An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs

Nikman, T., Mayeripour, M., Olamaei, J., & Arefi, A. (2008) An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs. International Review of Electrical Engineering, 3(3), pp. 513-524.

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Abstract

This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

Impact and interest:

19 citations in Scopus
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7 citations in Web of Science®

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ID Code: 68735
Item Type: Journal Article
Refereed: Yes
Keywords: Ant colony optimization (ACO), Distributed generators, Particle Swarm optimization (PSO), Voltage and reactive power control
ISSN: 1827-6660
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright © 2008 Praise Worthy Prize S.r.l.
Deposited On: 19 Mar 2014 03:44
Last Modified: 04 Dec 2015 02:37

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