This paper presents a new application of particle swarm optimization (PSO) to an optimal phase arrangement in a radial distribution system. Most conventional methods that have been used to solve this kind of problem are based on trials and errors. In many cases, a lot of single-phase transformers have been connected to the distribution system and the conventional method is unable to solve an optimal phase arrangement. This paper will focus on this problem. The PSO performance is represented by an exploration of an optimum phase rearrangement as minimized imbalance on the feeder. The PSO inertia weight is modified in order to find the best configuration of radial distributions. Consequently, the performance of PSO can be improved. The benefit of this approach is that many phase arrangement patterns have been generated by PSO. The optimal phase arrangement depends on an operation cost of phase rearrangement. As a result, the utility staff members are able to select suitable configuration which also depend on optimal engineering and economic criteria
[1]
M. A. Abido.
Optimal des'ign of Power System Stabilizers Using Particle Swarm Opt'imization
,
2002,
IEEE Power Engineering Review.
[2]
Mo-Yuen Chow,et al.
Phase balancing using simulated annealing
,
1999
.
[3]
M. Dilek,et al.
Simultaneous Phase Balancing at Substations and Switches with Time-Varying Load Patterns
,
2001,
IEEE Power Engineering Review.
[4]
A.P. Alves da Silva,et al.
Applications of evolutionary computation in electric power systems
,
2002,
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[5]
Mo-Yuen Chow,et al.
Phase balancing using mixed-integer programming [distribution feeders]
,
1998
.