Optimal Scheduling of Replacement and Rehabilitation in Wastewater Pipeline Networks
Publication: Journal of Water Resources Planning and Management
Volume 136, Issue 3
Abstract
To fulfill the objective of providing acceptable level of service to customers, the water managers have to plan how to operate, maintain, and rehabilitate the system under budget constraints. The model presented in this paper uses risk cost as an appropriate framework to define the optimal replacement time prediction based on the balance between investment for replacing and expenditures for maintaining the asset. An economic analysis compares the costs associated with maintaining an existing pipe in service, being completely depreciated or not, to the cost of replacing or rehabilitating the pipe. On this basis, the right time in the future to rehabilitate the pipeline can be determined. The costs associated with an existing pipe include direct operational and maintenance costs and indirect costs, such as those associated with risk of failure. The optimal replacement time is identified as the year in which the cost to maintain the existing stock of pipes exceeds the investment to replace it. A dynamic programming tool was developed to search the vast combinatorial solution space of the problem. The model was applied, with the aim of supporting management decisions, to the wastewater network of Oslo in Norway, managed by Oslo Vann og Avløpsetaten, using available real-world information to estimate expected costs of maintenance and rehabilitation. The results show that a constant value for lifetime should not be applied to all the pipelines in the stock, as currently done by the utility for long-term investment; rather it is wiser to define different values for different cohorts of pipelines to reduce the uncertainties associated with generalizations for simplification. The model has been applied to wastewater pipes but is in principle valid for any aging infrastructure.
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Acknowledgments
The writers would like to thank the personnel at the Oslo VAV for providing the data for model application and for their kind support during the course of this study. The encouragement of our colleagues at SINTEF and NTNU is gratefully acknowledged.
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© 2010 ASCE.
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Received: Dec 5, 2008
Accepted: Jun 25, 2009
Published online: Jun 29, 2009
Published in print: May 2010
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