Assessment of optimal cleaning strategies for Fresnel solar collectors

Overview

Solar collectors are gaining popularity and relevance in the sustainably energy sources exploitation. The efficient harvesting of sun power may guarantee a safe transition from polluting fossil-fuel systems to renewable energy. However, these collectors may be affected by soiling, i.e. deposition of airborne pollutants and dust on their surfaces. Soiling hinders the optical efficiency of the reflectors thus limiting the achievable power generation of the plant. The identification of optimal cleaning strategy would then greatly help in ensuring high rates of productivity for solar plants.

Research engagement

The project will be mostly based on analytical modelling of soiling predictions and impact of cleaning strategies. An initial literature review is required to identify previous studies in the same area

Research activities

A rigorous literature review of currently available cleaning optimization studies on Fresnel systems is required. Subsequently, the identification of optimal cleaning strategies can be performed exploiting a previously developed soiling model. Optimization algorithms will be eventually used to tune the cleaning of the Fresnel collectors.

Outcomes

The main outcome of this work is a well-documented code for Fresnel collectors cleaning optimization. A written report regarding the activities performed is also expected.

Skills and experience

The ideal candidate should be curious and well prepared in coding (Matlab and/or Python), energy conversion systems, process control.

Start date

10 November, 2024

End date

20 February, 2025

Location

Gardens Point campus

Additional information

The student will be provided with assistance in every step of the project. Previous models developed to predict soiling will also be available.

Keywords

• solar
• cleaning
• fresnel
• optimization

Contact

Dr Giovanni Picotti, g.picotti@qut.edu.au