A dynamic micro-layout method, system and equipment for offshore wind farms

Abstract

The present invention provides a method, system and equipment for dynamic micro-layout of an offshore wind farm, comprising the following steps: step 1, obtaining wind speed information and wind direction information of an offshore wind farm to be measured; step 2, predicting the probability distribution characteristics of the wind speed information and wind direction information based on the wind speed information and wind direction information obtained in step 1; step 3, optimizing the micro-layout of the offshore wind farm to be measured according to the probability distribution characteristics predicted in step 2, and obtaining the target position of each unit in the offshore wind farm to be measured; step 4, obtaining the current coordinates and translational velocity vector of each unit in the offshore wind farm to be measured; step 5, calculating the pitch angle control value and yaw angle control value corresponding to each unit; step 6, performing dynamic micro-layout of the offshore wind farm to be measured according to the obtained pitch angle control value and yaw angle control value. The present invention can enhance the adaptability of the micro-layout to the external environment and improve the power generation of the entire field.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind power generation, and in particular relates to a dynamic microscopic layout method, system and equipment for an offshore wind farm. Background Art

[0002] With the rapid development of the wind power industry, onshore wind energy resources are gradually being depleted, and offshore wind power has become the focus of new wind power installations. While offshore wind power installations are primarily based on fixed offshore wind turbines, floating offshore wind turbines are economically preferred for installations in deep waters. Unlike fixed offshore wind turbines and onshore wind turbines, floating wind turbines introduce additional degrees of freedom in their floating foundations, significantly increasing system uncertainty and instability. Conversely, floating wind turbines also benefit from the additional degrees of freedom offered by their floating foundations, and leveraging these properties will significantly promote the rapid, large-scale development of floating wind turbines.

[0003] Theoretically, one way to take advantage of the flexibility of floating foundations is to micro-layout the wind farm. Generally, after conducting a wind resource analysis and macro-site selection for a wind farm, the micro-layout of the wind farm is carried out by comprehensively considering the impact of the wake effect on the wind turbines. The micro-layout of an onshore wind farm is relatively simple. A single operating condition, multiple typical operating conditions, or the average wind speed spectrum distribution throughout the year are often selected to design the layout of wind turbines with the goal of maximizing the utilization rate of the entire wind energy. The micro-layout of an onshore wind farm is determined in the early stages and is difficult to change. However, the wind resource characteristics of a wind farm vary with the year, season, and month. A fixed micro-layout is not adaptable enough to changes in wind resource characteristics, which can easily lead to energy capture losses for the entire farm. Summary of the Invention

[0004] The purpose of the present invention is to provide a dynamic micro-layout method, system and equipment for offshore wind farms, which solves the problem that there is currently no micro-layout of offshore wind farms, resulting in energy capture loss of the entire field. The dynamic micro-layout method provided by the present invention is used to improve the adaptability of the micro-layout to the external environment and increase the power generation of the entire field.

[0005] In order to achieve the above object, the technical solution adopted in the present invention is:

[0006] The present invention provides a dynamic micro-layout method for an offshore wind farm, comprising the following steps:

[0007] Step 1: Obtain wind speed and direction information of the offshore wind farm to be tested;

[0008] Step 2: predicting the probability distribution characteristics of the wind speed information and wind direction information based on the wind speed information and wind direction information obtained in step 1;

[0009] Step 3: Optimize the microscopic layout of the offshore wind farm to be tested based on the probability distribution characteristics predicted in step 2 to obtain the target position of each unit in the offshore wind farm to be tested;

[0010] Step 4: Obtain the current coordinates and translational velocity vector of each unit in the offshore wind farm to be measured;

[0011] Step 5, calculate the position error and direction error corresponding to each unit;

[0012] Step 6: Perform dynamic micro-layout of the offshore wind farm to be measured based on the obtained position error and direction error.

[0013] Preferably, in step 2, the probability distribution characteristics of the wind speed information and the wind direction information are predicted based on the wind speed information and the wind direction information obtained in step 1, and the specific method is:

[0014] The probability density distribution of wind speed and direction information is fitted using the Weibull distribution function to obtain scale parameters and shape parameters.

[0015] The obtained scale parameters and shape parameters are combined with the prediction algorithm to predict the Weibull distribution law of wind speed and wind direction in the future set time period, and the probability distribution characteristics of wind speed information and wind direction information are obtained.

[0016] Preferably, in step 3, the microscopic layout of the offshore wind farm to be measured is optimized according to the probability distribution characteristics predicted in step 2 to obtain the target position of each unit in the offshore wind farm to be measured, specifically by:

[0017] Based on the probability distribution characteristics predicted in step 2, the optimization goal is to maximize the wind energy utilization throughout the year, season, or month. The optimization algorithm is used to optimize the micro-layout of the offshore wind farm to obtain the target position of each unit in the offshore wind farm to be tested.

[0018] Preferably, in step 5, the position error and direction error corresponding to each unit are calculated by:

[0019] Calculate the angle between the translational velocity vector of each unit and the x-axis, the distance between the current coordinate and the target position, and the angle between the displacement vector between the current coordinate and the target coordinate and the x-axis;

[0020] Calculate the position error of each unit based on the distance between the current coordinates and the target position;

[0021] The directional error of each unit is calculated based on the angle between the translational velocity vector and the x-axis, the displacement vector between the current coordinate and the target position, and the angle between the current coordinate and the x-axis.

[0022] Preferably, in step 6, a dynamic microscopic layout of the offshore wind farm to be measured is performed according to the obtained position error and direction error, and the specific method is:

[0023] Determine the start and stop of the specific position control strategy of each unit based on the position error of each unit;

[0024] When the judgment result is on, the pitch angle control value and yaw angle control value corresponding to each unit are calculated, and each unit is controlled to move to a circle with the target position as the center and r1 as the radius, where r1 is the preset threshold;

[0025] When the judgment result is stop, the pitch angle control value and the yaw angle control value corresponding to each unit are set to zero, and the coordinate position of each unit is controlled to remain unchanged.

[0026] Preferably, the start and stop of the specific position control strategy of each unit is determined according to the position error and direction error of each unit. The specific method is:

[0027] If the current position control is in the enabled state, the logic quantity for switching the current position control strategy from enabled to disabled is: e β ≤r1;

[0028] If the current position control is in the off state, the logic quantity for the current position control strategy to switch from off to on is: e β ≥r2;

[0029] Among them, r1 and r2 are preset thresholds, and r1 <r2。

[0030] The present invention provides a dynamic micro-layout system for an offshore wind farm, comprising:

[0031] An information acquisition unit, used to acquire wind speed information and wind direction information of the offshore wind farm to be measured;

[0032] a position acquisition unit, configured to predict probability distribution characteristics of wind speed information and wind direction information based on the obtained wind speed information and wind direction information;

[0033] The microscopic layout of the offshore wind farm to be tested is optimized based on the predicted probability distribution characteristics to obtain the target position of each unit in the offshore wind farm to be tested;

[0034] A parameter calculation unit is used to obtain the current coordinates and translational velocity vector of each unit in the offshore wind farm to be measured;

[0035] Calculate the position error and direction error corresponding to each unit;

[0036] The control unit is used to perform dynamic micro-layout of the offshore wind farm to be measured according to the obtained position error and direction error.

[0037] The present invention provides a dynamic micro-layout device for an offshore wind farm, comprising a processor and a computer program capable of running on the processor, and is characterized in that the processor implements the steps of the method when executing the computer program.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] The present invention provides a dynamic micro-layout method for an offshore wind farm. The method can update the layout of wind turbines in the wind farm according to different time scales such as years, seasons or months, thereby enhancing the adaptability of the micro-layout to the external environment and improving the power generation of the entire farm. The method corresponds the probability density distribution law of wind speed and wind direction to the scale parameter a and the shape parameter b based on the assumption of Weibull distribution, and directly predicts the scale parameter a and the shape parameter b. The accuracy is simpler and more efficient than first predicting the time series of wind speed and wind direction and then performing statistical analysis. The method performs dynamic layout updates according to time scales such as years, seasons or months, thereby avoiding the loss of pitch change, yaw energy consumption and wind energy utilization caused by frequent activation of the dynamic micro-layout of the wind farm. The method is based on the position error e β The size of the position error is used to determine whether to enable or stop the position control strategy, thereby reducing the loss of pitch, yaw energy consumption and wind energy utilization caused by frequent position control processes; the method uses the position error e β The size of the position control start-stop buffer is used to establish the position control start-stop buffer zone, which reduces the frequent start-up and shutdown switching position control process; the method decouples the position control of the unit according to the position error control and the direction error control, and uses the yaw control to change the thrust direction, and uses the pitch control to change the thrust size, thereby realizing the decoupling control of the thrust size and direction, and further realizing the decoupling control of the direction and size of the unit translation speed; the method designs the pitch angle and yaw angle PID controllers respectively, and the pitch angle control loop is used to reduce the position error e β , the yaw angle control loop is used to eliminate the direction error e γ , and finally the unit moves to a circle with the target position as the center and r1 as the radius. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flow chart of the method of the present invention;

[0041] Figure 2 The figure is a schematic diagram of the coordinates and translational speed of a certain unit in a wind field in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0042] The present invention will be further described below with reference to the accompanying drawings.

[0043] like Figure 1As shown, the present invention provides a dynamic micro-layout method for an offshore wind farm, which specifically includes the following steps:

[0044] S1: Use the SCADA system of the wind farm to collect environmental information such as wind speed and wind direction, average the wind speed and wind direction signals in a 1-hour period, and use a data storage device to store the obtained 1-hour average wind speed and 1-hour average wind direction.

[0045] S2: Predict the probability distribution characteristics of wind speed and wind direction based on the environmental information collected in S1.

[0046] S2-1: Based on the wind speed, wind direction and other signals stored in S1, the analysis period is set to 1 year, 1 quarter or 1 month, and the Weibull distribution function is used to fit the probability density distribution of the 1-hour average wind speed and average wind direction stored in S1. The Weibull distribution is determined by its scale parameter a and shape parameter b, and the parameters a and b representing the historical wind speed and wind direction distribution on the annual, seasonal or monthly scale are stored.

[0047] S2-2: Based on the annual, seasonal, or monthly historical wind speed and direction distribution parameters a and b stored in S2-1, a prediction algorithm is used to predict the Weibull distribution of wind speed and direction for the next year, quarter, or month, respectively. This is equivalent to predicting the scale parameter a and shape parameter b. The prior art has a wealth of well-established algorithms for predicting future data based on known historical data, which will not be elaborated upon in this disclosure.

[0048] S3: Combining the Weibull distribution of wind speed and direction for the next year, quarter, or month predicted in S2, an optimization algorithm is used to optimize the wind farm's microscopic layout, with the goal of maximizing wind energy utilization throughout the year, quarter, or month. The optimized layout results in the target positions for each turbine. The prior art provides numerous known probability distributions of wind speed and direction for wind farms, and the optimization algorithm for determining the optimal wind farm layout is beyond the scope of this invention.

[0049] Frequently updating wind farm layout results will lead to frequent activation of wind farm micro-layout strategies, consuming a large amount of pitch and yaw energy. Furthermore, during the transition between turbine startup positions, the pitch and yaw movements result in low wind energy utilization efficiency, hindering the turbine's ability to capture maximum wind energy. Therefore, to reduce the losses caused by frequent activation of the wind farm's dynamic micro-layout, the results of micro-layout optimization are not continuously updated, but are updated once a year, quarter, or month. Accordingly, the target position setpoints for each turbine are also updated only once a year, quarter, or month. For the updated optimized layout results, the target position of a turbine is denoted as the coordinates (c, d) in the wind farm.

[0050] Advantages: ① Based on the assumption of Weibull distribution, the probability density distribution law of wind speed and wind direction is corresponded to the scale parameter a and shape parameter b, and the scale parameter a and shape parameter b are directly predicted. Its accuracy is simpler and more efficient than predicting the time series of wind speed and wind direction and then performing statistical analysis; ② The probability density distribution law is dynamically updated on time scales such as years, seasons, and months, avoiding the loss of pitch change, yaw energy consumption and wind energy utilization caused by frequent startup of the dynamic micro-layout of the wind farm.

[0051] S4: Detect the current coordinates and translational velocity vectors of each unit in the wind field.

[0052] The coordinates and translational velocity diagram of a certain unit in the wind field is as follows: Figure 2 High-precision GPS, gyroscopes, and other sensors are installed on the floating foundation or nacelle of each turbine. After sensor calibration, the current coordinates of each turbine and the turbine's translational velocity vector can be calculated. The coordinates of a turbine's current position in the wind field are denoted as (e, f), and the translational velocity vector of the turbine in the wind field is v = (g, h).

[0053] S5: Calculate the angle α between the translational velocity vector v = (g, h) obtained from S4 and the x-axis, calculate the distance L between the current coordinates (e, f) obtained by S4 and the target coordinates (c, d) obtained by S3, and the angle θ between the displacement vector between the current coordinates (e, f) and the target coordinates (c, d) and the x-axis.

[0054]

[0055]

[0056]

[0057] S6: Each unit calculates the pitch angle control value β and yaw angle control value γ corresponding to each unit based on the target coordinates (c, d) obtained in S3 and the current coordinates (e, f) obtained in S4, and performs dynamic micro-layout of the wind farm based on the obtained pitch angle control value β and yaw angle control value γ.

[0058] S6-1: Calculate the position error e β :

[0059] e β =L

[0060] S6-2: Calculate the direction error e based on the angle α between the unit translation velocity vector and the x-axis and the angle θ between the displacement vector between the current coordinate and the target coordinate and the x-axis obtained in S5 γ :

[0061] e γ =θ-α

[0062] S6-3: In order to reduce the loss of pitch control, yaw energy consumption and wind energy utilization caused by frequent position control process, according to the position error e β The size of the position control strategy is used to determine whether to enable or stop the position control strategy. At the same time, in order to reduce the frequent startup and shutdown of the position control process, the position control strategy is started and stopped by e β The size of the position control start and stop buffer is established. In summary, the start and stop logic of the specific position control strategy is:

[0063] ① If the current position control is in the start state, the logic quantity of the current position control strategy switching from start to close is: e β ≤r1;

[0064] ② If the current position control is in the off state, the logic quantity for the current position control strategy to switch from off to on is: e β ≥r2;

[0065] Among them, r1 and r2 are preset positive constants, and r1 <r2。

[0066] When the current position control strategy described in S6-4: S6-3 is started, its theoretical control logic is: yaw control can be used to change the thrust direction, and pitch control can be used to change the thrust magnitude, thus achieving decoupling control of thrust magnitude and direction, and further achieving decoupling control of the unit's translational speed direction and magnitude. PID controllers for pitch angle and yaw angle are designed separately, and the pitch angle control loop is used to reduce the position error e β , the yaw angle control loop is used to eliminate the direction error e γ , and finally the unit moves to a circle with the target position as the center and r1 as the radius.

[0067] The specific PID control algorithm is:

[0068] The pitch angle control quantity is:

[0069]

[0070] The yaw angle control quantity is:

[0071]

[0072] Among them, K pβ , K iβ , K dβ are the proportional, integral and differential gains of the pitch angle control loop respectively; K pγ , K iγ , K dγ They are the proportional, integral and differential gains of the yaw angle control loop respectively.

[0073] Advantages: The position control of the unit is decoupled into position error control and direction error control, and two simple and reliable PID controllers can be designed to realize position vector control.

[0074] When the judgment result is stop, the pitch angle control value and the yaw angle control value corresponding to each unit are set to zero, and the coordinate position of each unit is controlled to remain unchanged.

[0075] The present invention provides a dynamic micro-layout system for an offshore wind farm, comprising:

[0076] An information acquisition unit, used to acquire wind speed information and wind direction information of the offshore wind farm to be measured;

[0077] a position acquisition unit, configured to predict probability distribution characteristics of wind speed information and wind direction information based on the obtained wind speed information and wind direction information;

[0078] The microscopic layout of the offshore wind farm to be tested is optimized based on the predicted probability distribution characteristics to obtain the target position of each unit in the offshore wind farm to be tested;

[0079] A parameter calculation unit is used to obtain the current coordinates and translational velocity vector of each unit in the offshore wind farm to be measured;

[0080] Calculate the position error and direction error corresponding to each unit;

[0081] The control unit is used to perform dynamic micro-layout of the offshore wind farm to be measured according to the obtained position error and direction error.

[0082] The present invention also provides a device for dynamic micro-layout of offshore wind farms. The device can be a computing device such as a desktop computer, laptop, PDA, or cloud server. The device can include, but is not limited to, a processor and memory.

[0083] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. ...

Claims

1. A dynamic microscopic layout method for an offshore wind farm, characterized in that: The following steps are involved: Step 1: Obtain wind speed and direction information of the offshore wind farm to be tested; Step 2: predicting the probability distribution characteristics of the wind speed information and wind direction information based on the wind speed information and wind direction information obtained in step 1; Step 3: Optimize the microscopic layout of the offshore wind farm to be tested based on the probability distribution characteristics predicted in step 2 to obtain the target position of each unit in the offshore wind farm to be tested; Step 4: Obtain the current coordinates and translational velocity vector of each unit in the offshore wind farm to be measured; Step 5, calculate the position error and direction error corresponding to each unit; Step 6: Perform dynamic micro-layout of the offshore wind farm to be measured based on the obtained position error and direction error. In step 2, predict the probability distribution characteristics of the wind speed information and wind direction information based on the wind speed information and wind direction information obtained in step 1. The specific method is: The probability density distribution of wind speed and direction information is fitted using the Weibull distribution function to obtain scale parameters and shape parameters. The obtained scale parameters and shape parameters are combined with the prediction algorithm to predict the Weibull distribution law of wind speed and wind direction in the future set time period, and the probability distribution characteristics of wind speed information and wind direction information are obtained; In step 3, the microscopic layout of the offshore wind farm to be tested is optimized according to the probability distribution characteristics predicted in step 2 to obtain the target position of each unit in the offshore wind farm to be tested. The specific method is: Based on the probability distribution characteristics predicted in step 2, the optimization goal is to maximize the wind energy utilization throughout the year, season, or month. The optimization algorithm is used to optimize the micro-layout of the offshore wind farm to obtain the target position of each unit in the offshore wind farm. In step 6, a dynamic micro-layout of the offshore wind farm to be measured is performed based on the obtained position error and direction error. The specific method is: Determine the start and stop of the specific position control strategy of each unit based on the position error of each unit; When the judgment result is on, the pitch angle control value and yaw angle control value corresponding to each unit are calculated, and each unit is controlled to move to a circle with the target position as the center and r1 as the radius, where r1 is the preset threshold; When the judgment result is stop, the pitch angle control value and the yaw angle control value corresponding to each unit are set to zero, and the coordinate position of each unit is controlled to remain unchanged.

2. The dynamic microscopic layout method of an offshore wind farm according to claim 1, characterized in that: In step 5, the position error and direction error corresponding to each unit are calculated. The specific method is: Calculate the angle between the translational velocity vector of each unit and the x-axis, the distance between the current coordinate and the target position, and the angle between the displacement vector between the current coordinate and the target coordinate and the x-axis; Calculate the position error of each unit based on the distance between the current coordinates and the target position; The directional error of each unit is calculated based on the angle between the translational velocity vector and the x-axis, the displacement vector between the current coordinate and the target position, and the angle between the current coordinate and the x-axis.

3. The dynamic micro-layout method for an offshore wind farm according to claim 1, characterized in that: The start and stop of the specific position control strategy of each unit is determined based on the position error of each unit. The specific method is: If the current position control is in the enabled state, the logic quantity for switching the current position control strategy from enabled to disabled is: ; If the current position control is in the off state, the logic quantity for switching the current position control strategy from off to on is: ; in, and is the preset threshold, and ; is the position error.

4. A dynamic microscopic layout system for an offshore wind farm, characterized in that: The method according to claim 1, comprising: An information acquisition unit, used to acquire wind speed information and wind direction information of the offshore wind farm to be measured; a position acquisition unit, configured to predict probability distribution characteristics of wind speed information and wind direction information based on the obtained wind speed information and wind direction information; The microscopic layout of the offshore wind farm to be tested is optimized based on the predicted probability distribution characteristics to obtain the target position of each unit in the offshore wind farm to be tested; A parameter calculation unit is used to obtain the current coordinates and translational velocity vector of each unit in the offshore wind farm to be measured; Calculate the position error and direction error corresponding to each unit; The control unit is used to perform dynamic micro-layout of the offshore wind farm to be measured according to the obtained position error and direction error.

5. A dynamic microscopic layout device for an offshore wind farm, characterized in that: The method comprises a processor and a computer program that can be run on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 3 when executing the computer program.

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