Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
In a reservoir operation model, it is very important to check the efficiency by means of some performances measuring indexes. Risk analysis of this kind of optimization-simulation model may consist - reliability, vulnerability and resiliency of the model. These basic performance measuring indices are analyzed in this study. A Particle Swarm Optimization (PSO) algorithm is used to minimize the water deficit of a reservoir system. Also another well-established optimization technique, Genetic Algorithm (GA) has used to compare the results. Inflow patterns are categorized into three different situations (high, medium and low) to construct optimum release curves for every month. The release curves, constructed for a particular month indicates the amount of water release for a known storage condition. After constructing the release policy, simulation has done with historical inflow data. The simulation results showed that the PSO provide better results in terms of reliability analysis of the model. Also, it can handle the critical situation of low inflow more efficiently than GA optimization technique.
How to cite this article:
S. Hossain. A Reservoir Release Optimization-Simulation Model
Using Particle Swarm Optimization (PSO) Algorithm.
DOI: https://doi.org/10.36478/jeasci.2016.2186.2192
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2016.2186.2192