scholarly journals Multi-Objective and Multi-Criteria Analysis for Optimal Pump Scheduling in Water Systems

10.29007/vk44 ◽  
2018 ◽  
Author(s):  
Silvia Carpitella ◽  
Bruno Brentan ◽  
Idel Montalvo ◽  
Joaquín Izquierdo ◽  
Antonella Certa
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Pareto Front ◽  
Water Systems ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Operation Optimization ◽  
Multi Objective ◽  
Pump Scheduling ◽  
Multi Criteria Analysis

This contribution focuses on the problem of optimal pump scheduling, a fundamental element in pursuing operation optimization of water distribution systems. A combined approach of multi-objective optimization and multi-criteria analysis is herein suggested to first find the Pareto front of non-dominated solutions and then to rank them based on a set of weighted criteria. The Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve the multi-objective problem, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to achieve the final ranking.

Optimization of Vehicle-Borne Radar Antenna Pedestal Based on Modified NSGA-II

2014 ◽  
Vol 945-949 ◽  
pp. 2241-2247
Author(s):  
De Gao Zhao ◽  
Qiang Li
Keyword(s):  
Pareto Front ◽  
Optimization Problems ◽  
Population Diversity ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Sorting Process ◽  
Definition Of ◽  
Radar Antenna ◽  
Modified Algorithm

This paper deals with application of Non-dominated Sorting Genetic Algorithm with elitism (NSGA-II) to solve multi-objective optimization problems of designing a vehicle-borne radar antenna pedestal. Five technical improvements are proposed due to the disadvantages of NSGA-II. They are as follow: (1) presenting a new method to calculate the fitness of individuals in population; (2) renewing the definition of crowding distance; (3) introducing a threshold for choosing elitist; (4) reducing some redundant sorting process; (5) developing a self-adaptive arithmetic cross and mutation probability. The modified algorithm can lead to better population diversity than the original NSGA-II. Simulation results prove rationality and validity of the modified NSGA-II. A uniformly distributed Pareto front can be obtained by using the modified NSGA-II. Finally, a multi-objective problem of designing a vehicle-borne radar antenna pedestal is settled with the modified algorithm.

scholarly journals Multi-objective Evolutionary Algorithms for Power Distribution System Optimal Reconfiguration

2019 ◽  
Vol 22 (3) ◽  
Author(s):  
Ivo Benitez Cattani
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Multi Objective Optimization ◽  
Power Losses ◽  
Nsga Ii ◽  
Power Distribution System ◽  
Multi Objective ◽  
Three Phase ◽  
Unbalanced Voltage

In this paper two reconfiguration methodologies for three-phase electric power distribution systems based on multi-objective optimization algorithms are developed in order to simultaneously optimize two objective functions, (1) power losses and (2) three-phase unbalanced voltage minimization. The proposed optimization involves only radial topology configurations which is the most common configuration in electric distribution systems. The formulation of the problem considers the radiality as a constraint, increasing the computational complexity. The Prim and Kruskal algorithms are tested to fix infeasible configurations. In distribution systems, the three-phase unbalanced voltage and power losses limit the power supply to the loads and may even cause overheating in distribution lines, transformers and other equipment. An alternative to solve this problem is through a reconfiguration process, by opening and/or closing switches altering the distribution system configuration under operation. Hence, in this work the three-phase unbalanced voltage and power losses in radial distribution systems are addressed as a multi-objective optimization problem, firstly, using a method based on weighted sum; and, secondly, implementing NSGA-II algorithm. An example of distribution system is presented to prove the effectiveness of the proposed method.

Multi-objective optimization of a hybrid electromagnetic suspension system for ride comfort, road holding and regenerated power

2016 ◽  
Vol 23 (5) ◽  
pp. 782-793 ◽  
Author(s):  
Mansour Ataei ◽  
Ehsan Asadi ◽  
Avesta Goodarzi ◽  
Amir Khajepour ◽  
Mir Behrad Khamesee
Keyword(s):  
Pareto Front ◽  
Ride Comfort ◽  
Optimization Method ◽  
Suspension System ◽  
Multi Objective Optimization ◽  
Damping Force ◽  
Nsga Ii ◽  
Electromagnetic Suspension ◽  
Multi Objective ◽  
Electromagnetic Component

This paper reports work on the optimization and performance evaluation of a hybrid electromagnetic suspension system equipped with a hybrid electromagnetic damper. The hybrid damper is configured to operate with hydraulic and electromagnetic components. The hydraulic component produces a large fail-safe baseline damping force, while the electromagnetic component adds energy regeneration and adaptability to the suspension. For analyzing the system, the electromagnetic component was modeled and integrated into a 2DOF quarter-car model. Three criteria were considered for evaluating the performance of the suspension system: ride comfort, road holding and regenerated power. Using the genetic algorithm multi-objective optimization (NSGA-II), the suspension design was optimized to improve the performance of the vehicle with respect to the selected criteria. The multi-objective optimization method provided a set of solutions called Pareto front in which all solutions are equally good and the selection of each one depends on conditions and needs. Among the given solutions in the Pareto front, a small number of cases, with different design purposes, were selected. The performances of the selected designs were compared with two reference systems: a conventional and a nonoptimized hybrid suspension system. The results show that the ride comfort and road holding qualities of the optimized hybrid system are improved, and the regenerated power is considerably increased.

scholarly journals Advances in Modeling and Management of Urban Water Networks

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2956
Author(s):  
Alberto Campisano ◽  
Enrico Creaco
Keyword(s):  
Asset Management ◽  
Distribution Systems ◽  
Water Distribution ◽  
Urban Water ◽  
Multi Objective Optimization ◽  
Water Networks ◽  
Special Issue ◽  
Leakage Reduction ◽  
Multi Objective ◽  
Pipe Burst

This Editorial presents a representative collection of 15 papers, presented in the Special Issue on Advances in Modeling and Management of Urban Water Networks (UWNs), and frames them in the current research trends. The most analyzed systems in the Special Issue are the Water Distribution Systems (WDSs), with the following four topics explored: asset management, modelling of demand and hydraulics, energy recovery, and pipe burst identification and leakage reduction. In the first topic, the multi-objective optimization of interventions on the network is presented to find trade-off solutions between costs and efficiency. In the second topic, methodologies are presented to simulate and predict demand and to simulate network behavior in emergency scenarios. In the third topic, a methodology is presented for the multi-objective optimization of pump-as-turbine (PAT) installation sites in transmission mains. In the fourth topic, methodologies for pipe burst identification and leakage reduction are presented. As for the Urban Drainage Systems (UDSs), the two explored topics are asset management, with a system upgrade to reduce flooding, and modelling of flow and water quality, with analyses on the transition from surface to pressurized flow, impact of water use reduction on the operation of UDSs and sediment transport in pressurized pipes. The Special Issue also includes one paper dealing with the hydraulic modelling of an urban river with a complex cross-section.

scholarly journals Self-Adaptive Models for Water Distribution System Design Using Single-/Multi-Objective Optimization Approaches

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1293 ◽  
Author(s):  
Choi ◽  
Kim
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Mathematical Problem ◽  
Benchmark Problems ◽  
Future Research ◽  
Multi Objective Optimization ◽  
Adaptive Approach ◽  
Multi Objective ◽  
Self Adaptive

This study compares the performance of self-adaptive optimization approaches in efficient water distribution systems (WDS) design and presents a guide for the selection of the appropriate method employing optimization utilizing the characteristic of each technique formulation. To this end, this study performs three types of analyses. First, the sensitivity analysis of each self-adaptive approach is conducted on single/multi-objective mathematical benchmark problems with various problem types (e.g., using solution shape or many local optimal solutions). Second, based on the applications and results of the mathematical problem, the performance of the algorithm is verified in the WDS design problem considering the minimum cost and the maximum system resilience under the single/multi-objective optimization framework. Third, the characteristics of search operators in the self-adaptive approach are compared according to the presence or absence of additional parameters and operators. Moreover, various performance indices are employed to compare the quantitative evaluation of each algorithm. Each algorithm is found to exhibit different characteristics depending on the problem scale and solution type. These results are expected to benefit future research in the formulation of new approaches and developments. Hence, this study provides rigorous testing of the performance of newly proposed algorithms in a highly simplified manner.

Multi-Objective Optimization of the Impingement-Film Cooling Structure of a Gas Turbine Endwall Using Conjugate Heat Transfer Simulations

2017 ◽  
Vol 10 (2) ◽  
Author(s):  
Zhongran Chi ◽  
Haiqing Liu ◽  
Shusheng Zang
Keyword(s):  
Heat Transfer ◽  
Film Cooling ◽  
Conjugate Heat Transfer ◽  
Pareto Front ◽  
Parametric Design ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Lift Off ◽  
Optimization Search

This paper discusses the approach of cooling design optimization of a high-pressure turbine (HPT) endwall with applied 3D conjugate heat transfer (CHT) computational fluid dynamics (CFD). This study involved the optimization of the spacing of impingement jet array and the exit width of shaped holes, which are different for each cooling cavity. The optimization objectives were to reduce the wall-temperature level and to increase the aerodynamic performance. The optimization methodology consisted of an in-house parametric design and CFD mesh generation tool, a CHT CFD solver, a database of CFD results, a metamodel, and an algorithm for multi-objective optimization. The CFD tool was validated against experimental data of an endwall at CHT conditions. The metamodel, which could efficiently estimate the optimization objectives of new individuals without CFD runs, was developed and coupled with nondominated sorting genetic algorithm II (NSGA II) to accelerate the optimization process. Through the optimization search, the Pareto front of the problem was found in each iteration. The accuracy of metamodel with more iterations was improved by enriching database. But optimal designs found by the last iteration are almost identical with those of the first iteration. Through analyzing extra CFD results, it was demonstrated that the design variables in the Pareto front successfully reached the optimal values. The optimal pitches of impingement arrays could be decided accommodating the local thermal load while avoiding jet lift-off of film coolant. It was also suggested that cylindrical film holes near throat should be beneficial to both aerodynamic and cooling performances.

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