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Optimal Sizing, Operation and Sensitivity Analysis of CCHP System Based on Fuel Cell Prime Mover for a Typical Building
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Mohammad Sadegh Gazizadeh   , Adel Gholami * , SayedJavad MirrezaiRoudaki |
| , gholamiadel7@gmail.com |
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Abstract: (20790 Views) |
| Recently, energy issues and global warming have gained serious attentions all around the world. In this regard, using renewable energy options are of great importance. Among numerous options, tri-generation systems with fuel cell can be a good candidate for this unique purpose. Trigeneration means to produce cooling, heating and power simultaneously with one source of input energy. The importance of using Tri-generation systems are both higher efficiency and lower environmental impacts. They can be used widespread in residential applications though. Tri-generation prime movers can be internal combustion engine, micro turbines, fuel cells or sterling engine. Among these various prime movers, fuel cellsare the best option due to their high efficiency, low pollution and high reliability. In this paper, by using an economic analysis the size and operation of the required fuel cell for the specific electricity, cooling and heating load of a typical building located in Tehran, Iran are selected. To carry out this analysis, an objective function has been introduced and maximized using developed mixed integer nonlinear method. The operation strategy and the payback period of the chosen system are also determined in this study. In addition, the results end up with finding an optimal capacity, optimal chiller capacity. The results show that using fuel cell is not economical now but for afuture by considering the cost of environmental impact it will be the best option. Finally, the sensitivity analysis is performed by changes in fuel cost, electricity cost and investment cost. The results show that theses parameters have significant effects on the system performance. |
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| Keywords: CCHP, Optimization, Fuel Cell, Environmental Impacts, Sensitivity Analysis |
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Full-Text [PDF 1234 kb]
(2243 Downloads)
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Type of Study: Research |
Subject:
Energy Planning Models
Received: 2011/12/29 | Published: 2011/07/15
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