Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia

Temporal distribution of forecasted wind speed is important to assess wind capacity for wind-related technology purposes. Regional wind energy estimation needs the development of wind pattern to monitor and forecast temporal wind behaviour. Temporal wind in Malaysia mainly depends on monsoonal facto...

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Bibliographic Details
Published in:Pertanika Journal of Science and Technology
Main Author: Deros S.N.M.; Asmat A.; Mansor S.
Format: Article
Language:English
Published: Universiti Putra Malaysia Press 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049148389&partnerID=40&md5=4e09216d166efd484da1607472a89918
id 2-s2.0-85049148389
spelling 2-s2.0-85049148389
Deros S.N.M.; Asmat A.; Mansor S.
Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia
2017
Pertanika Journal of Science and Technology
25
S4

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049148389&partnerID=40&md5=4e09216d166efd484da1607472a89918
Temporal distribution of forecasted wind speed is important to assess wind capacity for wind-related technology purposes. Regional wind energy estimation needs the development of wind pattern to monitor and forecast temporal wind behaviour. Temporal wind in Malaysia mainly depends on monsoonal factor that circulates yearly and each monsoon derives distinct character of wind. This paper aims to develop a model of wind speed pattern from historical wind speed data. Then, the model was used to forecast 5-years seasonal wind speed and identify temporal distribution. Wind speed model development and forecast was performed by identifying the best combination of wind speed seasonal component using Seasonal Auto-regressive and Moving Average (SARIMA) model. Thus, three distribution models, Lognormal, Weibull and Gamma models, were exploited to further observe consistency using Kolmogorov-Smirnov goodness-of-fit test. The best fit model to represent seasonal wind distribution in each monsoon season at Pulau Langkawi, Malaysia, is Log-normal distribution (0.04679-0.108). © 2017 Universiti Putra Malaysia Press.
Universiti Putra Malaysia Press
1287680
English
Article

author Deros S.N.M.; Asmat A.; Mansor S.
spellingShingle Deros S.N.M.; Asmat A.; Mansor S.
Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia
author_facet Deros S.N.M.; Asmat A.; Mansor S.
author_sort Deros S.N.M.; Asmat A.; Mansor S.
title Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia
title_short Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia
title_full Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia
title_fullStr Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia
title_full_unstemmed Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia
title_sort Seasonal temporal distribution of forecasted wind speed data in Langkawi, Malaysia
publishDate 2017
container_title Pertanika Journal of Science and Technology
container_volume 25
container_issue S4
doi_str_mv
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049148389&partnerID=40&md5=4e09216d166efd484da1607472a89918
description Temporal distribution of forecasted wind speed is important to assess wind capacity for wind-related technology purposes. Regional wind energy estimation needs the development of wind pattern to monitor and forecast temporal wind behaviour. Temporal wind in Malaysia mainly depends on monsoonal factor that circulates yearly and each monsoon derives distinct character of wind. This paper aims to develop a model of wind speed pattern from historical wind speed data. Then, the model was used to forecast 5-years seasonal wind speed and identify temporal distribution. Wind speed model development and forecast was performed by identifying the best combination of wind speed seasonal component using Seasonal Auto-regressive and Moving Average (SARIMA) model. Thus, three distribution models, Lognormal, Weibull and Gamma models, were exploited to further observe consistency using Kolmogorov-Smirnov goodness-of-fit test. The best fit model to represent seasonal wind distribution in each monsoon season at Pulau Langkawi, Malaysia, is Log-normal distribution (0.04679-0.108). © 2017 Universiti Putra Malaysia Press.
publisher Universiti Putra Malaysia Press
issn 1287680
language English
format Article
accesstype
record_format scopus
collection Scopus
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