Evolutionary computing methodology for small wind turbine supporting structures

The paper presents a comprehensive, complex, numerical, optimization methodology (computational framework) dedicated for supporting structures of small-scale wind turbines. The small wind turbine (SWT) supporting structure is one of the key components determining the cost of such a device. Therefore, the supporting structure optimization will allow cost reduction and, hence, popularization of these devices around the world. The presented methodology is based on the following: single-objective (aggregation-approach to multi-objective problem) evolutionary algorithm driven optimization, finite-element structural analyses, estimation of wind energy capture efficiency (coupled aero-servo-elastic numerical simulations), and economic evaluation (based on real meteorological data). Then, the methodology is proposed for a guy-wired mast structure of an arbitrary chosen SWT model. The optimization of chosen design features of the structure is performed and as a result the optimal solution for given assumptions is presented and scaling factor for that case is identified (total mass of the foundations). The successful use of combined numerical methods (genetic algorithms, FE method analyses, coupled aero-servo-elastic numerical simulations, pre-/post-processing scripts, and economic evaluation models) is the main novelty of this work.