Fuzzy forecasting methods for energy planning

Basar Oztaysi, Sezi Çevik Onar, Eda Bolturk, Cengiz Kahraman*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationStudies in Systems, Decision and Control
PublisherSpringer International Publishing
Pages65-81
Number of pages17
DOIs
Publication statusPublished - 2018

Publication series

NameStudies in Systems, Decision and Control
Volume149
ISSN (Print)2198-4182
ISSN (Electronic)2198-4190

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.

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