International Journal of Systems Science and Applied Mathematics

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Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method

Received: Jun. 07, 2018    Accepted: Jul. 03, 2018    Published: Jul. 27, 2018
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Abstract

In this study end-users energy consumption of Iran are predicted using ANN (artificial neural network) by historical data and socio-economic parameters (1990-2013) up to 2030 horizon. Iran energy balances are forecasted by bottom up analysis using LEAP (long-range energy alternative planning). On other hand solar energy promotion policies around the world, Iran policies and its solar energy potentials are investigated. Novel policy for Iran photovoltaic systems promotion are proposed and impact of this scenario implementation evaluated on Iran energy balance. Result show 750 MBOE (million barrel of oil equivalents) will be saved and 320 million metric tons co2 equivalent emission reduced up to 2030.

DOI 10.11648/j.ijssam.20180302.15
Published in International Journal of Systems Science and Applied Mathematics ( Volume 3, Issue 2, March 2018 )
Page(s) 52-61
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Energy Consumption, Energy Planning, ANN, LEAP, Policy, Photovoltaic

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Cite This Article
  • APA Style

    Reza Gerami, Morteza Mohammadi Ardehal. (2018). Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method. International Journal of Systems Science and Applied Mathematics, 3(2), 52-61. https://doi.org/10.11648/j.ijssam.20180302.15

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    ACS Style

    Reza Gerami; Morteza Mohammadi Ardehal. Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method. Int. J. Syst. Sci. Appl. Math. 2018, 3(2), 52-61. doi: 10.11648/j.ijssam.20180302.15

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    AMA Style

    Reza Gerami, Morteza Mohammadi Ardehal. Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method. Int J Syst Sci Appl Math. 2018;3(2):52-61. doi: 10.11648/j.ijssam.20180302.15

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  • @article{10.11648/j.ijssam.20180302.15,
      author = {Reza Gerami and Morteza Mohammadi Ardehal},
      title = {Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method},
      journal = {International Journal of Systems Science and Applied Mathematics},
      volume = {3},
      number = {2},
      pages = {52-61},
      doi = {10.11648/j.ijssam.20180302.15},
      url = {https://doi.org/10.11648/j.ijssam.20180302.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijssam.20180302.15},
      abstract = {In this study end-users energy consumption of Iran are predicted using ANN (artificial neural network) by historical data and socio-economic parameters (1990-2013) up to 2030 horizon. Iran energy balances are forecasted by bottom up analysis using LEAP (long-range energy alternative planning). On other hand solar energy promotion policies around the world, Iran policies and its solar energy potentials are investigated. Novel policy for Iran photovoltaic systems promotion are proposed and impact of this scenario implementation evaluated on Iran energy balance. Result show 750 MBOE (million barrel of oil equivalents) will be saved and 320 million metric tons co2 equivalent emission reduced up to 2030.},
     year = {2018}
    }
    

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    T1  - Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method
    AU  - Reza Gerami
    AU  - Morteza Mohammadi Ardehal
    Y1  - 2018/07/27
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    DO  - 10.11648/j.ijssam.20180302.15
    T2  - International Journal of Systems Science and Applied Mathematics
    JF  - International Journal of Systems Science and Applied Mathematics
    JO  - International Journal of Systems Science and Applied Mathematics
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    PB  - Science Publishing Group
    SN  - 2575-5803
    UR  - https://doi.org/10.11648/j.ijssam.20180302.15
    AB  - In this study end-users energy consumption of Iran are predicted using ANN (artificial neural network) by historical data and socio-economic parameters (1990-2013) up to 2030 horizon. Iran energy balances are forecasted by bottom up analysis using LEAP (long-range energy alternative planning). On other hand solar energy promotion policies around the world, Iran policies and its solar energy potentials are investigated. Novel policy for Iran photovoltaic systems promotion are proposed and impact of this scenario implementation evaluated on Iran energy balance. Result show 750 MBOE (million barrel of oil equivalents) will be saved and 320 million metric tons co2 equivalent emission reduced up to 2030.
    VL  - 3
    IS  - 2
    ER  - 

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Author Information
  • Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

  • Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

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