scholarly journals Organic Rankine Cycle for Energy Recovery System

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5253
Author(s):  
Andrea De Pascale
Keyword(s):  
Energy Recovery ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Energy Recovery System ◽  
Recovery System

This book contains the successful invited submissions [...]

Study of Energy Recovery System Based on Organic Rankine Cycle for Hydraulic Retarder

2016 ◽  
Author(s):  
Li Zhou ◽  
Gangfeng Tan ◽  
Xuexun Guo ◽  
Ming Chen ◽  
Kangping Ji ◽  
...  
Keyword(s):  
Energy Recovery ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Energy Recovery System ◽  
Recovery System ◽  
Hydraulic Retarder

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.

scholarly journals Racer: The Contractor’s View

1984 ◽  
Author(s):  
John T. Halkola
Keyword(s):  
Research And Development ◽  
Energy Recovery ◽  
Development Program ◽  
Rankine Cycle ◽  
Preliminary Design ◽  
Design Phase ◽  
Major Research ◽  
Technical Feasibility ◽  
Energy Recovery System ◽  
Recovery System

The RACER (RAnkine Cycle Energy Recovery) system has progressed from a technical feasibility investigation, through a competitive preliminary design phase and is now a major research and development program. Transition to a specific ship application is becoming more likely as milestones are accomplished. There are several views of any program: the sponsor’s, the contractor’s, the test facility’s and the ultimate user’s. This paper summarizes the contractor’s view.

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