Introducing Faraday — Our Smart Meter Load Profile Generating Tool
At Centre for Net Zero, we work on research that focuses on the future energy system, and how we could accelerate a people-centred net zero transition. We’re particularly interested in electrification, consumer behaviour and how people use low carbon technologies both now and in the future.
Our relationship with Octopus Energy means we have access to smart meter data. Ten of thousands of Octopus Energy customers own some form of low carbon technology, including electric vehicles, heat pumps, solar PV and home batteries. How these customers currently behave can provide important insights for those interested in the energy system of the future.
Partners we’ve worked with in the past have highlighted the value of this dataset in advancing research, helping policymakers and shaping the DNO to DSO transition. We have therefore been exploring ways that we can unlock its utility for the energy community whilst strictly protecting customer data and privacy.
Simulating Load Profiles at a Household Level
Our team is building a tool called Faraday. It models daily load “profiles” consisting of half-hourly kWh consumption for a given set of user-specified inputs (e.g. low carbon technology, property type, season etc) which specify a consumer archetype and day type. The goal is to let end-users select from a variety of consumer archetypes, enabling the Faraday tool to simulate the entire distribution of load profiles of that population (e.g. at different quantile levels) instead of a point estimate.
Household smart meter data is a type of personal data, and thus protected by GDPR. Our modelling approach means that we’re able to generate realistic profiles for each consumer archetype that can’t be attributed to specific customers.
Helping Researchers Answer the Big ‘What-if’ Questions
By modelling at a household level, we can capture the variability of how each household uses energy differently. Allowing end-users like researchers, policy makers and Distribution Network Operators (DNOs) to select from a variety of user-inputs enables researchers to simulate how households consume energy and model many ‘what-if’ scenarios, such as:
- What if we designed a new innovative tariff — how would this impact energy consumption and the grid?
- What if X% of households in the UK now have electric vehicles — how would it affect energy demand and the grid?
- What if we build more properties of a given type in an area? Could the grid handle it?
- What if extreme weather conditions like heat waves and cold snap become more common and severe? What needs to happen to our grid to manage these demand spikes?
Some of these scenarios are already happening today:
- National Grid paying 5000% above typical price to avoid blackout during July 2022 heat wave
- West London potentially faces new home bans as the grid has run out of capacity
- Norway threatens to ration electricity in fresh blow for UK energy supplies — live updates
By building Faraday, we hope to empower researchers and policy makers to answer the big questions of tomorrow and come up with people-centric solutions and policies to move to a net-zero future energy system. In the future we’ll also combine Faraday with our research on flexibility (such as our recent Big Dirty Turn Down trial) to allow end-users to model the impact of different flexibility interventions.
Progress to date: Alpha
We began development in June 2022 and have now built an alpha version of our web app and an API.
Earlier in summer 2022 we put out a registration of interest form on the UK Energy Research Centre’s website (UKERC) to recruit alpha testers and have since received responses from a wide variety of candidates. We have selected a small number of alpha testers to help us shape how this tool will develop for the benefit of the wider research community, and we hope to extend access to our Faraday tool to more users in the near future when it has become more mature.
In the meantime, we will be blogging about our progress over the next few months as we continue to develop the tool and we hope to welcome more users to use Faraday in the near future.
