Analysis and Comparison of Wind Potential by Estimating the Weibull Distribution Function: Application to Wind Farm in the Northern of Morocco

Author:

Bousla Mohamed1ORCID,Haddi Ali1,El Mourabit Youness1ORCID,Sadki Ahmed2ORCID,Mouradi Abderrahman2,El Kharrim Abderrahman2,Mobayen Saleh3ORCID,Zhilenkov Anton4ORCID,Bossoufi Badre5ORCID

Affiliation:

1. Innovating Technologies Team, National School of Applied Sciences, Tetouan, Abdelmalek Essaadi University, Tetouan 93000, Morocco

2. Energy, Materials and Computing Physics Research Group, ENS, Abdelmalek Essaadi University, Tetouan 93020, Morocco

3. Graduate School of Intelligent Data Science, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou 640301, Yunlin, Taiwan

4. Department of Cyber-Physical Systems, St. Petersburg State Marine Technical University, 190121 Saint-Petersburg, Russia

5. LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30050, Morocco

Abstract

To assess wind energy potential in Northern Morocco, a validated approach based on the two-parameter Weibull distribution is employed, utilizing wind direction and speed data. Over a span of two years, from January 2019 to December 2020, measurements taken every 10 min are collected. This study is centered on a comprehensive and statistical analysis of electricity generated from a wind farm situated in the Tetouan region in Morocco. This wind farm boasts a total capacity of 120 MW, comprising 40 wind turbines, each with a 3 MW capacity, strategically positioned along the ridge. Among the available techniques for estimating Weibull distribution parameters, the maximum likelihood method (MLM) is chosen due to its statistical robustness and exceptional precision, especially for large sample sizes. Throughout the two-year period, monthly wind speed measurements fluctuated between 2.1 m/s and 9.1 m/s. To enhance accuracy, monthly and annual theoretical power densities were recalculated using the Weibull parameters and compared with actual measurements. This has enabled the detection of production disparities and the mitigation of forecast errors throughout the entire wind farm. In conclusion, over the two-year production period, turbines WTG 30 and WTG 33 displayed the most significant shortcomings, primarily attributed to orientation issues within the “Yaw system”.

Funder

Ministry of Science and Higher Education of the Russian Federation as part of the World-class Research Center program: Advanced Digital Technologies

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference31 articles.

1. Sustainable production of wind energy in the main Morocco’s sites using permanent magnet synchronous generators;Derouich;Int. Trans. Electr. Energy Syst.,2020

2. The influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries;Dogan;Renew. Sustain. Energy Rev.,2016

3. Renewable energy resources: Current status, future prospects and their enabling technology;Ellabban;Renew. Sustain. Energy Rev.,2014

4. Implementation and validation of backstepping control for PMSG wind turbine using dSPACE controller board;Youness;Energy Rep.,2019

5. Direct utilization of geothermal energy 2015 worldwide review;Lund;Geothermics,2016

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