Looking to list your PhD opportunities? Log in here.
This project is no longer listed on FindAPhD.com and may not be available.
Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
Power systems stability has been an active area of research for many decades. However, recently, the large number of renewable energy sources being integrated to the power network has started to significantly affect the stable and reliable operation of the grid. This has created essential requirements for the grid-connected units to contribute to the stability of the network by assisting in the regulation of the grid voltage and frequency via adjusting the injected real and reactive power. Hence, control design methods for grid-tied inverters will play a key role in the future smart grid architecture, which will be dominated by inverter-interfaced units.
Although several control methods have been developed for grid-tied inverters to achieve power regulation or provide ancillary services (contribute to the voltage and frequency regulation), the stability properties of the resulting closed-loop system have not been adequately exploited, especially for a system with multiple inverters, such as in the case of a smart grid. Most of the existing approaches to analyse stability are based on small-signal model and linearization methods. However, the inherent nonlinear dynamics of the power inverters together with the nonlinearities that arise from the power expressions in the control loop make nonlinear analysis essential to achieve global stability results.
This project will focus on the development of nonlinear control methods for grid-tied inverters that are based on a strong mathematical background and guarantee nonlinear closed-loop stability. These methods are required to: a) have simple structure, b) be independent of the system parameters and c) fulfil the technical requirements of the grid. Hardware-in-the-loop and experimental implementation of the developed methods are essential to verify the theoretical development.
Funding Notes
We require applicants to have either an undergraduate honours degree (1st) or MSc (Merit or Distinction) in a relevant science or engineering subject from a reputable institution.
Prospective candidates for this project should have a background in nonlinear control/systems theory, power systems and/or electrical engineering and knowledge of DPS programming is desirable. Competence in Matlab/Simulink is essential.
Full details of how to apply can be found at the following link:
https://www.sheffield.ac.uk/acse/research-degrees/applyphd
Applicants can apply for a Scholarship from the University of Sheffield but should note that competition for these Scholarships is highly competitive: https://www.sheffield.ac.uk/postgraduate/phd/scholarships
References
J. W. Simpson-Porco, F. Dörfler, and F. Bullo, “Synchronization and power sharing for droop-controlled inverters in islanded microgrids,” Automatica, vol. 49, no. 9, pp. 2603–2611, 2013.
J. Schiffer, R. Ortega, A. Astolfi, J. Raisch, and T. Sezi, “Conditions for stability of droop-controlled inverter-based microgrids,” Automatica, vol. 50, no. 10, pp. 2457–2469, 2014.
M. Karimi-Ghartemani, “Universal integrated synchronization and control for single-phase dc/ac converters,” IEEE Trans. Power Electron., vol. 30, no. 3, pp. 1544–1557, Mar. 2015.
G. C. Konstantopoulos, Q.-C. Zhong, B. Ren, and M. Krstic, “Bounded droop controller for parallel operation of inverters,” Automatica, vol. 53, pp. 320 – 328, 2015.
G. C. Konstantopoulos, Q.-C. Zhong, B. Ren, and M. Krstic, “Bounded Integral Control of Input-to-State Practically Stable Non-linear Systems to Guarantee Closed-loop Stability,” IEEE Trans. on Automatic Control, 2016, to appear."

Search suggestions
Based on your current searches we recommend the following search filters.
Check out our other PhDs in Sheffield, United Kingdom
Check out our other PhDs in United Kingdom
Start a New search with our database of over 4,000 PhDs

PhD suggestions
Based on your current search criteria we thought you might be interested in these.
Adaptive Security Threat Detection for Small Footprint Computing Devices within Industrial Control Systems, Intelligent Homes, Medical Devices & Smart Infrastructure
Anglia Ruskin University ARU
Optical fibre sensors for overhead conductor line sag monitoring in smart grid
Edinburgh Napier University
Data-Driven robust and optimal smart grid control
Glasgow Caledonian University