Optimising feedstock flowrate to improve the performance of an existing anaerobic digestion system.

This paper presents an approach to model and optimise the feedstock flowrate of an anaerobic digestion (AD) cooking system by simultaneously minimising the volume of flared biogas, the unmet cooking demand and the energy cost. As research has typically focused on optimising the digester and its associated parameters to maximise the biogas yield; this research examines how different objectives can influence how one might want to control the system. The system is initially modelled and validated with measured data and an optimisation algorithm is then applied to control the feedstock flow rate. The results show that the performance of first order AD models, in predicting the biogas yield, only differs from measured data by 9% and that by controlling the feeding rate, the amount of flared biogas and unmet cooking demand can be reduced by 100% and approximately 87%, respectively when they are the only objective functions considered. If the energy cost is also added an objective function, then more precise control of feeding rate is needed to ensure that all three conflicting objectives are equally minimised. This result highlights the importance of using the correct feeding rate in the system and considering the overall system during optimisation as producing more biogas might not result in the most cost-effectivesystem.