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Handling arch effects in wind speed data using state space approach model

In general, Malaysia experiences low wind speed, but some areas in this country experience strong wind in certain periods of time within a year. In line with the necessity to enhance the utilization of indigenous renewable energy resources in order to contribute towards national electricity supply,...

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Main Author: Jamaludin, Aaishah Radziah
Format: Thesis
Language:English
Published: 2017
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/77773/1/AaishahRadziahJamaludinMFS2017.pdf
http://eprints.utm.my/id/eprint/77773/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:105132
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spelling my.utm.777732018-07-04T11:47:46Z http://eprints.utm.my/id/eprint/77773/ Handling arch effects in wind speed data using state space approach model Jamaludin, Aaishah Radziah QA Mathematics In general, Malaysia experiences low wind speed, but some areas in this country experience strong wind in certain periods of time within a year. In line with the necessity to enhance the utilization of indigenous renewable energy resources in order to contribute towards national electricity supply, the study on the potential of the wind speed as a new source of renewable energy is significantly crucial. For that reason, this study aims to model and forecast wind speed data in 10 stations all over Peninsular Malaysia by using three different methods; Autoregressive Moving Average (ARMA), hybrid model (ARMA with Generalized Autoregressive Conditional Heteroscedasticity (ARMA-GARCH)) and Dynamic Linear models (DLM). ARMA was used as the benchmark in identifying an adequate linear model. The Autoregressive Conditional Heteroscedasticity (ARCH) effect in the residuals data from the developed conventional model was determined. The presence of ARCH shows that the model is not appropriate to be treated as a linear model. Therefore, to overcome this problem, ARMA model was hybridized with GARCH model. However, there is still some remaining ARCH exists in the residuals data for several datasets. Thus, a new approach namely DLM was introduced in order to treat the shortcoming. At the end of the research, a comparative study was made. It was discovered that in most cases, DLM outperforms than other models. DLM is found to be flexible in treating the dynamical fluctuation of the data and superior in terms of predictive accuracy with just a small error when compared with other methods 2017-02 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/77773/1/AaishahRadziahJamaludinMFS2017.pdf Jamaludin, Aaishah Radziah (2017) Handling arch effects in wind speed data using state space approach model. Masters thesis, Universiti Teknologi Malaysia, Faculty of Science. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:105132
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Jamaludin, Aaishah Radziah
Handling arch effects in wind speed data using state space approach model
description In general, Malaysia experiences low wind speed, but some areas in this country experience strong wind in certain periods of time within a year. In line with the necessity to enhance the utilization of indigenous renewable energy resources in order to contribute towards national electricity supply, the study on the potential of the wind speed as a new source of renewable energy is significantly crucial. For that reason, this study aims to model and forecast wind speed data in 10 stations all over Peninsular Malaysia by using three different methods; Autoregressive Moving Average (ARMA), hybrid model (ARMA with Generalized Autoregressive Conditional Heteroscedasticity (ARMA-GARCH)) and Dynamic Linear models (DLM). ARMA was used as the benchmark in identifying an adequate linear model. The Autoregressive Conditional Heteroscedasticity (ARCH) effect in the residuals data from the developed conventional model was determined. The presence of ARCH shows that the model is not appropriate to be treated as a linear model. Therefore, to overcome this problem, ARMA model was hybridized with GARCH model. However, there is still some remaining ARCH exists in the residuals data for several datasets. Thus, a new approach namely DLM was introduced in order to treat the shortcoming. At the end of the research, a comparative study was made. It was discovered that in most cases, DLM outperforms than other models. DLM is found to be flexible in treating the dynamical fluctuation of the data and superior in terms of predictive accuracy with just a small error when compared with other methods
format Thesis
author Jamaludin, Aaishah Radziah
author_facet Jamaludin, Aaishah Radziah
author_sort Jamaludin, Aaishah Radziah
title Handling arch effects in wind speed data using state space approach model
title_short Handling arch effects in wind speed data using state space approach model
title_full Handling arch effects in wind speed data using state space approach model
title_fullStr Handling arch effects in wind speed data using state space approach model
title_full_unstemmed Handling arch effects in wind speed data using state space approach model
title_sort handling arch effects in wind speed data using state space approach model
publishDate 2017
url http://eprints.utm.my/id/eprint/77773/1/AaishahRadziahJamaludinMFS2017.pdf
http://eprints.utm.my/id/eprint/77773/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:105132
_version_ 1643657630027087872
score 13.211869

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