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Multi-step Time Series Forecasting of Electric Load Using Machine Learning Models

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Artificial Intelligence and Soft Computing (ICAISC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10841))

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Abstract

Multi-step forecasting is very challenging and there are a lack of studies available that consist of machine learning algorithms and methodologies for multi-step forecasting. It has also been found that lack of collaborations between these different fields is creating a barrier to further developments. In this paper, multi-step time series forecasting are performed on three nonlinear electric load datasets extracted from Open-Power-System-Data.org using two machine learning models. Multi-step forecasting performance of Auto-Regressive Integrated Moving Average (ARIMA) and Long-Short-Term-Memory (LSTM) based Recurrent Neural Networks (RNN) models are compared. Comparative analysis of forecasting performance of the two models reveals that the LSTM model has superior performance in comparison to the ARIMA model for multi-step electric load forecasting.

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Author information

Authors and Affiliations

  1. School of Engineering, University of Portsmouth, Anglesea Building, Anglesea Road, Portsmouth, PO1 3DJ, UK

    Shamsul Masum, Ying Liu & John Chiverton

Authors
  1. Shamsul Masum
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  2. Ying Liu
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  3. John Chiverton
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Corresponding author

Correspondence to Shamsul Masum .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Masum, S., Liu, Y., Chiverton, J. (2018). Multi-step Time Series Forecasting of Electric Load Using Machine Learning Models. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Computer Science(), vol 10841. Springer, Cham. https://doi.org/10.1007/978-3-319-91253-0_15

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  • DOI: https://doi.org/10.1007/978-3-319-91253-0_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91252-3

  • Online ISBN: 978-3-319-91253-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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