit influence of the whole project decision.
The total weight of each part is 100 percent, and the total score is 0-10 minutes. The system default total score 60 points (inclusive) is below "bad" indicating that the portion of the review does not suggest passing; the score between 60 and 85 (inclusive) is "good", which means that the part of the evaluation passes the condition after the correction and optimization; more than 85 "excellent" indicates that the portion passed the evaluation.
In this embodiment, a wind energy resource evaluation device is further provided, and the device is used to implement the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The present embodiment provides a wind energy resource evaluation device, as shown in fig. 5, including:
the first generation module 501 is configured to acquire wind energy resource data, perform qualitative index evaluation on the wind energy resource data, and generate a qualitative index confidence coefficient; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results;
the second generation module 502 is configured to perform quantitative index evaluation on the wind energy resource data, and generate a quantitative index score; the quantitative indexes comprise a hub height average wind speed index, an average wind power density index, an effective wind time index, a wind shear index, a turbulence intensity index and a wind power density grade index;
an evaluation module 503 for obtaining a quantitative indicator weight, determining a total score of the wind energy resource based on the qualitative indicator confidence, the quantitative indicator score and the quantitative indicator weight.
In some alternative embodiments, the first generation module 501 includes:
the first generation unit is used for judging the reliability of the wind resource assessment result in the wind energy resource data through the resource measurement and calculation parameters and generating a reliability index value of the wind resource assessment result;
the second generation unit is used for judging the stability of wind resource data in the wind energy resource data through the long-sequence resource characteristic data, the monthly resource data and the quarterly resource data, and generating a wind resource stability index value;
and the third generation unit is used for determining the qualitative index confidence level based on the wind resource assessment result reliability index value and the wind resource stability index value.
In some alternative embodiments, the second generating module 502 includes:
the first determining unit is used for determining a hub height average wind speed index value based on a wind speed observation sequence in wind energy resource data and the number of wind speed sequences in a target period;
the second determining unit is used for determining an average wind power density index value based on the monthly average air density in the wind energy resource data, the wind speed sequence and the number of the wind speed sequences in the target period;
the third determining unit is used for determining an effective wind time index value based on the effective time of the wind speed of the fan in the target period of the wind energy resource data;
a fourth determining unit for determining a wind shear index value at a high speed based on the current wind speed and the wind speed in the wind energy resource data;
a fifth determining unit for determining a turbulence intensity index value based on the pulsating wind speed value and the average wind speed value in the wind energy resource data;
the sixth determining unit is used for comparing the annual effective wind power density, the annual accumulated time of wind speed and the annual average wind speed in the wind energy resource data with preset thresholds respectively to determine a wind power density grade index value;
the matching unit is used for respectively matching the hub height average wind speed index value, the average wind power density index value, the effective wind time index value, the wind shear index value, the turbulence intensity index value and the wind power density grade index value with the scoring rule database to generate quantitative index scores; the quantitative indicator scores include a hub altitude average wind speed indicator score, an average wind power density indicator score, an effective wind time index score, a wind shear index indicator score, a turbulence intensity indicator score, and a wind power density grade indicator score.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
One wind energy resource assessment device in this embodiment is in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit ) circuit, a processor and memory executing one or more software or fixed programs, and/or other devices that can provide the above functions.
The embodiment of the invention also provides computer equipment, which is provided with the wind energy resource evaluation device shown in the figure 5.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a computer device according to an alternative embodiment of the present invention, as shown in fig. 6, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 6.
The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform the methods shown in implementing the above embodiments.
The memory 20 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; the memory 20 may also comprise a combination of the above types of memories.
The computer device also includes a communication interface 30 for the computer device to communicate with other devices or communication networks.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1. A method for evaluating a wind energy resource, the method comprising:
acquiring wind energy resource data, performing qualitative index evaluation on the wind energy resource data, and generating qualitative index confidence; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results;
performing quantitative index evaluation on the wind energy resource data to generate quantitative index scores; the quantitative indexes comprise a hub height average wind speed index, an average wind power density index, an effective wind time index, a wind shear index, a turbulence intensity index and a wind power density grade index;
and acquiring quantitative index weight, and determining the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score and the quantitative index weight.
2. The method of claim 1, wherein said qualitatively evaluating the wind energy resource data to generate qualitative index confidence comprises:
performing reliability judgment on wind resource assessment results in the wind energy resource data through the resource measurement parameters to generate a reliability index value of the wind resource assessment results;
performing stability judgment on wind resource data in the wind energy resource data through long-sequence resource feature data, monthly resource data and quarterly resource data to generate a wind resource stability index value;
and determining the qualitative index confidence level based on the wind resource assessment result reliability index value and the wind resource stability index value.
3. The method of claim 1, wherein said performing a quantitative index assessment on said wind energy resource data generates a quantitative index score comprising:
determining a hub height average wind speed index value based on a wind speed observation sequence in the wind energy resource data and the number of wind speed sequences in a target period;
determining an average wind power density index value based on the monthly average air density in the wind energy resource data, the wind speed sequence and the number of the wind speed sequences in the target period;
determining an effective wind time index value based on the effective time of the wind speed of the fan in the target period in the wind energy resource data;
determining a wind shear index value at a high speed based on the current wind speed and the wind speed in the wind energy resource data;
determining a turbulence intensity index value based on the pulsating wind speed value and the average wind speed value in the wind energy resource data;
comparing the annual effective wind power density, the annual accumulated time of wind speed and the annual average wind speed in the wind energy resource data with preset thresholds respectively to determine a wind power density grade index value;
respectively matching the hub height average wind speed index value, the average wind power density index value, the effective wind time index value, the wind shear index value, the turbulence intensity index value and the wind power density grade index value with a scoring rule database to generate the quantitative index score; the quantitative index scores comprise a hub altitude average wind speed index score, an average wind power density index score, an effective wind time index score, a wind shear index score, a turbulence intensity index score and a wind power density grade index score.
4. A method according to claim 3, wherein the determination of a total wind energy resource score based on the qualitative indicator confidence, the quantitative indicator score and the quantitative indicator weight is performed by the following calculation formula:
S＝C*∑(x 1 *w 1 +x 2 *w 2 +x 3 *w 3 +x 4 *w 4 +x 5 *w 5 +x 6 *w 6 )
wherein S represents the total score of the wind energy resource, C represents the confidence coefficient of the qualitative index, and x 1 Index score, w, representing hub altitude average wind speed 1 Indicating the weight of the index weight of the average wind speed of the hub height, x 2 Indicating the average wind power density index score, w 2 Indicating the weight of the average wind power density index, x 3 Index score indicating effective wind time, w 3 Indicating the index weight of effective wind time number, x 4 Index score, w, representing wind shear index 4 Indicating wind shear index weight, x 5 Indicating strong turbulenceDegree index score, w 5 Indicating the turbulence intensity index weight, x 6 Index score indicating wind power density level, w 6 Representing wind power density class indicator weights.
5. A wind energy resource assessment device, the device comprising:
the first generation module is used for acquiring wind energy resource data, carrying out qualitative index evaluation on the wind energy resource data and generating qualitative index confidence coefficient; the qualitative indexes comprise reliability indexes and wind resource stability indexes of wind resource assessment results;
the second generation module is used for carrying out quantitative index evaluation on the wind energy resource data and generating quantitative index scores; the quantitative indexes comprise a hub height average wind speed index, an average wind power density index, an effective wind time index, a wind shear index, a turbulence intensity index and a wind power density grade index;
and the evaluation module is used for acquiring quantitative index weight and determining the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score and the quantitative index weight.
6. The apparatus of claim 5, wherein the first generation module comprises:
the first generation unit is used for judging the reliability of the wind resource assessment result in the wind energy resource data through the resource measurement and calculation parameters, and generating a reliability index value of the wind resource assessment result;
the second generation unit is used for judging the stability of wind resource data in the wind energy resource data through the long-sequence resource characteristic data, the monthly resource data and the quarterly resource data, and generating a wind resource stability index value;
and the third generation unit is used for determining the qualitative index confidence level based on the wind resource assessment result reliability index value and the wind resource stability index value.
7. The apparatus of claim 5, wherein the second generation module comprises:
the first determining unit is used for determining a hub height average wind speed index value based on a wind speed observation sequence in the wind energy resource data and the number of wind speed sequences in a target period;
the second determining unit is used for determining an average wind power density index value based on the monthly average air density in the wind energy resource data, the wind speed sequence and the number of the wind speed sequences in the target period;
a third determining unit, configured to determine an effective wind time index value based on an effective time of a wind speed of the wind turbine in the target period in the wind energy resource data;
a fourth determining unit for determining a wind shear index value at a high speed based on the current wind speed and the wind speed in the wind energy resource data;
a fifth determining unit for determining a turbulence intensity index value based on the pulsating wind speed value and the average wind speed value in the wind energy resource data;
a sixth determining unit, configured to compare the annual effective wind power density, the annual cumulative time count of wind speed and the annual average wind speed in the wind energy resource data with preset thresholds, respectively, and determine a wind power density class index value;
the matching unit is used for respectively matching the hub height average wind speed index value, the average wind power density index value, the effective wind time index value, the wind shear index value, the turbulence intensity index value and the wind power density grade index value with a scoring rule database to generate the quantitative index score; the quantitative index scores comprise a hub altitude average wind speed index score, an average wind power density index score, an effective wind time index score, a wind shear index score, a turbulence intensity index score and a wind power density grade index score.
8. The apparatus according to claim 5, wherein the evaluation module is configured to determine a total wind energy resource score based on the qualitative indicator confidence, the quantitative indicator score and the quantitative indicator weight, wherein the total wind energy resource score is calculated according to the following formula:
S＝C*∑(x 1 *w 1 +x 2 *w 2 +x 3 *w 3 +x 4 *w 4 +x 5 *w 5 +x 6 *w 6 )
wherein S represents the total score of the wind energy resource, C represents the confidence coefficient of the qualitative index, and x 1 Index score, w, representing hub altitude average wind speed 1 Indicating the weight of the index weight of the average wind speed of the hub height, x 2 Indicating the average wind power density index score, w 2 Indicating the weight of the average wind power density index, x 3 Index score indicating effective wind time, w 3 Indicating the index weight of effective wind time number, x 4 Index score, w, representing wind shear index 4 Indicating wind shear index weight, x 5 Indicating turbulence intensity index score, w 5 Indicating the turbulence intensity index weight, x 6 Index score indicating wind power density level, w 6 Representing wind power density class indicator weights.
9. A computer device, comprising:
a memory and a processor, said memory and said processor being communicatively connected to each other, said memory having stored therein computer instructions, said processor executing a method for evaluating a wind energy resource according to any of claims 1 to 4 by executing said computer instructions.
10. A computer readable storage medium having stored thereon computer instructions for causing a computer to perform a wind energy resource assessment method according to any of claims 1 to 4.
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