Presented in Session PP9A – Instrumentation and control 11 th IWA World Congress on Anaerobic Digestion, 23-27 September 2007, Brisbane, Australia Monitoring and control of the biogas process based on propionate concentration using online VFA measurement K. Boe, J-P Steyer* and I. Angelidaki** Institute of Environment & Resources DTU, Technical University of Denmark, Building 113, DK-2800, Kgs. Lyngby, Denmark * Laboratory of environmental biotechnology, French National Institute for Agronomic Research, Avenue des Etangs, 11100 Narbonne, France (Email: steyer@ensam.inra.fr ) ** Corresponding author. Phone: (+45)45251429, Fax: (+45)45932850, E-mail: ria@er.dtu.dk Abstract Simple logic control algorithms were tested for automatic control of a lab-scale CSTR manure digester. Using an online VFA monitoring system, propionate concentration in the reactor was used as parameter for control of the biogas process. The propionate concentration was kept below a threshold of 10 mM by manipulating the feed flow. Other online parameters such as pH, biogas production, total VFA, and other individual VFA were also measured to examine process performance. The experimental results showed that a simple logic control can successfully prevent the reactor from overload, but with fluctuations of the propionate level due to the nature of control approach. The fluctuation of propionate concentration could be reduced, by adding a lower feed flow limit into the control algorithm to prevent undershooting of propionate response. It was found that use of the biogas production as a main control parameter, rather than propionate can give a more stable process, since propionate was very persistent and only responded very slowly to the decrease of the feed flow which lead to high fluctuation of biogas production. Propionate, however, was still an excellent parameter to indicate process stress under gradual overload and thus recommended as an alarm in the control algorithm. Keywords Anaerobic digestion; propionate; simple control; volatile fatty acids Introduction One of the topics that have been under focus in anaerobic digestion technology for more than one decade is monitoring and control of the process. The increasing number of large-scale biogas plants increases the demand for proper monitoring and control of these systems (Steyer et al., 2006). The control applications can be based on various monitoring parameters, such as pH, alkalinity, volatile fatty acids (VFA) or biogas production. Most of the control applications are based on feed flow manipulation while this requires an equalisation tank in the feeding line. There are several control strategies in combination with different monitoring parameters in the anaerobic process. Pretorius (1994) used a simple on/off control for startup and operation of a UASB reactor treating petrochemical wastes containing short chain fatty acids where the feed pump was turned on or off according to the pH set point. Denac et al. (1990) used empirical control approach to control the effluent quality expressed in total acids concentration by regulating feed rate and using alkaline addition (to maintain pH at 7) as the controlled variable. The PID controller has been used by Marsili-Libelli and Beni (1996) to maintain the bicarbonate alkalinity in an anaerobic filter by manipulating the bicarbonate dosing (NaHCO 3 ). Bernard et al. (2001) successfully tested a model- based adaptive linearising controller and a fuzzy logic controller, for controlling the ratio of intermediate alkalinity to total alkalinity and the level of total alkalinity, by regulating feed flow in a pilot-scale anaerobic filter treating distillery wastewater. Other control parameters that have been suggested are biogas production and VFA (total or individual). The control applications that have been used for optimizing the biogas production were found in Steyer et al. (1999) and Liu et al. (2004). In Steyer et al. (1999), a probing control strategy was used by applying a disturbance (changing feed flow) on purpose and then analysing the gas production response to determine the reactor capability of handling the higher feed rate. Thereby, the pH was used as an alarm in the control algorithm. A similar strategy was used in Liu et al. (2004) where a cascade PID controller embedded into a rule-based supervisory system was used to