• • • SMART BUILDINGS & IOT • • •
it’s about the individual building’s requirements. However, some things will remain consistent: the need to drive down energy usage, move towards carbon net zero, improve indoor air quality and provide an impressive and comfortable experience for occupants. All of this is harder to achieve when a building’s data is sitting in siloes, underutilised and unable to provide a 360-degree view of what a building can really offer.
Utilising technology to
widen potential To reach this potential, we have to get deep below the surface level of smart technologies to unlock the insights they generate. This happens when we connect smart technology systems together to create an ecosystem or platform for smart solutions, looking at the bigger picture. The data and insights this creates can then be analysed to make vast improvements across a building, and even the whole enterprise. To make this a reality, the data needs to be
connected and easily accessible in the cloud. Then decision makers can analyse the data in its entirety and identify areas of improvement. They can focus this analysis on processes such as maintenance, energy savings and sustainable
development – wherever needs attention at that time. Then, they can pinpoint the smart technologies that can make these adjustments autonomously and improve the experience that tenants receive. From these foundations, building and office decision-makers can create something which is truly smart. Once the building data is embedded and
utilises technologies such as Artificial Intelligence (AI) and Machine Learning (ML), we can truly reap the rewards and increase occupant safety and comfort, while saving on costs and achieving sustainability targets.
Control over goals With the use of technology, including data and tracking software with AI and intuitive dashboards that follow indoor air quality and energy consumption, our buildings can make predictions with smart algorithms. Based on historical patterns, algorithms
predict load profiles as well as plant and equipment-level energy performance at different operating conditions. Every major piece of equipment, including chillers, boilers, pumps, cooling towers and energy storage, has an energy model that predicts the equipment’s
performance under different operating conditions. The optimisation algorithms run every 10-15
minutes to decide ‘dispatch decisions’. Here, it decides which equipment to turn on or off and what system level setpoints to run for a wide variety of cooling, heating, and power generation systems. This continuously minimises costs and reduces energy. Analytics and AI solutions have historically
focused on solving one goal at a time, whether it be clean air, energy efficiency, safety, or even comfort and experience. However, measuring, tracking and acting on data gives us control over every single goal we want to achieve.
Democratise data now to
save money later As the UK is going through the turmoil of a recession, businesses are doing everything possible to keep costs low and return on investment high. However, we must keep in mind that cost savings, energy efficiency, and clean air can all coexist. We can begin to see a change in our buildings with AI, ML, and democratised data that will improve.
26 ELECTRICAL ENGINEERING • DECEMBER 2022/JANUARY 2023
electricalengineeringmagazine.co.uk
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