UK study aims to identify nuclear cost reductions

27 October 2017

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A new project aimed at gaining a better understanding of the factors influencing the cost of nuclear power plant projects has been launched by the UK's Energy Technologies Institute (ETI). The study could help identify potential cost reductions for future projects.

The Nuclear Cost Drivers Project, launched yesterday, will identify and analyse historic, contemporary and future nuclear power projects to identify areas of nuclear power plant design, construction and operation to deliver potential cost reductions. ETI said this would be achieved through the development and application of a "comprehensive, cost study evidence base".

The project - which will run until April 2018 - is being led by UK-based consultancy CleanTech Catalyst Ltd working with Cambridge, Massachusetts-based energy and climate consultants Lucid Strategy.

ETI's strategy manager Mike Middleton said, "There are currently no evidence-led projects which can illustrate whether the costs of generating electricity from new nuclear power plants can be reduced. The renewables industry, particularly offshore wind, is able to show a meaningful route to getting costs down through research, development and deploying at scale."

He added, "The challenge for nuclear new build in the UK is to demonstrate that it can show a credible way of delivering reduced costs. The expectation for advanced reactor technologies is that they should deliver a step reduction in costs."

"The challenge for nuclear new build in the UK is to demonstrate that it can show a credible way of delivering reduced costs."



Mike Middleton,

Strategy Manager, ETI

Kirsty Gogan, director of CleanTech Catalyst, noted: "Developing meaningful cost reduction strategies to accelerate global nuclear deployment is essential to unlock the potential £1.0 trillion ($1.3 trillion) global market for scalable nuclear technology. This will be critical to urgent and inevitable deep decarbonisation pathways in the next half century."

British businessman and senior expert adviser Tim Stone, who will act as an independent reviewer of the study, said: "Reliable data is vital to enable an understanding of the system costs for the UK government and others who recognise the potential of nuclear as a low-carbon generation source."

He noted, "It has long been recognised that the only two numbers which matter in nuclear power are the capital cost and the cost of capital. This important project is the first to approach the first of these on a thorough and independent basis."

The ETI is a public-private partnership between global energy and engineering companies and the UK government, mandated with accelerating the development and deployment of low-carbon technologies in the UK.

The Institute considers nuclear power has a potentially significant role to play in the UK's transition to a low-carbon economy. However, it says nuclear needs to be cost competitive with the overall energy mix and there must be a market need for it. The ETI said the initial challenge is to bring new nuclear projects online within the next ten years "with acceptable norms of budget and schedule variation". The subsequent challenge will be to deliver cost reductions for follow-on plants.

Earlier this month, the UK government published its Clean Growth Strategy, which defines how it aims to reduce carbon emissions across the whole economy. On policies and proposals for growing low-carbon sources of electricity, the strategy highlights the delivery of new nuclear capacity through the final investment decision last year on Hinkley Point C - under construction in Somerset, England - and the government's intention to "progress discussions with developers to secure a competitive price for future projects in the pipeline". Regarding government innovation investment, the strategy states the need to bring down the costs of nuclear power while maintaining safety by investing in innovation that will help plants to be built to time and budget.

Researched and written

by World Nuclear News

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