Solar panel efficiency is calculated using standardised testing conditions, allowing like-for-like comparison of systems under the same conditions.
However, data collected over a three year period from two collocated solar systems of different technologies are showing unexpected results. The most efficient system's yearly output is comparatively lower. Initial data analysis explains some differences from the operational conditions, but further investigation is required.
During this research project, you'll perform data analytics to identify the real-world factors that are impacting the solar output and explain the difference in annual yield.
The relationship between solar output and on-site weather-related information (irradiance, wind, etc.) will first be investigated.
The inverter's control algorithms will also be studied to understand how they differ and determine which one performs better.
The output of this project will be used to refine existing solar output models.
Skills and experience
This research will suit you if you're an engineering student with an appetite for data analytics and an interest in renewable energy.
The following skills and experience are desirable:
- programming (preferably R or Python)
- data analytics and visualisation.
Initial code has been developed in R which can be reused or converted to your preferred programming language.
You may be able to apply for a research scholarship in our annual scholarship round.
Contact the supervisor for more information.