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Comparison of three probability distributions and techno-economic analysis of wind energy production along the coastal belt of Pakistan
Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application...
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Published in: | Energy exploration & exploitation 2021-11, Vol.39 (6), p.2191-2213 |
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description | Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application of three probability distributions, i.e. Weibull, Rayleigh, and lognormal for wind resource estimation at six sites along the coastal belt of Pakistan. Four years’ (2015–2018) wind data measured each 60-minutes at 50m height for six locations were collected from Pakistan Meteorological Department. Comparison of these distributions was done based on coefficient of determination (R²), root mean square error, and mean absolute percentage deviation. Comparison showed that Weibull distribution is the most accurate followed by lognormal and Rayleigh, respectively. Wind power density (PD
) was evaluated and it was found that Karachi has the highest wind speed and PD
as 5.82 m/s and 162.69 W/m², respectively, while Jiwani has the lowest wind speed and PD
as 4.62 m/s and 76.76 W/m², respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out. |
doi_str_mv | 10.1177/0144598720931587 |
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) was evaluated and it was found that Karachi has the highest wind speed and PD
as 5.82 m/s and 162.69 W/m², respectively, while Jiwani has the lowest wind speed and PD
as 4.62 m/s and 76.76 W/m², respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out.</description><identifier>ISSN: 0144-5987</identifier><identifier>EISSN: 2048-4054</identifier><identifier>DOI: 10.1177/0144598720931587</identifier><language>eng</language><publisher>London, England: Sage Publications, Inc</publisher><subject>Research Article</subject><ispartof>Energy exploration & exploitation, 2021-11, Vol.39 (6), p.2191-2213</ispartof><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c411t-4610333ef6a539c2f43d7569ff53e0d90777f04b9b0467a6d087ee094e9823243</citedby><cites>FETCH-LOGICAL-c411t-4610333ef6a539c2f43d7569ff53e0d90777f04b9b0467a6d087ee094e9823243</cites><orcidid>0000-0001-9026-1092</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0144598720931587$$EPDF$$P50$$Gsage$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0144598720931587$$EHTML$$P50$$Gsage$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,21945,27830,27901,27902,44921,45309</link.rule.ids></links><search><creatorcontrib>Sumair, Muhammad</creatorcontrib><creatorcontrib>Aized, Tauseef</creatorcontrib><creatorcontrib>Gardezi, Syed Asad Raza</creatorcontrib><creatorcontrib>Bhutta, Muhammad Mahmood Aslam</creatorcontrib><creatorcontrib>Rehman, Syed Muhammad Sohail</creatorcontrib><creatorcontrib>Rehman, Syed Ubaid ur</creatorcontrib><title>Comparison of three probability distributions and techno-economic analysis of wind energy production along the coastal belt of Pakistan</title><title>Energy exploration & exploitation</title><description>Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application of three probability distributions, i.e. Weibull, Rayleigh, and lognormal for wind resource estimation at six sites along the coastal belt of Pakistan. Four years’ (2015–2018) wind data measured each 60-minutes at 50m height for six locations were collected from Pakistan Meteorological Department. Comparison of these distributions was done based on coefficient of determination (R²), root mean square error, and mean absolute percentage deviation. Comparison showed that Weibull distribution is the most accurate followed by lognormal and Rayleigh, respectively. Wind power density (PD
) was evaluated and it was found that Karachi has the highest wind speed and PD
as 5.82 m/s and 162.69 W/m², respectively, while Jiwani has the lowest wind speed and PD
as 4.62 m/s and 76.76 W/m², respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out.</description><subject>Research Article</subject><issn>0144-5987</issn><issn>2048-4054</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>DOA</sourceid><recordid>eNp9kc9u1DAQhy1EJZaWOxckv0Da8Z_Y8RGtoFSqBAc4RxNnvPWSjVe2V2ifgNcmYaseOHAaaeb3fSPNMPZewK0Q1t6B0Lp1nZXglGg7-4ptJOiu0dDq12yzjpt1_oa9LWUPAMopu2G_t-lwxBxLmnkKvD5lIn7MacAhTrGe-RhLzXE41ZjmwnEeeSX_NKeGfJrTIfqlh9O5xLLyv-ISoJny7rxaxpNfOY5TmneLnLhPWCpOfKCprsA3_LkswPmGXQWcCr17rtfsx-dP37dfmsev9w_bj4-N10LURhsBSikKBlvlvAxajbY1LoRWEYwOrLUB9OAG0MaiGaGzROA0uU4qqdU1e7h4x4T7_pjjAfO5Txj7v42Udz3mGv1EvZeEUhiiVqL2PnRhIN2JAMoaab1bXHBx-ZxKyRRefAL69Sn9v09ZkOaCFNxRv0-nvByv_C__4ZLfl5ryi19aYUwnrfoDuJ2X7A</recordid><startdate>20211101</startdate><enddate>20211101</enddate><creator>Sumair, Muhammad</creator><creator>Aized, Tauseef</creator><creator>Gardezi, Syed Asad Raza</creator><creator>Bhutta, Muhammad Mahmood Aslam</creator><creator>Rehman, Syed Muhammad Sohail</creator><creator>Rehman, Syed Ubaid ur</creator><general>Sage Publications, Inc</general><general>SAGE Publications</general><general>SAGE Publishing</general><scope>AFRWT</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-9026-1092</orcidid></search><sort><creationdate>20211101</creationdate><title>Comparison of three probability distributions and techno-economic analysis of wind energy production along the coastal belt of Pakistan</title><author>Sumair, Muhammad ; Aized, Tauseef ; Gardezi, Syed Asad Raza ; Bhutta, Muhammad Mahmood Aslam ; Rehman, Syed Muhammad Sohail ; Rehman, Syed Ubaid ur</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c411t-4610333ef6a539c2f43d7569ff53e0d90777f04b9b0467a6d087ee094e9823243</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Research Article</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sumair, Muhammad</creatorcontrib><creatorcontrib>Aized, Tauseef</creatorcontrib><creatorcontrib>Gardezi, Syed Asad Raza</creatorcontrib><creatorcontrib>Bhutta, Muhammad Mahmood Aslam</creatorcontrib><creatorcontrib>Rehman, Syed Muhammad Sohail</creatorcontrib><creatorcontrib>Rehman, Syed Ubaid ur</creatorcontrib><collection>SAGE Open Access</collection><collection>CrossRef</collection><collection>Directory of Open Access Journals</collection><jtitle>Energy exploration & exploitation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sumair, Muhammad</au><au>Aized, Tauseef</au><au>Gardezi, Syed Asad Raza</au><au>Bhutta, Muhammad Mahmood Aslam</au><au>Rehman, Syed Muhammad Sohail</au><au>Rehman, Syed Ubaid ur</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of three probability distributions and techno-economic analysis of wind energy production along the coastal belt of Pakistan</atitle><jtitle>Energy exploration & exploitation</jtitle><date>2021-11-01</date><risdate>2021</risdate><volume>39</volume><issue>6</issue><spage>2191</spage><epage>2213</epage><pages>2191-2213</pages><issn>0144-5987</issn><eissn>2048-4054</eissn><abstract>Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application of three probability distributions, i.e. Weibull, Rayleigh, and lognormal for wind resource estimation at six sites along the coastal belt of Pakistan. Four years’ (2015–2018) wind data measured each 60-minutes at 50m height for six locations were collected from Pakistan Meteorological Department. Comparison of these distributions was done based on coefficient of determination (R²), root mean square error, and mean absolute percentage deviation. Comparison showed that Weibull distribution is the most accurate followed by lognormal and Rayleigh, respectively. Wind power density (PD
) was evaluated and it was found that Karachi has the highest wind speed and PD
as 5.82 m/s and 162.69 W/m², respectively, while Jiwani has the lowest wind speed and PD
as 4.62 m/s and 76.76 W/m², respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out.</abstract><cop>London, England</cop><pub>Sage Publications, Inc</pub><doi>10.1177/0144598720931587</doi><tpages>23</tpages><orcidid>https://orcid.org/0000-0001-9026-1092</orcidid><oa>free_for_read</oa></addata></record> |
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title | Comparison of three probability distributions and techno-economic analysis of wind energy production along the coastal belt of Pakistan |
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