Multi-Objective Optimization an‎d Comprehensive 4E Analysis of a Hybrid Cycle

4/21/2026 12:00:00 AM

With the increasing global population an‎d the simultaneous growth in electricity deman‎d, the need for efficient power generation systems has become more pressing. In addition, climate change an‎d the rise in the global average temperature highlight the need for innovative systems with higher efficiency an‎d lower greenhouse gas emissions. This study eva‎luates an optimal system for power generation, carbon dioxide absorption an‎d liquefaction, an‎d simultaneous heating an‎d cooling. The system is based on a combined cycle power plant integrated with carbon capture units to reduce greenhouse gas emissions. Parametric an‎d sensitivity analyses, including energy, exergy, economic, an‎d environmental assessments, were conducted. The base system delivers a net combined cycle power output of 232 MW an‎d a carbon dioxide production rate of 19.7 kg/s. Analysis of the organic Rankine unit shows that using R245fa as the working fluid yields the maximum efficiency, producing a net power output of 3.4 MW an‎d an energy efficiency of %17.3 in this unit. Furthermore, by actively employing methyl diethanolamine (MDEA) an‎d piperazine (PZ) solvents, the heat consumption of the separation tower has been reduced by 2.38 megajoules per kilogram of captured carbon dioxide. Based on the economic analysis an‎d the revenue from selling carbon dioxide, the levelized cost of electricity is $38 per megawatt-hour, an‎d the payback time under optimal conditions is 7.33 years. System optimization using artificial neural networks an‎d genetic evolutionary algorithms reduces the levelized cost of electricity an‎d increases both energy an‎d exergy efficiencies. In the optimized system, the energy efficiency is %58.6 an‎d the exergy efficiency is %54.

انرژي , اگزرژي , اقتصادي , نيروگاه تركيبي , كربن گيري

energy , exergy , economic , Combined Cycle , Carbon Capture

Seyed Reza Seyed Azimi

Mahdi Moghimi