AN APPLICATION OF MULTIPLE CRITERIA DECISION MAKING ON SELECTING THE PRIME MOVER FOR TRIGENERATION SYSTEMS

  • Ali Nadi Ünal
  • Gülgün Kayakutlu
  • Seçil Ercan
Keywords: Fuzzy TOPSIS, Multiple Criteria Decision Making, Tri-generation

Abstract

In today's world, fossil fuels are still considered to be the primary energy source. Increasing energy demand leads researchers to conduct studies on energy efficiency field. Two facades of energy efficiency problems are production type and consuming type, respectively. Fossil fuels are mainly used for generating electricity and heating. Tri-generation technologies enable simultaneous satisfaction of electricity, heating and cooling demands. Increasing number of studies show that these systems are more preferable regarding technical, economic, environmental and social aspects. On the other hand, choosing the right system configuration and operating this system optimally is an important problem itself. In this study, the most suitable alternative for a small sized tri-generation system is chosen using a multiple criteria decision making method. The alternatives of systems are adopted from the literature. The attributes that affect the selection process are also taken from the literature. Fuzzy TOPSIS is used in order to select the best alternative.

References

[1] International Energy Agency, “Key World Energy Statistics,” 2013.
[2] “Türkiye Cumhuriyeti Enerji ve Tabii Kaynaklar Bakanlığı,” 2014. [Online]. Available: http://www.enerji.gov.tr.
[3] M. Jradi and S. Riffat, “Tri-generation systems: Energy policies, prime movers, cooling technologies, configurations and operation strategies,” Renew. Sustain. Energy Rev., vol. 32, pp. 396–415, Apr. 2014.
[4] P. Liu, D. I. Gerogiorgis, and E. N. Pistikopoulos, “Modeling and optimization of polygeneration energy systems,” Catal. Today, vol. 127, no. 1–4, pp. 347–359, Sep. 2007.
[5] A. Nieto-Morote and F. Ruz-Vlila, “A Fuzzy AHP Multi-Criteria Decision-Making Approach Applied to Combined Cooling, Heating, and Power Production Systems.,” Int. J. Inf. Technol. Decis. Mak., vol. 10, no. 3, pp. 497–517, 2011.
[6] E. Moretti, E. Bonamente, C. Buratti, and F. Cotana, “Development of Innovative Heating and Cooling Systems Using Renewable Energy Sources for Non-Residential Buildings.,” Energies (19961073), vol. 6, no. 10, pp. 5114–5129, Oct. 2013.
[7] F. A. Al-Sulaiman, I. Dincer, and F. Hamdullahpur, “Thermoeconomic optimization of three trigeneration systems using organic Rankine cycles: Part II – Applications,” Energy Convers. Manag., vol. 69, pp. 209–216, May 2013.
[8] M. Demir, “Enerji İthalatı Cari Açık İlişkisi, VAR Analizi ile Türkiye Üzerine Bir İnceleme,” Akad. Araştırmalar ve Çalışmalar Derg., vol. 5, no. 9, pp. 2–27, 2013.
[9] Q. Gu, H. Ren, W. Gao, and J. Ren, “Integrated assessment of combined cooling heating and power systems under different design and management options for residential buildings in Shanghai,” Energy Build., vol. 51, pp. 143–152, Aug. 2012.
[10] H. Cho, A. D. Smith, and P. Mago, “Combined cooling, heating and power: A review of performance improvement and optimization,” Appl. Energy, vol. 136, pp. 168–185, Dec. 2014.
[11] F. A. Al-Sulaiman, F. Hamdullahpur, and I. Dincer, “Trigeneration: A comprehensive review based on prime movers.,” Int. J. Energy Res., vol. 35, no. 3, pp. 233–258, Mar. 2011.
[12] M. Liu, Y. Shi, and F. Fang, “Combined cooling, heating and power systems: A survey,” Renew. Sustain. Energy Rev., vol. 35, pp. 1–22, Jul. 2014.
[13] G. Chicco and P. Mancarella, “Distributed multi-generation: A comprehensive view,” Renew. Sustain. Energy Rev., vol. 13, no. 3, pp. 535–551, Apr. 2009.
[14] D. Sonar, S. L. Soni, and D. Sharma, “Micro-trigeneration for energy sustainability: Technologies, tools and trends,” Appl. Therm. Eng., Dec. 2013.
[15] J. Deng, R. Z. Wang, and G. Y. Han, “A review of thermally activated cooling technologies for combined cooling, heating and power systems,” Prog. Energy Combust. Sci., vol. 37, no. 2, pp. 172–203, Apr. 2011.
[16] P. J. Mago and L. M. Chamra, “Analysis and optimization of CCHP systems based on energy, economical, and environmental considerations,” Energy Build., vol. 41, no. 10, pp. 1099–1106, Oct. 2009.
[17] M. Ebrahimi and A. Keshavarz, “Prime mover selection for a residential micro-CCHP by using two multi-criteria decision-making methods,” Energy Build., vol. 55, pp. 322–331, Dec. 2012.
[18] Y.-Y. Jing, H. Bai, and J.-J. Wang, “A fuzzy multi-criteria decision-making model for CCHP systems driven by different energy sources,” Energy Policy, vol. 42, pp. 286–296, Mar. 2012.
[19] Y.-Y. Jing, J.-H. Zhao, and J.-J. Wang, “Using the Multi Criteria Analysis Method PROMENTHEE II to Select the Optimal CCHP System: A Case Study,” in ASME 2009 3rd International Conference on Energy Sustainability, Volume 2, 2009, pp. 35–41.
[20] A. Nieto-Morote, F. Ruz-Vlila, and F. J. Canovas-Rodrigez, “Selection of a trigeneration system using a fuzzy AHP multi-criteria decision-making approach,” Int. J. Energy Res., vol. 35, no. 9, pp. 781–794, 2011.
[21] H. Ren, W. Gao, W. Zhou, and K. Nakagami, “Multi-criteria evaluation for the optimal adoption of distributed residential energy systems in Japan,” Energy Policy, vol. 37, no. 12, pp. 5484–5493, Dec. 2009.
[22] J.-J. Wang, Y.-Y. Jing, and C.-F. Zhang, “Weighting methodologies in multi-criteria evaluations of combined heat and power systems.,” Int. J. Energy Res., vol. 33, no. 12, pp. 1023–1039, Oct. 2009.
[23] J.-J. Wang, Y.-Y. Jing, C.-F. Zhang, G.-H. Shi, and X.-T. Zhang, “A fuzzy multi-criteria decision-making model for trigeneration system,” Energy Policy, vol. 36, no. 10, pp. 3823–3832, Oct. 2008.
[24] J.-J. Wang, Y.-Y. Jing, C.-F. Zhang, X.-T. Zhang, and G.-H. Shi, “Integrated evaluation of distributed triple-generation systems using improved grey incidence approach,” Energy, vol. 33, no. 9, pp. 1427–1437, Sep. 2008.
[25] M. Velasquez and P. T. Hester, “An Analysis of Multi-Criteria Decision Making Methods,” Int. J. Oper. Res., vol. 10, no. 2, pp. 56–66, 2013.
[26] C.-T. Chen, “Extensions of the TOPSIS for group decision-making under fuzzy environment,” Fuzzy Sets Syst., vol. 114, no. 1, pp. 1–9, Aug. 2000.
[27] H.-S. Shih, H.-J. Shyur, and E. S. Lee, “An extension of TOPSIS for group decision making,” Math. Comput. Model., vol. 45, no. 7–8, pp. 801–813, Apr. 2007.
[28] A. Öztürk, İ. Ertuğrul, and N. Karakaşoğlu, “Nakliye firması seçiminde bulanık AHP ve bulanık TOPSIS yöntemlerinin karşılaştırılması,” Marmara Üniversitesi İİ BF Derg., vol. 25, no. 2, pp. 785–824, 2008.
[29] D. Tadic, A. Gumus, S. Arsovski, A. Aleksic, and M. Stefanovic, “An evaluation of quality goals by using fuzzy AHP and fuzzy TOPSIS methodology,” J. Intell. Fuzzy Syst., no. 25, pp. 547–556, 2013.
[30] T. Kaya and C. Kahraman, “Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul,” Energy, vol. 35, no. 6, pp. 2517–2527, Jun. 2010.
Published
2016-01-25
How to Cite
[1]
A. Ünal, G. Kayakutlu, and S. Ercan, “AN APPLICATION OF MULTIPLE CRITERIA DECISION MAKING ON SELECTING THE PRIME MOVER FOR TRIGENERATION SYSTEMS”, JAST, vol. 9, no. 1, pp. 43-56, Jan. 2016.
Section
Articles