@inproceedings{64da0541e5b040ac82784e88c7c66f92,
title = "Control of COD Flow to a Waste Water Treatment Plant",
abstract = "Flow variations of the inlet to a wastewater treatment plant (WWTP) are problematic due to the biological purification process. A way to reduce variations from industrial areas is to insert a buffer tank and control the outlet from this. Traditionally the only on-line measurement is the inlet flow to the wastewater treatment plant and reliable measurements in the system are difficult to establish. This lack of on-line measurements makes online control impossible, instead the aim of the project is to make a day-ahead plan for the buffer tank outlet. In this work two approaches are tested. First a model predictive controller (MPC) is designed to make a plan for keeping the Chemical Oxygen Demand (COD) flow to the WWTP constant assuming that the flows and concentrations can be predicted. Secondly the total mass flow to the WWTP is kept constant only using flow predictions in the optimisation. This leads to variations in the COD flow. The severeness of these variations is simulated and compared to the uncontrolled situation. It turns out that control of the total flow gives improvements in the COD flow variations compared to the existing sewer network without control.",
keywords = "Model predictive control, Sewer COD-flow control, Sewer flow modelling",
author = "Nielsen, {Kirsten M{\o}lgaard} and Pedersen, {Tom S{\o}ndergaard} and Carsten Kalles{\o}e and Palle Andersen",
year = "2022",
doi = "10.1007/978-3-030-92442-3_6",
language = "English",
isbn = "978-3-030-92441-6",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer",
pages = "83--104",
editor = "Oleg Gusikhin and Kurosh Madani and Janan Zaytoon",
booktitle = "Informatics in Control, Automation and Robotics 2020",
address = "Germany",
note = "Informatics in Control, Automation and Robotics 2020 ; Conference date: 07-07-2020 Through 10-07-2020",
}