Environmental Valuation & Cost-Benefit News
An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors
03/31/07
02:49:26 am, by damageva 
, 261 words, 355 views 
Categories: Energy, Asia, Companies,CSR,Business,Finance, Academic Study/Journal Article, Costs and Benefits
An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors
Abstract: This paper introduces an integrated approach based on data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT) for total energy efficiency assessment and optimization in energy intensive manufacturing sectors. Total energy efficiency assessment and optimization of the proposed approach considers structural indicators in addition conventional consumption and manufacturing sector output indicators. The validity of the DEA model is verified and validated by PCA and NT through Spearman correlation experiment. Moreover, the proposed approach uses the measure-specific super-efficiency DEA model for sensitivity analysis to determine the critical energy carriers. Four energy intensive manufacturing sectors are discussed in this paper: iron and steel, pulp and paper, petroleum refining and cement manufacturing sectors. To show superiority and applicability, the proposed approach has been applied to refinery sub-sectors of some OECD (Organization for Economic Cooperation and Development) countries. This study has several unique features which are: (1) a total approach which considers structural indicators in addition to conventional energy efficiency indicators; (2) a verification and validation mechanism for DEA by PCA and NT and (3) utilization of DEA for total energy efficiency assessment and consumption optimization of energy intensive manufacturing sectors.
Keywords: Energy efficiency; Optimization; Energy intensive manufacturing sectors
by A. Azadeh, M.S. Amalnick, S.F. Ghaderi and S.M. Asadzadeh; all of Department of Industrial Engineering, Faculty of Engineering, Center of Excellence for Intelligent Experimental Mechanics, Research Institute of Energy Management and Planning, P.O. Box, University of Tehran, Iran; Telephone:; fax:.
Energy Policy via Elsevier Science Direct www.ScienceDirect.com
Article in Press, Corrected Proof
http://dx.doi.org/10.1016/j.enpol.2007.01.018
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