An innovative optimal integrated solar-lignocellulosic biomass polygeneration system with biorefinery and solid oxide electrolyzer cell

Abstract

Polygeneration systems combine various energy sources and processes to produce multiple products for residential and industrial needs in a unified system, offering enhanced sustainability and resilience compared to single-process systems. Optimizing these systems maximizes energy resource utilization. This study introduces a comprehensive polygeneration system generating eight products to satisfy power, cooling, heating, and secondary product requirements like fresh water, hydrogen, oxygen, carbon dioxide, and ethanol. The system is based on two renewable energy sources, solar and biomass, as well as traditional methane energy. Through a comprehensive evaluation encompassing energy, exergy, exergo-economic, exergo-environmental, emergo-economic, and emergo-environmental considerations, the system is thoroughly evaluated. Mathematical modeling in MATLAB assesses thermal, economic, and ecological factors for optimization. Validation is performed using Thermoflex and Aspen Plus for an ethanol and power co-production biorefinery from corn stover. Multi-objective optimization employs a machine learning and genetic algorithm approach in two phases. The initial phase targets three objectives for the hybrid multi-effect distillation adsorption desalination unit to optimize fresh water production, performance ratio, and energy consumption. Our results demonstrate that in the optimal scenario, there is an 8.2% increase in fresh water production rate, a 10.2% increase in performance ratio, and a 9.2% reduction in specific energy consumption. In the second phase, the overall system is optimized with the objective of maximizing thermodynamic performance while minimizing economic and environmental indicators. The six-objective optimization results in a 2.54% increase in overall energy efficiency, a 3.38% increase in overall exergy efficiency, and a 59.66% improvement in the coefficient of performance of the ejector refrigeration cycle. Additionally, it leads to a 1.88% reduction in overall exergy costs, a 39.78% reduction in overall environmental impacts, and a 19.77% reduction in overall emergy for the system. Therefore, the selected optimization approach has been recognized as a valuable tool for achieving more efficient utilization of energy resources.