This study is an extended and comprehensive analysis to accomplish optimal sizing for a biological nutrient removal (BNR) system with an A 2 O BNR activated sludge process using activated sludge models (ASM) kinetic models. A highly nonlinear activated sludge model combined with the EAWAG Bio-P module is formulated and optimized using a generalized reduced gradient solver. Primary and final clarifications are included with the A 2 O biotreatment scheme along with oxygen-supplying units. This paper includes a detailed description of model formulation, problem definition and discussion of optimal design in terms of capital (CAPEX) and operating (OPEX) cost estimates. The optimization problem is formulated and solved using typical cost factors and operating/design constraints applied to a typical illustrative system treating medium-strength wastewater. Results indicated that maintenance and sludge disposal expenditures represent more than 50% of the total annual cost and 80% of the annual running operating cost. Another major finding was that a primary clarifier is found to be cost ineffective in the A 2 O BNR process. Sensitivity of the optimal solutions and model performance to varying inflow conditions and to other effluent limits and model parameters will be discussed in another paper.
This paper presents the performance of an optimization model for a biological nutrient removal (BNR) system using the anaerobic-anoxic-oxic (A(2)O) process. The formulated model simulates removal of organics, nitrogen, and phosphorus using a reduced International Water Association (IWA) Activated Sludge Model #3 (ASM3) model and a Swiss Federal Institute for Environmental Science and Technology (EAWAG) Bio-P module. Optimal sizing is attained considering capital and operational costs. Process performance is evaluated against the effect of influent conditions, effluent limits, and selected parameters of various optimal solutions with the following results: an increase of influent temperature from 10 degrees C to 25 degrees C decreases the annual cost by about 8.5%, an increase of influent flow from 500 to 2500 m(3)/h triples the annual cost, the A(2)O BNR system is more sensitive to variations in influent ammonia than phosphorus concentration and the maximum growth rate of autotrophic biomass was the most sensitive kinetic parameter in the optimization model.
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