Method and system for synthesizing theoretical power curve of wind turbine generator
By preprocessing wind turbine data and synthesizing theoretical power curves, the problems of wind farm wind turbine calculation speed and accuracy are solved, and more efficient wind turbine theoretical power curve calculation is achieved to meet the needs of various equipment manufacturers and models.
Patent Information
- Application Number
- CN202410322633.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-03-20
- Publication Date
- 2025-09-23
Smart Images
Figure CN120688333A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of wind power generation, and in particular to a method and system for synthesizing theoretical power curves of wind turbines. Background Art
[0002] Wind turbine operators typically source their wind turbines from multiple wind turbine manufacturers. Mainstream domestic wind turbine manufacturers offer different technology approaches, including direct drive, semi-direct drive, and dual-fed (DFIG). They offer a wide variety of wind turbine PLC brands and models, and the definitions of wind turbine status information vary widely. Consequently, wind turbine manufacturers provide wind turbine operators with varying data point tables, often with varying data quality. Furthermore, wind resources may vary from turbine to turbine site, and potential differences arise from factors such as the wind energy utilization coefficient (Cp) of specific wind turbines, the measurement characteristics of wind speed and direction instruments from different brands, sensor installation errors, and the wind speed transfer function of the nacelle. Utilizing a unified theoretical power curve to calculate wind turbine power loss will result in certain deviations.
[0003] When analyzing wind farm wind turbine power loss over a preset time period (monthly, annual, and other time intervals), wind power operators face a series of constraints, including different wind turbine technology routes and characteristics among various wind turbine manufacturers, multiple models, various terrains, and actual turbine site characteristics. Therefore, the adaptability, speed, and accuracy of theoretical power curve calculation methods for actual wind farm wind turbines have always been one of their key optimization directions.
[0004] Existing wind farm wind turbine theoretical curve calculations either consume excessive hardware computing resources during the data processing process, or fail to consider certain scenarios (such as varying wind speed and direction instrument measurement characteristics, no power generation or constant power limit in certain wind speed ranges) and the corresponding processing strategies for these scenarios. This makes it difficult to meet the wind farm-level wind turbine theoretical power curve calculation needs under a series of restrictive conditions, including wind turbine technology routes from various complete machine manufacturers, multiple machine models, various terrains, actual machine site characteristics, and wind turbine configurations. Furthermore, if the theoretical power curve for a wind turbine at an actual wind farm site fails to generate power due to faults in certain wind speed ranges during this time period, or if certain wind speed ranges are constantly limited in power or pitch angle, the theoretical power curve may be incomplete or even non-existent. Consequently, the deviations in the non-grid-connected power generation losses and power-limited power generation losses calculated based on this theoretical power curve will increase, resulting in low calculation speed, adaptability, and accuracy of the theoretical power curves for each wind turbine in existing wind farms. Summary of the Invention
[0005] The present application provides a method and system for synthesizing theoretical power curves of wind turbines, so as to at least solve the technical problems of low calculation speed, adaptability and accuracy of theoretical power curves of wind turbines in existing wind farms.
[0006] The first embodiment of the present application provides a method for synthesizing a theoretical power curve of a wind turbine generator system, the method comprising:
[0007] Acquire wind turbine generator set data and a reference power data table of the wind turbine generator set at each moment within a preset time period, and preprocess the wind turbine generator set data;
[0008] Determine the wind frequency data of each wind speed interval according to the preprocessed wind turbine data, and generate a wind frequency data table of the wind turbine within the preset time period;
[0009] Determining actual power data corresponding to each wind speed interval based on the preprocessed wind turbine data, and generating a first actual power data table of the wind turbine within the preset time period;
[0010] Merging the wind frequency data table and the first actual power data table to generate a second actual power data table of the wind turbine generator within the preset time period;
[0011] The theoretical power curve of the wind turbine generator set within the preset time period is determined according to the second actual power data table of the wind turbine generator set within the preset time period and the reference power data table of the wind turbine generator set.
[0012] Preferably, the wind turbine generator set data includes: wind speed data and power generation data.
[0013] Furthermore, the pre-processing of the wind turbine data includes:
[0014] The wind turbine generator set data is sequentially subjected to abnormal data elimination and standardization processing.
[0015] Furthermore, determining the wind frequency data of each wind speed interval based on the pre-processed wind turbine data and generating a wind frequency data table of the wind turbines within the preset time period includes:
[0016] Determining a maximum wind speed and a minimum wind speed based on the wind speed data, and constructing a wind speed range;
[0017] Dividing the wind speed range into a plurality of wind speed intervals according to a preset wind speed interval;
[0018] Determine the accumulated time difference corresponding to each wind speed interval, and determine the wind frequency data of each wind speed interval based on the accumulated time difference corresponding to each wind speed interval;
[0019] Generate a wind frequency data table of the wind turbine generator system within the preset time period based on the wind frequency data of each wind speed interval;
[0020] The wind frequency data table includes: wind farm number, wind turbine number, wind speed range, and wind frequency data.
[0021] Furthermore, determining the actual power data corresponding to each wind speed interval based on the pre-processed wind turbine data and generating a first actual power data table of the wind turbines within the preset time period includes:
[0022] Determine the corresponding average power generation value of each wind speed interval according to the power generation data;
[0023] Using the corresponding average power generation value of the wind speed interval as the corresponding actual power data of each wind speed interval;
[0024] Generating a first actual power data table of the wind turbine generator system within the preset time period based on the actual power data corresponding to each wind speed interval;
[0025] The first actual power data table includes: wind farm number, wind turbine number, wind speed range, and actual power data.
[0026] Furthermore, the second actual power data table includes: wind farm number, wind turbine number, wind speed range, wind frequency data, and actual power data;
[0027] The reference power data table includes: wind farm number, wind turbine number, wind speed range, and reference power data.
[0028] Furthermore, determining the theoretical power curve of the wind turbine generator set within the preset period according to the second actual power data table of the wind turbine generator set within the preset period and the reference power data table of the wind turbine generator set includes:
[0029] Merging the second actual power data table of the wind turbine generator set within the preset time period and the reference power data table of the wind turbine generator set to generate an initial theoretical power table of the wind turbine generator set within the preset time period;
[0030] Using the actual power data in the second actual power data table as the theoretical power data in the initial theoretical power table;
[0031] Screening out data rows in the initial theoretical power table where actual power data is missing, and determining theoretical power data corresponding to the data rows based on wind speed interval data of the data rows, a preset first interpolation table and a preset second interpolation table;
[0032] Inserting the theoretical power data corresponding to the data row into the initial theoretical power table to obtain a revised theoretical power table of the wind turbine generator within the preset time period;
[0033] Drawing a theoretical power curve of the wind turbine generator set within the preset time period based on the revised theoretical power table;
[0034] The theoretical power table includes: wind farm number, wind turbine number, wind speed range, actual power data, theoretical power data and reference power data.
[0035] Furthermore, the method further comprises:
[0036] Determine whether the maximum value in the theoretical power curve is greater than a preset upper limit coefficient. If so, generate a power overlimit warning log and record it.
[0037] The second embodiment of the present application provides a wind turbine theoretical power curve synthesis system, including:
[0038] an acquisition module, configured to acquire wind turbine generator set data and a reference power data table of the wind turbine generator set at each moment within a preset time period, and to pre-process the wind turbine generator set data;
[0039] A first determining module is configured to determine the wind frequency data of each wind speed interval based on the pre-processed wind turbine data, and generate a wind frequency data table of the wind turbines within the preset time period;
[0040] a second determining module, configured to determine actual power data corresponding to each wind speed interval based on the preprocessed wind turbine data, and generate a first actual power data table of the wind turbine within the preset time period;
[0041] a merging module, configured to merge the wind frequency data table and the first actual power data table to generate a second actual power data table of the wind turbine generator within the preset time period;
[0042] The third determining module is configured to determine a theoretical power curve of the wind turbine generator set within the preset period of time according to the second actual power data table of the wind turbine generator set within the preset period of time and the reference power data table of the wind turbine generator set.
[0043] A third aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect of the present application.
[0044] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:
[0045] The present application proposes a method and system for synthesizing a theoretical power curve of a wind turbine, wherein the method includes: obtaining wind turbine data at each moment within a preset time period and a reference power data table of the wind turbine, and preprocessing the wind turbine data; determining wind frequency data for each wind speed interval based on the preprocessed wind turbine data, and generating a wind frequency data table for the wind turbine within the preset time period; determining corresponding actual power data for each wind speed interval based on the preprocessed wind turbine data, and generating a first actual power data table for the wind turbine within the preset time period; merging the wind frequency data table and the first actual power data table to generate a second actual power data table for the wind turbine within the preset time period; and determining the theoretical power curve of the wind turbine within the preset time period based on the second actual power data table of the wind turbine within the preset time period and the reference power data table of the wind turbine. The technical solution proposed in the present application improves the adaptability, speed, and accuracy of calculating the theoretical power curve of the wind turbine.
[0046] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS
[0047] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:
[0048] Figure 1 This is a flow chart of a method for synthesizing a theoretical power curve of a wind turbine generator system according to one embodiment of the present application;
[0049] Figure 2 A schematic diagram of system parameter configuration according to one embodiment of the present application;
[0050] Figure 3 A schematic diagram of a theoretical curve generation process according to one embodiment of the present application;
[0051] Figure 4 This is a schematic diagram of a theoretical power curve of a wind turbine at an actual unit site in a wind farm 1 in October according to one embodiment of the present application;
[0052] Figure 5 This is a schematic diagram of a theoretical power curve of a wind turbine at an actual unit site 2 of a certain wind farm in October according to one embodiment of the present application;
[0053] Figure 6 This is a first structural diagram of a wind turbine theoretical power curve synthesis system provided according to one embodiment of the present application;
[0054] Figure 7This is a second structural diagram of a wind turbine theoretical power curve synthesis system provided according to an embodiment of the present application. DETAILED DESCRIPTION
[0055] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.
[0056] The present application proposes a method and system for synthesizing a theoretical power curve of a wind turbine, wherein the method includes: obtaining wind turbine data at each moment within a preset time period and a reference power data table of the wind turbine, and preprocessing the wind turbine data; determining wind frequency data for each wind speed interval based on the preprocessed wind turbine data, and generating a wind frequency data table for the wind turbine within the preset time period; determining corresponding actual power data for each wind speed interval based on the preprocessed wind turbine data, and generating a first actual power data table for the wind turbine within the preset time period; merging the wind frequency data table and the first actual power data table to generate a second actual power data table for the wind turbine within the preset time period; and determining the theoretical power curve of the wind turbine within the preset time period based on the second actual power data table of the wind turbine within the preset time period and the reference power data table of the wind turbine. The technical solution proposed in the present application improves the adaptability, speed, and accuracy of calculating the theoretical power curve of the wind turbine.
[0057] A method and system for synthesizing theoretical power curves of wind turbines according to an embodiment of the present application will be described below with reference to the accompanying drawings.
[0058] Example 1
[0059] Figure 1 This is a flow chart of a method for synthesizing a theoretical power curve of a wind turbine generator system according to one embodiment of the present application. Figure 1 As shown, the method includes:
[0060] Step 1: Obtain wind turbine generator set data at each moment within a preset time period and a reference power data table of the wind turbine generator set, and pre-process the wind turbine generator set data.
[0061] It should be noted that the wind turbine data includes wind speed data and power generation data.
[0062] In the embodiment of the present disclosure, the pre-processing of the wind turbine data includes:
[0063] The wind turbine generator set data is sequentially subjected to abnormal data elimination and standardization processing.
[0064] It should be noted that this method is implemented based on a data acquisition and monitoring control system, and before step 1, it also includes: configuration of system parameters, such as Figure 2 The specific process is as follows:
[0065] 201: Function parameter configuration mainly includes general parameters, including wind speed selection, wind direction selection, wind speed normalization enable, available sector screening enable, wind deviation screening enable, wind deviation threshold, power limit screening blade angle allowable error, etc. Among them, enable indicates that the function is enabled. For example, if wind speed normalization enable is equal to 1, it means that the wind speed normalization function is enabled; if wind speed normalization enable is equal to 0, it means that the wind speed normalization function is not enabled.
[0066] 202: Configure wind farm model parameters according to different equipment manufacturers and models, including wind farm model, cut-in speed, optimal blade angle, wind direction mode, available sector range, pre-variable pitch parameters, etc.
[0067] 203: Set reference curves corresponding to wind farm models based on different equipment manufacturers and models.
[0068] 204: Configure according to the specific information of each wind turbine in the wind farm, including the wind turbine number, model, rated power Pn, etc.
[0069] Step 2: determining the wind frequency data of each wind speed interval based on the pre-processed wind turbine data, and generating a wind frequency data table of the wind turbine within the preset time period.
[0070] In the embodiment of the present disclosure, step 2 specifically includes:
[0071] Step 2-1: determining a maximum wind speed and a minimum wind speed based on the wind speed data, and constructing a wind speed range;
[0072] Step 2-2: Divide the wind speed range into multiple wind speed intervals according to a preset wind speed interval;
[0073] Step 2-3: Determine the cumulative time difference corresponding to each wind speed interval, and determine the wind frequency data of each wind speed interval based on the cumulative time difference corresponding to each wind speed interval;
[0074] Step 2-4: generating a wind frequency data table of the wind turbine generator system within the preset time period based on the wind frequency data of each wind speed interval;
[0075] The wind frequency data table includes: wind farm number, wind turbine number, wind speed range, and wind frequency data.
[0076] In the embodiment of the present disclosure, the steps 1 and 2 specifically include:
[0077] 301: Obtain a time series data table S for a preset time period. The data point collection interval in S should be no longer than 10 minutes. The preset time period is typically a monthly or weekly interval. The time series data table S for this preset time period should include data points such as the wind farm number, wind turbine number, data timestamp, wind speed, wind direction, power, generator speed, blade angle, nacelle position, and wind turbine PLC status. Data points such as power limit status, power generation status, power curve marker, and air density, if any, are also read into the time series data table.
[0078] 302: 1) Eliminate abnormal data; 2) Since there are multiple data sources for data input, the data point names need to be standardized; 3) Select the wind speed source according to the wind speed selection parameter. The actual wind speed source used can be the wind speed of the wind turbine nacelle anemometer at the machine site, the wind speed of the wind measuring radar, and the wind speed of the wind tower near the machine site; 4) Select the wind direction source according to the wind direction selection parameter. The actual wind direction source used can be the wind direction measured by the wind vane in the nacelle of the wind turbine at the machine site, or the wind direction measured by the wind measuring radar; 5) To prevent possible time sequence confusion during the acquisition of time series data, sort S by timestamp to obtain S′; 6) Calculate the time difference of each data and store it in S′ for calculation of wind frequency and power generation based on time accumulation in subsequent steps.
[0079] 303: In the actual analysis of power generation operators, due to the differences in equipment manufacturers and models, data transmission and other limitations, some sites do not have wind turbine operating information such as power generation status and power limit status. Taking into account the adaptability of the wind turbine actual power curve calculation function to wind turbines at different sites and different machine locations, the optimal blade angle, cut-in speed, pre-pitch parameters and other parameter information in the actual machine location wind turbine configuration can be used to identify and extract new power generation marks and power limit marks from the time series data table without relying on wind turbine status information. Optionally, the power limit mark and the power limit status of the time series data table are synthesized (if not, the new mark is used directly). Finally, the power generation mark and power limit mark actually used are obtained.
[0080] 304: Determine whether to perform wind speed normalization based on multiple conditions, including the wind speed normalization enable parameter, whether the time series data table S′ contains air density data, and whether the fan ambient temperature is available. Note: 1) Using wind speed normalization helps improve the accuracy of the theoretical power curve; 2) A simplified air density can be calculated using the ambient temperature; 3) If there is no air density data or ambient temperature data on site, the accuracy of the theoretical power curve based on unnormalized wind speed statistics will decrease.
[0081] 305: If wind speed normalization is enabled, the wind speed in the time series data table S′ is calculated according to the following formula and stored in S′.
[0082]
[0083] Among them, V is the measured wind speed, Vn is the converted wind speed, ρ is the air density, and ρ0 is the standard air density.
[0084] 306: For the wind speed in the time series data table S′ (differentiated according to whether the wind speed is normalized, using standardized wind speed or unstandardized wind speed), the wind speed is divided into several wind speed intervals according to the Bien method according to the specified wind speed interval (the wind speed interval in this article is 0.5 m / s).
[0085] 307: Classify each row of time series data in S' according to the divided wind speed intervals. Then sort the wind speed intervals from small to large, calculate the cumulative time difference of each wind speed interval, and then calculate the wind frequency based on the cumulative time difference. Among them, the cumulative time difference T(i) on the i-th wind speed interval (represented by W(i)) is calculated as follows:
[0086]
[0087] Among them, N u is the number of data in the current wind speed interval W(i), t i,j is the time difference of each row of data in the current wind speed interval W(i). The wind frequency F(i) in the i-th wind speed interval (represented by W(i)) is calculated as follows: T(i) is the cumulative total time (i.e., cumulative time difference) of the wind speed interval W(i), and N is the number of wind speed intervals;
[0088] 308: Wind frequency data is denoted as Twf.
[0089] Step 3: Determine the actual power data corresponding to each wind speed interval based on the pre-processed wind turbine data, and generate a first actual power data table of the wind turbine within the preset time period.
[0090] In the embodiment of the present disclosure, step 3 specifically includes:
[0091] Step 3-1: Determine the corresponding average power generation value of each wind speed interval according to the power generation data;
[0092] Step 3-2: using the average power generation value corresponding to the wind speed interval as the actual power data corresponding to each wind speed interval;
[0093] Step 3-3: generating a first actual power data table of the wind turbine generator system within the preset time period based on the actual power data corresponding to each wind speed interval;
[0094] The first actual power data table includes: wind farm number, wind turbine number, wind speed range, and actual power data.
[0095] It should be noted that 401: Due to the existence of multiple data sources, the time intervals between the time series data tables obtained in the preset time period may be 1s, 1min, 10min, etc., and they need to be aggregated into data with a fixed time interval (usually 10min). The new aggregated time series data table is denoted as S".
[0096] 402: According to the actual wind farm and turbine site constraints, the unnecessary data in S″ is eliminated through the actual generation mark, power limit mark, and optional available sector screening, wind deviation screening, power curve mark screening, etc., to obtain S flt .
[0097] 403: According to the Bien method, S flt Medium wind speeds (depending on whether wind speed standardization is performed, using standardized wind speed or unstandardized wind speed) are divided into multiple wind speed bin intervals according to the interval length (generally 0.5 m / s). The power mean in each wind speed interval is counted to obtain the wind speed power data table (denoted as Twp), which is the first actual power data table and also the actual power curve of the wind turbine.
[0098] Step 4: Merge the wind frequency data table and the first actual power data table to generate a second actual power data table of the wind turbine generator within the preset time period.
[0099] The second actual power data table includes: wind farm number, wind turbine number, wind speed range, wind frequency data, and actual power data.
[0100] It should be noted that 501: the wind speed range in the wind frequency is checked according to the preset boundaries (depending on the model, the general boundary is >0 and not more than 25m / s), and the values exceeding the boundaries are eliminated.
[0101] 502: According to the generation principle of Twp and Twf, {Twp wind speed interval}∈{Twf wind speed interval}.
[0102] 503: The main data extracted from Twf are wind farm number, wind turbine number, and wind speed range.
[0103] 506: Insert the current wind speed interval W(i) of Twf into Twp according to the corresponding wind farm number and wind turbine number. In the row of wind speed interval newly inserted into Twp, except for the wind farm number, wind turbine number and current wind speed interval W(i), the rest of the data is filled with empty data nan.
[0104] 507: After traversing all wind speed intervals of Twf and merging them, Twpnew, the second actual power data table, is formed.
[0105] Step 5: Determine a theoretical power curve of the wind turbine generator set within the preset time period according to the second actual power data table of the wind turbine generator set within the preset time period and the reference power data table of the wind turbine generator set.
[0106] It should be noted that the reference power data table includes: wind farm number, wind turbine number, wind speed range, and reference power data.
[0107] In the embodiment of the present disclosure, step 5 specifically includes:
[0108] Step 5-1: merging the second actual power data table of the wind turbine generator set within the preset time period and the reference power data table of the wind turbine generator set to generate an initial theoretical power table of the wind turbine generator set within the preset time period;
[0109] Step 5-2: using the actual power data in the second actual power data table as the theoretical power data in the initial theoretical power table;
[0110] Step 5-3: Filtering out data rows in the initial theoretical power table where actual power data is missing, and determining theoretical power data corresponding to the data rows based on the wind speed interval data of the data rows, a preset first interpolation table, and a preset second interpolation table;
[0111] Step 5-4: inserting the theoretical power data corresponding to the data row into the initial theoretical power table to obtain a revised theoretical power table of the wind turbine generator within the preset time period;
[0112] Step 5-5: drawing a theoretical power curve of the wind turbine generator set within the preset time period based on the revised theoretical power table;
[0113] The theoretical power table includes: wind farm number, wind turbine number, wind speed range, actual power data, theoretical power data and reference power data.
[0114] It should be noted that the detailed implementation process of step 5 can be as follows Figure 3 As shown, Figure 3 The main steps are as follows: The actual power curves of specific wind turbines at different locations within the same wind farm may lead or lag the reference curve, and the actual full-power outputs of the two may also differ. Therefore, for functional versatility, the secondary synthesis primarily uses interpolation predictions based on the actual power curve, while interpolation predictions based on the reference curve are used as an auxiliary judgment. The main interpolation tables used are Tinpd, the preset first interpolation table, and Tinpc, the preset second interpolation table.
[0115] Taking the interpolation table Tinpd as an example, the wind speed range of Twpd [W d0 ,W dn] is the interpolation interval, and the reference power corresponding to the wind speed interval is [P d0 ,P dn ], where n+1 is the number of wind speed intervals of Twpd. d0 ,W dn ] is divided into n small segments, in each small segment [W di-1 ,W di ](i=1,2,…,n), the linear interpolation formula for this segment is:
[0116]
[0117] Select the interpolation segment according to the following:
[0118]
[0119] Where, Tinpd(x) is the interpolation value corresponding to wind speed x, P di is the power corresponding to the i-th wind speed interval in the reference power data table, P di-1 is the power corresponding to the i-1th wind speed interval in the reference power data table, W di is the wind speed corresponding to the i-th wind speed interval, W di-1 is the wind speed corresponding to the i-1th wind speed interval, W dj-1 is the wind speed corresponding to the j-1th wind speed interval, W dj is the wind speed corresponding to the j-th wind speed interval, W d0 is the wind speed corresponding to the first wind speed interval in the reference power data table, W dn is the wind speed corresponding to the nth wind speed interval in the reference power data table.
[0120] That is, if the interpolation point x does not exceed W d1 , use [W d0 ,W d1 ] Perform linear interpolation; if the interpolation point x exceeds W dn , use [W n-1 ,W n ] for linear interpolation; in other cases, linear interpolation is performed using the wind speed segment corresponding to x. For example, the interpolation interval of the reference wind speed interval is [3,14], and the interval interval is 0.5m / s. Then: 1) When the interpolation point input is 2.6m / s, the segment interval used for interpolation prediction power is [3,3.5]; 2) When the interpolation point input is 4.8m / s, the segment interval used for interpolation prediction power is [4.5,5]; 3) When the interpolation point input is 20m / s, the segment interval used for interpolation prediction power is [13.5,14];
[0121] The rules of the Tinpc table are similar to those of Tinpd.
[0122] Figure 3 In step 601: obtaining a reference power data table Twpd;
[0123] 602: Based on the wind speed intervals and power of the reference power data table Twpd, an interpolation table Tinpd, i.e., a preset first interpolation table, is formed; wherein, when the number of data in some wind speed intervals in Twp is small (generally, the number of data in the high wind speed interval N i It will affect the accuracy of the interpolation results and needs to be eliminated according to the quantity threshold conditions;
[0124] 603: 1) Check the curve smoothness of the power corresponding to the wind speed interval below the rated power * power coefficient in Twp, mark the abnormal data (denoted as Pwrtag), and update Pwrtag to Twp; 2) Filter the data based on the number of data in the Twp wind speed interval and the abnormal mark Pwrtag to obtain Twp_t, which is the first marked actual power data table;
[0125] 604: Based on the wind speed range Twp_t and the power, an interpolation table Tinpp is formed, i.e., the first actual power data table after marking abnormal values;
[0126] 605: Combine Twp_t and Twpd to obtain the actual power and design power synthesis table Twpd_t. This table combines the actual power curve and the design curve of the secondary screening and is mainly used for the interpolation calculation of the theoretical power curve.
[0127] 606: Obtain power data Pnew through interpolation according to the interpolation table Tinpp, and update Twpd_t;
[0128] 607: Update the maximum value of Pnew in Twpd_t;
[0129] 608: Generate an interpolation table Tinpc based on the wind speed Twpd_t and Pnew;
[0130] 609: Read Twpnew, i.e., the second actual power data table;
[0131] 610: Determine whether the Twpnew wind speed range has been traversed. If so, proceed to 618; otherwise, proceed to 611.
[0132] 611: Get the current data row index i;
[0133] 612: Determine whether P(i) is empty or Pwrtag(i) is set. If so, proceed to 613; otherwise, proceed to 616.
[0134] 613: Determine whether P(i) is empty or Pwrtag(i) is set below the specified wind speed. If so, proceed to 614; otherwise, proceed to 615. The specified wind speed may be 6 m / s.
[0135] 614: Pcpd(i)=max(0,Tinpc(W(i)));
[0136] 615: Pcpd(i)=max(0, max(Tinpd(W(i)), Tinpc(W(i)));
[0137] 616: Pcpd(i)=P(i);
[0138] 618: theoretical power curve check;
[0139] 619: End.
[0140] It should be noted that in steps 604-608, when performing interpolation predictions based on the actual power curve, the fact that the wind turbine may not be generating full power in all wind speed ranges during the preset time period is taken into account. Under this factor, the interpolation table established based on the actual power curve (Twp) before merging with the wind frequency will be incomplete. Therefore, it is necessary to introduce the complete wind speed range of the reference curve into the Tinpc establishment process. At the same time, it is necessary to update the maximum value of the predicted power in step 607 to form the interpolation table Tinpc.
[0141] 607: In some scenarios, the interpolation strategy may cause the predicted power Pnew(i) corresponding to some wind speed intervals W(i) in Twpd_t to exceed the maximum actual power or reference power. Therefore, it is necessary to check the maximum value of Pnew(i). Check Pnew(i) corresponding to each wind speed interval W(i) and determine whether to update Pnew(i). The update rules are as follows:
[0142] If (actual power curve maximum value > reference curve maximum value):
[0143] If (predicted power Pnew(i)>actual power curve maximum):
[0144] Pnew(i) = maximum value of the international power curve
[0145] Else:
[0146] If (predicted power Pnew(i)>reference curve maximum):
[0147] Pnew(i) = maximum value of the reference curve
[0148] 612-616: Pcpd(i) and P(i) are the theoretical and actual power values corresponding to wind speed interval W(i). Tinpd(W(i)) and Tinpc(W(i)) are the predicted power values from the design curve and the predicted power values from the composite curve, respectively, obtained by interpolation from wind speed interval W(i).
[0149] 618: Extract the data columns such as wind speed range and theoretical power value from Twpnew to obtain the theoretical power curve data table T_theory. Then perform a curve smoothness check on the power corresponding to the wind speed segments below the specified wind speed range, remove outliers, and update T_theory to obtain the final synthesized theoretical power curve.
[0150] like Figure 4 The figure below shows the theoretical power curve of a wind turbine at the actual unit site in a wind farm in October. Figure 5 This is the theoretical power curve of the wind turbine at the actual unit site 2 of a wind farm in October.
[0151] It should be noted that other data prediction methods such as linear regression may also be used to determine the theoretical power curve of the wind turbine generator set within the preset time period involved in step 5.
[0152] In an embodiment of the present disclosure, the method further includes:
[0153] Determine whether the maximum value in the theoretical power curve is greater than a preset upper limit coefficient. If so, generate a power overlimit warning log and record it.
[0154] The preset upper limit coefficient is equal to Pn*Pn, where Pn is the rated power of the wind turbine generator set.
[0155] In an embodiment of the present disclosure, the method further includes: storing a theoretical power curve of the wind turbine generator set within the preset time period.
[0156] The technical solution provided by the present invention can a) improve the adaptability, speed and accuracy of the calculation method of the theoretical power curve of wind turbines in wind farms based on the synthesis process of theoretical power curves of actual power curves, wind frequency and reference curves. b) adapt to the requirements of wind turbines of different models and actual machine sites in wind farms by adapting the parameter configuration method of the synthesis process of theoretical power curves of wind turbines in wind farms. c) improve the adaptability and accuracy of calculation methods such as wind frequency, actual power curve and theoretical power curve by using data acquisition and wind frequency statistics methods. d) The calculation method of the actual power curve of wind turbines can quickly obtain calculation results, and the data aggregation step helps to reduce computing resource consumption and unify the data scale of wind turbines in different wind farms. e) Strategies such as the introduction of reference curves of wind turbines in wind farms, the primary synthesis of wind frequency and actual power curves, and the secondary synthesis of reference curves and primary synthesis results can help solve the problem of difficulty in calculating theoretical power curves in some scenarios and improve the adaptability and accuracy of the results. f) Synthetic curve boundary checking can help check the validity of the process.
[0157] In summary, the method for synthesizing the theoretical power curve of a wind turbine generator set proposed in this embodiment improves the adaptability, speed, and accuracy of calculating the theoretical power curve of a wind turbine generator set.
[0158] Example 2
[0159] Figure 6 This is a structural diagram of a wind turbine theoretical power curve synthesis system provided according to one embodiment of the present application, such as Figure 6 As shown, the system includes:
[0160] An acquisition module 100 is configured to acquire wind turbine data and a reference power data table of the wind turbine at each moment within a preset time period, and to pre-process the wind turbine data;
[0161] A first determining module 200 is configured to determine wind frequency data of each wind speed interval based on the pre-processed wind turbine data, and generate a wind frequency data table of the wind turbines within the preset time period;
[0162] A second determining module 300 is configured to determine actual power data corresponding to each wind speed interval based on the pre-processed wind turbine data, and generate a first actual power data table of the wind turbine within the preset time period;
[0163] a merging module 400, configured to merge the wind frequency data table and the first actual power data table to generate a second actual power data table of the wind turbine generator within the preset time period;
[0164] The third determining module 500 is configured to determine a theoretical power curve of the wind turbine generator set within the preset period of time according to the second actual power data table of the wind turbine generator set within the preset period of time and the reference power data table of the wind turbine generator set.
[0165] The wind turbine generator set data includes wind speed data and power generation data.
[0166] It should be noted that the pre-processing of the wind turbine data includes:
[0167] The wind turbine generator set data is sequentially subjected to abnormal data elimination and standardization processing.
[0168] In the embodiment of the present disclosure, the first determining module 200 is further configured to:
[0169] Determining a maximum wind speed and a minimum wind speed based on the wind speed data, and constructing a wind speed range;
[0170] Dividing the wind speed range into a plurality of wind speed intervals according to a preset wind speed interval;
[0171] Determine the accumulated time difference corresponding to each wind speed interval, and determine the wind frequency data of each wind speed interval based on the accumulated time difference corresponding to each wind speed interval;
[0172] Generate a wind frequency data table of the wind turbine generator system within the preset time period based on the wind frequency data of each wind speed interval;
[0173] The wind frequency data table includes: wind farm number, wind turbine number, wind speed range, and wind frequency data.
[0174] In the embodiment of the present disclosure, the second determining module 300 is further configured to:
[0175] Determine the corresponding average power generation value of each wind speed interval according to the power generation data;
[0176] Using the average value of the generated power corresponding to the wind speed interval as the actual power data corresponding to each wind speed interval;
[0177] Generating a first actual power data table of the wind turbine generator system within the preset time period based on the actual power data corresponding to each wind speed interval;
[0178] The first actual power data table includes: wind farm number, wind turbine number, wind speed range, and actual power data.
[0179] It should be noted that the second actual power data table includes: wind farm number, wind turbine number, wind speed range, wind frequency data, and actual power data;
[0180] The reference power data table includes: wind farm number, wind turbine number, wind speed range, and reference power data.
[0181] In the embodiment of the present disclosure, the third determining module 500 includes:
[0182] Merging the second actual power data table of the wind turbine generator set within the preset time period and the reference power data table of the wind turbine generator set to generate an initial theoretical power table of the wind turbine generator set within the preset time period;
[0183] Using the actual power data in the second actual power data table as the theoretical power data in the initial theoretical power table;
[0184] Screening out data rows in the initial theoretical power table where actual power data is missing, and determining theoretical power data corresponding to the data rows based on wind speed interval data of the data rows, a preset first interpolation table and a preset second interpolation table;
[0185] Inserting the theoretical power data corresponding to the data row into the initial theoretical power table to obtain a revised theoretical power table of the wind turbine generator within the preset time period;
[0186] Drawing a theoretical power curve of the wind turbine generator set within the preset time period based on the revised theoretical power table;
[0187] The theoretical power table includes: wind farm number, wind turbine number, wind speed range, actual power data, theoretical power data and reference power data.
[0188] In the embodiment of the present disclosure, Figure 7 As shown, the system further includes: a judgment module 600;
[0189] The judgment module 600 is used to judge whether the maximum value in the theoretical power curve is greater than a preset upper limit coefficient. If so, a power over-limit warning log is generated and recorded.
[0190] In summary, the wind turbine theoretical power curve synthesis system proposed in this embodiment improves the adaptability, speed and accuracy of wind turbine theoretical power curve calculation.
[0191] Example 3
[0192] In order to implement the above embodiments, the present disclosure further proposes a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the method described in the first embodiment is implemented.
[0193] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.
[0194] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.
[0195] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.
Claims
1. A method for synthesizing theoretical power curves of wind turbines, characterized in that: The method comprises: Acquire wind turbine generator set data and a reference power data table of the wind turbine generator set at each moment within a preset time period, and preprocess the wind turbine generator set data; Determine the wind frequency data of each wind speed interval according to the preprocessed wind turbine data, and generate a wind frequency data table of the wind turbine within the preset time period; Determining actual power data corresponding to each wind speed interval based on the preprocessed wind turbine data, and generating a first actual power data table of the wind turbine within the preset time period; Merging the wind frequency data table and the first actual power data table to generate a second actual power data table of the wind turbine generator within the preset time period; The theoretical power curve of the wind turbine generator set within the preset time period is determined according to the second actual power data table of the wind turbine generator set within the preset time period and the reference power data table of the wind turbine generator set.
2. The method according to claim 1, wherein The wind turbine generator set data includes: wind speed data and power generation data.
3. The method according to claim 2, wherein The preprocessing of the wind turbine generator set data includes: The wind turbine generator set data is sequentially subjected to abnormal data elimination and standardization processing.
4. The method according to claim 3, wherein The step of determining the wind frequency data of each wind speed interval based on the pre-processed wind turbine data and generating a wind frequency data table of the wind turbine within the preset time period includes: Determining a maximum wind speed and a minimum wind speed based on the wind speed data, and constructing a wind speed range; Dividing the wind speed range into a plurality of wind speed intervals according to a preset wind speed interval; Determine the accumulated time difference corresponding to each wind speed interval, and determine the wind frequency data of each wind speed interval based on the accumulated time difference corresponding to each wind speed interval; Generate a wind frequency data table of the wind turbine generator system within the preset time period based on the wind frequency data of each wind speed interval; The wind frequency data table includes: wind farm number, wind turbine number, wind speed range, and wind frequency data.
5. The method according to claim 4, wherein The determining of the actual power data corresponding to each wind speed interval based on the pre-processed wind turbine data, and generating a first actual power data table of the wind turbine within the preset time period, includes: Determine the corresponding average power generation value of each wind speed interval according to the power generation data; Using the corresponding average power generation value of the wind speed interval as the corresponding actual power data of each wind speed interval; Generating a first actual power data table of the wind turbine generator system within the preset time period based on the actual power data corresponding to each wind speed interval; The first actual power data table includes: wind farm number, wind turbine number, wind speed range, and actual power data.
6. The method according to claim 5, wherein The second actual power data table includes: wind farm number, wind turbine number, wind speed range, wind frequency data, and actual power data; The reference power data table includes: wind farm number, wind turbine number, wind speed range, and reference power data.
7. The method according to claim 6, wherein The determining of the theoretical power curve of the wind turbine generator set within the preset time period according to the second actual power data table of the wind turbine generator set within the preset time period and the reference power data table of the wind turbine generator set includes: Merging the second actual power data table of the wind turbine generator set within the preset time period and the reference power data table of the wind turbine generator set to generate an initial theoretical power table of the wind turbine generator set within the preset time period; Using the actual power data in the second actual power data table as the theoretical power data in the initial theoretical power table; Screening out data rows in which actual power data is missing from the initial theoretical power table, and determining theoretical power data corresponding to the data rows based on wind speed interval data of the data rows, a preset first interpolation table and a preset second interpolation table; Inserting the theoretical power data corresponding to the data row into the initial theoretical power table to obtain a revised theoretical power table of the wind turbine generator within the preset time period; Drawing a theoretical power curve of the wind turbine generator set within the preset time period based on the revised theoretical power table; The theoretical power table includes: wind farm number, wind turbine number, wind speed range, actual power data, theoretical power data and reference power data.
8. The method according to claim 7, wherein The method further comprises: Determine whether the maximum value in the theoretical power curve is greater than a preset upper limit coefficient. If so, generate a power overlimit warning log and record it.
9. A wind turbine theoretical power curve synthesis system, characterized in that: The system comprises: an acquisition module, configured to acquire wind turbine generator set data and a reference power data table of the wind turbine generator set at each moment within a preset time period, and to pre-process the wind turbine generator set data; A first determining module is configured to determine the wind frequency data of each wind speed interval based on the pre-processed wind turbine data, and generate a wind frequency data table of the wind turbines within the preset time period; a second determining module, configured to determine actual power data corresponding to each wind speed interval based on the preprocessed wind turbine data, and generate a first actual power data table of the wind turbine within the preset time period; a merging module, configured to merge the wind frequency data table and the first actual power data table to generate a second actual power data table of the wind turbine generator within the preset time period; The third determining module is configured to determine a theoretical power curve of the wind turbine generator set within the preset period of time according to the second actual power data table of the wind turbine generator set within the preset period of time and the reference power data table of the wind turbine generator set.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.