Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method
International Journal of Systems Science and Applied Mathematics
Volume 3, Issue 2, March 2018, Pages: 52-61
Received: Jun. 7, 2018; Accepted: Jul. 3, 2018; Published: Jul. 27, 2018
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Authors
Reza Gerami, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Morteza Mohammadi Ardehal, Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
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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.
Keywords
Energy Consumption, Energy Planning, ANN, LEAP, Policy, Photovoltaic
To cite this article
Reza Gerami, Morteza Mohammadi Ardehal, Suggestion a Novel Scenario in Iran Renewable Energy Planning Based on Modified ANN Method, International Journal of Systems Science and Applied Mathematics. Vol. 3, No. 2, 2018, pp. 52-61. doi: 10.11648/j.ijssam.20180302.15
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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