Set point optimization of controlled Organic Rankine Cycle systems  

作　　者：Jianhua Zhang Mingming Lin Fei Shi Jia Meng Jinliang Xu 

机构地区：[1]State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University [2]School of Control and Computer Engineering, North China Electric Power University [3]The Beijing Key Laboratory of New and Renewable Energy,North China Electric Power University

出　　处：《Chinese Science Bulletin》2014年第33期4397-4404,共8页

基　　金：supported by the National Basic Research Program of China(2011CB710706);the National Natural Science Foundation of China(51210011,61374025)

摘　　要：In this paper, an approach to optimize set points is proposed for controlled Organic Rankine Cycle(ORC)systems. Owing to both disturbances and variations of operating point existing in ORC systems, it is necessary to optimize the set points for controlled ORC systems so as to improve the energy conversion efficiency. At first, the optimal set points of controlled ORC systems are investigated by revisiting performance analysis and optimization of ORC systems. The expected set points of the evaporating pressure and the temperature at evaporator outlet are then determined by combining genetic algorithm with least squares support vector machine(GA-LSSVM). Simulation results show that the predicted results by GA-LSSVM can be regarded as the optimal set points of controlled ORC systems with varying operating conditions.In this paper, an approach to optimize set points is proposed for controlled Organic Rankine Cycle （ORC） systems. Owing to both disturbances and variations of operating point existing in ORC systems, it is necessary to optimize the set points for controlled ORC systems so as to improve the energy conversion efficiency. At first, the optimal set points of controlled ORC systems are investi- gated by revisiting performance analysis and optimization of ORC systems. The expected set points of the evaporating pressure and the temperature at evaporator outlet are then determined by combining genetic algorithm with least squares support vector machine （GA-LSSVM）. Simulation results show that the predicted results by GA-LSSVM can be regarded as the optimal set points of controlled ORC systems with varying operating conditions.

关 键 词：优化设置 循环系统 点控制 定点 最小二乘支持向量机 RC系统 能量转换效率 优化设定 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TK115[自动化与计算机技术—控制科学与工程]