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Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy


Citation

Kadhem, Athraa Ali and Abdul Wahab, Noor Izzri and Abdalla, Ahmed N. (2019) Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy. In: 5th International Conference on Power Generation Systems and Renewable Energy Technologies (PGSRET 2019), 26-27 Aug. 2019, Istanbul, Turkey. .

Abstract

Generating systems are said to be adequately reliable when they can satisfy the load demand. Meanwhile, the reliability of electrical systems is currently being influenced by the increasing acceptance of "Wind Energy Conversion System" (WECS) in power systems compared to other conventional sources. This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). The DEOA technique is used to improve the assessment of the reliability and adequacy of the generation systems by incorporating wind energy from a WECS. The basis of DEOA is the meta- heuristic searching used to simulate the generation systems operation and considering the random failures of existing systems and the unstable character of WECS- sourced wind energy. The effectiveness of the suggested algorithm to assess the reliability and adequacy of power generation systems with WECS was demonstrated. Additionally, the efficiency of the planned algorithm in numerical simulation was compared to that of the "Monte Carlo simulation" (MCS).


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1109/PGSRET.2019.8882705
Publisher: IEEE
Keywords: Reliability assessment; Generating system; Differential evolution optimization algorithm; Wind energy
Depositing User: Nabilah Mustapa
Date Deposited: 15 Jun 2020 01:51
Last Modified: 15 Jun 2020 01:51
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/PGSRET.2019.8882705
URI: http://psasir.upm.edu.my/id/eprint/78132
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