[School of Engineering PhD Scholarships] Distributed adaptive optimal control of offshore renewable energy farms

About the project

About the Project Oceans provide abundant offshore renewable energy (ORE) resources, mainly including wind, wave, and tidal energy. ORE converters are typically attached to floating platforms moored to the seabed, enabling the converters to harness abundant and consistent energy in deep sea, and additionally offer benefits such as reduced environmental and ecosystem impact, economic land use, and minimal visual/noise disruption. Current ORE research focuses on the design and control of individual devices. The modelling and control of an ORE farm is still at its infancy and many technical challenges need to be resolved. This project aims to develop the next-generation ORE farm control framework and a control-informed co-design platform that integrates farm layout and device design into the control strategies, aiming to substantially reduce the Levelized Cost of Energy (LCOE) and enhance safe farm operations by optimally balancing three critical factors: energy capture maximization, platform stabilization, and cost reduction. Major theoretical methods will be developed to tackle the fundamental large-scale modelling, optimisation and control problems for ORE farm applications. The student will be expected to have a solid background in Engineering (especially control system designs), strong mathematical and numerical simulation skills. A good knowledge of MATLAB/SIMULINK will be desirable. 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 Control Systems or a Engineering discipline directly relevant to the PhD (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in Control Systems or a Engineering discipline directly relevant to the PhD (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