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A fuzzy-TOPSIS approach for techno-economic viability of lighting energy efficiency measure in public building projects
- Source :
- Journal of Project Management, Vol 3, Iss 4, Pp 197-206 (2018)
- Publication Year :
- 2018
- Publisher :
- Growing Science, 2018.
-
Abstract
- Retrofitting technologies have helped to manage energy consumptions in residential, public and industrial buildings. However, understanding of the technical and economic considerations for selection of appropriate retrofitting technology is still evolving and divergent. Thus, this study presents a framework that combines techno-economic requirements as a means for evaluating the important retrofitting criteria and suitable lighting retrofit technologies for building projects. The framework is hinged on the unique features of entropy fuzzy and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods. The analysis of the lighting technology selection was performed from technical, economic and techno-economic perspectives. During the application of the proposed framework, four lighting technologies (CFL, T5, E-ballast and T8-electronic) and nine techno-economic criteria were considered. The most and least important techno-economic criteria for the case study were net present value and electricity saved, respectively. The least and most suitable retrofitting technologies were T8-electronic and CFL, respectively, from techno-economic perspective. T5 and T8-electronic were identified as the most suitable lighting technologies from an economic and technical perspectives, respectively. This discrepancy in the results justified the need for the techno-economic approach for the retrofitting technologies evaluation.
- Subjects :
- Measure (data warehouse)
lcsh:Management. Industrial management
Operations research
Computer science
Fuzzy topsis
Techno economic
TOPSIS
lcsh:Business
Similarity (network science)
Techno-economic criteria
Public buildings
lcsh:HD28-70
Retrofitting
Lighting technology
lcsh:HF5001-6182
Decision making
Selection (genetic algorithm)
Efficient energy use
Subjects
Details
- Language :
- English
- ISSN :
- 23718374 and 23718366
- Volume :
- 3
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Journal of Project Management
- Accession number :
- edsair.doi.dedup.....24bfa302499c6c965bc45ef2b3ded9a2