UCL Energy Institute


ESDA MSc student part of winning hackathon team solving climate emergency challenge

13 February 2020

UCL Energy Institute postgraduate student Thomas Falconer and his team won the top prize at The Climate Emergency Hackathon, for their work developing a data-driven solution to a climate emergency challenge.

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The hackathon, hosted by Valtech and Ofgem, asked teams to collate never-before-linked datasets across industries, uncovering ways to catalyse the decarbonisation of the UK energy system.

The two-day competition started on the morning of Friday 31 January, and teams had until the evening of Saturday 1 February to develop their concepts.

Leveraging data provided by MET Office, Smart DCC, BEIS and Electralink, the winning team developed a platform which ranked and compared postcodes based on their ratio of solar power potential to rolling electricity demand and present embedded generation, in order to enable effective targeting of areas best suited for solar photovoltaic uptake and localised feed-in-tariffs.

Thomas Falconer, who studies on the Energy Systems and Data Analytics MSc at UCL Energy Institute, said:

Our analysis brought together insights from a variety of disciplines, ranging from computer science, data analytics, app development and industry expertise, and highlighted how data-driven solutions can help catalyse our transition to a net zero energy system.”

The Energy Systems and Data Analytics MSc (ESDA MSc) is the first programme of its kind in the UK, combining the study of Energy Systems with Data Science. 

The programme is aimed at students with a quantitative background who have an interest in energy and are motivated by the use of data science to solve sustainability problems. 

Students gain a multi-sector, multi-vector understanding of Energy Systems, while developing advanced statistical and machine learning skills and getting practical experience of data analysis.

The advanced degree programme is designed to provide a broad understanding of energy systems, machine learning, programming, energy use in the built environment, energy use in the transport sector and the role of data and advanced analytics in solving relevant sustainability problems. Find out more on our programme page.