On the most suitable sites for wind farm development in Nigeria

被引:22
作者
Ayodele, T. R. [1 ]
Ogunjuyigbe, A. S. O. [1 ]
Odigie, O. [1 ]
Jimoh, A. A. [2 ]
机构
[1] Univ Ibadan, Fac Technol, Dept Elect & Elect Engn, Power Energy Machine & Dr Res Grp, Ibadan, Nigeria
[2] Tshwane Univ Technol, Dept Elect Engn, Private Bag X680,Pretoria 0001, Pretoria West, South Africa
来源
DATA IN BRIEF | 2018年 / 19卷
关键词
D O I
10.1016/j.dib.2018.04.144
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The increasing demand for energy and the need for clean and affordable energy in Nigeria have necessitated the need for renewable energy resource assessment and subsequent determination of suitable sites within the country. One of the promising renewable energy resources with good potentials of meeting the energy requirements is wind. One of the main challenges of wind power development in Nigeria is lack of scientific data for policy formulation and decision making that will aid the development of wind power utilization. The data presented in this article were obtained with proper evaluation of the wind resource while taking into consideration environmental, social, and economic factors. The information from the data could be useful for taking optimal site selection decision by the policy makers, government, engineers etc. This will ensure optimal investment and return on investment for wind farm developers. (C) 2018 The Authors. Published by Elsevier Inc.
引用
收藏
页码:29 / 41
页数:13
相关论文
共 5 条
  • [1] The application of artificial neural networks to mapping of wind speed profile for energy application in Nigeria
    Fadare, D. A.
    [J]. APPLIED ENERGY, 2010, 87 (03) : 934 - 942
  • [2] A GIS-based multi-criteria evaluation for wind farm site selection. A regional scale application in Greece
    Latinopoulos, D.
    Kechagia, K.
    [J]. RENEWABLE ENERGY, 2015, 78 : 550 - 560
  • [3] Multi-criteria decision support system for wind farm site selection using GIS
    Noorollahi, Younes
    Yousefi, Hossein
    Mohammadi, Mohammad
    [J]. SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2016, 13 : 38 - 50
  • [4] Odigie O., 2018, THESIS
  • [5] Oztaysi B, 2015, ADV ENV ENG GREEN TE, P191, DOI 10.4018/978-1-4666-6631-3.ch008