Cost reduction of the wastewater treatment plant operation by MPC based on modified ASM1 with two-step nitrification/denitrification model
ABSTRACT The Activated Sludge Model No. 1 (ASM1) considers that nitrification and denitrification are single step processes and nitrite nitrogen (NO2–N), which is an intermediate for the two processes, is not accounted for. The first part of this paper presents the development of an enhanced ASM1 with two step nitrification/denitrification processes and its implementation in the Benchmark Simulation Model No.1 wastewater treatment plant (WWTP). The secondary settler was considered to be reactive in order to achieve a better fit between the simulation model and the behavior of the real WWTP. The second part presents the investigation of Model Predictive Control approach for the advanced control of the WWTP. Two control strategies are implemented for the wastewater treatment plant and they are analyzed from the perspective of the benefits brought to the WWTP operation. The proposed control strategy shows a reduction of the operational costs and the improvement of the effluent quality index.
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ABSTRACT: The first part of this paper presents the development of a 4-stage Bardenpho wastewater treatment plant simulator model. The simulator model is an adaptation of the Benchmark Simulation Model No. 1 for the 4-stage Bardenpho process, and it consists of seven reactor arranged in series followed by a secondary settler. The bio-kinetic model used to describe the biological processes in the reactors is a modified Activated Sludge Model No. 3 that considers parallel growth of the heterotrophic biomass on both biodegradable substrate and internal storage products. The secondary settler was considered to be reactive and the biological processes that occur in the settler were accounted for. The second part of the paper focuses on the analysis of the benefits that decentralized control has on the operation of the 4-stage Bardenpho process. Four control strategies of the 4-stage Bardenpho are analyzed from a control performance, operational costs and effluent quality perspective. The control strategies are based on PI controller designed using the Internal Model Control principle. In order to make the simulation more realistic the sensors and reactors were not considered being ideal and their complex behavior was considered in the simulator model.16th International Conference on System Theory, Control and Computing (ICSTCC 2012); 10/2012
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ABSTRACT: The objective of the current study is to investigate various control strategies implemented to wastewater treatment plants. The paper starts with discussion in modeling part of wastewater system and continues with designation of control objectives and control parameters. Subsequently, the implementations of common control structures including feedback, feedforward-feedback, supervisory and hierarchical controls are explained. The study is exclusively emphasized on four control techniques. Model predictive control performs superior control in optimizing nitrogen removal based on predictions of future behavior of wastewater systems. The performances of PID control in dissolve oxygen and nitrate control is improved significantly with multivariable configuration. Similar results achieved by data-driven approach compared to default PI simulation. Finally, artificial neural networks are commonly suggested for modeling and prediction purposes. A study is emphasized on Benchmark Simulation Model No. 1. The paper serve as a reference and for future research improvements in developing new advanced control techniques for wastewater field that aims in achieving stringent effluent quality standards. Key words: Wastewater treatment plant, control strategies, BSM1 benchmark.Australian Journal of Basic and Applied Sciences 01/2011; 5(8):446-455.
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ABSTRACT: Basing on the cost data of the wastewater treatment plant (WWTP) in Tianjin, the construction, operation and management cost was calculated. A regression model was developed considering the discount, and the average cost of sewage treatment was calculated. Three price policies were put forward, and the influence of the policies was simulated with the model. The results are powerful tools for government to pricing the wastewater treatment fee.Applied Mechanics and Materials 12/2012; DOI:10.4028/www.scientific.net/AMM.253-255.949