本文介绍了污水泵的设计和实施结果 E&C Engineering开发的控制算法，适用于业主拥有和运营的泵站 加州的一家机构。对控制策略进行了优化，以最小化商业用电费用 同时满足泵送要求。太平洋天然气和电力公司（PG&E）提供商业服务 权力 为了最大限度地降低电力成本，在电费较低的时期，抽水量最大化 在高计费率期间最小化。 对于大用户，电力公司会为 能量（kWh）和最大使用量，或“需求”（峰值千瓦）。夏季，中午能量 （kWh）费率远高于夜间费率。此外，单一的短期高点 电力负荷条件将导致以下12个月的需求（峰值千瓦）费用增加 月。最大限度地减少高峰时段的运营可以节省大量资金。 该控制算法使用现场水库蓄水，将抽水推迟到较低的周期。 水库的模拟液位测量和净系统流量（流入-流出）信息 用于计算总体质量平衡以及填充或清空储液罐所需的时间。 这种计算是连续进行的，它还取决于基于 泵运行的数量。控制系统通过以下方式“过滤”瞬态条件: 泵送条件的变化在加或减之前等待一个可配置的间隔 泵。 根据一天中的时间和一周中的某一天，优化运行的泵的数量。 在峰值速率期间，泵运行的数量最小化，以确保所需的时间 所有水库的注水时间将尽可能接近下一个部分峰值 时期 该算法通过一个由10个恒速垂直泵组成的泵送系统实现 涡轮泵。系统存储容量由三个蓄水池提供，每个蓄水池有一个容量 800万至1100万加仑，总储存量为2900万加仑。包括数字。

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.