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Optimal Design and Operation of Cycl...

Ostadrahimi, Leila.

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Optimal Design and Operation of Cyclic Storage System Using a Hybrid Multi-Swarm PSO-LP Algorithm.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Optimal Design and Operation of Cyclic Storage System Using a Hybrid Multi-Swarm PSO-LP Algorithm./
Author:	Ostadrahimi, Leila.
Description:	152 p.
Notes:	Source: Dissertation Abstracts International, Volume: 74-10(E), Section: B.
Contained By:	Dissertation Abstracts International74-10B(E).
Subject:	Water resources management. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3565545
ISBN:	9781303154324

Optimal Design and Operation of Cyclic Storage System Using a Hybrid Multi-Swarm PSO-LP Algorithm.
Ostadrahimi, Leila.

Optimal Design and Operation of Cyclic Storage System Using a Hybrid Multi-Swarm PSO-LP Algorithm. - 152 p.

Source: Dissertation Abstracts International, Volume: 74-10(E), Section: B.

Thesis (Ph.D.)--University of California, Davis, 2013.

Cyclic storage of surface water and groundwater (CSSG) refers to physically integrated and operationally-interconnected surface water and groundwater subsystems with their full interactions. In such a system, surface and subsurface impoundment subsystems may be treated as competing and potentially interconnected parallel storage facilities that might reduce most of the problems associated with large-scale surface impoundments. This study combines a semi-distributed groundwater model with a hybrid of linear programming (LP) and multi-swarm version of particle swarm optimization (MSPSO) to develop a set of operation rule curves for the conjunctive use of groundwater and surface water subsystems in a CSSG environment, employing a parameterization-simulation-optimization approach. Physical interactions and operational management are integrated in an optimization model to enhance the level of the objective function's satisfaction. In order to improve the performance of the standard PSO algorithm, the model benefits from different swarms in the trial-solution generation stage in a new strategic mechanism called multi-swarm. The resulting model is highly nonlinear and non-convex, and accounts for operational and physical interactions between the well-defined, interconnected elements of the system. In spite of the very narrow and small feasible zone in a very-large policy space, the proposed approach performs efficiently in determining feasible and near-optimal solutions. Although in relatively short operation horizons existing NLP solvers may efficiently be used for the solution of the problem, it is shown that the proposed MSPSO-LP approach is superior in longer operation periods. The proposed algorithm in this study is used to solve the simplified real-world problem located at Zanjan County in Iran. Kinevars dam and its downstream basin of Abhar River is the point of attraction in the study.

ISBN: 9781303154324Subjects--Topical Terms:

794747
Water resources management.

Optimal Design and Operation of Cyclic Storage System Using a Hybrid Multi-Swarm PSO-LP Algorithm.
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245 1 0 $a Optimal Design and Operation of Cyclic Storage System Using a Hybrid Multi-Swarm PSO-LP Algorithm.
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500 $a Adviser: Miguel A. Marino.
502 $a Thesis (Ph.D.)--University of California, Davis, 2013.
520 $a Cyclic storage of surface water and groundwater (CSSG) refers to physically integrated and operationally-interconnected surface water and groundwater subsystems with their full interactions. In such a system, surface and subsurface impoundment subsystems may be treated as competing and potentially interconnected parallel storage facilities that might reduce most of the problems associated with large-scale surface impoundments. This study combines a semi-distributed groundwater model with a hybrid of linear programming (LP) and multi-swarm version of particle swarm optimization (MSPSO) to develop a set of operation rule curves for the conjunctive use of groundwater and surface water subsystems in a CSSG environment, employing a parameterization-simulation-optimization approach. Physical interactions and operational management are integrated in an optimization model to enhance the level of the objective function's satisfaction. In order to improve the performance of the standard PSO algorithm, the model benefits from different swarms in the trial-solution generation stage in a new strategic mechanism called multi-swarm. The resulting model is highly nonlinear and non-convex, and accounts for operational and physical interactions between the well-defined, interconnected elements of the system. In spite of the very narrow and small feasible zone in a very-large policy space, the proposed approach performs efficiently in determining feasible and near-optimal solutions. Although in relatively short operation horizons existing NLP solvers may efficiently be used for the solution of the problem, it is shown that the proposed MSPSO-LP approach is superior in longer operation periods. The proposed algorithm in this study is used to solve the simplified real-world problem located at Zanjan County in Iran. Kinevars dam and its downstream basin of Abhar River is the point of attraction in the study.
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