Design of Container Ship Main Engine Waste Heat Recovery Supercritical CO2 Cycles, Optimum Cycle Selection through Thermo-Economic Optimization with Genetic Algorithm and Its Exergo-Economic and Exergo-Environmental Analysis

Abstract

In the present study, energy and exergy analyses of a simple supercritical, a split supercritical and a cascade supercritical CO2 cycle are conducted. The bottoming cycles are coupled with the main two-stroke diesel engine of a 6800 TEU container ship. An economic analysis is carried out to calculate the total capital cost of these installations. The functional parameters of these cycles are optimized to minimize the electricity production cost (EPC) using a genetic algorithm. Exergo-economic and exergo-environmental analyses are conducted to calculate the cost of the exergetic streams and various exergo-environmental parameters. A parametric analysis is performed for the optimum bottoming cycle to investigate the impact of ambient conditions on the energetic, exergetic, exergo-economic and exergo-environmental key performance indicators. The theoretical results of the integrated analysis showed that the installation and operation of a waste heat recovery optimized split supercritical CO2 cycle in a 6800 TEU container ship can generate almost 2 MW of additional electric power with a thermal efficiency of 14%, leading to high fuel and CO2 emission savings from auxiliary diesel generators and contributing to economically viable shipping decarbonization.

Research on ship route and speed optimization considering rolling meteorological data: intelligent decision design based on genetic algorithm

“…Therefore, researchers have been actively seeking methods to improve the efficiency and sustainability of maritime operations. For example, chemists have analyzed various supercritical carbon dioxide cycles [1] to obtain optimal bottoming cycle parameters for increasing electrical power at the same pollution level.…”