Operations Simulator for MBRs on the Windows .NET Platform – AquaNET Aquifas – Full Scale Verification and Energy Optimization
Abstract:A MBR operations simulator was developed based on the IWA ASM2d model for activated sludge and on the IWA principles for biofilm modeling. The graphical interface was developed using the Windows .NET platform. The interface has separate menus for designers and operators. The model allows the user the option to simulate the MBR and the whole plant. The whole plant interface includes headworks, primary, secondary, sludge handling, digestion and dewatering facilities.
Several features related to plant operations were included in the simulator. These include: (a) varying the cyclic air scour on-time fraction; (b) flow pacing or changing the aeration at different times of the day; (c) reducing the MBR recycle while managing the solids flux; (d) reducing the operating DO in the aeration zone upstream of membrane cell; (e) reducing the aeration in the MBR cell such that it simultaneously meets both the air scour and process demand requirements; (f) computing the characteristics and removals in the biofilm growing on membranes in the membrane cell or in biofilm support media. These features are based on experiences with operation of MBRs with hollow fiber and flat sheet modules, and in-line and side-line cross flow submerged membranes.
The simulator was verified against observations made a full scale plants. It was able to predict reduction in energy observed through reduction in operating DO to within 94% of actual values at Redlands, CA; it was able to predict reduction in energy by changing the MBR cycle times to within 99% of observed values at Traverse City, MI. Its predictions of optimized energy requirements (0.36 KWH/m3 of flow treated) were consistent with measurements following optimization at the Ulu Pandan, Singapore plant (0.38 KWH/m3). For flat sheet membranes, it predicted 0.45 KWH/m3 of flow treated, which was consistent with the best values reported. Based on this verification of its ability to predict optimization in full scale facilities, the model can be used as a tool for operations optimization in existing systems and to improve the design and MBRs.
Document Type: Research Article
Publication date: January 1, 2010
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