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Renewable Integration in Power Systems: Challenges in Modelling, Estimation and Control

  • Full or part time
  • Application Deadline
    Thursday, April 30, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Supervisor: Dr Abhinav Kumar Singh
Co-supervisor Prof. Eric Rogers

Project description

A fully-funded 3-year PhD studentship for UK nationals (or EU nationals who have been in the UK for past three years) on Renewable Integration in Power Systems at the University of Southampton, a top university for Electrical Power Engineering in the UK and worldwide.

A transition from coal and gas based non-renewable generation to wind and solar based renewable generation is necessary to ensure a sustainable low-carbon future. But this transition introduces several challenges to power system operation. An essential requirement for the development of sustainable networks is the ability to support future demand through integration of distributed energy resources (DERs), including wind, solar, electric vehicles (EVs), etc. Modelling of EVs is more complex compared to the traditional demands on the energy network as their amount vary stochastically in time, direction and location. Moreover, unlike traditional large synchronous generators, characteristics of power converter interfaced DERs is not well modelled and understood. Static model of the system does not help as we are interested in dynamic security of the system driven by developing events. In particular, we need to find the impact of stochastic and intermittent dynamics of DERs on power grid, and how these dynamics can be better controlled to ensure global system stability. With so many sensors installed in the system, estimation of the dynamics of DERs can be done using measurements from these sensors to assess DERs’ impact on system stability, which can be subsequently used to devise a suitable control law.

This project will find such solutions to challenges related to maintaining the stability of power grids in light of renewable integration by exploring DERs’ modelling and dynamic state estimation (DSE) of DERs for control.
For any queries contact: Dr Abhinav Kumar Singh ()

Key facts
Entry requirements: first or upper second-class degree or equivalent in Electrical/Electronic Engineering, with knowledge of power systems. Good programming skills in MATLAB/Simulink or a similar simulation software required. Additional subject knowledge desired in control design, signal processing, dynamic modelling, and renewable energy systems.

Closing date: 30 April 2020.

Duration: four years (full-time candidature)

Funding eligibility: Full tuition fees and a tax-free stipend of £15009 per year, for 3.5 years for a UK national or an EU national who has been working or studying in the UK for at least 3 years prior to the start of this PhD. Self-funded international students are also welcome to apply.

Assessment: Nine month and 18-month reports, viva voce and thesis examination

Latest start date: 23 September 2020

Applying: http://www.southampton.ac.uk/postgraduate/pgstudy/howdoiapplypg.html

About the research environment
The studentship is based in the Electrical Power Engineering research group (www.epe.ecs.soton.ac.uk). Ranked in the top 1% of universities globally and among the UK’s top 20 for research, the University of Southampton has an international reputation for its research, teaching and enterprise activities.

We aim to be an equal opportunities employer and welcome applications from all sections of the community. Due consideration will be given to applicants who have taken a career break. University of Southampton holds an Athena Swan Silver Award. The University has a generous maternity policy and onsite childcare facilities; employees are able to participate in the childcare vouchers scheme.

Related Subjects

How good is research at University of Southampton in Electrical and Electronic Engineering, Metallurgy and Materials?

FTE Category A staff submitted: 84.25

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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