title: Reducing aeration energy consumption in a large-scale membrane bioreactor: Process simulation and engineering application.
abstract: Reducing the energy consumption of membrane bioreactors (MBRs) is highly important for their wider application in wastewater treatment engineering. Of particular significance is reducing aeration in aerobic tanks to reduce the overall energy consumption. This study proposed an in situ ammonia-N-based feedback control strategy for aeration in aerobic tanks; this was tested via model simulation and through a large-scale (50,000 m(3)/d) engineering application. A full-scale MBR model was developed based on the activated sludge model (ASM) and was calibrated to the actual MBR. The aeration control strategy took the form of a two-step cascaded proportion-integration (PI) feedback algorithm. Algorithmic parameters were optimized via model simulation. The strategy achieved real-time adjustment of aeration amounts based on feedback from effluent quality (i.e., ammonia-N). The effectiveness of the strategy was evaluated through both the model platform and the full-scale engineering application. In the former, the aeration flow rate was reduced by 15-20%. In the engineering application, the aeration flow rate was reduced by 20%, and overall specific energy consumption correspondingly reduced by 4% to 0.45 kWh/m(3)-effluent, using the present practice of regulating the angle of guide vanes of fixed-frequency blowers. Potential energy savings are expected to be higher for MBRs with variable-frequency blowers. This study indicated that the ammonia-N-based aeration control strategy holds promise for application in full-scale MBRs.
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Jianyu
authors.initials: J
authors.lastname: Sun
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Liang
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Xiaoxu
authors.initials: X
authors.lastname: Yan
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Kuichang
authors.initials: K
authors.lastname: Zuo
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address: kxiao@ucas.ac.cn.
authors.forename: Kang
authors.initials: K
authors.lastname: Xiao
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Junlin
authors.initials: J
authors.lastname: Xia
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Qiu
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Wu
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Shijia
authors.initials: S
authors.lastname: Wu
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China. Electronic address: xhuang@tsinghua.edu.cn.
authors.forename: Xia
authors.initials: X
authors.lastname: Huang
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Meng
authors.initials: M
authors.lastname: Qi
authors.affiliation: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
authors.forename: Xianghua
authors.initials: X
authors.lastname: Wen
mesh_terms: D000388:Air; D000465:Algorithms; D000641:Ammonia / Q000737:chemistry / Q000378:metabolism; D019149:Bioreactors; D003198:Computer Simulation; D004738:Engineering / Q000295:instrumentation / Q000379:methods; D008567:Membranes, Artificial; D008962:Models, Theoretical; D010100:Oxygen / Q000378:metabolism; D014865:Waste Disposal, Fluid / Q000295:instrumentation / Q000379:methods*; D018508:Water Purification / Q000295:instrumentation / Q000379:methods*
chemical_list: D008567:Membranes, Artificial; D000641:Ammonia; D010100:Oxygen
keywords: Ammonia-N-based aeration control strategy; Engineering application; Membrane bioreactor; Simulation