Synergetic fusion of energy optimization and waste heat reutilization using nature-inspired algorithms: a case study of Kraft recovery process

被引：0
作者：
Smitarani Pati
Drishti Yadav
Om Prakash Verma
机构：
[1] Dr B R Ambedkar National Institute of Technology Jalandhar,Department of Instrumentation and Control Engineering
来源：
Neural Computing and Applications | 2021年 / 33卷
关键词：
Multiple-stage evaporator; Energy efficiency; Energy reduction schemes; Flash tanks; Nature-inspired algorithms;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This article presents a novel energy management strategy of multiple-stage evaporator (MSE). The maximum efficiency of MSE is achieved by optimum selection of unknown steady-state process parameters such as vapor temperatures and liquor flow rates. Various energy reduction schemes (ERSs) have been integrated to achieve a substantial enhancement in energy efficiency. For energy optimization, a set of nonlinear mathematical models for various ERSs are formulated and transformed to optimization problems. Three nature-inspired algorithms, namely GA, DE and PSO, are employed to compute these optimal process parameters and hence evaluate the energy efficiency. The simulated results accentuate that these algorithms efficiently converge approximately at the same values. The results reveal that the hybrid model with maximum efficiency of 8.24 is characterized as the most energy-efficient operating strategy. The amalgamation of flash tanks with the intention of reutilizing the waste steam further enhances the energy efficiency by 4.97%, thereby proving to be the most prominent operating strategy with the highest efficiency of 8.65.
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页码：10751 / 10770
页数：19
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