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Building Energy Simulation and Monitoring: A Review of Graphical Data Representation

Author

Listed:
  • Ofelia Vera-Piazzini

    (Laboratory of Building Physics, Università Iuav di Venezia, Via Torino, 153/A, 30172 Venezia, Italy)

  • Massimiliano Scarpa

    (Department of Architecture and Arts, Università Iuav di Venezia, Dorsoduro 2206, 30123 Venezia, Italy)

  • Fabio Peron

    (Laboratory of Building Physics, Università Iuav di Venezia, Via Torino, 153/A, 30172 Venezia, Italy)

Abstract

Data visualization has become relevant in the framework of the evolution of big data analysis. Being able to understand data collected in a dynamic, interactive, and personalized way allows for better decisions to be made when optimizing and improving performance. Although its importance is known, there is a gap in the research regarding its design, choice criteria, and uses in the field of building energy consumption. Therefore, this review discusses the state-of-the-art of visualization techniques used in the field of energy performance, in particular by considering two types of building analysis: simulation and monitoring. Likewise, data visualizations are categorized according to goals, level of detail and target users. Visualization tools published in the scientific literature, as well as those currently used in the IoT platforms and visualization software, were analyzed. This overview can be used as a starting point when choosing the most efficient data visualization for a specific type of building energy analysis.

Suggested Citation

  • Ofelia Vera-Piazzini & Massimiliano Scarpa & Fabio Peron, 2022. "Building Energy Simulation and Monitoring: A Review of Graphical Data Representation," Energies, MDPI, vol. 16(1), pages 1-26, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:390-:d:1018996
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    References listed on IDEAS

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    1. Francisco, Abigail & Truong, Hanh & Khosrowpour, Ardalan & Taylor, John E. & Mohammadi, Neda, 2018. "Occupant perceptions of building information model-based energy visualizations in eco-feedback systems," Applied Energy, Elsevier, vol. 221(C), pages 220-228.
    2. Costa, Andrea & Keane, Marcus M. & Torrens, J. Ignacio & Corry, Edward, 2013. "Building operation and energy performance: Monitoring, analysis and optimisation toolkit," Applied Energy, Elsevier, vol. 101(C), pages 310-316.
    3. Koldobika Martin-Escudero & Garazi Atxalandabaso & Aitor Erkoreka & Amaia Uriarte & Matteo Porta, 2021. "Comparison between Energy Simulation and Monitoring Data in an Office Building," Energies, MDPI, vol. 15(1), pages 1-24, December.
    4. Dario Cottafava & Giulia Sonetti & Paolo Gambino & Andrea Tartaglino, 2018. "Explorative Multidimensional Analysis for Energy Efficiency: DataViz versus Clustering Algorithms," Energies, MDPI, vol. 11(5), pages 1-18, May.
    5. Giuseppe Desogus & Emanuela Quaquero & Giulia Rubiu & Gianluca Gatto & Cristian Perra, 2021. "BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings," Sustainability, MDPI, vol. 13(8), pages 1-22, April.
    6. Tae-Keun Oh & Donghwan Lee & Minsoo Park & Gichun Cha & Seunghee Park, 2018. "Three-Dimensional Visualization Solution to Building-Energy Diagnosis for Energy Feedback," Energies, MDPI, vol. 11(7), pages 1-18, July.
    7. Yanxue Li & Weijun Gao & Yingjun Ruan & Yoshiaki Ushifusa, 2018. "Grid Load Shifting and Performance Assessments of Residential Efficient Energy Technologies, a Case Study in Japan," Sustainability, MDPI, vol. 10(7), pages 1-19, June.
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