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A Novel Mixed Integer Programming Formulation for Selecting the Best Renewable Energies to Invest: A Fuzzy Goal Programming Approach

A Novel Mixed Integer Programming Formulation for Selecting the Best Renewable Energies to Invest: A Fuzzy Goal Programming Approach
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Author(s): Masoud Rabbani (School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran), Mahsa Ghanbarpour Mamaghani (School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran), Amir Farshbaf-Geranmayeh (School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran) and Mahsa Mirzayi (School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran)
Copyright: 2016
Volume: 7
Issue: 3
Pages: 22
Source title: International Journal of Operations Research and Information Systems (IJORIS)
Editor(s)-in-Chief: John Wang (Montclair State University, USA)
DOI: 10.4018/IJORIS.2016070101

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Abstract

The governments seeking to invest renewable energies for electrifying far spots and/or isolated islands are always confronted with the problem of selecting the best energy (portfolio of energies) technology. To reach the optimum decision, they must take into account a variety of criteria including technical, economic, environmental and social aspects at the same time. Therefore, the main objective of this study is to address the mentioned concern by developing a multi objective mixed integer programming formulation that not only takes into account the above criteria with a focus on tax, depreciation costs and time value of money, but also optimizes a set of objective functions simultaneously. Furthermore, to model the intrinsic uncertainty of some parameters like demand and budget, a fuzzy goal programming approach is applied. In order to demonstrate the applicability of the model, a numerical example, based on the data obtained from the literature, is developed. The results indicate that, for the given conditions, hydro and PV are superior to their counterparts.

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