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Optimizing LID Performance with Distributed Real-Time Controls
2011 National LID Symposium
Joe Jeray, Geosyntec Consultants, Inc.Kathy DeBusk, North Carolina State University
Alex Bedig, Geosyntec Consultants, Inc.
September 26, 2011
Presentation Outline
Project Objectives/Goals Technology Description
Distributed Real-Time Control (RTC) Systems
Site Description Monitoring and Control Setup Implementation and Control Logic Model Results Applications & Opportunities
Project Objective
Design and install a rainwater harvesting system equipped with real-time controls (RTC) to study the effectiveness of RTC systems for optimizing performance of stormwater control measures.
Develop and implement monitoring and control strategies using internet-based precipitation forecasts and site data.
What is an RTC system for stormwater?
Typical BMP/SCM implementation:
Overflow/Bypass
Volume Recovery/Drawdown
Runoff
Off-site drainage
CSS/SSS?Receiving stream?Downstream control?
What is an RTC system for stormwater?
BMP/SCM with RTC:
Volume Recovery/Drawdown
Runoff
Off-site drainage
CSS/SSS?Receiving stream?Downstream control?
RTCDry Weather Discharge
Technology Description
How do RTC systems work?Use latest computer hardware/software Exchange data in real-time over the internetMonitor system performanceOn-site measurements
Integrate external dataWeather forecasts Downstream monitoring
Optimize system based on current conditions
Costs/Benefits of RTC
Low cost (~$5k incremental cost) Performance-based approach to BMP design
Feedback mechanism Iterative design process Modify software/logic to achieve design goals Engineering design Software design Flexible and adaptable Field results Changes in design goals Additional research
Site Description
Pilot Site: Tryon Palace – New Bern, NC
Advanced rainwater harvesting system Collection Area: ~ 3,100 sf roof area
Total storage volume: ~3250 gallons
Five 650-gallon cisterns
Harvested water used for irrigation
Bioretention cell to manage overflow
Site Description
System Design Goals: Maximize on-site reuse
Minimize stormwater runoff
Peak flow attenuation
Research Goals Evaluate on-board logic
Effective use of forecast data
Evaluate performance as compared to passive systems
Controller during Tryon Palace Installation
Site Photos
Site Photos
Monitoring and Control Setup
ioBridge Pro monitor and control module
WIKA LS-10 pressure transducer
Omega FTB8010B-PT water meter
Plastomatic 1” solenoid valve (24 VDC)
Field Monitoring and Control(Sensors, Gauges, and Actuators)
Internet Based Weather Forecast or other data
sources (METSTAT or other Web service API
OptiRTC User Interface Web Services and User Dashboards
OptiRTC Data Aggregator and Decision
Space
Data Logging and Telemetry Solutions
EmailTweetSMS
Voice Autodial
Azure Tables/Blobs
Tryon Palace System Dashboard
Implementation & Control Logic
Goal: Optimize available storage volume Balance water conservation vs. runoff reduction
Strategy: Release water (if necessary) to rain garden during dry
weather prior to storm event Available storage volume = Anticipated runoff volume
Implementation & Control Logic
Inputs: 6-hr Quantitative Precipitation Forecast (QPF) - NOAA 12-hr Probability of precipitation (PoP) - NOAA Assumed volumetric runoff coefficient Water level in cisterns Additional “conservation factors”
Drain to ‘Set Point’
Basic Decision Logic
6-24 hrQPF
0-6 hrQPF Calculate
‘Set Point’
6-24 hrPoP
New Forecast Data?
No
Yes
=0? No
Yes
>70%?
No
Cistern Water Level
Water Level >
‘Set Point’?Yes
Yes
No
Runoff Hydrograph
Depth in Storage Tank
Performance During Smaller Event
Model Results
Runoff Hydrograph
Depth in Storage Tank
Performance During Large Event
Model Results
Applications & Opportunities
Other RTC opportunities Combined Sewer Overflow (CSO) Reduction Flood Control Peak flow attenuation
Mitigation of Geomorphic Impacts
Ongoing Research Other LID/Green infrastructure applications Large scale cost/benefit analysis
Opportunities for Additional Research
Flexible platform creates research opportunities Implement changes and receive immediate feedback
Real-time monitoring and data analysis
Quickly test multiple design options
Potential areas for expanded research Improved algorithm for using forecast data
Incorporate additional data sources
Network analysis – multiple controls in same drainage area
