Modern Building Services

MODERN BUILDING SERVICES APRIL 2023 11 FEATURE NET ZERO More information can be at new.abb.com However, by leveraging readily available AI technology, existing HVAC equipment can be upgraded to learn, reason and even solve problems. Take the example of an office lobby that has had revolving doors installed, letting outside air in. A standard HVAC systemwould have wasted energy struggling to regulate the fluctuating temperatures, but with AI installed, the upgraded system quickly learns, adapts and reacts to its changing surroundings to deliver efficient, cost-effective heating and cooling. Using machine learning, AI can not only deduce that an office’s communal area grows warmer at lunchtime as more workers congregate in that space, but it can also adapt and adjust the air conditioning proactively prior to the lunch period, thus keeping the area consistently comfortable for occupants. This kind of speedy, accurate auto-adjustment not only conserves energy, it also eases the burden on those tasked with managing office workers’ comfort, freeing up hours that can be directed elsewhere. Collaboration is the key to energy-efficiency AI Climate change is everyone’s problem and it stands to reason that next to smart technology systems, and of equal importance, is collaboration and knowledge-sharing between all industry stakeholders. As a developer of digital, automation and electrification solutions we’ve taken an in-depth look at businesses worldwide that can deploy AI and IoT in infrastructure, and where it can have the biggest impact. In one initiative, through partnership with Montreal-based AI pioneer BrainBox AI, predictive, self-adaptive and scalable cloud- based AI solutions have been developed that help reduce energy usage, costs, and carbon emissions, fromHVAC systems in commercial buildings across a range of sectors. The platform is engineered to provide the owners of smart buildings with a simple way of optimizing their energy consumption. Once installed, it learns the patterns of the building’s HVAC systemby observing crucial data points, establishes a workablemap of the HVAC system’s operational patterns and then gathers ideas for greater efficiencies. Following initial analysis, the solution then examines other external factors that affect the internal environment such as weather, occupancy trends, local electricity prices and even outdoor pollution. The solution is currently being used in approximately 100,000,000 ft 2 of commercial real estate worldwide and has the potential to reduce carbon footprint by up to 40 % 7 and energy costs by up to 25% 8 . Leading the way in US, Australia, Canada and the UK Looking at uses in retail settings, a 275,000 ft 2 shopping centre in Australia, annualized HVAC energy savings of 36% have been achieved, saving 388 metric tons of carbon emissions annually. Following suit, another Australian shopping complex has also now leveraged predictive and self- adaptive capabilities of this AI technology to fully automate its HVAC system using AI, cloud computing and customised algorithms, resulting in electricity savings of 43,73kWh, or 16%, after just five months. Meanwhile, in Canada, the owners of a 300,000 ft 2 office building in Ontario have reduced annual HVAC energy usage by 29% and saved 218 metric tons of annualized carbon emissions through AI integration. In an 82,500 ft 2 medical centre in Garden City, NewYork, the solution controls fresh air handling units and downstream variable air volume, significantly reducing asset and equipment run-times, and HVAC energy consumption, equating to 39% electricity savings on HVAC equipment in just six months 9 . We’re seeing similar innovations in the Europe, including the UK. Manchester Metropolitan University, ranked top in the People & Planet League of UK universities, has installed a web-based Building Management System (BMS) that provides real-time access to data to support energy efficiency, while minimising operational and maintenance costs 10 . The BMS provides automated control and 24/7 web browser access to alarms, trends and scheduling for temperature, lighting and air quality, and has helped the university’s new Grosvenor East building to be certified as excellent under the UK’s Building Research Establishment Environmental Assessment Method (BREEAM). Smart solutions to climate change In conclusion, we can see that bringing building facility systems such as HVAC onto an intelligent, autonomous, AI-enabled digital platform and integrating them seamlessly with each other gives businesses a single, holistic view of how efficiently and effectively their infrastructure operates. Armed with this data, managers can take steps to optimise energy use, slash emissions and costs, and reduce carbon footprint. Increasingly, however, AI solutions for smart buildings are taking such decision-making out of the hands of workers, resulting in significant manpower and cost savings. Working with a mining operation in China this year, we’ve seen the installation of a new digital energy management system not only save 15% in energy costs, but also realise a 25% reduction in labour costs. Efficiency AI, in other words, is smart enough to leverage machine and deep learning to continue to deliver environmental and financial benefits 24 hours a day, 365 days of the year. By facilitating intelligent management of our living and working spaces, reducing energy consumption and emissions, AI has the power to ensure a safer, more sustainable, future for us all. Sources: 1,2,4,5,6,7,8,9 ABB draft white paper – ‘Artificial Intelligence (AI) in the building sector as a change driver towards carbon neutrality’ 3 https://www.bloomberg.com/ news/articles/2022-11-09/cop27- can-the-building-sector-clean-up- its-act 10 ABB case study: ‘Manchester Metropolitan University secures top sustainability rating with ABB smart building scheme’ 11 https://www.ibm.com/thought- leadership/institute-business- value/report/buildingintelligence