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Reliability assessment of power generation systems using intelligent search based on disparity theory


Kadhem, Athraa Ali and Abdul Wahab, Noor Izzri and Aris, Ishak and Jasni, Jasronita and Abdalla, Ahmed N. (2017) Reliability assessment of power generation systems using intelligent search based on disparity theory. Energies, 10 (343). pp. 1-13. ISSN 1996-1073


The reliability of the generating system adequacy is evaluated based on the ability of the system to satisfy the load demand. In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. The DEGA is based on metaheuristic searching for the truncated sampling of state-space for the reliability assessment of power generation system adequacy. Two reliability test systems (IEEE-RTS-79 and (IEEE-RTS-96) are used to demonstrate the effectiveness of the proposed algorithm. The simulation result shows the DEGA can generate a larger variety of the individuals in an early stage of the next population generation. It is also able to estimate the reliability indices accurately.

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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.3390/en10030343
Publisher: MDPI
Keywords: Reliability assessment; Power generation; Disparity theory; Genetic algorithm
Depositing User: Mas Norain Hashim
Date Deposited: 28 Sep 2018 10:45
Last Modified: 28 Sep 2018 10:45
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/en10030343
URI: http://psasir.upm.edu.my/id/eprint/62948
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