LAPSE:2018.0901
Published Article
LAPSE:2018.0901
Improved Spatio-Temporal Linear Models for Very Short-Term Wind Speed Forecasting
November 27, 2018
In this paper, the spatio-temporal (multi-channel) linear models, which use temporal and the neighbouring wind speed measurements around the target location, for the best short-term wind speed forecasting are investigated. Multi-channel autoregressive moving average (MARMA) models are formulated in matrix form and efficient linear prediction coefficient estimation techniques are first used and revised. It is shown in detail how to apply these MARMA models to the spatially distributed wind speed measurements. The proposed MARMA models are tested using real wind speed measurements which are collected from the five stations around Canakkale region of Turkey. According to the test results, considerable improvements are observed over the well known persistence, autoregressive (AR) and multi-channel/vector autoregressive (VAR) models. It is also shown that the model can predict wind speed very fast (in milliseconds) which is suitable for the immediate short-term forecasting.
Record ID
Keywords
autoregressive moving average model, forecasting, multi-channel, prediction, spatio-temporal, very short-term, wind energy, wind speed
Subject
Suggested Citation
Filik T. Improved Spatio-Temporal Linear Models for Very Short-Term Wind Speed Forecasting. (2018). LAPSE:2018.0901
Author Affiliations
Journal Name
Energies
Volume
9
Issue
3
Article Number
E168
Year
2016
Publication Date
2016-03-07
Published Version
ISSN
1996-1073
Version Comments
Original Submission
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PII: en9030168, Publication Type: Journal Article
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Published Article
LAPSE:2018.0901
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doi:10.3390/en9030168
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Version History
[v1] (Original Submission)
Nov 27, 2018
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Nov 27, 2018
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https://psecommunity.org/LAPSE:2018.0901
Original Submitter
Calvin Tsay
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