WWTP dynamic disturbance modelling--an essential module for long-term benchmarking development.

Intensive use of the benchmark simulation model No. 1 (BSM1), a protocol for objective comparison of the effectiveness of control strategies in biological nitrogen removal activated sludge plants, has also revealed a number of limitations. Preliminary definitions of the long-term benchmark simulation model No. 1 (BSM1_LT) and the benchmark simulation model No. 2 (BSM2) have been made to extend BSM1 for evaluation of process monitoring methods and plant-wide control strategies, respectively. Influent-related disturbances for BSM1_LT/BSM2 are to be generated with a model, and this paper provides a general overview of the modelling methods used. Typical influent dynamic phenomena generated with the BSM1_LT/BSM2 influent disturbance model, including diurnal, weekend, seasonal and holiday effects, as well as rainfall, are illustrated with simulation results. As a result of the work described in this paper, a proposed influent model/file has been released to the benchmark developers for evaluation purposes. Pending this evaluation, a final BSM1_LT/BSM2 influent disturbance model definition is foreseen. Preliminary simulations with dynamic influent data generated by the influent disturbance model indicate that default BSM1 activated sludge plant control strategies will need extensions for BSM1_LT/BSM2 to efficiently handle 1 year of influent dynamics.

[1]  L Benedetti,et al.  Assessment of WWTP design and upgrade options: balancing costs and risks of standards' exceedance. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[2]  Ulf Jeppsson,et al.  Phenomenological modelling of wastewater treatment plant influent disturbance scenarios , 2005 .

[3]  U Jeppsson,et al.  Multivariate on-line monitoring: challenges and solutions for modern wastewater treatment operation. , 2003, Water science and technology : a journal of the International Association on Water Pollution Research.

[4]  I. Takács A dynamic model of the clarification-thickening process , 1991 .

[5]  P A Vanrolleghem,et al.  Towards a benchmark simulation model for plant-wide control strategy performance evaluation of WWTPs. , 2006, Water science and technology : a journal of the International Association on Water Pollution Research.

[6]  W. Gujer,et al.  Activated sludge model No. 3 , 1995 .

[7]  ChangKyoo Yoo,et al.  Dynamic Monitoring Method for Multiscale Fault Detection and Diagnosis in MSPC , 2002 .

[8]  Krist V. Gernaey,et al.  Rapid WWTP performance evaluation over a wide range of operational conditions using artificial neural networks , 2005 .

[9]  P A Vanrolleghem,et al.  Towards a common benchmark for long-term process control and monitoring performance evaluation. , 2004, Water science and technology : a journal of the International Association on Water Pollution Research.

[10]  Sylvie Gillot,et al.  The COST Simulation Benchmark: Description and Simulator Manual , 2001 .

[11]  R. Otterpohl,et al.  Dynamic Models for Clarifiers of Activated Sludge Plants with Dry and Wet Weather Flows , 1992 .