Intelligent collaborative attainment of structure configuration and fluid selection for the Organic Rankine cycle

摘要: Abstract The feasibility of a 3D cycle construction method (adding the dimension zeotropic component) for improvement Organic Rankine Cycle (ORC) performance has been proven in previous studies. However, and optimization are difficult both human brain conventional analytical method; therefore, it requires intelligent realization with help computer. Starting from 2D optimization, using ORC as starting point, this paper proposes three-level nested algorithm to attain structure fluid selection intelligently collaboratively. takes net power output objective function employs computational intelligence utilizing an evolution algorithm. Verification is performed data references, followed by case studies pure mixture fluids application scenario liquefied natural gas cold energy recovery. verification results prove reliability relative error 2.5%. show that optimal R116 mixtures R290 R600a mass ratio 53 47. Thermal efficiencies systems 16.89% 26.07%, respectively, which improved compared reference. collaborative attainment achieved proposed algorithm, not only lays foundation construction, but also makes convenient explore better purposes.