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Short Term Load Forecasting for Residential Buildings—An Extensive Literature Review

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Book cover Intelligent Decision Technologies (IDT 2017)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 39))

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Abstract

Accurate Short Term Load Forecasting is an essential step towards load balancing methods in energy systems. With the recent introduction of Smart Meters for residential buildings, load forecasting and shifting methods can be implemented for individual households. The high variance of the load demand on the household level requires specific forecasting methods. This paper provides an overview of the methods which have been applied and points out what results are comparable. Therefore a structured literature review is carried out. In the process, 375 papers are analyzed and categorized via a concept matrix. Based on this review it is pointed out, which methods achieve good results for which purpose and which publicly available datasets can be used for evaluation.

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Notes

  1. 1.

    In Germany the installation of smart meters in new buildings has been forced since 2010 by law, cf. 21b Abs. 3a EnWG.

  2. 2.

    http://ieeexplore.ieee.org/.

  3. 3.

    https://scholar.google.de/.

  4. 4.

    The search has been performed on Google Scholar between \(27^{th}\) and \(29^{th} December \,2014\) and on IEEE xplore between \(7^{th}\) and \(10^{th} January \, 2015\).

  5. 5.

    http://www.ucd.ie/issda/data/commissionforenergyregulationcer/.

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Authors and Affiliations

  1. Institute for Information Systems, University Hildesheim, Universit ätsplatz 1, 31141, Hildesheim, Germany

    Carola Gerwig

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  1. Carola Gerwig
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Correspondence to Carola Gerwig .

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Editors and Affiliations

  1. FCT, Universidade Nova de Lisboa, Caparica, Portugal

    Rui Neves-Silva

  2. Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia

    Lakhmi C. Jain

  3. KES International, Shoreham-by-sea, United Kingdom

    Robert J. Howlett

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Gerwig, C. (2015). Short Term Load Forecasting for Residential Buildings—An Extensive Literature Review. In: Neves-Silva, R., Jain, L., Howlett, R. (eds) Intelligent Decision Technologies. IDT 2017. Smart Innovation, Systems and Technologies, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-319-19857-6_17

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  • DOI: https://doi.org/10.1007/978-3-319-19857-6_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19856-9

  • Online ISBN: 978-3-319-19857-6

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