Quick results by utilising AI to optimise energy consumption

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The Danish Municipality of Holstebro began using Ento's AI-based Energy Advisor in August 2021, achieving significant savings from the start and continuing to do so ever since. This reduction in energy consumption could only happen by replacing their old “data collecting” system with a more modern one, focused on actionable insights.

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The struggle of a small energy team with a large building portfolio

When you are a small energy team with a large building portfolio you have to prioritise your efforts. That was one of the realisations from the team in Holstebro Municipality, Denmark. With automated analytics, the employees have spent less time on manual analysis of energy consumption and more time in their buildings – creating value.

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More time spent in the buildings, less time spent analysing data

Holstebro Municipality has a facility management team dedicated to operations and maintenance of the municipality’s 230,000 m2 (2.5 million square feet) of properties.

The team is responsible for technical installations, construction and renovations, energy budgets, exterior maintenance, and carries out inspections to solve problems in the buildings.

Three people are responsible for energy, engineering, and installation, and five for construction projects and building maintenance. Energy management is just one of the centre’s many tasks. It is a complex task to manage the buildings, and it is therefore essential for Holstebro Municipality to have the right tools to support the employees.

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The conventional EMS did not provide any benefits

An essential tool for energy management can be an energy management system (EMS), which collects and clarifies data on energy consumption in buildings. But until the municipality replaced its EMS, the energy management team faced several challenges. Data came in from their loggers on electricity, water, and heat meters, but it required a lot of maintenance. For instance, when changing meters and adding buildings to their portfolio. Additionally, there was low confidence that the data was accurate. It, therefore, took too much time from the energy employees’ other tasks to maintain the system, and it was thus not used in practice.

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Ento's AI-based solution allowed a prioritised effort

The project manager in Team Fælles Ejendomscenter, Thøger Niels Pørtner, was hired to, among other things, decide what should happen to the municipality’s EMS. He had experience with various EMSs from previous employments and considered different systems. From that experience, he knew that the number one goal of choosing a system is that it’s going to support the everyday life of a small energy team. He and his colleagues need to be in the buildings while the EMS runs by itself, letting them know how they are doing.

With these pieces of information, the municipality got in talks with Ento.

“Had we bought another software where we would have to sit and manually configure the buildings, data and alarms ourselves, then we wouldn’t be done with the configuration yet” says Thøger Niels Pørtner.

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Electricity, heat, solar, and water will be monitored by AI

Holstebro is using Ento to analyse electricity, district heating, water, and solar PV data. The system is AI-based and utilises data from the systems users’ buildings, as well as external variables such as weather data, calendar and Covid-lockdown information, to identify deviating consumption patterns. In practice, it works in such a way that when Thøger and his colleagues access the system, they get to highlight the buildings with an increased or changed consumption that indicates ‘something is wrong here’.

Based on this information, they prioritise which buildings they should visit to identify and implement energy savings. This releases time to talk to the operational staff in the buildings. When the municipal employees return to the office, they can also report implemented measures in the system and keep an eye on whether they achieve the expected savings over the next few months.

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The new system has led to substantial energy savings

Thøger Niels Pørtner emphasises that even though it costs money to invest in data driven energy management, there is more money to be saved; this applies in the form of energy savings and the working hours the system saves employees from spending on data loggers, setting up reports, etc.

In the first year of using Ento, the municipality saved more than DKK 1 million. While monitoring of heating and water consumption was introduced at a later stage, a significant portion of the savings can be attributed to optimising electricity consumption. This was achieved primarily through adjustments to ventilation systems and fine-tuning settings in the building management systems.

“It’s cool that the analysis work and data processing now takes up so little time, that we can use our energy in the buildings. Now the time is spent on what creates value. It may be that some of the analyses seem simple but in my view, it is better than what we can do. And we trust that there is something to act on when we go out to the buildings,” says Thøger Niels Pørtner.

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