DOI: 10.1016/j.watres.2018.11.021
Scopus记录号: 2-s2.0-85056703569
论文题名: Real-time prediction of rain-impacted sewage flow for on-line control of chemical dosing in sewers
作者: Li J. ; Sharma K. ; Liu Y. ; Jiang G. ; Yuan Z.
刊名: Water Research
ISSN: 431354
出版年: 2019
起始页码: 311
结束页码: 321
语种: 英语
英文关键词: ARX
; Chemical dosing
; Flow rate
; Prediction
; Rainfall
; Sewer
Scopus关键词: Corrosion
; Cost effectiveness
; Flow rate
; Rain
; Sewage
; Sewers
; Sulfur compounds
; Auto regressive models
; Autoregressive with exogenous inputs
; Calibrated model
; Chemical dosing
; Climatic conditions
; Hydraulic characteristic
; Real-time prediction
; Sewage pumping station
; Forecasting
; hydrogen sulfide
; rain
; calibration
; chemical method
; optimization
; prediction
; pumping
; rainfall
; real time
; sewage
; sewer network
; Article
; climate
; flow rate
; online monitoring
; prediction
; priority journal
; sewage
; sewer
; weather
英文摘要: Chemical dosing is a commonly used strategy for mitigating sewer corrosion and odour problems caused by sulfide production. Prediction of sewage flow variation in real-time is critical for the optimization of chemical dosing to achieve cost-effective mitigation of hydrogen sulfide (H 2 S). Autoregressive (AR) models have previously been used for real-time sewage prediction. However, the prediction showed significant delays in wet weather conditions. In this paper, autoregressive with exogenous inputs (ARX) models are employed to reduce the delays with rainfall data used as model inputs. The model is applied to predicting sewage flows at two real-life sewage pumping stations (SPSs) with different hydraulic characteristics and climatic conditions. The calibrated models were capable of predicting flow rates in both cases, much more accurately than previously developed AR models under wet weather conditions. Simulation of on-line chemical dosing control based on the predicted flows showed excellent sulfide mitigation performance at reduced cost. © 2018 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/122153
Appears in Collections: 气候变化事实与影响
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作者单位: Advanced Water Management Centre, The University of Queensland, Building 60, Research Road, St. Lucia, Brisbane, QLD 4072, Australia; School of Automation Science & Engineering, South China University of Technology, Wushang Road, Guang Zhou, 510640, China
Recommended Citation:
Li J.,Sharma K.,Liu Y.,et al. Real-time prediction of rain-impacted sewage flow for on-line control of chemical dosing in sewers[J]. Water Research,2019-01-01