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Implementing conceptual model using renewable energies in rural area of Iran

Karami Dehkordi, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1016/j.inpa.2017.02.003
  3. Abstract:
  4. In a glance, more than three billion people live in the rural areas of low and middle income countries. In most cases, rural households have many unmet energy needs including cooking, lighting, heating, transportation and telecommunication needs. The main goal of this study is Implementing Conceptual Model Using Renewable Energies in Rural Area of Iran. In this study, the Weibull and Angestrom distribution methods were used to assess the potential of wind and solar energy range in Chaharmahal va Bakhtiari province of Iran (The Case study). After determining the values calculated based on meteorological stations' data, the IDW interpolation method in GIS software was used for the entire geographic range of the province. After reviewing multiple regions and identifying potential classes, a village which has the potential to be enough sun and wind energy was selected (Kahkesh village) and then a field survey based on biomass resources was accomplished. The needs of rural residents and rural renewable energy potential was evaluated by study conceptual frameworks during one year. By dividing the value of frameworks energies the amount of energy saving can be calculated. Finally, it recommended that for utilizing the renewable energies in rural areas, as will be discussed in the present work and particularly using the conceptual frameworks, is performed. © 2017 China Agricultural University
  5. Keywords:
  6. Renewable energy ; Energy conservation ; Heating ; Solar energy ; Weibull distribution ; Conceptual frameworks ; Conceptual model ; Interpolation method ; Low and middle income countries ; Meteorological station ; Renewable energies ; Renewable energy potentials ; Rural areas ; Alternative energy ; Biomass ; Conceptual framework ; Implementation process ; wind power ; Chahar mahall va bakhtiari
  7. Source: Information Processing in Agriculture ; Volume 4, Issue 3 , 2017 , Pages 228-240 ; 22143173 (ISSN)
  8. URL: https://www.sciencedirect.com/science/article/pii/S2214317316300762