遗传算法在火电机组冷端系统优化中的应用  

Application of genetic algorithm in cold end system optimization for thermal power plants

作　　者：李千军[1] 刘光耀 赵全斌[3] 巨林仓[3] 种道彤[3] LI Yuan 

机构地区：[1]广东电网公司电力科学研究院,广东广州510080 [2]华电电力科学研究院,浙江杭州310030 [3]西安交通大学动力工程多相流国家重点实验室,陕西西安710049

出　　处：《热力发电》2014年第1期21-25,共5页Thermal Power Generation

基　　金：国家科技支撑计划(2011BAA04B03)~~

摘　　要：针对火电机组冷端系统的影响因素进行全面的分析,获得以供电煤耗率最小为目标函数,以循环水流量、循环水温度、凝汽器过冷度、凝汽器结垢、漏空气等客观条件为变量的优化模型。运用遗传算法对机组多因素进行了优化,得到最小煤耗及其对应的各参数优化条件。通过比较发现运用遗传算法不仅能快速准确地对冷端系统进行优化,而且还能通过参数的自动调整对由于某些参数缺陷所造成的经济性下降进行补偿,以获得最佳的运行方式,实现最大的经济效益。Systematical analysis on factors affecting the cold end system was conducted. 1 ne opu- mization model was obtained,which regarded the minimum coal consumption rate as the target function,used several objective conditions as the variables, such as flow and temperature of the circulating water,sub-cooling degree of the condenser, fouling and air leakage in the condenser. Genetic algorithm was employed to optimize the multiple factors, and the optimization conditions for the minimum coal consumption rate and the corresponding parameters were obtained. Compar- ison indicated that this genetic algorithm not only can optimize the cold end system quickly and accurately, but also can compensate the economic efficiency drop that caused by defects of some parameters through automatic adjustment of the parameters.

关 键 词：遗传算法 循环水温度 凝汽器 传热系数 最小循环水流量 供电煤耗率 

分 类 号：TK264.1[动力工程及工程热物理—动力机械及工程]