Optimal Operation of Water Resources Systems by Using MOPSO Multi-Objective Algorithm

Document Type : Research Paper

Authors

1 University of Ahvaz

2 Razi University of Kermanshah

Abstract

In this study, a method is proposed by using a multi-objective structure and employing new formulations, in which instead of increasing reliability based on meeting a demand of 100 percent in some months regardless of the dry months, part of the water of wet months or seasons is stored in reservoirs so that it can be used in dry months in order to amend failure intensity. To this end, Multi-Objective Particle Swarm Optimization (MOPSO) algorithm was connected to the WEAP simulation model. The main purpose of this type of structures is to offer a resolution to increase the percentage of demand coverage in dry months in addition to reaching to an acceptable demand meeting reliability over the entire period considering the operation capacity of the reservoir. Ultimately, the results of three scenarios, including a current situation, land development management scenario and an optimization one, were evaluated. According to the results of the current situation scenario, in all of the operation period the situation was reported acceptable, except for a few months. In land development scenario, for most consumptions in most of the dry years and in the last six years of planning, the demand coverage was equal to zero in three to eight consecutive dry months, and it was lower than 5% in these months in the rest of the low-water years. On the other hand, the demand coverage increased from 28% to 60% in these months by implementing the optimization model. Also, in the optimal scenario of reliability, supplying downstream environmental demand and Maroon hydroelectric dam need was improved. This study depicts that using the strategies of this research will lead to a better reservoir management and will reduce failure intensity in supplying different consumptions during low-water months.

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References

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Iranian Journal of Soil and Water Research
Volume 48, Issue 4
Dec. and Jan
December 2017
Pages 701-714

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