CCWI2017: F38 'Real-time Whole-cost Optimization of Water Production and Distribution'
2017-09-01T15:07:21Z (GMT) by
Optimizing water production and distribution in near real-time can result in significant savings in energy and chemical costs. This paper presents a novel, generic optimization framework, based on a single-solution meta-heuristic optimization algorithm called modified hybrid discrete dynamically dimensioned search (MHD-DDS). The optimization framework finds optimal settings for all stations in the network and optimal frequencies for all variable-speed driven pumps (VSP) for the 24 hours following the optimization run start. Tampere water supply system was used as a large-scale case- study, and the optimization was able to reduce production and distribution costs by almost 20 % while ensuring better quality of service (QoS) than before.