A Genetic Algorithm Approach for Optimal Distribution System Network Reconfiguration

Electrical energy is an essential ingredient for the industrial and all-round development of any country. Power distribution systems are radial in configuration and this makes the networks hard to manage, thus, the need for optimization. This paper presents the optimization of network reconfiguration of distribution system using genetic algorithm to get the optimal switching scheme for network reconfiguration with objective function to reduce power loss and improve active power of the system. Load flow for the network reconfiguration problem was formulated as single objective optimization problem. The optimization model was simulated using MATLAB/SIMULINK and validated on standard IEEE 13-bus and 25-bus distribution test feeders. The result shows that active power increases by 91.1% (1.6469p.u.) while the power loss reduced by 99.4% (1.6372p.u.) for 13-bus system. For 25-bus system, active power increased by 27% (0.9154p.u.) and power loss reduced by 96.2% (4.3074p.u.) after optimization. The results provide solutions to the power distribution system for the optimal switching scheme for network reconfiguration with improvement in active power of the system. Total real power loss was minimized according to the corresponding fitness values of the genetic algorithm solutions. The paper provides technical information that could help in the future expansion and operation planning of the power distribution network. Keywords: Distribution System, Load Flow, Network Reconfiguration, Distribution Test Feeder, Active Power, Power Loss, Genetic Algorithm