Exergoeconomic multi-objective optimization of an externally fired gas turbine integrated with a biomass gasifier

This study deals with thermodynamic and economic analysis of a combined gas turbine and Organic Rankine Cycle integrated with a biomass gasifier. A modified model is used to increase the precision of the gasifier thermodynamic model. Seven decision variables, namely, biomass gasification temperature (Tgasif), combustion temperature (Tcomb), gas turbine inlet temperature (T3), gas turbine isentropic efficiency (ηGT), compressor isentropic efficiency (ηcomp), compressor pressure ration (rp) and maximum ORC operating pressure (P3R), are selected as the main decision variables of the combined system. The total cost rate and exergy efficiency of the system are chosen as the two main objective functions. A group method of data handling (GMDH) type neural network and evolutionary algorithm (EAs) are used for modeling the effects of the seven decision variables on both objective functions. The result of multi-objective optimization shows that the exergy efficiency of the system is 15.6%, which can be increase to 17.9% in the optimal state, regardless of the total cost rate of system as objective function. In addition, in order to better illustrate the effects of decision variables change in three selected points of the Pareto curve, a sensitive analysis is performed.