Biodiesel feedstocks selection strategies based on economic, technical, and sustainable aspects. (1st January 2021) - Anwar, Mohammad
Highlights: 16 most popular biodiesel feedstocks were analysed for screening the best feedstocks. 15 economic, technical, environmental, and social criteria were used. 5 weighting methods (EQUAL, CRITIC, ENTROPY, AHP, and FAHP) have been used. 4 MCDA processes, namely PROMETHEE GAIA, WSM, WPM, and TOPSIS were implemented. Soybean was ranked as the worst feedstock and Coconut rated the best performer. Abstract: The interest in sustainable energy sources such as biodiesel is growing due to unpredictable fossil fuel prices, depletion of their origins, inconsistent supply, geopolitical instability, and conflicts of fuel/oil-producing countries, global politics, and sanctions. The selection of the right biodiesel feedstocks is the first step of mass biodiesel production. This paper is aimed at defining the best possible biodiesel feedstocks using various multiple criteria decision analysis (MCDA) processes. Several facets that can effect on the biodiesel feedstocks selection process are economic, technical, environmental, and social aspects. This study concentrated on fifteen 'criteria' based on the economic aspect (cost of biodiesel production), technical aspects (physicochemical properties and structural composition (fatty acid) of biodiesel feedstocks), and environmental aspects (sustainable land usage for crop production) for the selection process. Sixteen most popular biodiesel feedstocks, namely Palm, Soybean, Sunflower, Moringa, Jatropha, Pongamia, Mustard, Coconut, Tallow, Peanut, Corn, Cottonseed, Ricebran, Beauty leaf, Rapeseed and waste cooking oil biodiesel were investigated as 'alternatives' in this analysis. For 'weight' determination of each criterion, five weighting methods in percentage, namely EQUAL, CRITIC, ENTROPY, Analytical hierarchical process (AHP), and Fuzzy Analytical Hierarchical Process (FAHP) were used. Four MCDA processes, namely PROMETHEE Graphical Analysis for Interactive Assistance (GAIA), Weighted sum method (WSM), Weighted product method (WPM), and Technique for order preference by similarity to ideal solution (TOPSIS) were implemented for this investigation. The findings indicate that Coconut rated best and Soybean was regarded as the worst feedstock among those alternatives.