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基于絮凝与滤池协同模型的沉后目标浊度节能优化研究

Research on Energy-saving Optimization of Target Turbidity after Sedimentation Based on Flocculation and Filter Collaborative Model
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摘要 在传统水厂运营模式中,沉淀后目标浊度的设定多依赖于经验判断,未能充分考量成本效益之间的关联与平衡。为了突破这一局限,提出了絮凝与滤池协同控制的优化节能模型,该模型融合了絮凝过程中复杂的药剂投加控制策略与滤池高效反冲洗优化机制,以水厂整体运营成本最低为目标,得到精准的水厂沉后目标浊度方案。以舟山某水厂为例,应用该模型后,在不同进水浊度下,得到不同的最经济沉后目标浊度,与水厂现行经验控制的沉后目标浊度实际运行情况相比较,年度能耗费用节省约26.5万元。 In the traditional water plant operation mode,the setting of the target turbidity after sedimentation mostly relies on empirical judgment,failing to fully consider the correlation and balance between cost and benefit.In order to break through this limitation,this paper innovatively puts forward the optimization model of flocculation and filtration,which deeply integrates the complex pharmaceutical dosage control strategy in the flocculation process and the efficient backwashing optimization mechanism in the filtration process,and aims at the lowest overall operation cost of the water plant,so as to get the precise and economic solution for setting the target turbidity after sedimentation.Zhoushan,a water plant as an example,after the application of the model,in different influent turbidity,set a different most economic after-sinking target turbidity,and the water plant’s current empirical control of the after-sinking target turbidity of the actual operation of the water plant,the annual energy cost savings of about 265000yuan.
作者 张孝洪 黄盼盼 王璐佳 郑雯 张卫平 于俊锋 王江霞 柳景青 ZHANG Xiaohong;HUANG Panpan;WANG Lujia;ZHENG Wen;ZHANG Weiping;YU Junfeng;WANG Jiangxia;LIU Jingqing(Zhoushan Water Co.,Ltd.,Zhoushan 316000,China;Binhai Industrial Technology Research Institute,Zhejiang University,Tianjin 300457,China;Northwestern Polytechnical University,Xi’an 710068,China;Tianjin Zhiyun Water Technology Co.,Ltd.,Tianjin 300301,China;Zhejiang University,Hangzhou 310000,China)
出处 《给水排水》 北大核心 2025年第1期160-165,共6页 Water & Wastewater Engineering
关键词 絮凝加药 滤池反冲洗 协同控制 沉后目标浊度 节能优化 Flocculation and dosing Filter backwash Cooperative control Target turbidity after sedimentation Energy conservation optimization
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