Multi-objective Optimisation of Floating Offshore Windfarms

Project description 

The drive to reduce our dependency on fossil fuels has led to rapid growth in the renewable energy sector, particularly with respect to offshore wind power. The efficacy of near-shore static wind turbines (OWTs) has been extensively demonstrated; approximately 10% of power generated in Q1 of 2019 came from offshore wind, and the UK Government seeks to increase this to 30% by 2030. 

Evolutionary computation has been widely applied to the design of OWT arrays. Recently, attention has moved to the design of floating offshore wind turbines (FOWTs) which can be placed in deeper water to take advantage of stronger wind conditions. This project will explore multi-objective techniques for optimising the design of FOWT arrays such that maximal benefit is achieved for the minimum possible cost and at the minimum possible environmental impact. 

The optimisation of static OWTs has been extensively studied. FOWT array optimisation poses a substantially more complex problem as it requires the use of a more complex model capable of incorporating the motion of the turbines. This project is an interdisciplinary collaboration between Computer Science and Mathematics, and would suit a candidate from either background. The successful applicant will explore the development of a model of FOWT positions that can be used in combination with a static OWT model to predict the output and impact of FOWT arrays. EC techniques will be used to optimise the placement of turbines within a floating array, with the model providing the measure of solution quality.

Eligibility 

Applicants should have (at least) a first or upper second class honours degree in an appropriate subject and preferably a relevant MSc or MRes qualification. 

The studentship is supported for 3.5 years and includes full home/EU tuition fees plus a stipend of £15,285 per annum. The studentship will only fully fund those applicants who are eligible for home/EU fees with relevant qualifications. Applicants normally required to cover overseas fees would have to cover the difference between the home/EU and the overseas tuition fee rates (approximately £12,405 per annum).

If you wish to discuss this project further informally, please contact Dr David Walker david.walker@plymouth.ac.uk. However, applications must be made in accordance with the details shown below.

General information about applying for a research degree at University of Plymouth is available at: https://www.plymouth.ac.uk/student-life/your-studies/doctoral-college/applicants-and-enquirers . You can apply via the online application available on the link above and by clicking 'Apply now'.

Please mark your application FAO Doctoral College and clearly state that you are applying for a PhD studentship within the School of Engineering, Computing and Mathematics.

For more information on the admissions process contact the Doctoral College doctoralcollege@plymouth.ac.uk.

The closing date for applications is 12 noon on Friday 1 May 2020. Shortlisted candidates will be invited for interview in the last week of May. We regret that we may not be able to respond to all applications. Applicants who have not received an offer of a place by the 2nd week of June should consider their application has been unsuccessful on this occasion.