OnGen is a software platform provider specialising in energy efficiency, onsite renewable energy feasibility and renewable energy supply contracts. They partnered with the University of Edinburgh's Bayes Centre to advance their technology through an MSc student project.
OnGen wanted to automate a currently semi-manual process of identifying suitable areas at an energy user's site for the deployment of solar PV and solar thermal technologies on roof spaces. This was research OnGen had wanted to conduct for many years, but they did not have the in-house time and knowledge to conduct it successfully.
The MSc project focused on using machine learning to automate the analysis process. While OnGen had already developed award-winning software that assesses up to ten renewable energy technologies, the machine learning approach helped rule out areas where certain technologies would not be suitable more efficiently.
Using machine learning limited the user input required, making for a more streamlined and user-friendly process for assessing the feasibility of onsite renewable energy. The project successfully automated what was previously a semi-manual assessment process.
OnGen offered the internship because it gave them access to specialist expertise they didn't have internally, at a very low cost. The project delivered valuable research outcomes that advanced their product capabilities.
