An integrated planning tool for design of recycled water distribution networks

Pipeline design of urban recycled water networks involves thousands of decisions to ensure delivery of water to multiple use locations with pipelines and pump stations correctly located, optimally sized, and compatible with existing infrastructure. Here, we introduce PRODOT, Pipeline ROuting and Design Optimization Tool, software that identifies near-minimum-cost pipeline routes; accounts for existing configurations, legal, environmental or safety concerns, and trade-offs in pipeline length, pipe installation methods, traffic congestion during construction; optimizes pump station locations, pumping energy, pipe diameters and pressure classes; and includes theoretical additional capacity of each pipe, facilitating future expansion. We illustrate the utility of PRODOT with a case study for a local utility comparing PRODOT-generated configurations to a configuration proposed by an experienced consulting firm. The comparison shows that PRODOT produces pipeline configurations similar to the consulting firm's proposal with improvements by effectively and more broadly incorporating options the consultant may not have considered. Near-minimum-cost pipeline configurations for recycled water distribution systems.źsptimal pipe routing, diameters, pressure classes, pump locations, and energy demand.Inclusion of many pragmatic constraints typical of complex urban environments.Inclusion of theoretical additional capacity of each pipe for future expansion.Consistency with and improvement on the design of an experienced consulting firm.

[1]  Ali Asghar Alesheikh,et al.  Routing of Water Pipeline Using GIS and Genetic Algorithm , 2009 .

[2]  Tianjiao Guo,et al.  Principles for scaling of distributed direct potable water reuse systems: a modeling study. , 2015, Water research.

[3]  Angus R. Simpson,et al.  Improving the efficiency of multi-objective evolutionary algorithms through decomposition: An application to water distribution network design , 2015, Environ. Model. Softw..

[4]  Jason Luettinger,et al.  Geographic Information System-based Pipeline Route Selection Process , 2005 .

[5]  A. Lodi,et al.  On the optimal design of water distribution networks: a practical MINLP approach , 2012 .

[6]  Holger R. Maier,et al.  Improved genetic algorithm optimization of water distribution system design by incorporating domain knowledge , 2015, Environ. Model. Softw..

[7]  M. Mair,et al.  Improving Incomplete Water Distribution System Data , 2014 .

[8]  Fabrizio Grandoni,et al.  An improved LP-based approximation for steiner tree , 2010, STOC '10.

[9]  Alan Hutson,et al.  Route Selection for a $2.2 Billion Pipeline , 2012 .

[10]  Lawrence Davis,et al.  Genetic Algorithms and Simulated Annealing , 1987 .

[11]  Peter Steen Mikkelsen,et al.  A critical review of integrated urban water modelling - Urban drainage and beyond , 2014, Environ. Model. Softw..

[12]  Juan Cao,et al.  Image Registration based on Genetic Algorithm , 2013 .

[13]  Eun Jung Lee,et al.  Assessing the scale of resource recovery for centralized and satellite wastewater treatment. , 2013, Environmental science & technology.

[14]  Güzin Bayraksan,et al.  Reclaimed water distribution network design under temporal and spatial growth and demand uncertainties , 2013, Environ. Model. Softw..

[15]  Alex Zelikovsky,et al.  Tighter Bounds for Graph Steiner Tree Approximation , 2005, SIAM J. Discret. Math..

[16]  Feifei Zheng,et al.  An efficient decomposition and dual-stage multi-objective optimization method for water distribution systems with multiple supply sources , 2014, Environ. Model. Softw..

[17]  Margarida Vaz Pato,et al.  A three‐phase procedure for designing an irrigation system's water distribution network , 2000, Ann. Oper. Res..

[18]  Margarida Vaz Pato,et al.  An improved decomposition-based heuristic to design a water distribution network for an irrigation system , 2014, Ann. Oper. Res..

[19]  J. Mallela,et al.  Work Zone Road User Costs: Concepts and Applications , 2011 .

[20]  Hilde Meisingset,et al.  Optimization of Pipeline Routes , 2004 .

[21]  George Markowsky,et al.  A fast algorithm for Steiner trees , 1981, Acta Informatica.

[22]  Angus R. Simpson,et al.  A new breakthrough technology optimizes distribution system design and operation , 1995 .

[23]  Thomas M. Walski Planning-Level Capital Cost Estimates for Pumping , 2012 .

[24]  Guido Van Rossum,et al.  Python Tutorial , 1999 .

[25]  David Kendrick,et al.  GAMS, a user's guide , 1988, SGNM.

[26]  Francesco Orsi,et al.  Routeing of power lines through least-cost path analysis and multicriteria evaluation to minimise environmental impacts , 2011 .

[27]  Alex Zelikovsky,et al.  An 11/6-approximation algorithm for the network steiner problem , 1993, Algorithmica.