Energy Saving Through Optimizing Parallel Pump Schedule at a Large-Scale Water Supply Station: A Case Study

Abstract

Diverse state-of-the-art methods can be utilized to reduce energy consumption in water supply and distribution systems, including using high-efficiency equipment, shifting energy use away from peak demand times, energy recovery and storage devices, and renewable energy. However, the benefit of using high efficiency equipment can sometimes never be completely realized, as the performance of the individual pumps within a site can be reduced from optimal owing to a variety of reasons: a lower operating rate of the water treatment plant than the design flow rate, hydraulic conditions such as pipeline resistance or determined pressure, and pump scheduling. This research focused on optimizing pump scheduling through real-time monitoring utilizing smart temperature and pressure sensors, wireless low-power data communicators, and a pump data analysis algorithm to determine the hydraulic efficiency from thermodynamic state variables with subsequent parallel pump optimization. Thermodynamic pump performance measurements provided real-time information, including flow rate, specific power, and pump efficiency, in both individual and parallel pump operations. Evaluation of the specific power under diverse parallel pump operation scenarios demonstrated a variation of 0.115–0.140 kWh/m3 in the range of 7,800–10,100 m3/h. However, the deviation in specific power was more than 17% when operating at less than 7,800 m3/h and more than 10,000 m3/h. The summary of the pump combination operation suggested that energy could be saved by up to 15% by optimum pump scheduling, that is, no capital investment, simple optimization of control through thermodynamic state variable measurement, analysis, and feedback.

Keywords: Energy saving, parallel pump operation, pump scheduling, real-time monitoring, sensor