Simulation of Dynamic Behaviour of a Biological Wastewater Treatment Plant in South East Queensland, Australia using Bio-Win Software

Abstract

Wastewater treatment is the process of removing pollutants from liquid waste using physical, chemical and biological methods by converting it into an acceptable final effluent before discharging into a water body or reuse, and to safely dispose of solids generated during the treatment process. Limited parameters in Wastewater Treatment Plant (WWTP) are usually measured due to the significant cost and time involved with them. The mathematical modelling is increasingly becoming a well-established technique among researchers as well as practicing engineers to study the behaviour of wastewater treatment process as it provides more accurate predictions within the limited time frame at a reduced cost. Therefore, this technique can be used to study the engineering design of modern water resource recovery facilities that experience in increasing demands on control of effluent quality. The research work presented here is focused on studying the dynamic (time dependent) behaviours of the wastewater treatment plant in south east Queensland, Australia using the mathematical modelling technique implemented using Bio-Win software. The model developed has been calibrated and validated based on the measured data from the WWTP. The main benefit of this research work is that the developed and validated model can be used to study the non-measured important parameters of the WWTP.

Emerging investigator series: modeling of wastewater treatment bioprocesses: current development and future opportunities

“…50 BioWin, for example, is a flexible software tool that includes multiple microbial processes presented in ASMs and anaerobic digestor models (ADMs). [51][52][53][54][55] It has been used to model the biological systems in full-scale wastewater treatment plants, [52][53][54][55] including activated sludge, 56 anaerobic digestion, 57,58 and anammox processes. 51 In some of the studies, BioWin provided a good match between the measured and predicted data (difference <10%) for both small-scale batch reactors and full-scale systems, [56][57][58] and it can perform optimization of sludge retention time and nitrogen removal under different DO and return activated sludge flows.…”

“…16,35 Real wastewater and sewage sludge are highly heterogeneous with various degradable and inhibitory compounds that result in diverse microbial populations. 43,55 For wellcharacterized populations with known functions, unmeasurable kinetic parameters are predominantly derived from biochemical measurements. 14,16,34,35,40 Although the data-driven component can help correct the estimates and improve the prediction performance, the estimated kinetic parameters do not necessarily reflect the actual activity of those populations.…”

Key performance indicators (KPIs) comparison of food chain reactor and conventional oxidation ditch technology in industrial waste treatment

“…According to Krejny, 2015 [16], wastewater KPIs of Wastewater Treatment Plant [17]. A mathematical model and pilot testing to performing carbon oxidation-nitrification, denitrification and settling was revealed that operational cycles which conducted in the range (120 -400 min), only one (220 min-nitrification: 120 min/ denitrification : 100 min), met fully the nitrogen's effluent criteria and minimum energy consumption [18].…”