San Francisco is the only coastal city in California with a combined sewer and storm water system that collects and treats both wastewater and storm water. This quirk makes it necessary to create enough storm water freeboard for an upcoming rain event ahead of time to keep from flooding the city combined storm water sewer system, which—with enough contributors—could overflow into the bay. A predictive weather algorithm customized by Envise allows the Moscone Center water treatment plant to intelligently apportion water levels among the holding tanks to prepare for a rain event before it arrives.
Envise configured the system to receive internet weather data from multiple redundant sources and provide the following input points to the monitoring system: previous day’s precipitation, current hour’s precipitation, today’s precipitation, forecast precipitation (current, tomorrow, and next nine days).
The predictive weather data interfaces seamlessly with the Envise controls of the facility using high resolution, high frequency weather data compiled from NOAA MADIS Stations, FAA automated surface observation stations at nearby airports, and certain private weather stations. Using trusted data from multiple sources provides us with a durable system accuracy not available with an on-site measuring solution.
The custom Moscone integration module was built up from the Delta data transfer module, which enables Envise to pull external data from any external non-BACnet system for use in logic calculations. “BAS integration with a custom BACnet solution gave us an opportunity to provide a custom weather data solution at much lower cost than alternative dedicated weather data services,” says Zev Hauser, project controls engineer. We evaluated an off the shelf system for integration but the lack of custom implementation and ongoing monthly fees were a big turn off for the owner (our system has no monthly fees!).
So, let’s say that tomorrow, San Francisco is expected to receive one inch of rainfall. The predictive weather data determines required storm water freeboard – our storage availability for a rain event. To maintain incoming freeboard in our main raw water tank we can predictively lower the tank height setpoint to gradually bleed it down and transfer to other locations ahead of time. The system gradually and automatically transfers water among the raw water tank, treated water tank, and garden cisterns as needed.
Our programming is focused on the next 12 hours. We have calculated freeboard volume available to us in the raw water incoming tank after our system proactively diverts water to drain or transfer. The raw water tank is fed by storm water piping, steam condensate, and ground water de-watering. As the piping network begins to fill the tank with rain water our systems are continuously monitoring tank level with ultrasonic level sensors. If we run low on freeboard, we transfer water to the treated water tank, and as a last resort to the garden cisterns. Our raw water tank is approximately 70,000 gallons and our treated water tank is approximately 40,000. “Approximately” because the tanks are actual concrete rooms that were coated with heavy industrial epoxy rubber for waterproofing.
The Moscone expansion roof is approximately 67,000 square feet and an annual rainwater collection of approximately 755,000 gallons is expected, however we know California weather can be dry, so this might be flexible. Since the rainwater inlet to the raw water collection tank will have partial flow most of the time, we meter it using an area velocity flow meter. This meter type is good for irregular, open channel flow measurement for part filled pipe with automatic temperature compensation. The steam condensate and ground dewatering sources utilize direct coupled turbine meters. The contributions to the system from each source are trending over time and facility operations will be able to compare them during annual utility reviews.
The Moscone on-site treatment plant is a real value to the facility. Not only does the treatment plant feed into water reuse—a benefit in a climate that is familiar with long term drought—but it also helps protect the health of the bay from the ecological impacts of runoff. By combining parts with smarts our Envise group was able to create a custom solution that is fully automatic and trackable. Utilizing redundant accuracy of multiple sources, we look forward to successful operation for years to come.
What are your thoughts on using predictive weather technology to operate your facility? Share your ideas in the comments section.
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