Melola Discovery

← Melola Discovery

Akses terbuka Jurnal SINTA 1

Data bank: nine numerical methods for determining the parameters of weibull for wind energy generation tested by five statistical tools

International Journal of Power Electronics and Drive Systems · Vol. 12 No. 2 (2021) · hlm. 1114–1130

DOI
10.11591/ijpeds.v12.i2.pp1114-1130
ISSN
2722-256X, 2088-8694
Terbit
2021-06-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

This study aims to determine the potential of wind energy in the mediterranean coastal plain of Palestine. The parameters of the Weibull distribution were calculated on basis of wind speed data. Accordingly, two approaches were employed: analysis of a set of actual time series data and theoretical Weibull probability function. In this analysis, the parameters Weibull shape factor ‘k’ and the Weibull scale factor ‘c’ were adopted. These suitability values were calculated using the following popular methods: method of moments (MM), standard deviation method (STDM), empirical method (EM), maximum likelihood method (MLM), modified maximum likelihood method (MMLM), second modified maximum likelihood method (SMMLM), graphical method (GM), least mean square method (LSM) and energy pattern factor method (EPF). The performance of these numerical methods was tested by root mean square error (RMSE), index of agreement (IA), Chi-square test (X2), mean absolute percentage error (MAPE) and relative root mean square error (RRMSE) to estimate the percentage of error. Among the prediction techniques. The EPF exhibited the greatest accuracy performance followed by MM and MLM, whereas the SMMLM exhibited the worst performance. The RMSE achieved the best prediction accuracy, whereas the RRMSE attained the worst prediction accuracy.

Kata kunci

Jaringan kolaborasi para penulis

40 penulis · 150 tautan kepenulisan bersama · 12 lintas organisasi · menampilkan 40 yang paling banyak terhubung

Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.

  • International Islamic University Malaysia
  • International Islamic University, Islamabad
  • Özyeğin University
  • Universiti Teknologi MARA
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Nurul Fadzlin HasbullahInternational Islamic University, Islamabad5
Ahmed Samir Abed BadawiInternational Islamic University Malaysia5
Mohammed ElamassieÖzyeğin University5
Alhareth ZyoudInternational Islamic University Malaysia5
Majdee TohtayongAfiliasi tidak diketahui4
Nur Shahida MidiAfiliasi tidak diketahui4
Teddy Surya GunawanInternational Islamic University Malaysia3
Mashkuri YaacobAfiliasi tidak diketahui3
Nurul Fadzlin HasbullahaAfiliasi tidak diketahui3
Musse Mohamud AhmedAfiliasi tidak diketahui2
Fawwaz WafaAfiliasi tidak diketahui2
Ezzidin AboadlaAfiliasi tidak diketahui2
Khairil Azhar AznanAfiliasi tidak diketahui2
Aisha H HashimAfiliasi tidak diketahui2
Mohamed Hadi HabaebiInternational Islamic University Malaysia1
Nur Syazana Izzati RazaliAfiliasi tidak diketahui1
Saerahany Legori IbrahimAfiliasi tidak diketahui1
Siti Nadiah Mohd SapihieAfiliasi tidak diketahui1
Mira KartiwiInternational Islamic University Malaysia1
Agus PratondoAfiliasi tidak diketahui1
Fatin Najihah Muhamad ZamriAfiliasi tidak diketahui1
Yasir Mohd. MustafahAfiliasi tidak diketahui1
Nofri Yenita DahlanUniversiti Teknologi MARA1
Adriana Haziqah Mohd AizamAfiliasi tidak diketahui1
Saidatul Habsah AsmanAfiliasi tidak diketahui1
S. M. A. MotakabberInternational Islamic University Malaysia1
Khadiza AkterAfiliasi tidak diketahui1
A. H. M. Zahirul AlamAfiliasi tidak diketahui1
Sajib AhmedAfiliasi tidak diketahui1
Tania AnnurAfiliasi tidak diketahui1
Suriza Ahmad ZabidiAfiliasi tidak diketahui1
Muhamad Aqil Muqri Muhamad FahmiAfiliasi tidak diketahui1
Mohd Shahrin Abu HanifahAfiliasi tidak diketahui1

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) http://ijpeds.iaescore.com/index.php/IJPEDS/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">Data bank: nine numerical methods for determining the parameters of weibull for wind energy generation tested by five statistical tools</dc:title>
	<dc:creator>Badawi, Ahmed Samir</dc:creator>
	<dc:creator>Yusoff, Siti Hajar</dc:creator>
	<dc:creator>Zyoud, Alhareth Mohammed</dc:creator>
	<dc:creator>Khan, Sheroz</dc:creator>
	<dc:creator>Hashim, Aisha</dc:creator>
	<dc:creator>Uyaroğlu, Yılmaz</dc:creator>
	<dc:creator>Ismail, Mahmoud</dc:creator>
	<dc:subject xml:lang="en-US">Average wind speed; Cumulative distribution function; Probability distribution function; Numerical analysis; Statistical tools; Weibull parameters; Wind energy</dc:subject>
	<dc:description xml:lang="en-US">This study aims to determine the potential of wind energy in the mediterranean coastal plain of Palestine. The parameters of the Weibull distribution were calculated on basis of wind speed data. Accordingly, two approaches were employed: analysis of a set of actual time series data and theoretical Weibull probability function. In this analysis, the parameters Weibull shape factor ‘k’ and the Weibull scale factor ‘c’ were adopted. These suitability values were calculated using the following popular methods: method of moments (MM), standard deviation method (STDM), empirical method (EM), maximum likelihood method (MLM), modified maximum likelihood method (MMLM), second modified maximum likelihood method (SMMLM), graphical method (GM), least mean square method (LSM) and energy pattern factor method (EPF). The performance of these numerical methods was tested by root mean square error (RMSE), index of agreement (IA), Chi-square test (X2), mean absolute percentage error (MAPE) and relative root mean square error (RRMSE) to estimate the percentage of error. Among the prediction techniques. The EPF exhibited the greatest accuracy performance followed by MM and MLM, whereas the SMMLM exhibited the worst performance. The RMSE achieved the best prediction accuracy, whereas the RRMSE attained the worst prediction accuracy.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2021-06-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/21000</dc:identifier>
	<dc:identifier>10.11591/ijpeds.v12.i2.pp1114-1130</dc:identifier>
	<dc:source xml:lang="en-US">International Journal of Power Electronics and Drive Systems (IJPEDS); Vol 12, No 2: June 2021; 1114-1130</dc:source>
	<dc:source>2722-256X</dc:source>
	<dc:source>2088-8694</dc:source>
	<dc:source>10.11591/ijpeds.v12.i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/21000/13465</dc:relation>
	<dc:relation>https://ijpeds.iaescore.com/index.php/IJPEDS/article/downloadSuppFile/21000/2903</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2021 Ahmed Samir Badawi, Siti Hajar Yusoff, Alhareth Mohammed Zyoud, Sheroz Khan, Aisha Hashim, Yılmaz Uyaroğlu, Mahmoud Ismail</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>