On a scorching summer day at Toronto’s Humber College, a smart system precools buildings in the early morning to avoid the afternoon spike in electrical rates at peak demand time. Another system turns on lights in rooms only when people are using them. And when the weather is cold, heat pumps have learned to redirect heat from crowded spaces on campus to other buildings that can use some warming.
Since 2014, Humber College facilities have grown by 25 per cent, yet the school’s use of smart controls as well as energy-efficiency initiatives and retrofits has reduced energy use per square foot by more than 20 per cent.
And the college is on track to achieve a 30-per-cent reduction in greenhouse gas emissions compared with a decade ago, says Aman Hehar, Humber’s associate director of energy and climate change.
It meant installing smart sensors throughout the school, and in older buildings with poor envelopes, it meant retrofitting windows and insulation to make them more efficient, he explains.
“Having the separate systems share information with each other is making the buildings run as optimally as possible,” he says.
It’s part of a collaboration between Humber College and Siemens Canada that developed a sustainable microgrid and renewable technology (SMART) lab that will be used to teach students about microgrids – systems that reliably manage the generation, storage and consumption of energy.
As the number of sensors, cameras and many other data-collection devices increases in buildings, so does the need for new tools to make sense of the massive amount of information being gathered, says Faisal Kazi, president and chief executive officer of Siemens Canada.
“Buildings represent about 40 per cent of global energy use and 27 per cent of emissions are from building operations. By creating digital twins – virtual versions of physical assets – we can optimize buildings to reduce their energy use and significantly lower their carbon footprint,” Mr. Kazi says.
While developing digital twinning to compare an optimal digital model to actual performance has been used in the past, until now, most systems for buildings have been independent silos, addressing only one sector or comparing only part of the infrastructure, Mr. Kazi says.
“Artificial intelligence can improve the efficiency of digital twins by providing insights that go beyond what real-world sensors provide,” he says. “[AI] can also make predictions about the future based on the data it receives. And it can then predict which actions would achieve the desired outcomes and make adjustments automatically. Plus, algorithms can quickly pick up on any abnormal information from the sensors.”
At the Collision 2023 conference in Toronto in June, Siemens launched Siemens Xcelerator, an open, scalable digital platform that monitors and manages all building systems and communicates with power grids to maximize their collective performance. The technology to monitor structures is known as Building X.
“These things can all be quantified into data that can be compared to the performance of other buildings so managers and engineers can make decisions on ways to improve,” Mr. Kazi says. “With artificial intelligence, you can detect problems before they occur, optimize operating costs more efficiently and precisely predict tomorrow’s energy consumption with today’s data.”
Building X puts building data from multiple sources and systems on a single cloud-based dashboard that is not limited to using Siemens’ hardware, so vendors and other building management companies can integrate their existing systems into the platform, reducing the initial investment and additional costs, he adds.
General Electric, Microsoft, IBM, ABB and Honeywell all have digital twin systems, with many companies offering specialized systems to analyze communications, engineering, real estate and health care.
“From a business point of view, aligning building environment, lighting and air quality to keep people feeling comfortable and not too hot or cool can have an important impact on productivity and shareholder value,” Mr. Kazi explains.
The trend is in how quickly the information can travel. Data-communication speed and volume between systems have evolved with more processing power and memory as prices of controls have decreased, so you can have huge volumes of information flowing back and forth between systems, which would have been very costly in the past, Mr. Hehar says.
“While humans still make the decisions today, the future is in machine learning, where systems can analyze vast amounts of data on the fly and make the changes automatically without needing intervention to optimize performance,” he says.
With the support of the Ontario government and Siemens, Humber’s investment in the SMART lab features sustainable digital technology, including a microgrid monitoring and controller system, distribution infrastructure, as well as generation and load simulation equipment. Battery energy storage systems and solar power generation allow for more efficient and sustainable use and consumption of electrical power. These small-scale power grids can operate on their own or as part of a larger grid, Mr. Hehar says.
An innovative test system is the Smartflower, an array of solar panels shaped like petals that follow the sun throughout the day, maximizing the amount of electricity that is generated. The Smartflower can generate 40 per cent more electricity than a comparable-sized stationary panel.
In the past five years, there has been an increasing focus on reducing emissions, energy efficiency and operating cost savings. Humber’s goal date to achieve net-zero greenhouse gas emissions is 2050, “but we’ve got a lot of things in place now, and we’re hoping to get there sooner,” Mr. Hehar says.
“All these are good investments that will pay off quickly. We’re trying to find things that are good for the planet and are financially beneficial for the college, while making the buildings more comfortable and the best environment to learn in,” he adds.
“That’s what these systems are accomplishing.”