Speeding up the water distribution network design optimization using the ΔQ method

• Published in: Journal of hydroinformatics 2016-01, Vol.18 (1), p.33-48
• Main Authors: Ivetic, Damjan, Vasilic, Zeljko, Stanic, Milos, Prodanovic, Dusan
• Format: Article
• Language: English
• Subjects: Algorithms; Civil engineering; Computation; Computational efficiency; Computational fluid dynamics; Computers; Computing time; Corrections; Design optimization; Distribution; Distribution management; Evaluation; Flow velocity; Fluid flow; Genetic algorithms; Hydraulics; International conferences; Methods; Network design; Parallel processing; Software; Solutions; Solvers; Water distribution; Water engineering; Water shortages; Water supply
• ISSN: 1464-7141; 1465-1734
• DOI: 10.2166/hydro.2015.118

To optimize the design of a water distribution network (WDN), a large number of possible solutions need to be examined; hence computation efficiency is an important issue. To accelerate the computation, one can use more powerful computers, parallel computing systems with adapted hydraulic solvers, hybrid algorithms, more efficient hydraulic methods or any combination of these techniques. This paper explores the possibility to speed up optimization using variations of the ΔQ method to solve the network hydraulics. First, the ΔQ method was used inside the evaluation function where each tested alternative was hydraulically solved and ranked. Then, the convergence criterion was relived in order to reduce the computation time. Although the accuracy of the obtained hydraulic results was reduced, these were feasible and interesting solutions. Another modification was tested, where the ΔQ method was used just once to solve the hydraulics of the initial network, and the unknown flow corrections were added to the list of other unknown variables subject to optimization. Two case networks were used for testing and were compared to the results obtained using EPANET2. The obtained results have shown that the use of the ΔQ method in hydraulic computations can significantly accelerate the optimization of WDN.