The amount of energy generated by renewable energy sources is on the rise. The BEIS reports that renewable sources now account for approximately 30% of all electricity generated.
This is in line with the government’s Clean Growth Strategy which aims to reduce carbon emissions while encouraging economic growth. The Clean Growth Strategy set various goals, including generating 85% of electricity from low-carbon sources by 2032.
However, earlier this year, the government Committee on Climate Change reported that the next two carbon budgets would be missed unless action was taken.
In the wake of this revelation, this article sums up a few ways in which technology could help the UK reduce its carbon emissions.
Machine Learning (ML) and the Smart Grid
Data such as weather forecasts and historic rates of energy consumption can be analysed and ML technology can use this to accurately balance demand with supply.
One large issue with our current low-carbon energy sources is that they are weather-dependant (and we all know how unpredictable the British weather can be!)
However, ML can be utilised to accurately monitor and predict energy generation and consumption. By making renewable and low-carbon energy sources more reliable, ML could pave the way for increased dependence on low-carbon energy sources.
Predicting supply and demand also means that energy distribution processes can be made much more energy efficient. For example, DeepMind used ML technology to reduce the energy used for cooling by almost 40% in Google offices.
Last year, the CEO of Google-owned DeepMind estimated that using AI and ML within the UK National Grid could reduce energy consumption by 10% “without any new infrastructure, just from optimisation”.
Internet of Things (IoT) and Smart Cities
With over half of the world’s population living in urban areas, it is crucial that these areas become as energy efficient as possible. Smart Cities utilise a combination of technologies, including AI, ML and IoT to harmonise infrastructure and optimise efficiency.
For example, street lights can be fitted with sensors and controlled remotely. This would allow local authorities to turn off the lights when they are not required. It is estimated that this could reduce energy bills by up to £50 million per year. All in all, quite a bright idea!
Similarly, the traffic and congestion on roads can be monitored and predicted, which allows traffic signals to change accurately in line with demand and therefore reduce congestion.
The government’s Science and Technology Committee recently launched an inquiry to explore the technologies needed to meet Clean Growth Strategy goals. In doing so, the government has arguably reconfirmed its commitment to developing technology for use within the energy sector.
Last week, the government also appointed an expert panel to advise on how best to ensure that new firms can compete in data-driven digital markets. The panel will be chaired by Professor Jason Furman (who was Barack Obama’s chief economic advisor).
The potential for these technologies is incredible. Time will tell whether the current government strategy will encourage sufficient investment in these disruptive technologies.
However, the government appetite for developing tech within the energy sector combined with its increasingly conscientious approach to competition within digital markets presents tech SMEs with a real opportunity for growth.
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 Based on Q1 in 2018 using figures from BEIS https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/720182/Press_Notice_June_18.pdf
The next two targets cover the periods 2023 – 2027 and 2028 - 2032
 When used by all UK local authorities: https://www.techuk.org/images/programmes/Technology%20-%20Enabling%20CO2%20reductions%20Final%20Digital%20Version.pdf