Integrated linear programming and analytical hierarchy process method for diesel/biodiesel/butanol in reducing diesel emissions

Abstract

In this study, an attempt to obtain the optimal fuel blends consisting of diesel/biodiesel/alcohol, which satisfies the ASTM D975 and EN590, has been performed. Fuel blending is complicated due to the trade-offs concerning the various criteria. The Linear Programming fuel blending model only evaluates solutions concerning quantitative criteria with one single objective function. In fuel blending, qualitative criteria must be considered in making the final decision. A new methodological framework that integrates a two-stage product design optimisation model consisting of a Linear Programming (quantitative) and Analytical Hierarchy Process (AHP) (qualitative) is developed. The AHP was used to evaluate the criteria weight. Four criteria were implied in selecting the optimal blends, covering good performance, emissions limitations, cost-effectiveness, and safety trade-offs. Seven sub-criteria such as cetane number, the heat of vaporisation, oxygen content, sulphur content, CO2 emissions, flash point, and feedstock cost are examined. Four alcohol oxygenates as alternatives to be selected methanol, ethanol, propanol, and butanol. The final AHP results depicted diesel/biodiesel/alcohol (Blend 1) comprising of 70% diesel, 20% biodiesel, 10% butanol as the optimal blends with higher performance (CN = 48.69), lowest cost (1.2 USD/L), and cleaner emission with 35% less sulphur concentration and 36% CO2 emissions mitigated. The AHP results were then validated by employing Sensitivity Analysis for four scenarios by increasing 20% of the priority vector. The solution of the sensitivity analysis of weights levels indicates the acceptable possibility of achieving the objective/goal. Blend 1 (diesel/biodiesel/butanol) is the optimal blend, followed by Blend 4 (diesel/biodiesel/methanol), Blend 2 (diesel/biodiesel/propanol) and Blend 3 (diesel/biodiesel/ethanol). In conclusion, this proposed new framework provides the confident decision to select alcohol oxygenates for future fuel diesel/biodiesel/alcohol without an extensive experiment, thereby saving time and money and reducing harmful environmental impacts.