Energy Systems Catapult

Jul 24, 2023

image credit: Energy Systems Catapult https://es.catapult.org.uk/insight/spotting-low-carbon-technologies-charlotte-avery/ Data Scientist,Energy Systems Catapult Ltd I work as a data scientist looking for ways to make impact in the energy sector to aid with our net-zero transition. My experience has focussed on analysis of time series energy data, using ML... Member since 2023 15 views Using half-hourly electricity smart meter data from ~300 homes, over half of which we know have a heat pump and/or an EV (based on consumer questionnaires), and the other half have neither a heat pump or EV,  I identified a straightforward way of quickly determining the presence of either an EV or heat pump in homes. Long story short,  an effective way of identifying if a home has either an EV or a heat pump (or both) is to sum up the electricity usage overnight (between 11pm and 6am): if the total night time usage is greater than 3.6 kWh, on average over the course of a week, this was a good identifier for homes having an EV and/or heat pump. All the details behind the methodology that I used to get to this conclusion are outlined in the link provided. We recommend that this simple method is used to help consumers find cheaper and greener tariffs and identify low carbon technologies for forecasting model development. If developing your own methods of identifying low carbon technologies in datasets, use our simple rule-of-thumb as a benchmark to improve upon. Please feel free to reach out with questions - I look forward to discussing data science methods in this forum! Charlotte