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: Wastewater treatment plant is a large-scale system and highly known with the nonlinearity of the parameters, making them a challenge to be controlled. In this paper, enhanced nonlinear PI (EN-PI) controller is developed for activated sludge process where a sector-bounded nonlinear gain with automatic gain adjustment is cascaded to conventional static-gain PI. The importance in controlling the dissolved oxygen concentration and the improvement of nitrogen removal process are discussed. The effectiveness of the proposed EN-PI controller is validated by comparing the performance of local control loops and the activated sludge process to the benchmark PI under three different weathers. The EN-PI controller is effectively applied in improving the performances of the static-gain PI, hence controlling the dynamic natures of the plant. Itwas proved by significant improvement in effluent violations, effluent quality index and energy saving of the Benchmark Simulation Model No.1.ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 07/2014; 39(8):6575-6586. DOI:10.1007/s13369-014-1285-2 · 0.37 Impact Factor
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ABSTRACT: The shortage of easily degradable carbon source in the denitrification process limits the biological nitrogen removal efficiency. Partial nitrification has shown to be an attractive technology due its savings in aeration and external carbon source addition cost in the biological nitrogen removal. In this article, a model predictive control method was proposed to optimize the aeration and the external carbon source addition under the disturbance of influent flow rate and nitrogen load. The results indicated that 56% saving in external carbon source addition and 26% saving in aeration cost can be achieved by the model predictive control method applied in the partial nitrification, in comparison to the complete nitrification.Journal of Environmental Chemical Engineering 12/2014; 2(4):1899–1906. DOI:10.1016/j.jece.2014.08.007
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ABSTRACT: Concentrated turtle aquaculture effluent poses an environmental threat to water bodies, and therefore needs to be treated prior to disposal. This study was conducted to assess the effect of multi-soil-layer (MSL) systems treating turtle aquaculture effluent with adding different amounts of sludge. Four MSL systems were constructed with dry weight ratios of sludge with 0%, 5%, 10%, and 20% (MSL 1, MSL 2, MSL 3, and MSL 4, respectively). The turtle aquaculture effluent had an average chemical oxygen demand (COD), ammonia nitrogen (NH4 (+)-N) and total nitrogen (TN) concentration of 288.4, 213.4, and 252.0 mg/L, respectively. The COD/TN (C/N) ratio was 1.2. The results showed that the four MSL systems could effectively treat the COD, NH4 (+)-N, and TN, and MSL 4 showed significantly improved NH4 (+)-N removal efficiency, suggesting the potential of sludge addition to improve the turtle aquaculture effluent treatment. The average COD, TN, and NH4 (+)-N removal efﬁciencies of MSL 4 were 70.3%, 66.5%, and 72.7%, respectively. To further interpret the contribution of microorganisms to the removal, the microbial community compositions and diversities of the four MSL systems were measured. Comparisons of the denaturing gradient gel electrophoresis (DGGE) profiles revealed that the amount of nitrifying bacteria and diversity in MSL 4 were higher than those in the other three systems. We concluded that adding 20% of sludge improved the NH4 (+)-N removal and stability of the system for nitrification, due to the enrichment of the nitrifying bacteria in MSL 4.Journal of Zhejiang University SCIENCE B 02/2015; 16(2):145-54. DOI:10.1631/jzus.B1400090 · 1.29 Impact Factor