Some improvements of wind speed Markov chain modeling

Jie Tang; Alexandre Brouste; Kwok Leung Tsui

doi:10.1016/j.renene.2015.03.005

Some improvements of wind speed Markov chain modeling

Jie Tang^*
, Alexandre Brouste
, Kwok Leung Tsui

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

63 Citations (Scopus)

Abstract

In this study, the traditional Markov chain method for wind speed modeling is analyzed and two improvements are introduced. New states categorization step and wind speeds simulation step are presented. They both take advantage of the empirical cumulative distribution function of the wind speed time series. Performances of the new method are tested in terms of modeling and short-term forecasting. The results suggest that this method overperforms the traditional one for modeling.

Original language	English
Pages (from-to)	52-56
Journal	Renewable Energy
Volume	81
Online published	26 Mar 2015
DOIs	https://doi.org/10.1016/j.renene.2015.03.005
Publication status	Published - Sept 2015

Research Keywords

Forecasting model
Markov chains modeling method
Wind speed

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RGC-funded

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10.1016/j.renene.2015.03.005

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@article{6e0f113dc2564f56bb34c4afe16007a4,

title = "Some improvements of wind speed Markov chain modeling",

abstract = "In this study, the traditional Markov chain method for wind speed modeling is analyzed and two improvements are introduced. New states categorization step and wind speeds simulation step are presented. They both take advantage of the empirical cumulative distribution function of the wind speed time series. Performances of the new method are tested in terms of modeling and short-term forecasting. The results suggest that this method overperforms the traditional one for modeling.",

keywords = "Forecasting model, Markov chains modeling method, Wind speed",

author = "Jie Tang and Alexandre Brouste and Tsui, \{Kwok Leung\}",

year = "2015",

month = sep,

doi = "10.1016/j.renene.2015.03.005",

language = "English",

volume = "81",

pages = "52--56",

journal = "Renewable Energy",

issn = "0960-1481",

publisher = "Elsevier Ltd.",

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TY - JOUR

T1 - Some improvements of wind speed Markov chain modeling

AU - Tang, Jie

AU - Brouste, Alexandre

AU - Tsui, Kwok Leung

PY - 2015/9

Y1 - 2015/9

N2 - In this study, the traditional Markov chain method for wind speed modeling is analyzed and two improvements are introduced. New states categorization step and wind speeds simulation step are presented. They both take advantage of the empirical cumulative distribution function of the wind speed time series. Performances of the new method are tested in terms of modeling and short-term forecasting. The results suggest that this method overperforms the traditional one for modeling.

AB - In this study, the traditional Markov chain method for wind speed modeling is analyzed and two improvements are introduced. New states categorization step and wind speeds simulation step are presented. They both take advantage of the empirical cumulative distribution function of the wind speed time series. Performances of the new method are tested in terms of modeling and short-term forecasting. The results suggest that this method overperforms the traditional one for modeling.

KW - Forecasting model

KW - Markov chains modeling method

KW - Wind speed

UR - https://www.scopus.com/pages/publications/84925787141

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84925787141&origin=recordpage

U2 - 10.1016/j.renene.2015.03.005

DO - 10.1016/j.renene.2015.03.005

M3 - RGC 21 - Publication in refereed journal

SN - 0960-1481

VL - 81

SP - 52

EP - 56

JO - Renewable Energy

JF - Renewable Energy

ER -

Some improvements of wind speed Markov chain modeling

Abstract

Research Keywords

RGC Funding Information

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Corrigendum to “Some improvements of wind speed Markov chain modeling” [Renew. Energy 81 (2015) 52–56]

FR/HKJRS: Forecasting Renewable Energy Production

Cite this

Some improvements of wind speed Markov chain modeling

Abstract

Research Keywords

RGC Funding Information

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Research output

Corrigendum to “Some improvements of wind speed Markov chain modeling” [Renew. Energy 81 (2015) 52–56]

Projects

FR/HKJRS: Forecasting Renewable Energy Production

Cite this