Non-stationary statistical modelling of wind speed: A case study in eastern Canada.
The assessment of wind energy potential is generally based on the analysis of the statistical distribution of observed wind speed of short time resolution. Record periods of observational data used in practice at sites of interest are often very short, often ranging from a few months to a few years....
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Online Access: | https://espace.inrs.ca/id/eprint/11854/ https://espace.inrs.ca/id/eprint/11854/1/P3915.pdf https://doi.org/10.1016/j.enconman.2021.114028 |
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ftinrsquebec:oai:espace.inrs.ca:11854 2023-05-15T17:36:02+02:00 Non-stationary statistical modelling of wind speed: A case study in eastern Canada. Ouarda, Taha B. M. J. Charron, Christian 2021 application/pdf https://espace.inrs.ca/id/eprint/11854/ https://espace.inrs.ca/id/eprint/11854/1/P3915.pdf https://doi.org/10.1016/j.enconman.2021.114028 en eng https://espace.inrs.ca/id/eprint/11854/1/P3915.pdf Ouarda, Taha B. M. J. orcid:0000-0002-0969-063X et Charron, Christian (2021). Non-stationary statistical modelling of wind speed: A case study in eastern Canada. Energy Conversion and Management , vol. 236 . p. 114028. DOI:10.1016/j.enconman.2021.114028 <https://doi.org/10.1016/j.enconman.2021.114028>. doi:10.1016/j.enconman.2021.114028 wind speed wind energy non-stationary model robability density function climate oscillation indices climate variability Article Évalué par les pairs 2021 ftinrsquebec https://doi.org/10.1016/j.enconman.2021.114028 2023-03-26T00:12:22Z The assessment of wind energy potential is generally based on the analysis of the statistical distribution of observed wind speed of short time resolution. Record periods of observational data used in practice at sites of interest are often very short, often ranging from a few months to a few years. Predictions based on such small record periods are likely to be biased as it is recognized that wind speed is subject to important interannual variability and long-term trends. Large-scale atmospheric circulation patterns have an important influence on wind speed. Their predictable nature can make them useful for the prediction of wind speed during the lifetime of wind farm projects. This feature is not exploited in practice. It is proposed in this study to introduce predictors of the wind speed in non-stationary statistical models. This approach allows the development of predictions of the wind speed distribution conditionally on the state of the predictors. The predictors used here are indices of atmospheric circulation to account for the interannual variability and a temporal index to account for the long-term temporal trend. The proposed approach was applied to hourly wind speed data at selected meteorological stations in the province of Québec (Canada). 20 stations with long record periods of over 30 years of data were used. The most important circulation indices identified in the study area are the North-Atlantic Oscillation (NAO) during the winter season and the Pacific North American (PNA) during the spring season. Results indicate that the annual goodness-of-fit at the stations of the case study improved on average when the non-stationary model is used compared to the stationary model. The proposed approach can potentially be used to model wind speed during the projected lifetime of wind farms using forecasts of the predictors. Article in Journal/Newspaper North Atlantic North Atlantic oscillation Institut national de la recherche scientifique, Québec: Espace INRS Canada Pacific Energy Conversion and Management 236 114028 |
institution |
Open Polar |
collection |
Institut national de la recherche scientifique, Québec: Espace INRS |
op_collection_id |
ftinrsquebec |
language |
English |
topic |
wind speed wind energy non-stationary model robability density function climate oscillation indices climate variability |
spellingShingle |
wind speed wind energy non-stationary model robability density function climate oscillation indices climate variability Ouarda, Taha B. M. J. Charron, Christian Non-stationary statistical modelling of wind speed: A case study in eastern Canada. |
topic_facet |
wind speed wind energy non-stationary model robability density function climate oscillation indices climate variability |
description |
The assessment of wind energy potential is generally based on the analysis of the statistical distribution of observed wind speed of short time resolution. Record periods of observational data used in practice at sites of interest are often very short, often ranging from a few months to a few years. Predictions based on such small record periods are likely to be biased as it is recognized that wind speed is subject to important interannual variability and long-term trends. Large-scale atmospheric circulation patterns have an important influence on wind speed. Their predictable nature can make them useful for the prediction of wind speed during the lifetime of wind farm projects. This feature is not exploited in practice. It is proposed in this study to introduce predictors of the wind speed in non-stationary statistical models. This approach allows the development of predictions of the wind speed distribution conditionally on the state of the predictors. The predictors used here are indices of atmospheric circulation to account for the interannual variability and a temporal index to account for the long-term temporal trend. The proposed approach was applied to hourly wind speed data at selected meteorological stations in the province of Québec (Canada). 20 stations with long record periods of over 30 years of data were used. The most important circulation indices identified in the study area are the North-Atlantic Oscillation (NAO) during the winter season and the Pacific North American (PNA) during the spring season. Results indicate that the annual goodness-of-fit at the stations of the case study improved on average when the non-stationary model is used compared to the stationary model. The proposed approach can potentially be used to model wind speed during the projected lifetime of wind farms using forecasts of the predictors. |
format |
Article in Journal/Newspaper |
author |
Ouarda, Taha B. M. J. Charron, Christian |
author_facet |
Ouarda, Taha B. M. J. Charron, Christian |
author_sort |
Ouarda, Taha B. M. J. |
title |
Non-stationary statistical modelling of wind speed: A case study in eastern Canada. |
title_short |
Non-stationary statistical modelling of wind speed: A case study in eastern Canada. |
title_full |
Non-stationary statistical modelling of wind speed: A case study in eastern Canada. |
title_fullStr |
Non-stationary statistical modelling of wind speed: A case study in eastern Canada. |
title_full_unstemmed |
Non-stationary statistical modelling of wind speed: A case study in eastern Canada. |
title_sort |
non-stationary statistical modelling of wind speed: a case study in eastern canada. |
publishDate |
2021 |
url |
https://espace.inrs.ca/id/eprint/11854/ https://espace.inrs.ca/id/eprint/11854/1/P3915.pdf https://doi.org/10.1016/j.enconman.2021.114028 |
geographic |
Canada Pacific |
geographic_facet |
Canada Pacific |
genre |
North Atlantic North Atlantic oscillation |
genre_facet |
North Atlantic North Atlantic oscillation |
op_relation |
https://espace.inrs.ca/id/eprint/11854/1/P3915.pdf Ouarda, Taha B. M. J. orcid:0000-0002-0969-063X et Charron, Christian (2021). Non-stationary statistical modelling of wind speed: A case study in eastern Canada. Energy Conversion and Management , vol. 236 . p. 114028. DOI:10.1016/j.enconman.2021.114028 <https://doi.org/10.1016/j.enconman.2021.114028>. doi:10.1016/j.enconman.2021.114028 |
op_doi |
https://doi.org/10.1016/j.enconman.2021.114028 |
container_title |
Energy Conversion and Management |
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236 |
container_start_page |
114028 |
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1766135371617271808 |