Adequacy evaluation of offshore wind farm considering wake effect

Author(s):  
Ziehen Zheng ◽  
Yang Fu ◽  
Shuai Shi
2021 ◽  
Vol 11 (1) ◽  
pp. 35-48
Author(s):  
Mohammed Amine Hassoine ◽  
Fouad Lahlou ◽  
Adnane Addaim ◽  
Abdessalam Ait Madi

The objective of this paper is to investigate the ability of analytical wake models to estimate the wake effects between wind turbines (WTs). The interaction of multiple wakes reduces the total power output produced by a large offshore wind farm (LOFWF). This power loss is due to the effect of turbine spacing (WTS), if the WTs are too close, the power loss is very significant. Therefore, the optimization of turbine positions within the offshore wind farm requires an understanding of the interaction of wakes inside the wind farm. To better understand the wake effect, the Horns Rev 1 offshore wind farm has been studied with four wake models, Jensen, Larsen, Ishihara, and Frandsen. A comparative study of the wake models has been performed in several situations and configurations, single and multiple wakes are taken into consideration. Results from the Horns Rev1 offshore wind farm case have  been evaluated and compared to observational data, and also  with the previous studies. The power output of a row of WTs is sensitive to the wind direction. For example, if a row of ten turbines is aligned with the 270° wind direction, the full wake condition of WTs is reached and the power deficit limit predicted by Jensen model exceeds 70%. When a wind direction changes only of  10° (260° and 280°), the deficit limit reduces to 30%. The obtained results show that a significant power deficit occurs when the turbines are arranged in an aligned manner. The findings also showed that all four models gave acceptable predictions of the total power output. The comparison between the calculated and reported power output of Horns Revs 1 showed that the differences ranged from - 8.27 MW (12.49%) to 15.27 MW (23.06%) for the Larsen and Frandsen models, respectively.


2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Binbin Zhang ◽  
Jun Liu

This paper proposed the SVD (singular value decomposition) clustering algorithm to cluster wind turbines into some group for a large offshore wind farm, in order to reduce the high-dimensional problem in wind farm power control and numerical simulation. Firstly, wind farm wake relationship matrixes are established considering the wake effect in an offshore wind farm, and the SVD of wake relationship matrixes is used to cluster wind turbines into some groups by the fuzzy clustering algorithm. At last, the Horns Rev offshore wind farm is analyzed to test the clustering algorithm, and the clustering result and the power simulation show the effectiveness and feasibility of the proposed clustering strategy.


Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8313
Author(s):  
Xin Liu ◽  
Lailong Li ◽  
Shaoping Shi ◽  
Xinming Chen ◽  
Songhua Wu ◽  
...  

Huaneng Rudong 300 MW offshore wind farm project is located in eastern China. The wake effect is one of the major concerns for wind farm operators, as all 70 units are plotted in ranks, and the sea surface roughness is low. This paper investigated the wake intensity by combining a field test and a numerical simulation. To carry out further yaw optimization, a Gaussian wake model was adopted. Firstly, a 3D Light Detection and Ranging device (LiDAR) was used to capture the features in both horizontal and vertical directions of the wake. It indicated that Gaussian wake model can precisely predict the characteristics under time average and steady state in the wind farm. The predicted annual energy production (AEP) of the whole wind farm by the Gaussian model is compared with the calculation result of the actuator line (AL)-based LES method, and the difference between the two methods is mostly under 10%.


2019 ◽  
Vol 9 (9) ◽  
pp. 1911
Author(s):  
Yuan-Kang Wu ◽  
Wen-Chin Wu ◽  
Jyun-Jie Zeng

Offshore wind farms will have larger capacities in the future than they do today. Thus, the costs that are associated with the installation of wind turbines and the connection of power grids will be much higher, thus the location of wind turbines and the design of internal cable connections will be even more important. A large wind farm comprises of hundreds of wind turbines. Modeling each using a complex model leads to long simulation times—especially in transient response analyses. Therefore, in the future, simulations of power systems with a high wind power penetration must apply the equivalent wind-farm model to reduce the burden of calculation. This investigation examines significant issues around the optimal design of a modern offshore wind farm layout and its equivalent model. According to a review of the literature, the wake effect and its modeling, layout optimization technologies, cable connection design, and wind farm reliability, are significant issues in offshore wind farm design. This investigation will summarize these important issues and present a list of factors that strongly influence the design of an offshore wind farm.


2019 ◽  
Vol 139 (4) ◽  
pp. 259-268
Author(s):  
Effat Jahan ◽  
Md. Rifat Hazari ◽  
Mohammad Abdul Mannan ◽  
Atsushi Umemura ◽  
Rion Takahashi ◽  
...  

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