Multi-objective optimization, techno-economic analysis, and life cycle assessment of an innovative solar-biomass-driven cogeneration system integrated with MED-RO-MD: A case study of the Canary Islands

Abstract

Managing freshwater and electricity production in islands is vital for sustainability and reducing dependency on external resources, ensuring energy security and environmental protection. This study explores the design, analysis, and feasibility of an innovative biomass-solar cogeneration system that produces both power and freshwater for the Canary Islands, Spain. The proposed system design incorporates a combination of the Brayton cycle, steam Rankine cycle, and organic Rankine cycle for power generation, while integrating multi-effect distillation, reverse osmosis, and membrane distillation desalination for freshwater production. Additionally, a CO2 capture unit is included to minimize environmental pollutant emissions. The solar field provides the necessary heat for the system via the solar tower, while the air-steam gasification unit supplies the required energy for the cycle using biomass. The biomass fuel selected is based on the local forest type, specifically Canary Pine Needles. Machine learning is applied to analyze the subsystems of the proposed system. The feasibility of the proposed system has been evaluated through technical-economic analysis and life cycle assessment. Dynamic modeling was performed based on the climatic conditions of Las Palmas. Finally, a sensitivity analysis and multi-objective optimization were conducted on the system's functional parameters. The objective functions in the optimization process included maximizing cogeneration efficiency, minimizing the payback period, and minimizing the total environmental impact rate. Three multi-objective optimization algorithms (NSGA-III, MOMVO, MOGOA) were used to optimize the proposed system. The results indicate that the proposed system achieves an average energy efficiency of 31.64 % and exergy efficiency of 14.35 % annually. The average levelized cost and environmental impact of electricity are calculated to be 0.19 $/kWh and 1.24 mPts/kWh, respectively. Additionally, the payback period for the system is estimated at 3.22 years. The multi-objective optimization of the proposed system resulted in a 54.04 % improvement in cogeneration efficiency, a 38.82 % reduction in payback period, and a 6.39 % decrease in the environmental impact rate, compared to the baseline performance of the system before optimization.