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2021 | OriginalPaper | Chapter

Towards Data-Driven Simulation Models for Building Energy Management

Authors : Juan Gómez-Romero, Miguel Molina-Solana

Published in: Computational Science – ICCS 2021

Publisher: Springer International Publishing

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Abstract

The computational simulation of physical phenomena is a highly complex and expensive process. Traditional simulation models, based on equations describing the behavior of the system, do not allow generating data in sufficient quantity and speed to predict its evolution and make decisions accordingly automatically. These features are particularly relevant in building energy simulations. In this work, we introduce the idea of deep data-driven simulation models (D3S), a novel approach in terms of the combination of models. A D3S is capable of emulating the behavior of a system in a similar way to simulators based on physical principles but requiring less effort in its construction—it is learned automatically from historical data—and less time to run—no need to solve complex equations.

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previous chapter Higher-Order Hierarchical Spectral Clustering for Multidimensional Data

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Title: Towards Data-Driven Simulation Models for Building Energy Management
Authors: Juan Gómez-Romero
Miguel Molina-Solana
Publisher: Springer International Publishing
Book: Computational Science – ICCS 2021
Print ISBN: 978-3-030-77976-4

Electronic ISBN: 978-3-030-77977-1

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-77977-1_32

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