Oxygen control in a wastewater treatment plant using adaptive predictive controllers Gregor Kandare, Jozef Stefan Institute, Slovenia

Adaptive predictive control

Process description 6 pools with butterfly valves and 2 dissolved oxygen sensors each. 4 blowers with diffuser for pressure control.

Process description

Control issues Biological dynamics of the process Aleatory operation context Lack of process information Interactive nature of the process

Control objectives Maintain the dissolved oxygen signal at its setpoint by manipulationg the aeration with butterfly valves. Maintain the air pressure in the main air conduct at a setpoint that minimises energy consumption and assures good oxygen control.

Control strategy 6 controllers – one for each pool

PID control Oxygen and valve opening

PID control Air pressure and airflow

Adaptive predictive control Oxygen and valve opening

Adaptive predictive control Air pressure and airflow

Oxygen control evaluation Reactor PIDAP Factor

Energy optimisation Objectives: Maintain air pressure at a minimal level which still permits satisfactory oxygen control. Maintain dissolved oxygen setpoints at a minimal level that ensures required effluent water quality.

Pressure optimisation

Change PID – adaptive predictive

Energy consumption estimation W – energy, p – pressure, V - volume P – power, Φ V - airflowW – consumed energy in each pool in a time interval [t 0,t 1 ]

Consumption reduction Pool Average power consumed with PID control Average power consumed with AP control with pressure optimisation Average energy savings [%] Pool Pool Pool Pool Total

Conclusions The adaptive predictive controllers stabilise the process and maintain oxygens at therir setpoints More stable oxygen control and pressure setpoint optimisation decrease energy consumption by %