| With the rapid development of economy, the demand of energy is growing quickly, which has made the conflict of energy problem and environmental problem much larger. Using Organic Rankine Cycle (ORC) system recover low temperature waste heat has many advantages, such as improving the utilization rate of energy, reducing pollution emissions and the cost of industrial. So it has widely attention by scholars at home and abroad in recent years.Actually, the low temperature heat source is unstable in nature, and the environment outside is changed all the time. This causes changes of the ORC system working condition and effects the performance of ORC system greatly. In order to obtain the maximization of the output power and the overall efficiency of system, controlled variables should be adjusted tracking the changing of the ORC system working condition.This article firstly analyzed the ORC system structure, and searched the performance evaluation target based on summaries of each unit energy consumption. Secondly, based on the ASPEN HYSYS software, the ORC system model mainly contained the evaporator, the condenser, the expansion machine and the refrigerant pump was built in this paper. Based on given working conditions, system performance was studied by regulating system parameters and the reasons were analyzed. At last, two operation optimization strategies of ORC system for the purpose to obtain the best system output power and maximize the overall system efficiency goals were proposed in this paper. In the first strategy which based on Support Vector Machine (SVM), the simulation results showed the controlled variables evaporating pressure set points were exactly optimized as well as in the improved strategy based on Genetic Algorithm-Least Squares Support Vector Machine (GA-LS-SVM) while the ORC system working condition was changing. However, by comparing the simulation results,the GA-LS-SVM strategy showed higher prediction accuracy than the other one. |
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