ScienceDirect - Renewable and Sustainable Energy Reviews : Application of multi-criteri... - 1 views
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Ihering Alcoforado on 15 Jul 10Application of multi-criteria decision making to sustainable energy planning-A review S. D. Pohekar , and M. Ramachandran Birla Institute of Technology and Science (BITS), Pilani 333 031, India Received 1 December 2003; accepted 19 December 2003. Available online 31 January 2004. Abstract Multi-Criteria Decision Making (MCDM) techniques are gaining popularity in sustainable energy management. The techniques provide solutions to the problems involving conflicting and multiple objectives. Several methods based on weighted averages, priority setting, outranking, fuzzy principles and their combinations are employed for energy planning decisions. A review of more than 90 published papers is presented here to analyze the applicability of various methods discussed. A classification on application areas and the year of application is presented to highlight the trends. It is observed that Analytical Hierarchy Process is the most popular technique followed by outranking techniques PROMETHEE and ELECTRE. Validation of results with multiple methods, development of interactive decision support systems and application of fuzzy methods to tackle uncertainties in the data is observed in the published literature. Author Keywords: Author Keywords: Multi-objective optimization; Multi-criteria decision making; Decision support systems; Sustainable energy planning Article Outline 1. Introduction 2. Overview of multi-criteria decision making (MCDM) methods 2.1. Weighted sum method (WSM) 2.2. Weighted product method (WPM) 2.3. Analytical hierarchy process (AHP) 2.4. Preference ranking organization method for enrichment evaluation (PROMETHEE) 2.5. The elimination and choice translating reality (ELECTRE) 2.6. The technique for order preference by similarity to ideal solutions (TOPSIS) 2.7. Compromise programming (CP) 2.8. Multi-attribute utility theory (MAUT) 3. Multi-criteria decision making applications in energy planning 3.1. Multi-objective optimization 3.2. Decision Suppor