Working fluid selection for organic Rankine cycles – Impact of uncertainty of fluid properties. (15th August 2016)

• Record Type: Journal Article
• Authors: Frutiger, Jérôme; Andreasen, Jesper; Liu, Wei; Spliethoff, Hartmut; Haglind, Fredrik; Abildskov, Jens; Sin, Gürkan
• Is Part Of: Energy. Volume 109(2016)
• Page Start: 987
• Page End: 997
• Publication Date: 2016-08-15
• Subjects: Working fluid -- Organic Rankine cycle -- Uncertainty analysis -- Monte Carlo procedure -- Property data -- Screening; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.05.010
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This study presents a generic methodology to select working fluids for ORC (Organic Rankine Cycles) taking into account property uncertainties of the working fluids. A Monte Carlo procedure is described as a tool to propagate the influence of the input uncertainty of the fluid parameters on the ORC model output, and provides the 95%-confidence interval of the net power output with respect to the fluid property uncertainties. The methodology has been applied to a molecular design problem for an ORC using a low-temperature heat source and consisted of the following four parts: 1) formulation of process models and constraints 2) selection of property models, i.e. Peng–Robinson equation of state 3) screening of 1965 possible working fluid candidates including identification of optimal process parameters based on Monte Carlo sampling 4) propagating uncertainty of fluid parameters to the ORC net power output. The net power outputs of all the feasible working fluids were ranked including their uncertainties. The method could propagate and quantify the input property uncertainty of the fluid property parameters to the ORC model, giving an additional dimension to the fluid selection process. In the given analysis 15 fluids had an improved performance compared to the base case working fluid. Highlights: Monte Carlo procedure to propagate fluid property uncertainty to the power cycle output. Modeling framework to screen 1965 organic Rankine cycle working fluids. Uncertainty analysis with respect to input property uncertainty for all feasible compounds. Uncertainties of fluid properties results in a distribution function of net power output. Property uncertainty depicted in logPh- and Ts-diagram.