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A new hybrid model to foretell thermal power efficiency from energy performance certificates at residential dwellings applying a Gaussian process regression

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Abstract

An energy performance certificate (EPC) provides information on the energy performance of an energy system. The objective of this research aimed at obtaining a predictive model for early detection of thermal power efficiency (TPE) for energy conversion and preservation in buildings. This article expounds a sound and solid nonparametric Bayesian technique known as Gaussian process regression (GPR) approach, based on a set of data collected from different dwellings in an oceanic climate. Firstly, this model introduces the relevance of each predictive variable on energy performance in residential buildings. The second result refers to the statement that we can predict successfully the TPE by using this model. A coefficient of determination equal to 0.9687 was thus established in order to predict the TPE from the observed data, using the GPR approach in combination with the differential evolution (DE) optimiser. The concordance between experimental observed data and the predicted data from the best-proposed novel hybrid DE/GPR-relied model demonstrated here the adequate efficiency of this innovative approach.

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Acknowledgements

The authors gratefully acknowledge the computational help supplied by the Department of Mathematics at University of Oviedo and financial help of the Research Projects PGC2018-098459-B-I00 and FC-GRUPIN-IDI/2018/000221, both partial funding from European Regional Development Fund (ERDF). In this sense, the authors acknowledge the collaboration based on the Research Project FUO-118-19. Likewise, it is mandatory to thank Anthony Ashworth their revision of English grammar and spelling of this article.

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Authors and Affiliations

  1. Department of Mathematics, Faculty of Sciences, University of Oviedo, 33007, Oviedo, Spain

    Paulino José García-Nieto & Esperanza García-Gonzalo

  2. Department of Energy, College of Mining, Energy and Materials Engineering, University of Oviedo, 33004, Oviedo, Spain

    José Pablo Paredes-Sánchez

  3. Department of Mining Technology, Topography and Structures, University of León, 24071, León, Spain

    Antonio Bernardo Sánchez

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  1. Paulino José García-Nieto
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  2. Esperanza García-Gonzalo
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  3. José Pablo Paredes-Sánchez
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  4. Antonio Bernardo Sánchez
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Correspondence to Paulino José García-Nieto.

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García-Nieto, P.J., García-Gonzalo, E., Paredes-Sánchez, J.P. et al. A new hybrid model to foretell thermal power efficiency from energy performance certificates at residential dwellings applying a Gaussian process regression. Neural Comput & Applic 33, 6627–6640 (2021). https://doi.org/10.1007/s00521-020-05427-z

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