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

  • Qian WangEmail author
  • Suleyman Dag
Conference paper
Part of the Springer Proceedings in Energy book series (SPE)


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.


Business model Geo-TABS MPC Sustainability EU buildings 



Air-handing units


Business to business


Coefficient of performance


Domestic hot water


Geothermal, including both active and passive ground-source systems


Ground-source heat pumps


Heating, ventilation and air conditioning


Low temperature/Medium temperature/High temperature


Intellectual property rights


Model predictive control


Percentage of mean vote based predicted percentage dissatisfied


Thermal active building systems


Value proposition


Temperature, ℃



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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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Division of Fluid and Climate Technology, Department of Civil and Architectural EngineeringKTH Royal Institute of TechnologyStockholmSweden
  2. 2.Uponor ABVästeråsSweden

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