Improved load forecasting model based on two-stage optimization of gray model with fractional order accumulation and Markov chain
Fuxiang Liu,
Wenzhang Guo,
Ran Liu and
Jun Liu
Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 11, 2659-2673
Abstract:
Accurate prediction of load is very important in the management of power system. This paper proposed a two-stage optimization method of gray-Markov model with fractional order accumulation for short-term load forecasting. Firstly, the gray model GMpq(1,1) with the optimal fractional order accumulation is investigated. Secondly, the Markov chain model with optimal state numbers is used to deal with residual error series to improve prediction accuracy. Thirdly, the results of case study show that the proposed gray-Markov model with fractional order accumulation and two-stage optimization method can perform more intelligent and further improve prediction accuracy in the short-term load forecasting relative to some other methods.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2019.1674873 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:50:y:2021:i:11:p:2659-2673
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2019.1674873
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().