A Hierarchical Fuzzy Data Envelopment Analysis to Locate the Solar Power Sites
Subject Areas :
Industrial Management
Navid Rafiei
1
,
Mahtab Sherafati
2
1 - PhD Student in Industrial Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran.
2 - Department of Industrial engineering, Collage of Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
Received: 2017-06-05
Accepted : 2017-10-17
Published : 2017-08-23
Keywords:
Abstract :
The creation of solar panels can be a turning point in the use of clean energy. Environmental protection, non-polluting, and efficiency of solar panels cause that they have been one of the important and novel means of electrical power generation in many parts of the world. In this paper, a hierarchical data envelopment analysis process is applied to determine the most efficient location for the solar power sites under uncertainty environment. Finally, the proposed approach is conducted for a real case study and the best and the most effective location is chosen for solar power generation site.
References:
Afshartous, D., Guan, Y., & Mehrotra, A. (2009). US Coast Guard air station location with respect to distress calls: A spatial statistics and optimization based methodology. European Journal of Operational Research, 196(3), 1086-1096.
Aras, H., Erdoğmuş, Ş., & Koç, E. (2004). Multi-criteria selection for a wind observation station location using analytic hierarchy process. Renewable Energy, 29(8), 1383-1392.
Choudhary, D., & Shankar, R. (2012). An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India. Energy, 42(1), 510-521.
Demirel, T., Demirel, N. Ç., & Kahraman, C. (2010). Multi-criteria warehouse location selection using Choquet integral. Expert Systems with Applications, 37(5), 3943-3952.
Domschke, W., & Drexl, A. (2013). Location and layout planning: An international bibliography (Vol. 238): Springer Science & Business Media.
Gamboa, G., & Munda, G. (2007). The problem of windfarm location: A social multi-criteria evaluation framework. Energy policy, 35(3), 1564-1583.
Jiménez, M., Arenas, M., Bilbao, A., & Rodrı, M. V. (2007). Linear programming with fuzzy parameters: an interactive method resolution. European Journal of Operational Research, 177(3), 1599-1609.
Saaty, T. L. (2000). Fundamentals of decision making and priority theory with the analytic hierarchy process (Vol. 6): Rws Publications.
Sueyoshi, T., & Goto, M. (2011). Measurement of Returns to Scale and Damages to Scale for DEA-based operational and environmental assessment: How to manage desirable (good) and undesirable (bad) outputs? European Journal of Operational Research, 211(1), 76-89.
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Afshartous, D., Guan, Y., & Mehrotra, A. (2009). US Coast Guard air station location with respect to distress calls: A spatial statistics and optimization based methodology. European Journal of Operational Research, 196(3), 1086-1096.
Aras, H., Erdoğmuş, Ş., & Koç, E. (2004). Multi-criteria selection for a wind observation station location using analytic hierarchy process. Renewable Energy, 29(8), 1383-1392.
Choudhary, D., & Shankar, R. (2012). An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India. Energy, 42(1), 510-521.
Demirel, T., Demirel, N. Ç., & Kahraman, C. (2010). Multi-criteria warehouse location selection using Choquet integral. Expert Systems with Applications, 37(5), 3943-3952.
Domschke, W., & Drexl, A. (2013). Location and layout planning: An international bibliography (Vol. 238): Springer Science & Business Media.
Gamboa, G., & Munda, G. (2007). The problem of windfarm location: A social multi-criteria evaluation framework. Energy policy, 35(3), 1564-1583.
Jiménez, M., Arenas, M., Bilbao, A., & Rodrı, M. V. (2007). Linear programming with fuzzy parameters: an interactive method resolution. European Journal of Operational Research, 177(3), 1599-1609.
Saaty, T. L. (2000). Fundamentals of decision making and priority theory with the analytic hierarchy process (Vol. 6): Rws Publications.
Sueyoshi, T., & Goto, M. (2011). Measurement of Returns to Scale and Damages to Scale for DEA-based operational and environmental assessment: How to manage desirable (good) and undesirable (bad) outputs? European Journal of Operational Research, 211(1), 76-89.