Water, Wastewater & Stormwater
397970 - Optimizing Energy Consumption in Wastewater Treatment Plants Using Monte Carlo Simulations of Process Parameters and Treatment Equations.
Tuesday, June 5
2:00 PM - 3:30 PM
Location: Greenway EF
Graduate Research Assistant
Bradley University, Peoria, IL
Wastewater treatment plants use a combination of physical, chemical, and biological methods for treatment. Activated sludge, a biological process involving sustained aeration of wastewater to accelerate aerobic decomposition, is expensive and consumes 50-90% of total energy requirements. This study sought to optimize this process by simulating design and operational parameters to reduce energy consumption.
Five-year data from the aeration process of a treatment plant were analyzed. These data range from hydraulic parameters like inflow, RAS and WAS, tank volume, detention time, to quality or treatment parameters like suspended solids, dissolved oxygen concentration, influent and effluent BOD concentrations, mean cell residence time, and energy consumption parameters like oxygen transfer efficiency and air supplied.
Mathematical relationships governing a wide-range of operational and treatment processes were applied and Monte Carlo simulations performed. Usually, the outcome of a single parameter in a given equation can be easily determined if the magnitudes of the other parameters are known or set. However, these simulations allowed for concurrent and/or consecutive adjustments of multiple parameters in multiple equations on which the aeration process depends in order to find optimum values of other parameters of interest. Results of desired parameters like effluent BOD removed, percent of total plant power consumed, KWh-power/lb-BOD, etc. all showed improvement. Despite limitations like slight reductions in BOD removal efficiencies (<5%) and hypothetical bases for parameter ranges, the results demonstrate some potential for reducing energy consumption in treatment plants if multiple process simulations are used to determine a wider range of operational policy options.