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| 基于GWO-BP神经网络算法的WFGD系统在线优化 | |
| 引用本文： | 王涛,任少君,司风琪,马利君,王力光. 基于GWO-BP神经网络算法的WFGD系统在线优化[J]. 发电设备, 2021, 35(2): 122-130 |
| 作者姓名： | 王涛 任少君 司风琪 马利君 王力光 |
| 作者单位： | 东南大学能源热转换及其过程测控教育部重点实验室,南京210096;大唐环境产业集团股份有限公司特许经营分公司,南京210096 |
| 摘 要： | 以浆液循环泵运行情况作为工况划分条件,通过提出的灰狼优化(GWO)-BP神经网络(GWO-BP神经网络)算法建立了针对湿法烟气脱硫(WFGD)系统多模态在线优化模型组,分析了机组负荷、入口SO2质量浓度对出口SO2质量浓度变化量的影响,并利用某660 MW机组切换试验对该模型组性能进行验证.结果 表明:随着机组负荷和入... |
| 关 键 词： | 湿法烟气脱硫 浆液循环泵 BP神经网络 GWO算法 |
Online Optimization of a WFGD System Based on GWO-BP Neural Network Algorithm |
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| Wang Tao,Ren Shaojun,Si Fengqi,Ma Lijun,Wang Liguang. Online Optimization of a WFGD System Based on GWO-BP Neural Network Algorithm[J]. Power Equipment, 2021, 35(2): 122-130 | |
| Authors: | Wang Tao Ren Shaojun Si Fengqi Ma Lijun Wang Liguang |
| Affiliation: | (Key Laboratory of Energy Thermal Conversion and Control,Ministry of Education,Southeast University,Nanjing 210096,China;Franchise Branch of Datang Environmental Industry Group Co.,Ltd.,Nanjing 210096,China) |
| Abstract: | Based on operation conditions of slurry circulation pumps,a group of multi-modality models were established for online optimization of a wet flue gas desulfurization(WFGD)system by the grey wolf-optimized BP(GWO-BP)neural network algorithm proposed,and subsequently the effects of the following factors on the variation of outlet SO2 concentration were analyzed,such as the unit load and inlet SO2 concentration,etc.In addition,the performance of the group of models was verified through the switching test of a 660 MW unit.Results show that with the increase of unit load and inlet SO2 concentration,the change of outlet SO2 concentration increases after switching the pump,indicating high prediction accuracy and strong generalization ability of the group of models. |
| Keywords: | WFGD slurry circulation pump BP neural network GWO algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |