This study discusses genetic algorithm (GA) optimization, a powerful, practical
tool that would assist utilities facing hard decisions about how to meet future
growth. GA optimization can be used to identify a range of feasible, low-cost
solutions that satisfy specific design and performance criteria. GA analysis fits
into the standard distribution system modeling and alternatives evaluation
approach 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 how
one city used GA optimization to identify the best overall water system expansion
plan to meet future needs. GA optimization considered such variables as location
and size of new pipes and storage; settings of pumps and flow control and
pressure-reducing valves; possible elimination of existing control valves, tanks,
and pump stations; and, the choice of supply rates from different water source
connections. The model optimized not only planned capital improvements (new
pipes, tanks, pumps, and valves) but also operational set points and schedules
for regulating valves and pumping operations. GA optimization regularly achieves
capital cost savings of 20-30%. Includes 12 references, table, figures.
| Edition : | Vol. 93 - No. 5 |
| File Size : | 1
file
, 280 KB |
| Note : | This product is unavailable in Ukraine, Russia, Belarus |
| Number of Pages : | 14 |
| Published : | 05/01/2001 |
