Optimal tuned mass dampers for wind turbines using a Sigmoid satisfaction function‐based multiobjective optimization during earthquakes

Abstract

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.

Keywords

• multiobjective optimization
• particle swarm algorithm
• satisfaction function
• tuned mass damper (TMD)
• wind turbine