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AI Energy Collaboration and Innovation

In Article, Artificial Intelligence (AI), Sustainability, Tech4Good by GuestContributor

Related to UN SDG:
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The worldwide demands on sustainable energy have often created more questions than answers. As net-zero initiatives gather pace, we’re starting to see realistic solutions in the form of AI machine learning, channelling complex and vital data to optimise the energy infrastructure.

On May 11th US AI and privacy-preserving software company VIA announced a $10m (£7m) Series A investment in their software, doubling its previous valuation. Designed to improve data quality and privacy, this next round of investment is further proof of AI’s ever growing influence.

In a press release VIA CEO Colin Gounden stated: “The grid simply cannot adopt 100% clean technologies without AI. Data access and privacy were always major hurdles.” Thankfully the VIA CEO isn’t the only person who sees the need for AI investment.

Last week trade association TechUK released their ‘AI For Energy Report’ outlining the short term and long term benefits of AI in the Energy Sector. The membership organisation has over 850 members, working with government, education providers and employers to realise the potential of digital technology.

I spoke with TechUK Associate Director of Climate, Environment and Sustainability Susanne Baker about why AI is starting to emerge in the energy sector: “What’s very apparent is that the decentralisation agenda along with the decarbonisation agenda is creating enormous system complexities.”

“What we’re very mindful of is that people talk a lot around AI. Machine learning can do this, or can do that, but without giving the specifics around the particular use cases. What we’ve tried to do in this paper is really draw out those use cases.”

Burgeoning AI and Future Participation

Susanne Baker suggested that the application of AI machine learning in the energy sector is very much in its infancy, with use cases only just starting to emerge. Open data is vital for machine learning and AI to flourish, and participation is at the centre of functionality.

“We’re moving from a situation where the number of actors in the energy system was quite AI for Energy report concentrated, to one where there could be potentially millions of different operators. With home owners themselves becoming potentially future participants in the future energy system.”

Another organisation that is working hard towards improving the landscape of participation is not-for-profit net-zero market catalyst IceBreaker One. The former CEO of the Open Data Institute Gavin Starks founded IceBreaker One with a view to achieve net-zero through connecting policy, strategy, risk management and investment.

The team at IceBreaker One aims to encourage and influence investment decisions worth a modest $3.61T (£2.5T) per year to deliver net-zero by 2030. A clear and positive stance on helping to improve the fortunes of the data infrastructure.

Speaking with Starks recently stated: “Data is now a fundamental part of our economy, society and environment – we live in a data-driven world. We also face vast societal challenges where data can work harder to help us make better decisions.”

Energy Infrastructure.

Sustainable electricity and gas supplier Octopus Energy have also realised the benefits of machine learning in their tariff support. Susanne Baker told me: “You can start to send price signals to people to use more energy when the sun is shining, and store energy when the wind is blowing. So there’s lots of exciting ways that AI can really support the energy sector’s transition to net zero.”

Octopus Energy supplies to over 1.4m homes across the UK, displaying a successful template for sustainable suppliers. Boasting a 160% revenue growth, from £477m to £1.24bn at the end of the fiscal year 2021. Yet expansion often comes at a cost, as administrative and interest expenses caused a fall to a pre-tax £61m loss according to The Times.

With innovation, expansion and investment financial portfolios will often suffer in the short term. Last year Octopus Energy acquired Upside Energy, establishing a new tech hub in Manchester focused on data science, AI and empowering not-for-profit organisations in technology.

Recently they also announced a white-label partnership with the UK’s first not-for-profit energy provider Ebico, to supply renewable energy to its customers. Seen as a sign that Octopus Energy are definitely investing in the ethical long term.

Octopus Energy founder and CEO Greg Jackson said on his website: “I asked myself what an energy supplier in the 21st century should look like. Then, with the backing of Octopus Investments and a team of great people who shared the same vision, we began building it.”


Alphabet Inc subsidiary and AI research lab DeepMind is at the forefront of data analysis, giving a secure basis for data use cases. With a neural network gathering data on weather forecasts and historical turbines, DeepMind is able to predict wind power output 36 hours ahead of actual generation.

In a DeepMind blog post Google Software Engineer Carl Elkin said: “Based on these predictions, our model recommends how to make optimal hourly delivery commitments to the power grid a full day in advance. This is important, because energy sources that can be scheduled (i.e. can deliver a set amount of electricity at a set time) are often more valuable to the grid.”

TechUK AI Report

TechUK Associate Director of Climate, Environment and Sustainability Susanne Baker

TechUK’s Susanne Baker suggests that the data optimisation that DeepMind provides is vital: “A very famous example is from DeepMind. They worked with data centres to essentially optimise cooling and heating and leading to some really significant reductions.”

Privacy and data security will be paramount for consumer confidence and the expansion of collaboration and investment, Susanne Bake said that: “People need to be very much reassured that their data is being managed in a very responsible and secure way.”

“Maybe you don’t necessarily need to trace it back to the individual user, it could be pooled. If it is traced back to the individual user, to what extent can you place safeguards to make sure that ultimately the user’s privacy is protected throughout the whole journey.”

The AI For Energy report covers an impressive cross section of energy priorities from increasing the energy efficiency of commercial and industrial facilities to supporting the integration of electric vehicles, naming but a few.

The Tech UK report also points out that AI in the energy sector is well and truly a developing tool, gaining pace in an industry that is calling out for a greener alternative and sustainable solutions.

As we see there are a series of organisations investing in AI machine learning and big data, some even pushing their fiscal boundaries for the sake of achieving net-zero. Participation, collaboration, and innovation will be the reason why this succeeds, and its also the reason why we’ve got this far.

With organisations like IceBreaker One, TechUK, AI research lab DeepMind, Octopus Energy and privacy-preserving software company VIA, it seems the infrastructure is ready to utilise the potential optimisation. All that’s needed now is increased participation, producing data for the artificial minds to forecast the future of our energy.

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