How can climate emissions and the energy costs of properties be reduced? In Optiwise's experiment, the energy consumption of refrigeration equipment in supermarkets declined when better digital tools were obtained for energy management.

What kind of problem was the project trying to solve?

How can climate emissions and the energy costs of properties be reduced? Energy management and its digitalisation provide one answer to mitigating the energy consumption of, for example, the refrigeration equipment of supermarkets.

The majority of the working hours used for energy management are currently spent on collecting data from various systems. When this work is digitalised, the data scattered in a number of building service automation systems and automated refrigeration systems can be collected in one place in a well-visualised format that is easy to process.

Experts will no longer need to spend their work day on collecting data – instead, they can focus on analysing the data and implementing energy saving measures. With the same resources, service providers can administrate an even larger building stock and focus on concrete measures.

As a result, the energy costs of properties are declining, the conditions of users are improving, climate emissions are being reduced, the responsibility of operations is increasing and the value of properties is rising. The results can be used, for example, in offices, day-care centres, schools and care homes.

Objective: to eliminate manual work stages

The principal objective was to eliminate most of the manual work stages in energy management. The interim objective was to improve the visualisation and transfer of data between different systems by using open interfaces.

What was done in the project?

In the experiment, the digitalisation of energy management was piloted in seven commercial properties. Three of them were hypermarkets, three supermarkets and one was a convenience store at a petrol station. In addition, the use of artificial intelligence based on artificial neural networks was investigated.

A new feature added to the Optiwise application was the monitoring of electricity, heating and water consumption of the property, which covers the electricity, heat and water meters and their submeters. Their visualisation was improved to make it easy for experts to find a single site in a large mass of properties and focus on its hourly consumption.

Artificial intelligence based on artificial neural networks was also developed for the application to judge whether the refrigeration equipment was working properly by analysing the temperature data of the equipment. For example, artificial intelligence is able to recognise deviating too high and too low temperatures. Based on the notification given by artificial intelligence, the expert from the refrigeration service or energy management company can find out the cause of the problem and carry out the necessary measures to rectify the situation.

Who benefits?

In addition to business premises, the results of the experiment can be used widely in offices, day-care centres, schools and care homes. With the same resources, service providers can administrate an even larger building stock and focus on concrete measures. Energy will be used more efficiently and the costs and emissions will fall.

What were the outcomes of the experiment?

Energy management became considerably more efficient at the sites of the experiment. During the experiment, the energy consumption of refrigerating equipment at the pilot sites decreased on average by 15 per cent.

The results can be used as such and the measures carried out can be repeated in almost 3,000 supermarket facilities in Finland. The service also has export potential and, for example, in Sweden, Denmark and Norway, the number of potential sites is slightly higher than in Finland. The markets in the rest of Europe are even larger.

One of the concrete objectives set for the project was to enable one expert to manage hundreds of properties instead of a few dozen. Thanks to the experiment, one expert is now able to manage about 150 sites. The expert's use of time will become even more efficient when it becomes possible to benefit from the analysis carried out by artificial intelligence in the operations.