Examining the Energy Performance Associated With Typical Pipe Unit Head Loss Thresholds

Abstract

The energy performance of water mains is rarely used as a criterion for pipe rehabilitation decisions, yet there is a need to identify the worst-performing pipes to target investment wisely. This study links pipe characteristics with energy performance to understand how traditional pipe replacement thresholds perform in terms of energy. A cross-correlation analysis between pipe characteristics and pipe energy performance metrics, using a benchmarking data set of more than 20,000 water mains from 17 distribution systems, showed that unit head loss is closely related to net energy efficiency and the energy lost to friction (ELTF) in pipes, along with flow. Under average flow conditions, 3.2% of the pipes exceeded 3 m/km (ft/1,000 ft) of unit head loss, with 1.1% exceeding the more stringent 10 m/km threshold. Over 90% of pipes have a unit head loss below 1 m/km, which corresponds to an ELTF of 1.9%.

Effect of Pipe Size and Location on Water-Main Head Loss in Water Distribution Systems

“…However, it is noted thatHashemi et al (2018 b) found that the results for calibrated and un-calibrated systems exhibit the same patterns. Since the calibrated values are ranked based on relative value, the effect of calibration is dwarfed by the effect of the ranking method used for Spearman's method.ResultsFurther investigation in the present study, based on the extensive statistical analysis byHashemi et al (2018a), revealed that ranking of the data exhibits a non-linear correlation between hydraulic proximity (x-axis) and unit headloss (y-axis) for different pipe sizes, shown inFigure 1. Smaller ranks on hydraulic proximity axis represent higher values of hydraulic proximity and pipes closer to a water source such as a booster station, elevated storage or a treatment plant, while, larger ranks represent pipes at the periphery of the network that experience smaller flows and pressure.…”

“…A pipe with a normalized proximity near 1.0 indicates the highest proximity to major components, and vice versa. Moreover, based on statistical analysis performed by Hashemi et al (2018a), Spearman's ranks of proximity and unit headloss were chosen, to capture the non-linear relationships between Hydraulic Proximity and Unit Headloss. Spearman's rank method uses the rank of each value, instead of the actual value.…”