Optimization of waste heat recovery in internal combustion engine using a dual-loop organic Rankine cycle: Thermo-economic and environmental footprint analysis

Abstract

Listen

Translate article

In this research, a waste heat recovery system based on a Dual-loop organic Rankine cycle (DORC) was optimized for a 2 MW natural gas engine. A thermo-economic and environmental assessment was carried out to study the energy, economic, and environmental performance of the system. A sensitivity analysis was developed to study the effects of the condenser and evaporator pinch point temperature, turbine efficiency, and high evaporation pressure on the payback period (PBP), the specific investment cost (SIC), the net power output (Wnet), and the levelized cost of energy (LCOE). Similarly, a multi-objectiveoptimization method from agenetic algorithm (GA) was conducted to determine the optimum Pareto frontier solution from the thermal and economical approach. Therefore, the net power output was maximized, as the thermo-economic indicators considered using toluene as the working fluid was minimized under constrains. The results of the thermo-economic study revealed that heat transfer equipment (ITC1, ITC2, ITC3, and ITC4) represent 86.34% of the total exergy destroyed in the system, followed by pumps (P1, P2, and P3) with 11.38%. Also, the ITC1 was the heat exchanger equipment with the greater saving potential due to the high investment costs. The study also shows that the heat exchanger ITC3 was the equipment with the highest exergy cost of the system, while the others showed slight variations in the evaluated range of the variables. Finally, the bi-objective optimization made it possible to establish the optimum operating point of the thermal system that maximized the net power output at 99.21 kW, minimizing the economic indicators (PBP and SIC), where the carbon footprint obtained was the lowest (54040 kg CO2 eq) at 67.2% engine load and the highest absolute decrease in the specific fuel consumption (6.2%) at 89.4% engine load. However, with the tri-objective optimization, better results were obtained for the net power output (100.07 kW), which represented an increase of 80% respect to the bi-objective method.