Conjunctive Management of Large-Scale Pressurized Water Distribution and Groundwater Systems in Semi-Arid Area with Parallel Genetic Algorithm

This study develops a production well management model for the conjunctive management of water resources in semi-arid areas. The management model integrates a large-scale pressurized water distribution system and a three-dimensional groundwater model under an optimization framework. The well pump operations optimization problem is formulated as a Boolean integer nonlinear programming (BINLP) problem to optimize the periodic 24-h pump on/off operations over a 1-week operation horizon. The management model considers multiple objectives and is solved by a parallel genetic algorithm (PGA) to overcome the difficulty of solving the BINLP problem. The PGA significantly reduces computation time for a case study in Chandler, Arizona. The Chandler water distribution model is built based on EPANET, and the Chandler three-dimension groundwater model is developed using MODFLOW. The high performance computing (HPC) of the genetic algorithm makes it possible to obtain 24-h real-time operations in the 7-day forecast model. The tank reliability, resilience, and vulnerability (R-R-V) are evaluated to infer the system reliability. The Pareto curve provides compromise solutions between the two competing objectives of energy reduction and pressure violation reduction.

[1]  U. Shamir,et al.  Design of optimal water distribution systems , 1977 .

[2]  R. L. Laney,et al.  Hydrogeology of the eastern part of the Salt River Valley area, Maricopa and Pinal Counties, Arizona , 1986 .

[3]  Jared L. Cohon,et al.  A Programming Model for Analysis of the Reliability, Resilience, and Vulnerability of a Water Supply Reservoir , 1986 .

[4]  Sophie Constans,et al.  Simulation and Control of Chlorine Levels in Water Distribution Networks , 2003 .

[5]  L. F. R. Reis,et al.  Water Supply Reservoir Operation by Combined Genetic Algorithm – Linear Programming (GA-LP) Approach , 2006 .

[6]  John W. Labadie,et al.  Optimal Operation of Multireservoir Systems: State-of-the-Art Review , 2004 .

[7]  D. Carroll.  Chemical laser modeling with genetic algorithms , 1996 .

[8]  William W.-G. Yeh,et al.  Reservoir Management and Operations Models: A State‐of‐the‐Art Review , 1985 .

[9]  Lindell Ormsbee,et al.  Nonlinear Heuristic for Pump Operations , 1995 .

[10]  Helena M. Ramos,et al.  Pressure Control for Leakage Minimisation in Water Distribution Systems Management , 2006 .

[11]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[12]  Nien-Sheng Hsu,et al.  WATER DISTRIBUTION NETWORK RELIABILITY: STOCHASTIC SIMULATION , 1996 .

[13]  Arlen W. Harbaugh,et al.  MODFLOW-2000, The U.S. Geological Survey Modular Ground-Water Model - User Guide to Modularization Concepts and the Ground-Water Flow Process , 2000 .

[14]  Larry W. Mays,et al.  Optimal Operation of Water Distribution Pumps Considering Water Quality , 2000 .

[15]  Dragan Savic,et al.  Genetic Algorithms for Least-Cost Design of Water Distribution Networks , 1997 .

[16]  Marios M. Polycarpou,et al.  Optimal Scheduling of Booster Disinfection in Water Distribution Systems , 1998 .

[17]  D. McKinney,et al.  Genetic algorithm solution of groundwater management models , 1994 .

[18]  D. McKinney,et al.  Approximate Mixed‐Integer Nonlinear Programming Methods for Optimal Aquifer Remediation Design , 1995 .

[19]  Avi Ostfeld,et al.  Optimal Operation of Multiquality Networks. II: Unsteady Conditions , 1993 .

[20]  Thomas M. Walski,et al.  Methodology for Improving Pump Operation Efficiency , 1989 .

[21]  Larry W. Mays,et al.  Battle of the network models: Epilogue , 1987 .

[22]  Daniel P. Loucks,et al.  Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation , 1982 .

[23]  Dan Rosbjerg,et al.  Choice of reliability, resilience and vulnerability estimators for risk assessments of water resources systems / Choix d’estimateurs de fiabilité, de résilience et de vulnérabilité pour les analyses de risque de systèmes de ressources en eau , 2004 .

[24]  Larry W. Mays,et al.  Water resources systems management tools , 2005 .

[25]  Jakobus E. van Zyl,et al.  Operational Optimization of Water Distribution Systems using a Hybrid Genetic Algorithm , 2004 .

[26]  Kevin E Lansey,et al.  Optimization of Water Distribution Network Design Using the Shuffled Frog Leaping Algorithm , 2003 .

[27]  Frank T.-C. Tsai,et al.  Optimization of Water Distribution and Water Quality by Hybrid Genetic Algorithm , 2005 .

[28]  William W.-G. Yeh,et al.  Planned Operation of Large-Scale Water-Distribution System , 1995 .

[29]  Avi Ostfeld,et al.  Optimal Operation of Multiquality Networks. I: Steady-State Conditions , 1993 .

[30]  A. Simpson,et al.  An Improved Genetic Algorithm for Pipe Network Optimization , 1996 .

[31]  Leon S. Lasdon,et al.  Solving nonlinear water management models using a combined genetic algorithm and linear programming approach , 2001 .

[32]  Robin Wardlaw,et al.  Multireservoir Systems Optimization Using Genetic Algorithms: Case Study , 2000 .

[33]  AD Savic,et al.  Genetic Algorithm Optimization of Large Water Distribution System Expansion , 1999 .

[34]  Ravindra K. Ahuja,et al.  Network Flows: Theory, Algorithms, and Applications , 1993 .

[35]  S. Ranjithan,et al.  Using genetic algorithms to solve a multiple objective groundwater pollution containment problem , 1994 .