Multi-objective evolutionary algorithm for operating parallel reservoir system
Resource
Journal of Hydrology, 377(1-2),12-20
Journal
Journal of Hydrology
Pages
12
Date Issued
2009-10
Date
2009-10
Author(s)
Chang, Li-Chiu
Abstract
This paper applies a multi-objective evolutionary algorithm, the non-dominated sorting genetic algorithm (NSGA-II), to examine the operations of a multi-reservoir system in Taiwan. The Feitsui and Shihmen reservoirs are the most important water supply reservoirs in Northern Taiwan supplying the domestic and industrial water supply needs for over 7 million residents. A daily operational simulation model is developed to guide the releases of the reservoir system and then to calculate the shortage indices (SI) of both reservoirs over a long-term simulation period. The NSGA-II is used to minimize the SI values through identification of optimal joint operating strategies. Based on a 49 year data set, we demonstrate that better operational strategies would reduce shortage indices for both reservoirs. The results indicate that the NSGA-II provides a promising approach. The pareto-front optimal solutions identified operational compromises for the two reservoirs that would be expected to improve joint operations.
Subjects
Optimization
Simulation model
Reservoir system
Multi-objective evolutionary algorithm
Type
journal article
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