PhD Scholarship in Switching Dynamics Approach for Distributed Global Optimisation

This projects aims to develop a breakthrough switching dynamics approach and new technology for global optimisation tasks in big-data applications.

The increasingly available big-data presents challenges as well as unprecedented opportunities for timely informed decision making. For example, for economic dispatch problems in power grids, traditionally, a two-settlement market strategy is utilised to only concentrate on main power generators where day-ahead market needs and quarterly hour demands are combined. However, when this economic dispatch task involves tens of thousands or even millions of distributed generations and storages due to integration of renewable energy sources under uncertain weather conditions, dispatch decisions have to be based on these complex situations to determine when and how much to generate, which generator to generate, and what the wholesale electricity price would be.

Specific objectives are to develop:

a) switching dynamics approach to accelerate optimal solution search

b) intelligent distributed global optimisation algorithms scalable to any size of big-data optimisation tasks

c) an efficient big-data learning based global optimisation system capable of handling uncertainties in big-data environments.

Successful applicant will work on this project for the PhD program in the School of Science at RMIT University.

This is a project funded by an Australian Research Council (ARC) Discovery Grant (DP200101197) for three years (2020-2022), which aims to develop a breakthrough switching dynamics approach and new technology for global optimisation tasks in big-data applications.

An ARC PhD Scholarship is available to work on the project. The scholarship consists of a $31,885 (tax free) stipend per year for the duration of three years.

You are required to have a Bachelor degree in a relevant discipline such as mathematical sciences or electrical engineering with at least 2nd class upper Honours or equivalent. Experience in one or more areas in nonlinear dynamical systems, discontinuous control systems, operations research or optimisation algorithms is desirable. The applicant must have a strong background in mathematics.

Candidates should contact Professor Andrew Eberhard by email via andy.eberhard@rmit.edu.au. Prospective candidates should provide CV, academic transcripts and a written expression of interest before lodging any application with SGR.

Applications are open now.

21 September 2021.

This scholarship will be governed by RMIT University's Research Scholarship Terms and Conditions.

Candidates should contact Professor Andrew Eberhard by email via andy.eberhard@rmit.edu.au

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Acknowledgement of country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Luwaytini' by Mark Cleaver, Palawa.