Design Optimization of Tapered Steel Wind Turbine Towers by QPSO Algorithm

Abstract

Wind energy has become one of the most widely used alternative energy sources in recent years due to its clean and renewable character. In the context of increasing demand for new facilities, the cost of a wind turbine is a key factor for the success of new wind farms. The reduction of the amount of material used to build the wind turbine tower is one way to reduce the project cost. This work presents a methodology for the minimization of the weight of the tubular steel towers of wind turbines using a metaheuristic optimization algorithm. The diameters of the cross-section at the base and the top of the conical tower are considered as continuous design variables. Due to constructional aspects, the tower is manufactured in many segments, which wall thicknesses are taken as discrete design variables. Besides the dead load, the design considers the action of wind load, which is taken as an equivalent static force determined using the Brazilian standard NBR6123. The design constraints considered in this work are the maximum admissible displacements at the top of the tower under service condition, the tower's lowest natural frequency and the safety criteria for steel structures defined by the Brazilian standard NBR8800. The mixed-integer nonlinear optimization problem formulated for the structural design in this work is solved using the quantum particle swarm optimization algorithm (QPSO). On average, the QPSO solution was 12% lighter than designs based on other well-established algorithms in a comparative study. Nonetheless, no significant improvement was observed concerning the standard particle swarm optimization.