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Exploring the Potential of Home Energy Monitors for Transactive Energy Supply Arrangements

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Advances in Artificial Intelligence, Software and Systems Engineering (AHFE 2018)

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Abstract

There has been considerable investment in micro energy generation from both domestic consumers and small-scale providers. However, current metering arrangements and home energy monitoring products are too basic to enable real-time billing and remuneration, limiting the effectiveness of this investment. This paper describes the exploration of home energy monitors as a technical enabler to unlock the local trading potential of the investment in micro energy generation, and the human factors involved in interacting with these products that might pose obstacles to successful uptake. First, a human factors analysis of eight home energy monitors was conducted, which identified a number of usability issues. Next, a range of design concepts were developed to address the key usability problems identified, incorporate the forward-looking facility for alternative energy supply models, and stimulate further investment in energy prosumption. This study contributes an understanding of the potential of home energy monitors for transactive energy supply arrangements.

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Notes

  1. 1.

    According to a study reported in IEEE Spectrum (Oct 2017), many major companies are working on integrating Blockchain Technology into their products. This is seen as a disruptive development as we move towards a more ‘digital future’ and at the macro level it is seen as a better way, a more cost effective way, of managing data and trust interfaces.

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Acknowledgements

The study is funded by EPSRC (EP/R002312/1). We thank all those who were involved for their time and support.

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Correspondence to Andrea Taylor .

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Taylor, A., Stephen, B., Whittet, C., Galloway, S. (2019). Exploring the Potential of Home Energy Monitors for Transactive Energy Supply Arrangements. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2018. Advances in Intelligent Systems and Computing, vol 787. Springer, Cham. https://doi.org/10.1007/978-3-319-94229-2_48

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