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PhD studentship: ICT and Control for Aggregated Demand Response

Teesside University

Qualification Type: PhD
Location: Middlesbrough
Funding for: UK Students, EU Students, International Students
Funding amount: This fully-funded PhD studentship covers tuition fees for the period of a full-time PhD registration of up to four years and provides an annual tax-free stipend of £18,622 for three years subject to satisfactory progress.
Hours: Full Time
Placed On: 12th June 2024
Closes: 5th July 2024
Reference: RDS

Supervisory team: Professor Michael Short, Dr Geetika Aggarwal (Teesside University);

Professor Raj Naidoo, Professor Xianming Ye (University of Pretoria)

Outline

An opportunity has arisen to support a fully-funded PhD studentship in the area of Smart Energy Systems – Aggregated Demand Response (ADR). The PhD candidate will explore flexible and scaleable ICT and control system achitectures for practical implementation of ADR in the South African and UK contexts. The research project proposes to research, develop, implement and test control and informatics concepts for an energy management system (EMS) for ADR and renewables integration. The EMS will offer new integrated approaches – based upon recent research in system-of-systems concepts and distributed reinforcement learning – for load and event forecasting, optimization of multiple buildings/assets with integrated photovoltaics, wind turbines, battery storage, hydrogen, and HVAC. The project involves modelling and simulation and will explore the possibility of limited practical implementation and experimentation.

The system is to be principally piloted at the Campus of the University of Pretoria, South Africa and the Net Zero Industry Innovation Center (NZIIC) at Teesside University in the UK. Demonstration use cases involving multiple residential office spaces to improve energy efficiency, enable better integration of local renewable resources (solar, wind) and HVAC cooling resources in real-world practical situations will be carried out. The student will also focus upon calibrated and HIL-based simulation work in NZIIC. The PhD candidate will have a suitable background in engineering and/or analytics/data science, and ideally have familiarity with software platforms such as Matlab/Simulink. The candidate will be jointly supervised by staff in both Teesside University (Professor Michael Short and Dr Geetika Aggarwal) and in Pretoria (Professor Raj Naidoo and Professor Xianming Ye). The student will be hosted by Teesside University and will visit Pretoria and demonstration sites in both countries during the course of the studentship (dependent upon visa requirements for international travel).

Funding eligibility

This fully-funded PhD studentship covers tuition fees for the period of a full-time PhD registration of up to four years and provides an annual tax-free stipend of £18,622 for three years subject to satisfactory progress.

Entry requirements

Applicants should hold or expect to obtain a good honours degree (2:1 or above) in a relevant discipline. A master’s level qualification in a relevant discipline is desirable, but not essential.  International students will be subject to the standard entry criteria relating to English language ability, Academic Technology Approval Scheme (ATAS) clearance and where relevant, UK visa requirements and procedures.

Research at Teesside

As a Teesside University research student, you will join a growing and dynamic research community, allowing you to share your experiences, insight and inspiration with fellow researchers. You will benefit from our academic expertise and be supported through a strong programme of research training. You will be offered opportunities and support at each stage of your research degree.

Our research is designed to have impact and to influence policy and practice within our region, the UK and beyond. We work with external organisations to anticipate and respond to research needs, and to put our research into practice in sectors as diverse as the arts, engineering, healthcare and computing. PhD students are encouraged to work with their supervisors to explore the potential impact of their work.

 

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