Background

inBetween - Monitoring, analysing & nudging towards energy efficiency

Background

Nowadays, we spend more than 80 percent of our lives within buildings. At the same time, households represent around 30 percent of the total energy consumption, with electricity consumption often higher than necessary. Making residents aware of this by analysing their consumption patterns and providing them with feedback therefore has the potential to generate significant energy savings: Informing electricity users about their energy consumption can trigger important psychological processes that can cause people to adjust their lifestyle and consumption preferences3 (for example by using energy-efficient vacuum cleaners or efficient light-emitting diodes (LEDs) instead of light bulbs, turning off espresso machines when not in use or using an eco-program on the washing machine).

At the same time, from an operator’s perspective, predicting electricity consumption is a vital for operating smart grids, especially when power is drawn from renewable power plants that are highly dependent on the weather. Thanks to recent developments in IoT (Internet of Things) devices and the current state of data processing technologies, we can now precisely monitor and analyse electricity consumption and predict electrical energy consumption using state of the art data-mining methods.

The name of the inBetween project is an acronym for “ICT-enabled BEhavioral change ToWards Energy EfficieNt lifestyles”. It was funded by the European Horizon 2020 fund and focused on how to use information technology to investigate energy-efficient residential lifestyles. The project monitored and analysed energy consumption behaviour inside residential buildings and predicted possible energy use as well as energy-saving potential. According to the project report, “the main motivation for such development is that more than 30% of the world’s electricity can be attributed to the residential and commercial buildings […] this figure can be reduced by up to 12% by only giving feedback to the customers on ways in which they consume their energy on an appliance level.”4

Project partners included:

• AIT Austrian Institute of Technology (research and technology organization responsible for data mining and evaluation) • Rina (private company responsible for integrating middleware, platform architecture and project coordination) • PUPIN (R&D institute responsible for mobile application deployment and middleware)

3 For an literature overview see: Dosmukhambetova, D. (2020). The use of behavioural insights in promoting residential energy efficiency: an overview of available literature. Auckland Council technical report, TR2020/015 4 Cited from inBetween’s non-public 1st Period Project Report. A summary of this internal project report can be found on the EC’s Cordis website