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...
Published in: | Pertanika Journal of Science and Technology |
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Language: | English |
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Universiti Putra Malaysia Press
2017
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Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049148389&partnerID=40&md5=4e09216d166efd484da1607472a89918 |
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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 |
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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 |
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record_format |
scopus |
collection |
Scopus |
_version_ |
1809677908356104192 |