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Neural Computing and Applications
Published in: Neural Computing and Applications 14/2020

11-11-2019 | Original Article

Design of fractional swarming strategy for solution of optimal reactive power dispatch

Authors: Yasir Muhammad, Rahimdad Khan, Farman Ullah, Ata ur Rehman, Muhammad Saeed Aslam, Muhammad Asif Zahoor Raja

Published in: Neural Computing and Applications | Issue 14/2020

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Abstract

Optimal reactive power dispatch (RPD) for reducing the real power losses of the transmission system is one of the paramount concerns for the research community to investigate the efficiency of power systems. In this paper, strength of meta-heuristic computing paradigm based on fractional-order Darwinian particle swarm optimization (FO-DPSO) is exploited for optimization of RPD problems in energy sector. The fitness functions including line loss minimization and voltage deviation (voltage profile index) are constructed to find the optimal reactive power flow for IEEE 30- and 57-bus test systems. The rich heritage of fractional evolutionary computing through variants of FO-DPSO is applied to minimization problem of optimal power flow by determination of control variables in terms of VAR compensators, bus voltages and transformer tap settings. Comparison of the results shows that fractional swarming intelligence outperformed the state-of-the-art counterparts by means of both line loss minimization and voltage deviation. Superiority of the proposed scheme is also validated for different degrees of freedom in the optimal RPD problems.
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Metadata
Title
Design of fractional swarming strategy for solution of optimal reactive power dispatch
Authors
Yasir Muhammad
Rahimdad Khan
Farman Ullah
Ata ur Rehman
Muhammad Saeed Aslam
Muhammad Asif Zahoor Raja
Publication date
11-11-2019
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 14/2020
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-019-04589-9

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