Patterns in the Course of Gas Production Rates in Anaerobic Digestion—Prediction of Gas Production Rates Based on Deconvolution and Linear Regression

Abstract

Anaerobic digestion, including the gas storage and the CHP unit plays a key role in energy management of water ressource recovery facilities (WRRF). By demand-driven feeding management, a higher degree of utilization of the gas storage tanks can be achieved, which means that a greater decoupling of energy demand and energy generation is taking place. In this context, the predictability of the produced gas volume plays an important role. In this study, a concept was suggested to forecast gas production rates without the need for any analytical substrate characterization. Substrates lead to specific patterns in the course of the gas production rates, which can be fitted using Gaussian functions. As the parameters describing the Gaussian functions have a good correlation to the amount of substrate fed to the digester a prediction of the rates is possible. Within this study a coefficient of determination 82.9% over a period of 5 days was achieved.

Keywords

• energy
• demand-driven
• biogas
• gas production rate
• patterns
• prediction