Techno-Economic Optimization of a Low-Temperature Organic Rankine System Driven by Multiple Heat Sources

This study presents the optimization of organic Rankine cycle (ORC) which utilizes low temperature waste heat from aluminum production process and two renewable energy sources, solar thermal geothermal energy. As is present at lower level compared to other separate ORC cycles are considered. Optimization proposed system performed based on a non-linear programming (NLP) formulation by maximizing thermodynamic economic performance system. The main variables considered in model include temperature, pressure, flowrate, mass enthalpy, flows all streams To optimize system, correlations were developed, formulated as NLP models optimized minimizing sum least squares. results show that most generated power output can be provided heat, while lowest due relatively average irradiance location. When monthly time periods considered, highest electricity working fluid R1245fa June, amounts 830.4 kW 246.5 149.4 economically feasible for three studied fluids discount rates 2% higher. final conclusions indicate utilizing energy, generate more sustainable way.