Real-time multistep prediction of sewer flow for online chemical dosing control

Chen, Jindong, Ganigue, Ramon, Liu, Yiqi and Yuan, Zhiguo (2014) Real-time multistep prediction of sewer flow for online chemical dosing control. Journal of Environmental Engineering, 140 11: 04014037.1-04014037.9. doi:10.1061/(ASCE)EE.1943-7870.0000860

Author Chen, Jindong
Ganigue, Ramon
Liu, Yiqi
Yuan, Zhiguo
Title Real-time multistep prediction of sewer flow for online chemical dosing control
Journal name Journal of Environmental Engineering   Check publisher's open access policy
ISSN 0733-9372
Publication date 2014-11-01
Year available 2014
Sub-type Article (original research)
DOI 10.1061/(ASCE)EE.1943-7870.0000860
Open Access Status
Volume 140
Issue 11
Start page 04014037.1
End page 04014037.9
Total pages 9
Place of publication Reston, VA United States
Publisher American Society of Civil Engineers
Collection year 2015
Language eng
Abstract Chemical dosing is the most common strategy for sulfide control in sewers. Recent research has shown that online control of chemical dosing can significantly reduce dosing costs, while achieving better control performance. One of the bottlenecks of online control is the prediction of sewage retention time in sewers, governed by future sewage flows. This study developed a methodology for real-time future flow prediction in sewers based on autoregressive moving average (ARMA) models and multistep iterative prediction. This methodology was validated with flow data collected from two pumping stations with different flow characteristics and different wet-well storage capacities. The results showed that the proposed methodology was capable of predicting future flow rates with good accuracy under different weather conditions. Online control of chemical dosing with real-time sewer flow prediction was tested through a simulation study. Results showed that future flow prediction improved sulfide control and significantly reduced chemical dosage.
Keyword Sewers
Autoregressive moving average models
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
Advanced Water Management Centre Publications
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