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

Author

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  • 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)

  • Mahsa Mirzayi

    (School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran)

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.

Suggested Citation

  • Masoud Rabbani & Mahsa Ghanbarpour Mamaghani & Amir Farshbaf-Geranmayeh & Mahsa Mirzayi, 2016. "A Novel Mixed Integer Programming Formulation for Selecting the Best Renewable Energies to Invest: A Fuzzy Goal Programming Approach," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 7(3), pages 1-22, July.
    • Handle: RePEc:igg:joris0:v:7:y:2016:i:3:p:1-22
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    Cited by:

    1. P. Senthil Kumar, 2018. "Linear Programming Approach for Solving Balanced and Unbalanced Intuitionistic Fuzzy Transportation Problems," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 9(2), pages 73-100, April.

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