Abstract: Carefully scheduling the operations of pumps can be
resulted to significant energy savings. Schedules can be defined
either implicit, in terms of other elements of the network such as tank
levels, or explicit by specifying the time during which each pump is
on/off. In this study, two new explicit representations based on timecontrolled
triggers were analyzed, where the maximum number of
pump switches was established beforehand, and the schedule may
contain fewer switches than the maximum. The optimal operation of
pumping stations was determined using a Jumping Particle Swarm
Optimization (JPSO) algorithm to achieve the minimum energy cost.
The model integrates JPSO optimizer and EPANET hydraulic
network solver. The optimal pump operation schedule of VanZyl
water distribution system was determined using the proposed model
and compared with those from Genetic and Ant Colony algorithms.
The results indicate that the proposed model utilizing the JPSO
algorithm is a versatile management model for the operation of realworld
water distribution system.
Abstract: This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial
Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water
flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by
sensors to construct an empirical model for time series prediction and
classification of events. These two components have been installed,
tested and verified in an experimental site in a UK water distribution
system. Verification of the system has been achieved from a series of
simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network
management.