Open AccessOptimal tuned mass dampers for wind turbines using a Sigmoid satisfaction function‐based multiobjective optimization during earthquakes
Author(s) -
Chen Xin,
Kareem Ahsan,
Xu Guoji,
Wang Hao,
Sun Yong,
Hu Liang
Publication year - 2021
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.2623
Subject(s) - sigmoid function , particle swarm optimization , multi objective optimization , tuned mass damper , weighting , damper , wind power , benchmark (surveying) , computer science , turbine , engineering , control engineering , artificial neural network , algorithm , medicine , mechanical engineering , electrical engineering , geodesy , machine learning , radiology , geography
Abstract Recent installation of many wind turbines in earthquake‐prone areas worldwide has increased concerns regarding their seismic performance. This study introduces a multiobjective optimization design method using a modified Sigmoid satisfaction function to efficiently minimize the seismic response by installing tuned mass dampers (TMDs) on wind turbines. Inspired by the human decision‐making process, the modified Sigmoid function was utilized to improve the satisfaction function and balance the optimization objectives. Incorporating the particle swarm optimization algorithm resulted in lower sensitivity to the combination weighting factors and significantly reduced the effort required to calibrate the weighting factors for any practical multiobjective optimization problem. To verify the efficacy of the proposed methodology, a TMD was designed on a National Renewable Energy Laboratory (NREL) 5‐MW benchmark wind turbine, with constraints on both the top displacement and TMD stroke as design objectives. The results were compared to those obtained using the conventional linear weighted sum method, thereby highlighting the advantages of the proposed method. The scope of application of the proposed method is further demonstrated by a more complex TMD design problem involving 13 design objectives with typical seismic excitations.