An integrated multi attribute decision model for energy efficiency processes in petrochemical industry applying fuzzy set theory. (1st June 2016)

• Record Type: Journal Article
• Authors: Taylan, Osman; Kaya, Durmus; Demirbas, Ayhan
• Is Part Of: Energy conversion and management. Volume 117(2016)
• Page Start: 501
• Page End: 512
• Publication Date: 2016-06-01
• Subjects: Compressor selection -- Energy efficiency and CO2 emission -- Decision making -- Fuzzy AHP -- Fuzzy TOPSIS; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2016.03.048
• Languages: English
• ISSNs: 0196-8904

Abstract

Graphical abstract: Evaluation of compressors by comparing the different cost parameters. Highlights: Fuzzy sets and systems are used for decision making in MCDM problems. An integrated Fuzzy AHP and fuzzy TOPSIS approaches are employed for compressor selection. Compressor selection is a highly complex and non-linear process. This approach increases the efficiency, reliability of alternative scenarios, and reduces the pay-back period. Abstract: Energy efficient technologies offered by the market increases productivity. However, decision making for these technologies is usually obstructed in the firms and comes up with organizational barriers. Compressor selection in petrochemical industry requires assessment of several criteria such as ' reliability, energy consumption, initial investment, capacity, pressure, and maintenance cost. ' Therefore, air compressor selection is a multi-attribute decision making (MADM) problem. The aim of this study is to select the most eligible compressor(s) so as to avoid the high energy consumption due to the capacity and maintenance costs. It is also aimed to avoid failures due to the reliability problems and high pressure. MADM usually takes place in a vague and imprecise environment. Soft computing techniques such as fuzzy sets and system can be used for decision making where vague and imprecise knowledge is available. In this study, an integrated fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) methodologies are employed for the compressor selection. Fuzzy AHP was used to determine the weights of criteria and fuzzy TOPSIS was employed to order the scenarios according to their superiority. The total effect of all criteria was determined for all alternative scenarios to make an optimal decision. Moreover, the types of compressor, carbon emission, waste heat recovery and their capacities were analyzed and compared by statistical approaches. Six different scenarios were compared, scenario III was determined to be the best which has the highest closeness coefficient. In this scenario, the turbo compressors of active system reduces the total energy consumption due to low specific energy consumption (SEC) characteristics. Although the screw compressors have high maintenance costs, the heat recovery potential makes scenario III still preferable than the other 5 scenarios.