Comparative study of multicriteria decision making methods for renewable energy technologies ranking in electricity production


Authors

  • César Aristóteles Yajure Ramírez 1) Universidad Central de Venezuela 2) Ministerio del Poder Popular para la Energía Eléctrica
  • Yaismir Arlenis Guzman 1) Universidad Nacional Experimental de la Fuerza Armada 2) Ministerio del Poder Popular para la Energía Eléctrica

DOI:

https://doi.org/10.22517/23447214.11591

Keywords:

Multicriteria, Promethee, AHP, TOPSIS, Renewable Energies, Electricity

Abstract

This paper presents a comparative study of different techniques of multicriteria decision making for ranking renewable energy technologies to be used in the production of electricity. Three different methods, AHP American School, PROMETHEE European School, and TOPSIS are analyzed. The technologies considered were: Solar Thermal, Solar Photovoltaic, Geothermal, Biomass, Wind, and Hydraulics; while the decision criteria used were: efficiency in percentage, installation cost in dollars per kilowatt, electricity cost in cents per kilowatt hour, CO2 emissions in kilograms per kilowatt-hour, life in years, and used area in square kilometers per kilowatt. The proposed methodology is applied to a case study already discussed in previous research by various authors.

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Author Biographies

César Aristóteles Yajure Ramírez, 1) Universidad Central de Venezuela 2) Ministerio del Poder Popular para la Energía Eléctrica

Ingeniero Electricista, Especialista en Sistemas de Potencia, Magister Scientiarum en Investigación de Operaciones. Docente de Postgrado UCV. Planificador en MPPEE.

Yaismir Arlenis Guzman, 1) Universidad Nacional Experimental de la Fuerza Armada 2) Ministerio del Poder Popular para la Energía Eléctrica

Ingeniero en Mantenimiento Mecánico, Magister en Mantenimiento

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Published

2017-09-06

How to Cite

Yajure Ramírez, C. A., & Guzman, Y. A. (2017). Comparative study of multicriteria decision making methods for renewable energy technologies ranking in electricity production. Scientia Et Technica, 22(3), 273–280. https://doi.org/10.22517/23447214.11591

Issue

Vol. 22 No. 3 (2017)

Section

Industrial

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