https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2564

Review of control strategy of large horizontal-axis wind turbines yaw system

The widespread availability of wind turbine operation data has considerably boosted the research and the applications for wind turbine monitoring. It is well established that a systematic misalignment of the wind turbine nacelle with respect to the wind direction has a remarkable impact in terms of down-performance, because the extracted power is in first approximation proportional to the cosine cube of the yaw angle. Nevertheless, due to the fact that in the wind farm practice the wind field facing the rotor is estimated through anemometers placed behind the rotor, it is challenging to robustly detect systematic yaw errors without the use of additional upwind sensory systems. Nevertheless, this objective is valuable because it involves the use of data that are available to wind farm practitioners at zero cost. On these grounds, the present work is a two-steps test case discussion. At first, a new method for systematic yaw error detection through operation data analysis is presented and is applied for individuating a misaligned multi-MW wind turbine. After the yaw error correction on the test case wind turbine, operation data of the whole wind farm are employed for an innovative assessment method of the performance improvement at the target wind turbine. The other wind turbines in the farm are employed as references and their operation data are used as input for a multivariate Kernel regression whose target is the power of the wind turbine of interest. Training the model with pre-correction data and validating on post-correction data, it is estimated that a systematic yaw error of 4 ∘ affects the performance up to the order of the 1.5% of the Annual Energy Production.

https://www.mdpi.com/1996-1073/13/9/2351/pdf

Wind Turbine Systematic Yaw Error: Operation Data Analysis Techniques for Detecting It and Assessing Its Performance Impact

Horizontal axis wind turbine yaw differential error reduction approach

Experimental study on the characteristics of wind turbine wake field considering yaw conditions

Matching contrastive learning: An effective and intelligent method for wind turbine fault diagnosis with imbalanced SCADA data

Progress and challenges on blade load research of large-scale

Active wake management (AWM) via yaw control has been discussed in recent years as a potential way to improve the power production of a wind farm. In such a technique, the wind turbines will be required to work frequently at misaligned yaw angles in order to reduce the vortices in the wake area behind the turbines. However, today, it is still not very clear about how yaw operation affects the dynamics and power generation performance of the wind turbines. To further understand the effects of yaw operation, numerical research is conducted in this paper. In the study, the optimal size of the flow field used in the computational fluid dynamics (CFD) calculation was specifically discussed in order to obtain an efficient numerical model to quickly and accurately predict the dynamics and the performance of the turbines. Through this research, the correlation between the blade loads during yaw and non-yaw operations is established for aiding yaw control, and the blade loads and power generation performances of the wind turbine during yaw operation under different wind shear and blade deflection conditions are analyzed for understanding the effects of yaw operation. It is found that the optimal size of the flow field for performing efficient and accurate CFD calculations does exist. The misaligned yaw operation generally tends to decrease the loads acting on the blade. However, the aerodynamic energy captured by the turbine rotor and blade loads during yaw operation is not only dependent on the yaw angle of the rotor but is also affected by wind speed, rotor speed, the pitch angle of the blades, blade deflection, and wind shear. Particularly, it is interestingly found that wind shear can cause undesirable fluctuation of the power, which will challenge the power quality of the wind farm if no measures are taken.

/pdf/further-study-on-the-effects-of-wind-turbine-yaw-operation-4kp0eyba3v.pdf

Further Study on the Effects of Wind Turbine Yaw Operation for Aiding Active Wake Management

The primary wind turbines’ in-service performance evaluation method is mining and analyzing the SCADA data. However, there are complex mathematical and physical relationships between multiple operating parameters, and so far, there is a lack of systematic understanding. To solve this issue, the distribution of wind turbines’ operating parameters was first analyzed according to the characteristics of the energy flow of wind turbines. Then, the correlation calculation was performed using the Spearman correlation coefficient method based on the minute-level data and second-level data. According to the numerical characteristics of the nacelle vibration acceleration, the data preprocessing technology sliding window maximum (SWM) was proposed during the calculation. In addition, taking temperature correlation as an example, two-dimensional scatter (including single-valued scatter) and three-dimensional scatter features were combined with numerical analysis and physical mechanism analysis to understand the correlation characteristics better. On this basis, a quantitative description model of the temperature characteristics of the gearbox oil pool was constructed. Through this research work, the complex mathematical and physical relationships among the multi-parameters of the wind turbines were comprehensively obtained, which provides data and theoretical support for the design, operation, and maintenance.

/pdf/correlation-investigation-of-wind-turbine-multiple-operating-dnrumnbe.pdf

Correlation Investigation of Wind Turbine Multiple Operating Parameters Based on SCADA Data

In large-scale wind turbines, the force state of the pitch system greatly influences safe operation and service life. This paper provides a novel method to estimate blade pitch load, bearing friction torque, and motor pitch torque. In this method, the force equilibrium equations are established by investigating the force of the pitch system under multiple operating conditions. The multidimensional BIN method is employed to classify the supervisory control and data acquisition (SCADA) data of wind turbines into several intervals. The multidimensional scatter data is processed in a single-valued way. Then, the estimating model of the pitch system forces is established by combining the obtained data and the equilibrium equations. Taking a 2 MW wind turbine as an example, the variation characteristics of blade pitch load, bearing friction torque, and motor pitch torque under multiple operating conditions are analyzed. Some interesting and valuable conclusions are obtained. For example, when the wind speed increases, the blade pitch load increases significantly in the maximum wind energy tracking region, but there is no obvious change in the observed constant power output region. The wind speed and azimuth have little effect on the bearing friction torque. The variation trend of motor pitch torque is consistent with that of blade pitch load in the maximum wind energy tracking region.

/pdf/research-on-force-model-and-characteristics-of-large-wind-22unvewq.pdf

Research on force model and characteristics of large wind turbine pitch system based on SCADA data

The key problem to be solved in the process of wind turbine (WT) operation and maintenance is to obtain the wind turbine performance accurately. The power curve is an important indicator to evaluate the performance of wind turbines. How to model and obtain the power curve of wind turbines has always been one of the hot topics in research. This paper proposes a novel idea to get the actual power curve of wind turbines. Firstly, the basic data preprocessing algorithm is designed to process the zero value and null value in the original supervisory control and data acquisition (SCADA) data. The moving average filtering (MAF) method is employed to deal with the wind speed, the purpose of which is to consider the comprehensive result of wind on the wind turbine power in a certain period. According to the momentum theory of the ideal wind turbine and combined with the characteristics of the anemometer installation position, the deviation between the measured wind speed and the actual wind speed is approximately corrected. Here, the influence of dynamic changes in air density is also considered. Then, the Gaussian fitting algorithm is used to fit the wind-power curve. The characteristics of the power curve before and after wind speed correction are compared and analyzed. At the same time, the influence of the parameter uncertainty on the reliability of the power curve is considered and investigated. Finally, the characteristics of the power curves of four wind turbines are compared and analyzed. The research results show that among these power curves, WT3 and WT4 are the closest, WT2 is the next, and WT1 has the farthest deviation from the others. The research work provides a valuable basis for on-site performance evaluation, overhaul, and maintenance of wind turbines.

/pdf/study-on-obtaining-real-power-curve-of-wind-turbines-using-5rjz6dh4.pdf

Mimi Li

Papers

Progress and challenges on blade load research of large-scale

Further Study on the Effects of Wind Turbine Yaw Operation for Aiding Active Wake Management

Correlation Investigation of Wind Turbine Multiple Operating Parameters Based on SCADA Data

Research on force model and characteristics of large wind turbine pitch system based on SCADA data

Study on Obtaining Real Power Curve of Wind Turbines Using SCADA Data