State estimation for anaerobic digesters using the ADM1.

The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.

An advanced simulation model for membrane bioreactors: development, calibration and validation.

Membrane wastewater treatment plants (WWTPs) have several advantages compared with conventionally designed WWTPs with classical purification techniques. The filtration process is the key to their commercial success in Germany with respect to energy consumption and effectiveness, enabled by the optimization of filtration using a dynamic simulation model. This work is focused on the development of a robust, flexible and practically applicable membrane simulation model for submerged hollow-fibre and flat-sheet membrane modules. The model is based on standard parameters usually measured on membrane WWTPs. The performance of the model is demonstrated by successful calibration and validation for three different full-scale membrane WWTPs achieving good results. Furthermore, the model is combinable with Activated Sludge Models.