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Machine Learning Approaches for Optimising Battery Operations in Smart Grids

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

The project will investigate various machine learning approaches to optimise battery operations in the smart grid. Battery storage plays a vital role in smoothing out the fluctuations in energy demand and generation from distributed renewable sources. Machine learning can help predict the energy demand, and solar and wind power generation. Using reinforced learning, it is possible to make optimal battery charging and discharging decisions to flatten the demand curve. The project will involve extensive simulations and building machine learning models. The prospective students will need to have a strong background in programming, simulation and machine learning. The knowledge of renewable energy generation and battery storage is also essential.

How to Apply

Research Higher Degree candidates apply via iStart with an Expression of Interest which asks you to select your course and location, along with providing a brief description of your proposed research topic. Expression of Interest must be submitted by the prospective candidate.
Depending upon the outcome of your Expression of Interest, you may be invited to submit a full application for admission as a research higher degree candidate. The University reserves the right to refuse admission to any applicant.

Application Deadlines

Our Research Higher Degree courses don’t have any deadlines as students can commences these courses at anytime.

Funding Notes

Funding is also provided by CQUniversity to support research higher degree student project costs, and to support national and international conference presentations. This includes:

For masters by research candidates:

-up to $4,000 in Candidate Support Funds
-up to $3,000 for Candidate Travel Support

For doctoral candidates:

-up to $6,000 in Candidate Support Funds
-up to $4,500 for Conference Travel Support

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