Full Description

This study discusses genetic algorithm (GA) optimization, a powerful, practicaltool that would assist utilities facing hard decisions about how to meet futuregrowth. GA optimization can be used to identify a range of feasible, low-costsolutions that satisfy specific design and performance criteria. GA analysis fitsinto the standard distribution system modeling and alternatives evaluationapproach and offers the added benefit of minimizing a project's life-cycle costs.This study describes a case study from Grand Prairie, Texas, that demonstrates howone city used GA optimization to identify the best overall water system expansionplan to meet future needs. GA optimization considered such variables as locationand size of new pipes and storage; settings of pumps and flow control andpressure-reducing valves; possible elimination of existing control valves, tanks,and pump stations; and, the choice of supply rates from different water sourceconnections. The model optimized not only planned capital improvements (newpipes, tanks, pumps, and valves) but also operational set points and schedulesfor regulating valves and pumping operations. GA optimization regularly achievescapital cost savings of 20-30%. Includes 12 references, table, figures.

Product Details

Edition: Vol. 93 - No. 5 Published: 05/01/2001 Number of Pages: 14File Size: 1 file , 280 KB