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Distributed Generation Aggregation and Optimisation in Future Power System (Advert Reference: RDF19/EE/MPEE/JIANG)

  • Full or part time
  • Application Deadline
    Friday, January 25, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Due to global environmental concerns, the UK has set an ambitious target of reducing greenhouse gas emissions by at least 80% from 1990 to 2050. To meet this low carbon target, developing a smart grid that delivers efficient energy usage via a flexible accessible system, is essential for future energy system. At the core of smart grid, the aggregation of the capacity of distributed energy resources (DERs), storage units, and flexible loads to create a single operating profile helps balance supply and demand. For example, virtual power plant platform or energy hub concept have a significant enabling value to benefit many stakeholders: Individual consumers could gain visibility and manageability to system operations; System operators would benefit from the cost-effective balance of demand and supply, and the efficient use of DERs.

To facilitate Distributed Generation (DG) aggregation, both optimization algorithms and communication technologies play important roles, but the full potential of DG aggregation has been hampered by the lack of joint power-communication system models and the thorough analysis of the impact of communication system imperfections to optimization/control algorithms.

This project aims to provide better understandings of the power-communication systems operating with close interactions, and develop more advanced design methods. These could potentially lead to more efficient management of DERs and flexible demands, ultimately to improved operational efficiency of electricity networks for system operators and to reduced cost for consumers. This project will provide advancement in knowledge of how to optimise the performance of smart grid applications, considering not only power systems but also realistic communication systems.

We are recruiting one PhD student to contribute to the project. The candidates are expected to have solid knowledge in Communications Engineering, Electrical/Electronic Engineering, demonstrably experiences of programming/simulations, strong analytic skills, and excellent communication skills, both written and oral, in English.

The principal supervisor of this project is Jing Jiang.

Eligibility and How to Apply:

Please note eligibility requirement:

• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. RDF19/EE/MPEE/JIANG) will not be considered.

Deadline for applications: Friday 25 January 2019
Start Date: 1 October 2019

Northumbria University is an equal opportunities provider and in welcoming applications for studentships from all sectors of the community we strongly encourage applications from women and under-represented groups.

Funding Notes

The studentship is available to Students Worldwide, and covers full fees and a full stipend, paid for three years at RCUK rates (for 2018/19, this is £14,777 pa).

References

1) J. W. Heron, J. Jiang*, H. Sun, and T. Doukoglou, “Round-Trip Latency Modelling of IoT SmartGrid Network Topologies,” IEEE Access, April 2018.
2) M. You, J. Jiang*, Andrea M. Tonello, and H. Sun, “On Statistical Power Grid Observability Performance under Communication Constraints,” invited paper, IET Smart Grid, vol. 1, no. 2, pp. 40-47, 7 2018.
3) J. Jiang* and Y. Qian, “Defense Mechanisms against Data Injection Attacks in Smart Grid Networks,” IEEE Communications Magazine, vol. 55, no. 10, pp. 76-82, October 2017.
4) M. You, H. Sun, J. Jiang* and J. Zhang, "Unified Framework for the Effective Rate Analysis of Wireless Communication Systems Over MISO Fading Channels," IEEE Transactions on Communications, vol. 65, no. 4, pp. 1775-1785, April 2017.
5) J. Jiang* and Y. Qian, “Distributed communication architecture for smart grid applications,” IEEE Communications Magazine, vol. 54, no. 12, pp. 60–67, December 2016.
6) J. Jiang*, H. Sun, D. Baglee and H. Vincent Poor, "Achieving Autonomous Compressive Spectrum Sensing for Cognitive Radios," IEEE Trans. on Vehicular Technology, vol. 65, no. 3, pp. 1281-1291, March 2016.
7) M. You, H. Sun, J. Jiang* and J. Zhang, "Effective Rate Analysis in Weibull Fading Channels," IEEE Wireless Communications Letters, vol. 5, no. 4, pp. 340-343, Aug. 2016.

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