WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil
Offshore wind power generation is expanding in several regions of the globe but in Brazil, particularly in its southern portion, prospection studies are still scarce. Thus, the present study aims to assess wind variability and power density (PD) simulated by the Weather Research and Forecasting Mode...
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creator | Tuchtenhagen, Patrícia Carvalho, Gilvani Gomes de Martins, Guilherme Silva, Pollyanne Evangelista da Oliveira, Cristiano Prestrelo de de Melo Barbosa Andrade, Lara Araújo, João Medeiros de Mutti, Pedro Rodrigues Lucio, Paulo Sérgio Silva, Cláudio Moisés Santos e |
description | Offshore wind power generation is expanding in several regions of the globe but in Brazil, particularly in its southern portion, prospection studies are still scarce. Thus, the present study aims to assess wind variability and power density (PD) simulated by the Weather Research and Forecasting Model (WRF) in the Southern Brazil, focusing on the offshore region. We compared the results of the simulations with data from the Blended Sea Winds (BSW) product, who quantify wind velocity over oceans. The numerical experiment was carried out during a 5-year period, between 00UTC of January 01, 2006 until 00UTC of December 31, 2010. The domain has a total of 340 grid points in the zonal direction, 180 points in the meridional direction and 35 vertical layers with the top set at 50 hPa. We concluded that the WRF model can be used as a tool to evaluate the potential for wind power generation in the Southern Brazil region. On the other hand, the model did not perform well in simulating wind in the regions near the Brazil and Falklands Currents. This shortcoming may be corrected by coupling the WRF with an oceanic model and using parameterizations which more adequately represent turbulence in the planetary boundary layer.
•The WRF model reproduces the position and intensity variability of the SASH.•Wind speed simulated was equivalent to observed values in 98% of cases.•The PD simulated was equivalent to observation in 90% of cases.•The WRF can be used for evaluation of wind power in the Southern Brazil. |
doi_str_mv | 10.1016/j.energy.2019.116341 |
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•The WRF model reproduces the position and intensity variability of the SASH.•Wind speed simulated was equivalent to observed values in 98% of cases.•The PD simulated was equivalent to observation in 90% of cases.•The WRF can be used for evaluation of wind power in the Southern Brazil.</description><identifier>ISSN: 0360-5442</identifier><identifier>EISSN: 1873-6785</identifier><identifier>DOI: 10.1016/j.energy.2019.116341</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Blended Sea Winds ; Boundary layers ; Computer simulation ; Electric power generation ; Environment and Society ; Environmental Engineering ; Environmental Sciences ; Global Changes ; Oceans ; Offshore energy sources ; Offshore operations ; Planetary boundary layer ; Renewable energy ; South Atlantic subtropical high ; Turbulence ; Weather forecasting ; Wind energy ; Wind power ; Wind power generation ; Wind speed</subject><ispartof>Energy (Oxford), 2020-01, Vol.190, p.116341, Article 116341</ispartof><rights>2019</rights><rights>Copyright Elsevier BV Jan 1, 2020</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-be3c0ccc5b8857c71999f572dd3da1a995e1b6764dc7829f88ac3ffbfa930e2a3</citedby><cites>FETCH-LOGICAL-c368t-be3c0ccc5b8857c71999f572dd3da1a995e1b6764dc7829f88ac3ffbfa930e2a3</cites><orcidid>0000-0003-2871-1595 ; 0000-0001-7607-1727</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0360544219320365$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://hal.science/hal-02400348$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Tuchtenhagen, Patrícia</creatorcontrib><creatorcontrib>Carvalho, Gilvani Gomes de</creatorcontrib><creatorcontrib>Martins, Guilherme</creatorcontrib><creatorcontrib>Silva, Pollyanne Evangelista da</creatorcontrib><creatorcontrib>Oliveira, Cristiano Prestrelo de</creatorcontrib><creatorcontrib>de Melo Barbosa Andrade, Lara</creatorcontrib><creatorcontrib>Araújo, João Medeiros de</creatorcontrib><creatorcontrib>Mutti, Pedro Rodrigues</creatorcontrib><creatorcontrib>Lucio, Paulo Sérgio</creatorcontrib><creatorcontrib>Silva, Cláudio Moisés Santos e</creatorcontrib><title>WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil</title><title>Energy (Oxford)</title><description>Offshore wind power generation is expanding in several regions of the globe but in Brazil, particularly in its southern portion, prospection studies are still scarce. Thus, the present study aims to assess wind variability and power density (PD) simulated by the Weather Research and Forecasting Model (WRF) in the Southern Brazil, focusing on the offshore region. We compared the results of the simulations with data from the Blended Sea Winds (BSW) product, who quantify wind velocity over oceans. The numerical experiment was carried out during a 5-year period, between 00UTC of January 01, 2006 until 00UTC of December 31, 2010. The domain has a total of 340 grid points in the zonal direction, 180 points in the meridional direction and 35 vertical layers with the top set at 50 hPa. We concluded that the WRF model can be used as a tool to evaluate the potential for wind power generation in the Southern Brazil region. On the other hand, the model did not perform well in simulating wind in the regions near the Brazil and Falklands Currents. This shortcoming may be corrected by coupling the WRF with an oceanic model and using parameterizations which more adequately represent turbulence in the planetary boundary layer.
•The WRF model reproduces the position and intensity variability of the SASH.•Wind speed simulated was equivalent to observed values in 98% of cases.•The PD simulated was equivalent to observation in 90% of cases.•The WRF can be used for evaluation of wind power in the Southern Brazil.</description><subject>Blended Sea Winds</subject><subject>Boundary layers</subject><subject>Computer simulation</subject><subject>Electric power generation</subject><subject>Environment and Society</subject><subject>Environmental Engineering</subject><subject>Environmental Sciences</subject><subject>Global Changes</subject><subject>Oceans</subject><subject>Offshore energy sources</subject><subject>Offshore operations</subject><subject>Planetary boundary layer</subject><subject>Renewable energy</subject><subject>South Atlantic subtropical high</subject><subject>Turbulence</subject><subject>Weather forecasting</subject><subject>Wind energy</subject><subject>Wind power</subject><subject>Wind power generation</subject><subject>Wind speed</subject><issn>0360-5442</issn><issn>1873-6785</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kEtrWzEQhUVoIG7Sf5CFoKsurqvHfUibgmviOmAolIQuhSyNEplryZXkBPfXV-aGLgMDhxm-OcwchG4pmVNC-6-7OQRIT6c5I1TOKe15Sy_QjIqBN_0gug9oRnhPmq5t2RX6mPOOENIJKWfI_v61wvtoYcQ6Z8h5D6FgFxN-9cFiHwqE7MsJ69od4iskbN8m2e-Poy4-horh8gw4x2OVFLCJOhccHf6e9F8_3qBLp8cMn970Gj2u7h6W62bz88f9crFpDO9FabbADTHGdFshusEMVErpuoFZy62mWsoO6LYf-taaQTDphNCGO7d1WnICTPNr9GXyfdajOiS_1-mkovZqvdio84ywlhDeihda2c8Te0jxzxFyUbt4TKGepxhvh56xWpVqJ8qkmHMC99-WEnXOXu3UlL06Z6-m7Ovat2kN6rcvHpLKxkMwYH0CU5SN_n2Df-HSj6g</recordid><startdate>20200101</startdate><enddate>20200101</enddate><creator>Tuchtenhagen, Patrícia</creator><creator>Carvalho, Gilvani Gomes de</creator><creator>Martins, Guilherme</creator><creator>Silva, Pollyanne Evangelista da</creator><creator>Oliveira, Cristiano Prestrelo de</creator><creator>de Melo Barbosa Andrade, Lara</creator><creator>Araújo, João Medeiros de</creator><creator>Mutti, Pedro Rodrigues</creator><creator>Lucio, Paulo Sérgio</creator><creator>Silva, Cláudio Moisés Santos e</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><general>Elsevier</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7ST</scope><scope>7TB</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope><scope>SOI</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0003-2871-1595</orcidid><orcidid>https://orcid.org/0000-0001-7607-1727</orcidid></search><sort><creationdate>20200101</creationdate><title>WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil</title><author>Tuchtenhagen, Patrícia ; Carvalho, Gilvani Gomes de ; Martins, Guilherme ; Silva, Pollyanne Evangelista da ; Oliveira, Cristiano Prestrelo de ; de Melo Barbosa Andrade, Lara ; Araújo, João Medeiros de ; Mutti, Pedro Rodrigues ; Lucio, Paulo Sérgio ; Silva, Cláudio Moisés Santos e</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-be3c0ccc5b8857c71999f572dd3da1a995e1b6764dc7829f88ac3ffbfa930e2a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Blended Sea Winds</topic><topic>Boundary layers</topic><topic>Computer simulation</topic><topic>Electric power generation</topic><topic>Environment and Society</topic><topic>Environmental Engineering</topic><topic>Environmental Sciences</topic><topic>Global Changes</topic><topic>Oceans</topic><topic>Offshore energy sources</topic><topic>Offshore operations</topic><topic>Planetary boundary layer</topic><topic>Renewable energy</topic><topic>South Atlantic subtropical high</topic><topic>Turbulence</topic><topic>Weather forecasting</topic><topic>Wind energy</topic><topic>Wind power</topic><topic>Wind power generation</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tuchtenhagen, Patrícia</creatorcontrib><creatorcontrib>Carvalho, Gilvani Gomes de</creatorcontrib><creatorcontrib>Martins, Guilherme</creatorcontrib><creatorcontrib>Silva, Pollyanne Evangelista da</creatorcontrib><creatorcontrib>Oliveira, Cristiano Prestrelo de</creatorcontrib><creatorcontrib>de Melo Barbosa Andrade, Lara</creatorcontrib><creatorcontrib>Araújo, João Medeiros de</creatorcontrib><creatorcontrib>Mutti, Pedro Rodrigues</creatorcontrib><creatorcontrib>Lucio, Paulo Sérgio</creatorcontrib><creatorcontrib>Silva, Cláudio Moisés Santos e</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Environment Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Energy (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tuchtenhagen, Patrícia</au><au>Carvalho, Gilvani Gomes de</au><au>Martins, Guilherme</au><au>Silva, Pollyanne Evangelista da</au><au>Oliveira, Cristiano Prestrelo de</au><au>de Melo Barbosa Andrade, Lara</au><au>Araújo, João Medeiros de</au><au>Mutti, Pedro Rodrigues</au><au>Lucio, Paulo Sérgio</au><au>Silva, Cláudio Moisés Santos e</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil</atitle><jtitle>Energy (Oxford)</jtitle><date>2020-01-01</date><risdate>2020</risdate><volume>190</volume><spage>116341</spage><pages>116341-</pages><artnum>116341</artnum><issn>0360-5442</issn><eissn>1873-6785</eissn><abstract>Offshore wind power generation is expanding in several regions of the globe but in Brazil, particularly in its southern portion, prospection studies are still scarce. Thus, the present study aims to assess wind variability and power density (PD) simulated by the Weather Research and Forecasting Model (WRF) in the Southern Brazil, focusing on the offshore region. We compared the results of the simulations with data from the Blended Sea Winds (BSW) product, who quantify wind velocity over oceans. The numerical experiment was carried out during a 5-year period, between 00UTC of January 01, 2006 until 00UTC of December 31, 2010. The domain has a total of 340 grid points in the zonal direction, 180 points in the meridional direction and 35 vertical layers with the top set at 50 hPa. We concluded that the WRF model can be used as a tool to evaluate the potential for wind power generation in the Southern Brazil region. On the other hand, the model did not perform well in simulating wind in the regions near the Brazil and Falklands Currents. This shortcoming may be corrected by coupling the WRF with an oceanic model and using parameterizations which more adequately represent turbulence in the planetary boundary layer.
•The WRF model reproduces the position and intensity variability of the SASH.•Wind speed simulated was equivalent to observed values in 98% of cases.•The PD simulated was equivalent to observation in 90% of cases.•The WRF can be used for evaluation of wind power in the Southern Brazil.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.energy.2019.116341</doi><orcidid>https://orcid.org/0000-0003-2871-1595</orcidid><orcidid>https://orcid.org/0000-0001-7607-1727</orcidid></addata></record> |
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subjects | Blended Sea Winds Boundary layers Computer simulation Electric power generation Environment and Society Environmental Engineering Environmental Sciences Global Changes Oceans Offshore energy sources Offshore operations Planetary boundary layer Renewable energy South Atlantic subtropical high Turbulence Weather forecasting Wind energy Wind power Wind power generation Wind speed |
title | WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil |
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