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Data-driven quantitative analysis of an integrated open digital ecosystems platform for user-centric energy retrofits: A case study in northern Sweden

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  • Liu, Bokai
  • Penaka, Santhan Reddy
  • Lu, Weizhuo
  • Feng, Kailun
  • Rebbling, Anders
  • Olofsson, Thomas

Abstract

This paper presents an open digital ecosystem based on a web-framework with a functional back-end server for user-centric energy retrofits. This data-driven web framework is proposed for building energy renovation benchmarking as part of an energy advisory service development for the Västerbotten region, Sweden. A 4-tier architecture is developed and programmed to achieve users’ interactive design and visualization via a web browser. Six data-driven methods are integrated into this framework as backend server functions. Based on these functions, users can be supported by this decision-making system when they want to know if a renovation is needed or not. Meanwhile, influential factors (input values) from the database that affect energy usage in buildings are to be analyzed via quantitative analysis, i.e., sensitivity analysis. The contributions to this open ecosystem platform in energy renovation are: 1) A systematic framework that can be applied to energy efficiency with data-driven approaches, 2) A user-friendly web-based platform that is easy and flexible to use, and 3) integrated quantitative analysis into the framework to obtain the importance among all the relevant factors. This computational framework is designed for stakeholders who would like to get preliminary information in energy advisory. The improved energy advisor service enabled by the developed platform can significantly reduce the cost of decision-making, enabling decision-makers to participate in such professional knowledge-required decisions in a deliberate and efficient manner. This work is funded by the AURORAL project, which integrates an open and interoperable digital platform, demonstrated through regional large-scale pilots in different countries of Europe by interdisciplinary applications.

Suggested Citation

  • Liu, Bokai & Penaka, Santhan Reddy & Lu, Weizhuo & Feng, Kailun & Rebbling, Anders & Olofsson, Thomas, 2023. "Data-driven quantitative analysis of an integrated open digital ecosystems platform for user-centric energy retrofits: A case study in northern Sweden," Technology in Society, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:teinso:v:75:y:2023:i:c:s0160791x23001525
    DOI: 10.1016/j.techsoc.2023.102347
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    References listed on IDEAS

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    1. Linnea Löfving & Viktoria Kamuf & Timothy Heleniak & Sabine Weck & Gustaf Norlén, 2022. "Can digitalization be a tool to overcome spatial injustice in sparsely populated regions? The cases of Digital Västerbotten (Sweden) and Smart Country Side (Germany)," European Planning Studies, Taylor & Francis Journals, vol. 30(5), pages 917-934, May.
    2. Zhang, Chunbo & Hu, Mingming & Laclau, Benjamin & Garnesson, Thomas & Yang, Xining & Tukker, Arnold, 2021. "Energy-carbon-investment payback analysis of prefabricated envelope-cladding system for building energy renovation: Cases in Spain, the Netherlands, and Sweden," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    3. Hussain, Shahid & Ahonen, Valtteri & Karasu, Taha & Leviäkangas, Pekka, 2023. "Sustainability of smart rural mobility and tourism: A key performance indicators-based approach," Technology in Society, Elsevier, vol. 74(C).
    4. Shoaib Azizi & Gireesh Nair & Thomas Olofsson, 2020. "Adoption of Energy Efficiency Measures in Renovation of Single-Family Houses: A Comparative Approach," Energies, MDPI, vol. 13(22), pages 1-16, November.
    5. Gatt, Damien & Yousif, Charles & Cellura, Maurizio & Camilleri, Liberato & Guarino, Francesco, 2020. "Assessment of building energy modelling studies to meet the requirements of the new Energy Performance of Buildings Directive," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    6. Li, Y. & Kubicki, S. & Guerriero, A. & Rezgui, Y., 2019. "Review of building energy performance certification schemes towards future improvement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    7. Sobol’, I.M. & Tarantola, S. & Gatelli, D. & Kucherenko, S.S. & Mauntz, W., 2007. "Estimating the approximation error when fixing unessential factors in global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 92(7), pages 957-960.
    8. Gómez-Carmona, Oihane & Buján-Carballal, David & Casado-Mansilla, Diego & López-de-Ipiña, Diego & Cano-Benito, Juan & Cimmino, Andrea & Poveda-Villalón, María & García-Castro, Raúl & Almela-Miralles, , 2023. "Mind the gap: The AURORAL ecosystem for the digital transformation of smart communities and rural areas," Technology in Society, Elsevier, vol. 74(C).
    9. Sanhudo, Luís & Ramos, Nuno M.M. & Poças Martins, João & Almeida, Ricardo M.S.F. & Barreira, Eva & Simões, M. Lurdes & Cardoso, Vítor, 2018. "Building information modeling for energy retrofitting – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 249-260.
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    2. Marcon, Arthur & Ribeiro, José Luis Duarte & Olteanu, Yasmin & Fichter, Klaus, 2024. "How the interplay between innovation ecosystems and market contingency factors impacts startup innovation," Technology in Society, Elsevier, vol. 76(C).

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