Imperial College London

Dr Andrew J Haslam

Faculty of EngineeringDepartment of Chemical Engineering

Research Fellow



+44 (0)20 7594 5618a.haslam CV




C406Roderic Hill BuildingSouth Kensington Campus






BibTex format

author = {White, MT and Oyewunmi, OA and Haslam, AJ and Markides, CN},
title = {High-efficiency industrial waste-heat recovery through computer-aided integrated working-fluid and ORC system optimisation},
year = {2017}

RIS format (EndNote, RefMan)

AB - In this paper, we develop a mixed-integer non-linear programming optimisation framework that combines working-fluid thermodynamic property predictions from a group-contribution equation of state, SAFT- Mie, with a thermodynamic description of an organic Rankine cycle. In this model, a number of working-fluids are described by their constituent functional groups (i.e., -CH3, -CH2, etc.), and integer optimisation variables are introduced in the description of the structure of the working-fluid. This facilitates combining the computer-aided molecular design of novel working-fluids with the power system optimisation into a single framework, thus removing subjective and pre-emptive screening criteria, and simultaneously moving towards the next generation of tailored working-fluids and optimised organic Rankine cycle systems for industrial waste-heat recovery applications. The thermodynamic model is first validated against an alternative formulation that uses (pseudo-experimental) thermodynamic property predictions from REFPROP, and against an optimisation study taken from the literature. Furthermore, molecular feasibility constraints are defined and validated in order to ensure all feasible working-fluid candidates can be found. Finally, the optimisation problem is formulated using the functional groups from the hydrocarbon family, and applied to three industrial waste-heat recovery case studies. The results demonstrate the potential of this framework to drive the search for the next generation of organic Rankine cycles, and to provide meaningful insights into which working-fluids are the optimal choices for a targeted application.
AU - White,MT
AU - Oyewunmi,OA
AU - Haslam,AJ
AU - Markides,CN
PY - 2017///
TI - High-efficiency industrial waste-heat recovery through computer-aided integrated working-fluid and ORC system optimisation
ER -