2016 MWEA 92 st Annual Conference Sunday, June 18 th - Wednesday, June 21 st Boyne Mountain Resort Integrated real-time SRT and aeration control in the city of Grand Rapids M. Lunn, City of Grand Rapids E. Belia, Primodal US Inc. Oliver Schraa, inctrl Solutions Leiv Rieger, inctrl Solutions John Copp, Primodal Inc
Grand Rapids, MI Design flow 61 MGD Average flow 38 MGD Peak wet weather 90 MGD Population 270,000 Serve 11 communities Enhanced biological phosphorus removal Aeration control Sludge Retention Time (SRT) control Disinfection (UV) Wet weather operation Grit aeration Future high strength waste equalization Future digestion
Monitoring & Control Platform Real-time data quality of sensors Optimization of sensor maintenance Control system design and testing Dynamic process modeling Process monitoring Decision support: data to information (KPIs, benchmarking) Process KPI1 KPI2 Nitrification kwh / lb NH x removed % TKN removal Phosphorus removal Mole metal / mole TP removed % TP removal Sludge production Lb sludge removed from the lb dry sludge per kg influent secondary per lb of BOD going BOD to the primaries Power consumption kw / MG treated kw / lb BOD or N Peak factors (annual) BOD, P, Ammonia Annual maximum hourly load rate / annual average hourly load rate $ / hourly average load
Real time plant-wide control Real-time control loops Wet weather operation Plant process model Aeration control Grit aeration RAS SRT / WAS Disinfection (UV) Enhanced biological phosphorus removal Future digestion Future high strength waste equalization
Commissioning the Ammonia-DO Controller
DO and Ammonia-DO control DO control Ammonia and DO control Rieger, L., Jones, R. M., Dold, P. L., & Bott, C. B. (2014). Ammonia-Based Feedforward and Feedback Aeration Control in Activated Sludge Processes. Water Environment Research, 86(1), 63 73.
Ammonia based aeration control Grand Rapids North AT 10 Q air Setpoint 2.5 scfm high PI 7,800 scfm 0.5 scfm low DO Setpoint NH x -N Setpoint 2.5 mg DO high /L PI 1.2 mg DO/L 2.0 mg N/L 0.5 mg DO low /L PID Q air 7,897 scfm 1.35 mg DO/L 1.75 mg N/L M valve Valve Position AT10 75 % VP AT7 VP AT8 55 % 45 % MOV VP AT9 45 % Pressure Setpoint 7.5 psig 300 % high 125 % PI 50 % low Blower Capacity Setpoint PT 7.35 psig
North ABAC Early implementation Final tuning
Blower power draw
Concentration (mg/l) Airflow per tank (scfm) Concentation (mg/l) Airflow per tank (scfm) ABAC full-scale and model comparison 4 3.5 3 2.5 2 1.5 1 0.5 4000 3500 3000 2500 2000 1500 1000 500 0 0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Time (d) Effluent ammonia DO control probe NHx Setpoint North DO Setpoint North Total airflow 4 3.5 3 2.5 2 1.5 1 0.5 0 4000 3500 3000 2500 2000 1500 1000 500 0 NHx_Setpoint NHx T09 DO_Setpoint Air_Flow (scfm) T9 15 per. Mov. Avg. (DO T09)
Ammonia based aeration control
Airflow [Nm3/d] Model estimated airflow savings 400,000 DO (1,5) 350,000 300,000 250,000 200,000 DO (1,5) 16 % DO (0.5,3) 23 % 150,000 NO ABAC DW ABAC DW ABAC DW
JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN kw blowers ammonia removed (kg/d) kw/kg ammonia removed kw blowers kw/kg kw/kg ammonia ammonia removed ammonia removed (kg/d) Temperature Temperature (oc) (oc) Development of success metrics 2600 2600 25 2400 2200 2000 1800 1600 1400 1200 1000 900 800 700 600 500 400 0.6 0.5 0.4 0.3 0.2 0.1 0 2400 2200 2000 1800 1600 1400 1200 1000 900 800 700 600 21% 12% SEP '15 SEP '16 OCT '15 OCT '16 500 0.0 400 0.0 JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN without ABAC with ABAC 20 15 10 5 0 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 Ammonia removed no ABAC Ammonia removed with ABAC T no ABAC T with ABAC kw without ABAC kw with ABAC kw/kg ammonia removed without ABAC kw/kg ammonia removed with ABAC
Monitoring and Control Savings South Plant ammonia based aeration control: $60,800 /year North Plant ammonia based aeration control (estimate): $62,500 /year
Commissioning the Ammonia-SRT Controller
Combined DO-SRT control Measured NH x NH x set point Ammonia Controller Measured DO DO set point DO Controller Airflow Desired Average DO Concentration SRT set point Optimizer SRT set point Calculated Dynamic SRT SRT Controller Selects optimal SRT in context of desired DO set point WAS Flow Rate Schraa, O., Rieger, L. and Alex, J. (2016). Coupling SRT Control with Aeration Control Strategies. Proceedings of WEFTEC.16, New Orleans, LA, USA.
Ammonia - SRT control Grand Rapids North ABAC-SRT Q WAS Setpoint MLSS Setpoint SRT Setpoint DO setpoint target 1 mgd high 3500 mg TSS high /L 15 d SRT high Q WAS 0.55 mgd PI 2500 mg TSS/L PI 5.0 d SRT 1.0 mg DO/L PI 0 mgd low 1000 mg TSS low /L 3 d SRT low 3480 mg TSS/L SRT estim 4.85 d DO average 1.05 mg DO/L
SRT (d) MLSS (mg/l) Ammonia (mg/l) DO (mg/l) MLSS (mg/l) Q was (gpm) DO (mg/l) SRT (d) Model-based controller evaluation ABAC and independent MLSS control 2000 1800 1600 1400 1200 MLSS-WAS controller 280 270 260 250 240 230 220 210 200 0 2 4 6 8 10 12 14 16 18 20 Days 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 DO controller - SRT 0 0 5 10 15 20 Days 9 8 7 6 5 4 3 2 1 MLSS_setpoint MLSS_filtered Qwas Qwas bound max DO setpoint SRT_setpoint SRT-MLSS controller Ammonia-DO controller 9 2000 2 2 8.5 8 7.5 1800 1600 1.75 1.5 1.25 1 1.75 1.5 1.25 1 7 6.5 1400 1200 0.75 0.5 0.25 0.75 0.5 0.25 6 1000 0 2 4 6 8 10 12 14 16 18 20 Days 0 0 0 5 10 15 20 Days SRT_setpoint SRT_estimated MLSS_setpoint Ammonia setpoint DO setpoint NH4 exit
SRT (d) MLSS (mg/l) Ammonia (mg/l) DO (mg/l) MLSS (mg/l) Q was (gpm) DO (mg/l) SRT (d) Model-based controller evaluation DO-SRT integrated control MLSS-WAS controller DO controller - SRT 2000 450 3.5 8 1800 1600 1400 1200 400 350 300 250 3 2.5 2 1.5 1 0.5 7 6 5 4 3 2 1 1000 200 0 2 4 6 8 10 12 14 16 18 Days 0 0 0 2 4 6 8 10 12 14 16 18 Days MLSS measurement MLSS_setpoint MLSS_filtered Qwas DO setpoint DO_filtered SRT_setpoint SRT-MLSS controller Ammonia-DO controller 8 2000 2.5 3.5 7 6 5 4 3 2 1 1800 1600 1400 1200 2 1.5 1 0.5 3 2.5 2 1.5 1 0.5 0 1000 0 2 4 6 8 10 12 14 16 18 Days 0 0 0 2 4 6 8 10 12 14 16 18 Days SRT_setpoint SRT_estimated MLSS_setpoint Ammonia Ammonia setpoint DO setpoint
Commissioning the MLSS-Qwas PI
MLSS - Qwas
SRT - MLSS
Controller In-Out
Full-scale implementation challenges Controller performance - slow response time Plant planned maintenance Hydraulic issues Internet security - remote access Plant upgrades - SCADA
DO SRT control Tank 7 Tank 8 Tank 9 Tank 10 Primary influent RAS
SCADA upgrade
Steps to successful ICA Design: Include ICA as part of the design process Instrumentation: make use of new sensors and instruments implement adequate maintenance plans on-site develop Standard Operation Procedures for these sensors similar to laboratory measurements Computers: Take advantage of computing and storage capacity G. Olsson, B. Carlsson, J. Comas, J. Copp, K. V. Gernaey, P. Ingildsen, U. Jeppsson, C. Kim, L. Rieger, I. Rodríguez-Roda, J.-P. Steyer, I. Takács, P. A. Vanrolleghem, A. Vargas, Z. Yuan and L. Åmand (2014) Instrumentation, control and automation in wastewater from London 1973 to Narbonne 2013, Water Science & Technology April 2014
Steps to successful ICA Signal treatment and monitoring: Develop data validation tools and monitoring, fault detection and diagnosis methods integrate and re-use the data in operator support tool Process control: apply control technology test already-developed process control ideas in full scale System-wide: from unit process to whole plant perspective to wider system understand how to manage disparate objectives and performance criteria G. Olsson, B. Carlsson, J. Comas, J. Copp, K. V. Gernaey, P. Ingildsen, U. Jeppsson, C. Kim, L. Rieger, I. Rodríguez-Roda, J.-P. Steyer, I. Takács, P. A. Vanrolleghem, A. Vargas, Z. Yuan and L. Åmand (2014) Instrumentation, control and automation in wastewater from London 1973 to Narbonne 2013, Water Science & Technology April 2014
Staff Changes Environmental Resource Technician 1 part Laboratory Technician 1 part Air Pollution Control Inspector 1 part Operator Responsible for Laboratory Analysis, Online Sensors (Air, Water, Wastewater, Stormwater, River) and Data Quality
Decade of Progress
Summary Decades of work Data Quality Installation Controls Staff New Jobs Reduced Energy Improved Operation