Big Data Driven Deep Learning for Design of Electrical Power Distribution Systems with Renewables, Storage and Electric Transport (RDS19-SSEE)

Fully funded PhD studentships for October 2019
As part of ongoing investment into areas of research strength, Teesside University is pleased to offer a number of fully-funded PhD studentships to exceptional doctoral candidates to commence in October 2019. The School of Science, Engineering and Design invites applications for fully-funded full-time PhD studentships in the following research projects:

Smart Systems and Energy Informatics Research Group
https://research.tees.ac.uk/en/organisations/smart-systems-and-energy-informatics-research-group

RDS19-SSEE Big Data Driven Deep Learning for Design of Electrical Power Distribution Systems with Renewables, Storage and Electric Transport

Under current electricity trading framework distribution network operators (DNOs) buy power in the wholesale market at volatile prices and retails sell it at fixed tariffs to consumers. Volatility of prices is the result of fluctuations in day-ahead and intraday markets. With smart meters, large data sets of time-resolved customer consumption data is becoming available to DNOs. Electrical Vehicles(EVs) are a source of not just journey data, but also charging profiles. The contribution of renewables to electricity mix is expected to be about 50% by 2030. The project will develop Big Data processing approaches which form the basis for developing new power trading market concepts for DNOs based on a literature review of the state of the art in this domain and other fields of Big Data. Deep learning algorithms will then be customised and applied for activities such as short term demand/generation forecasting and real-time network constraint identification to realise the new market concepts.

Supervisor: Dr Gobind Pillai
https://research.tees.ac.uk/en/persons/gobind-gopalakrishna-pillai

Applicants should use the link provided against the project area to the Research Centres and Research Groups identified and to the named supervisors for each project, to ensure that their application and proposal fits with the studentship offered.
Funding Eligibility
The studentship will cover tuition fees and provide an annual tax-free stipend of £15,000 for three years, subject to satisfactory progress. Applications are welcome from strong UK and International students.
Entry Requirements
Applicants should hold or expect to obtain a good honours degree (2:1 or above) and/or Masters level qualification in a relevant discipline, as well as a demonstrable understanding of the area; further details of the expected background may appear in the specific project details. International students would be subject to the standard entry criteria relating to English language ability, ATAS clearance and, when relevant, Tier 4 procedures.
How to Apply
Applicants should apply online for this opportunity. Please use the Full Time Funded PhD online application form. When asked to specify funding select “other” and enter the relevant studentship code given against the project that you applying for in the field required. You should also ensure that you add the studentship code as well as the title of the project on the proposal that you will need to upload when applying. If you would like to apply for more than one project, you will need to complete a further application form and specify the relevant title and code for each application to a topic or project. Please note that applications for funded studentships that do not quote the studentship title AND the Project ID on the proposal will be invalid and your application may not be considered for the appropriate funding.

For academic enquiries, please contact the relevant supervisor or staff in the research area directly. For administrative enquiries, contact [Email Address Removed].
Research at Teesside
The successful candidate will be expected to participate fully in research group and centre activities, including training sessions and workshops, and will become a member of the University’s wider postgraduate research community. Mentoring and support will be provided for the development of a strong academic and professional CV during the PhD.
Key Dates
Closing date for applications is 5pm on Monday 29 April 2019

We envisage that interviews will take place in May 2019

Successful applicants will be expected to start on 7th October 2019