Wouters, J.W. – RWB Special Products BV & Brightwork BV
Heslegrave, C. – Aquabio Ltd UK
Sutman, P. – University of Applied Sciences Van Hall Larenstein & Brightwork BV
Opijnen, E. Van. – Brightwork BV
(free)Abstract
More stringent effluent criteria for N and P has led to the increased implementation of tertiary moving bed biofilters to (simultaneously) remove phosphorus and nitrogen.
In order to meet these stringent criteria it is important to optimize day-to-day operations, reduce downtime of equipment, have access to real-time status updates and act quickly to remedy failures. Field surveys however reveal that many plants suffer from non-optimal operating conditions, which may last long before being detected. This will seriously impact actual performances.
In order to optimize the use of these assets an “internet-of-things” based monitoring and control system is successfully implemented. A sophisticated remote control system has been developed in the Netherlands, based upon radio frequency ID mote technology. It is applicable to all currently operating continuously moving bed (bio)filters, but has a much broader range of applications. Implementing this mote technology in MBFs will allow operators to optimize the output of the plant, with less effort. Real time dash boards are available for plant operators, indicating current status conditions and clear instructions for detected malfunctions.
Keywords
Continuous sand filter, moving bed filter, data analytics, effluent polishing, filter control, motes, nitrification, phosphorus removal, remote control, RFID
Introduction
Asset management is a key issue for water utilities. Simultaneously the waste water treatment assets should be capable of meeting the requested process performance targets at the lowest possible operational expenditures. In the last centuries utilities have invested heavily in process equipment, including effluent polishing processes to meet more stringent criteria for suspended solids, BOD, nitrate-N, total-N and/or phosphorus. These assets are now challenged to meet even more stringent effluent targets. But operator attendance is reduced and operator tasks are intensified. This paradigm requires a significant shift in monitoring and control strategies. Remote sensing, expert judgement and big data analysis are key to support the optimization of the assets. This paper describes the implementation of smart monitoring tools for operating moving bed continuous sand filters (MBFs), to illustrate the relevancy of smart monitoring in day-to-day operations of waste water treatment works.
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