Dr S Jiang, Prof S Kollias, Prof C Bingham
No more applications being accepted
Funded PhD Project (European/UK Students Only)
About the Project
This project will focus on efficient AI-based energy management of smart grids to reduce energy costs and lower carbon footprint.
With population growth and economic development, the total world energy consumption will increase 50% between 2018 and 2050, according to the US energy information administration (EIA). Great energy efficiency measures must be taken now to address the energy crisis and safeguard the future of energy. Smart grid is the enabling technology for this challenge as it allows two-way communication between energy suppliers and their customers, can automatically balance power supply and demand in the distribution grid, deliver a deeper insight into energy consumption and efficiently integrate renewable energy.
This project will focus on efficient AI-based energy management of smart grids to reduce energy costs and lower carbon footprint. In particular, it will investigate novel AI-based decision-making strategies trade-offing the profit of energy suppliers and the cost of energy users. This work involves computational modelling of smart grids in different scenarios and optimisation of energy management for each scenario. The project will develop an AI-based decision-making tool for smart grids that will be experimentally tested and analysed in order for academic and commercial use.
The successful candidate will work with the Machine Learning group at the School of Computer Science and School of Engineering at the University of Lincoln. This is an exciting opportunity for developing a career in AI for smart energy.
Specific requirements for candidates
Interested applicants should hold, at a minimum, a 2.1 degree in AI, computer science, mathematics, engineering, or any other relevant discipline and are encouraged to demonstrate any skills and/or experience relevant to the project subject area(s) of interest. They must evidence an ability to engage in scientific research and to work collaboratively as part of a team, must be able to carry out mathematic modelling for practical problems, and have a good knowledge of operational research and optimisation approaches, such as evolutionary computation, and multi-criteria decision making. They are expected to have good communication skills in written and spoken English in order to work with both computer scientists and engineers, to present research findings in workshops/conferences, and to publish papers in high-quality journals.
How to apply
For the full application, please apply on the Lincoln website here: https://www.lincoln.ac.uk/home/engineering/dtpstudentships/
Eligibility
To be eligible for a full award a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship (with some further constraint regarding residence for education. For a fees only award, a Student must be ordinarily resident in a member state of the EU, in the same way as UK Students must be ordinarily resident in the UK. For further information regarding residence requirements, please see the regulations: https://www.ukri.org/files/funding/ukri-training-grant-terms-and-conditions-pdf/
Funding Notes
The University of Lincoln has received funding from the Engineering and Physical Sciences research Council to establish a Doctoral Training Partnership (DTP), which will provide skills training to foster the next generation of world-class research leadership in areas of strategic importance to both EPSRC and the University of Lincoln.
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