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Moltames, R., Azizimehr, B., Assareh, E.. (1397). Energy and Exergy Efficiency Improvement of a Solar Driven Trigeneration System Using Particle Swarm Optimization Algorithm. , 4(1), 31-39. doi: 10.22059/jser.2019.70905
R. Moltames; B. Azizimehr; E. Assareh. "Energy and Exergy Efficiency Improvement of a Solar Driven Trigeneration System Using Particle Swarm Optimization Algorithm". , 4, 1, 1397, 31-39. doi: 10.22059/jser.2019.70905
Moltames, R., Azizimehr, B., Assareh, E.. (1397). 'Energy and Exergy Efficiency Improvement of a Solar Driven Trigeneration System Using Particle Swarm Optimization Algorithm', , 4(1), pp. 31-39. doi: 10.22059/jser.2019.70905
Moltames, R., Azizimehr, B., Assareh, E.. Energy and Exergy Efficiency Improvement of a Solar Driven Trigeneration System Using Particle Swarm Optimization Algorithm. , 1397; 4(1): 31-39. doi: 10.22059/jser.2019.70905

Energy and Exergy Efficiency Improvement of a Solar Driven Trigeneration System Using Particle Swarm Optimization Algorithm

Journal of Solar Energy Research
مقاله 3، دوره 4، شماره 1، فروردین 2019، صفحه 31-39    اصل مقاله (685.47 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22059/jser.2019.70905
نویسندگان
R. Moltames* 1؛ B. Azizimehr2؛ E. Assareh2
1Energy Engineering Department, Sharif University of Technology, Tehran, Iran
2Mechanical Engineering Department, Dezful Branch, Islamic Azad University, Dezful, Iran
چکیده
In this paper, a solar micro Combined Cooling, Heating, and Power (mCCHP) system based on ORC cycle is thermodynamically and economically analyzed. The model of conservation of mass, energy, and linear momentum is used to energy analysis of the system. On the other hand, a model based on the first and the second laws of the thermodynamics is used to exergy analysis of the system. Sensitivity analysis of the inlet temperature, back turbine pressure, turbine inlet pressure, and evaporator temperature are considered as the decision variables of the optimization algorithm. The performance of the mCCHP system is determined by some important indices including energy efficiency, exergy efficiency, and investment cost rate. Hence, the three mentioned indices are considered as the objective functions of the optimization. The Particle swarm optimization (PSO) algorithm is used for both single-objective and multi-objective optimization of the system and its code is developed in MATLAB software. The implementation of the multi-objective optimization using PSO for R123 working fluid improves 27.65% thermal efficiency, 27.46% exergy efficiency and reduces 11.98% of the system cost rate.
کلیدواژه‌ها
micro CCHP؛ Particle Swarm Optimization؛ organic Rankine cycle؛ Solar energy
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