The City of Chico, California wastewater treatment plant’s small and limited staff means automation is critical to the facilities ongoing processes, which are especially important to maintaining eight-hour work days for the WWTP workers. The automation systems they put into place worked well, but occasionally the breakpoint chlorination during the disinfection process would go out of range. Working with Ekster & Associates, three employees at the plant implemented an automatic ammonia control system to address dissolved oxygen issues in the plant.
James Carr, Chico WWTP manager, and Travis Elliott, Chico lead wastewater operator, discuss the city’s background, flow, and challenges with maintaining the facility with a small staff. Jim Hagstrom, Carollo Engineers managing director of technical practices, highlights how anticipated growth and real growth of the community created difficulties for the plant. And Alex Ekster, Ekster & Associates technical director, dives deep into the city’s automation systems and machine learning algorithm for automatic ammonia control.
- Intro: (0:00)
- City of Chico plant and project background: (0:51)
- Complications from expected and unrealized community growth: (4:10)
- What led Chico to work toward a dissolved oxygen algorithm?: (5:06)
- What the algorithm worked to solve for the city: (7:50)
- Operational challenges and budget constraints: (10:50)
- Primary obstacles in implementing the algorithm: (13:47)
- Obstacles from engineers and how it relates to national conversations: (14:55)
- Deep dive into the machine learning algorithm: (16:54)
- Why machine learning was better than a mechanistic model: (21:34)
- How did this shift the workload and what advice do you have for other utilities? (24:26)
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