[School of Engineering PhD Scholarships] Optimisation of wind and tidal-stream turbine arrays using advanced wake and turbine-control algorithms

About the project

About the Project The generation of energy from fossil fuels which has prompted huge economic growth since the industrial revolution is now faltering under two major problems: climate change and international geopolitics. Overcoming these has driven a huge growth in renewable-energy technologies, of which two – wind and tidal-stream energy – the UK is particularly well positioned to exploit. However, just as for solar power, producing energy at a scale which is economically viable comes with its own problems: notably, visibility, large-scale land use and variability / unpredictability of resource, particularly for windpower. Thus, it is vital that any deployment and operation of turbines in an array be optimised, primarily for power per unit area, but also for cost and availability. For windpower, optimisation of the layout and operating points of an array under a representative sample of meteorological conditions means a large number of evaluations of an objective function, which must, therefore, be cheap to evaluate. This rules out the use of CFD (except, possibly, as an adjunct in wake-validation models) in favour of semi-analytical wake models and validated means of superposing them for multiple turbines. The project will consider the optimisation of layout and control of (onshore and offshore floating) wind and tidal turbine arrays and will produce the following. (1) Well-tested individual-wake and wake-superposition models for wind and tidal turbines. (2) Realistic models of turbine control – specifically, blade pitch and generator torque – and the resulting power and thrust coefficients. In some conditions we may choose to allow “altruistic” control – upstream turbines sacrificing potential wind resource to permit greater generation in the depths of the array. (3) Representative onset-flow conditions, reflecting realistic distributions of windspeed and direction. These will be probabilistically deployed – a recent MSc project showed that automatic optimisation for a discretely distributed windrose simply lined up the turbines to avoid the discrete wind directions considered! (4) A realistic cost model, including capital cost, operation (including fatigue and maintenance) and end-of-life costs. (5) A fast, efficient, multi-objective optimisation scheme (drawing on recent experiences with stochastic, biologically-inspired schemes such as genetic algorithms and particle-swarm optimisation). It will also be pragmatic – good, but not necessarily the best – allowing for realistic calculation times and inaccuracy in the model or onset-flow conditions without substantially compromising array performance. This project is expected to start in September 2027. Before you apply: We strongly recommend that you contact the supervisors for this project before you apply. How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Engineering Scholarships . If you don’t already have an applicant account, please follow the instructions here. . When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing the motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications . Please note late or incomplete applications will not be considered. Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status. We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder. Eligibility : The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in a discipline directly relevant to the PhD such as Engineering, Physics or Mathematics (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD such as Engineering, Physics or Mathematics (or international equivalent). This project will remain open until filled. If your application is submitted by 1 st November 2026, you can expect a decision by 18 th December 2026. If your application is submitted by 15 th January 2027, you can expect a decision by 30 th March 2027. Self or externally funded students can also be considered for this project. FSESoE

Research areas