A comparative energy and exergy optimization of a supercritical-CO2 Brayton cycle and Organic Rankine Cycle combined system using swarm intelligence algorithms

Guillermo Valencia Ochoa; Jorge Duarte Forero; Jhan Piero Rojas

doi:10.1016/j.heliyon.2020.e04136

A comparative energy and exergy optimization of a supercritical-CO₂ Brayton cycle and Organic Rankine Cycle combined system using swarm intelligence algorithms

Heliyon. 2020 Jun 8;6(6):e04136. doi: 10.1016/j.heliyon.2020.e04136. eCollection 2020 Jun.

Authors

Guillermo Valencia Ochoa¹, Jorge Duarte Forero¹, Jhan Piero Rojas²

Affiliations

¹ Programa de Ingeniería Mecánica, Universidad del Atlántico, Carrera 30 Número 8-49, Puerto Colombia, Barranquilla 080007, Colombia.
² Engineering Faculty, Universidad Francisco de Paula Santander, Avenida Gran Colombia No. 12E-96, Cúcuta 540003, Colombia.

Abstract

This article presents a multivariable optimization of the energy and exergetic performance of a power generation system, which is integrated by a supercritical Brayton Cycle using carbon dioxide, and a Simple Organic Rankine Cycle (SORC) using toluene, with reheater ( $S - C O_{2}^{R H} - S O R C$ ), and without reheater ( $S - C O_{2}^{N R H} - S O R C$ ) using the PSO algorithm. A thermodynamic model of the integrated system was developed from the application of mass, energy and exergy balances to each component, which allowed the calculation of the exergy destroyed a fraction of each equipment, the power generated, the thermal and exergetic efficiency of the system. In addition, through a sensitivity analysis, the effect of the main operational and design variables on thermal efficiency and total exergy destroyed was studied, which were the objective functions selected in the proposed optimization. The results show that the greatest exergy destruction occurs at the thermal source, with a value of 97 kW for the system without Reheater (NRH), but this is reduced by 92.28% for the system with Reheater (RH). In addition, by optimizing the integrated cycle for a particle number of 25, the maximum thermal efficiency of 55.53% (NRH) was achieved, and 56.95% in the RH system. Likewise, for a particle number of 15 and 20 in the PSO algorithm, exergy destruction was minimized to 60.72 kW (NRH) and 112.06 kW (RH), respectively. Comparative analyses of some swarm intelligence optimization algorithms were conducted for the integrated S-CO₂-SORC system, evaluating performance indicators, where the PSO optimization algorithm was favorable in the analyses, guaranteeing that it is the ideal algorithm to solve this case study.

Keywords: Brayton supercritical CO2 cycle; Energy; Energy analysis; Energy conservation; Exergetic analysis; Mathematical optimization; Mechanical engineering; Organic Rankine cycle; Swarm intelligence algorithms; Thermodynamics.