Sofia Pinto

Start at home for newly trained heat pump installers Helping heating professionals bridge the gap from heat pump training to real-world installation by starting in their own homes

We’ve been giving newly trained heat pump installers a heat pump to install in their own home! We though it’d help heating engineers newly trained in heat pumps enter the industry faster, grow their confidence and do better installs. It seems to be working! www.nesta.org.uk/report/start...

💡 How is electricity consumed by households in Great Britain?

At @nestauk.bsky.social, we have been prototyping a method for identifying patterns of energy usage.

📈 Read our project update and explore our dashboard here: bit.ly/3zW1RB5

🧑‍💻 You can read our technical appendix here: shorturl.at/LFx9u

Thank you for letting me know Jeremy!

The goal of this publication was to share our method and get feedback on it, before we improve the existing profiles. Hence, the profiles we're sharing are not the final profiles.

🙏 Leave suggestions here: shorturl.at/Ojb4s

👩‍💻 Data science work so far included:
- Defining smart meter data features that capture the main drivers of electricity usage
- Clustering households based on smart meter data features to identify electricity-use profiles
- Contextualising profiles with information about homes and households

⏭️ The second phase of the work will focus on improving the existing profiles in response to stakeholder feedback and potential use-cases we identify. The final set of profiles will include gas consumption, alongside electricity.

🏡 The goal was to understand whether smart meter data could be used to identify different patterns of energy usage and characteristics of homes and households associated with each usage pattern.

🔋 In the first phase of our project, we have developed two prototypes based on half-hourly electricity smart meter data to group households based on how they use energy.

💡 How is electricity consumed by households in Great Britain?

At @nestauk.bsky.social, we have been prototyping a method for identifying patterns of energy usage.

📈 Read our project update and explore our dashboard here: bit.ly/3zW1RB5

🧑‍💻 You can read our technical appendix here: shorturl.at/LFx9u

We've analysed over 1 million forum interactions relating to home heating posted in the past 20 years.

🍃 Read our learnings here: lnkd.in/deX_SWNr
🖥️ Access our GitHub repository: lnkd.in/dtHXjG8p
🧑‍💻 Check our technical appendix: lnkd.in/dt_hkjum

✨ Are you a data scientist? Do you want to learn about analysing online forums text data? You've heard about topic modelling but unsure where to start? Do you need a resource on sentiment analysis?

Thank you Marcus! Credit to @helloaidank.bsky.social as well, who delivered the data science with me.

Findings can be explored in the dashboard at the end of the piece (you can see differences across profiles for different contextual features). Feel free to suggest additional contextual features you’d like to see in a next phase of the project, through our feedback form.

Hello Mary - yes, we’re using a pseudonymised UPRN to join information about households in specific energy-use profiles with their respective EPC information. You can read more about how we do it in the technical appendix (it’s linked at the end of the project update page).

Many people at Nesta provided support during this project.
Cath Sleeman, @lizgzil.bsky.social, @karlisk.bsky.social, Jack Vines, Daniel Lewis, @acjsissons.bsky.social, Adrian Stymne, Codrina Cretu, Andy Marsden, Oliver Zanetti,
Genna Barnett , Zayn Meghji, Elin Price and Robert Harris.

🙌Acknowledgements:🙌
@helloaidank.bsky.social
for delivering the data science work with me!

🔍Main takeaways:
- There has been an increased interest in heat pumps over time!
- Homeowners are still facing issues that are preventing them from getting a heat pump.
@nestauk.bsky.social's sustainable future team has been working across most of them!

You can also see more information for some of the above topics. Cost can be split into several sub-themes including the upfront cost of installing a heat pump, the running costs of having a heat pump as a heating system and the related rise of electricity prices.

Here we have the same for the second forum, which is more focused on self-building.

The topics of conversation identified in the context of heat pump conversations and respective breakdown of sentiment, for one of the forums analysed - where we find mostly opinions from homeowners.
NB: those who are unhappy are more likely to share their negative experiences.

🆕 Some of the learnings: 🆕
For most of the 2000s and 2010s, heat pumps were a niche topic on the forums we analysed. But interest has surged, and they were the 7th most discussed energy / heat topic in 2023.

🤓The methodologies we used and the code we shared publicly can be applied to other domain areas/ other sources of forum/text data.

To know more, you can:
- read our technical appendix: shorturl.at/A8bvk
- check our code through this GitHub repository: t.co/up7yjKYgRk

📈 About the data science: 📈
We have identified topics of conversation using a topic modelling approach called BERTopic. We used sentiment analysis to identify the share of interactions that were positive, neutral or negative.

🏡We have analysed over 1 million forum interactions to identify what homeowners say about home heating and heat pumps when posting in online forums. 🏡

Read our report and explore our dashboard here: nesta.org.uk/data-visuali...

More in thread ⬇️

Thank you Adrian, very kind!
As mentioned by Andrew, all the code used in the analysis is available on this GitHub repo (see link below) and can be applied to other forum data.

github.com/nestauk/asf_...