Manara - Qatar Research Repository
Browse

Feasibility analysis of wind energy potential along the coastline of Pakistan

Download (6.91 MB)
journal contribution
submitted on 2024-09-02, 06:33 and posted on 2024-09-02, 06:35 authored by Syed Sulman Ahmad, Ans Al Rashid, Syed Ali Raza, Asad A. Zaidi, Sohaib Z. Khan, Muammer Koç

Wind energy is gaining popularity, especially across the countries with strong and continuous wind currents. Pakistan is bestowed with multiple wind corridors with prospective energy extraction, mainly concentrated along the coastline. This work aims to analyze the effectiveness and feasibility of wind energy potential in Pakistan coastline by choosing four unique zones (Karachi, Ormara, Pasni, and Gawadar) through analysis and demonstration for a 50 MW wind farm. Four years of seasonal data is used for the selected zones, reflecting the wind effectiveness in wind speed, wind density, and wind directions. Computer-based predictive models and artificial neural networks are also implemented to forecast the wind effectiveness, primarily based on the observed wind seasonal data. The wind farm's feasibility is proposed through a comparative evaluation for various turbine designs considering both geographical, installation, operational and financial factors. The factors of energy output, economic feasibility, environmental impact, and fuel-saving are analyzed for multiple locations and turbine designs. Critical observations, data, and findings are presented and discussed in detail for all zones. Zone 1 has a highest capacity factor of 46% followed by 40.4% (Zone 2), 29.3% (Zone 3), 37.5% (Zone 4). The study revealed that Karachi is the best-suited location for a 50 MW wind farm with the highest wind speed and the lowest variation in wind direction annually. It also represented the highest internal rate of return, benefit-to-cost ratio, and annual saving with a minimum payback period (4.5–7.2 years) for various commercially available turbine designs.

Other Information

Published in: Ain Shams Engineering Journal
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.asej.2021.07.001

History

Language

  • English

Publisher

Elsevier

Publication Year

  • 2022

License statement

This Item is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU

Geographic coverage

Pakistan

Usage metrics

    College of Science and Engineering - HBKU

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC