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
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spelling	my-utm-ep.777732018-07-04T11:47:46Z Handling arch effects in wind speed data using state space approach model 2017-02 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 http://eprints.utm.my/id/eprint/77773/ http://eprints.utm.my/id/eprint/77773/1/AaishahRadziahJamaludinMFS2017.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:105132 masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
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
qualification_level	Master's degree
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
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2017
url	http://eprints.utm.my/id/eprint/77773/1/AaishahRadziahJamaludinMFS2017.pdf
_version_	1747817827441573888

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

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