CARBON REDUCTION INITIATIVES
and manual readings, as well as other sources, enabling accurate analysis of the building’s performance to be relayed to the digital twin. Reliable data is essential to make informed decisions and set realistic improvement targets. However, a significant number of NHS buildings do not have a BMS system in place, or have archaic systems that need updating. A basic level digital twin can be created
at the application stage from data gathered, enabling high-level analysis which creates a more robust bid. For example, instead of simply suggesting that the funding will be used for a heat pump, digital tools can be used to determine the optimum size of this, and the potential savings it could unlock.
In the UK, healthcare campuses are often a mix of old and new buildings, which creates complex systems and a lack of visibility around how buildings are performing.
funding will be used. Technology can be utilised to gather data on facilities’ current performance, and carry out an initial assessment to determine how the building or buildings can be adapted to enhance performance.
Use of digital tools to provide detailed bids Applicants need to provide details on current performance and measures that could improve this to demonstrate to the government how the funding will be used to decarbonise. Digital tools such as ‘digital twins’ can be used to provide the above, helping to de-risk the investment
and provide decision support information. Digital twins are virtual models of buildings, the most sophisticated of which use physics-based simulation and building data to create models that respond as their real-world counterparts would. A digital twin can be created of a building or an entire healthcare estate, and used to gain insights into how a building is performing. This data can then be used in the application process to highlight where changes need to be made to improve energy efficiency and prevent energy wastage. Data is gathered from the Building Management System (BMS), smart meters,
Spending funding wisely once secured When a Trust has successfully secured funding, the digital twin can be used to create a heat decarbonisation plan. This will detail the exact measures that need to be implemented to reach targets. Using the digital twin, different scenarios and improvements can be tested – such as heat pumps, lighting changes, and differing levels of insulation. Once the most effective solutions are determined, it’s possible to gather data on the potential savings that these measures will generate and input these into the plan. Applicants to the funding schemes
are required to fulfil monthly or quarterly reporting requirements, allowing for continued updates on how the project is progressing and identification of any issues. Monthly spend forecasts are also required, so it’s important that Trusts can cost the improvements and the time it will take to provide return on investment. Often, there is a limited timeframe to draw down the funding, which means providers need to act quickly to get a plan in place. However, when creating a heat decarbonisation plan, there are several challenges to consider. In the UK, healthcare campuses are
often a mix of old and new buildings, which creates complex systems and a lack of visibility around how buildings are performing. This can lead to higher operating costs and lower levels of occupant comfort. It also poses the question of whether attention should be focused on deep retrofit of old buildings, or optimising the energy performance of new ones. However, a digital twin of the entire campus can be used to determine where to focus improvements to achieve the best results. In addition, it can be used to analyse how the mix of buildings can work together, and how heat networks can be shared across the estate to maximise efficiency. It’s also important to ensure a balance
Taking the time to find the data to ‘fill in the gaps’ will make for a more robust application.
68 Health Estate Journal January 2024
between reducing carbon impact, alongside other priorities, such as
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