scholarly journals Parametric Optimization of Regenerative Organic Rankine Cycle System for Diesel Engine Based on Particle Swarm Optimization

Energies ◽  
2015 ◽  
Vol 8 (9) ◽  
pp. 9751-9776 ◽  
Author(s):  
Hongjin Wang ◽  
Hongguang Zhang ◽  
Fubin Yang ◽  
Songsong Song ◽  
Ying Chang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Diesel Engine ◽  
Parametric Optimization ◽  
Particle Swarm ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Swarm Optimization ◽  
Cycle System

Comparative Analysis of Intelligence Optimization Algorithms in the Thermo-Economic Performance of an Energy Recovery System Based on Organic Rankine Cycle

2021 ◽  
Vol 143 (11) ◽  
Author(s):  
Jorge Duarte-Forero ◽  
Luis Obregón-Quiñones ◽  
Guillermo Valencia-Ochoa
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Recovery ◽  
Particle Swarm ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Absolute Error ◽  
Swarm Optimization ◽  
Energy Recovery System ◽  
Squared Error ◽  
Recovery System

Abstract This paper compares the performance of a group of intelligent algorithms such as the genetic algorithm (GA), particle swarm optimization (PSO), and repulsive particle swarm optimization (RPSO) based on the optimization of thermo-economic indicators such as the payback period (PBP), the levelized energy cost (LEC), the specific investment cost (SIC), and also in the optimization of the thermodynamic process (net power output) of an energy recovery system in a 2 MW natural gas internal combustion engine based on an organic Rankine cycle. Four parameters were considered to analyze and compare the performance of these algorithms: integral of squared error (ISE), integral of absolute error (IAE), integral of time-weighted absolute error (ITAE), and the integral of time-weighted squared error (ITSE). Analyses of variances (ANOVA) were proposed for each of the parameters studied. The PSO and RPSO algorithms presented the best performance in terms of the mean and the standard deviation of the ISE, IAE, ITAE, and ITSE parameters. Significant differences were not found between the three algorithms in terms of the parameters considered. However, significant differences did exist when comparing groups (pairs) of algorithms considering a significance level of 5%. The ANOVA analysis showed that ITAE was the most affected parameter by population size, while the IAE and ITSE parameters were the less affected. In the optimization, the PSO algorithm obtained the best performance in terms of convergence with values of 0.1110 USD/kWh (LCOE), 4.6971 years (PBP), 1114 USD/kWh (SIC), and 173.64 kW (Wnet). PSO-based algorithms obtained better performance in computational terms compared with the genetic algorithms.

Study on the Performance of the Organic Rankine Cycle System with Internal Heat Exchanger under Vehicle Engine Various Operating Conditions

2013 ◽  
Vol 856 ◽  
pp. 349-356 ◽  
Author(s):  
Kai Yang ◽  
Hong Guang Zhang ◽  
Zhen Wang ◽  
Jian Zhang ◽  
Fu Bin Yang ◽  
...  
Keyword(s):  
Heat Exchanger ◽  
Diesel Engine ◽  
High Speed ◽  
Organic Rankine Cycle ◽  
Internal Heat ◽  
Rankine Cycle ◽  
Operating Conditions ◽  
Combined System ◽  
Cycle System ◽  
Internal Heat Exchanger

Through experiment, the variation of the exhaust energy of the vehicle diesel engine is studied, a set of vehicle diesel engine-organic Rankine cycle (ORC) combined system with internal heat exchanger (IHE) is designed, the zeotropic mixtures R416A is used as the working fluids for the ORC system with IHE, by theoretical analysis and numerical calculation, the variation of the vehicle diesel engine-ORC combined system with IHE under entire operating conditions of the diesel engine is studied, the calculation results show that, when engine is operating at high speed and high torque, the performance of the vehicle diesel engine-ORC combined system with IHE is higher.

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