Skip to main content
SpringerLink
Log in

A Fuzzy Inference System to Evaluate the Environmental Effects of Electricity Generation Technologies

  • Conference paper
  • First Online:
2nd International Congress on Energy Efficiency and Energy Related Materials (ENEFM2014)

Part of the book series: Springer Proceedings in Energy ((SPE))

  • 1507 Accesses

Abstract

Power plants activity can have positive and negative effects on the population, which must be taken into account. In many cases various kinds of power generation systems can have a significant adverse impact on the environment, increasing health risks and reducing the standard of living of local communities. In this paper a methodology based on fuzzy-sets is proposed to assess the impact on a local scale of the sustainability of the most important electricity power production technologies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. E. Santoyo-Castelazo, A. Azapagic, Sustainability assessment of energy systems: integrating environmental, economic and social aspects. J. Clean. Prod. 80(1), 119–138 (2014)

    Article  Google Scholar 

  2. A. Evans, V. Strezov, T.J. Evans, Assessment of sustainability indicators for renewable energy technologies. Renew. Sustain. Energy Rev. 13(5), 1082–1088 (2009)

    Article  Google Scholar 

  3. V.R. Prakash, I.B. Bhat, Energy, economics and environmental impacts of renewable energy systems. Renew. Sustain. Energy Rev. 13(9), 2716–2721 (2009)

    Article  Google Scholar 

  4. A. Maxim, Sustainability assessment of electricity generation technologies using weighted multi-criteria decision analysis. Energy Policy 65, 284–297 (2014)

    Article  Google Scholar 

  5. F. Cavallaro, L. Ciraolo, Sustainability assessment of solar technologies based on linguistic information, in Assessment and Simulation Tools for Sustainable Energy Systems: Theory and Applications, ed. by F. Cavallaro (Springer, 2013)

    Google Scholar 

  6. F. Cavallaro, Fuzzy TOPSIS approach for assessing thermal-energy storage in concentrated solar power (CSP) systems. Appl. Energy 87(2), 496–503 (2010)

    Article  Google Scholar 

  7. Y. Chai, L. Jia, Z. Zhang, Mamdani model based adaptive neural fuzzy inference system and its application. Int. J. Inf. Math. Sci. 5(1), 22–29 (2009)

    Google Scholar 

  8. A.M.G. Cornelissen, J. Van den Berg, W.J. Koops et al., Assessment of the contribution of sustainability indicators to sustainable development: a novel approach using fuzzy set theory. Agric. Ecosyst. Environ. 86(2), 173–185 (2001)

    Article  Google Scholar 

  9. B. Öztaysi, H. Behret, Ö. Kabak, et al., Fuzzy inference systems for disaster response, in Decision Aid Models for Disaster Management and Emergencies, ed. by B. Vitoriano, L. Montero, D. Ruan (Atlantis-Springer, 2013)

    Google Scholar 

  10. J.C. Bezdek, Fuzzy models—what are they, and why? IEEE Trans. Fuzzy Syst. 1(1), 1–6 (1993)

    Article  MathSciNet  Google Scholar 

  11. D. Dubois, F. Esteva, L. Godo, et al., in Fuzzy-set Based Logics—An History-oriented Presentation of Their Main Developments, ed. by D.M. Gabbay, J. Woods. Handbook of the History of Logic, vol. 8 (Elsevier BV, 2007)

    Google Scholar 

  12. G.J. Klir, B. Yuan, Fuzzy sets and fuzzy logic—theory and applications (Prentice Hall, New Jersey, 1995)

    MATH  Google Scholar 

  13. A. Reveiz, C. León, Operational Risk Management Using a Fuzzy Logic Inference System. Borradores de Economia, Banco de la República Colombia, n.574 (2009)

    Google Scholar 

  14. A. Saberi Nasr, M. Rezaei, M. Dashti Barmaki, Analysis of groundwater quality using mamdani fuzzy inference system (MFIS) in Yazd Province, Iran. Int. J. Comput. Appl. 59(7), 45–53 (2012)

    Google Scholar 

  15. IPCC Working Group III—Mitigation of Climate Change, Special Report on Renewable Energy Sources and Climate Change Mitigation, Annex III Technology—specific cost and performance parameters (2011)

    Google Scholar 

  16. V. Fthenakis, H. Chul Kim, Land use and electricity generation: A life-cycle analysis. Renew. Sustain. Energy Rev. 13(6–7), 1465–1474 (2009)

    Article  Google Scholar 

  17. E.E. Michaelides, Environmental and ecological effects of energy production and consumption, in Alternative Energy Sources, ed. by E.E. Michaelides (Springer, Berlin Heidelberg, 2012)

    Chapter  Google Scholar 

  18. S.J.W. Klein, E.S. Rubin, Life cycle assessment of greenhouse gas emissions, water and land use for concentrated solar power plants with different energy backup systems. Energy Policy 63, 935–950 (2013)

    Article  Google Scholar 

  19. M.Z. Jacobson, Review of solutions to global warming, air pollution, and energy security. Energy Environ. Sci. 2, 148–173 (2009)

    Article  Google Scholar 

  20. S. Guillaume, B. Charnomordic, Learning interpretable fuzzy inference systems with FisPro. Inf. Sci. 181(20), 4409–4427 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Economics, Management, Society and Institutions (EGSI), University of Molise, Via De Sanctis, Campobasso, 86100, ITALY

    Fausto Cavallaro

Authors
  1. Fausto Cavallaro
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fausto Cavallaro .

Editor information

Editors and Affiliations

  1. Dept of Materials Science & Engineering, Gebze Technical University, Gebze, Kocaeli, Turkey

    A.Y Oral

  2. Dept of Environmental Engineering, Gebze Technical University, Gebze, Kocaeli, Turkey

    Z.B Bahsi Oral

  3. Department of Physics, Istanbul Kultur University, Bakirkoy, Istanbul, Turkey

    M. Ozer

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Cavallaro, F. (2015). A Fuzzy Inference System to Evaluate the Environmental Effects of Electricity Generation Technologies. In: Oral, A., Bahsi Oral, Z., Ozer, M. (eds) 2nd International Congress on Energy Efficiency and Energy Related Materials (ENEFM2014). Springer Proceedings in Energy. Springer, Cham. https://doi.org/10.1007/978-3-319-16901-9_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-16901-9_28

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16900-2

  • Online ISBN: 978-3-319-16901-9

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics

Search

Navigation