TY - GEN
T1 - A Graph Theory Modelling Approach for the Optimal Operation of Water Distribution Systems under Water Quality Constraints
AU - Price, Eyal
AU - Ostfeld, Avi
N1 - Publisher Copyright: © ASCE.
PY - 2016
Y1 - 2016
N2 - Optimal water system operation, including hydraulic and water quality constraints are complex problems to solve due to the nonlinear relationship of head-loss to flow and disinfectant-loss to time. A common approach used today is evolutionary algorithms (EA) such as genetic algorithms or others. For large problems with a large number of decision variables, ether over extended period or having several pumping units, the extended solution time of the EA approach may render the approach not relevant. The proposed method utilized the operation graph optimization (OGO) algorithm proposed previously by the authors, demonstrating high speed discrete minimal cost, optimization with hydraulic constraints. A minimal cost algorithm is proposed, including hydraulic and water quality constraints. The suggested algorithm raises the concentration of the residual chlorine in the network by optimally decreasing the operational volume of the water tanks, and by such increasing the pump switching frequency. The algorithm is demonstrated and compared to enumeration on a single pressure zone example network (1 water tank, 1 pumping unit), on a large example network (C-Town, 7 water tanks, 11 pumping units). The resulting pump schedule is not a global minimum when compared to the best enumeration result on a single pressure zone. However, the algorithm may serve, especially in large water systems, as a quick and feasible answer to system operators, regarding the water volume to maintain in the different tanks to provide minimal chlorine service concentration at near minimal cost.
AB - Optimal water system operation, including hydraulic and water quality constraints are complex problems to solve due to the nonlinear relationship of head-loss to flow and disinfectant-loss to time. A common approach used today is evolutionary algorithms (EA) such as genetic algorithms or others. For large problems with a large number of decision variables, ether over extended period or having several pumping units, the extended solution time of the EA approach may render the approach not relevant. The proposed method utilized the operation graph optimization (OGO) algorithm proposed previously by the authors, demonstrating high speed discrete minimal cost, optimization with hydraulic constraints. A minimal cost algorithm is proposed, including hydraulic and water quality constraints. The suggested algorithm raises the concentration of the residual chlorine in the network by optimally decreasing the operational volume of the water tanks, and by such increasing the pump switching frequency. The algorithm is demonstrated and compared to enumeration on a single pressure zone example network (1 water tank, 1 pumping unit), on a large example network (C-Town, 7 water tanks, 11 pumping units). The resulting pump schedule is not a global minimum when compared to the best enumeration result on a single pressure zone. However, the algorithm may serve, especially in large water systems, as a quick and feasible answer to system operators, regarding the water volume to maintain in the different tanks to provide minimal chlorine service concentration at near minimal cost.
UR - http://www.scopus.com/inward/record.url?scp=84976490723&partnerID=8YFLogxK
U2 - https://doi.org/10.1061/9780784479865.052
DO - https://doi.org/10.1061/9780784479865.052
M3 - منشور من مؤتمر
T3 - World Environmental And Water Resources Congress 2016: Environmental, Sustainability, Groundwater, Hydraulic Fracturing, and Water Distribution Systems Analysis - Papers from Sessions of the Proceedings of the 2016 World Environmental and Water Resources Congress
SP - 497
EP - 504
BT - World Environmental And Water Resources Congress 2016
A2 - Pathak, Chandra S.
A2 - Reinhart, Debra
T2 - 16th World Environmental and Water Resources Congress 2016: Environmental, Sustainability, Groundwater, Hydraulic Fracturing, and Water Distribution Systems Analysis
Y2 - 22 May 2016 through 26 May 2016
ER -