首页> 外文期刊>International journal of hydrogen energy >Optimization of a combined heat and power system based gasification of municipal solid waste of Urmia University student dormitories via ANOVA and taguchi approaches
【24h】

Optimization of a combined heat and power system based gasification of municipal solid waste of Urmia University student dormitories via ANOVA and taguchi approaches

机译:Acova和Taguchi方法优化基于Urmia大学生宿舍的城市固体浪费综合电力系统

获取原文
获取原文并翻译 | 示例
           

摘要

Municipal solid waste (MSW) of Urmia University student dormitories was utilized to trigger a co-generation system. The combined heat and power system consisted of a gasifier, a micro gas turbine, an organic Rankine cycle, a heat exchanger, and a domestic heat recovery. The system performance was validated by comparing the results with experimental results available in the literature. Air, steam, and oxygen were considered as different gasification mediums. Hydrogen content in the case of the steam medium was higher at all gasification temperatures and low moisture contents. However, hydrogen content of the system based oxygen medium was higher at high moisture contents. The system performances from power generation and hot water flow rate viewpoints were assessed versus the MSW flow rate, gasification temperature, pressure ratio, and turbine inlet temperature. Taguchi approach was employed to optimize the generated power in air, steam, and oxygen medium cases. The optimum conditions were the same for all cases. The optimum powers were 281.1 kW, 279.4 kW, and 266.9 kW for the system based steam, air, and oxygen gasifying agents, respectively. (c) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
机译:利用乌利亚大学学生宿舍的市政固体废物(MSW)触发了同一制度。组合的热量和动力系统包括气化器,微燃气轮机,有机朗肯循环,热交换器和国内热回收。通过将结果与文献中可用的实验结果进行比较来验证系统性能。空气,蒸汽和氧被认为是不同的气化介质。在所有气化温度和低水分含量的情况下,蒸汽介质的氢含量较高。然而,高水分含量的基于系统的氧培养基的氢含量较高。评估来自发电和热水流量观点的系统性能与MSW流速,气化温度,压力比和涡轮机入口温度相比。使用Taguchi方法来优化空气,蒸汽和氧气筛例中的产生功率。所有病例的最佳条件都是相同的。基于系统的蒸汽,空气和氧气气化剂分别为281.1kW,279.4kW和266.9kW。 (c)2020氢能源出版物LLC。 elsevier有限公司出版。保留所有权利。

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