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This paper presents results obtained from the design and implementation of a sewage pumping control algorithm developed by E&C Engineering for a pumping station owned and operated by a California agency. The control strategy was optimized to minimize commercial power charges while meeting pumping requirements. Pacific Gas and Electric (PG&E) provides commercial power. To minimize electrical costs, pumping was maximized during low electric billing periods, and minimized during high billing rate periods. For large users, power companies billed for energy (kWh) and maximum usage, or "demand" (peak kW). Summertime, mid-day energy (kWh) rates were considerably higher than night-time rates. Furthermore, a single, short-term high electrical load condition will result in increased demand (peak kW) charges for the following 12 months. Minimizing operations during peak rate periods can provide significant savings. The control algorithm uses onsite reservoir storage to defer pumping to lower rate period(s). Analog level measurement at the reservoirs and net system flow (flow in - flow out) information is used to calculate the overall mass balance and the time required to fill or empty the reservoirs. This calculation is performed continuously, and it also depends on the pumping rate based on the number of pumps running. Transient conditions are "filtered" by the control system by requiring that a change in pumping condition wait for a configurable interval prior to adding or subtracting pump(s). Based on the time of day and day of the week, the number of pumps running is optimized. During peak rate periods, the number of pumps running is minimized such that the time required to fill all reservoirs will be as close as possible to the time until the next partial-peak billing period. The algorithm was implemented with a pumping system consisting of 10 constant-speed vertical turbine pumps. The system storage capacity is provided by three reservoirs each with a volume between 8 and 11 million gallons, for a total storage of 29 million gallons. Includes figures.