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Many companies across the energy sector and beyond are looking for ways to achieve net zero transition whilst meeting the needs of their customers. This must be accomplished despite rising prices and economic uncertainty. Here are 3 ways we’ve been working with UK energy companies to help their decision-making become more efficient, effective and sustainable.

Driving towards net zero

We have worked with the National Grid ESO (NGESO), the electricity system operator for Great Britain, to provide safe and economical electricity to the country and progress toward a net zero carbon grid by 2025. The rapid growth of renewable and embedded generation has led to increasing uncertainty when making decisions on how to move electricity around the country to keep supply and demand in perfect balance.

By harnessing the power of mathematics, the NGESO’s Electricity National Control Centre (ENCC) has been able to make more economical and secure balancing decisions, helped identify and quantify the inaccuracies in the existing forecasts and spotted opportunities for economic performance improvement.

Keeping reactors online safely

We have also supported EDF to deliver low-carbon energy safely. EDF currently operates a fleet of 14 Advanced Gas-cooled (Nuclear) Reactors (AGRs), which play a crucial role in delivering clean, low-carbon energy to the UK. These 1,400 tonne structures currently generate one-sixth of the UK’s electricity. Graphite at the core of these reactors cracks over time. It is important to accurately forecast the future rate of cracking to ensure the safe continuation of operations within the current expected life.

Smith Institute developed CrackSmith forecasting and analysis software. It enables EDF to accurately predict future cracking, and to continue delivering safe, low-carbon energy to UK homes. This has enabled EDF to avoid taking reactors offline unnecessarily so they can continue to safely provide low-carbon, efficient power to their customers.

Ensuring a just transition

We are addressing the Future Energy scenarios with Scottish and Southern Electricity Networks (SSEN) to identify potentially vulnerable customers. SSEN is seeing a significant uptake of low-carbon technologies (LCT) on its network. This is typically from solar panels, electric vehicles and heat pumps, and requires action to manage the network to accommodate that increased electricity demand cost-effectively. To ensure a Just Transition to Future Energy Scenarios, no one can be left behind.

In the face of the increasing costs of fossil fuels, it has never been more important to ensure that everyone who wishes to adopt clean, electrified technologies, can do so. However, the transition to new technologies carries a risk for more vulnerable customers who may be unwilling or unable to make the switch. We are collaborating with SSEN, Imperial College London and National Energy Action to identify consumers in vulnerable positions and forecast how those communities and their needs may change in the transition to net zero.

The project deploys foresighting, machine learning and expert validation to test whether a reliable forecast of vulnerability trends can be developed. The aim is to support better-informed operational practices and investment planning which in future will be able to take vulnerable communities into account.

To achieve a just transition to Future Energy Scenarios, we must ensure no one is left behind.

Supporting sustainable decisions

Sustainability is high on the agenda at Smith Institute. We help our clients to achieve the environmental targets stated in the Path to Net Zero, by enabling digitisation, optimisation and forecasting. As UK’s industry completes the energy transition to renewable energies, we know that businesses and sectors are going to need to make significant changes to their operations, policies and modelling. These changes will involve large and complex investment decisions in different areas of capital expenditure, plus operational and personnel resources. It’s therefore vital that companies have confidence in their decision-making processes to plan for and prioritise investment decisions. Whether it’s the assurance that their current decisions are efficient and effective, supported by modelling that reflects reality, and can be trusted to base crucial decision on, or forecasting the impact of future decisions and the direction and strategy of the business. Having the confidence that the critical decisions being made are supported by the most accurate and reliable modelling, forecasting and insights means reduces risk and enables the march towards increased industrial sustainability can have a sure footing.

We know that sustainability also means minimising wastage and doing more with less. Our AI, machine learning and algorithms can identify efficiencies and optimisations that can help businesses identify areas and processes that can be made leaner. The application of machine learning to asset management takes the guesswork out of inspections. We enable our clients to save valuable time and therefore cost with asset-specific predictive models. The condition monitoring of assets over time, builds up a trend curve, ensuring costly inspections are targeted and timely.  The predictive maintenance models can also help extend the lifespan of existing assets, from vehicles to nuclear reactors. Safe sustainability requires the identification of areas of improvement and the confidence that comes from understanding the results that the changes will have for key business decisions.

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