Wind energy resource evaluation method, device, computer equipment and storage medium

Abstract

This application relates to the field of new energy technologies, acquires wind energy resource data, conducts qualitative index evaluation on the wind energy resource data, generates qualitative index confidence levels, where the qualitative indices include a reliability index of the wind energy assessment result and a stability index of the wind energy resource, conducts quantitative index evaluation on the wind energy resource data, generates quantitative index scores, where the quantitative indices include a hub height average wind speed index, an average wind power density index, an effective wind hours index, a wind shear index, a turbulence intensity index, and a wind power density level index, acquires quantitative index weights, and determines a total score of the wind energy resource based on the qualitative index confidence levels, the quantitative index scores, and the quantitative index weights. This application discloses a wind energy resource evaluation method, apparatus, computer device, and storage medium, which integrally and quantitatively evaluate the rationality and feasibility of wind energy resources, realize multi-dimensional evaluation of wind energy resources, and improve the evaluation efficiency and accuracy of wind energy resources.

Description

Technical Field

[0001] The present application relates to the field of new energy technologies, and specifically to a method and apparatus for evaluating wind energy resources, a computer device, and a storage medium.

Background Art

[0002] At home and abroad, in order to provide a certain theoretical basis and practical reference for the development of the new energy power generation industry and the development and evaluation of new energy grid connection projects, research on new energy technologies including investigations of resources, location selection, power generation costs, construction geology, project economics, etc. and related work on economic evaluation have been somewhat advanced.

[0003] However, the related evaluation technology does not comprehensively and quantitatively analyze all aspects of wind energy resources, nor is there any research on the development of an automated, digital, and accurate decision-making support system. For wind energy evaluation, there is a lack of a complete and scientific index evaluation system for horizontal comparison of different projects, and it cannot provide quantitative, comprehensive, and clear evaluation results.

Summary of the Invention

Problems to be Solved by the Invention

[0004] In view of this, the present application provides a method and apparatus for evaluating wind energy resources, a computer device, and a storage medium to solve the problem that there is a lack of a complete and scientific index evaluation system for wind energy resource evaluation.

Means for Solving the Problems

[0005] According to a first aspect, the present application acquires wind energy resource data, performs qualitative index evaluation on the wind energy resource data, and generates a qualitative index confidence level, where the qualitative index includes a reliability index of the wind energy resource evaluation result and a stability index of the wind energy resource, and Perform a quantitative index evaluation on wind energy resource data to generate a quantitative index score. Here, the quantitative indexes include the hub height average wind speed index, the average wind power density index, the effective wind time number index, the wind shear index, the turbulence intensity index, and the wind power density level index. Obtain a quantitative index weight, and determine the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score, and the quantitative index weight. Provide a wind energy resource evaluation method including the above.

[0006] The wind energy resource evaluation method according to the present application performs qualitative index evaluation and quantitative index evaluation on wind energy resource data respectively, and realizes a multi-dimensional evaluation of the wind energy resource by comprehensively and quantitatively evaluating the rationality and feasibility of the wind energy resource, improving the evaluation efficiency and evaluation accuracy of the wind energy resource, and providing a theoretical basis for the decision-making of project investors.

[0007] In any embodiment, performing a qualitative index evaluation on wind energy resource data to generate a qualitative index confidence includes: Judging the reliability of the wind energy resource evaluation result in the wind energy resource data according to the resource measurement parameters, and generating a reliability index value of the wind energy resource evaluation result; Judging the stability of the wind energy resource data in the wind energy resource data according to the long-sequence resource feature data, monthly resource data, and quarterly resource data, and generating a stability index value of the wind energy resource; Determining the qualitative index confidence based on the reliability index value of the wind energy resource evaluation result and the stability index value of the wind energy resource.

[0008] The wind energy resource evaluation method according to the present application realizes the feasibility evaluation of the wind energy resource by performing qualitative index evaluation on the wind energy resource data, and provides a basis for the decision-making of the project.

[0009] In any embodiment, performing a quantitative index evaluation on wind energy resource data and generating a quantitative index score includes: 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 within a target time period; determining an average wind power density index value based on the monthly average air density, wind speed sequence in the wind energy resource data, and the number of wind speed sequences within the target time period; determining an effective wind energy hours index value based on the number of effective hours of the wind speed of the blower within the target time period in the wind energy resource data; determining a wind shear index value based on the current wind speed and the height of 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 each of the annual effective wind power density, the annual cumulative number of hours of wind speed, and the annual average wind speed in the wind energy resource data with a preset threshold value to determine a wind power density level index value; matching each of the hub height average wind speed index value, the average wind power density index value, the effective wind energy hours index value, the wind shear index value, the turbulence intensity index value, and the wind power density level index value with a scoring rule database to generate a quantitative index score including a hub height average wind speed index score, an average wind power density index score, an effective wind energy hours index score, a wind shear index score, a turbulence intensity index score, and a wind power density level index score.

[0010] The wind energy resource evaluation method according to the present application realizes a rationality evaluation of the wind energy resource by performing a quantitative index evaluation on the wind energy resource data, and provides a basis for project decision-making.

[0011] In any embodiment, based on the qualitative index confidence, the quantitative index score, and the quantitative index weight, the total score of the wind energy resource is determined, and the calculation formula for the total score of the wind energy resource is JPEG2025524269000002.jpg8168where S represents the total score of the wind energy resource, C represents the qualitative index confidence, x1 represents the hub height average wind speed index score, w1 represents the hub height average wind speed index weight, x2 represents the average wind power density index score, w2 represents the average wind power density index weight, x3 represents the effective wind hours index score, w3 represents the effective wind hours index weight, x4 represents the wind shear index score, w4 represents the wind shear index weight, x5 represents the turbulence intensity index score, w5 represents the turbulence intensity index weight, x6 represents the wind power density level index score, and w6 represents the wind power density level index weight.

[0012] The wind energy resource evaluation method according to the present application determines the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score, and the quantitative index weight, thereby making the wind energy resource evaluation process more flexible and improving the accuracy of the wind energy resource evaluation result.

[0013] According to a second aspect, the present application is for obtaining wind energy resource data and performing a qualitative index evaluation on the wind energy resource data to generate a qualitative index confidence, where the qualitative index includes a first generation module including a reliability index of the wind energy resource evaluation result and a stability index of the wind energy resource, and for performing a quantitative index evaluation on the wind energy resource data to generate a quantitative index score, where the quantitative index includes a second generation module including a hub height average wind speed index, an average wind power density index, an effective wind hours index, a wind shear index, a turbulence intensity index, and a wind power density level index, and An evaluation module for obtaining quantitative index weights and determining the total score of wind energy resources based on qualitative index confidence, quantitative index scores, and quantitative index weights, A wind energy resource evaluation device including is provided.

[0014] In any embodiment, the first generation module A first generation unit for performing a reliability judgment on the wind resource evaluation result in the wind energy resource data according to the resource measurement parameter and generating a reliability index value of the wind resource evaluation result, A second generation unit for performing a stability judgment on the wind resource data in the wind energy resource data according to the long sequence resource feature data, monthly resource data, and quarterly resource data and generating a stability index value of the wind resource, And a third generation unit for determining the qualitative index confidence based on the reliability index value of the wind resource evaluation result and the stability index value of the wind resource.

[0015] In any embodiment, the second generation module A first determination unit for determining a hub height average wind speed index value based on the wind speed observation sequence in the wind energy resource data and the number of wind speed sequences within the target time period, A second determination unit for determining an average wind power density index value based on the monthly average air density, wind speed sequence in the wind energy resource data, and the number of wind speed sequences within the target time period, A third determination unit for determining an effective wind power hour index value based on the effective number of hours of the wind speed of the blower within the target time period in the wind energy resource data, A fourth determination unit for determining a wind shear index value based on the current wind speed and the height of the wind speed in the wind energy resource data, A fifth determination 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 determination unit for comparing each of the annual effective wind power density, the annual cumulative number of hours of wind speed, and the annual average wind speed in the wind energy resource data with a preset threshold value to determine a wind power density level index numerical value, a matching unit for matching each of the hub height average wind speed index numerical value, the average wind power density index numerical value, the effective wind power hours index numerical value, the wind shear index numerical value, the turbulence intensity index numerical value, and the wind power density level index numerical value with a scoring rule database to generate a quantitative index score including a hub height average wind speed index score, an average wind power density index score, an effective wind power hours index score, a wind shear index score, a turbulence intensity index score, and a wind power density level index score.

[0016] In any embodiment, the evaluation module is specifically for determining the total score of the wind energy resource based on the qualitative index confidence level, the quantitative index score, and the quantitative index weight. The calculation formula for the total score of the wind energy resource is JPEG2025524269000003.jpg8168where S represents the total score of the wind energy resource, C represents the qualitative index confidence level, x1 represents the hub height average wind speed index score, w1 represents the hub height average wind speed index weight, x2 represents the average wind power density index score, w2 represents the average wind power density index weight, x3 represents the effective wind power hours index score, w3 represents the effective wind power hours index weight, x4 represents the wind shear index score, w4 represents the wind shear index weight, x5 represents the turbulence intensity index score, w5 represents the turbulence intensity index weight, x6 represents the wind power density level index score, and w6 represents the wind power density level index weight.

[0017] According to a third aspect, the present application provides a computer device including a memory and a processor, where the memory and the processor are communicably connected to each other, computer instructions are stored in the memory, and the processor executes the computer instructions to execute the wind energy resource evaluation method according to the first aspect or any corresponding embodiment thereof.

[0018] According to a fourth aspect, the present application provides a computer-readable storage medium storing computer instructions for causing a computer to execute the wind energy resource evaluation method according to the first aspect or any corresponding embodiment thereof.

[0019] Hereinafter, in order to more clearly explain the specific embodiments of the present application or the technical solutions in the prior art, the drawings necessary for the description of the specific embodiments or the prior art will be briefly described. The drawings in the following description are some embodiments of the present application, and it is obvious to those skilled in the art that other drawings can be obtained based on these drawings without creative effort.

Brief Description of the Drawings

[0020]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Modes for Carrying Out the Invention

[0021] In the following, in order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, while referring to the drawings in the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. It is obvious that the described embodiments are only some, rather than all, of the embodiments of the present application. According to the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the scope of the present application.

[0022] The embodiments of the present application provide a method for evaluating wind energy resources, which achieves the effect of multi-dimensional evaluation of wind energy resources by performing qualitative index evaluation and quantitative index evaluation on wind energy resources.

[0023] According to the embodiments of the present application, embodiments of the method for evaluating wind energy resources are provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in, for example, a computer system of a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described in a different order here can be executed.

[0024] In this embodiment, a method for evaluating wind energy resources used in the above-mentioned mobile terminals such as mobile phones and tablets is provided. FIG. 1 is a flowchart of the method for evaluating wind energy resources according to the embodiments of the present application. As shown in FIGS. 1 to 2, the flow includes: Obtaining wind energy resource data, performing qualitative index evaluation on the wind energy resource data, and generating a qualitative index confidence level. Here, the qualitative index includes S101 including a reliability index of the wind energy resource evaluation result and a stability index of the wind energy resource, and Performing quantitative index evaluation on the wind energy resource data and generating a quantitative index score. Here, the quantitative index includes S102 including a hub height average wind speed index, an average wind power density index, an effective wind time number index, a wind shear index, a turbulence intensity index, and a wind power density level index, and Obtain the quantitative index weights, and determine the total score of the wind energy resources based on the qualitative index confidence level, the quantitative index score, and the quantitative index weights, including S103.

[0025] Specifically, set the weight ratio based on the impact of each quantitative index on the overall investment return of the wind energy resource decision-making, and the sum of the weights of each quantitative index is 100%.

[0026] Optionally, the calculation formula for the total score of the wind energy resources is JPEG2025524269000004.jpg8150, and where S represents the total score of the wind energy resources, C represents the qualitative index confidence level, x1 represents the hub height average wind speed index score, w1 represents the hub height average wind speed index weight, x2 represents the average wind power density index score, w2 represents the average wind power density index weight, x3 represents the effective wind hours index score, w3 represents the effective wind hours index weight, x4 represents the wind shear index score, w4 represents the wind shear index weight, x5 represents the turbulence intensity index score, w5 represents the turbulence intensity index weight, x6 represents the wind power density level index score, and w6 represents the wind power density level index weight.

[0027] Optionally, the total score of the wind energy resources is divided into 0 - 10 levels. A total score of 60 points (inclusive) or less for the wind energy resources is considered "poor", indicating that this part of the evaluation fails. A score between 60 and 85 points (inclusive) is considered "good", indicating that this part of the evaluation conditionally passes after modification and optimization. A score of 85 points or more is considered "excellent", indicating that this part of the evaluation passes.

[0028] The wind energy resource evaluation method according to this embodiment respectively performs qualitative index evaluation and quantitative index evaluation on wind energy resource data, and realizes multi-dimensional evaluation of wind energy resources by integrally and quantitatively evaluating the rationality and feasibility of wind energy resources, improves the evaluation efficiency and evaluation accuracy of wind energy resources, provides a theoretical basis for the decision-making of project investors, and makes the wind energy resource evaluation process more flexible and improves the accuracy of the wind energy resource evaluation result by determining the total score of wind energy resources based on the qualitative index confidence, quantitative index score, and quantitative index weight.

[0029] In this embodiment, a wind energy resource evaluation method used for the above-mentioned mobile terminals such as mobile phones and tablets is provided. FIG. 3 is a flowchart of the wind energy resource evaluation method according to the embodiment of the present application. As shown in FIG. 3, the flow includes the following steps.

[0030] Step S301: Obtain wind energy resource data, perform qualitative index evaluation on the wind energy resource data, and generate a qualitative index confidence. Here, the qualitative index includes a reliability index of the wind energy resource evaluation result and a stability index of the wind energy resource.

[0031] Specifically, the above step S301 includes the following steps.

[0032] Step S3011: Perform a reliability judgment on the wind energy resource evaluation result in the wind energy resource data according to the resource measurement parameter, and generate a reliability index value of the wind energy resource evaluation result.

[0033] Specifically, the resource measurement parameters include the observation location (coordinates), on-site photos, elevation, wind measurement time zone, surrounding terrain, the composition of the wind measurement equipment and the wind measurement height, maintenance records, mesoscale data, operation data of projects constructed in the vicinity, the completeness rate of the observation data, the processing methods for unreasonable data and missing data, the wind speed and wind power before and after data interpolation, the wind direction frequency, the wind shear index, the wind speed estimation method and results at the hub height, and the measurement data comparison chart (wind speed, wind direction, turbulence, etc.) by different sensors at the same height.

[0034] Step S3012: Based on the long-sequence resource characteristic data, monthly resource data, and quarterly resource data, perform a stability judgment on the wind power resource data in the wind energy resource data, and generate the stability index value of the wind power resource.

[0035] Specifically, the long-sequence resource characteristic data and monthly resource data include the meteorological element characteristics, resource characteristics, annual and intra-year change laws of wind speed, meteorological element characteristic values, statistics of low temperatures in winter, the number of icing days in high-humidity regions, and the actual operation stop status of surrounding wind power plants, the correlation between the wind speed per hour at the meteorological observation station and the measurement tower in the same time zone, the annual change of the long-sequence wind speed at the measurement tower in the same time zone, the consistency with the wind direction frequency distribution law, and the observation data of the long-sequence wind speed.

[0036] Step S3013: Based on the reliability index value of the wind power resource evaluation result and the stability index value of the wind power resource, determine the confidence level of the qualitative index.

[0037] Specifically, the confidence level is given based on the qualitative index. Here, the resource stability mainly performs a stability judgment based on the long-sequence resource characteristic data, monthly and quarterly resource data. The reliability of the evaluation result is mainly judged by the data quality, algorithm, key parameters, etc. used in the resource measurement process. The reliability parameter is given by summarizing the resource stability and the reliability of the evaluation conclusion.

[0038] The method for evaluating wind energy resources according to the present application realizes the feasibility evaluation of wind energy resources by performing qualitative index evaluation on wind energy resource data, and provides a basis for project decision-making.

[0039] Step S302: Perform quantitative index evaluation on the wind energy resource data to generate a quantitative index score. Here, the quantitative indexes include hub height average wind speed index, average wind power density index, effective wind hour number index, wind shear index, turbulence intensity index, and wind power density level index. For details, refer to step S102 of the embodiment shown in FIG. 1, and the description here is omitted.

[0040] Step S303: Obtain the quantitative index weights, and determine the total score of the wind energy resources based on the qualitative index confidence, quantitative index score, and quantitative index weights. For details, refer to step S103 of the embodiment shown in FIG. 1, and the description here is omitted.

[0041] In this embodiment, a method for evaluating wind energy resources used in the above-mentioned mobile terminals such as mobile phones and tablets is provided. FIG. 4 is a flowchart of the method for evaluating wind energy resources according to an embodiment of the present application. As shown in FIG. 4, the flow includes the following steps.

[0042] Step S401: Obtain wind energy resource data, perform qualitative index evaluation on the wind energy resource data, and generate a qualitative index confidence. Here, the qualitative indexes include a reliability index of the wind energy resource evaluation result and a stability index of the wind energy resource. For details, refer to step S301 of the embodiment shown in FIG. 3, and the description here is omitted.

[0043] Step S402: Perform quantitative index evaluation on the wind energy resource data to generate a quantitative index score.

[0044] Specifically, step S402 includes the following steps.

[0045] Step S4021: Determine the hub height average wind speed index value based on the wind speed observation sequence in the wind energy resource data and the number of wind speed sequences within the target time period.

[0046] Specifically, the calculation formula for the hub height average wind speed index value is shown in JPEG2025524269000005.jpg16124, where E represents the hub height average wind speed index value, V i represents the wind speed observation sequence, and n represents the number of wind speed sequences within the average wind speed calculation time period (year, month) (i.e., the number of wind speed sequences within the target time period).

[0047] Step S4022: Determine the average wind power density index value based on the monthly average air density, wind speed sequence in the wind energy resource data, and the number of wind speed sequences within the target time period.

[0048] JPEG2025524269000006.jpg57170

[0049] Step S4023: Determine the effective wind power hours index value based on the effective hours of the wind speed of the blower within the target time period in the wind energy resource data.

[0050] Specifically, count the number of hours of the wind speed of the blower within the target time period that is higher than the cut-in wind speed and lower than the cut-out wind speed, and then determine the effective hours.

[0051] Step S4024: Determine the wind shear index value based on the current wind speed and the height of the wind speed in the wind energy resource data.

[0052] Specifically, the wind shear index indicates how much the wind speed changes with height. A large value indicates that the wind energy increases rapidly with height and the wind speed gradient is large, while a small value indicates that the wind energy increases slowly with height and the wind speed gradient is small.

[0053] JPEG2025524269000007.jpg45170

[0054] Step S4025: Determine the turbulence intensity index value based on the pulsating wind speed value and the average wind speed value in the wind energy resource data.

[0055] JPEG2025524269000008.jpg45170

[0056] Step S4026: Compare each of the annual effective wind power density, the annual cumulative number of hours of wind speed, and the annual average wind speed in the wind energy resource data with a preset threshold value to determine the wind power density level index value.

[0057] Specifically, when the annual effective wind power density is greater than 200 W / m 3 (watts per cubic meter), the annual cumulative number of hours of wind speed of 3 to 20 m / s (meters per second) is greater than 5000 h (hours), and the annual average wind speed is greater than 6 m / s, the current wind power generation area in the wind energy resource is an area rich in wind energy resources, and the wind power density level index value is 4.

[0058] Optionally, when the annual effective wind power density is 200 - 150 W / m 3 and the annual cumulative number of hours of wind speed of 3 to 20 m / s is 5000 h - 4000 h, and the annual average wind speed is about 5.5 m / s, the current wind power generation area in the wind energy resource is a second-class area rich in wind energy resources, and the wind power density level index value is 3.

[0059] As an option, the annual effective wind power density is 150 - 100 W / m 3 and the annual cumulative number of hours with wind speeds of 3 - 20 m / s is 4000 h - 2000 h. When the annual average wind speed is about 5 m / s, the current wind power generation areas in wind energy resources are areas where wind energy resources are available, and the wind power density level index numerical value is 2.

[0060] As an option, the annual effective wind power density is less than 100 W / m 3 and the annual cumulative number of hours with wind speeds of 3 - 20 m / s is less than 2000 h. When the annual average wind speed is 4.5 m / s, the current wind power generation areas in wind energy resources are areas with poor wind energy resources, and the wind power density level index numerical value is 1.

[0061] Step S4027: Match each of the hub height average wind speed index numerical value, average wind power density index numerical value, effective wind hour index numerical value, wind shear index numerical value, turbulence intensity index numerical value, and wind power density level index numerical value with the scoring rule database to generate a quantitative index score including the hub height average wind speed index score, average wind power density index score, effective wind hour index score, wind shear index score, turbulence intensity index score, and wind power density level index score.

[0062] Specifically, based on the above - mentioned each quantitative index numerical value, quantitative scoring is performed on a scale of 0 - 10 to obtain a quantitative index score.

[0063] The wind energy resource evaluation method according to the present application realizes a rationality evaluation of wind energy resources by performing a quantitative index evaluation on wind energy resource data, and provides a basis for project decision - making.

[0064] Step S403: Obtain the quantitative index weights, and determine the total score of the wind energy resources based on the qualitative index confidence, the quantitative index scores, and the quantitative index weights. For details, refer to Step S303 of the embodiment shown in FIG. 3, and the description here is omitted.

[0065] The following describes the process of the wind energy resource evaluation method through a specific embodiment.

[0066] Embodiment 1: The full life cycle evaluation process of a wind power project mainly includes the evaluation of the project's pre-approval documents, the feasibility study report evaluation, the preliminary design report evaluation, the EPC tender purchase evaluation, the equipment quality evaluation, and the operation evaluation of the project after production starts.

[0067] The main evaluation indicators of wind energy resources in the feasibility study, preliminary design evaluation, and operation evaluation of the project after production starts are shown in Table 1 below.

[0068] JPEG2025524269000009.jpg73170

[0069] The main quantitative indicators and their units are defined as shown in Table 2 below.

[0070] JPEG2025524269000010.jpg60170

[0071] The evaluation method is designed as follows.

[0072] (1) Quantitative indicators: Based on the actual quantitative indicator data of the project, perform quantitative scoring on a scale of 0 to 10.

[0073] (2) Qualitative indicators: Confidence levels are assigned based on qualitative indicators. Here, for resource stability, stability judgments are mainly made based on long-sequence resource characteristic data, monthly and quarterly resource data. The reliability of the evaluation results is mainly determined by the data quality, algorithms, key parameters, etc. used in the resource measurement process. By summarizing the resource stability and the reliability of the evaluation conclusions, reliability parameters are given. According to the influence of the indicators of each part on the overall investment return of the project's overall decision-making, weight ratios are set. (Confidence level * Σ(score * weight)) is the final score result corresponding to the evaluation content of this part.

[0074] The sum of the weights of each part is 100%, and the total score is on a scale of 0 to 10. The default total score of the system is that 60 points (inclusive) or less is "poor", indicating that the evaluation of this part fails; 60 to 85 points (inclusive) is "good", indicating that the evaluation of this part conditionally passes after modification and optimization; 85 points or more is "excellent", indicating that this part passes the evaluation.

[0075] In this embodiment, a wind energy resource evaluation device for realizing the above embodiments and any embodiments is further provided. For those already described, the description here is omitted. As follows, the term "module" may be a combination of software and / or hardware that realizes a predetermined function. The device described in the following embodiments is preferably realized by software, but may also be realized by hardware, or may be realized by a combination of software and hardware, and is assumed.

[0076] As shown in FIG. 5, this embodiment is for acquiring wind energy resource data, performing qualitative indicator evaluation on the wind energy resource data, and generating qualitative indicator confidence levels. Here, the qualitative indicators include a first generation module 501 that includes a reliability indicator of the wind energy resource evaluation result and a stability indicator of the wind energy resource, It is for performing a quantitative index evaluation on wind energy resource data and generating a quantitative index score. Here, the quantitative indexes include a second generation module 502 including a hub height average wind speed index, an average wind power density index, an effective wind time number index, a wind shear index, a turbulence intensity index, and a wind power density level index, an evaluation module 503 for obtaining a quantitative index weight and determining a total score of the wind energy resource based on the qualitative index confidence, the quantitative index score, and the quantitative index weight, and provides a wind energy resource evaluation device including the same.

[0077] In some optional embodiments, the first generation module 501 includes a first generation unit for performing a reliability judgment on the wind energy resource evaluation result in the wind energy resource data according to the resource measurement parameters and generating a reliability index value of the wind energy resource evaluation result, a second generation unit for performing a stability judgment on the wind energy resource data in the wind energy resource data according to the long sequence resource feature data, the monthly resource data, and the quarterly resource data and generating a stability index value of the wind energy resource, and a third generation unit for determining the qualitative index confidence based on the reliability index value of the wind energy resource evaluation result and the stability index value of the wind energy resource.

[0078] In some optional embodiments, the second generation module 502 includes a first determination unit for determining a hub height average wind speed index value based on the wind speed observation sequence in the wind energy resource data and the number of wind speed sequences in the target time period, a second determination unit for determining an average wind power density index value based on the monthly average air density, the wind speed sequence in the wind energy resource data, and the number of wind speed sequences in the target time period, a third determination unit for determining an effective wind time number index value based on the effective time number of the wind speed of the blower in the target time period in the wind energy resource data, A fourth determination unit for determining a wind shear index numerical value based on the current wind speed and the height of the wind speed in the wind energy resource data, A fifth determination unit for determining a turbulence intensity index numerical value based on the pulsating wind speed value and the average wind speed value in the wind energy resource data, A sixth determination unit for comparing each of the annual effective wind power density, the annual cumulative number of hours of wind speed, and the annual average wind speed in the wind energy resource data with a preset threshold value to determine a wind power density level index numerical value, A matching unit for matching each of the hub height average wind speed index numerical value, the average wind power density index numerical value, the effective wind power hour index numerical value, the wind shear index numerical value, the turbulence intensity index numerical value, and the wind power density level index numerical value with a scoring rule database to generate a quantitative index score including a hub height average wind speed index score, an average wind power density index score, an effective wind power hour index score, a wind shear index score, a turbulence intensity index score, and a wind power density level index score.

[0079] Since the further function descriptions of the above modules and units are the same as those in the corresponding embodiments, the description is omitted here.

[0080] The wind energy resource evaluation device in this embodiment appears in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0081] The embodiment of the present application further provides a computer device having the wind energy resource evaluation device shown in FIG. 5 above.

[0082] Referring to FIG. 6, FIG. 6 is a structural schematic diagram of a computer device according to any embodiment of the present application. As shown in FIG. 6, the computer device includes one or more processors 10, a memory 20, and a member connection interface including a high-speed interface and a low-speed interface. Each member is communicatively connected via a different bus and may be implemented on a common motherboard or in other forms as needed. The processor can handle instructions stored in the memory or on the memory and executed within a computer device that includes instructions for displaying graphic information of the GUI on an external input / output device (for example, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses and multiple memories can be used together with multiple memories. Similarly, multiple computer devices can be connected and each device can provide a part of the required operations (for example, an array of servers, a set of blade servers, or a multiprocessor system). In FIG. 6, one processor 10 is taken as an example.

[0083] The processor 10 may be a central processing unit, a network processor, or a combination thereof. Here, the processor 10 may further include a hardware chip. 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.

[0084] Here, the memory 20 stores instructions executable by the at least one processor 10 such that the at least one processor 10 executes the method shown in the above embodiments.

[0085] The memory 20 may include a program storage area capable of storing an operating system and application programs necessary for at least one function, and a data storage area capable of storing data constructed according to the use of the computer device. Further, the memory 20 may include a high-speed random access memory, and may include non-volatile memories such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some optional embodiments, the memory 20 may include a memory provided remotely from the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local network, a mobile communication network, and combinations thereof.

[0086] The memory 20 may include a volatile memory such as a random access memory, the memory may include a non-volatile memory such as a flash memory, a hard disk, or a solid state disk, and the memory 20 may include a combination of the above types of memories.

[0087] The computer device further includes a communication interface 30 for communicating with other devices or a communication network.

[0088] The embodiments of the present application further provide a computer-readable storage medium. The method according to the embodiments of the present application may be implemented in hardware or firmware, or may be implemented in a recordable manner on a storage medium, downloaded via a network, and originally stored in a remote storage medium or a non-transitory device-readable storage medium and stored in a local storage medium by computer code, and the method described herein may be processed by software stored in a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Here, the storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc. Optionally, the storage medium may further include a combination of the above types of memories. A computer, a processor, a microprocessor controller, or programmable hardware includes a storage component capable of storing or receiving software or computer code, and it should be understood that when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is realized.

[0089] As described above, the embodiments according to the present application have been described with reference to the drawings. However, those skilled in the art can make various modifications and changes without departing from the gist or scope of the present application, and all such modifications and changes are included within the scope limited by the appended claims.

Claims

1. Obtain wind energy resource data, conduct a qualitative index evaluation on the wind energy resource data, and generate a qualitative index confidence level. Here, the qualitative index includes a reliability index of the wind energy evaluation result and a stability index of the wind energy resource. Conduct a quantitative index evaluation on the wind energy resource data, and generate a quantitative index score. Here, the quantitative index includes a hub height average wind speed index, an average wind power density index, an effective wind time number index, a wind shear index, a turbulence intensity index, and a wind power density level index. Obtain a quantitative index weight, and determine the total score of the wind energy resource based on the qualitative index confidence level, the quantitative index score, and the quantitative index weight. A wind energy resource evaluation method, characterized by including the above.

2. Conducting a qualitative index evaluation on the wind energy resource data as described above and generating a qualitative index confidence level includes: Judging the reliability of the wind energy evaluation result in the wind energy resource data based on the resource measurement parameters, and generating a reliability index value of the wind energy evaluation result. Judging the stability of the wind energy resource data in the wind energy resource data based on the long-sequence resource feature data, monthly resource data, and quarterly resource data, and generating a stability index value of the wind energy resource. Determining the qualitative index confidence level based on the reliability index value of the wind energy evaluation result and the stability index value of the wind energy resource. The method according to claim 1, characterized by including the above.

3. Conducting a quantitative index evaluation on the wind energy resource data as described above and generating a quantitative index score includes: Determining the hub height average wind speed index value based on the wind speed observation sequence in the wind energy resource data and the number of wind speed sequences within the target time period. Determining the average wind power density index value based on the monthly average air density, wind speed sequence in the wind energy resource data, and the number of wind speed sequences within the target time period. Determining the effective wind time number index value based on the effective time number of the wind speed of the blower within the target time period in the wind energy resource data. Determining the wind shear index value based on the current wind speed and the height of 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 each of the annual effective wind power density, the annual cumulative number of hours of wind speed, and the annual average wind speed in the wind energy resource data with a preset threshold value to determine a wind power density level index value; Matching each of the hub height average wind speed index value, the average wind power density index value, the effective wind hour index value, the wind shear index value, the turbulence intensity index value, and the wind power density level index value with a scoring rule database to generate the quantitative index score including the hub height average wind speed index score, the average wind power density index score, the effective wind hour index score, the wind shear index score, the turbulence intensity index score, and the wind power density level index score; The method according to claim 1, characterized by including the above.

4. Based on the qualitative index confidence, the quantitative index score, and the quantitative index weight described above, determining the total score of the wind energy resource, and the calculation formula for the total score of the wind energy resource is However, S represents the total score of wind energy resources, C represents the qualitative index confidence level, and x １ represents the hub height average wind speed index score, and w １ represents the hub height average wind speed index weight, and x ２ represents the average wind power density index score, and w ２ represents the average wind power density index weight, and x ３ represents the effective wind hours index score, and w ３ represents the effective wind hours index weight, and x ４ represents the wind shear index score, and w ４ represents the wind shear index weight, and x ５ represents the turbulence intensity index score, and w ５ represents the turbulence intensity index weight, and x ６ represents the wind power density level index score, and w ６ represents the wind power density level index weight, characterized in that the method according to claim 3.

5. Obtaining wind energy resource data and performing a qualitative index evaluation on the wind energy resource data to generate a qualitative index confidence. Here, the qualitative index includes a first generation module including a reliability index of the wind resource evaluation result and a stability index of the wind resource; Performing a quantitative index evaluation on the wind energy resource data to generate a quantitative index score. Here, the quantitative index includes a second generation module including a hub height average wind speed index, an average wind power density index, an effective wind hour index, a wind shear index, a turbulence intensity index, and a wind power density level index; Obtaining a quantitative index weight and an evaluation module for determining the total score of the wind energy resource based on the qualitative index confidence, the quantitative index score, and the quantitative index weight; A wind energy resource evaluation device characterized by including the above.

6. The first generation module includes A first generation unit for performing a reliability judgment on the wind resource evaluation result in the wind energy resource data according to the resource measurement parameter and generating a reliability index value of the wind resource evaluation result; A second generation unit for performing stability judgment on the wind power resource data in the wind energy resource data and generating a stability index value of the wind power resource based on the long sequence resource characteristic data, monthly resource data, and quarterly resource data. A third generation unit for determining the qualitative index confidence based on the reliability index value of the wind power resource evaluation result and the stability index value of the wind power resource. The apparatus according to claim 5, characterized by including the above.

7. The second generation module includes: A first determination unit for determining a hub height average wind speed index value based on the wind speed observation sequence in the wind energy resource data and the number of wind speed sequences within a target time period. A second determination unit for determining an average wind power density index value based on the monthly average air density, wind speed sequence in the wind energy resource data, and the number of wind speed sequences within the target time period. A third determination unit for determining an effective wind power hour index value based on the effective number of hours of the wind speed of the blower within the target time period in the wind energy resource data. A fourth determination unit for determining a wind shear index value based on the current wind speed and the height of the wind speed in the wind energy resource data. A fifth determination 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 determination unit for comparing the annual effective wind power density, the annual cumulative number of hours 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 level index value. A matching unit for generating the quantitative index scores including the hub height average wind speed index score, the average wind power density index score, the effective wind power hour index score, the wind shear index score, the turbulence intensity index score, and the wind power density level index score by matching each of the hub height average wind speed index value, the average wind power density index value, the effective wind power hour index value, the wind shear index value, the turbulence intensity index value, and the wind power density level index value with a scoring rule database. The apparatus according to claim 5, characterized by including the above.

8. Specifically, the evaluation module is for determining the total score of the wind energy resources based on the qualitative index confidence, the quantitative index score, and the quantitative index weight. The calculation formula for the total score of the wind energy resources is However, S represents the total score of wind energy resources, C represents the qualitative index confidence level, and x １ represents the hub height average wind speed index score, and w １ represents the hub height average wind speed index weight, and x ２ represents the average wind power density index score, and w ２ represents the average wind power density index weight, and x ３ represents the effective wind hours index score, and w ３ represents the effective wind hours index weight, and x ４ represents the wind shear index score, and w ４ represents the wind shear index weight, and x ５ represents the turbulence intensity index score, and w ５ represents the turbulence intensity index weight, and x ６ represents the wind power density level index score, and w ６ represents the wind power density level index weight, characterized in that the device according to claim 5.

9. A computer device comprising a memory and a processor, the memory and the processor being communicably connected to each other, computer instructions being stored in the memory, and the processor executing the computer instructions to execute the wind energy resource evaluation method according to any one of claims 1 to 4.

10. A computer-readable storage medium storing computer instructions for causing a computer to execute the wind energy resource evaluation method according to any one of claims 1 to 4.

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