A Thermodynamical Model Study for an Energy Saving Algorithm View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009

AUTHORS

Enrique de la Cal , José Ramón Villar , Javier Sedano

ABSTRACT

A local Spanish company that produces electric heaters needs an energy saving device to be integrated with the heaters. It was proven that a hybrid artificial intelligent systems (HAIS) could afford the energy saving reasonably, even though some improvements must be introduced. One of the critical elements in the process of designing an energy saving system is the thermodynamical modeling of the house to be controlled. This work presents a study of different first order techniques, some taken from the literature and other new proposals, for the prediction of the thermal dynamics in a house. Finally it is concluded that a first order prediction system is not a valid prediction model for such an energy saving system. More... »

PAGES

384-390

References to SciGraph publications

  • 2007. Energy Saving by Means of Fuzzy Systems in INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2007
  • 2008. Minimizing Energy Consumption in Heating Systems under Uncertainty in HYBRID ARTIFICIAL INTELLIGENCE SYSTEMS
  • 2007-01. Artificial neural network models for indoor temperature prediction: investigations in two buildings in NEURAL COMPUTING AND APPLICATIONS
  • Book

    TITLE

    Hybrid Artificial Intelligence Systems

    ISBN

    978-3-642-02318-7
    978-3-642-02319-4

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-02319-4_46

    DOI

    http://dx.doi.org/10.1007/978-3-642-02319-4_46

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1004307683


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