Evolutionary optimization of combined sewer overflow control

Andrea Zimmer, David Hill, Barbara Minsker, Avi Ostfeld, Arthur Schmidt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Model predictive control (MPC) is coupled with a real-coded Genetic Algorithm to predict a decision sequence that minimizes combined sewer overflow (CSO) volume for a 3-hour rainfall event over a hypothetical sewer system. Rainfall is transformed to overland runoff through the cell model which depicts each sewershed (draining to an overflow dropshaft) by two linear reservoirs in series, and water entering the interceptor is routed downstream to establish water levels at the dropshaft connections. A pumping rate at the most downstream end of the interceptor plus one sluice gate position for each dropshaft connection will be altered to produce the best control strategy. Resulting management scenarios disperse overflows differently throughout the sewer, but may yield similar overflow volumes. This paper describes the simulation approach taken and displays the overflow distribution for favorable control sequences.

Original languageEnglish (US)
Title of host publicationProceedings of World Environmental and Water Resources Congress 2009 - World Environmental and Water Resources Congress 2009
Subtitle of host publicationGreat Rivers
PublisherAmerican Society of Civil Engineers
Pages1092-1104
Number of pages13
ISBN (Print)9780784410363
DOIs
StatePublished - 2009
EventWorld Environmental and Water Resources Congress 2009: Great Rivers - Kansas City, MO, United States
Duration: May 17 2009May 21 2009

Publication series

NameProceedings of World Environmental and Water Resources Congress 2009 - World Environmental and Water Resources Congress 2009: Great Rivers
Volume342

Other

OtherWorld Environmental and Water Resources Congress 2009: Great Rivers
CountryUnited States
CityKansas City, MO
Period5/17/095/21/09

ASJC Scopus subject areas

  • Environmental Science(all)

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