Wind power plant output calculation method considering reduction, storage medium and electronic equipment

Abstract

The invention relates to the technical field of wind power plant output calculation, in particular to a reduction-considered wind power plant output calculation method, a storage medium and electronic device.The reduction-considered wind power plant output calculation method comprises the steps that time sequence simulation data of a wind power plant and draught fans are obtained; obtaining a simulation result summary sheet and a power curve; determining reduction coefficients, wherein the reduction coefficients comprise a plant power reduction coefficient, an uncertainty reduction coefficient and a total reduction coefficient of the wind power plant; calculating the output added with the uncertainty reduction; adjusting power above a rated wind speed; calculating the total loss below the rated wind speed; and obtaining a wind power plant output time sequence after the reduction is considered. According to the technical scheme, the problem that in the prior art, the wind power plant output calculation error is large is effectively solved.

Description

Technical Field

[0001] The present application relates to the technical field of wind farm output calculation, and in particular to a wind farm output calculation method taking reduction into account, a storage medium and an electronic device. Background Art

[0002] With the rapid development of the global economy, the reserves of traditional fossil energy are gradually decreasing, and the energy crisis is gradually emerging. As a clean energy, wind power plays an important role in alleviating environmental pollution and energy shortage problems. With the development of comprehensive utilization technology of renewable energy, the field of wind power + has received extensive attention. For example, the combination of wind power with hydrogen production, energy storage and other technologies can not only improve the utilization rate of wind power, but also provide additional value for industrial production and power grids.

[0003] However, the active output of wind farms is affected by wind speed and is random, which poses challenges to the node voltage, line transmission power and system operating frequency of the power system, limiting the further development and utilization of wind energy. In this context, it is particularly important to calculate the output curve of wind farms more accurately. Accurate output curves can provide strong support for the planning and operation of wind power + projects, thereby optimizing resource utilization and improving economic benefits. Traditional output curve calculation methods usually perform uniform reductions based on simulation time series data, but these methods have large errors. Summary of the invention

[0004] The present application provides a wind farm output calculation method taking into account reduction, so as to solve the problem of large error in wind farm output calculation in the prior art.

[0005] A method for calculating wind farm output taking into account reduction is provided in the present application, comprising: obtaining time series simulation data of the wind farm and the wind turbine; obtaining a simulation result summary table and a power curve; determining a reduction factor, the reduction factor comprising: a plant power reduction factor, an uncertainty reduction factor and a total reduction factor of the wind farm; calculating the output with uncertainty reduction added; power adjustment above the rated wind speed; total loss estimation below the rated wind speed; and obtaining a time series of wind farm output after taking into account the reduction.

[0006] Furthermore, when determining the reduction factor, the uncertainty reduction model is used to calculate the equivalent reduction factor of the wind speed and the comprehensive factor of other reduction items.

[0007] Furthermore, the uncertainty reduction model includes: setting the total reduction factor of the wind farm Rf , farm factor reduction and uncertainty factor reduction Rf1 , Wind speed equivalent uncertainty factor reduction coefficient Rf_v And other reduction items comprehensive factor Rf_other; Wind speed equivalent uncertainty factor reduction coefficient ; The reduction factor without considering the factory electricity consumption is ; Comprehensive coefficient of other reduction items .

[0008] Furthermore, the output after adding uncertainty reduction is calculated: the time series simulation data of each wind turbine is read in turn, the wind speed of the average wind speed of the wake is calculated after being affected by uncertain factors, and the output after adding uncertainty reduction is calculated in combination with the power curve of the wind turbine, specifically: represents the time series data set of wind turbine i, which contains date, average wind speed considering wake (m / s), and power considering wake effect (kW); exist A column of data is added to the collection to represent the wind speed with uncertainty, named 'Wind speed with uncertainty', and its calculation formula is: Wind speed with uncertainty = average wind speed considering wake turbulence × Rf_v .

[0009] Further, a continuous and smooth interpolation function is generated according to the array of discrete wind speed-power data points (speed0, power_i) of the given power curve file; and the interpolation function is applied to ['Add uncertainty to wind speed'] to calculate the corresponding power value, which is named ['Output kW after adding uncertainty'].

[0010] Furthermore, when the wind speed reaches or exceeds the rated wind speed, a power adjustment strategy is adopted to take into account the uncertainty in actual operation; specifically: filter [Average wind speed considering wake turbulence_(m / s)] is greater than or equal to the rated wind speed, generating data set TR1, which includes time, average wind speed considering wake turbulence_(m / s), power considering wake effect_(kW), wind speed with uncertainty added, and output after uncertainty added; Calculate the number of data points number_rated of data set TR1; Set the full-fire ratio after the rated wind speed to n, and the incomplete-fire ratio to (1-n). Multiply number_rated by 1-n to get the number of data points that are not fully fired after reaching the rated wind speed, which is need_n. Generate a random reduction factor dataset f_random. The dataset must satisfy the uniform distribution of random numbers, the number of which is need_n, and the average value is equal to Rf_other , and the value range is [ Rf_other - deta0, Rf_other + deta0 ],in deta0 1 - Rf_other ; These random numbers are used to simulate other reduction effects besides uncertainty reduction; Multiply the random reduction factor data set f_random by TR1[Power considering wake effect_(kW)] to obtain TR1[output after processing], that is, the output time sequence of full power reduction that satisfies the full power ratio of n.

[0011] Furthermore, for the operating state below the rated wind speed, a random reduction method based on total loss calculation is implemented to further optimize the simulation results, specifically: Filter data points below the rated wind speed: filter out data points whose wind speed is less than the rated wind speed after adding uncertainty from the wind speed data set to generate data set TR2; Calculate the cumulative energy output above the rated wind speed: Calculate the sum of the "random full output" when the wind speed is greater than or equal to the rated wind speed ,Right now:

[0012] Calculate the cumulative energy output below the rated wind speed: Calculate the sum of the "output after adding uncertainty" when the wind speed is less than the rated wind speed ,Right now

[0013] Calculate the total loss factor below rated wind speed f3 :According to the preset reduction factor Rf_use and known , calculate the total loss factor below the rated wind speed f3 , and its calculation formula is:

[0014]

[0015] Generate a pre-rated random reduction factor data set f3_random. The data set must meet the following requirements: a uniformly distributed random number array, the number of which is the data length of TR2, the average value is equal to f3, and the value range is [ f3 - deta , f3 + deta ],in deta 1 - f3 ; Apply random reduction: multiply the pre-rated random reduction factor data set f3_random by TR2 [output after adding uncertainty] to obtain TR2 [output after processing]; The data set TR1 and TR2 are combined in time series to obtain the data set TR3, where TR3 [output after processing] is the reduction factor of wind turbine i. Output time series.

[0016] Furthermore, based on the calculated processed output of each wind turbine, combined with the reduction of plant power consumption, the output time series of the entire wind farm that meets the total reduction coefficient is calculated, specifically: The processed output of each wind turbine is added in time series to obtain the wind farm that meets the reduction factor: Output time series [Output without considering the reduction of plant power consumption], that is, the output of the wind farm without considering the reduction of plant power consumption; The output of the wind farm without considering the reduction of plant power consumption is compared with the reduction of plant power consumption farmfactor Multiply them together to get the total output of the wind farm that ultimately meets the total reduction factor Rf: .

[0017] According to another aspect of the present application, a storage medium is further provided, wherein the storage medium stores instructions for executing the above-mentioned method for calculating wind farm output taking into account reduction.

[0018] According to another aspect of the present application, an electronic device is provided, including a controller, wherein the controller runs a program for representing the above-mentioned method for calculating the output of a wind farm taking into account the reduction.

[0019] By applying the technical solution of the present application, the reduction coefficient is determined by obtaining the time series simulation data of the wind farm, the simulation result summary table and the power curve. The reduction coefficient includes: the wind farm's plant power reduction coefficient, the uncertainty reduction coefficient and the total reduction coefficient. By adding uncertainty reduction processing, and adjusting the power above the rated wind speed and calculating the total loss below the rated wind speed, the wind farm output curve after reduction is obtained, and such calculation is more accurate and reliable. The technical solution of the present application effectively solves the problem of large errors in wind farm output calculation in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0022] Figure 1 A schematic flow chart of a method for calculating wind farm output taking into account reduction according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0023] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0024] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0025] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used herein to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" may include both "above" and "below". The device may also be positioned in other different ways, rotated 90 degrees or in other orientations, and the spatially relative descriptions used herein are interpreted accordingly.

[0026] like Figure 1 As shown, the method for calculating wind farm output considering reduction in this embodiment includes: obtaining time series simulation data of the wind farm and the wind turbines; obtaining a summary table of simulation results of each wind turbine and a power curve of the wind turbine; determining a reduction factor, the reduction factor including: a reduction factor of plant electricity consumption of the wind farm, an uncertainty reduction factor and a total reduction factor; calculating the output with uncertainty reduction added; power adjustment above the rated wind speed; total loss estimation below the rated wind speed; and obtaining a time series of wind farm output after reduction.

[0027] By applying the technical solution of this embodiment, the reduction coefficient is determined by obtaining the time series simulation data of the wind farm, the simulation result summary table and the power curve. The reduction coefficient includes: the wind farm's plant power reduction coefficient, the uncertainty reduction coefficient and the total reduction coefficient. By adding uncertainty reduction processing, adjusting the power above the rated wind speed and calculating the total loss below the rated wind speed, the wind farm output curve after reduction is obtained, and such calculation is more accurate and reliable. The technical solution of this embodiment effectively solves the problem of large errors in wind farm output calculation in the prior art.

[0028] In the technical solution of this embodiment, the reduction coefficients of the wind farm are classified as shown in the following table, where serial number 6 is the above-mentioned plant power reduction coefficient, serial number 9 is the above-mentioned uncertainty reduction coefficient, and the comprehensive reduction coefficient is the above-mentioned total reduction coefficient.

[0029] Table Wind Farm Reduction Factor Table

[0030] The reduction factors include: a. Availability of wind turbines: does not take into account the impact of downtime caused by factors such as wind turbines, transmission lines, and electrical equipment maintenance and failures.

[0031] b. Blade contamination reduction takes into account that when the temperature is low and the humidity is high in winter, icing may occur, and the blades will gradually wear and age with use, and the aerodynamic performance will decrease, thus affecting the power generation performance of the wind turbine.

[0032] c. Control and influence of turbulence intensity Ideally, the wind turbine will control the status of the unit as the wind speed and direction change. The actual situation is that the control of the running unit always lags behind the change of wind, resulting in power generation loss.

[0033] d. Reduction of power consumption in the factory: the part of electricity that will be lost in the transmission line and the proportion of the wind farm’s own electricity consumption in the total power generation, which is generally related to the wind farm’s transmission line and the wind farm’s own design.

[0034] e. Power curve correction Considering that the power curve of a wind turbine generally fluctuates from the standard power curve, it should be properly considered when calculating the power generation.

[0035] f. Climate impact: The site area may have special climate conditions and destructive weather, which may be different from the design standard climate conditions and have certain uncertainties.

[0036] g. Uncertainty factors reduce other unconsidered factors, such as software calculation errors, map data errors, etc., which have large uncertainties.

[0037] In the technical solution of this embodiment, the uncertainty reduction model is used to calculate the equivalent reduction coefficient of wind speed. The uncertainty reduction model includes: setting the total reduction coefficient Rf of the wind farm, the reduction coefficient farmfactor of the power consumption, the reduction coefficient Rf1 of the uncertainty factor, the wind speed equivalent uncertainty factor reduction coefficient Rf_v and the comprehensive coefficient Rf_other of other reduction items; the wind speed equivalent uncertainty factor reduction coefficient ; The reduction factor without considering the factory electricity consumption is ; Comprehensive coefficient of other reduction items .

[0038] In the technical solution of this embodiment, the output with uncertainty reduction is calculated: the time series simulation data of each wind turbine is read in turn, the wind speed of the average wind speed of the wake is calculated after being affected by uncertain factors, and the output with uncertainty reduction is calculated in combination with the power curve of the wind turbine, specifically: represents the time series data set of wind turbine i, which contains the date, average wind speed considering the wake (m / s), and power considering the wake effect (kW); A column of data is added to the collection to represent the wind speed with uncertainty, named 'wind speed with uncertainty', and its calculation formula is: wind speed with uncertainty = average wind speed considering wake × Rf_v .

[0039] In the technical solution of this embodiment, a continuous and smooth interpolation function is generated according to the array of discrete wind speed-power data points (speed0, power_i) of a given power curve file; and the interpolation function is applied to TS i ['Add uncertain wind speed'] to calculate the corresponding power value, which is named TS i ['Output kW after adding uncertainty'].

[0040] In the technical solution of this embodiment, when the wind speed reaches or exceeds the rated wind speed, this technology adopts a power adjustment strategy to take into account the uncertainty in actual operation; specifically: screening [Average wind speed considering wake turbulence_(m / s)] is greater than or equal to the rated wind speed, generating data set TR1, which includes time, average wind speed considering wake turbulence_(m / s), power considering wake effect_(kW), wind speed with uncertainty added, and output after uncertainty added; Calculate the number of data points number_rated of data set TR1; Set the full-fire ratio after the rated wind speed to n, and the incomplete-fire ratio to (1-n). Multiply number_rated by 1-n to get the number of data points that are not fully fired after reaching the rated wind speed, which is need_n. Generate a random reduction factor dataset f_random. The dataset must satisfy the uniform distribution of random numbers, the number of which is need_n, and the average value is equal to Rf_other , and the value range is [ Rf_other - deta0 , Rf_other + deta0 ],in deta0 1 - Rf_other ; These random numbers are used to simulate other reduction effects besides uncertainty reduction; Multiply the random reduction factor data set f_random by TR1[Power considering wake effect_(kW)] to obtain TR1[output after processing], that is, the output time sequence of full power reduction that satisfies the full power ratio of n.

[0041] In the technical solution of this embodiment, for the operating state below the rated wind speed, a random reduction method based on total loss extrapolation is implemented to further optimize the simulation results, specifically: filtering data points below the rated wind speed: filtering data points whose wind speed is less than the rated wind speed after adding uncertainty from the wind speed data set to generate data set TR2; Calculate the cumulative energy output above the rated wind speed: Calculate the sum of the "random full output" when the wind speed is greater than or equal to the rated wind speed ,Right now:

[0042] Calculate the cumulative energy output below the rated wind speed: Calculate the sum of the "output after adding uncertainty" when the wind speed is less than the rated wind speed ,Right now

[0043] Calculate the total loss factor below rated wind speed f3 :According to the preset reduction factor Rf_use and known , calculate the total loss factor below the rated wind speed f3 , and its calculation formula is:

[0044]

[0045] Generate a pre-rated random reduction factor data set f3_random. The data set must meet the following requirements: a uniformly distributed random number array, the number of which is the data length of TR2, the average value is equal to f3, and the value range is [ f3 - deta , f3 + deta ],in deta 1 - f3 ; Apply random reduction: multiply the pre-rated random reduction factor data set f3_random by TR2 [output after adding uncertainty] to obtain TR2 [output after processing]; The data set TR1 and TR2 are combined in time series to obtain the data set TR3, where TR3 [output after processing] is the reduction factor of wind turbine i. Output time series.

[0046] In the technical solution of this embodiment, the processed output of each wind turbine is calculated, combined with the reduction of the power consumption of the plant, and the output time series of the entire wind farm that meets the total reduction coefficient is calculated. Specifically, the processed output of each wind turbine is added according to the time series to obtain the wind farm that meets the reduction coefficient of Output time series [Output without considering the reduction of plant power consumption], that is, the output of the wind farm without considering the reduction of plant power consumption; the output of the wind farm without considering the reduction of plant power consumption and the reduction of plant power consumption farmfactor Multiply them together to get the total output of the wind farm that ultimately meets the total reduction factor Rf: .

[0047] Based on the above, the wind farm output calculation method considering the reduction includes: Collect a full year of time series simulation data for the wind farm and each wind turbine, including detailed information such as wind speed after the wake and power generation after the wake. Determine the reduction factor for plant power consumption, uncertainty reduction factor, and total reduction factor of the wind farm. Use the uncertainty reduction model to calculate the equivalent reduction factor of wind speed and the comprehensive factor of other reduction items. Read the time series simulation data of each wind turbine, calculate the wind speed after adding uncertainty, and calculate the output in combination with the power curve. Determine the number of data points above the rated wind speed, set the ratio of full and non-full power generation, and perform random reduction processing. Filter the data points below the rated wind speed, calculate the cumulative energy output, deduce the total loss factor, and perform random reduction processing.

[0048] The specific process of calculating the wind farm output with reduction in mind includes: (1) First, obtain the time series simulation data of the wind farm and each wind turbine for a full year. These data should include the post-wake wind speed and post-wake power generation of each wind turbine at each time series for a full year. The specific data include: Timing simulation data of each unit: label, time, average wind speed, average wind speed considering wake, power, power considering wake effect, and energy density.

[0049] Timing simulation data for the entire field: time, power, and power considering wake effects.

[0050] In addition, it is necessary to obtain a summary table of simulation results of the wind farm and the power curve of each type of wind farm, including: The simulation result summary table should include: wind turbine type, label, Weibull parameter A (m / s), Weibull parameter k, energy density (watt / m2), annual power generation (MWh / year), average wind speed (m / s), power generation considering wake effect (MWh / year), average wind speed considering wake effect, air density at the point (kg / m3), and average reduction rate caused by wake effect (%).

[0051] The power curve should include: air density (kg / m3), rated power (kW), impeller diameter (m), hub height, list of wind speeds at intervals of 0.5m / s, and power corresponding to wind speed (kW).

[0052] (2) Set the total reduction factor Rf of the wind farm, the reduction factor for plant power consumption farmfactor, and the reduction factor for uncertain factors Rf1.

[0053] Among them, in the evaluation process of wind farms, the wind farm’s discounted electricity should be estimated based on the theoretical annual power generation of the wind farm and the comprehensive reduction rate. The reduction of power consumption refers to the part of the power lost in the transmission line and the proportion of the wind farm’s self-consumption in the total power generation, which is generally related to the wind farm’s transmission line and the wind farm’s own design. The reduction of uncertain factors refers to the reduction caused by other factors that are not considered, such as software calculation errors, map data errors, etc., which have large uncertainties.

[0054] (3) Using the uncertainty reduction model, calculate the equivalent reduction coefficient of the uncertainty factor on the wind speed, and calculate the comprehensive coefficient of other reduction items at the same time, specifically: Wind speed equivalent uncertainty factor reduction factor , Comprehensive factors of other reduction items ; (4) Calculate the output after adding uncertainty reduction: Read the time series simulation data of each wind turbine in turn, calculate the wind speed after the average wind speed of the wake is affected by uncertain factors, and calculate the output after adding uncertainty reduction in combination with the power curve of the wind turbine. Specifically: represents the time series data set of wind turbine i, which contains date, average wind speed considering wake (m / s), and power considering wake effect (kW); Add a column of data to the TS set to represent the wind speed with uncertainty, named 'wind speed with uncertainty', and its calculation formula is: Wind speed with uncertainty = average wind speed considering wake turbulence × Rf_v; Generates a continuous, smooth interpolation function based on the array of discrete wind speed-power data points (speed0, power_i) of the given power curve file. Apply it to TS i ['Wind speed with uncertainty added'] to calculate the corresponding power value, which is named ts_df['Output kW after adding uncertainty'].

[0055] (5) Power adjustment strategy above rated wind speed: In the present invention, when the wind speed reaches or exceeds the rated wind speed, the system adopts a power adjustment strategy to take into account the uncertainty in actual operation. Specifically, Determine the number of data points above the rated wind speed number_rated; Set the full-fire ratio after the rated wind speed to n, and the incomplete-fire ratio to (1-n). Multiply number_rated by 1-n to get the number of data points that are not fully fired after reaching the rated wind speed, which is need_n. Stratified random sampling is used to randomly select need_n data points from the data set with wind speed greater than or equal to the rated wind speed for reduction to simulate the uncertainty and variability in actual operation.

[0056] Generate a random reduction factor dataset f_random. The dataset must satisfy the uniform distribution of random numbers, the number of which is need_n, and the average value is equal to Rf_other , and the range of values ​​is [Rf_other - deta0, Rf_other +deta0], where deta0 is 1 - Rf_other. These random numbers are used to simulate other reduction effects besides uncertainty reduction.

[0057] Multiply the random reduction factor data set f_random by TR1[Power considering wake effect_(kW)] to obtain TR1[output after processing], that is, the output time sequence of full power reduction that satisfies the full power ratio of n.

[0058] (6) Calculation of total losses below rated wind speed For the operation state below the rated wind speed, a random reduction method based on total loss calculation is implemented to further optimize the simulation results. Specifically, Filter data points below the rated wind speed: Filter data points whose wind speed is less than the rated wind speed after adding uncertainty from the wind speed data set to generate data set TR2.

[0059] Calculate the cumulative energy output above the rated wind speed: Calculate the sum of the "random full output" when the wind speed is greater than or equal to the rated wind speed ,Right now:

[0060] Calculate the cumulative energy output below the rated wind speed: Calculate the sum of the "output after adding uncertainty" when the wind speed is less than the rated wind speed ,Right now

[0061] Calculate the total loss factor below rated wind speed f3 :According to the preset reduction factor Rf_use and known , calculate the total loss factor below the rated wind speed f3, and its calculation formula is:

[0062]

[0063] Generate a pre-rated random reduction factor data set f3_random. The data set must meet the following requirements: a uniformly distributed random number array, the number of which is the data length of TR2, the average value is equal to f3, and the value range is [ f3 - deta , f3 + deta ],in deta 1 - f3 ; Apply random reduction: multiply the pre-rated random reduction factor data set f3_random by TR2 [output after adding uncertainty] to obtain TR2 [output after processing]; The data set TR1 and TR2 are combined in time series to obtain the data set TR3, where TR3 [output after processing] is the reduction factor of wind turbine i. Output time series.

[0064] Based on the calculated processed output of each wind turbine, combined with the reduction of plant power consumption, the output time series of the entire wind farm that meets the total reduction coefficient is calculated, specifically: The processed output of each wind turbine is added in time series to obtain the wind farm that meets the reduction factor: Output time series [Output without considering the reduction of plant power consumption], that is, the output of the wind farm without considering the reduction of plant power consumption; Multiply the wind farm output without considering the reduction of plant power consumption by the reduced farm factor to obtain the total wind farm output that ultimately meets the total reduction factor Rf: .

[0065] This application provides a wind farm output calculation method that takes into account reduction, which can effectively simulate and adjust the uncertainty and variability in actual operation, thereby improving the overall performance and reliability of power generation system prediction. This application has important guiding significance for wind farm output prediction and power generation assessment, has industrial utilization value in engineering, and has good application prospects.

[0066] The present application uses the uncertainty reduction model to calculate the equivalent reduction factor of wind speed. The present application can effectively deal with the uncertainty of wind speed, which is an important aspect that is often overlooked in the prior art. In this way, the present application can more accurately simulate the impact of actual wind speed changes on wind farm output.

[0067] This application uses stratified random sampling and uniform distribution random reduction algorithms, which can simulate the uncertainty and variability in actual operation and enhance the adaptability and flexibility of the model. Compared with the fixed mode reduction method, this method can better adapt to different operating conditions and scenarios.

[0068] This application has certain guiding significance for the calculation of wind farm output taking into account reduction, has industrial utilization value in engineering, and has good application prospects in engineering.

[0069] Uncertainty reduction model: The uncertainty reduction model is used to calculate the equivalent reduction factor of wind speed to deal with the uncertainty of wind speed.

[0070] Stratified random sampling and random reduction algorithm: Stratified random sampling and random reduction are performed on data points above the rated wind speed to simulate the uncertainty and variability in actual operation.

[0071] Random reduction method based on total loss calculation: The total loss factor below the rated wind speed is calculated by the cumulative output above and below the rated wind speed, thereby generating a random reduction factor and performing random reduction on the data points below the rated wind speed.

[0072] According to another aspect of the present application, a storage medium is further provided, wherein the storage medium stores instructions for executing the above-mentioned method for calculating wind farm output taking into account reduction.

[0073] According to another aspect of the present application, an electronic device is provided, including a controller, wherein the controller runs a program for representing the above-mentioned method for calculating the output of a wind farm taking into account the reduction.

[0074] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0075] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0076] The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for calculating wind farm output taking into account reduction, characterized in that: include: Obtain time series simulation data of wind farms and wind turbines; Get the simulation result summary table and power curve; Determining reduction factors, wherein the reduction factors include: a reduction factor for power consumption of the wind farm, an uncertainty reduction factor, and a total reduction factor; Calculate the output with uncertainty reduction added; Power adjustment above rated wind speed; Calculation of total losses below rated wind speed; The wind farm output time series after considering the reduction is obtained.

2. The method for calculating wind farm output considering reduction according to claim 1, characterized in that: When determining the reduction factor, the uncertainty reduction model is used to calculate the equivalent reduction factor of wind speed and the comprehensive factor of other reduction items.

3. The method for calculating wind farm output considering reduction according to claim 2, characterized in that: Uncertainty reduction models include: Setting the total reduction factor for wind farms R , farm factor reduction and uncertainty factor reduction Rf1 , Wind speed equivalent uncertainty factor reduction coefficient Rf And other reduction items comprehensive factor Rf_other ; Wind speed equivalent uncertainty factor reduction factor ; The reduction factor without considering the power consumption of the factory is ; Comprehensive factors of other reduction items .

4. The method for calculating wind farm output considering reduction according to claim 3, characterized in that: Calculate the output after adding uncertainty reduction: read the time series simulation data of each wind turbine in turn, calculate the wind speed after the average wind speed of the wake is affected by uncertain factors, and calculate the output after adding uncertainty reduction in combination with the power curve of the wind turbine, specifically: represents the time series data set of wind turbine i, which contains date, average wind speed considering wake (m / s), and power considering wake effect (kW); exist A column of data is added to the collection to represent the wind speed with uncertainty, named 'Wind speed with uncertainty', and its calculation formula is: Wind speed with uncertainty = average wind speed considering wake turbulence × Rf .

5. The method for calculating wind farm output considering reduction according to claim 4, characterized in that: Generate a continuous, smooth interpolation function based on the array of discrete wind speed-power data points (speed0, power_i) of the given power curve file; and apply the interpolation function to ['Add uncertainty to wind speed'] to calculate the corresponding power value, which is named ['Output kW after adding uncertainty'].

6. The method for calculating wind farm output considering reduction according to claim 1, characterized in that: When the wind speed reaches or exceeds the rated wind speed, a power adjustment strategy is adopted to take into account the uncertainty in actual operation; specifically: filter [Average wind speed considering wake turbulence_(m / s)] is greater than or equal to the rated wind speed, generating data set TR1, which includes time, average wind speed considering wake turbulence_(m / s), power considering wake effect_(kW), wind speed with uncertainty added, and output after uncertainty added; Calculate the number of data points number_rated of data set TR1; Set the full-fire ratio after the rated wind speed to n, and the incomplete-fire ratio to (1-n). Multiply number_rated by 1-n to get the number of data points that are not fully fired after reaching the rated wind speed, which is need_n. Generate a random reduction factor dataset f_random. The dataset must satisfy the uniform distribution of random numbers, the number of which is need_n, and the average value is equal to Rf_other , and the value range is [ Rf_other - deta0 , Rf_other + deta0 ],in deta0 1 - Rf_other ; These random numbers are used to simulate other reduction effects besides uncertainty reduction; Multiply the random reduction factor data set f_random by TR1[Power considering wake effect_(kW)] to obtain TR1[output after processing], that is, the output time sequence of full power reduction that satisfies the full power ratio of n.

7. The method for calculating wind farm output considering reduction according to claim 6, characterized in that: For the operation state below the rated wind speed, a random reduction method based on total loss calculation is implemented to further optimize the simulation results, specifically: Filter data points below the rated wind speed: filter out data points whose wind speed is less than the rated wind speed after adding uncertainty from the wind speed data set to generate data set TR2; Calculate the cumulative energy output above the rated wind speed: Calculate the sum of the "random full output" when the wind speed is greater than or equal to the rated wind speed ,Right now: Calculate the cumulative energy output below the rated wind speed: Calculate the sum of the "output after adding uncertainty" when the wind speed is less than the rated wind speed ,Right now Calculate the total loss factor below rated wind speed f3 :According to the preset reduction factor Rf_use and known , calculate the total loss factor below the rated wind speed f3 , and its calculation formula is: Generate a pre-rated random reduction factor data set f3_random. The data set must meet the following requirements: a uniformly distributed random number array, the number of which is the data length of TR2, the average value is equal to f3, and the value range is [ f3 - deta , f3 + deta ],in deta 1 - f3 ; Apply random reduction: multiply the pre-rated random reduction factor data set f3_random by TR2 [output after adding uncertainty] to obtain TR2 [output after processing]; The data set TR1 and TR2 are combined in time series to obtain the data set TR3, where TR3 [output after processing] is the reduction factor of wind turbine i. Output time series.

8. The method for calculating wind farm output considering reduction according to claim 6, characterized in that: Based on the calculated processed output of each wind turbine, combined with the reduction of plant power consumption, the output time series of the entire wind farm that meets the total reduction coefficient is calculated, specifically: The processed output of each wind turbine is added in time series to obtain the wind farm that meets the reduction factor: The output time series TS [output without considering the reduction of plant power consumption], that is, the output of the wind farm without considering the reduction of plant power consumption; Multiply the wind farm output without considering the reduction of plant power consumption by the reduced farm factor to obtain the total wind farm output that ultimately meets the total reduction factor Rf: 。 9. A storage medium, characterized in that: The storage medium stores instructions for executing the method for calculating wind farm output taking into account reduction as described in any one of claims 1 to 8.

10. An electronic device, characterized in that: The method comprises a controller, wherein the controller runs a program for representing the method for calculating the output of a wind farm taking into account reduction according to any one of claims 1 to 8.

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