Study level

  • PhD
  • Honours

Faculty/School

Faculty of Engineering

School of Mechanical, Medical and Process Engineering

Topic status

We're looking for students to study this topic.

Research centre

Supervisors

Professor Emilie Sauret
Position
Professor
Division / Faculty
Faculty of Engineering

External supervisors

  • Dr Sahan Kuruneru, CSIRO Newcastle

Overview

The increase in global energy demand necessitates further advancement in photovoltaic (PV) systems. Advancements in PVs could potentially play a role to help meet the Paris Agreement of limiting global temperature increase to below 2°C.

The performance of ground-mounted PV panels commonly found in solar farms depends on a myriad of factors such as tilt angle, microclimate i.e. wind loads, shading, solar irradiance, and dust deposition. This project aims to develop an advanced numerical model, namely computational fluid dynamics (CFD), backed by thorough experimental validation, to unravel the fundamental mechanisms of air flow and heat transfer around PV panels. Parallel to CFD, PV field layout optimisation software and/or machine learning/AI will be implemented to assess optimum PV solar farm layout under varying microclimate conditions such as varying solar irradiance, wind velocities, etc.

Research activities

  • Carry out CFD modelling and simulations.
  • Deploy machine learning (ML) approaches to optimise PV farm layouts.
  • Evaluate the influence of wind loads, solar irradiance, etc on PV performance.
  • Develop fundamental understanding of the performance of PV arrays.

This project is a collaboration between QUT and CSIRO. It is part of a long-term vision/endeavour to tackle the growing energy demand thereby aligning with CSIRO's initiatives, primarily on Sustainable Energy and Resources (Towards Net Zero and Renewable Energy) under the 'Ultra Low Cost Solar (ULCS)' program at CSIRO Energy. It also directly aligns with the Australian Government's national priority area of renewables and low emission technologies.

Outcomes

  • Validated CFD model for fluid flow and heat transfer.
  • Optimised solar PV fields to maximize PV solar thermal performance using ML techniques.

Skills and experience

  • Some experience in fluid mechanics/dynamics, and computational modelling and simulation is required.
  • Strong knowledge in math, mechanical and process engineering are preferable.

Scholarships

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Keywords

Contact

Contact the supervisor for more information.