Sensor bias impact on efficient aeration control during diurnal load variations

Abstract

Abstract This study highlights the need to increase our understanding of the interplay between sensor drift and the performance of the automatic control system. The impact from biased sensors on the automatic control systems is rarely considered when different control strategies are assessed in water resource recovery facilities. Still, the harsh measurement environment with negative effects on sensor data quality is widely acknowledged. Simulations were used to show how sensor bias in an ammonium cascade feedback controller impacts aeration energy efficiency and total nitrogen removal in an activated sludge process. Response surface methodology was used to reduce the required number of simulations, and to consider the combined effect of two simultaneously biased sensors. The effects from flow variations, and negatively biased ammonium (−1 mg/L) and suspended solids sensors (−500 mg/L) reduced the nitrification aeration energy efficiency by between 7 and 25%. Less impact was seen on total nitrogen removal. There were no added non-linear effects from the two simultaneously biased sensors, apart from an interaction between a biased ammonium sensor and dissolved oxygen sensor located in the last aerated zone. Negative effects from sensor bias can partly be limited if the expected bias direction is considered when the controller setpoint-limits are defined.