Abstract
This paper describes an automatic sampling system for anaerobic reactors that allows taking representative samples following the guidelines of Gy’s (1998) theory of sampling. Due to the high heterogeneity degree in a digester the sampling errors are larger than the analysis error, making representative sampling a prerequisite for successful process control. In our system, samples are automatically processed, generating a higher density of data and avoiding human error by sample manipulation. The combination of a representative sampling system with a commercial automate titration unit generates a robust online monitoring system for biogas plants. The system was successfully implemented in an operating biogas plant to control a feeding-on-demand biogas system.
Highlights
Online monitoring in anaerobic digestion is fundamental for the technical and economic optimization of the process
The parameters most used to determine the stability of the anaerobic digestion process are total Volatile Fatty Acids (VFA), concentration of each specific acid, alkalinity and hydrogen concentration in the liquid phase
It could be seen that the measured values for VFA and TIC are varying up to 50% while the VFA/TIC ratio is almost constant
Summary
Online monitoring in anaerobic digestion is fundamental for the technical and economic optimization of the process. At the time of writing there was no commercial unit for online measurement of anaerobic digestion that includes a representative sampling procedure. Research is focused on the evaluation of the capacity and required time to detect a generated instability. Representative sampling is required because digestates are characterized by a mixture of different substrates like energy crops, manure or organic wastes at different stages of fermentation (Constitution Heterogeneity, CH). The mixing system in Continuous Stirring Tank Reactors (CSTR) is not designed to generate a complete homogeneous mixture, but to increase the contact of the substrate with the bacteria [4]. Optimum mixing conditions are difficult to achieve in the practice, as the agitation performance is based on visual monitoring of the fermentation surface and there is no information on the layers below
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