Identifying the optimum operating conditions for the integration of a solar loop to power an industrial flash dryer: Combining an exergy analysis with genetic algorithm optimization

Zhor El Hallaoui, Fayrouz El Hamdani, Sébastien Vaudreuil, Tijani Bounahmidi and Souad Abderafi

Renewable Energy, 2022, vol. 191, issue C, 828-841

Abstract: With the objective to reduce fossil fuels consumption and greenhouse gas emissions, the integration of solar thermal energy into energy-intensive processes represents the most effective solution. This paper investigates the best solar integration scenarios to an industrial dryer unit through an exergy analysis. The exergetic balance for each subsystem is conducted, and a sensitivity parametric analysis was carried out. The optimization using the Genetic Algorithm was then conducted to define the optimum solar operating conditions. The exergetic evaluation showed an important exergy destruction at the dryer and combustion chamber, accounting for 58% and 42% of the inlet exergy flow, respectively. The sensitivity analysis outcomes showed that the exergy efficiency is clearly increased by increasing both drying temperature, decreasing the inlet moisture content, with preheating the combustion air temperature. Considering these variables, the optimization problem enabled enhancing the exergy efficiency by 40% and 30% for the overall process and flash dryer, respectively, when increasing drying temperature to 850 °C, an inlet moisture content of 14.9% and a preheated air combustion of 150 °C. Finally, the solar field could be integrated to the industrial dryer to preheat the ambient air for the combustion chamber to the setpoint temperature of 150 °C.

Keywords: Solar thermal integration; Exergy analysis; Industrial flash dryer; Parametric sensitivity analysis; Genetic algorithm; Optimization (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:191:y:2022:i:c:p:828-841

DOI: 10.1016/j.renene.2022.04.072

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