Analysis of Thermodynamic Models for Simulation and Optimisation of Organic Rankine Cycles

Durakovic Durakovic,Skaugen Skaugen

doi:10.3390/en12173307

Abstract

Equations of state (EOSs) form the base of every thermodynamic model used in the design of industrial processes, but little work has been done to evaluate these in the context of such models. This work evaluates 13 EOSs for their accuracy, computational time and robustness when used in an in-house optimisation program that finds the maximum power output of an organic Rankine cycle. The EOSs represent popular choices in the industry, such as the simple cubic EOSs, and more complex EOSs such as the ones based on corresponding state principles (CSP). These results were compared with results from using the Groupe Européen de Recherches Gazières (GERG) EOS, whose error is within experimental uncertainty. It appears that the corresponding state EOSs find a solution to the optimisation problem notably faster than GERG without significant loss of accuracy. A corresponding state method which used the Peng–Robinson EOS to calculate the shape factors and a highly accurate EOS for propane as the reference EOS, was shown to have a total deviation of just 0.6% as compared to GERG while also being 10 times as fast. The CSP implementation was also more robust, being able to converge successfully more often.

Highlights

Simulations of thermodynamic systems are necessary in the design of new industrial processes.It is essential that the results of such simulations reflect how the system would perform in reality
We studied the use of several different Equations of state (EOSs) in an optimization problem for organic Rankine cycles, and compared the EOSs on accuracy, time and robustness
It was found that for the purpose of simple cycle modelling and optimisation of the scenario in this work, thermodynamic models based on the corresponding state principle (CSP) using a highly accurate reference equation and a simple 2-parameter cubic EOS for the scaling of mixture properties to the reference property offered a good trade-off: Retaining high accuracy while being both fast and robust

Summary

Introduction

Simulations of thermodynamic systems are necessary in the design of new industrial processes.It is essential that the results of such simulations reflect how the system would perform in reality. In this study we investigate the trade-offs and compromises between computational time, accuracy and robustness on an organic Rankine cycle (ORC) optimisation problem. Thermodynamic models play a major role in simulations of power cycles, little work seems to have been dedicated to investigating how they influence the accuracy, computational time and robustness of the simulation. Of all the studies that were found that investigated equations of state, none studied the robustness of the thermodynamic model when implemented in a simulation tool, nor the time it took to obtain results. They only examined the accuracy of the various thermodynamic models

Methods

Results

Conclusion