4.7 Article

Optimization of radial inflow wind turbines for urban wind energy harvesting

期刊

ENERGY
卷 202, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.117772

关键词

Wind turbine; Radial inflow wind turbine; Energy in buildings; Design optimization; CFD; Machine learning

资金

  1. Izmir Katip Celebi University [2016-ONP-MUMF-0030]

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Radial (inflow) turbines with volutes have received limited attention in the body of literature for open-field wind harvesting. Few existing data in the literature indicate low maximum C-p, around 0.1. This study pursues demonstration of competitive radial wind turbines (RWT) towards exploring their potentials and increase the alternatives for a future urban energy planner. RWT may have advantages in adapting the renewable energy concept into buildings due to their an order-of-magnitude lower rotational speeds compared to propeller turbines, enclosed rotors and discharge of air uniquely from the top of the turbine (therefore the building). Moreover, such features may enable low-noise and fatigue-free rotors made of less durable but recyclable materials, crucial for acoustical comfort, safety and sustainability in urban areas. Design exploration over the complex 3D flowfleld of the turbine is pursued by machine learning algorithms coupled with Computational Fluid Dynamics simulations. With the achieved peak C-p of 0.29 at Re-c = 1.7 x 10(5), 103% improvement is attained relative to the existing RWTs with identical simulation methodologies. A sensitivity analysis revealed the most important parameters. The optimized turbine is compared with traditional alternatives, and it was elucidated that RWT is a competitive alternative among conventional alternatives with the described additional fundamental advantages. (C) 2020 Elsevier Ltd. All rights reserved.

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