Design of an integrated monitoring and optimal control system for supervisory operation of anaerobic digesters

Abstract

Anaerobic digestion with biogas production has both economic and environmental benefits. 25 % of all bioenergy in the future could potentially be sourced from biogas (Holm-Nielsen et al., 2009). Although anaerobic digesters have seen wide applicability, they typically perform below their optimum as a consequence of the complexity of the underlying process. This work involves the development of a generic advanced process control system for the optimisation of the performance of anaerobic digesters. There is a requirement for a configurable monitoring and optimisation system with associated sensors to optimise the production of biogas, combined with a degree of flexibility for quality and content of the digestate. Several analyses are conducted to establish the baseline performance of the four benchmarked sites. Significant findings are revealed which include lack of superior technology between the four varying processes, differing performance due to optimisation activities through increased monitoring and whole plant optimisation such as energy usage and production. Potential improvements are presented including increased monitoring and a reduction in the variability of key parameters such as thicker percentage dry solids (% DS), steady feed rate, and temperature. The lack of instrumentation in anaerobic digestion processes is a key bottleneck as sensors and analysers are necessary to reduce the uncertainty related to the initial conditions, kinetics and the input concentrations of the process. Without knowledge of the process conditions, the process is inevitably difficult to control. Financial gains that can be achieved through increased instrumentation were calculated to justify the business case for the need for process improvement. An instrumentation review is presented with the minimum and ideal instrumentation requirements for the AD process. Improved monitoring is achieved through soft sensor development for volatile solids (VS), an important variable that is currently only monitored offline. The inferential sensor is developed using data from an industrial process and compared with the results from a simulation study where feed flow and biogas production rate are used for modelling VS. This theme of improving monitoring with inferential sensors is continued with development of soft sensors with microbial data and data from different reactor designs.