Ad: AI reduces energy consumption and carbon emissions in commercial real estate

Commercial HVAC systems optimised using AI algorithms yield  benefits for all parties and are fast becoming a preferred solution to making buildings more energy efficient, reducing operating costs and carbon emissions.

Heating, ventilation and air conditioning (HVAC) systems are usually the largest energy-consuming loads in commercial real estate. For this reason, energy efficiency measures that target HVAC can achieve major savings and significantly reduce emissions and using today’s technological advances, it has become easier than ever before.

Why does building optimisation matter?

Research shows that buildings in the EU account for around 40 percent of total energy use and are responsible for some 36 percent of greenhouse gas emissions. A typical HVAC system uses around 39 percent of a building’s total energy consumption, and it is estimated that around 75 percent of buildings in the EU are energy inefficient, meaning a large part of the energy used goes to waste, creating unnecessary greenhouse gas emissions.

The built environment must therefore progress decarbonisation urgently for a number of reasons, the first being that the Minimum Energy Efficiency Standards (MEES) are now in force, and it is a legal requirement for buildings to become increasingly energy efficient over the next few years.

The second, soaring energy prices, have brought building optimisation quickly up the agenda for building owners and managers. And in addition, the demand for green buildings is rising rapidly as found in the recent RICS Sustainability Report.

The report found that occupier and investor demand for green buildings is continuing to rise in the UK, with nearly half of respondents reporting lower rents and sale prices for non-sustainable buildings.

Building owners and managers must adopt a holistic, systemwide approach and establish smart HVAC systems in their buildings if they are to better manage energy use whilst maintaining balance between occupant comfort and energy consumption.

So, what does it take to equip a building with a smart HVAC system?

Well not that much really, especially if there’s already a traditional HVAC control system in place like a building management system (BMS). The BMS receives control data such as building temperature, humidity and CO2 levels, and outdoor weather conditions from multiple sensors.

So, when it gets dark outside, indoor spaces become overcrowded, or when outdoor temperatures change, the BMS system responds automatically to adapt the indoor environment using predefined setpoints.

An AI-based solution, like Evotech’s myBEMS, uses non-linear control techniques instead of a rule-based approach, processing real-time data from sensors and adjusting the system automatically. myBEMS constantly analyses the data inputs using advance machine learning algorithms.

It notices the subtlest of changes in outdoor temperature, weather forecast and occupancy and adjusts the BMS and HVAC settings accordingly, monitoring multiple parameters, specifying set points, turning units on or off, and performing a number of other actions. All this happens autonomously, to keep building occupants comfortable whilst reducing energy consumption and carbon emissions.

Traditional BMS and HVAC systems allow users to manually adjust temperature, ventilation rates, and other parameters to achieve the desired indoor environmental comfort. However, this is often driven by occupant complaints leading to differing micro-climates within floor spaces, with demands for both heating and cooling plant to run at the same time.

Ageing BMS and HVAC control systems, often blighted with software glitches, uncalibrated and faulty sensors and switches and lack of user experience, are all too often to blame for a building’s HVAC plant running far longer than needed due to rogue heating, cooling and ventilation demands.

As the ventilation, heating and cooling needs of a building are constantly changing, the control system is vital in ensuring the efficient running of HVAC plant to deliver the required occupant comfort. myBEMS is able to adapt to these changing circumstances, processing real-time data from IoT sensors and adjusting the HVAC system automatically.

The system is able to analyse occupant behaviour and continually learns, modifies and improves its algorithms to provide deeper insight into how the building performs. This delivers greater energy efficiency, cost reductions and occupant wellbeing over the long term.

A good example to highlight this is that many buildings have ventilation systems that operate at full airflow all the time which wastes a significant amount of energy, as cooling or heating higher volumes of outdoor air uses much more energy and emits higher levels of greenhouse gases.

When ventilation controls have AI, they can determine the optimal airflow required by the building. The system can also track the number of occupants in the building, and the concentration of key air pollutants like VOCs and particulate matter (PM) automatically increasing ventilation as it does so.

And the benefits are vast for both building occupants and building managers alike, with the system reacting quickly to the needs of occupants whilst significantly reducing energy bills and cutting carbon emissions as it does so. In fact, one of our client’s buildings has already saved 114.3 tCO2 in carbon emissions in less than 9 months, helping improve ambient air quality. Overall, typical annual energy savings of 20 – 40 percent can be achieved with a ROI less than 12 months.

For more information about myBEMS, Evotech’s smart AI technology for commercial HVAC systems, please visit Evotech online.


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