Data-driven tool for early building energy performance diagnostic

Olaia Eguiarte*, Antonio Garrido-Marijuan, Iñigo López, Noelia Vicente-Gómez, Ander Romero-Amorrortu

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    The building sector is responsible for a large part of the final energy consumption in Europe. One of the most relevant steps in the process of reducing energy consumption in buildings is the energy performance diagnostic. In this paper, a data-driven methodology to obtain early energy performance assessment of commercial buildings using the energy signature approach is used. As a result, a web-dashboard and API that can analyse user data input and produce streamlined outputs like suggestions for energy-saving measures is developed. In order to prove the correct functioning of the tool, a demo site of a commercial building in Dublin has been used.

    Original languageEnglish
    Title of host publication36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023
    PublisherInternational Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems
    Pages3307-3314
    Number of pages8
    ISBN (Electronic)9781713874928
    DOIs
    Publication statusPublished - 2023
    Event36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023 - Las Palmas de Gran Canaria, Spain
    Duration: 25 Jun 202330 Jun 2023

    Publication series

    Name36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023

    Conference

    Conference36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023
    Country/TerritorySpain
    CityLas Palmas de Gran Canaria
    Period25/06/2330/06/23

    Keywords

    • Data-driven tool
    • building performance diagnostic
    • commercial buildings
    • energy signature

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