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New Directions In Real-time Control For Green Infrastructure Marcus Quigley, PE, D.WRE Aaron Poresky, PE Dan Pankani, PE. Thursday September 16, 2010. The Big Picture. What roles can and should technology play in addressing specific urban water control problems?
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New Directions In Real-time Control For Green InfrastructureMarcus Quigley, PE, D.WREAaron Poresky, PEDan Pankani, PE Thursday September 16, 2010
The Big Picture • What roles can and should technology play in addressing specific urban water control problems? • Can passive approaches achieve optimal solutions given the realities of the built environment? • What can we do with dynamic intelligent controls? • What is the state of the art? • Where are we heading? • What is the larger vision for Water Information Systems?
Initial ResearchReal-Time Tide Gate Retrofit for Salt Mash Restoration Patent # 60/850,600 and 11/869,927
Intelligent Distributed Infrastructure Forecast-Controlled Distributed Detention and On-Site Stormwater Use Systems
Local Manual Control Local Automatic Control Real-Time Control – EPA 2006 Automatic (Remote) Regional Control Supervisory Control Automatic System-wide Global Control Predictive System-wide Global Control
Recent Innovation by Others EmNet, Inc.(Timothy Ruggaber et al., 2008)
Conventional Underground Detention System Roof Runoff Passive Detention Discharge to Combined Sewer Overflow • Compulsory, distributed storage widespread • Substantial aggregate discharges during storms
Forecast-Controlled Distributed Detention Systems Roof Runoff Controlled Discharge to Combined Sewer Overflow • Installed Cost $3 - $4 per gallon • Cheaper, compelling retrofit opportunities
Intelligent Distributed Detention with Integrated Harvesting Systems Non-potable Use Irrigation Roof Runoff Controlled Discharge to Combined Sewer Overflow • Water savings benefit at low incremental cost • Mitigates total flows to Combined Sewers
Advanced Rainwater Harvesting Simplest Definition Drain storage in advance of predicted rainfall or other trigger
Modeling • Continuous simulation - USEPA SWMM 5 • Hourly rainfall data (DCA) • 3900 sf of roof area • Drain a 2500 gallon, 6-ft deep tank when full in 12 hours (orifice) • Both an uncontrolled cistern and a forecast controlled cistern were modeled • Selected model years: 01/1/1965 - 12/31/1974
Flow Comparison Baseline: Runoff without detention storage Uncontrolled Cistern: Runoff with passive orifice Controlled Cistern: Runoff with active orifice
Cistern Depths Controlled Cistern Depth Uncontrolled Cistern Depth
Tank Storage Volumes Uncontrolled Cistern Depth Controlled Cistern Depth
Cistern Depth Frequencies Mean Daily Water Depth = 0.064 feet Mean Daily Water Depth = 4.7 feet
Wet-Weather Runoff Volumes • Summation of runoff volume during times when baseline flow is greater than zero • Baseline runoff volume: • 12,680 cf/yr • Uncontrolled wet-weather runoff volume: • 11,326 cf/yr (11% reduction) • Controlled wet-weather runoff volume: • 3,899 cf/yr (69% reduction)
Flow Splitter/Filter Installed on Existing Downspout Inverted Siphon Downspout Design (Note: location of cistern is shown close to building for illustrative purposes only) Inverted Siphon Downspout Pipe (Extends 8’-10’ Above Ground Level) Flow During Cleaning Cycle or When Cistern Full Automated Cistern Drain Flow During Typical Use Proposed Connection to Combined Sewer 4” Automatic Drain Valve Open During Automated Cleaning Cycle and When Cistern is Full Existing Downspout Connection to Combined Sewer Flow During Emergency Bypass
Green Harvesting Cube • Automatic watering of green harvesting cube.
Water Budget Analysis • C • B • A
Water Budget Analysis • C • B • A
Technology Developments • Traditional RTC • Limited functionality • Abundant input and control relay devices • Size and form-factor issues • Advanced RTC • Wide-ranging, customizable functionality • Access to web-based information streams • Integrate modeling software • Ubiquitous remote access and control
OptiRTC/OptiStorm Solution • Uses Internet feeds (e.g., NWS Quantitative Precipitation Forecasts and POP) and real-time sensors to control detention function of water storage • Operate autonomously or as integrated system via server-side solution • Web interfaces can be independent of server-side solution.
Internet Based Weather Forecast or other data source or Web service API OptiStorm Data Warehouse Opti Storm Node OptiStormData Aggregator and Decision Space OptiStormUser Interface Web Services and User Dashboards Compete Harvesting System Monitoring and Control (Sensors, Valves, and Actuators)
SYSTEM 1 SYSTEM 2 SYSTEM 3 DECISION DATASET 1 DECISION DATASET 2 DECISION DATASET 3
System Operation • Interfaces with in-the-field measurement devices and internet data feeds • Logs data to internet connected servers • Runs models on logged data – producing “Decision Space” data • With measured data, decision-space data, and conditional logic… • Actuates devices in the field • Sends internet-based communications • Client-specific data visualization dashboards at optistorm.geosyntec.com (coming soon)
OptiRTC/OptiStorm is…. • A means for adding real-time monitoring, conditional decision-making, control, and communications to existing infrastructure • and making passive BMP technologies active • A method of making existing and future active BMP technologies adaptive to changing environmental conditions
Where are we headed – Short Term? • RTC modeled hydrograph matching • Embedded Models (VS-SWMM) • Actuated Green Roofs • Retrofit wetlands • Retrofit Flood Control Facilities • Etc…
The Really Big Picture Availability of an omnipresent physical computing aggregation, analysis, and actuation engine.