Respirometry in Control of the Activated Sludge Process: Principles

Copp, John B.; Spanjers, Henri; Vanrolleghem, Peter

doi:10.2166/9781780402611

Cited by 1 publication

(1 citation statement)

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“…The effluent quality index is a parameter that considers the effects of several important wastewater contaminants in aggregate and includes the total suspended solids, chemical oxygen demand, five-day biochemical oxygen demand, total Kjeldahl nitrogen and nitrates/nitrites. The effluent quality index has been used previously as a performance and sensitivity index for wastewater treatment (Copp 2002, Kim et al 2006.…”

Section: Pollution Load Evaluationmentioning

confidence: 99%

Evolutionary Multi-Objective Optimal Control of Combined Sewer Overflows

Rathnayake

Tanyimboh

2015

Water Resour Manage

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This paper presents a novel multi-objective evolutionary optimization approach for the active control of intermittent unsatisfactory discharges from combined sewer systems. The procedure proposed considers the unsteady flows and water quality in the sewers together with the wastewater treatment costs. The distinction between the portion of wastewater that receives full secondary treatment and the overall capacity of the wastewater treatment works (including storm overflow tanks) is addressed. Temporal and spatial variations in the concentrations of the primary contaminants are incorporated also. The formulation is different from previous approaches in the literature in that in addition to the wastewater treatment cost we consider at once the relative polluting effects of the various primary contaminants in wastewater. This is achieved by incorporating a measure of the overall pollution called the effluent quality index. The differences between two diametrically opposed control objectives are illustrated, i.e. the minimization of the pollution of the receiving water or, alternatively, the minimization of the wastewater treatment cost. Results are included for a realistic interceptor sewer system that show that the combination of a multi-objective genetic algorithm and a stormwater management model is effective. The genetic algorithm achieved consistently the frontier optimal control settings that, in turn, revealed the trade-offs between the wastewater treatment cost and pollution of the receiving water.

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Section: Pollution Load Evaluationmentioning

confidence: 99%