Otimização de torres protendidas para turbinas eólicas

• Ano de defesa: 2021
• Autor(a) principal: Melo, Maurício Alves de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Torres eólicas; Concreto protendido; Algoritmo genético; Elementos finitos
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/59339

In recent years, traditional steel tubular towers have been replaced by prestressed concrete or hybrid towers to place wind turbines at great heights. Considering that the cost of these structures represents a significant portion of the cost of implementing a wind farm, the use of optimization techniques can strongly contribute to increase the competitiveness of wind energy. The objective of this work is to formulate a cost optimization model for externally prestressed wind turbine towers, using one-dimensional finite elements in nonlinear analyses of the structure. The tower is composed of tapered tubular segments of equal height. The design variables are the external diameters and thicknesses of the base of each segment and the number of prestressing tendons. The objective function is the cost of materials, and the constraints are related to geometric parameters, fundamental frequency, service limit states and ultimate stresses in concrete and prestressing steel. The optimization problem is solved using a Genetic Algorithm (GA) available in MATLAB optimization toolbox, and the structural analyses are performed through a non-linear finite element routine implemented in the same software, based on a formulation found in the literature. In the analyses, the reinforced concrete structure is modeled by plane frame elements, and the prestressing tendons are modeled by unbonded tendon elements. It was found that this formulation was able to represent the overall behavior of the structure with satisfactory accuracy and computational cost. Applications of the optimization model were made to towers with one and two segments, and the results indicated that this flexibilization in the geometry of the tower did not bring significant improvements to the cost of the solutions. The performance of the GA proved to be suitable in solving the optimization problem, so that cost reductions could be obtained, although, due to the simplifications adopted, the parameters provided by the optimizer should be assumed to be preliminary results, assisting the preliminary design stage of wind turbine towers.