Search

Water age is the time taken for water to travel through a distribution system and reach the consumer. Generally, there is a trade-off between water pressure and water age in a water distribution system—higher pressure results in higher flow velocity, which often means shorter traveling time for the water, while lower pressure leads to slower flow and thus higher water age. Low pressure is a desired objective in a distribution system, as it reduces the physical stress on its components and minimizes water losses in the event of a leak. Low water age is a desired objective as well, as increased age is regarded as having a low water quality. Therefore, the two objectives compete with one another. The problem of trying to minimize both water pressure and age is a common problem in water distribution systems' design and management. This paper introduces an algorithm for pressure reducing valves' (PRVs) placement for reducing water age in water distribution systems. The algorithm is based on graph-theory elements and uses EPANET 2.2 for simulation and analysis. The method is demonstrated on two small scale examples, and the results present relatively significant improvements in respect to water age. [ABSTRACT FROM AUTHOR]

The optimal allocation of protective devices is a serious issue in an electrical power system; in order to reduce the possibility of faults, the protection devices should be optimally placed. The paper presents a continuous genetic algorithm (CGA) for the optimal allocation of directional relays for the efficient energy minimization in a radial distribution system (DG). The algorithm is flexible to use for the changes and improvements in the optimal location for a DG unit and can optimize the energy consumption in the radial distribution system. The proposed algorithm has been implemented on IEEE 33 and 69-bus system using MATLAB (R2014b, MathWorks). Low energy consumption is a common design objective in an energy-constrained distribution system. Engineers, power utilities, and network operators can profit from the proposed methodology to enhance the use of DG in distribution networks. [ABSTRACT FROM AUTHOR]

This paper presents a modified Shuffled Frog Leaping Algorithm (SFLA) applied to the design of water distribution networks. Generally, one of the major disadvantages of the traditional SFLA is the high number of parameters that need to be calibrated for proper operation of the algorithm. A method for calibrating these parameters is presented and applied to the design of three benchmark medium-sized networks widely known in the literature (Hanoi, New York Tunnel, and GoYang). For each of the problems, over 35,000 simulations were conducted. Then, a statistical analysis was performed, and the relative importance of each of the parameters was analyzed to achieve the best possible configuration of the modified SFLA. The main conclusion from this study is that not all of the original SFL algorithm parameters are important. Thus, the fraction of frogs in the memeplex q can be eliminated, while the other parameters (number of evolutionary steps Ns, number of memeplexes m, and number of frogs n) may be set to constant values that run optimally for all medium-sized networks. Furthermore, the modified acceleration parameter C becomes the key parameter in the calibration process, vastly improving the results provided by the original SFLA. [ABSTRACT FROM AUTHOR]

The design of a water distribution network (WDN) is conceptually a multiobjective problem characterized by stringent constraints. Even in its most simple formulation, which requires only the maintenance of minimum pressures, it is difficult to solve, and the simplifications introduced often impair the practicality of the solutions. The paper aims at integrating an engineering approach to the optimization problem by generating pseudofronts in the hydraulically feasible region of the search space. The optimization algorithms provide an entirely feasible trade-off between cost and considered constraints, which may be directly used by a hypothetical decision maker. This engineering approach requires a fast tool to search for feasible solutions: the recently developed genetic heritage by stochastic evolution transmission (GHEST) algorithm, used herein, has proved to be effective and efficient in solving the optimal design problem of WDNs. Tests are carried out on two large-size water distribution networks (Balerma and Modena), using the GHEST algorithm, modified to account for several objectives. [ABSTRACT FROM AUTHOR]

In design of water distribution networks, there are several constraints that need to be satisfied; supplying water at an adequate pressure being the main one. In this paper, a self-adaptive fitness formulation is presented for solving constrained optimization of water distribution networks. The method has been formulated to ensure that slightly infeasible solutions with a low objective function value remain fit. This is seen as a benefit in solving highly constrained problems that have solutions on one or more of the constraint bounds. In contrast, solutions well outside the constraint bounds are seen as containing little genetic information that is of use and are therefore penalized. In this method, the dimensionality of the problem is reduced by representing the constraint violations by a single infeasibility measure. The infeasibility measure is used to form a two-stage penalty that is applied to infeasible solutions. The performance of the method has been examined by its application to two water distribution networks from literature. The results have been compared with previously published results. It is shown that the method is able to find optimum solutions with less computational effort. The proposed method is easy to implement, requires no parameter tuning, and can be used as a fitness evaluator with any evolutionary algorithm. The approach is also robust in its handling of both linear and nonlinear equality and inequality constraint functions. Furthermore, the method does not require an initial feasible solution, this being an advantage in real-world applications having many optimization variables. [ABSTRACT FROM AUTHOR]

Water distribution network that includes supply reservoirs, overhead tanks, consumer demand nodes, interconnecting pipes, lifting pumps, and control valves is the main mode of water supply for majority of the communities especially in urban areas. Supply of required quantity of water and at right time is the primary objective of water distribution network analysis. The analysis of water distribution networks can be broadly classified into design and operation problems and both problems have been the focus of many researchers over the past three decades. In the water distribution network design problems, the target is attaining the cost effective configuration that satisfies the minimum hydraulic head requirement at the demand nodes. In this paper, a new algorithm for design of water distribution network namely “heuristics-based algorithm” which completely utilizes the implicit information associated with the water distribution network to be designed has been proposed and validated with two water distribution networks. It is found that the proposed algorithm performs well for the least-cost design of water distribution networks. [ABSTRACT FROM AUTHOR]

This paper presents a linearization approach to be used within the framework of water distribution system optimization problems where the searching algorithm is guided by the ranking of the possible solutions characterized by a system performance indicator such as the resilience index. The results obtained in addressing two different problems applied to real water distribution systems, namely, identification of the optimal placement of flow meters in a district meter area and multi-objective design of a water distribution system, show that a linearized hydraulic simulator although not capable of correctly describing the hydraulic functioning of the network, nonetheless enables each solution it finds to be assigned a value of the performance indicator whose ranking closely approximates the ranking of the corresponding solution that would be obtained if the full hydraulic simulator was used. This ensures significant reductions in computational times. [ABSTRACT FROM AUTHOR]

The paper presents the comparison of two different algorithms for the optimal location of control valves for leakage reduction in water distribution networks (WDNs). The former is based on the sequential addition (SA) of control valves. At the generic step Nval of SA, the search for the optimal combination of Nval valves is carried out, while containing the optimal combination of Nval − 1 valves found at the previous step. Therefore, only one new valve location is searched for at each step of SA, among all the remaining available locations. The latter algorithm consists of a multi-objective genetic algorithm (GA), in which valve locations are encoded inside individual genes. For the sake of consistency, the same embedded algorithm, based on iterated linear programming (LP), was used inside SA and GA, to search for the optimal valve settings at various time slots in the day. The results of applications to two WDNs show that SA and GA yield identical results for small values of Nval. When this number grows, the limitations of SA, related to its reduced exploration of the research space, emerge. In fact, for higher values of Nval, SA tends to produce less beneficial valve locations in terms of leakage abatement. However, the smaller computation time of SA may make this algorithm preferable in the case of large WDNs, for which the application of GA would be overly burdensome. [ABSTRACT FROM AUTHOR]

In water distribution system (WDS), chlorine is often injected as disinfectant to control the growth of microorganism in WDS. However, the chlorine reacts with organism to form disinfectant byproduct, which can bring risk to human health. As such, the chlorine at nodes in WDS should be kept between acceptable range, which is simulated based on the response at nodes corresponding to unit injection mass at boosters. To deal with the uncertainty in chlorine decay process and lower and upper chlorine concentration limits, an inexact left-hand-side chance-constrained programming (ILCCP) model was proposed in this paper and applied to two WDSs. The response coefficients matrix was expressed as random variables with normal probability distribution in the constraints of lower and upper limits, which was obtained through Monte Carlo simulation by linking with EPANET software. The intervals of injection mass were obtained by solving the ILCCP model with a two-step algorithm. Moreover, the effects of random bulk decay coefficients and interval of chlorine limits on the injection mass were analyzed and compared. The results indicated that the lower bounds of optimal injection mass increased with the rise of probability lever for lower limits, while the upper bounds decreased with the rise of the probability level for upper limits. The results can help managers determine the chlorine injection mass under uncertain scenarios, and can be applied to more complicated WDS to obtain meaningful results. • An inexact left-hand-side chance-constrained programming model was proposed. • Response coefficients were expressed as random variables with normal distribution. • Effects of decay coefficients and limits on the injection mass were analyzed. [ABSTRACT FROM AUTHOR]

A sequential irrigation schedule that honors user demands of duration and minimizes earliness and tardiness is interpreted as a single-machine schedule with earliness and tardiness costs and a common deadline (or fixed interval). A heuristic solution is presented for this irrigation scheduling problem. Four models are presented to reflect the different methods in which an irrigation system at the tertiary unit level may be operated, the first model permits jobs to be noncontiguous, i.e., idle time between jobs is permitted, whereas the others permit contiguous jobs only. The heuristic is tested extensively and the solution quality is compared with either an optimum solution from an integer program or the best available solution obtained from an integer program within allocated computation time. The heuristic is computationally efficient for all models presented, however for schedules with noncontiguous jobs, or where idle time is inserted before and after a contiguous set of jobs, solution quality deteriorates. The work brings the science of single scheduling from operations research into irrigation scheduling and suggests areas for further development. [ABSTRACT FROM AUTHOR]

The investment and operating costs of pumping stations in drinking water distribution networks are some of the highest public costs in urban sectors. Generally, these systems are designed based on extreme scenarios. However, in periods of normal operation, extra energy is produced, thereby generating excess costs. To avoid this problem, this work presents a new methodology for the design of pumping stations. The proposed technique is based on the use of a setpoint curve to optimize the operating and investment costs of a station simultaneously. According to this purpose, a novel mathematical optimization model is developed. The solution output by the model includes the selection of the pumps, the dimensions of pipelines, and the optimal flow distribution among all water sources for a given network. To demonstrate the advantages of using this technique, a case study network is presented. A pseudo-genetic algorithm (PGA) is implemented to resolve the optimization model. Finally, the obtained results show that it is possible to determine the full design and operating conditions required to achieve the lowest cost in a multiple pump station network. [ABSTRACT FROM AUTHOR]