Surrogate Models Applied to Optimized Organic Rankine Cycles

• Published in: Energies (Basel) 2021-12, Vol.14 (24), p.8456
• Main Authors: Vilasboas, Icaro Figueiredo, dos Santos, Victor Gabriel Sousa Fagundes, Ribeiro, Armando Sá, da Silva, Julio Augusto Mendes
• Format: Article
• Language: English
• Subjects: Computer applications; Computing time; Configurations; economic; Efficiency; Energy; Flue gas; Fluids; Global optimization; Heat exchangers; Heat transfer; Industrial plants; metamodel; Optimization; organic Rankine cycle; Payback periods; Polynomials; surrogate model; thermodynamic; Turbines; Working fluids
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en14248456

Global optimization of industrial plant configurations using organic Rankine cycles (ORC) to recover heat is becoming attractive nowadays. This kind of optimization requires structural and parametric decisions to be made; the number of variables is usually high, and some of them generate disruptive responses. Surrogate models can be developed to replace the main components of the complex models reducing the computational requirements. This paper aims to create, evaluate, and compare surrogates built to replace a complex thermodynamic-economic code used to indicate the specific cost (US$/kWe) and efficiency of optimized ORCs. The ORCs are optimized under different heat sources conditions in respect to their operational state, configuration, working fluid and thermal fluid, aiming at a minimal specific cost. The costs of 1449.05, 1045.24, and 638.80 US$/kWe and energy efficiencies of 11.1%, 10.9%, and 10.4% were found for 100, 1000, and 50,000 kWt of heat transfer rate at average temperature of 345 °C. The R-square varied from 0.96 to 0.99 while the number of results with error lower than 5% varied from 88% to 75% depending on the surrogate model (random forest or polynomial regression) and output (specific cost or efficiency). The computational time was reduced in more than 99.9% for all surrogates indicated.