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A comparative energy and exergy optimization of a supercritical-CO2 Brayton cycle and Organic Rankine Cycle combined system using swarm intelligence algorithms

机译:使用群体智能算法的超临界CO2布雷顿循环和有机朗肯周期组合系统的比较能量和漏洞优化

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摘要

This article presents a multivariable optimization of the energy and exergetic performance of a power generation system, which is integrated by a supercritical Brayton Cycle using carbon dioxide, and a Simple Organic Rankine Cycle (SORC) using toluene, with reheater (S−CO2RH−SORC), and without reheater (S−CO2NRH−SORC) using the PSO algorithm. A thermodynamic model of the integrated system was developed from the application of mass, energy and exergy balances to each component, which allowed the calculation of the exergy destroyed a fraction of each equipment, the power generated, the thermal and exergetic efficiency of the system. In addition, through a sensitivity analysis, the effect of the main operational and design variables on thermal efficiency and total exergy destroyed was studied, which were the objective functions selected in the proposed optimization. The results show that the greatest exergy destruction occurs at the thermal source, with a value of 97 kW for the system without Reheater (NRH), but this is reduced by 92.28% for the system with Reheater (RH). In addition, by optimizing the integrated cycle for a particle number of 25, the maximum thermal efficiency of 55.53% (NRH) was achieved, and 56.95% in the RH system. Likewise, for a particle number of 15 and 20 in the PSO algorithm, exergy destruction was minimized to 60.72 kW (NRH) and 112.06 kW (RH), respectively. Comparative analyses of some swarm intelligence optimization algorithms were conducted for the integrated S-CO2-SORC system, evaluating performance indicators, where the PSO optimization algorithm was favorable in the analyses, guaranteeing that it is the ideal algorithm to solve this case study.
机译:本文介绍了能量和发电系统,其通过超临界布雷顿循环使用二氧化碳集成的火用性能,和一个简单的有机兰金循环(SORC)使用甲苯的多变量优化,用再热器(S-CO2RH-SORC ),并且在不再热器(使用PSO算法S-CO2NRH-SORC)。集成系统的热力学模型由质量,能量和有效能平衡的应用,每个组件,这使得有效能的计算毁坏每个设备的一小部分,所产生的功率,所述系统的热和火用效率显影。此外,通过灵敏度分析中,对热效率和破坏总有效能的主要操作和设计变量的影响进行了研究,这是在所提出的优化选择的目标函数。结果表明,最大的有效能的破坏发生在热源,以97千瓦的系统的再热器无(NRH)的值,但是这是由92.28%减少用于与再热器(RH)的系统。此外,通过优化的25粒子数的积分周期,的55.53%的最大热效率(NRH)达到了,而在RH系统56.95%。同样地,对于在PSO算法15和20中的粒子数,有效能破坏分别最小化,以60.72千瓦(NRH)和112.06千瓦(RH)。一些群体智能优化算法比较分析均为一体的S-CO2-SORC系统进行,评估性能指标,其中PSO算法是在分析有利的,保证它是解决这一案例研究理想的算法。

著录项

  • 期刊名称 Heliyon
  • 作者单位
  • 年(卷),期 2020(6),6
  • 年度 2020
  • 页码 e04136
  • 总页数 16
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

    机译:能量;机械工程;热力学;数学优化;节能;群智能算法;布雷顿超临界有限公司;
  • 入库时间 2022-08-21 12:11:08

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