Volume : 6, Issue : 3, March - 2017

Optimization of Organic Rankine Cycle for different working fluids operated by low grade waste heat by using Genetic Algorithm

Dharmendra Singh Shekhawat, M. N. Karimi

Abstract :

<p>&nbsp;<b style="text-align: justify;"><span lang="EN-IN" style="font-size:10.0pt;font-family:&quot;Times New Roman&quot;,serif">This research work deals with optimization of Organic Rankine Cycle (ORC) system driven by waste heat using R-11, R-141b and R-245fa as working fluids. Thermodynamic performance analysis has been performed. Design of experiment was performed on Genetic Algorithm. Thermal efficiency and network done of system are maximized and exergy destruction rate of evaporator and overall system are minimized by using Genetic Algorithm. The result shows for same power output of turbine R-11 has maximum mass flow rate. Work output for R-245fa is 104.94% greater than R-11, 57.53% greater than R-141b, work output for R-141b is 30.097% greater than R-11 at optimized point. R-245fa has maximum and R-11 has minimum thermal efficiency at optimized point. Ambient temperature has significant effect on exergy destruction rate of overall system, when ambient temperature is too high then exergy destruction rate of overall system is high. In summer weather conditions, exergy destruction rate exceeds 25% more than the winter conditions. Maximum utilization of exhaust heat is a good way to improve work output of system. Overall result shows that R-245fa is best working fluid for inlet temperature of turbine from 390 K to 425K.</span></b></p> <p class="MsoNormal" style="margin-bottom:0in;margin-bottom:.0001pt;text-align:&#10;justify;text-justify:inter-ideograph;line-height:normal"><b><span lang="EN-IN" style="font-size:10.0pt;font-family:&quot;Times New Roman&quot;,serif"><o:p></o:p></span></b></p>

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Cite This Article:

Dharmendra Singh Shekhawat, M.N.Karimi, Optimization of Organic Rankine Cycle for different working fluids operated by low grade waste heat by using Genetic Algorithm, GLOBAL JOURNAL FOR RESEARCH ANALYSIS : Volume-6, Issue-3, March‾2017


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