Exergoeconomic analysis and multi objective optimization of a solar based integrated energy system for hydrogen production
| Autor: | Hadi Ganjehsarabi, Parisa Heidarnejad, Shoaib Khanmohammadi, Nader Javani |
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| Rok vydání: | 2017 |
| Předmět: |
Organic Rankine cycle
Renewable Energy Sustainability and the Environment business.industry 020209 energy Nuclear engineering Cooling load Energy Engineering and Power Technology Thermodynamics 02 engineering and technology 021001 nanoscience & nanotechnology Condensed Matter Physics Cooling capacity Multi-objective optimization Renewable energy Fuel Technology Electricity generation 0202 electrical engineering electronic engineering information engineering Exergy efficiency Mass flow rate Environmental science 0210 nano-technology business |
| Zdroj: | International Journal of Hydrogen Energy. 42:21443-21453 |
| ISSN: | 0360-3199 |
| DOI: | 10.1016/j.ijhydene.2017.02.105 |
| Popis: | In the current study, an integrated renewable based energy system consisting of a solar flat plate collector is employed to generate electricity while providing cooling load and hydrogen. A parametric study is carried out in order to determine the main design parameters and their effects on the objective functions of the system. The outlet temperature of generator, inlet temperature to organic Rankine cycle turbine, solar irradiation intensity ( I ) , collector mass flow rate ( m ˙ c o l ) and flat plate collector area ( A P ) are considered as five decision variables. The results of parametric study show that the variation of collector mass flow rate between 3 kg/s and 8 kg/s has different effects on exergy efficiency and total cost rate of the system. In addition, the result shows that increment of inlet temperature to the ORC evaporator has a negative effect on cooling capacity of the system. It can lead to a decrease the cooling capacity from 44.29 kW to 22.6 kW, while the electricity generation and hydrogen production rate of the system increase. Therefore, a multi objective optimization is performed in order to introduce the optimal design conditions based on an evolutionary genetic algorithm. Optimization results show that exergy efficiency of the system can be enhanced from 1.72% to 3.2% and simultaneously the cost of the system can increase from 19.59 $/h to 22.28 $/h in optimal states. |
| Databáze: | OpenAIRE |
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