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CPOTE2022 logo
7th International Conference on
Contemporary Problems of Thermal Engineering
Hybrid event, Warsaw | 20-23 September 2022

Abstract CPOTE2022-1135-A

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Rotor shape optimisation of novel Savonius type wind turbine with reduced order models and evolutionary algorithms

Tomasz KRYSIŃSKI, Silesian University of Technology, Poland
Zbigniew BULIŃSKI, Silesian University of Technology, Poland
Łukasz MARZEC, Silesian University of Technology, Poland
Jakub TUMIDAJSKI, Silesian University of Technology, Poland

As the wind energy sector rapidly expands both in popularity and affordability the paper presents an attempt to improve the design of a drag-based Savonius like vertical axis wind turbine (VAWT) design. The utilised optimisation methodology involved high accuracy computational fluid dynamics model of an operating wind turbine combined with differential evolution optimisation algorithm (DE). Evaluations of the wind turbine performance has been carried out using unsteady two-dimensional numerical model. In order to reduce computational time needed to evaluate turbine performance and make the turbine shape optimisation possible, reduced order method (ROM) in a form of repeatedly trained neural network (NN) was developed. The design of the wind turbine blades has been parametrised with low order Bezier curves to allow unobstructed exploration of the design space and ensure the smoothness of the blades shape. Contributing to the aimed holistic approach to newly designed VAWT the optimisation runs have been performed for various operating regimes of the wind turbine, known commonly to be suboptimal for the Savonius type wind turbines. The performance of the optimised wind turbine designs have been verified against previously known optimised Savonius like wind turbine designs. As a result of the performed optimisation, significant increase in the value of energy conversion efficiency has been predicted, reaching as high as 35%.

Keywords: Design optimisation, Reduced order modelling, Computational fluid dynamics (CFD), Evolutionary algorithm, Vertical axis wind turbine
Acknowledgment: The financial support of The National Science Centre, Poland, within OPUS scheme under contract 2017/27/B/ST8/02298 is gratefully acknowledged herewith.