An intelligent NSGA-II-based optimization of a novel biogas-fed oxyfuel gas turbine cycle using CO2 capture option coupled with a multi-heat recovery network and a multi-effect desalination cycle

This study explores the advantages of biogas utilization in high-temperature power. The key innovations of the study include design of a novel polygeneration system that utilizes biogas fuel through an oxyfuel combustion method and incorporates an advanced multi-heat recovery approach. It features a cascade multi-heat recovery technique that minimizes energy loss and includes a CO₂ capture unit. The entire system is also optimized using a multi-objective strategy based on advance data-driven methods. The network incorporates a supercritical CO₂ Brayton cycle, a combined cooling and power cycle utilizing ammonia-water working fluid, a multi-effect desalination unit, and a steam Rankine cycle to produce electricity, cooling, heating, and desalinated water. The engineering equation solver is employed for simulation, allowing comprehensive thermodynamic, exergoeconomic, and sustainability analyses. In addition, an intelligent optimization process is conducted using the NSGA-II method coupled with artificial neural networks to enhance the optimization procedure's speed and accuracy. The final optimum solution is selected based on TOPSIS decision-making method. The parametric analysis result identifies the temperature of the combustion chamber as the most significant parameter, evidenced by a mean sensitivity index of 0.556. Furthermore, the multi-criteria optimization incorporates exergy efficiency, desalinated water rate, and total unit cost of products as the objective functions, revealing optimal values of 49.32 %, 66.35 m³/day, and 27.54 $/GJ, respectively. Besides, the system achieves a net electricity output of 1644 kW, alongside cooling and heating loads of 44.71 kW and 41.81 kW, respectively. The optimization process has been streamlined to take <20 min, resulting in cost savings and enhanced efficiency through predictive maintenance and integrated energy strategies. Finally, the optimal sustainability index and net present value are calculated to be 1.97 and 18.32 M$, respectively.