摘要
针对空冷机组冷端轴流风机能耗大、冷却性能低、机械与电气故障多发问题,研究多性能目标下风机群各分区最优转速求解,对提升空冷机组冷端节能运行水平,降低火电厂能耗有重要意义。该文以660MW机组1×8空冷单元为对象,采用计算流体力学方法,在阶跃和随机输入下求解风机群空气动力场;基于阶跃扰动下风机群动态特性,对风机群聚类分析,并制定分区方案;利用长短期记忆神经网络,在自然风和转速指令双重随机扰动下,构建分布式驱动风机群的非参数动态响应模型;综合考虑风机入口空气流量、电机能耗和机械电气损耗等性能指标,提出一种基于精英策略的非支配排序遗传算法,通过模糊隶属度函数计算各区域风机转速指令的Perato最优解。仿真结果表明,在自然风的随机扰动下,与现有的风机群集中调速策略相比,多目标分区优化控制在显著提高机组冷端运行经济性的同时,降低了调节过程的机械电气损耗。结果可为直接空冷机组的优化节能安全运行提供理论依据和工程参考。
With the problems of high energy consumption,low cooling performance and frequent mechanical and electrical faults of axial-flow fans at the cold-end of air-cooled units,it is of great significance to study the optimal speed solution in each zone of the fans group under multiperformance objectives,so as to improve the energy-saving operation level of the cold-end of air-cooled units and reduce the energy consumption of thermal power plants.Taking 1×8air-cooled units of 660MW unit as object,the aerodynamic field of fans group was numerically solved by using computational fluid dynamics under step and random input.Based on the dynamic characteristics of the fans group under step disturbance,the cluster analysis of the fans group was carried out,and the distribution scheme was formulated.A nonparametric dynamic response model of distributed driven fans under the double random disturbances of natural wind and speed command was constructed with the long short-term memory neural network.Considering the performance indicators such as inlet air flow of fans,motor energy consumption and mechanical and electrical loss,a non-dominated sorting genetic algorithm with the elite strategy was proposed,and the Perato optimal solution of fan speed command in each zone was calculated through fuzzy membership function.Under the random disturbance of natural wind,the simulation results show that the multi-objective distributed optimal control can significantly improve the operational economic performance of the cold-end,meanwhile reduce the mechanical and electrical losses as comparing to the existing fan speed centralized regulation strategy.The research can provide the theoretical basis and engineering references for the energy-saving and safe operation of direct air-cooled units.
作者
杨婷婷
蓝流剑
庄志宝
孙阳
赵天阳
邓慧
YANG Tingting;LAN Liujian;ZHUANG Zhibao;SUN Yang;ZHAO Tianyang;DENG Hui(School of Control and Computer Engineering,North China Electric Power University,Changping District,Beijing 102206,China;Baicheng Power Generation Company,Jilin Electric Power Company Limited,Baicheng 137000,Jilin Province,China;Energy and Electricity Research Center,Jinan University,Zhuhai 519070,Guangdong Province,China)
出处
《中国电机工程学报》
EI
CSCD
北大核心
2022年第S01期204-214,共11页
Proceedings of the CSEE
基金
白城发电公司1号机组空冷岛冷端优化与运行技术研究(410011JX20200024)
关键词
直接空冷机组
分布式控制
随机自然风扰动
长短期记忆网络
多目标优化
direct air-cooled units
distributed control
random natural wind disturbance
long short-term memory neural network
multi-objective optimization
作者简介
杨婷婷(1981),女,工学博士,副教授,研究方向为发电过程建模和优化控制、氮氧化物排放控制,yangtingting@necpu.edu.cn;蓝流剑(1997),男,硕士研究生,研究方向为直接空冷系统建模与运行优化,1787335353@qq.com;通信作者:邓慧(1979),男,工学博士,副教授,研究方向为空冷火电机组建模与优化控制,dengh@jnu.edu.cn。
