The evolutionary artificial intelligence-based algorithm to find the minimum GHG emission via the integrated energy system using the MSW as fuel in a waste heat recovery plant. (October 2022)

• Record Type: Journal Article
• Authors: Hai, Tao; Alsharif, Sameer; Dhahad, Hayder A.; Attia, El-Awady; Shamseldin, Mohamed A.; Najat Ahmed, Ahmed
• Is Part Of: Sustainable energy technologies and assessments. Volume 53:Part B(2022)
• Publication Date: 2022-10
• Subjects: Digestion -- Municipal solid waste -- Waste heat recovery -- GHG emission reduction; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2022.102531
• Languages: English
• ISSNs: 2213-1388

Abstract

Abstract: In the present study, the system is developed to be optimized via artificial intelligence to reduce the environmental impact of the combined energy system based on fuel cells and powered by municipal solid waste as fuel. The municipal solid waste enters the waste treatment plant to prepare to enter the digester. The biogas from the digester is then put into the combined energy system as fuel. The artificial intelligence-based genetic algorithm is proposed to minimize the effect of CO2 emission on the environment. Furthermore, the environmental impact reduction via biogas is compared to that of ordinary systems. The system is modeled regarding technical and economic aspects, and the effect of key design variables is foreseen. Optimization, which is carried out, shows that in the best operation state, the system is capable of producing not only the work of 250 kW but also the second law efficiency, cost rate, and GHG emission of 36.3 %, 22 dollars per hour and 0.93 Ton/MWh, respectively.