This study presents experimental testing on a 13 m long glass-fibre epoxy composite wind turbine blade. The results of the test were used to calibrate finite element models. A design optimisation study was then performed using a genetic algorithm. The goal of the optimisation was to minimise the material used in blade construction and, thereby, reduce the manufacturing costs. The thickness distribution of the composite materials and the internal structural layout of the blade were considered for optimisation. Constraints were placed on the objective based on the stiffness of the blade and the blade surface stresses. A variable penalty function was used with limits derived from the blade test and the structural layout of the turbine. The model shows good correspondence to the test results (blade mass within 6% and deflection within 9%) and the differences between test and model are discussed in detail. The genetic algorithm resulted in five optimal blade designs, showing a reduction in mass up to 24%. Structural modelling in combination with numerical search algorithms provide a powerful tool for designers and demonstrates that the reader can have confidence in the claimed potential savings when the reference blade models are calibrated against physical test data.
Structural optimisation of a wind turbine blade is presented in this work. The optimisation was performed using a multi-objective genetic algorithm and finite element modelling to determine the optimal structural design for a glass fibre-reinforced polypropylene composite blade. A candidate blade design from the Pareto efficient set was manufactured and tested for a range of structural characteristics. Static testing was carried out using a Whiffletree test rig and a laser scanner was used to determine the deflection of the blade to a high degree of accuracy. The finite element model results for the custom-made design are compared to the measured blade response. The FE model predictions for strains, mass and natural frequencies are in general agreement with the test results; however, notable deviations in the deflections predictions are attributed to modifications to the blade for manufacture and the shell-based modelling approach. The differences are discussed in detail and recommendations for future design work are outlined. The test results of the bespoke blade are also compared to two additional designs to determine the level of improvement afforded by the genetic algorithm approach. The bespoke glass fibre blade demonstrated an improvement in tip deflection of 16% relative to the original blade design.
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