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• W2078669430 abstract "This paper presents a newly developed teaching learning based optimization (TLBO) algorithm to solve multi-objective optimal reactive power dispatch (ORPD) problem by minimizing real power loss, voltage deviation and voltage stability index. To accelerate the convergence speed and to improve solution quality quasi-opposition based learning (QOBL) concept is incorporated in original TLBO algorithm. The proposed TLBO and quasi-oppositional TLBO (QOTLBO) approaches are implemented on standard IEEE 30-bus and IEEE 118-bus test systems. Results demonstrate superiority in terms of solution quality of the proposed QOTLBO approach over original TLBO and other optimization techniques and confirm its potential to solve the ORPD problem." @default.
• W2078669430 created "2016-06-24" @default.
• W2078669430 creator A5034899973 @default.
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• W2078669430 date "2013-12-01" @default.
• W2078669430 modified "2023-10-16" @default.
• W2078669430 title "Optimal reactive power dispatch using quasi-oppositional teaching learning based optimization" @default.
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• W2078669430 doi "https://doi.org/10.1016/j.ijepes.2013.04.011" @default.
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