Bioprocess Intelligent Operating System -Beyond Ammonia Control-

Transcription

1 Bioprocess Intelligent Operating System -Beyond Ammonia Control- BioChem Technology, Inc. King of Prussia, PA May 20, 2015

2 Company Milestones 1978 Incorporation of BioChem Technology, Inc. as a pharmaceutical process consulting firm 1990 Transition to consulting for wastewater treatment processes Focus on R&D and municipal WW process consulting 1997 Begin development of current product line 2000 Installation of first self-calibrating ammonium ISE analyzer 2004 First installation of BIOS process controller 2008 First installation of BACS in US 2011 ISO 9001:2008 and 14001:2004 Certification

3 Process Control Objectives in BNR Plants Stabilize the biology Improve effluent quality Improve energy efficiency Maximize nitrogen removal.

4 Energy in WWTPs Water and wastewater processing consume 3% of US electricity (EPA Region 1) In 2008 the US had 14,750 WWTPs with secondary (or greater) treatment Average combined flow through these plants is 31.9 billion gd (2008 Clean Watershed Needs Survey) Typical electrical consumption of a WWTP is 1,300 to 2,000 kwh/mg. (WEF MOP 32, 2009) Aeration Data from WEF MOP 32 (2009)

5 BioChem Products BIOS - Optimal Process Control (Ammonia Control) BACS - Integrated Aeration Control System Engineering Services Process Simulation & Optimization

6 Diurnal Plant Loading Influent ammonia concentration as a measure of loading

7 Process Control and Optimization Current Technology Manual operating set points to treat maximum (expected) load leads to over-treatment most of the time or Feedback control based on effluent conditions leads to delayed response and instability BioChem Solution Model-based feed-forward control Measure influent conditions Model plant response to effluent changes Calculate set points for optimal treatment at minimum airflow Leads to process stability, energy savings and permit compliance

8 Increased Interest in Ammonia Control Systems are showing up on the market: Hach RTC E+H CDC80 Xylem Sanitaire OSCAR Bilfinger Aqualogic BioWin Controller Siemens But all have limited capabilities and support

9 BIOS Layout

10 BIOS Features Optimal DO control Multiple, individual set points Nitrate recycle control Carbon feed control WAS/SRT Control Instrumentation monitoring Auto tuning Facilitate simultaneous nitrification & denitrification

11 BIOS Process Control System Works for: Conventional ASP and extended aeration BNR and ENR activated sludge processes MLE 4 & 5 Stage Bardenpho Step Feed IFAS MBBR MBR AAO AOAO Oxidation Ditch SBR

12 Feed-Forward Control Theory Measured Values

13 Feed-Forward Control Theory Controlled Value

14 Feed-Forward Control Theory Manipulated Values

15 Activated Sludge Model Description Biological Kinetics

16 Feed-Forward Control Theory Measured Values DO Set-Points Optimization Algorithm Minimum DO to meet effluent ammonia goal Not all DO are equal, in regards to airflow DO set points with the least amount of airflow

17 Aeration Savings* Airflow Reduction as Function of DO OTE = k*sote*(c s -C)/C s * Assuming constant oxygen demand Required DO Set Point [mg/l]

18 Influent Ammonia Effluent Ammonia Influent Ammonia Effluent Ammonia Dynamic DO Control High NH 4 Loading Current Control Practice: Fixed or static DO Control Low NH 4 Loading Effluent Target - Ammonia bleed through during peak loading - Wasted power during low loading Distance Along Aeration Tank High NH 4 Loading High DO Set Point Low NH 4 Loading Low DO Set Point Distance Along Aeration Tank Ammonium-based Control: Dynamic DO Control - Lower power required during low loading - Consistently low DO in last zone - Stabilized process Effluent Target

19 Nitrate Recycle Optimization NO 3 Influent = Q NH 4, BOD anoxic NO 3 +BOD -> N 2 + Cell growth aerated NH 4 +O 2 -> NO 3 BOD+O2 -> Cell growth Effluent = Q NO 3 IMLR = 2-5*Q IMLR control maximizes total nitrogen removal by optimizing the performance of the pre-anoxic zone Under loaded pre-anoxic zone (due to insufficient recycle flow rate) does not complete denitrification Over loaded pre-anoxic zone carries excess nitrate through the system and can negatively impact nitrification

20 Denver MWRD North Secondary 80 MGD average daily flow 4 quads, 3 trains per quad BIOS Control Baseline

21 Activated Sludge Model Description Physical Characteristics

22 RESULTS Ammonium (infl. loading/effl. conc.) Airflow Average DO Set Points

23 BIOS Aeration Savings 11% aeration savings 13.5% aeration savings 6% aeration savings Baseline DO set points lowered by operations DCS Upgrade Week 22-26

24 SND Potential 7% Nitrate Reduction

25 Ammonia Loading (lbs/day) Analyzer Data Analysis s (99.85 Percentile) 1s (84.1 Percentile) Average (50 Percentile) -1s (15.9 Percentile) s (0.15 Percentile) Normal Distribution Chart % of the data is between 1s and -1s 99.7% of the data is between 3s and -3s 0 0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00 0:00 TIME

26 MWRD Performance Data

27 Results Installed and running the pilot within 3 Months Estimated aeration savings during pilot 11% Estimated Yearly Savings $134,000 Thirty-six (36) individual calculated DO set-points. Twelve (12) individual ammonia effluent set points Two (2) sets of NH4 analyzers for control; one (1) set for comparison by DCS. Use of analyzer data analysis for fault detection and backup Ammonia removal rate auto tuning to ensure that the effluent ammonia is as close to the effluent target as possible.

28 Lebanon Process Controller 8 MGD BNR Upgrade MLE (IFAS) with post anoxic Ammonium & Nitrate Analyzers DO Meters in all swing and IFAS Zones

29 Lebanon Process Controller Plant Description Four process trains Trickling filter bypass for carbon addition Four 200 HP single stage centrifugal blowers Process Control System DO set point control Swing zone control IMLR control Trickling filter bypass control

30 Lebanon Control Objective Optimally utilize the plant capacity to meet effluent permit requirements with the lowest possible energy and chemical consumption and without system disruptions Switch swing zones on/off based on aerobic demand Determine optimal DO set point in each zone Maintain DO set points in IFAS zones and swing zones Control blowers to meet total demand Control air flow to each zone Minimize aeration system pressure using most-openvalve logic Control mixed liquor recycle to manage denitrification Control trickling filter bypass to provide carbon in anoxic zones as needed

31 Results: Aeration Control Swing zone on/off control with MOV control Header Pressure 7.4 psi IFAS Zone: DO actual and set point 6.8 psi Swing Zone: DO actual and set point

32 Results: Ammonia Control Influent Ammonia (Anoxic) Effluent Ammonia

33 Results: Ammonia Control Influent Ammonia Effluent Ammonia IFAS Zone: DO set point Swing Zone: DO set point

34 Results: Denitrification Control TF bypass flow IMLR flow Nitrate set point Nitrate leaving anoxic zone

35 Summary Aeration control, ammonia control and denitrification control in one integrated control package Combination swing zones and IFAS zones aerated based on aerobic capacity requirements Flow-based blower control MOV control on combined coarse and fine bubble diffusers on common air header Denitrification control through active control of mixed liquor recycle and carbon shunt

36 Results: Energy Savings DO set point control (ammonia control) saves approx. 15% of aeration energy MOV control saves approx. 4% of aeration energy Nitrate recycle pumping minimized to reduce pump energy The plant consistently meets permit.

37 Lebanon Aeration Energy Savings Calculated Savings at Lebanon: o Process Control: 15% vs. fixed DO set-points o Aeration Control: additional 9% savings vs. constant pressure through flow-based mostopen-valve control

38 IRQ IRQ IRQ IRQ Enfield WWTP Case Study Influent + RAS #1 #2 #3 #4 NH 4 + Enfield, CT 10 MGD (40,000 m 3 /d) capacity 5.5 MGD (22,000 m 3 /d) ADF NH 4 + NO 3 - NH 4 +/ NO 3 -

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40 Effluent TIN [mg/l] Average TIN Improvement with BIOS = 37.6% /15 2/22 2/29 3/7 3/14 3/21 3/28 4/4 4/11 with BIOS Control Constant DO and IRQ Settings

41 Summary Ammonia based feed-forward process control o Provides stable operation o Can be applied to any plant size and configuration and be tailored to meet the needs of the operator o Adds intelligence to your system o Optimizes TN removal o Saves 10 to 15% aeration energy

42 Strategic Objectives/Next Steps Develop plug-and-play BIOS for smaller plants Develop one or several strategic partnerships with ESCOs, contract operators, utilities Process equipment manufacturers: water conglomerates, diffuser, blower, instrument manufacturers Develop market presence in Western USA Projects Partners, manufacturers reps,

43 Thank You More information at: or