Optimal pipe replacement strategy based on break rate prediction through genetic programming for water distribution network

Abstract

Pipe breaks often occur in water distribution networks and result in large water loss and social-economic damage. To reduce the water loss and maintain the conveyance capability of a pipe network, pipes that experienced a severe break history are often necessary to be replaced. However, when to replace a pipe is a difficult problem to the management of water distribution system. This study took part of the water distribution network of Beijing as a case and collected the pipe properties and the pipe breaks data in recent years (2008–2011). A prediction model of pipe beak rate was first developed using genetic programming. Then, an economically optimal pipe replacement model was set up. Finally, the optimal pipe replacement time was determined by the model. The results could help the utility managers to make cost-effective pipe maintenance plans.