A Hierarchical Data–driven Wind Farm Power Optimization Approach Using Stochastic Projected Simplex Method

2021 ◽  
pp. 1-1
Author(s):  
Zhiwei Xu ◽  
Hua Geng ◽  
Bing Chu
Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1796
Author(s):  
Francesco Castellani ◽  
Davide Astolfi

This Special Issue collects innovative contributions in the field of wind turbine optimization technology. The general motivation of the present Special Issue is given by the fact that there has recently been a considerable boost of the quest for wind turbine efficiency optimization in the academia and in the wind energy practitioners communities. The optimization can be focused on technology and operation of single turbine or a group of machines within a wind farm. This perspective is evidently multi-faced and the seven papers composing this Special Issue provide a representative picture of the most ground-breaking state of the art about the subject. Wind turbine power optimization means scientific research about the design of innovative aerodynamic solutions for wind turbine blades and of wind turbine single or collective control, especially for increasing rotor size and exploitation in offshore environment. It should be noticed that some recently developed aerodynamic and control solutions have become available in the industry practice and therefore an interesting line of development is the assessment of the actual impact of optimization technology for wind turbines operating in field: this calls for non-trivial data analysis and statistical methods. The optimization approach must be 360 degrees; for this reason also offshore resource should be addressed with the most up to date technologies such as floating wind turbines, in particular as regards support structures and platforms to be employed in ocean environment. Finally, wind turbine power optimization means as well improving wind farm efficiency through innovative uses of pre-existent control techniques: this is employed, for example, for active control of wake interactions in order to maximize the energy yield and minimize the fatigue loads.


Fuel ◽  
2021 ◽  
Vol 306 ◽  
pp. 121647
Author(s):  
Jian Long ◽  
Siyi Jiang ◽  
Renchu He ◽  
Liang Zhao

2022 ◽  
Vol 251 ◽  
pp. 113479
Author(s):  
Hua Huang ◽  
Chunliang Xue ◽  
Wei Zhang ◽  
Mengxue Guo

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 49990-50002 ◽  
Author(s):  
Qian Tao ◽  
Chunqin Gu ◽  
Zhenyu Wang ◽  
Joseph Rocchio ◽  
Weiwen Hu ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document