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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 12/2020

27.06.2019 | Original Article

A novel modified whale optimization algorithm for load frequency controller design of a two-area power system composing of PV grid and thermal generator

verfasst von: Rajendra Kumar Khadanga, Amit Kumar, Sidhartha Panda

Erschienen in: Neural Computing and Applications | Ausgabe 12/2020

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Abstract

This paper proposes a modified approach to the original whale optimization algorithm which is a nature-inspired swarm-based optimization algorithm known as the modified whale optimization (MWOA) algorithm. The superiority of proposed modified algorithm over original algorithm in terms of implementation time and solution quality is compared by taking several benchmark test functions. Further, the real application of the said approach in the engineering field is carried out by designing a PID with derivative (PIDF) controller for frequency regulation of a the most realistic scenario of automatic generation control of a two-area interconnected power system composing of a PV grid and a thermal generator. It is observed that MWOA-based PIDF controller is more effective for the load frequency control compared to conventional PID controller.
Vorheriger Artikel Graph constraint-based robust latent space low-rank and sparse subspace clustering
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Metadaten
Titel
A novel modified whale optimization algorithm for load frequency controller design of a two-area power system composing of PV grid and thermal generator
verfasst von
Rajendra Kumar Khadanga
Amit Kumar
Sidhartha Panda
Publikationsdatum
27.06.2019
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 12/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-019-04321-7

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