Using green hydrogen as the supplementary fuel for a scheme of power/fresh water production: An application of AI for optimal energy management and emission reduction

• Published in: Process safety and environmental protection 2024-10, Vol.190, p.1273-1289
• Main Authors: Luo, Jie, Abed, Azher M., Salah, Bashir, Chohan, Mandeep Kaur, Yajid, Mohd Shukri Ab, MGM, Johar, Chen, Yong
• Format: Article
• Language: English
• Subjects: Biomass; Clean energy; Hydrogen; MED; Multi-objective optimization; PV panel; Renewable hybridization
• ISSN: 0957-5820
• DOI: 10.1016/j.psep.2024.07.091

The primary objective of the current research is to speed up the shift towards a carbon-neutral economy and reduce our reliance on fossil fuels by developing a novel, highly efficient, environmentally friendly, and economically feasible multi-generation system based on solar-biomass hybridization. The essential element of this concept involves the introduction of green hydrogen into the combustion chamber, aiming to enhance the quality of the incineration products and facilitate the implementation of a waste-to-power Rankine cycle. The practicality of the suggested model is compared with a system that does not incorporate hydrogen injection. As a part of artificial intelligence, a neural network model integrated with the grey wolf optimizer is applied to ascertain the most optimal energy conversion/management condition with reduced computational time. The results show that the injection of additional hydrogen exhibits superior performance compared to the base system from all facets. The optimization achieves higher exergy efficiency and drinkable water production of 8.7 % and 27.9 kg/s while reducing the total cost and emission index of 13.7 $/h and 410.7 kg/GWh. The results indicate that the combustion chamber and steam generator are the poorest parts in terms of exergy under ideal conditions. Potential future directions of this work are to explore alternate techniques for generating hydrogen and perform regional evaluations to comprehend the accessibility and fluctuation of biomass and solar resources in various geographical areas. [Display omitted] •A novel hybrid system based on solar and biomass hybridization is proposed.•The system feasibility is compared with the conventional model from all aspects.•Various optimization scenarios based on machine learning techniques are applied.•The hydrogen injection leads to better techno-economic-environmental performance.•The optimization achieves lower cost and emission of 2.1 $/MWh and 410.7 kg/GWh.