The Experts below are selected from a list of 15855 Experts worldwide ranked by ideXlab platform
Vicenç Puig - One of the best experts on this subject based on the ideXlab platform.
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optimal Sensor Placement for leak location in water distribution networks using evolutionary algorithms
Water, 2015Co-Authors: Myrna V. Casillas, Luis E Garzacastanon, Vicenç PuigAbstract:In this paper, a Sensor Placement approach to improve the leak location in waterdistribution networks is proposed when the leak signature space (LSS) method is used.The Sensor Placement problem is formulated as an integer optimization problem where thecriterion to be minimized is the number of overlapping signature domains computed fromthe original LSS representation. First, a semi-exhaustive search approach based on a lazyevaluation mechanism ensures optimal Placement in the case of low complexity scenarios.For more complex cases, a stochastic optimization process is proposed, based on eitherthe genetic algorithms (GAs) or particle swarm optimization (PSO). Experiments on twodifferent networks are used to evaluate the performance of the resolution methods, as well asthe efficiency achieved in the leak location when using the Sensor Placement results.
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Sensor Placement for leak location in water distribution networks using the leak signature space
IFAC-PapersOnLine, 2015Co-Authors: Myrna V. Casillas, Luis E Garzacastanon, Vicenç PuigAbstract:Abstract In this paper, a Sensor Placement approach to improve the leak location in water distribution networks is proposed. The Sensor Placement problem is formulated as an integer optimization problem where the criterion to minimize is the number of overlapping signature domains computed from the leak signature space (LSS) representation. A stochastic optimization process is proposed to solve this problem, based on either a Genetic Algorithms (GA) or a Particle Swarm Optimization (PSO) approach. Experiments on two different DMAs are used to evaluate the performance of the resolution methods as well as the efficiency achieved in the leak location when using the Sensor Placement results.
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optimal Sensor Placement for leak location in water distribution networks using genetic algorithms
Conference on Control and Fault-Tolerant Systems, 2013Co-Authors: Myrna V. Casillas, Luis E Garzacastanon, Vicenç Puig, Albert RosichAbstract:In this paper, a new approach for Sensor Placement in water distribution networks (WDN) is proposed. The Sensor Placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the non-linear integer and large-scale nature of the resulting optimization problem, genetic algorithms (GA) are used as solution approach. To validate the results obtained, they are compared with exhaustive search methods with higher computational cost proving that GA allow to find near-optimal solutions with less computational load. The proposed Sensor Placement algorithm is combined with a projection-based isolation scheme. However, the proposed methodology does not depend on the isolation method chosen by the user and it could be easily adapted to any other isolation scheme. Experiments on a real network allow to evaluate the performance of such approach.
Rick S. Blum - One of the best experts on this subject based on the ideXlab platform.
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Sensor Placement for Outage Identifiability in Power Distribution Networks
IEEE Transactions on Smart Grid, 2020Co-Authors: Ananth Narayan Samudrala, M. Hadi Amini, Soummya Kar, Rick S. BlumAbstract:Accurate topology information is critical for effective operation of power distribution networks. Line outages change the operational topology of a distribution network. Hence, outage detection is an important task. Power distribution networks are operated as radial trees and are recently adopting the integration of advanced Sensors to monitor the network in real time. In this paper, a dynamic-programming-based minimum cost Sensor Placement solution is proposed for outage identifiability. A novel formulation of the Sensor Placement as a cost optimization problem involving binary Placement decisions is proposed, along with a dynamic programming algorithm to solve it in polynomial time. Our Sensor Placement solution provides a set of locations in a distribution network where Sensor Placement is mandatory for outage identifiability. We also extend our Sensor Placement optimization problem and dynamic programming algorithm to the case in which the number of measurement channels of Sensors are limited. The advantage of Placement strategies are that they incorporate various types of Sensors, have a polynomial execution time, are cost effective and ensure outage identifiability for any arbitrary values of loads. Numerical results illustrating the proposed Sensor Placement solutions are presented under different scenarios for multiple feeder models including standard IEEE test feeders.
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Sensor Placement for Outage Identifiability in Power Distribution Networks
arXiv: Systems and Control, 2019Co-Authors: Ananth Narayan Samudrala, M. Hadi Amini, Soummya Kar, Rick S. BlumAbstract:Accurate topology information is critical for effective operation of power distribution networks. Line outages change the operational topology of a distribution network. Hence, outage detection is an important task. Power distribution networks are operated as radial trees and are recently adopting the integration of advanced Sensors to monitor the network in real time. In this paper, a dynamic-programming-based minimum cost Sensor Placement solution is proposed for outage identifiability. We propose a novel formulation of the Sensor Placement as a cost optimization problem involving binary Placement decisions, and then provide an algorithm based on dynamic programming to solve it in polynomial time. The advantage of the proposed Placement strategy is that it incorporates various types of Sensors, is independent of time varying load statistics, has a polynomial execution time and is cost effective. Numerical results illustrating the proposed Sensor Placement solution are presented for multiple feeder models including standard IEEE test feeders.
Myrna V. Casillas - One of the best experts on this subject based on the ideXlab platform.
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optimal Sensor Placement for leak location in water distribution networks using evolutionary algorithms
Water, 2015Co-Authors: Myrna V. Casillas, Luis E Garzacastanon, Vicenç PuigAbstract:In this paper, a Sensor Placement approach to improve the leak location in waterdistribution networks is proposed when the leak signature space (LSS) method is used.The Sensor Placement problem is formulated as an integer optimization problem where thecriterion to be minimized is the number of overlapping signature domains computed fromthe original LSS representation. First, a semi-exhaustive search approach based on a lazyevaluation mechanism ensures optimal Placement in the case of low complexity scenarios.For more complex cases, a stochastic optimization process is proposed, based on eitherthe genetic algorithms (GAs) or particle swarm optimization (PSO). Experiments on twodifferent networks are used to evaluate the performance of the resolution methods, as well asthe efficiency achieved in the leak location when using the Sensor Placement results.
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Sensor Placement for leak location in water distribution networks using the leak signature space
IFAC-PapersOnLine, 2015Co-Authors: Myrna V. Casillas, Luis E Garzacastanon, Vicenç PuigAbstract:Abstract In this paper, a Sensor Placement approach to improve the leak location in water distribution networks is proposed. The Sensor Placement problem is formulated as an integer optimization problem where the criterion to minimize is the number of overlapping signature domains computed from the leak signature space (LSS) representation. A stochastic optimization process is proposed to solve this problem, based on either a Genetic Algorithms (GA) or a Particle Swarm Optimization (PSO) approach. Experiments on two different DMAs are used to evaluate the performance of the resolution methods as well as the efficiency achieved in the leak location when using the Sensor Placement results.
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optimal Sensor Placement for leak location in water distribution networks using genetic algorithms
Conference on Control and Fault-Tolerant Systems, 2013Co-Authors: Myrna V. Casillas, Luis E Garzacastanon, Vicenç Puig, Albert RosichAbstract:In this paper, a new approach for Sensor Placement in water distribution networks (WDN) is proposed. The Sensor Placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the non-linear integer and large-scale nature of the resulting optimization problem, genetic algorithms (GA) are used as solution approach. To validate the results obtained, they are compared with exhaustive search methods with higher computational cost proving that GA allow to find near-optimal solutions with less computational load. The proposed Sensor Placement algorithm is combined with a projection-based isolation scheme. However, the proposed methodology does not depend on the isolation method chosen by the user and it could be easily adapted to any other isolation scheme. Experiments on a real network allow to evaluate the performance of such approach.
H. Vincent Poor - One of the best experts on this subject based on the ideXlab platform.
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New formulation and optimization methods for water Sensor Placement
Environmental Modelling & Software, 2016Co-Authors: Yue Zhao, Rafi Schwartz, Elad Salomons, Avi Ostfeld, H. Vincent PoorAbstract:Optimal Sensor Placement for detecting contamination events in water distribution systems is a well explored problem in water distribution systems security. We study herein the problem of Sensor Placement in water networks to minimize the consumption of contaminated water prior to contamination detection. For any Sensor Placement, the average consumption of contaminated water prior to event detection amongst all simulated events is employed as the sensing performance metric. A branch and bound Sensor Placement algorithm is proposed based on greedy heuristics and convex relaxation. Compared to the state of the art results of the battle of the water Sensor networks (BWSN) study, the proposed methodology demonstrated a significant performance enhancement, in particular by applying greedy heuristics to repeated sampling of random subsets of events. Mixed integer convex programming (MICP) for Sensor Placement.Branch and bound for finding the global optimum of the MICP.Competitive comparison to the battle of the water Sensor networks.Branch and bound algorithm based on convex relaxation and a greedy heuristic.Implementation capability on real sized water networks.
Ananth Narayan Samudrala - One of the best experts on this subject based on the ideXlab platform.
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Sensor Placement for Outage Identifiability in Power Distribution Networks
IEEE Transactions on Smart Grid, 2020Co-Authors: Ananth Narayan Samudrala, M. Hadi Amini, Soummya Kar, Rick S. BlumAbstract:Accurate topology information is critical for effective operation of power distribution networks. Line outages change the operational topology of a distribution network. Hence, outage detection is an important task. Power distribution networks are operated as radial trees and are recently adopting the integration of advanced Sensors to monitor the network in real time. In this paper, a dynamic-programming-based minimum cost Sensor Placement solution is proposed for outage identifiability. A novel formulation of the Sensor Placement as a cost optimization problem involving binary Placement decisions is proposed, along with a dynamic programming algorithm to solve it in polynomial time. Our Sensor Placement solution provides a set of locations in a distribution network where Sensor Placement is mandatory for outage identifiability. We also extend our Sensor Placement optimization problem and dynamic programming algorithm to the case in which the number of measurement channels of Sensors are limited. The advantage of Placement strategies are that they incorporate various types of Sensors, have a polynomial execution time, are cost effective and ensure outage identifiability for any arbitrary values of loads. Numerical results illustrating the proposed Sensor Placement solutions are presented under different scenarios for multiple feeder models including standard IEEE test feeders.
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Sensor Placement for Outage Identifiability in Power Distribution Networks
arXiv: Systems and Control, 2019Co-Authors: Ananth Narayan Samudrala, M. Hadi Amini, Soummya Kar, Rick S. BlumAbstract:Accurate topology information is critical for effective operation of power distribution networks. Line outages change the operational topology of a distribution network. Hence, outage detection is an important task. Power distribution networks are operated as radial trees and are recently adopting the integration of advanced Sensors to monitor the network in real time. In this paper, a dynamic-programming-based minimum cost Sensor Placement solution is proposed for outage identifiability. We propose a novel formulation of the Sensor Placement as a cost optimization problem involving binary Placement decisions, and then provide an algorithm based on dynamic programming to solve it in polynomial time. The advantage of the proposed Placement strategy is that it incorporates various types of Sensors, is independent of time varying load statistics, has a polynomial execution time and is cost effective. Numerical results illustrating the proposed Sensor Placement solution are presented for multiple feeder models including standard IEEE test feeders.
