Pergamon PH: 50273-1223(98)00467-3 War. Sci Tech. Vol. 38. No.3. pp. 271-280. 1998. IAWQ C J 998 Published by Elsevier Science Ltd. Printed in Oreal Drilain. AllrightJ reserved 0273-1 223198$19·Olh· 0'00 APPLYINa REAL-TIME CONTROL TO ENHANCE THE PERFORMANCE OF NITROGEN REMOVAL IN THE CONTINUOUS-FLOW SBR SYSTEM Ruey-Fang Yu", Shu-Liang Liaw", Cheng-Nan Chang** and Wan-Yuan Cheng* • GraduateInstitute of Environmental Engineering. NationalCentral University. Chung-li32054. Taiwan. R .O.C. •• GraduateInstitute of Environmental Science, Tunghai University, Talchung40704, Taiwan. R.O.C. ABSTRACf Conventional operations of wastewater treatment systems use the concepts of steady-state control. and often lead to unnecessaryresource consumptionfor maintainingsystem functions. Real-time control was examined as a useful approach for improving the operation of wastewater treatment systems. This paper presents the application of real-time control to enhance the performance of nitrogen removal in a continuous-flow SBR system. A real-time control system combining on-line measurement of ORP and pH with Artificial Neural Network (ANN) model was proposed to carry out unsteady-stateregulation of the hydraulicretention time of different operation phases. The result of this study shows that the performance of nitrogen removal was enhanced under real-time operation. Compared with fixed-time operation. the retention time of aerobic and anoxic phases can be reduced by approximately45% and 1S.5% in real-time operation respectively, also meaning that 45% aeration energy can be saved. The real-timeoperation also reveals a higher total nitrogen removal in a relative short retention time. Moreover. some dynamics and kinetics of nitrogen were investigated. These indicate the occurrenceof nitrite-typenitrificationunder real-timeoperation. This nitrite- type nitrification results in the enhancement of denitrification performance with less carbon resource requirement and higher denitrification efficiency. C 1998 Published by Elsevier Science Ltd. All rights reserved KEYWORDS Artificial neural network; biological nutrient removal; continuous-flow SBR; kinetic; real-time control ; on- line measurement; ORP and pH. INTRODUCTION Conventional steady-state operations in wastewater treatment plants frequently present difficulties in regulating optimal conditions due to the inherent dynamic and complex characteristics of system. Continuous monitoring and automatic control provide some information which can be used for real-time control and process optimization (Vassos, 1993). On-line monitoring of ORP and pH has proved a useful technique for process control of activated sludge process, sludge digestion. biological nutrient removal 271