“We have an ambitious energy action plan, so one of my most important tasks is to ensure that we use electricity and heat as efficiently as possible. The operation of our buildings constitutes one of the greatest potentials for energy savings in the municipality at all, so this is something we have a strong focus on”.
The municipality already has an energy management program, but it has not been kept up to modern standards. It is too inefficient and time-consuming to manually analyze data from electricity meters to make them concrete and valuable for identifying any energy fluctuations at the municipality’s many schools, stadiums, etc.
Pernille decided to search for new tools and entered into a dialogue with the Danish entrepreneurial company Ento Labs, which has solved similar energy optimization tasks for other municipalities and companies using artificial intelligence.
“I was primarily concerned with the level of detail that lay in monitoring each property’s energy consumption. Previously, when I contacted the reponsible staff at one of our schools due to an unexpected increase in their energy consumption, it was difficult for me to give him a more accurate indication of what “leak” he should look after. I can do better now. The system captures the exact time and how the usage pattern changes”.
Basically, artificial intelligence automatically analyzes consumption and suggests potential energy savings – an overview that Pernille has access to via an online portal. The solution is based on electricity data from the utility and includes several other sources to give artificial intelligence a deeper understanding of the energy consumption.
“One of the extraordinary things about the platform is the automatic loading of data, e.g., the weather, holidays and vacations, the building, and even information about the shutdown due to Coronavirus. In this way, we can, for example, avoid an alarm when the school children return from the summer holidays. At the same time, it automatically picks up increases in the usage pattern – something I really appreciate, as I no longer have to go in and analyze myself”.
Of the municipality’s total 450 properties, 210 are relevant to analyze. Artificial intelligence has already identified the first handful of buildings, and Pernille expects more, both large and small energy savings along the way.
“We have always been able to access and retrieve electricity meter data from Energinet’s DataHub. But where it really makes a difference for us as users is when the platform adds an extra layer of intelligence that gives us more insight so that we as a organization can become more efficient at optimizing energy. It helps us to reach our energy saving goals faster and ultimately make a difference to the green transition”.