In the realm of energy and biotechnology, a team of researchers from the University of Hohenheim in Stuttgart, Germany, has been exploring ways to improve the monitoring and operation of anaerobic digestion (AD) plants, which are crucial for biogas production. The team, comprising Simon Hellmann, Terrance Wilms, Stefan Streif, and Sören Weinrich, has developed a method to better handle the different sampling rates and delays inherent in the data collected from these plants.
Anaerobic digestion plants often rely on a mix of online sensors and offline laboratory analyses for monitoring. The challenge lies in the fact that these measurements are taken at different rates and times, with offline measurements often delayed due to laboratory procedures. This multirate (MR) setting can complicate the use of Kalman filtering, a common method for estimating the state of a process based on noisy measurements. Traditional Kalman filters assume measurements are taken at regular intervals and without delays.
The researchers have developed a multirate extended Kalman filter (MR-EKF) that addresses these issues. Their approach involves sample state augmentation, which allows the filter to handle delayed offline measurements more effectively. The team tested the MR-EKF in various scenarios, including different delay lengths, measurement noise levels, plant-model mismatch (PMM), and initial state errors.
The results showed that with proper tuning, the MR-EKF can reliably estimate the process state, effectively fuse delayed offline measurements, and smooth noisy online measurements. The study found that the delay length of offline measurements does not critically impair state estimation performance, provided the system remains observable during the delays. However, poor state initialization and PMM were found to affect convergence more than measurement noise levels.
The researchers emphasize the importance of appropriate tuning for the successful application of the MR-EKF. They provide a systematic approach to this tuning, offering practical guidance for practitioners aiming to apply state estimation in multirate systems. This research contributes to the development of demand-driven operation of biogas plants, which can aid in stabilizing the renewable electricity grid.
The study, titled “A Tutorial to Multirate Extended Kalman Filter Design for Monitoring of Agricultural Anaerobic Digestion Plants,” was published in the IEEE Control Systems Society Conference. The findings offer valuable insights for the energy sector, particularly for those involved in biogas production and the integration of renewable energy sources into the grid. By improving the monitoring and operation of anaerobic digestion plants, this research can help enhance the efficiency and reliability of biogas as a renewable energy source.
This article is based on research available at arXiv.