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Erschienen in: Neural Computing and Applications 5/2014

01.04.2014 | Original Article

Performance analysis of artificial bee colony (ABC) algorithm in optimizing release policy of Aswan High Dam

verfasst von: Md. S. Hossain, A. El-shafie

Erschienen in: Neural Computing and Applications | Ausgabe 5/2014

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Abstract

The paper presents a study on developing an effective reservoir operation policy by using artificial bee colony (ABC) algorithm. The decision maker of a reservoir system always needs a guideline to operate the reservoir in an optimal way. Such guidelines named ‘release curves’ have developed for high-, medium-, and low-inflow category that can answer how much water needs to be released for a month by observing the reservoir level (storage condition). The Aswan High Dam of Egypt has been considered for the case study. For comparing the model efficiency, another heuristic approach—genetic algorithm (GA)—has been used. So far, GA is well established and most popular in reservoir release optimization. Historical inflow data for 18 years have been used for simulation purpose, and the general system performance-measuring indices (such as reliability, resiliency, and vulnerability) have been measured. The application procedure and problem formulation of ABC are very simple and can be used in optimizing reservoir system. After using the actual historical inflow, the release policy succeeded in meeting demand for about 98 % of the total time period. According to the simulation results, ABC algorithm showed better performance than the GA approach in reservoir release optimization.

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Metadaten
Titel
Performance analysis of artificial bee colony (ABC) algorithm in optimizing release policy of Aswan High Dam
verfasst von
Md. S. Hossain
A. El-shafie
Publikationsdatum
01.04.2014
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 5/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-012-1309-3

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