Multiple criteria evaluation of current energy resources for Turkish manufacturing industry


Önüt S., Tuzkaya U. R., Saadet N.

ENERGY CONVERSION AND MANAGEMENT, cilt.49, ss.1480-1492, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 49
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1016/j.enconman.2007.12.026
  • Dergi Adı: ENERGY CONVERSION AND MANAGEMENT
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1480-1492
  • Anahtar Kelimeler: energy resources, Turkish manufacturing industry, analytic network process, ANALYTIC HIERARCHY PROCESS, EFFICIENCY, OPTIMIZATION, ELECTRICITY, SECTOR, TURKEY, PRIORITIZATION, MANAGEMENT, SYSTEMS, DEMAND
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Energy is the main component of natural resources of developing, as well as developed, countries like Turkey. Because of economic and social developments, the demand for energy, in general, has increased considerably in Turkey. Since Turkey is not an oil or natural gas (NG) producing country, the energy resource usage for energy consumption should be effective. The Turkish industrial sector comprises approximately 36% of Turkey's primary energy consumption, and the manufacturing industry is the largest industrial sector. In this study, the focus was on the manufacturing industry as the major energy consuming sector in Turkey, and it was analyzed in terms of efficient use of energy resources. The most widely used energy resources in the Turkish manufacturing industry, namely fuel-oil, coal, electricity, LPG and NG were taken into account. Evaluation and selection of current energy resources in this selected industry can be viewed as a multiple criteria decision making (MCDM) problem, including human judgments, tangible and intangible criteria and priorities and trade offs between goals and criteria. The analytic network process (ANP), one of the MCDM methods, was used to evaluate the most suitable energy resources for the manufacturing industry in this study. (C) 2008 Elsevier Ltd. All rights reserved.