Influence of the Pump Control System in the Selection of the Number of Fixed Speed and Variable Speed Drive Pumps in Water Pumping Stations

[EN] Proper design of a pumping system requires the use of a pump curve and set-point curve system. Both have to be as close as possible to optimize energy use. This is achieved by control systems in which the type of control (flow or pressure) and the combination between fixed speed drive (FSD) pumps and variable speed drive (VSD) pumps are involved. The objective of this work is to determine the optimal number of FSD and VSD pumps for each flow rate range in order to discuss the classic design of pumping stations and their control systems. For this, a methodology is applied that defines the parametric form of the pump curve, efficiency curve, and set-point curve in relation to the most efficient point. In this way, dimensionless expressions are obtained and the influence of the set-point parameters on the design of the control system can be analyzed. Additionally, the method includes an expression that estimates the performance of the frequency inverter, which is based on the load and pump speed rotation. The application of the methodology to different case studies allows us to question many classic procedures for pumping stations. In summary, it can be concluded that the appropriate number of variable speed pumps for each control system cannot be established in advance but requires an in-depth study of different available options.Briceño, C.; Iglesias Rey, PL.; Martínez-Solano, FJ. (2019). Influence of the Pump Control System in the Selection of the Number of Fixed Speed and Variable Speed Drive Pumps in Water Pumping Stations. Proceedings. 48(1):1-11. https://doi.org/10.3390/ECWS-4-06445S11148

Multi-Objective Optimization of Drainage Networks for Flood Control in Urban Area Due to Climate Change

[EN] The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) of the United Nations mentions that extreme rainfalls might increase their intensity and frequency in most mid-latitude locations and tropical regions by the end of this century, as a consequence of the rise of the average global surface temperature. Human action has given way to global warming which manifests with an increase in extreme rainfall. If these climatic conditions are added to the waterproofing that cities have been experiencing as a result of urban development, a scenario of growing concern for the managers of drainage systems is generated. The objective of drainage networks is preventing the accumulation of rainwater on the surface. Under the new conditions of climate change, these need to be modified and adapted to provide cities with the security they demand. The following article describes a method for flood control by using a rehabilitation model that connects the Storm Water Management Model (SWMM) 5 model with a genetic algorithm to find the best solutions to the flood problem. The final analysis is performed using the Pareto efficiency criteria. The innovation of this method is the inclusion of a local head loss in the drainage network, allowing the upstream flow to be retained by decreasing the downstream concentration time. These elements called hydraulic controls improve system performance and are installed in the initial part of some pipes coming out of storm tanks. As a case study, the developed method has been applied in a section of the drainage network of the city of Bogotá.Bayas-Jiménez, L.; Iglesias Rey, PL.; Martínez-Solano, FJ. (2019). Multi-Objective Optimization of Drainage Networks for Flood Control in Urban Area Due to Climate Change. Proceedings. 48(1):1-9. https://doi.org/10.3390/ECWS-4-06451S1948

Search Space Reduction for Genetic Algorithms Applied to Drainage Network Optimization Problems

[EN] In recent years, a significant increase in the number of extreme rains around the world has been observed, which has caused an overpressure of urban drainage networks. The lack of capacity to evacuate this excess water generates the need to rehabilitate drainage systems. There are different rehabilitation methodologies that have proven their validity; one of the most used is the heuristic approach. Within this approach, the use of genetic algorithms has stood out for its robustness and effectiveness. However, the problem to be overcome by this approach is the large space of solutions that algorithms must explore, affecting their efficiency. This work presents a method of search space reduction applied to the rehabilitation of drainage networks. The method is based on reducing the initially large search space to a smaller one that contains the optimal solution. Through iterative processes, the search space is gradually reduced to define the final region. The rehabilitation methodology contemplates the optimization of networks using the joint work of the installation of storm tanks, replacement of pipes, and implementation of hydraulic control elements. The optimization model presented uses a pseudo genetic algorithm connected to the SWMM model through a toolkit. Optimization problems consider a large number of decision variables, and could require a huge computational effort. For this reason, this work focuses on identifying the most promising region of the search space to contain the optimal solution and to improve the efficiency of the process. Finally, this method is applied in real networks to show its validity.This work was supported by the Program Fondecyt Regular (Project No. 1210410 and Project No. 1180660) of the Agencia Nacional de Investigación y Desarrollo (ANID), Chile.Bayas-Jiménez, L.; Martínez-Solano, FJ.; Iglesias Rey, PL.; Mora-Meliá, D. (2021). Search Space Reduction for Genetic Algorithms Applied to Drainage Network Optimization Problems. Water. 13(15):1-24. https://doi.org/10.3390/w13152008S124131

Combining Skeletonization, Setpoint Curves, and Heuristic Algorithms to Define District Metering Areas in the Battle of Water Networks District Metering Areas

[EN] The problem presented in this edition of the Battle of the Water Networks is to define district metering areas (DMAs) in a large network. The problem is addressed in two phases. First, the complexity of the network is simplified by dividing it into three operational areas. Second, an optimization algorithm defines DMAs, looking for the best feasible solution. A preliminary simulation of the network is made. From this, engineering judgment allows for defining an initial set of elements suitable to change. In the second stage, a heuristic algorithm is used to search for the best DMA definition by selecting the locations and settings of the pressure-reducing valves and isolation valves. The network is then divided into two categories: the main pipes and the distribution pipes. Only the distribution pipes can be closed. With these restrictions and those described in the problem, the algorithm looks for the best DMA definition based on both the pressure and demand distribution among all the DMAs.This work was supported by the Program Fondecyt Regular (Project 1180660) of the Comision Nacional de Investigacion Cientifica y Tecnologica (Conicyt), Chile.Martínez-Solano, FJ.; Iglesias Rey, PL.; Mora Melia, D.; Ribelles-Aguilar, J. (2018). Combining Skeletonization, Setpoint Curves, and Heuristic Algorithms to Define District Metering Areas in the Battle of Water Networks District Metering Areas. Journal of Water Resources Planning and Management. 144(6):04018023-1-04018023-7. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000938S04018023-104018023-7144

Impact of Hydraulic Variable Conditions in the Solution of Pumping Station Design through Sensitivity Analysis

[EN] A proper pumping station (PS) design should consider multiple criteria, such as technical, economic, and environmental aspects. The analytic hierarchy process (AHP) method can be applied for multi-criteria analysis in this type of engineering design, and it is based on the judgment of a group of experts for the criteria considered. On the other hand, the most common method for PS design is one based solely on economic aspects or life cycle cost (LCC). This paper presents a sensitivity analysis of the impact of the hydraulic conditions of a water distribution network (WDN) on the ultimate solution in two PS design approaches. The first approach was the classic method based on LCC minimization and the second approach was based on multi-criteria analysis by means of AHP accounting for technical, economic, and environmental aspects. In this way, the effects of different meaningful variables for PS design, such as the mean demand, parameters of the setpoint curve, electric tariffs, and interest rates, were evaluated to determine the robustness of the PS solutions obtained. The obtained results of the sensitivity analysis in the case study demonstrated that the PS design based on multiple criteria decision analysis was more reliable and robust than the classic PS design against variations that can occur in a WDN, especially in the mean flow, setpoint curve, and electric tariff. The variations in these parameters of the WDN did not impact the ultimate solutions of the PS design approaches when within the tolerance ranges, but these ranges were wider in the second approach to PS design than in the first approach.Briceño-León, CX.; Iglesias Rey, PL.; Martínez-Solano, FJ.; Creaco, E. (2023). Impact of Hydraulic Variable Conditions in the Solution of Pumping Station Design through Sensitivity Analysis. Water. 15(17):1-23. https://doi.org/10.3390/w15173067123151

Multi-Objective Optimization for Urban Drainage or Sewer Networks Rehabilitation through Pipes Substitution and Storage Tanks Installation

[EN] Drainage networks are civil constructions which do not generally attract the attention of decision-makers. However, they are of crucial importance for cities; this can be seen when a city faces floods resulting in extensive and expensive damage. The increase of rain intensity due to climate change may cause deficiencies in drainage networks built for certain defined flows which are incapable of coping with sudden increases, leading to floods. This problem can be solved using different strategies; one is the adaptation of the network through rehabilitation. A way to adapt the traditional network approach consists of substituting some pipes for others with greater diameters. More recently, the installation of storm tanks makes it possible to temporarily store excess water. Either of these solutions can be expensive, and an economic analysis must be done. Recent studies have related flooding with damage costs. In this work, a novel solution combining both approaches (pipes and tanks) is studied. A multi-objective optimization algorithm based on the NSGA-II is proposed for the rehabilitation of urban drainage networks through the substitution of pipes and the installation of storage tanks. Installation costs will be o set by damage costs associated with flooding. As a result, a set of optimal solutions that can be implemented based on the objectives to be achieved by municipalities or decisions makers. The methodology is finally applied to a real network located in the city of Bogotá, Colombia.This work was supported by the Program Fondecyt Regular (Project 1180660) of the Comision Nacional de Investigacion Cientifica y Tecnologica (Conicyt), Chile.Ngamalieu-Nengoue, UA.; Martínez-Solano, FJ.; Iglesias Rey, PL.; Mora-Meliá, D. (2019). Multi-Objective Optimization for Urban Drainage or Sewer Networks Rehabilitation through Pipes Substitution and Storage Tanks Installation. Water. 11(5). https://doi.org/10.3390/w11050935S115Kordana, S. (2018). The identification of key factors determining the sustainability of stormwater systems. E3S Web of Conferences, 45, 00033. doi:10.1051/e3sconf/20184500033Yazdi, J., Lee, E. H., & Kim, J. H. (2015). Stochastic Multiobjective Optimization Model for Urban Drainage Network Rehabilitation. Journal of Water Resources Planning and Management, 141(8), 04014091. doi:10.1061/(asce)wr.1943-5452.0000491Starzec, M., Dziopak, J., Słyś, D., Pochwat, K., & Kordana, S. (2018). Dimensioning of Required Volumes of Interconnected Detention Tanks Taking into Account the Direction and Speed of Rain Movement. Water, 10(12), 1826. doi:10.3390/w10121826Mailhot, A., & Duchesne, S. (2010). Design Criteria of Urban Drainage Infrastructures under Climate Change. Journal of Water Resources Planning and Management, 136(2), 201-208. doi:10.1061/(asce)wr.1943-5452.0000023Gulizia, C., & Camilloni, I. (2014). Comparative analysis of the ability of a set of CMIP3 and CMIP5 global climate models to represent precipitation in South America. International Journal of Climatology, 35(4), 583-595. doi:10.1002/joc.4005Ma, M., He, B., Wan, J., Jia, P., Guo, X., Gao, L., … Hong, Y. (2018). Characterizing the Flash Flooding Risks from 2011 to 2016 over China. Water, 10(6), 704. doi:10.3390/w10060704Kirshen, P., Caputo, L., Vogel, R. M., Mathisen, P., Rosner, A., & Renaud, T. (2015). Adapting Urban Infrastructure to Climate Change: A Drainage Case Study. Journal of Water Resources Planning and Management, 141(4), 04014064. doi:10.1061/(asce)wr.1943-5452.0000443Moselhi, O., & Shehab-Eldeen, T. (2000). Classification of Defects in Sewer Pipes Using Neural Networks. Journal of Infrastructure Systems, 6(3), 97-104. doi:10.1061/(asce)1076-0342(2000)6:3(97)Driessen, P., Hegger, D., Kundzewicz, Z., van Rijswick, H., Crabbé, A., Larrue, C., … Wiering, M. (2018). Governance Strategies for Improving Flood Resilience in the Face of Climate Change. Water, 10(11), 1595. doi:10.3390/w10111595Reyna, S. M., Vanegas, J. A., & Khan, A. H. (1994). Construction Technologies for Sewer Rehabilitation. Journal of Construction Engineering and Management, 120(3), 467-487. doi:10.1061/(asce)0733-9364(1994)120:3(467)Abraham, D. M., Wirahadikusumah, R., Short, T. J., & Shahbahrami, S. (1998). Optimization Modeling for Sewer Network Management. Journal of Construction Engineering and Management, 124(5), 402-410. doi:10.1061/(asce)0733-9364(1998)124:5(402)Sebti, A., Fuamba, M., & Bennis, S. (2016). Optimization Model for BMP Selection and Placement in a Combined Sewer. Journal of Water Resources Planning and Management, 142(3), 04015068. doi:10.1061/(asce)wr.1943-5452.0000620Zahmatkesh, Z., Burian, S. J., Karamouz, M., Tavakol-Davani, H., & Goharian, E. (2015). Low-Impact Development Practices to Mitigate Climate Change Effects on Urban Stormwater Runoff: Case Study of New York City. Journal of Irrigation and Drainage Engineering, 141(1), 04014043. doi:10.1061/(asce)ir.1943-4774.0000770Mora-Melià, D., López-Aburto, C., Ballesteros-Pérez, P., & Muñoz-Velasco, P. (2018). Viability of Green Roofs as a Flood Mitigation Element in the Central Region of Chile. Sustainability, 10(4), 1130. doi:10.3390/su10041130Ugarelli, R., & Di Federico, V. (2010). Optimal Scheduling of Replacement and Rehabilitation in Wastewater Pipeline Networks. Journal of Water Resources Planning and Management, 136(3), 348-356. doi:10.1061/(asce)wr.1943-5452.0000038Ngamalieu-Nengoue, U., Iglesias-Rey, P., Martínez-Solano, F., Mora-Meliá, D., & Saldarriaga Valderrama, J. (2019). Urban Drainage Network Rehabilitation Considering Storm Tank Installation and Pipe Substitution. Water, 11(3), 515. doi:10.3390/w11030515Lee, E., & Kim, J. (2017). Development of Resilience Index Based on Flooding Damage in Urban Areas. Water, 9(6), 428. doi:10.3390/w9060428Iglesias-Rey, P. L., Martínez-Solano, F. J., Saldarriaga, J. G., & Navarro-Planas, V. R. (2017). Pseudo-genetic Model Optimization for Rehabilitation of Urban Storm-water Drainage Networks. Procedia Engineering, 186, 617-625. doi:10.1016/j.proeng.2017.03.278Fadel, A. W., Marques, G. F., Goldenfum, J. A., Medellín-Azuara, J., & Tilmant, A. (2018). Full Flood Cost: Insights from a Risk Analysis Perspective. Journal of Environmental Engineering, 144(9), 04018071. doi:10.1061/(asce)ee.1943-7870.0001414Duan, H.-F., Li, F., & Yan, H. (2016). Multi-Objective Optimal Design of Detention Tanks in the Urban Stormwater Drainage System: LID Implementation and Analysis. Water Resources Management, 30(13), 4635-4648. doi:10.1007/s11269-016-1444-1Starzec, M. (2018). A critical evaluation of the methods for the determination of required volumes for detention tank. E3S Web of Conferences, 45, 00088. doi:10.1051/e3sconf/20184500088Pochwat, K. B., & Słyś, D. (2018). Application of Artificial Neural Networks in the Dimensioning of Retention Reservoirs. Ecological Chemistry and Engineering S, 25(4), 605-617. doi:10.1515/eces-2018-0040Cunha, M. C., Zeferino, J. A., Simões, N. E., & Saldarriaga, J. G. (2016). Optimal location and sizing of storage units in a drainage system. Environmental Modelling & Software, 83, 155-166. doi:10.1016/j.envsoft.2016.05.015Martino, G. D., De Paola, F., Fontana, N., Marini, G., & Ranucci, A. (2011). Pollution Reduction in Receivers: Storm-Water Tanks. Journal of Urban Planning and Development, 137(1), 29-38. doi:10.1061/(asce)up.1943-5444.0000037Andrés-Doménech, I., Montanari, A., & Marco, J. B. (2012). Efficiency of Storm Detention Tanks for Urban Drainage Systems under Climate Variability. Journal of Water Resources Planning and Management, 138(1), 36-46. doi:10.1061/(asce)wr.1943-5452.0000144Wang, M., Sun, Y., & Sweetapple, C. (2017). Optimization of storage tank locations in an urban stormwater drainage system using a two-stage approach. Journal of Environmental Management, 204, 31-38. doi:10.1016/j.jenvman.2017.08.024Cunha, M. C., Zeferino, J. A., Simões, N. E., Santos, G. L., & Saldarriaga, J. G. (2017). A decision support model for the optimal siting and sizing of storage units in stormwater drainage systems. International Journal of Sustainable Development and Planning, 12(01), 122-132. doi:10.2495/sdp-v12-n1-122-132Dziopak, J. (2018). A wastewater retention canal as a sewage network and accumulation reservoir. E3S Web of Conferences, 45, 00016. doi:10.1051/e3sconf/20184500016Słyś, D. (2018). An innovative retention canal – a case study. E3S Web of Conferences, 45, 00084. doi:10.1051/e3sconf/20184500084Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182-197. doi:10.1109/4235.996017Martínez-Solano, F., Iglesias-Rey, P., Saldarriaga, J., & Vallejo, D. (2016). Creation of an SWMM Toolkit for Its Application in Urban Drainage Networks Optimization. Water, 8(6), 259. doi:10.3390/w8060259Wang, Q., Zhou, Q., Lei, X., & Savić, D. A. (2018). Comparison of Multiobjective Optimization Methods Applied to Urban Drainage Adaptation Problems. Journal of Water Resources Planning and Management, 144(11), 04018070. doi:10.1061/(asce)wr.1943-5452.0000996Mora-Melia, D., Iglesias-Rey, P. L., Martinez-Solano, F. J., & Ballesteros-Pérez, P. (2015). Efficiency of Evolutionary Algorithms in Water Network Pipe Sizing. Water Resources Management, 29(13), 4817-4831. doi:10.1007/s11269-015-1092-xMora-Melià, D., Martínez-Solano, F. J., Iglesias-Rey, P. L., & Gutiérrez-Bahamondes, J. H. (2017). 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Hydraulic modeling during filling and emptying processes in pressurized pipelines: a literature review

[EN] Filling and emptying processes are common maneuvers while operating, controlling and managing water pipeline systems. Currently, these operations are executed following recommendations from technical manuals and pipe manufacturers; however, these recommendations have a lack of understanding about the behavior of these processes. The application of mathematical models considering transient flows with entrapped air pockets is necessary because a rapid filling operation can cause pressure surges due to air pocket compressions, while an uncontrolled emptying operation can generate troughs of sub-atmospheric pressure caused by air pocket expansion. Depending on pipe and installation conditions, either situation can produce a rupture of pipe systems. Recently, reliable mathematical models have been developed by different researchers. This paper reviews and compares various mathematical models to simulate these processes. Water columns can be analyzed using a rigid water column model, an elastic water model, or 2D/3D CFD models; air-water interfaces using a piston-flow model or more complex models; air pockets through a polytropic model; and air valves using an isentropic nozzle flow or similar approaches. This work can be used as a starting point for planning filling and emptying operations in pressurized pipelines. Uncertainties of mathematical models of two-phases flow concerning to a non-variable friction factor, a polytropic coefficient, an air pocket sizes and an air valve behavior are identified.This work was supported by the Program Fondecyt Regular (Chile) [Project 1180660]; Fundacion Centro de Estudios Intedisciplinarios Basicos y Aplicados, CEIBA (Colombia).Fuertes-Miquel, VS.; Coronado-Hernández, OE.; Mora-Melia, D.; Iglesias Rey, PL. (2019). Hydraulic modeling during filling and emptying processes in pressurized pipelines: a literature review. Urban Water Journal. 16(4):299-311. https://doi.org/10.1080/1573062X.2019.1669188S29931116

Pumping Station Design in Water Distribution Networks Considering the Optimal Flow Distribution between Sources and Capital and Operating Costs

[EN] 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.This work was supported by the Program Fondecyt Regular (Project N. 1210410) of the Agencia Nacional de Investigación y Desarrollo (ANID), Chile. It is also supported by CONICYT PFCHA/DOCTORADO BECAS CHILE/2018-21182013.Gutiérrez-Bahamondes, JH.; Mora-Meliá, D.; Iglesias Rey, PL.; Martínez-Solano, FJ.; Salgueiro, Y. (2021). Pumping Station Design in Water Distribution Networks Considering the Optimal Flow Distribution between Sources and Capital and Operating Costs. Water. 13(21):1-14. https://doi.org/10.3390/w13213098S114132

Urban Drainage Network Rehabilitation Considering Storm Tank Installation and Pipe Substitution

[EN] The drainage networks of our cities are currently experiencing a growing increase in runoff flows, caused mainly by the waterproofing of the soil and the effects of climate change. Consequently, networks originally designed correctly must endure floods with frequencies much higher than those considered in the design phase. The solution of such a problem is to improve the network. There are several ways to rehabilitate a network: conduit substitution as a former method or current methods such as storm tank installation or combined use of conduit substitution and storm tank installation. To find an optimal solution, deterministic or heuristic optimization methods are used. In this paper, a methodology for the rehabilitation of these drainage networks based on the combined use of the installation of storm tanks and the substitution of some conduits of the system is presented. For this, a cost-optimization method and a pseudo-genetic heuristic algorithm, whose efficiency has been validated in other fields, are applied. The Storm Water Management Model (SWMM) model for hydraulic analysis of drainage and sanitation networks is used. The methodology has been applied to a sector of the drainage network of the city of Bogota in Colombia, showing how the combined use of storm tanks and conduits leads to lower cost rehabilitation solutions.This work was supported by the Program Fondecyt Regular (Project 1180660) of the Comision Nacional de Investigación Científica y Tecnológica (Conicyt), Chile.Ngamalieu-Nengoue, UA.; Iglesias Rey, PL.; Martínez-Solano, FJ.; Mora-Meliá, D.; Saldarriaga, J. (2019). Urban Drainage Network Rehabilitation Considering Storm Tank Installation and Pipe Substitution. Water. 11(3):515-537. https://doi.org/10.3390/w11030515S51553711

Urban Drainage Networks Rehabilitation Using Multi-Objective Model and Search Space Reduction Methodology

[EN] The drainage network always needs to adapt to environmental and climatic conditions to provide best quality services. Rehabilitation combining pipes substitution and storm tanks installation appears to be a good solution to overcome this problem. Unfortunately, the calculation time of such a rehabilitation scenario is too elevated for single-objective and multi-objective optimization. In this study, a methodology composed by search space reduction methodology whose purpose is to decrease the number of decision variables of the problem to solve and a multiobjective optimization whose purpose is to optimize the rehabilitation process and represent Pareto fronts as the result of urban drainage networks optimization is proposed. A comparison between different model results for multi-objective optimization is made. To obtain these results, Storm Water Management Model (SWMM) is first connected to a Pseudo Genetic Algorithm (PGA) for the search space reduction and then to a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. Pareto fronts are designed for investment costs instead of flood damage costs. The methodology is applied to a real network in the city of Medellin in Colombia. The results show that search space reduction methodology provides models with a considerably reduced number of decision variables. The multi-objective optimization shows that the models¿ results used after the search space reduction obtain better outcomes than in the complete model in terms of calculation time and optimality of the solutions.Ngamalieu-Nengoue, UA.; Iglesias Rey, PL.; Martínez-Solano, FJ. (2019). Urban Drainage Networks Rehabilitation Using Multi-Objective Model and Search Space Reduction Methodology. Infrastructures. 4(2). https://doi.org/10.3390/infrastructures4020035S4