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This paper uses artificial intelligent algorithms for reconfiguration of the distribution network. The problem is formulated as an optimization problem where the objective function to be minimized is the power losses, and the constraints are nodal voltage magnitude limits, branch current limits, Kirchhoff’s current law (KCL), Kirchhoff’s voltage law (KVL) and the network radiality condition. While the state (on-off) of the tie switch is considered as control or independent variable, the nodal voltage magnitude, branch current are considered as state or dependent variables. These state variables are continuous whilst the switch state is an integer (binary) variable. The problem being a mixed-integer programming one because of the state of switch (on=closed=1 or off=open=0), a Binary Particle Swarm Optimization (BPSO) and Neural Network are used separately to solve this problem. The effectiveness of proposed method is demonstrated through an example.

A NEW DISTRIBUTION SYSTEM RECONFIGURATION APPROACH USING PARTICLE SWARM OPTIMIZATION AND NEURAL NETWORK