Operational Optimization: Water Losses versus Energy Costs

Management efficiency of water distribution networks (WDNs) is of relevant interest for the water industry, and operational optimization plays an important role. The energy to pump water is a significant element of operational costs and depends on electricity tariffs varying over time. As a result, pumping optimization accounting for electricity costs and relevant boundary conditions of a WDN, e.g., demands, is of practical interest. When the electricity tariffs are lower, for example, during the night hours, optimization generally results in pumping more water during those hours, if the presence of tanks, which are internal to the hydraulic system, allows for water storage. Nevertheless, the pressure and therefore, water leakage of the network greatly vary from night to daylight hours. Pressure and leakage generally increase in the night because of a lower level of demands and a greater level of pressures. Previous studies rarely account for this. This work investigates pumping optimization background leaks, i.e., the nonrevenue water cost beside the energy cost. It is shown and discussed that the reduction of background leaks conflict with, and generally dominate, energy cost. DOI: 10.1061/(ASCE)HY.1943- 7900.0000681. © 2013 American Society of Civil Engineers. CE Database subject headings: Water distribution systems; Pumps; Scheduling; Energy efficiency; Leakage; Optimization. Author keywords: Water distribution networks; Pump scheduling; Energy saving; Leakages.

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

[2]  Bryan W. Karney,et al.  Impacts of Leaks on Energy Consumption in Pumped Systems with Storage , 2005 .

[3]  Orazio Giustolisi,et al.  Scour depth modelling by a multi-objective evolutionary paradigm , 2011, Environ. Model. Softw..

[4]  Orazio Giustolisi,et al.  Pressure-Driven Demand and Leakage Simulation for Water Distribution Networks , 2008 .

[5]  M. A. Brdys,et al.  Operational Control of Water Systems: Structures, Algorithms, and Applications , 1994 .

[6]  Elaine C. Sadowski,et al.  Optimization of Water Supply System Operation , 1996 .

[7]  Jakobus E. van Zyl,et al.  Explicit Integration Method for Extended-Period Simulation of Water Distribution Systems , 2006 .

[8]  George Germanopoulos,et al.  A technical note on the inclusion of pressure dependent demand and leakage terms in water supply network models , 1985 .

[9]  Steven G. Buchberger,et al.  Intensity, Duration, and Frequency of Residential Water Demands , 1996 .

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

[11]  David H. Marks,et al.  Water Distribution Reliability: Simulation Methods , 1988 .

[12]  Thomas M. Walski Tips for Saving Energy in Pumping Operations , 1993 .

[13]  Orazio Giustolisi,et al.  Demand Components in Water Distribution Network Analysis , 2012 .

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

[15]  Ezio Todini,et al.  Extending the global gradient algorithm to unsteady flow extended period simulations of water distribution systems , 2011 .

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

[17]  Lindell Ormsbee,et al.  Computer-generated pumping schedules for satisfying operational objectives , 1993 .

[18]  Luigi Berardi,et al.  Generalizing WDN simulation models to variable tank levels , 2012 .

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

[20]  Kevin E Lansey,et al.  Optimal Control of Water Supply Pumping Systems , 1994 .

[21]  Luigi Berardi,et al.  An Excel-based solution to bring water distribution network analysis closer to users , 2011 .