Triple-objective optimization of a double-tube heat exchanger with elliptic cross section in the presence TiO2 nanofluid

Khanmohammadi, Shoaib; Rahimi, Zeynab; Khanmohammadi, Saber; Afrand, Masoud

doi:10.1007/s10973-019-08744-1

Cited by 9 publications

(1 citation statement)

References 26 publications

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“…Every solution associated with a point on the Pareto front is a vector whose components represent trade-offs in the decision space [29,42]. Therefore, without additional information, Pareto optimal solutions are considered equally good [43,44]. Selecting an optimal solution thus depends on the trade-offs between objective functions.…”

Section: Pareto Front Multiobjective Optimizationmentioning

confidence: 99%

Multiobjective Optimization of the Energy Efficiency and the Steam Flow in a Bagasse Boiler

Molina,

Vidal Medina,

Sagastume Gutiérrez

et al. 2023

Sustainability

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Renewable energy and energy efficiency are essential for a transition to cleaner and sustainable energy. Photovoltaic and wind turbine systems introduce operation, control, protection, and planning issues, particularly affecting frequency stability in the grid. In contrast to more widespread wind turbines and photovoltaic systems, biomass based electricity systems are more stable with no negative impacts on the grid stability. The efficiency of bagasse boilers is essential to guaranteeing adequate economic profit and environmental performance in sugar plants. To realize universal access to affordable, reliable, and modern energy services by 2030 (SDG 7), the use of renewable energy sources in energy mixing and energy efficiency must increase globally. Sugar plants include cogeneration systems to provide heat and electricity to the process and frequently sell an electricity surplus to the grid, which depends on their energy efficiency. Boilers are an essential component of cogeneration systems in sugar plants, and their efficiency is crucial to guarantee electricity surplus. Therefore, this study assessed a bagasse boiler to optimize its operational efficiency. To this end, the exergy assessment and multiobjective optimization based on a genetic algorithm are used. The results show that the exergy efficiency of the boiler improved by 0.8% with the optimization, reducing bagasse consumption by 23 t/d.

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