School of Computer and Information, Qiannan Normal University for Nationalities, Duyun, Guizhou, 558000, China; School of Electronics and Information Engineering, Ankang University, Ankang, China; Institute for Big Data Analytics and Artifcial Intelligence (IBDAAI), Universiti Teknologi MARA, Shah Alam, Selangor, 40450, Malaysia.
Department of Computer Science, College of Computer Engineering and Sciences in Al-Kharj, Prince Sattam Bin Abdulaziz University, P.O. Box 151, Al-Kharj 11942, Saudi Arabia.
Chemosphere. 2023 Oct;338:139371. doi: 10.1016/j.chemosphere.2023.139371. Epub 2023 Jul 11.
Combined cooling, heating and power (CCHP) is one of methods for enhancing the efficiency of the energy conversion systems. In this study a CCHP system consisting of a gas turbin (GT) as the topping cycle, and an organic Rankine cycle (ORC) associated with double-effect absorbtion chiller (DEACH) is decisioned as the bottoming cycle to recover the waste heat from GT exhaust gas. The considered CCHP system is investigated to maintain electricity, heating and cooling demand of a town. A parametric study is investigated and the effect decision variables on the performance indicators including exergy efficiency, total cost rate (TCR), cooling capacity, and ORC power generation is examined. Decision variables of the ORC system consist of HRVG pressure, and condenser pressure and the DEACH including evaporator pressure, condseser pressure, concentration of the concentrated solution, concentration of the weak solution, and solution mass flow rate. Finally a multi-objective optimization performed using Genetic Algorithm (GA) and the optimal design point is selected. It is observed at the optimum point the exergy efficiency, TCR, and sustainability index are 17.56%, 74.49 $/h, and 1.21, respectively.
联合供冷、供热和发电 (CCHP) 是提高能源转换系统效率的方法之一。在本研究中,选择了由燃气轮机 (GT) 作为 topping 循环和与双效吸收式制冷机 (DEACH) 相关的有机朗肯循环 (ORC) 组成的 CCHP 系统作为底部循环,以回收 GT 废气中的余热。所考虑的 CCHP 系统用于满足城镇的电力、供热和制冷需求。进行了参数研究,并考察了决策变量对包括火用效率、总费用率 (TCR)、制冷量和 ORC 发电量在内的性能指标的影响。ORC 系统的决策变量包括 HRVG 压力和冷凝器压力,以及 DEACH 的蒸发器压力、冷凝器压力、浓缩溶液的浓度、稀溶液的浓度和溶液质量流量。最后,使用遗传算法 (GA) 进行了多目标优化,并选择了最优设计点。在最优点观察到的火用效率、TCR 和可持续性指数分别为 17.56%、74.49 美元/小时和 1.21。