Advanced Control Strategies for Renewable Energy system

About the project

About the Project Renewable energy systems are central to achieving the UK’s Net Zero goals, but their variability and interdependence pose major challenges for reliable operation. Addressing these challenges requires advanced control and optimisation methods that can coordinate generation, storage, and demand under uncertain conditions. This PhD project will focus on developing decentralised stochastic control strategies for renewable microgrids, with tidal energy as a key application example. The aim is to design control frameworks that explicitly consider uncertainty, improve efficiency and stability, and make renewable energy systems more resilient and scalable. What you will do Develop and analyse decentralised control algorithms for generation–storage–demand coordination. Incorporate stochastic modelling and optimisation to address uncertainty in renewable energy systems. Apply and test these methods in simulations of tidal and marine energy microgrids, with opportunities to connect to Scotland’s clean energy initiatives. Extend the approaches to other renewable and hybrid microgrids. Academic qualifications First class degree (minimum 2:1 classification) in one of the following areas: Control Engineering / Automation Electrical and Electronic Engineering (EEE) Energy Systems / Renewable Energy Engineering Mechanical Engineering with strong control/energy focus Computer Science with relevant experience in optimisation or simulation Applied Mathematics with interest in control and energy systems English language requirement IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online. Subject knowledge: Control theory Energy systems and renewable integration Probability and stochastic processes Mathematics for control and systems analysis Programming and simulation tools Essential attributes: Willingness to learn new methods in control, optimisation, and energy systems Strong motivation to contribute to clean energy and Net Zero research Ability to think critically and solve complex problems Capacity for independent research as well as teamwork Good written and verbal communication skills Commitment to completing a challenging long-term research project Desirable attributes: Prior research experience in control, optimisation, or renewable energy Familiarity with programming for simulation and data analysis (e.g. MATLAB, Python) Ability to connect theoretical methods with practical applications Experience in presenting research (e.g. conferences, seminars, or project reports) Interest in interdisciplinary collaboration across engineering and mathematics Enthusiasm for developing transferable skills and contributing to the research community APPLICATION CHECKLIST Completed application form CV 2 academic references, using the Postgraduate Educational Reference Form (download) Research project outline of 2 pages (list of references excluded). The outline may provide details about Background and motivation of the project. The motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results. Research questions or objectives. Methodology: types of data to be used, approach to data collection, and data analysis methods. List of references. The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support. Statement no longer than 1 page describing your motivations and fit with the project. Evidence of proficiency in English (if appropriate) To be considered, the application must use the advertised title as project title For informal enquiries about this PhD project, please contact y.zhou@napier.ac.uk Application Enquiries: https://www.napier.ac.uk/research-and-innovation/doctoral-college/application-guidance Application link : https://evision.napier.ac.uk/si/sits.urd/run/siwsso.go?mP9MDnTs1Rwm8ftb3WVhDhXtraMQwXSUMdHC9wIc34es5bJqXf

Research areas