Wind Turbine Performance Assessment and Condition Monitoring with Performance Index

Author(s):  
Xiangyu Zhou ◽  
Xin Huang ◽  
Zhulin Dong ◽  
Weizhi Li ◽  
Minghao Jiang
2021 ◽  
Vol 3 (8) ◽  
Author(s):  
M. Niyat Zadeh ◽  
M. Pourfallah ◽  
S. Safari Sabet ◽  
M. Gholinia ◽  
S. Mouloodi ◽  
...  

AbstractIn this paper, we attempted to measure the effect of Bach’s section, which presents a high-power coefficient in the standard Savonius model, on the performance of the helical Savonius wind turbine, by observing the parameters affecting turbine performance. Assessment methods based on the tip speed ratio, torque variation, flow field characterizations, and the power coefficient are performed. The present issue was stimulated using the turbulence model SST (k- ω) at 6, 8, and 10 m/s wind flow velocities via COMSOL software. Numerical simulation was validated employing previous articles. Outputs demonstrate that Bach-primary and Bach-developed wind turbine models have less flow separation at the spoke-end than the simple helical Savonius model, ultimately improving wind turbines’ total performance and reducing spoke-dynamic loads. Compared with the basic model, the Bach-developed model shows an 18.3% performance improvement in the maximum power coefficient. Bach’s primary model also offers a 12.4% increase in power production than the initial model’s best performance. Furthermore, the results indicate that changing the geometric parameters of the Bach model at high velocities (in turbulent flows) does not significantly affect improving performance.


2021 ◽  
pp. 2813-2823
Author(s):  
Firas A. Hadi ◽  
Zaid F. Makki ◽  
Rafa A. Al-Baldawi

The main objective of this paper is present a novel method to choice a certain wind turbine for a specific site by using normalized power and capacity factor curves. The site matching is based on identifying the optimum turbine rotation speed parameters from turbine performance index (TPI) curve, which is obtained from the higher values of normalized power and capacity factor curves. Wind Turbine Performance Index a new ranking parameter, is defined to optimally match turbines to wind site. The relations (plots) of normalized power, capacity factor, and turbine performance index versus normalized rated wind speed are drawn for a known value of Weibull shape parameter of a site, thus a superior method is used for Weibull parameters estimation which is called Equivalent Energy Method (EEM).


2014 ◽  
Vol 140 (4) ◽  
pp. 06014001
Author(s):  
Y. Ditkovich ◽  
A. Kuperman ◽  
A. Yahalom ◽  
M. Byalsky

2012 ◽  
Vol 45 ◽  
pp. 86-95 ◽  
Author(s):  
Edzel Lapira ◽  
Dustin Brisset ◽  
Hossein Davari Ardakani ◽  
David Siegel ◽  
Jay Lee

Author(s):  
Yuri Ditkovich ◽  
Alon Kuperman ◽  
Asher Yahalom ◽  
Michael Byalsky ◽  
Yael Ditkovich ◽  
...  

Author(s):  
Ravi Kumar Pandit ◽  
David Infield

Loss of wind turbine power production identified through performance assessment is a useful tool for effective condition monitoring of a wind turbine. Power curves describe the nonlinear relationship between power generation and hub height wind speed and play a significant role in analyzing the performance of a turbine.Performance assessment using nonparametric models is gaining popularity. A Gaussian Process is a nonlinear, non-parametric probabilistic approach widely used for fitting models and forecasting applications due to its flexibility and mathematical simplicity. Its applications extended to both classification and regression related problems. Despite promising results, Gaussian Process application in wind turbine condition monitoring is limited.In this paper, a model based on a Gaussian Process developed for assessing the performance of a turbine. Here, a reference power curve using SCADA datasets from a healthy turbine is developed using a Gaussian Process and then was compared with a power curve from an unhealthy turbine. Error due to yaw misalignment is a standard issue with a wind turbine, which causes underperformance. Hence it is used as case study to test and validate the algorithm effectiveness.


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