Exergy-Based Multi-Objective Optimization of an Organic Rankine Cycle with a Zeotropic Mixture.

Zineb Fergani,Djamel Touil,Tatiana Morosuk

doi:10.3390/e23080954

Abstract

In this paper, the performance of an organic Rankine cycle with a zeotropic mixture as a working fluid was evaluated using exergy-based methods: exergy, exergoeconomic, and exergoenvironmental analyses. The effect of system operation parameters and mixtures on the organic Rankine cycle’s performance was evaluated as well. The considered performances were the following: exergy efficiency, specific cost, and specific environmental effect of the net power generation. A multi-objective optimization approach was applied for parametric optimization. The approach was based on the particle swarm algorithm to find a set of Pareto optimal solutions. One final optimal solution was selected using a decision-making method. The optimization results indicated that the zeotropic mixture of cyclohexane/toluene had a higher thermodynamic and economic performance, while the benzene/toluene zeotropic mixture had the highest environmental performance. Finally, a comparative analysis of zeotropic mixtures and pure fluids was conducted. The organic Rankine cycle with the mixtures as working fluids showed significant improvement in energetic, economic, and environmental performances.

Highlights

The organic Rankine cycle (ORC) has a large potential for electricity generation from heat sources with relatively low temperatures such as geothermal, solar, biomass, and waste industrial heat
The results indicated that zeotropic mixtures showed a higher performance than one-component working fluids
Exergy, exergoeconomic, and exergoenvironmental analyses were applied in order to evaluate the performance of the ORC system using zeotropic mixtures as working fluids

Summary

Introduction

The organic Rankine cycle (ORC) has a large potential for electricity generation from heat sources with relatively low temperatures such as geothermal, solar, biomass, and waste industrial heat. Different aspects of ORCs have been studied intensively. In ORC, the selection of a working fluid is an essential factor that affects the cycle’s performances [1]. For the bibliometric analysis of the state-of-the-art developments in the field of multiobjective optimization applied for ORC, the Scopus database (April 2021) was used with the following algorithm. The initial keyword “ORC” was used with the following equivalents: “Organic Rankine cycle” = “Organic Rankine cycle (ORC)” = “Organic Rankine cycles” = “ORCs”. The only publications were considered if they met the following criteria:

Objectives

Results

Conclusion