Ofgem announced that it has given a provisional green light for £24 billion to be spent over 5 years to maintain and upgrade Britain’s gas and electricity networks. £15 billion is going into keeping the gas network safe, and nearly £9 billion is being committed to high voltage electricity systems. Another £1.3 billion is ready to be released soon.
This is only the first part of a planned £80 billion programme that will increase the electricity grid’s ability to handle more power. Ofgem says this work will include more than 80 transmission projects across the country. These upgrades will cover over 4,400 kilometres of existing lines and add 3,500 kilometres of new ones. Some of these will be offshore.
The plan is to connect up to 126 gigawatts of clean electricity by 2030. This will be used to power homes and businesses without having to rely on gas plants, which have been vulnerable to global price spikes.
Jonathan Brearley, Ofgem’s CEO said, “Britain’s reliance on imported gas has left us at the mercy of volatile international gas prices which during the energy crisis would have caused bills to rise as high as £4000 for an average household without government support. Even today the price cap can move up or down by hundreds of pounds with little we can do about it.”
What Does This Mean For Energy Bills?
Businesses will pay higher network charges. Ofgem estimates that by March 2031, charges will rise by about £104 per year. Of this, £30 will be related to gas, and £74 to electricity. These charges cover maintenance, depreciation, and expanding the grid to handle the growing electricity demand.
The electricity grid upgrade is expected to lead to lower wholesale energy costs in the long term. For example, Ofgem predicts that the £52 cost from expanding the grid could result in £80 of avoided costs by reducing payments made to wind farms when the grid cannot use their output.
On balance, the total yearly impact on bills is expected to be about £24, or 40p a week. That number may go down more through the 2030s, as the benefits of the investment take hold. But even at the current levels, businesses will need to account for these extra costs in planning their operations and pricing.
More from Artificial Intelligence
- How to Use AI For Customer Support
- Experts Comment: Is There A Lack of AI Expertise Among the General Workforce In the UK?
- How AI Startups Deal With The Messy Side of Data
- Do We Put Too Much Trust in AI Chatbots? Altman Raises Eyebrows, Once Again
- Experts Comment: Should We Go to AI Doctors for First Opinions Instead of Second?
- How to Add AI Chat to Your Website
- What Is Automated Code, And Who Uses It?
- OpenAI Granted $200 Million Contract To Help US Military Boost AI Defence
Why Is AI Making Energy Demand Increase Faster?
The UK government is also responding to a new source of energy pressure, and that is, artificial intelligence. The Department for Science, Innovation and Technology said on 30 June that compute demand (the power needed to run AI) could reaaly increase in 5 years. This is the estimate being discussed at the second meeting of the AI Energy Council.
Compute refers to the electricity used to power large servers, data centres, and the systems behind advanced AI models. These models are used in everything from personalised medicine to air traffic control, and the systems they run on draw heavy and constant power.
The council, which includes Ofgem, the National Energy System Operator and tech firms like Google and Microsoft, is working on ways to predict this future demand so the energy system is not caught off guard. Government also wants data centres to get grid connections more quickly to avoid long delays in powering new projects.
How Will This Affect Business Planning?
The sectors most likely to use more AI, including finance, logistics, retail, and healthcare, will also need more energy. This could make electricity costs a larger part of a business’s budget. Those running or leasing space in data centres will have to monitor how grid access and pricing change in the coming years.
Businesses not directly involved in AI could also be affected. So, if AI users take up more capacity in the grid, for example, other businesses might face longer waits for their own energy projects to be connected. This might affect construction timelines or the decision to switch to electric fleets or machinery.
It is also likely that energy prices could become more volatile during this adjustment period. Grid planners must now look at multiple demands from AI, renewable energy, storage and electric vehicles, all while maintaining system stability.