Determination of the Weibull parameters and wind power potential: A case of Okorobo-Ile town, Rivers state, Nigeria

In this study, we investigate the potential of wind power and subsequently determine the Weibull parameters of a rural community (Okorobo-Ile town, in Andoni local government area of Rivers State, Nigeria) using four years of real-time measured data (2020, 2021, 2022, and 2023). The Weibull shape and scale factors are crucial parameters in modeling wind energy systems or hybrid systems involving wind turbines. The computed scale factor and an optimized (adjusted) shape factor from the two-parameter Weibull model used in this study showed a good fit with the actual measured data, which was captured at a height of 10 m. The average annual power density, power generated, and energy for the region are 81.07 W/m², 0.41 MW, and 3557.79 MWh, respectively. Based on these values, the potential of the energy in the wind at Okorobo-Ile town can be said to be marginal and belongs to wind power class 2. The site is considered appropriate for small to medium-scale power generation from the wind. Analysis of five wind turbine models indicates that the Siemens SWT-2.3–101 turbine is the most appropriate, with an average annual energy contribution (58.55 %). The Vestas V90–3.0 MW and Enercon E-82 E4 also show good performance with average annual energy contributions of 46.48 % and 38.59 % respectively. These turbines can collectively meet and exceed the community’s daily energy demand of 656 kWh, providing a reliable and sustainable energy source that supports economic growth and energy independence for the region.

Authors

Institutions

Publication Details

Journal
Wind energy and engineering research.
Published
2024-11-26
DOI
https://doi.org/10.1016/j.weer.2024.100006
Citations
4
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
5.20
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Determination of the Weibull parameters and wind power potential: A case of Okorobo-Ile town, Rivers state, Nigeria

Kelvin Nkalo Ukoima, Ogbonnaya I. Okoro, Udochukwu B. Akuru, Innocent E. Davidson
4 citations
Wind energy and engineering research.
Wind Energy Research and Development
5.20
article

Determination of the Weibull parameters and wind power potential: A case of Okorobo-Ile town, Rivers state, Nigeria

Kelvin Nkalo Ukoima, Ogbonnaya I. Okoro, Udochukwu B. Akuru, Innocent E. Davidson
article en
4 citations

Abstract

In this study, we investigate the potential of wind power and subsequently determine the Weibull parameters of a rural community (Okorobo-Ile town, in Andoni local government area of Rivers State, Nigeria) using four years of real-time measured data (2020, 2021, 2022, and 2023). The Weibull shape and scale factors are crucial parameters in modeling wind energy systems or hybrid systems involving wind turbines. The computed scale factor and an optimized (adjusted) shape factor from the two-parameter Weibull model used in this study showed a good fit with the actual measured data, which was captured at a height of 10 m. The average annual power density, power generated, and energy for the region are 81.07 W/m², 0.41 MW, and 3557.79 MWh, respectively. Based on these values, the potential of the energy in the wind at Okorobo-Ile town can be said to be marginal and belongs to wind power class 2. The site is considered appropriate for small to medium-scale power generation from the wind. Analysis of five wind turbine models indicates that the Siemens SWT-2.3–101 turbine is the most appropriate, with an average annual energy contribution (58.55 %). The Vestas V90–3.0 MW and Enercon E-82 E4 also show good performance with average annual energy contributions of 46.48 % and 38.59 % respectively. These turbines can collectively meet and exceed the community’s daily energy demand of 656 kWh, providing a reliable and sustainable energy source that supports economic growth and energy independence for the region.

Wind energy and engineering research.Vol. 2
Tshwane University of Technology (ZA), Cape Peninsula University of Technology (ZA), Michael Okpara University of Agriculture (NG)
Affordable and clean energy
Openalex Percentile: Top 5%
Wind Energy Research and Development
5.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.