Investigation of wake dynamics of Vertical Axis Wind Turbine farm layout in urban environment

About the Project

Summary of the proposed research :

Vertical axis wind turbines (VAWTs) also have an omnidirectional design characteristic, allowing these turbines to extract wind from any direction. VAWTs can be positioned much closer together on a farm and have been shown to produce approximately 8 times more power density than HAWTs for a similar land. The use of strategic spacing can allow a VAWT wind farm to increase the individual turbine efficiencies and improve the power density of the overall farm by taking advantage of the wake formation blades downstream of each turbine. In addition, wind turbines may be exposed to different environmental conditions, ranging from harsh icy types to deserts with sandstorms, where both extremes can affect the smoothness of the wind turbine blade. Such conditions can generate irregularities on the blade surface and increase roughness, subsequently affecting the flow field around the blade. Therefore, it is crucial to gain more insight into the effects of surface roughness on wind turbine blade aerodynamics and overall torque generation, hence the turbine performance. Computational fluid dynamics (CFD) modelling techniques and experiments were implemented to investigate the performance of wind turbines on a farm. However, there is a research gap in understanding both cluster and icing effects of VAWT farms to improve the efficiency of wind energy production, as land area and location are critical limitations to the size of a wind farm. Therefore, a comprehensive numerical model is required to enhance the understanding of wind farm design and optimisation.

The aim of the project is to accurately model and analyse the effect of icing on the aerodynamics of novel hybrid turbines in a wind farm to maximise the energy density. The specific objectives of the project are to:

• Develop three-dimensional Computational Fluid Dynamics (CFD) models of open and augmented rotor VAWT to investigate icing effect on turbine performance and wake formation in wind farm
• Predict the performance of VAWT at different operating blade surface conditions (the icing shape and ice accretion along the directions of blade chord and span) using multi objective goal driven optimisation and machine learning algorithms.
• Validation of Design of experiment (DOE) method and data analytics techniques predicted results of optimized design against wind tunnel experiments
• Develop an optimum wind farm design to maximize efficiency of single turbine and overall power density of wind farm at extreme icing conditions

How to apply:

For further information please contact: Dr Sheikh Z Islam at sheikh.islam@staffs.ac.uk

The applications should consist of a cover letter or personal statement of interest, and a CV.

Dr Sheikh Z Islam

Head of Engineering

School of Digital, Technology, Innovation & Business

University of Staffordshire

Stoke-on-Trent Campus

College Road

Stoke-on-Trent

ST4 2DE

The expected start dates are January and April 2026.

Entry Requirements:

Applicants should have a First- or Upper Second-Class UK honours degree, or equivalent, in a relevant discipline such Mechanical Engineering or Aerospace Engineering. An MSc with Distinction or Merit in a relevant subject is highly desirable. Knowledge or experience of computational fluid dynamics modelling & optimisation is advantageous.

The standard minimum IELTS Academic requirement is 6.5 overall with no less than 6.0 in each band. Some International students are also required to meet UKVI requirements for the appropriate study visa. A valid ATAS certificate (where required) must be secured as a prerequisite to enrolment.