Building energy efficiency faces growing pressure

The value of a building is greatly affected by the energy efficiency of the building. With the help of IoT, energy optimization is becoming one of the most effective ways to reduce energy use, thereby increasing property value and reducing CO2 emissions.

The world is getting smarter - cars drive themselves, drones cultivate apple trees, body sensors monitor human health , and many other smart IoT applications. However, one industry sector that has been rather slow to adapt to smart solutions is the building sector, although the energy efficiency of buildings is a hot topic – and for good reason: Overall, buildings in the EU account for 40% of energy consumption and 36% of greenhouse gas emissions are simply unsustainable

Today, 75% of buildings in Europe are not energy-efficient buildings, and it is predicted that by 2050, 95% of them will still be In use, this means that, especially in times of energy crisis, owners will waste a lot of money. To meet the EU's overall target of reducing emissions by 55% by 2030, the building industry needs to reduce its own emissions by 60%, which is very demanding. Requirements

Europe is going through an energy crisis and many utilities are falling back on fossil energy production to meet demand. The call for action is strong, but money, time and resources are limited. The most important question is where to invest.

Where to invest – steel and concrete or IoT and AI?

The short answer is: both!

SOLVED Obvious solutions to the above challenges are to improve building insulation, replace windows, and replace fossil heating systems with heat pumps and solar panels. Obviously, this is something that needs to be done, but let’s face it, it’s not going to happen overnight. The current energy renewal rate for the European building stock is 1%, and most of the global building stock that currently exists will still be there in 2050. If the building sector is to reduce its carbon emissions by 60% by 2030, the energy renewal rate of Europe's building stock will need to double – a considerable sum given the cost of procuring building materials and the scarcity of resources in the sector. challenge.

For many industries, digitalization offers another way to deal with challenges. Collecting various data related to the indoor climate of the building, weather conditions outside the building, energy consumption and heating system performance, and analyzing and visualizing this data can generate valuable insights into the energy performance of the building and further guide heating and cooling systems optimize the building’s energy consumption and minimize carbon emissions.

In this approach, value is created not by insulating buildings and replacing windows, but by leveraging IoT and artificial intelligence engines to collect and process building data. The technology is already there, requiring much less investment than mechanical construction and delivering results much faster. But we must also be clear: smart building solutions complement building energy transformation, not replace it!

But the reality is that the construction industry is a bit behind in digitalization. The collection and visualization of data can be used not only to reduce energy consumption, but also to support decisions about where and why to invest. Today, 80-90% of an organization's data is unstructured. The data points needed to optimize energy efficiency, such as humidity, temperature, electricity consumption, building infrastructure, etc., are often available and structured.

Meanwhile, only a few people know or remember that pioneering work in smart buildings dates back to 1977 - the year James Southerland, a young engineer at Westinghouse Electric, built his ECHO IV (Electronic Computing Home operator) computer. In addition to proving that the control panel can control alarm clocks and TVs, it can also remotely control thermostats - very forward-looking at this point in time!

Back to the present day, reflect on the business value of building energy management.

Money Talks – Business Benefits of Energy Management

Data-driven reductions in energy consumption will significantly reduce energy costs. Looking at larger multi-tenant buildings, and of course depending on the circumstances, annual energy cost reductions of 10%-15% are easily achievable, particularly by lowering and more dynamically adapting the supply temperature of the heating system. This is classic low-hanging fruit!

Another critical aspect, and perhaps more worthy of monitoring, is the early detection of technical failures in heating systems. Typical problems are a faulty temperature sensor or valve servo motor. In addition to unnecessary energy costs, subsequent repair or replacement costs can be avoided. Remote detection and analysis helps minimize on-site visits by service personnel, allowing them to resolve issues on the first visit.

From a property owner's perspective, property value is obviously of critical importance. Investment funds are optimizing their real estate portfolios from an energy efficiency perspective. While extremely energy-inefficient buildings run the risk of becoming stranded assets, investments in energy management and optimization can significantly increase property values.

As can be seen, investing in data-driven building energy management can generate significant business value in a short period of time with limited investment. This will not eliminate the need for building energy retrofits, but it can quickly improve energy efficiency. The data collected will further provide insights into where to invest in renovations to maximize return on investment.

Conclusion and Outlook

Intelligent building energy management has come a long way since James Southerland built the ECHO IV home computer in 1977, and there is clear potential in the building sector. From a digital laggard to an innovation hotspot.

The concept of virtual sensors allows the aggregation and combination of data from various sources without the need to install physical sensors at every location.

Creating comprehensive digital twins of buildings is becoming increasingly realistic, powered by accelerated data streams from physical and virtual sensors. A digital twin represents not only the physical structure of a building, but also all active operating technologies and building usage. Energy efficiency is just one of many aspects of building management.

Machine learning and artificial intelligence are the beginning of data-driven smart buildings that can control themselves and continuously learn new patterns to self-optimize operations.

There are many contributing factors to the success of building automation, from artificial intelligence systems to sensors and actuators, and last, but not least, IoT connectivity. In this sector of the industry, the key to success also lies in shared value creation within the ecosystem to turn smart buildings into a reality.

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