- Opens: Tuesday 20 June 2023
- Number of places: 1
- Duration: 3 years (with potential to extend)
OverviewThe University of Strathclyde’s Department of Electronic & Electrical Engineering is offering a three-year fully funded PhD in the field of Artificial Intelligence (AI) for Smart Grids. This is based within the Intelligent Systems Team and will investigate distributed intelligence and the application of state-of-the-art Multi Agent System and related AI techniques to the control of distributed energy systems and smart grids.
Applicant Qualifications and Preferences:
- High-quality undergraduate or Masters degree in a relevant field (engineering, mathematical or scientific)
- Relevant experience in (at least one of) the related areas of AI: MAS, ML and DST
- Proactive initiative with the ability to work both independently and as part of a team
- Excellent organisational and communication skills
- Excellent written and spoken English
The University of Strathclyde’s Department of Electronic & Electrical Engineering is offering a three-year fully funded PhD in the field of Artificial Intelligence (AI) for Smart Grids. This is based within the Intelligent Systems Team (IST) and will investigate distributed intelligence and the application of state-of-the-art Multi Agent System (MAS) and related AI techniques to the control of distributed energy systems and smart grids.
The IST conducts industrially relevant research in collaboration with extensive domestic and international industry partners; hence, the successful candidate should expect extensive industrial engagement with the intention to deploy the resulting research within industry.
This studentship is part of a collaboration with Nanyang Technological University in Singapore. It will include regular engagement with the team within the School of Electrical and Electronic Engineering at NTU, and has the potential option/opportunity to spend time in Singapore. Any additional time would be fully funded and potentially extend the duration of the studentship.
A distributed intelligence MAS-based approach to the control of power system operation is becoming essential to deliver our Net Zero ambitions. Self-organising and autonomous control is required to integrate machine learning based forecasting of energy need, generation and utilisation with the complex protection, control and operation of electricity grids. MAS deliver opportunities for novel distributed intelligence and autonomy and complements areas that are concurrently the focus of the AI community. The successful candidate will investigate:
- interfacing MAS with machine learning (ML), to provide means of accurate power demand forecasting
- utilising Dynamical Systems Theory (DST) on MAS, to understand, validate and manage in real-time the non-linear behaviour of smart grids components
- developing hybrid MAS-ML-DST approaches to smart grid control to aid or potentially replace existing control and monitoring methods
The ultimate objective of the PhD is to demonstrate new distributed intelligence architectures that allow autonomous and self-organising control that delivers the flexible energy grids required for renewable generation, electrification of transport and heat, and integrated energy systems. The research will focus on the creation of advances in analytical techniques and automation with due consideration of their industrial application.
PhD tasks & responsibilities:
- Reviewing the state-of-the-art in MAS, ML and DST as applied in the power industry in order to subsequently scope the PhD and associated research tasks
- Fundamental research to support the development of related technologies
- Domestic and international conference attendance and presentation
- International collaboration with NTU in Singapore
- Engagement with industry to ensure relevance of the research
- Peer-reviewed academic journal publications
- The student would join the University of Strathclyde’s 60-credit postgraduate training programme leading to the Postgraduate Certificate in Researcher Professional Development
- The PhD student will gain a range of technical, practical and problem-solving skills required by the AI and energy industries. With the specific technical expertise gained, a wide range of career routes is possible including in the energy industry, AI and data companies/units, consultancy and government agencies. Further academic and research routes will also be possible
- The student will also benefit from interaction with other academics and PhD students within the IST’s active research programme, which includes multiple industrial partners and additional academic institutions
Full funding is available for UK-Home Students Only.
Overseas applicants must self-fund the difference between Home/EU and Overseas fees each year.
Students have the potential to earn additional income supporting teaching and laboratories (but this will not be sufficient to fund the additional overseas tuition fees).
Number of places: 1
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