Energy Submetering at WRRFs October 2017 October 2017 Nancy - PowerPoint PPT Presentation

weftec 2017 | 90 th Annual WEFTEC Conference we Energy Submetering at WRRFs October 2017 October 2017 Nancy Andrews rews

Survey Data Indicates Operations Frequently Implement Energy Monitoring Not Implemente ted d Due to 10 12 18 13 25 Other Barriers Not Implemente ted d Due to Lack of 3 4 6 3 9 Financ ncial ial Viabi bili lity ty Not Applicabl ble or 5 5 10 13 16 Techni nically ally Feasible ble Change Made 114 103 70 66 27 Not Consider ered ed 16 27 39 48 67 Digester Other Secondary DO Opti timi mizatio tion Energy Enhanced Opti timizatio tion Treatmen ent t Changes Monito torin ing Primary Treatmen ent 2

Barriers to Operations Initiatives Less than 5 mgd Greater than 5 mgd Prioritizing permit compliance Lack of support from decision Going beyond compliance maker 8.00 We don't want to be the first to Operational conservatism 7.00 try a new operating strategy 6.00 5.00 Energy efficiency is not 4.00 considered sufficiently Lack of energy data 3.00 important 2.00 1.00 0.00 New technologies lack track Lack of operation staff time records Insufficient training and Lack of technical support knowledge Energy data are from various Insufficient operator response sources and have long lag to high energy use times 3

Energy Culture Reduces Barriers to Operations Initiatives Developed Energy Programs Undeveloped Energy Programs Lack of support from decision maker 8.00 We don't want to be the first to try 7.00 Operation conservatism a new operating strategy 6.00 5.00 4.00 Energy efficiency is not Lack of energy data considered sufficiently important 3.00 2.00 1.00 0.00 New technologies lack track of Lack of operation staff time records Insufficient training and Lack of technical support knowledge Energy data are from various Slow response from operators to sources and have long lag times make adjustments when needed 4

Brown and Caldwell 5

Pump Energy Brown and Caldwell | 90th Annual WEFTEC Conference 6

Pump Efficiency Degrades Due to Internal Recirculation Pump discharge Pump suction Recirculation Brown and Caldwell | 90th Annual WEFTEC Conference 7

Pump Wear Increases Power Consumption Brown and Caldwell | 90th Annual WEFTEC Conference 8

Pump Efficiency Increased by Routine Maintenance Brown and Caldwell | 90th Annual WEFTEC Conference 9

10 Example Pump Station Instrumentation Schematic

SCADA Data Tracks Energy Impairments Flow Power er Pressure essure Speed eed Sympt mptom om Likely y Root t Cause se High Power Pipe Obstructed or Pump Impairment High Pressure Pipe Obstructed Sagging Pump Curve Pump Wear or Impairment High Speed Line Obstructed or Pump Impairment High Speed without High Pressure Pump Impairment CSWEA | 5-12-10 11

12 Benchmark Equation Derived from Power Data 350 4/21/10, 5/3/10 7/1/10 to 7/21/10 330 7/24/10 - 7/26/10 7/27/10 - 8/7/10 310 8/19/10 11/2/10 - 11/5/10 290 Poly. (11/2/10 - 11/5/10) 270 er, kW Pump power performance target for sample real-time flow Power 250 230 210 y = 0.2717x 2 + 0.4799x + 99.637 R² = 0.9775 190 Sample real-time flow rate 170 150 12 14 16 18 20 22 24 26 28 Flow, mgd

13 Power Performance Compared to Power Target 350 4/21/10, 5/3/10 7/1/10 to 7/21/10 330 7/24/10 - 7/26/10 7/27/10 - 8/7/10 8/19/10 Sample operating condition 310 11/2/10 - 11/5/10 Poly. (11/2/10 - 11/5/10) 290 Percent of Target 235/215 = 109% 270 er, kW Power, 250 230 210 y = 0.2717x 2 + 0.4799x + 99.637 R² = 0.9775 190 Sample real-time flow rate 170 150 12 14 16 18 20 22 24 26 28 Flow, ow, mgd

14 Target Power Metric for Alarming Problems and Tracking Improvements Over Variable Flow Conditions 120% Pump Power Alarm Setting 115% Pump 3 cleaned mp Power 110% t - Pump 105% t of Target Pump impairment 100% returns cent Percen Target Pump 95% Performance Goal 90% 4/22/2010 4/27/2010 5/2/2010 5/7/2010 5/12/2010 5/17/2010 5/22/2010 5/27/2010

Leveraging Pump Data for Energy Reduction • Use flow vs. power curve to establish target conditions • Compare current conditions to shop drawing data to quantify wear conditions • Optimize wear ring maintenance to restore efficiency • Focus on largest pumps • Bias run hours toward most efficient pumps • Identify pump and forcemain obstructions • Abnormally high discharge pressure (force main) • Abnormally high speed or energy (pump) Brown and Caldwell | 90th Annual WEFTEC Conference 15

Aeration Blower Energy Brown and Caldwell | 90th Annual WEFTEC Conference 16

Expected factors affecting blower power relative to ideal behavior Blower 100% turndown inefficiency 90% 80% Blower minimum airflow Mixing limits 70% Minimum flow per diffuser er er Power 60% 50% Blower 40% 30% 20% “Ideal” 10% relationship 0% No Load 50% Load Design Load Oxygen gen Demand nd Removal (CBO BOD 5 and NH 3 ) Brown and Caldwell | 90th Annual WEFTEC Conference 17

Actual data is typically very scattered and power demand is flat or “non - ideal” Brown and Caldwell | 90th Annual WEFTEC Conference 18

MCES Metro plant appears to have a more pronounced slope Brown and Caldwell | 90th Annual WEFTEC Conference 19

MCES Metro “slope” is actually driven by seasonal effects Summer Nitrification Winter Carbonaceous Brown and Caldwell | 90th Annual WEFTEC Conference 20

Non-ideal response across observed loads 100% 90% Blower power less than expected at 80% peak load 70% Typical blower power modulation relative to load er Power er 60% 50% Blower 40% 30% 20% Ideal blower power relationship to load 10% 0% No Load 50% Load Design Load Oxygen gen Demand nd (CBO BOD 5 and N) Brown and Caldwell | 90th Annual WEFTEC Conference 21

Non-ideal response divided between aeration control and blower efficiency effects 100% 90% 80% 70% Typical blower power modulation relative to load er er Power 60% 50% Blower 40% 30% Non-ideal power due to inefficient blower 20% part-load operation Ideal blower power relationship to load 10% 0% No Load 50% Load Design Load Oxygen gen Demand nd (CBO BOD 5 and N) Brown and Caldwell | 90th Annual WEFTEC Conference 22

Quantifying blower modulation efficiency 𝑄𝑠𝑝𝑑𝑓𝑡𝑡 𝑁𝑝𝑒𝑣𝑚𝑏𝑢𝑗𝑝𝑜 𝐹𝑔𝑔𝑗𝑑𝑗𝑓𝑜𝑑𝑧 = 𝑇𝑚𝑝𝑞𝑓 𝑏𝑑𝑢𝑣𝑏𝑚 𝑇𝑚𝑝𝑞𝑓 𝑗𝑒𝑓𝑏𝑚 Actual blower Ideal blower • Ideal slope assumes both variables rise proportionally • Process Modulation Efficiency is 100% if process is behaving ideally Brown and Caldwell | 90th Annual WEFTEC Conference 23

Statistical parameters show range of blower non-idealness and variability 𝐷𝑊 = 𝑇𝑢𝑏𝑜𝑒𝑏𝑠𝑒 𝐸𝑓𝑤𝑗𝑏𝑢𝑗𝑝𝑜 𝐵𝑤𝑓𝑠𝑏𝑕𝑓 MCES Metro Summer Littleton-Englewood Brightwater Brown and Caldwell | 90th Annual WEFTEC Conference 24

Non-ideal response divided between to aeration control and blower efficiency effects 100% 90% 80% 70% Typical blower power modulation relative to load er er Power 60% Non-ideal power due 50% to aeration control Blower limitations 40% 30% Non-ideal power due to inefficient blower 20% part-load operation Ideal blower power relationship to load 10% 0% No Load 50% Load Design Load Oxygen gen Demand nd (CBO BOD 5 and N) Brown and Caldwell | 90th Annual WEFTEC Conference 25

Overall process efficiency: Nitrifying WRRFs 𝑄𝑠𝑝𝑑𝑓𝑡𝑡 𝑁𝑝𝑒𝑣𝑚𝑏𝑢𝑗𝑝𝑜 𝐹𝑔𝑔𝑗𝑑𝑗𝑓𝑜𝑑𝑧 = 𝑃2 𝐸𝑓𝑛𝑏𝑜𝑒 𝑇𝑚𝑝𝑞𝑓 𝑏𝑑𝑢𝑣𝑏𝑚 𝑇𝑚𝑝𝑞𝑓 𝑗𝑒𝑓𝑏𝑚 Boulder, CO No Ammonia Control Grand Rapids, MI South Side Ammonia Control Brown and Caldwell | 90th Annual WEFTEC Conference 26

Overall process efficiency Boulder Grand Rapids North and South NYC DEP Jamaica Brown and Caldwell | 90th Annual WEFTEC Conference 27

Slightly higher response to peak load conditions at some plants 𝑀𝑝𝑏𝑒 𝑞𝑓𝑏𝑙𝑗𝑜𝑕 𝑔𝑏𝑑𝑢𝑝𝑠 = 99𝑢ℎ 𝑞𝑓𝑠𝑑𝑓𝑜𝑢𝑗𝑚𝑓 𝑚𝑝𝑏𝑒 𝐵𝑤𝑓𝑠𝑏𝑕𝑓 𝑚𝑝𝑏𝑒 𝐶𝑚𝑝𝑥𝑓𝑠 𝑞𝑝𝑥𝑓𝑠 ∗ 𝐶𝑚𝑝𝑥𝑓𝑠 𝑞𝑓𝑏𝑙𝑗𝑜𝑕 𝑔𝑏𝑑𝑢𝑝𝑠 = 𝐵𝑤𝑓𝑠𝑏𝑕𝑓 𝑐𝑚𝑝𝑥𝑓𝑠 𝑞𝑝𝑥𝑓𝑠 *on peak load days Brown and Caldwell | 90th Annual WEFTEC Conference 28

Significant blower energy correlation parameters Brown and Caldwell | 90th Annual WEFTEC Conference 29

Influent CBOD-normalized blower power can be used to benchmark energy performance Brown and Caldwell | 90th Annual WEFTEC Conference 30

Impact of primary TSS removal efficiency Brown and Caldwell | 90th Annual WEFTEC Conference 31