دانلود مقاله ISI انگلیسی شماره 96862
ترجمه فارسی عنوان مقاله

تجزیه و تحلیل فرایند و حساسیت هزینه های اگزرژی یک نیروگاه سوخت سلولی سوخت کربن ذوب هیبرید و روند جذب دی اکسید کربن

عنوان انگلیسی
Process development and exergy cost sensitivity analysis of a hybrid molten carbonate fuel cell power plant and carbon dioxide capturing process
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
96862 2017 17 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Power Sources, Volume 364, 1 October 2017, Pages 299-315

پیش نمایش مقاله
پیش نمایش مقاله  تجزیه و تحلیل فرایند و حساسیت هزینه های اگزرژی یک نیروگاه سوخت سلولی سوخت کربن ذوب هیبرید و روند جذب دی اکسید کربن

چکیده انگلیسی

An integrated power plant with a net electrical power output of 3.71 × 105 kW is developed and investigated. The electrical efficiency of the process is found to be 60.1%. The process includes three main sub-systems: molten carbonate fuel cell system, heat recovery section and cryogenic carbon dioxide capturing process. Conventional and advanced exergoeconomic methods are used for analyzing the process. Advanced exergoeconomic analysis is a comprehensive evaluation tool which combines an exergetic approach with economic analysis procedures. With this method, investment and exergy destruction costs of the process components are divided into endogenous/exogenous and avoidable/unavoidable parts. Results of the conventional exergoeconomic analyses demonstrate that the combustion chamber has the largest exergy destruction rate (182 MW) and cost rate (13,100 $/h). Also, the total process cost rate can be decreased by reducing the cost rate of the fuel cell and improving the efficiency of the combustion chamber and heat recovery steam generator. Based on the total avoidable endogenous cost rate, the priority for modification is the heat recovery steam generator, a compressor and a turbine of the power plant, in rank order. A sensitivity analysis is done to investigate the exergoeconomic factor parameters through changing the effective parameter variations.