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Energy Management—Collective and Computational Intelligence with Theory and Applications pp 65–81Cite as

Fuzzy Forecasting Methods for Energy Planning

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Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 149))

Abstract

For energy planning, forecasting the energy demand for a specific time interval and supply of a specific source is very crucial. In the energy sector, forecasting may be long term, midterm or short term. While traditional forecasting techniques provide results for crisp data, for data with imprecision or vagueness fuzzy based approaches can be used. In this chapter, fuzzy forecasting methods such as, fuzzy time series (FTS), fuzzy regression, adaptive network-based fuzzy inference system (ANFIS) and fuzzy inference systems (FIS) as explained. Later, an extended literature review of fuzzy forecasting in energy planning is provided. Finally, a numerical application is given to give a better understanding of fuzzy forecasting approaches.

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Acknowledgements

As a specialist in Information Technologies Department, Eda Bolturk thanks İstanbul Takas ve Saklama Bankası A.S. for getting support for this study.

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Authors and Affiliations

  1. Istanbul Technical University, Macka, Istanbul, Turkey

    Basar Oztaysi, Sezi Çevik Onar & Cengiz Kahraman

  2. Istanbul Takas ve Saklama Bankası A.S, Istanbul, Turkey

    Eda Bolturk

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  1. Basar Oztaysi
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  2. Sezi Çevik Onar
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  3. Eda Bolturk
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  4. Cengiz Kahraman
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Correspondence to Cengiz Kahraman .

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Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Energy Institute, Istanbul Technical University, Istanbul, Turkey

    Gülgün Kayakutlu

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Oztaysi, B., Çevik Onar, S., Bolturk, E., Kahraman, C. (2018). Fuzzy Forecasting Methods for Energy Planning. In: Kahraman, C., Kayakutlu, G. (eds) Energy Management—Collective and Computational Intelligence with Theory and Applications. Studies in Systems, Decision and Control, vol 149. Springer, Cham. https://doi.org/10.1007/978-3-319-75690-5_4

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  • DOI: https://doi.org/10.1007/978-3-319-75690-5_4

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  • Print ISBN: 978-3-319-75689-9

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