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Business Model Analysis of Geo-TABS Buildings with Predictive Control Systems

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Cold Climate HVAC 2018 (CCC 2018)

Part of the book series: Springer Proceedings in Energy ((SPE))

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Abstract

This paper investigates the conceptual framework and impacts of business models in model predictive control (MPC)-based geothermal Thermally Active Building System (Geo-TABS). The analysis is done by compiling technical, political, economic, social and environmental analytical frameworks of MPC Geo-TABS. The elements of the business model Canvas are identified and analyzed in this application. Theoretical bases of business model generation are verified by substantiating arguments and potential profit analysis for stakeholders via four demonstration buildings. The focused building types/cases involve office building, schools, elder-care houses and multi-family house. Methods to verify the proposed value propositions in the business model are given special interests. The results show that correctly sizing and combining the four major components: MPC, geothermal, TABS and suitable building types, are the core in both technical and business development perspectives. Complete design guidelines are crucial for promoting MPC Geo-TABS business in its service chains. Transforming the conventional economy-oriented business development method to holistic sustainability-oriented profit matrix can further strength the value propositions of MPC Geo-TABS. The findings aim at supporting decision-makers and further improving engineering guidelines in implementing MPC based Geo-TABS in a larger scale in Europe.

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Abbreviations

AHU:

Air-handing units

B2B:

Business to business

COP:

Coefficient of performance

DHW:

Domestic hot water

Geo:

Geothermal, including both active and passive ground-source systems

GSHP:

Ground-source heat pumps

HVAC:

Heating, ventilation and air conditioning

LT/MT/HT:

Low temperature/Medium temperature/High temperature

IPR:

Intellectual property rights

MPC:

Model predictive control

PMV-PPD:

Percentage of mean vote based predicted percentage dissatisfied

TABS:

Thermal active building systems

VP:

Value proposition

θ :

Temperature, ℃

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Acknowledgements

The authors are grateful to European Union for providing financial support in Horizon 2020 project “Model Predictive Control and Innovative System Integration of GEOTABS in Hybrid Low Grade Thermal Energy Systems-Hybrid MPC GEOTABS”. We also gratefully appreciate the support of DTU Technical University of Denmark, Feramat Cybernetics Ltd. for providing valuable information in the project.

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Authors and Affiliations

  1. Division of Fluid and Climate Technology, Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Brinellvägen 23, 100 44, Stockholm, Sweden

    Qian Wang

  2. Uponor AB, Hackstavägen 1, 721 32, Västerås, Sweden

    Qian Wang & Suleyman Dag

Authors
  1. Qian Wang
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  2. Suleyman Dag
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Corresponding author

Correspondence to Qian Wang .

Editor information

Editors and Affiliations

  1. Division of Building Services, Lund University, Lund, Sweden

    Dennis Johansson

  2. Division of Building Physics, Lund University, Lund, Sweden

    Hans Bagge

  3. Division of Building Services, Lund University, Lund, Sweden

    Åsa Wahlström

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Wang, Q., Dag, S. (2019). Business Model Analysis of Geo-TABS Buildings with Predictive Control Systems. In: Johansson, D., Bagge, H., Wahlström, Å. (eds) Cold Climate HVAC 2018. CCC 2018. Springer Proceedings in Energy. Springer, Cham. https://doi.org/10.1007/978-3-030-00662-4_64

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  • DOI: https://doi.org/10.1007/978-3-030-00662-4_64

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00661-7

  • Online ISBN: 978-3-030-00662-4

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