Advanced Control of Wastewater Treatment Plants
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My contribution in this European-funded project has been the development of software sensors in the water line of wastewater treatment plants (WWTPs), which serves for monitoring the ammonia concentrations in the aerobic tanks of the plant line and in the anoxic tank. In addition, the software sensor serves to track the maximum nitrification rate. Specifically, Extended Kalman filter is derived and shown the Kalman filter to a much broader class of non-Gaussian distributions. The filter has several desirable properties, such as its ability to preserve statistical relationships in the prior state and converge to highly accurate observations [1].
Some projects in this field where I have been working on:
DARROW – Making wastewater treatment more sustainable and efficient using a data-driven AI solution
DARROW aims to build a data-driven AI solution to optimise resource recovery from wastewater by making wastewater treatment plants more autonomous and energy efficient.
Award institution: European Union’s Horizon Europe research and innovation programme within the project DARROW (grant agreement Nº 101070080)
References
- Ricardo Rodríguez Jorge, A grey-box model for real-time control and monitoring, Lecture Notes in Networks and Systems – Proceedings of the 19th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC-2024), Springer Nature Switzerland AG, San Benedetto del Tronto, Italy, November 13-15, 2024 (Web of Science, SCOPUS).
- Cristina Rodríguez-García, Cesar Arenas, Saioa Arrizabalaga, Luis V. Varcárcel, Ricardo Rodríguez-Jorge, Itxaro Errandonea, Decision support tool for WWTP operations: DARROW project case study, Poster, in: Book of Abstracts. IWA Young Water Professionals Spain Conference 2024.