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Exergoeconomic assessment and multi-objective optimization of a solar chimney integrated with waste-to-energy

机译:结合废物转化为能源的太阳能烟囱的能效经济评估和多目标优化

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In this study, an integrated renewable energy system is proposed by integrating Tehran's waste-to-energy plant with a solar chimney power plant. The integration is performed by exploiting warm air of the condensers cooling air for injecting under the turbine of solar chimney power plant. The proposed system is analyzed from energy, exergy, exergoeconomic, and environmental viewpoints through the parametric study. Exergy efficiency, net power output, solar chimney power plant power output, total product cost and cost rates of the system are plotted and compared during the night and daytime. Additionally, influence of the effective parameters is examined on the CO2 emissions indicator. Subsequently, the proposed system is optimized by multi-objective optimization method using a developed MATLAB code based on a genetic algorithm. Four effective design parameters are presumed for multi-objective optimization purpose and exergy efficiency along with total cost rate are considered as the objective functions. Accordingly, a group of the optimal solution points is gathered as a Pareto frontier and the most favorable solution points are ascertained from an exergy/exergoeconomic viewpoints. In addition, a point which is well-balanced between the conflicting objectives is selected as the final solution. Eventually, scatter distribution of the effective parameters are presented to have a better outlook of optimal ranges of the parameters. Results indicate that exergy efficiency of the system is higher during the nighttime while total product cost is lower during the daytime. Results further indicate, turbine inlet pressure has the highest impact on the CO2 emissions and the solar chimney power plant has the highest exergy destruction. Results of the multi-objective optimization demonstrate that at the best solution point, exergy efficiency and total cost rate of the system are 7.56% and 406.8 $/h. Furthermore, analyzing scatter distribution of the effective parameters reveals that higher values of the superheater temperature difference may be a better choice for designing the system.
机译:在这项研究中,通过将德黑兰的垃圾发电厂与太阳能烟囱发电厂整合在一起,提出了一个综合可再生能源系统。通过利用冷凝器的温暖空气,冷却空气注入太阳能烟囱发电厂的涡轮机来进行集成。通过参数研究从能源,火用,能效经济和环境的角度分析了拟议的系统。绘制了火用效率,净功率输出,太阳能烟囱发电厂的功率输出,总产品成本和系统的成本率,并在夜间和白天进行了比较。此外,还要检查有效参数对CO2排放指标的影响。随后,使用已开发的基于遗传算法的MATLAB代码,通过多目标优化方法对提出的系统进行优化。为实现多目标优化目的,假定了四个有效的设计参数,并且将火用效率和总成本率视为目标函数。因此,收集了一组最佳解点作为帕累托边界,并且从(火用)/(人类)经济角度确定了最有利的解点。此外,选择一个在冲突目标之间保持良好平衡的点作为最终解决方案。最终,提出了有效参数的散布分布,以更好地了解参数的最佳范围。结果表明,系统的火用效率在夜间较高,而白天的总产品成本较低。结果进一步表明,涡轮机入口压力对CO2排放的影响最大,而太阳能烟囱发电厂的火用破坏最大。多目标优化的结果表明,在最佳解决方案点,系统的火用效率和总成本率分别为7.56%和406.8 $ / h。此外,分析有效参数的散布分布表明,过热器温度差的较高值可能是设计系统的更好选择。

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