Large commercial buildings often struggle with inefficient energy use, especially in heating, ventilation, and air conditioning (HVAC) systems. By using occupancy profiles—data that tracks how many people are in different parts of the building—HVAC systems can adjust in real-time, reducing energy use and improving comfort.
This case study shows how Tallinn’s Ülemiste City achieved significant energy savings through this approach.
The challenge
One of the main challenges with HVAC systems in large commercial buildings is their inefficiency. According to data from the U.S. Department of Energy, these systems can account for as much as 70% of a building's total energy consumption. In addition to high energy use, poorly maintained HVAC systems can lead to tenant discomfort, impacting the overall environment of the building.
The goal of our project was to reduce energy consumption in a large office space in the Nordics. To achieve this, the HVAC analytics partner of the building updated the occupancy profile based on real-time data. The data indicated the number of people inside the building at any given time.
Our approach
Elevator data played a key role in this optimization process.
- Using Elevator Data: Data was collected from KONE elevators in the building, covering six elevators across 13 floors. This data helped track how many people were using the space at different times.
- Occupancy Profiles: KONE provided information on how full each floor was at various times, which was then analyzed by the HVAC (Heating, Ventilation, and Air Conditioning) analytics partner. They used this information to adjust the building's air conditioning system to match the actual number of people in the building.
- Making Adjustments: The HVAC partner used this data to fine-tune the Air Handling Units (AHU), ensuring it worked more efficiently when fewer people were in the building, and provided more cooling when needed during busier times.
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Solution
The impact of these changes was significant:
- Energy Savings: By optimizing the air conditioning system, the building saved 36% of its energy (compared with a standard, non-optimized building state), which equals around 45,000 kWh each year. This also resulted in financial savings of EUR 6,000 annually, with a total potential savings of EUR 348,000 over the building's lifetime.
- Reducing Carbon Emissions: These energy savings also helped the environment, reducing carbon emissions by 21 kg every year, and 1,320,000 kg over the building’s lifetime.
- Happy Tenants: The best part? The tenants in the building didn’t even notice the change, with no complaints about comfort during the first three months after the adjustments were made.
Why it matters
This case study in the Nordics is a great example of how smart data can help businesses save energy and reduce costs. By using data from the building’s elevator system, the HVAC partner was able to adjust the air conditioning system based on how many people were in the building at different times.
Data source: https://www.eia.gov/energyexplained/use-of-energy/commercial-buildings-in-depth.php
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