Probabilistic analysis of monthly peak factors in a regional water distribution system

[摘要] ENGLISH ABSTRACT: The design of a water supply system relies on the knowledge of the water demands of its specific end-users.It is also important to understand the end-users' temporal variation in water demand. Failure of the system toprovide the required volume of water at the required flow-rate is deemed a system failure. The systemtherefore needs to be designed with sufficient capacity to ensure that it is able to supply the required volumeof water during the highest demand periods. In practice, bulk water supply systems do not have to cater forthe high frequency, short duration high peak demand scenarios of the end-user, such as the peak hour or peakday events, as the impact of events is reduced by the provision of water storage capacity at the off-take fromthe bulk supply system. However, for peak demand scenarios with durations longer than an hour or a day,depending on the situation, the provision of sufficient storage capacity to reduce the impact on the bulk watersystem, becomes impractical and could lead to potential water quality issues during low demand periods. Itis, therefore, a requirement that bulk water systems be designed to be able to meet the peak weekly or peakmonth end-user demands. These peak demand scenarios usually occur only during a certain portion of theyear, generally concentrated in a two to three month period during the drier months. Existing designguidelines usually follow a deterministic design approach, whereby a suitable DPF is applied to the averageannual daily system demand in order to determine the expected peak demand on the system. This DPF doesnot account for the potential variability in end-user demand profiles, or the impact that end-storage has onthe required peak design factor of the bulk system.This study investigated the temporal variations of end-user demand on two bulk water supply systems. Thesesystems are located in the winter rainfall region of the Western Cape province of South Africa. The dataanalysed was the monthly measured consumption figures of different end-users supplied from the twosystems. The data-sets extended over 14 years of data. Actual monthly peak factors were extracted from thisdata and used in deterministic and probabilistic methods to determine the expected monthly peak factor forboth the end-user and the system design. The probabilistic method made use of a Monte Carlo analysis,whereby the actual recorded monthly peak factor for each end-user per bulk system was used as an input intodiscrete probability functions. The Monte Carlo analysis executed 1 500 000 iterations in order to produceprobability distributions of the monthly peak factors for each system. The deterministic and probabilisticresults were compared to the actual monthly peak factors as calculated from the existing water use data, aswell as against current DPFs as published in guidelines used in the industry. The study demonstrated that thedeterministic method would overstate the expected peak system demand and result in an oversized system.The probabilistic method yielded good results and compared well with the actual monthly peak factors. It isthus deemed an appropriate tool to use to determine the required DPF of a bulk water system for a chosenreliability of supply. The study also indicated the DPFs proposed by current guidelines to be too low. Thestudy identified a potential relationship between the average demand of an end-user and the expectedmaximum monthly peak factor, whereas in current guidelines peak factors are not indicated as beinginfluenced by the end-user average demand.

[发布机构] Stellenbosch University