Analysis of Water Distribution System under Uncertainty Based on Genetic Algorithm and Trapezoid Fuzzy Membership

2021 ◽  
Vol 12 (4) ◽  
pp. 04021043
Author(s):  
Yumin Wang ◽  
Guangcan Zhu
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Fuzzy Membership

Multiple Leakage Detection and Localization Method Based on Bayesian Theory and Genetic Algorithm

2014 ◽  
Vol 635-637 ◽  
pp. 924-927
Author(s):  
Tao Jin ◽  
Ze Yuan Zhou
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Bayesian Theory ◽  
Leakage Detection ◽  
Localization Method ◽  
Simulation Results ◽  
Detection And Localization ◽  
Leakage Location

To detect and locate the leakage of the pipe correctly, genetic algorithm is combined with Bayesian theory to determine the leaked pipes. Leakage detection and leakage location are carried out separately. Leakage detection is conducted based on the assumption that there is only one leaked pipe, and the simulation result demonstrates its feasibility. When the leakage detection demonstrates there is leaked pipe in the water distribution system, leakage location starts. Based on the information gathered by the manometers, leakage probability in different combinations of the virtual nodal demand can be fixed according to calculating the pressure of the monitored node, then GA is applied to search the maximum Bayesian value, the pipes with maximum Bayesian leakage possibility are believed to be leaked pipes. Optimization programme was made with combination of Matlab and Epanet, numerical simulation results demonstrate the feasibility and effectiveness of the proposed method.

scholarly journals Using a Genetic Algorithm with a Mathematical Programming Solver to Optimize a Real Water Distribution System

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1318 ◽  
Author(s):  
Beatriz Martínez-Bahena ◽  
Marco Cruz-Chávez ◽  
Erika Ávila-Melgar ◽  
Martín Cruz-Rosales ◽  
Rafael Rivera-Lopez
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Extended Period ◽  
Storage Tanks ◽  
Specific Point ◽  
Hydraulic Network ◽  
Satisfaction Model

This research proposes a genetic algorithm that provides a solution to the problem of deficient distribution of drinking water via the current hydraulic network in the neighborhood “Fraccionamiento Real Montecasino” (FRM), in Huitzilac, Morelos, Mexico. The proposed solution is the addition of new elements to the FRM network. The new elements include storage tanks, pipes, and pressure-reducing valves. To evaluate the constraint satisfaction model of mass and energy conservation, the hydraulic EPANET solver (HES) is used with an optimization model to minimize the total cost of changes in the network (new pipes, tanks, and valves). A genetic algorithm was used to evaluate the optimization model. The analysis of the results obtained by the genetic algorithm for the FRM network shows that adequate and balanced pressures were obtained by means of small modifications to the existing network, which entailed minimal costs. Simulations were performed for an extended period, which means that the pressure was obtained by simulation with HSE at one-hour intervals, during the algorithm execution, to verify adequate pressure at a specific point in the system, or to make corrections to ensure proper distribution, this with the aim of having a final optimized network design.

Multi-objective optimisation of the operation of a water distribution network

2014 ◽  
Vol 64 (3) ◽  
pp. 235-249
Author(s):  
Michael Mulholland ◽  
M. Abderrazak Latifi ◽  
Andrew Purdon ◽  
Christopher Buckley ◽  
Christopher Brouckaert
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Water Distribution Network ◽  
Reservoir Water ◽  
Minimum Interval ◽  
Pareto Fronts ◽  
The Cost ◽  
Near Optimality

The aim of the present paper was to move water through a reservoir network in such a way as to meet consumer demands and level constraints, minimise the cost of electricity, and minimise the loss of chlorine. This was to be achieved by choosing the switching intervals of reservoir inlet pumps and valves, at the same time complying with the allowed minimum interval size of each device. Switching combinations that threatened to exceed constraints were rejected heuristically. Flows were balanced by linear programming (LP). The genetic algorithm gave confidence in the near-optimality of its solutions, through the well-defined Pareto fronts between the competing objectives. The method was applied to a 16-reservoir water distribution system in Durban, South Africa. Comparison with an equivalent ‘dead-band’ control showed a 30% improvement in a weighted objective.

Upgrading Water Distribution System Based on GA-RBF Neural Network Model

2011 ◽  
Vol 267 ◽  
pp. 605-608 ◽  
Author(s):  
Hong Xiang Wang ◽  
Wen Xian Guo
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Radial Basis Function ◽  
Network Model ◽  
Basis Function ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Calibration Model ◽  
Radial Basis

Hydraulic network calibration model is to minimize the sum of the squares of the differences between the calibrated and initial pipe roughness estimates, under a set of constraints determined from a sensitivity matrix. The upgrading problem of water distribution system was put forward after the preferable network model was obtained. Radial Basis Function neural network (RBF) based on genetic algorithm (GA) was proposed to solve the model. Genetic algorithm was applied to optimize the parameters of the neural network, and overcome the over-fitting problem. Case study concludes that using Radial Basis Function neural network (RBF) based on genetic algorithm (GA) and good results were obtained.

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