Postgraduate research opportunities Fast computation for power system dynamic security assessment
ApplyKey facts
- Opens: Tuesday 19 April 2022
- Deadline: Monday 20 June 2022
- Number of places: 1
- Duration: 42 months
- Funding: Home fee, Equipment costs, Stipend
Overview
This project is aiming to investigate the use of techniques and methods for increasing computational speed for power system dynamic security assessment, with focus on representing the increasingly complex dynamic behaviour of power systems. The PhD project will explore applications of machine learning and quantum computing in this area.Eligibility
To be considered for the project, candidates must:
- hold, or be about to gain preferably a 1st class UK BEng Honours or MEng degree or MSc with Distinction, or equivalent, in Electronic / Electrical Engineering, Computer & Information Sciences, Mathematics or a related subject.
- Be a UK or eligible EU national and adhere to EPSRC eligibility criteria or an exceptional international candidate.
The successful candidate will preferably have:
- good understanding of power system stability and dynamic behaviour
- programming skills
- knowledge and understanding of machine learning methods
- excellent analytical skills
- excellent communication skills
International students can apply, however should note that funding will cover the stipend and home tuition fee rate (not the overseas rate). The difference between the Home and Overseas fee will require to be covered through other funding.
Project Details
Dynamic Security Assessment (DSA) focuses on the stability of the power system over various timescales, from milliseconds up to a few minutes, usually requiring computationally intensive time domain simulations.
Analytical or direct methods have provided a useful, descriptive representation of power system dynamics for many years and remain in use presently due to the ability to provide useful insights into power system dynamics. However, using such methods, it is difficult to represent controller actions in detail, which gains much higher significance with the increasing number of Power Electronic Interfaced (PEI) devices.
Time domain simulation models are currently considered “state of the art” and used by power system operators to perform dynamic studies though only rarely in an online, close to ‘real-time’ environment. Such models can represent the detailed dynamics of devices with reasonable detail and accuracy. However, they are computationally intensive, and with the increasing uncertainty introduced in power system operation as described above, the number of required simulations to cover all possible operating states “explodes”, while the operational time scale available to perform DSA is limited (usually several minutes).
New types of faster dynamic interactions (outside of the well-understood power system dynamic phenomena) have started to arise – largely due to the introduction of PEI devices to power systems, and these require more elaborate, higher order Electromagnetic Transient (EMT) models, which are even more computationally intensive than predecessors. This challenge might lead to reduced ability to evaluate system stability in operational as well as planning time scales.
This project is aiming to investigate the use of techniques and platforms for increasing computational speed of power system dynamic security assessment. Machine learning has been widely proposed for such cases in the literature and is an active research area within the research team the PhD student will be working.
Potential applications of quantum computing and quantum machine learning will also be explored as part of this project. Finally, the possibility to use other computational techniques to speed up dynamic security assessment will be investigated, looking into the capability of computation using GPUs in high-performance computers already available in the research team where the student will be working.
Further information
The successful candidate will be part of a team built around a UK Research and Innovation Future Leaders Fellowship on Addressing the complexity of future power system dynamic behaviour.
This will also offer extensive opportunities for collaborations with research institutions and industrial partners as well as opportunities for research and/or industrial placements, in the UK and abroad.
The PhD project is expected to start in October 2022.
Funding details
Funding for eligible candidates is provided for full tuition fees, along with a generous stipend for the duration of the project. Additional support of £1,500/year for conferences/equipment etc. is also available.
Supervisors
Apply
Candidates interested in applying should email Dr. Panagiotis Papadopoulos (panagiotis.papadopoulos@strath.ac.uk) with their CV, academic references or referee details, academic transcript, and a covering letter outlining their suitability for the position. Shortlisted candidates will be invited for interview.
Number of places: 1
To read how we process personal data, applicants can review our 'Privacy Notice for Student Applicants and Potential Applicants' on our Privacy notices' web page.