The Royal Opera House in London is taking an innovative step forward on its journey to become Net Zero. As part of its renewed focus on sustainability, the Royal Opera House is embracing Artificial Intelligence and Machine Learning working with its new clean-technology partner Grid Edge. Due to the size and complexity of the building, two months were spent creating a full digital ‘twin’ of the 163-year old building using the latest technology. 12,000 pieces of data per second are now being analysed by the digital twin from 1400 different data points, which will ultimately optimise energy use throughout the building to cut carbon emissions.
The Grid Edge technology has been created to make older buildings more efficient. Powered by Artificial Intelligence, the software quickly learns patterns and behaviours from a range of internal and external data sets. New data and insights are then created by the platform to identify how money and carbon can be saved, whilst also improving the performance of the building.
Laura Stevenson, Renewal Programme Director at the Royal Opera House, said: “Grid Edge technology was the ideal solution for the Royal Opera House as we set the foundations to reach net zero by 2035. Grid Edge is one of many new developments ROH has invested in in recent years in order for us to move our operations towards a more sustainable future. We are currently in the implementation phase linking the Grid Edge Technology with operational data from our Building Management System. Once completed, the technology will allow us to see in real time how we are performing against targets which is an invaluable resource as we take our next steps on this journey.”
Paul McCorquodale, CEO at Grid Edge said, “The Royal Opera House is an iconic building – a national treasure – so we are incredibly excited to be working with the team. We will help the Royal Opera House push the boundaries of what’s possible, with future proofed technology to reduce carbon emissions and save money. Grid Edge will balance the preservation of the building, whilst proactively managing the environmental impact of its energy requirements.
“The race to Net Zero is on and commercial buildings make up 40% of global carbon emissions. Whilst the direction and speed of the journey to Net Zero will be different for every organisation, the common key to success will be creating a strategy driven by data, which evolves with each phase of energy and carbon optimisation” Paul added. Using live, historic and predictive data, the technology learns the patterns of how a building manages energy. It identifies opportunities to shift energy demand, to avoid peaks in carbon and price, whilst always maintaining the comfort and performance of the building. The AI interrogates data to retrieve insights, while notifications and alerts remove help people running the building quickly decide what different energy management strategies can be implemented.