Five ways the Turing is helping tackle climate change
26 April 2021
Research led by Dr Dan Stowell, Lecturer in Machine Learning for Visual Data Analysis and Signal Processing and Queen Mary Turing Fellow, was mentioned in the latest Turing blog post: "Five ways the Turing is helping tackle climate change".
Mapping the UK's solar panels
There are no comprehensive records of the location of the UK's solar panels, which means that precisely how much solar energy is being pumped into the UK's electricity grid at any time is not well known, even by?the National Grid. In the absence of accurate measurements and predictions of solar energy input, fossil fuels are burnt unnecessarily to keep generators running so they can take the strain when the network is underpowered. Our project, in collaboration with Open Climate Fix and OpenStreetMap, aims to?resolve that by using a combination of AI (machine vision), open data and short-term forecasting.
Through a crowdsourcing exercise, volunteers tagged the locations of solar panels on OpenStreetMap, mapping one-quarter of all the solar panels in the UK. Using this data, the researchers created an open dataset of solar panel locations that will help provide a short-term forecast of how much solar power is being fed into the National Grid, in turn helping to cut carbon emissions. The team is also working on machine learning methods to detect solar panels from satellite images, which would automate the process and fill in some of the map's gaps, further improving solar power forecasting.
Dan has also been a guest speaker on one of the latest Turing podcasts, explaining his work on addressing climate change via creating high-coverage open dataset of solar photovoltaic installations in the UK. The Turing podcast series can be accessed here.
Updated by: Michal Filus