Feed-forward coagulant control using online UV/Vis monitoring

Abstract

Water quality from the Murray River, Australia, can vary considerably and is expected to become more challenging to treat due to recent drought followed by widespread flooding and future climate change impacts. Better tools are required to help plant operators maintain water quality. Morgan water treatment plant (WTP) operates overnight to take advantage of off-peak electricity, however the stop/start practices add an additional complication to accurate coagulant dosing. Online monitoring and feed forward prediction is ideal in these situations as it can provide information while there is still a chance to make adjustments, unlike the feedback (post-dosing) control achieved with many other methods. Using a multiport sampling arrangement, water quality was monitored at Morgan WTP for a 6 month period. Data were validated against other online parameters and laboratory measured samples. In a comparison of predicted versus actual plant dose, results showed that treatment was optimised when the plant dose was changed in response to product water quality deterioration and eventually matched the prediction, even though this was not known to the operators at the time. The software prediction demonstrated faster reaction to inlet water quality changes and can produce more stable treated water quality. The predicted dose was added to the operator's Supervisory Control and Data Acquisition (SCADA) system for several months as a real-time display to provide an additional tool to aid decision making and instill confidence in the resulting water quality.