Antlion Optimization of Solar-Assisted CCHP Systems: Enhancing Efficiency and Reducing Emissions through Optimal Design Configuration
Year: 2025
Type: preprint
Abstract: Solar-assisted combined cooling, heating, and power (CCHP) systems offer a sustainable solution to address the escalating energy demand resulting from economic and population growth. This advancement has facilitated a reduction in excessive fuel consumption, thereby mitigating the associated impacts of climate change and global warming. These multi-generation systems undeniably possess the advantage of fuel efficiency, leading to enhanced overall system efficiency compared to individual cooling, heating, and power generation systems. However, optimizing these systems is imperative to realize optimal system design configurations that enhance their thermodynamic performance indicators. Therefore, this study proposed the antlion multi-objective optimization approach to optimize the performance of a solar-assisted CCHP system. The aim was to create a mathematical programming model that would ascertain the ideal ratio for compression, the difference in temperature at the pinch point, the temperature of the inlet turbine, and the temperature of the combustion chamber. This would enable the optimization of net power and energy efficiency while reducing carbon dioxide emissions. The results obtained emphasized that optimized net power, exergy efficiency, and CO 2 emission values could be realized by a reduced compression ratio and inlet combustion chamber temperature. A relatively lower CO 2 emission rate of at least 6.5% and better exergy values were realized, outperforming the response surface method. The suggested optimization method produced 100 Pareto optimum solutions, giving decision-makers a variety of options and insightful information for improving systems and making decisions in the power production industry.
Authors: Uchechi Ukaegbu, Lagouge Tartibu, C. W. Lim
Institutions: University of Johannesburg, City University of Hong Kong
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4413276860