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Customer application 18 January 2022

Using Artificial Intelligence to Reduce Heating and Air-Conditioning Costs

Automation specialists mrm² have developed a system that employs machine learning to make heating and cooling office and industrial buildings significantly more efficient, and reduces energy costs by up to 20 %. WAGO provides the PFC200 Controller and Edge Computer, two key components in the system.

It all started a few years ago, when Marc Gruber, co-founder and Managing Director of mrm², wanted to build a house for his family. Gruber’s company, which includes around 30 employees and is headquarters in Bad Ditzenbach-Gosbach in Swabia, specializes in intelligent automation technology. So obviously, building technology from a pre-digital era was unlikely meet his standards for use in his own house. “I took a good look around at all of the products available to automatically control heating systems – and was completely underwhelmed. Everything on offer was simplistic, without a shred of intelligence,” he recalls. Only one possibility remained: “If there’s no intelligent solution on the market, we’ll just have to build one ourselves!”

No sooner said than done! The experts at mrm² developed a system to keep each room at exactly the desired temperature when occupied. The key to this is artificial intelligence (AI): Integrated machine learning methods predict when and for how long individual rooms will be used. Using this knowledge, the heating elements or heating surfaces can be controlled so to provide comfortable temperatures precisely when needed with the lowest possible energy consumption. This prevents the heating system from warming rooms up unnecessarily and continuing to run. In the summer, the system keeps the climate control systems operating efficiently on an as-needed basis. Movement sensors provide the necessary data for predicting occupancy. In offices, these are often already installed anyway, in order to regulate the lighting.

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“The Optimal Interplay among the Building Systems”

“Thanks to the AI, our solution is able to take information about changes in the usage of individual rooms and very quickly incorporate it into the control process,” explains Gruber. The system can also factor weather predictions into the calculations. For example, if sunshine is expected in one room at a certain time in the winter, then the supply temperature for the heating can be set somewhat lower than on overcast days.

The positions of the blinds are also targeted to increase energy efficiency in the building. This is most important in the spring and fall, when rooms need to be heated or cooled according to outdoor temperatures and sunshine. According to Gruber, this is unique on the market. “Other solutions are isolated applications, which control only the heating or only the blinds. In contrast, we bring it all together,” he explains. And he is quick to emphasize that “WAGO’s technology allows us integrate heterogeneous building automation systems in the best possible way!”