• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International journal of green energy >Performance optimization of multiple stage evaporator using interior-point method and metaheuristic approaches in environment of real-time plant complexities
【24h】

Performance optimization of multiple stage evaporator using interior-point method and metaheuristic approaches in environment of real-time plant complexities

机译：利用内部点法的多阶段蒸发器的性能优化和实时植物复杂环境中的成分培养方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper aims to maximize the energy efficiency of Multiple Stage Evaporator (MSE) to increase the solid concentration of the black liquor in the Kraft recovery process. The incorporation of different energy reduction schemes ensures a considerable magnification in energy efficiency, which is realized by developing a set of nonlinear energy models of the MSE. These models are optimized to attain the optimum process parameters that estimate the optimum energy efficiency in Steam Economic (SE) and Steam Consumption (SC). The formulated optimization problems are efficiently solved using three novel approaches, Interior Point Method, Particle Swarm Optimization, and Artificial Electric Field Algorithm. With these algorithms' advent, the obtained results are approaching efficient outcomes (SE increased by 77.58% and SC decreased by 26.99% compared to real-time plant data). Further, the present work investigates the influence of Boiling Point Elevation and Fouling's effect on energy efficiency, which causes a reduction in SE (7.189). Finally, this study extends up to utilizing the waste steam as a heat source, collected from the condensate to accelerate the evaporation process, enhancing the SE by 2.94%.
机译：本文旨在最大化多级蒸发器（MSE）的能量效率，以增加牛皮纸回收过程中黑液的固体浓度。结合不同的能量减少方案确保了能效的相当大的放大率，这是通过开发MSE的一组非线性能量模型来实现的。这些模型经过优化，以获得最佳过程参数，该参数估计蒸汽经济（SE）和蒸汽消耗（SC）中的最佳能量效率。使用三种新方法，内部点法，粒子群优化和人工电场算法有效地解决了配制的优化问题。通过这些算法的出现，获得的结果接近有效的结果（SE增加77.58％，并且SC与实时植物数据相比减少了26.99％）。此外，本作研究调查了沸点高度和结垢对能效影响的影响，这导致SE的减少（7.189）。最后，该研究延伸到利用废气作为热源，从冷凝物收集以加速蒸发过程，增强SE 2.94％。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号