The Optimal Evaporation And Condensation Temperatures For Subcritical Organic Rankine Cycle Based On The Multi-objective Function

Organic Rankine cycle (ORC) is one of the most promising technologies ofconverting low grade heat into power. Advantages of using ORC are high efficiency,environment friendly, simple system, and so on. Therefore, it has increasingly attractedattention in the field of energy conversion and utilization in the past several decades. Atpresent, the researches about ORC mainly concentrate on working fluid selection andparameter optimization. However, performance indicator is very important to theselection of the working fluid and parametric optimization for ORC. Therefore, it isnecessary to present a comprehensive review on the research status and development ofthe performance indicator of ORC. It is shown that the single-objective optimizationresults always have some inconformity with the need of actual projects. Theperformance evaluation of ORC often involves multiple indicators from which theoptimization results vary widely. The multi-objective optimization of the ORC whichguides to the optimal design from different aspects seems superior.Based on the survey on the performance indicator of ORC, in this paper, amulti-objective optimization model which incorporates the net power output Wnet,exergy drop of the exhaust fluid from inlet to outlet ΔEg, total exergy destruction rate Iand system total cost C2013into one function is built and solved with the method oflinear weighted evaluation function. Taking pure working fluids R600a, R245fa, R601a,R601, R123, and non-azeotropic mixed working fluids R600a/R601a, R245fa/R601a,R245fa/R601, R600a/R245fa as examples, the evaporation temperature Teandcondensation temperature Tcof subcritical ORC are optimized repspectively. In addition,Teand Tcof subcritical ORC with R245fa and R245fa/R601are optimizedsimultaneously. The results reveal that the optimal point sometimes can not beenobtained using single-objective function, while it always does with multi-objectivefunction. Moreover, the multi-objective optimization of ORC seems superior tosingle-objective optimization, because the multi-objective optimization coordinates therelationships among various performance indicators, which ensures each indicator reachthe optimal point as possible. Additionally, there exists optimal evaporation temperatureTe,optand condensation temperature Tc,optminimizing the multi-objective function F(X)values, but Te,optand Tc,optvary with different working fluids. Not only the comparisonsof the Te,optand Tc,optof pure and mixed working fluids for multi-objective optimizations, but also the comparisons of different single-objective function values and F(X) betweenpure and mixed working fluids under Te,optand Tc,optfor multi-objective optimizationshow that the ORC performance of mixed working fluids is not always better than thatof pure working fluids. Te,optand Tc,optfor R245fa and R245fa/R601are393.15K and328.15K respectively when Teand Tcof ORC are multi-objective optimizedsimultaneously, and Te,optincreases with increasing Tc.