Multi-objective optimization and life cycle assessment of mass-integrated combined heat and power system.

As the effects of climate change become more widely recognized, technical innovation and green energy will promote the growth of combined heat and power systems. This study proposes a novel mass-integrated combined heat and power system and conducts energy analysis, exergy analysis, and techno-economic analysis for the system. The optimization strategy integrated polynomial regression and non-dominated sorting genetic algorithm III is established, with system thermal efficiency, exergy efficiency, and return on investment (ROI) as objective functions.