Process simulation and stochastic multiobjective optimisation of homogeneously acid-catalysed microalgal in-situ biodiesel production considering economic and environmental criteria. (1st November 2022)

• Record Type: Journal Article
• Authors: Ahmed, Mukhtar; Abdullah, Anas; Laskar, Abdullah; Patle, Dipesh S.; Vo, Dai-Viet N.; Ahmad, Zainal
• Is Part Of: Fuel. Volume 327(2022)
• Publication Date: 2022-11-01
• Subjects: Multiobjective optimisation -- Non-dominated sorting genetic algorithm (NSGA-II) -- In-situ transesterification -- Algal biodiesel -- Total Annualised Cost (TAC) -- CO2 emissions; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2022.125165
• Languages: English
• ISSNs: 0016-2361

Abstract

Highlights: Simulation and EMOO of one-pot biodiesel production from algal biomass. Optimization considering economic and environmental criteria. NSGA-II algorithm reveals alternate optimal designs for in-situ biodiesel synthesis. First rank solution was determined by net flow method. Significant reductions in TAC (13.1%), organic waste (55%), and CO2 emissions (41%) respectively. Abstract: The present work aims at the simulation and multiobjective optimisation (MOO) of dry microalgae-based in-situ biodiesel plant, modelled using the Aspen Plus V11. The process optimisation was carried out by excel-based multiobjective optimisation (EMOO) considering the non-dominated sorting genetic algorithm-II (NSGA-II). Economic and environmental criteria were considered for constrained MOO with total annualised cost (TAC), organic wastes, and CO2 emissions as objectives. The statistical trade-offs were analysed by assessing the impacts of the decision variables on the chosen objectives. Firstly, bi-objective optimisation scenarios were studied, and finally, a tri-objective optimisation scenario was investigated. The results imply that the TAC increases with the decrease in organic waste generation and CO2 emissions. The decision-makers will be able to assess the Pareto-optimal front to find the preferred optimal solution to enhance plant performance. The first rank solution in the generated Pareto-optimal front was chosen by the net flow method (NFM). Compared to the base case study with a TAC of 69.31 million USD, Scenario A, Scenario B, and Scenario C resulted in an optimal plant operation with a TAC of 62.64 million USD, 61.52 million USD, and 60.23 million USD, respectively, with a saving of 6.67 million USD, 7.79 million USD, and 9.08 million USD respectively. Simultaneous optimisation of all three conflicting objectives yielded significant reductions in TAC (13.1%), organic waste (55%), and CO2 emissions (41%), respectively.