Deriving peak factors for residential indoor water demand by means of a probability based end-use model

[摘要] ENGLISH ABSTRACT: The expected peak water demand in a water distribution system (WDS) is an important consideration for WDS design purposes. In South Africa the most common method of estimating peak demand is by multiplying the average demand by a dimensionless peak factor. A peak factor is the ratio between the maximum flow rate (which refers to the largest volume of flow to be received during a relatively short time period, say , expressed as the average volume per unit time), and the average flow rate over an extended time period.The magnitude of the peak factor will vary, for a given daily water demand pattern, depending on the chosen value of . The design guidelines available give no clear indication of the time intervals most appropriate for different peak factor applications. It is therefore important to gain a better understanding regarding the effect of on the derived peak factor.A probability based end-use model was constructed as part of this study to derive diurnal residential indoor water demand patterns on a temporal scale of one second. These stochastically derived water demand patterns were subsequently used to calculate peak factors for different values of , varying from one second to one hour.The end-use model derived the water demand patterns by aggregating the synthesised end-use events of six residential indoor end-uses of water in terms of the water volume required, duration and the time of occurrence of each event. The probability distributions describing the end-use model parameters were derived from actual end-use measurements that had previously been collected in a noteworthy North-American end-use project (Mayer et al., 1999). The original comprehensive database, which included water measurements from both indoor and outdoor end-uses, was purchased for use in this project.A single execution of the end-use model resulted in the synthesised diurnal water demand pattern for a single household. The estimated water demand pattern for simultaneous water demand by groups of households was obtained by adding individual iterations of the end-use model, considering group sizes of between one and 2 000 households in the process. A total of 99 500 model executions were performed, which were statistically aggregated by applying the Monte Carlo method and forming 4 950 unique water demand scenarios representing 29 different household group sizes. For each of the 4 950 water demand scenarios, a set of peak factors was derived for eight selected values.The end-use model presented in this study yielded realistic indoor water demand estimations when compared to publications from literature. In agreement with existing knowledge, as expected, an inverse relationship was evident between the magnitude of the peak factors and . The peak factors across all time intervals were also found to be inversely related to the number of households, which agreed with other publications from literature. As the number of households increased, the degree to which the peak factor was affected by the time intervals decreased.This study explicitly demonstrated the effect of time intervals on peak factors. The results of this study could act as the basis for the derivation of a practical design guideline for estimating peak indoor flows in a WDS, and the work could be extended in future to include outdoor water demand and sensitivity to WDS pressure.

[发布机构] Stellenbosch University