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User-Adapting System Design for Improved Energy Efficiency During the Use Phase of Products: Case Study of an Occupancy-Driven, Self-Learning Thermostat

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Sustainability Through Innovation in Product Life Cycle Design

Part of the book series: EcoProduction ((ECOPROD))

Abstract

Tailoring products to user requirements can improve the energy efficiency without sacrificing user satisfaction. This study considers the case of an occupancy-driven smart thermostat in an office environment. Identifying patterns in past user behaviour enables occupancy prediction to control the heating accordingly. Potential energy savings and related environmental impact reductions, compared to a fixed schedule heating system, are calculated for various heating and building types in three regions (Leuven, Calgary and Tokyo) to account for variations in climate. The obtained energy savings range between 93.2 and 546.5 kWh per year and environmental impact reductions between 2 and 38 EcoPoints.

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Notes

  1. 1.

    Momit: www.momit.com/smartthermostat.html. Lyric: lyric.honeywell.com. Tado: www.tado.com

  2. 2.

    The used LCI datasets are:

    1. 1.

      Heat, district or industrial, natural gas {RoW}|heat production, natural gas, at boiler modulating >100 kW

    2. 2.

      Heat, district or industrial, other than natural gas {RoW}|heat production, heavy fuel oil, at industrial furnace 1 MW

    3. 3.

      Heat, district or industrial, other than natural gas {RoW}|heat production, at hard coal industrial furnace 1–10 MW

    4. 4.

      Heat, district or industrial, other than natural gas {RoW}|heat production, softwood chips from forest, at furnace 1000 kW

    5. 5a.

      Electricity, low voltage {BE}| market for

    6. 5b.

      Electricity, low voltage {JP}| market for

    7. 5c.

      Elecbtricity, low voltage {CA-AB}| market for

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Acknowledgments

The authors would like to thank IWT Vlaanderen for the financial support and Prof. D. Cattrysse for facilitating a real-life use case.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, KU Leuven, Leuven, Belgium

    Y. De Bock, A. Auquilla, K. Kellens, D. Vandevenne & J. R. Duflou

  2. Department of Computer Science, University of Cuenca, Cuenca, Ecuador

    A. Auquilla

  3. Computational Modeling Lab, Vrije Universiteit Brussel, Brussels, Belgium

    A. Nowé

Authors
  1. Y. De Bock
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  2. A. Auquilla
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  3. K. Kellens
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  4. D. Vandevenne
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  5. A. Nowé
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  6. J. R. Duflou
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Corresponding author

Correspondence to Y. De Bock .

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Editors and Affiliations

  1. National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

    Mitsutaka Matsumoto

  2. National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

    Keijiro Masui

  3. Osaka University, Suita, Japan

    Shinichi Fukushige

  4. National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

    Shinsuke Kondoh

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De Bock, Y., Auquilla, A., Kellens, K., Vandevenne, D., Nowé, A., Duflou, J.R. (2017). User-Adapting System Design for Improved Energy Efficiency During the Use Phase of Products: Case Study of an Occupancy-Driven, Self-Learning Thermostat. In: Matsumoto, M., Masui, K., Fukushige, S., Kondoh, S. (eds) Sustainability Through Innovation in Product Life Cycle Design. EcoProduction. Springer, Singapore. https://doi.org/10.1007/978-981-10-0471-1_60

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