Multi-Objective Optimization of Organic Rankine Cycle for Low-Grade Waste Heat Recovery

The organic Rankine cycle (ORC) is considered as one of the most viable technology to recover low-grade waste heat. A multi-objective optimization model is established to simultaneously derive the maximum exergy efficiency and the minimum electricity production cost (EPC) of a specific ORC system by employing the genetic algorithm (GA). Evaporation temperature and condensation temperature are selected as decision variables. At first, variations of exergy efficiency and EPC with evaporation temperature and condensation temperature are investigated respectively using R245fa, R245ca, R600, R600a, R601 and R601a as working fluids. Subsequently, a multi-objective optimization is performed and the Pareto frontiers for various working fluids are obtained. Results indicate that performance of the specific ORC system with R245fa as working fluid is better that with other working fluids