Data-driven assessment for the supervision of District Heating Networks

Eguiarte, Olaia; Garrido-Marijuan, Antonio; Garay-Martinez, Roberto; Raud, Margus; Hagu, Indrek

doi:10.1016/j.egyr.2022.10.212

Cited by 8 publications

(1 citation statement)

References 10 publications

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“…A wide variety of datadriven models exist and have been successfully implemented for early building performance diagnosis. Moreover, several authors have implemented this approach at district scale [7][8][9]. Data-driven models can be classified in different groups and one of them is the black-box models, which are purely based on data and statistical techniques with no physical interpretation of the building.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Tool for Early Building Energy Performance Diagnostic

Vicente Gómez,

López,

Eguiarte

et al. 2023

36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 20

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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.

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Section: Introductionmentioning

confidence: 99%