Optimal operation of water distribution networks with intermediate storage facilities

Abstract The nexus between water and energy reveals that transporting water for end use is a highly energy intensive operation. In this work we consider the optimal operation of a water distribution network consisting of pumps delivering water to different reservoirs, with each reservoir catering to a time varying demand. Pumps and ON/OFF valves are used as manipulated variables to minimize energy consumption while meeting the demand. Due to the nonlinear nature of the pump operating curve and the hydraulics, this results in a Mixed Integer Nonlinear Program (MINLP). We propose a three step decomposition approach to solve this problem efficiently. The applicability of this technique is demonstrated on a water network proposed for a municipality in India and the potential advantages are reported. We also compare the solution times required for the proposed technique and a standard solver and demonstrate the efficiency of the proposed approach.

[1]  F. Glover.  IMPROVED LINEAR INTEGER PROGRAMMING FORMULATIONS OF NONLINEAR INTEGER PROBLEMS , 1975 .

[2]  Luigi Berardi,et al.  Modeling Local Water Storages Delivering Customer Demands in WDN Models , 2014 .

[3]  Kevin E Lansey,et al.  Optimal Pump Operations Considering Pump Switches , 1994 .

[4]  Christian von Lücken,et al.  Multi-objective pump scheduling optimisation using evolutionary strategies , 2005, Adv. Eng. Softw..

[5]  Pramod R. Bhave,et al.  Analysis of Water Distribution Networks , 2006 .

[6]  József Gergely Bene,et al.  Optimal (short-term) pump schedule detection for water distribution systems by neutral evolutionary search , 2012, Appl. Soft Comput..

[7]  C. M. Fontanazza,et al.  A model of the filling process of an intermittent distribution network , 2010 .

[8]  Kala Vairavamoorthy,et al.  Intermittent Water Supply under Water Scarcity Situations , 2007 .

[9]  Adil M. Bagirov,et al.  An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling , 2013, Math. Comput. Model..

[10]  Paul Jowitt,et al.  Optimal Pump Scheduling in Water‐Supply Networks , 1992 .

[11]  G Waterworth,et al.  Comparison of Methods of Pump Scheduling in Water Supply Systems , 2001 .

[12]  L. Reynolds,et al.  The energy-efficiency benefits of pump-scheduling optimization for potable water supplies , 2009, IBM J. Res. Dev..

[13]  Anthony J. Tarquin,et al.  Optimal Pump Operation in Water Distribution , 1989 .

[14]  M. López-Ibáñez,et al.  Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks , 2008 .

[15]  Andrea Lodi,et al.  Mathematical programming techniques in water network optimization , 2015, Eur. J. Oper. Res..

[16]  Akihiro Kishimoto,et al.  A Lagrangian decomposition approach for the pump scheduling problem in water networks , 2015, Eur. J. Oper. Res..

[17]  Helena Mala-Jetmarova,et al.  Lost in optimisation of water distribution systems? A literature review of system operation , 2017, Environ. Model. Softw..

[18]  Sung-Pil Hong,et al.  A precision pump schedule optimization for the water supply networks with small buffers , 2017 .

[19]  Fengqi You,et al.  Energy optimization of water supply system scheduling: Novel MINLP model and efficient global optimization algorithm , 2016 .

[20]  Lijun Zhang,et al.  Model predictive control strategy of energy-water management in urban households , 2016 .

[21]  Bharadwaj S. Amrutur,et al.  WaterOpt: a method for checking near-feasibility of continuous water supply , 2016, 2016 International Workshop on Cyber-physical Systems for Smart Water Networks (CySWater).

[22]  Ben Paechter,et al.  Optimal pump scheduling: Representation and multiple objectives , 2005 .

[23]  Jorge J. Moré,et al.  The NEOS Server , 1998 .

[24]  P. S. Kelkar,et al.  Influence of Intermittent and Continuous Modes of Water Supply on Domestic Water Consumption , 2009 .

[25]  Nadia Maïzi,et al.  A convex mathematical program for pump scheduling in a class of branched water networks , 2017 .

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

[27]  Alberto Bemporad,et al.  Uncertainty-aware demand management of water distribution networks in deregulated energy markets , 2018, Environ. Model. Softw..

[28]  José M. Pinto,et al.  A novel continuous time representation for the scheduling of pipeline systems with pumping yield rate constraints , 2008, Comput. Chem. Eng..

[29]  Flávio Neves,et al.  A mixed integer programming approach for scheduling commodities in a pipeline , 2004, Comput. Chem. Eng..

[30]  Elizabeth D. Dolan,et al.  NEOS Server 4.0 Administrative Guide , 2001, ArXiv.

[31]  E. Kumpel,et al.  Intermittent Water Supply: Prevalence, Practice, and Microbial Water Quality. , 2016, Environmental science & technology.

[32]  S. Mohan Kumar,et al.  Optimal control of water distribution networks with storage facilities , 2015 .

[33]  William Gropp,et al.  Optimization environments and the NEOS server , 1997 .

[34]  Joe Naoum-Sawaya,et al.  Simulation-optimization approaches for water pump scheduling and pipe replacement problems , 2015, Eur. J. Oper. Res..

[35]  Bharadwaj S. Amrutur,et al.  Towards an IoT based water management system for a campus , 2015, 2015 IEEE First International Smart Cities Conference (ISC2).

[36]  Jaime Cerdá,et al.  MINLP model for the detailed scheduling of refined products pipelines with flow rate dependent pumping costs , 2015, Comput. Chem. Eng..

[37]  Marc C. Steinbach,et al.  Optimization models for operative planning in drinking water networks , 2009 .

[38]  Jaime Cerdá,et al.  Optimal scheduling of multiproduct pipeline systems using a non-discrete MILP formulation , 2004, Comput. Chem. Eng..