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.

Heliothermic technologies are affected by their low density, intermittence and low economic competitiveness. Hybrid solar–waste heat power systems can increase plant conversion efficiency and power generation while reducing intermittence. This study focused on the development of software (AERES) to economically optimize hybrid solar–waste heat power systems in terms of technology selection, sizing, operating conditions and power block characteristics. The technologies considered for algorithm selection were (i) heat exchangers that recover a wide range of waste heat sources, (ii) non-concentrating and concentrating solar collectors (a flat plate, an evacuated tube, a linear Fresnel and a parabolic trough), (iii) organic Rankine cycle power blocks and (iv) storage tanks (direct thermal storage systems). The last two technologies were represented by surrogate models so that a large number of decision variables could be optimized simultaneously. The optimization considered local climate conditions hourly to provide irradiation, local temperature and wind speed. The case studies indicated that optimized ORCs for waste heat recovery are economically competitive, reaching internal rates of return (IRRs) of 44%, 39% and 34% for a waste heat of 50 MWt at 350 °C, 300 °C and 250 °C, respectively. On the other hand, heliothermic technologies were not selected by the algorithm and provided non-competitive results for the analyzed cases.