scholarly journals Multi-objective thermo-economic optimization of biomass retrofit for an existing solar organic Rankine cycle power plant based on NSGA-II

2020 ◽  
Vol 6 ◽  
pp. 136-145 ◽  
Author(s):  
Joseph Oyekale ◽  
Mario Petrollese ◽  
Giorgio Cau
Keyword(s):  
Power Plant ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Economic Optimization ◽  
Nsga Ii ◽  
Multi Objective

scholarly journals Multi-objective analysis of an influence of a brine mineralization on an optimal evaporation temperature in ORC power plant

2018 ◽  
Vol 70 ◽  
pp. 01005 ◽  
Author(s):  
Marcin Jankowski ◽  
Sławomir Wiśniewski ◽  
Aleksandra Borsukiewicz
Keyword(s):  
Power Plant ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Electricity Production ◽  
Working Fluid ◽  
Low Grade ◽  
Multi Objective ◽  
Evaporation Temperature ◽  
Cycle System ◽  
Low Grade Heat

The fact that Organic Rankine cycle system is very promising technology in terms of electricity production using low grade heat sources, necessitates constant research in order to determine the best cycle configuration or choose the most suitable working fluid for certain application. In this paper, multi-objective optimization (MOO) approach has been applied in order to conduct an analysis that is to resolve if there is an influence of a mineralization of a geothermal water on an optimal evaporation temperature in ORC power plant with R1234yf as the working fluid.

scholarly journals An oppositional Salp Swarm: Jaya algorithm for thermal design optimization of an Organic Rankine Cycle

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Mert Sinan Turgut ◽  
Oguz Emrah Turgut
Keyword(s):  
Optimization Problems ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Thermal Design ◽  
Design Parameters ◽  
Nsga Ii ◽  
Multi Objective ◽  
Specific Investment ◽  
Weighted Sum Method ◽  
Pareto Curve

AbstractThis study proposes a hybrid metaheuristic algorithm to tackle both single and multi objective optimization problems that are subjected to hard constraints. Twenty-four single objective optimization benchmark problems comprising unimodal and multi modal test functions have been solved by the proposed hybrid algorithm (OPSSAJ) and numerical results have been compared with those acquired by some of the new emerged metaheuristic optimizers. The proposed OPSSAJ shows a significant accuracy and robustness in most of the cases and proves its efficiency in solving high dimensional problems. As a real-world case study, seventeen operational design parameters of an organic rankine cycle (ORC) operating with a binary mixture of R227EA and R600 refrigerants are optimized by the proposed hybrid OPSSAJ to obtain the optimum values of contradicting dual objectives of second law efficiency and Specific Investment Cost. A Pareto curve composed of non-dominated solutions is constructed through the weighted sum method and the final solution is chosen by the reputed TOPSIS decision-maker. The pareto curve and best-compromising result obtained by utilizing the OPPSAJ are compared with that of acquired by using nondominated sorting genetic algorithm II (NSGA-II) and multiple objective particle swarm optimization (MOPSO) algorithms. The multi-objective ORC design obtained with the OPSSAJ yields a significant improvement in thermal efficiency and cost values compared to designs found by the NSGA-II and MOPSO algorithms. Furthermore, a sensitivity analysis is performed to observe the influences of the selected design variables on problem objectives.

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