A novel multi-objective self-adaptive modified θ-firefly algorithm for optimal operation management of stochastic DFR strategy

• Published in: International transactions on electrical energy systems Vol. 25; no. 6; pp. 976 - 993
• Main Authors: Kavousi-Fard, Abdollah, Niknam, Taher, Baziar, Aliasghar
• Format: Journal Article
• Language: English
• Published: Blackwell Publishing Ltd 01.06.2015
• Subjects: optimal operation management of DFR; self-adaptive modified theta firefly algorithm (SAM-θ-FA); stochastic analysis; uncertainty
• ISSN: 2050-7038; 2050-7038
• DOI: 10.1002/etep.1881

Summary This paper suggests a new self‐adaptive modification method using firefly algorithm (FA) to investigate the multi‐objective probabilistic distribution feeder reconfiguration problem. In this regard, the idea of phase angle vector is employed to replace the traditional Cartesian framework in the FA and thus called θ‐FA. Also, a new modification method based on an adaptive mechanism is suggested that will allow each firefly to choose the appropriate modification technique during the optimization suitably. As regards the objective functions, the main focus of this paper is to assess the effect of the reconfiguration on the reliability indices including active power losses, voltage deviation, and system average interruption frequency index. In order to handle the uncertainty effects, a sufficient framework based on 2m + 1 point estimate method is proposed too. The satisfying performance of the proposed method is checked using IEEE 32‐bus radial distribution system. Copyright © 2014 John Wiley & Sons, Ltd.