Optimal placement and sizing of Distributed Generation using Quantum Genetic Algorithm for reducing losses and improving voltage profile

In this paper Quantum Genetic Algorithm (QGA) is combined with The Newton Raphson power flow (NR power flow) to optimize the placement and sizing of Distributed Generations (DG's) in electrical power systems. QGA is used to find the optimal placement and generate real power of DG in accordance with mathematical calculations and NR Power Flow is used to calculate the loss on the network and determine the voltage at bus. The goal is to minimize the losses, while at the same time still maintain the acceptable voltage profiles. DG's may be placed at any load bus. Which load buses to have the DG's and of what size they are respectively are determined using this proposed method. Observations are based on standard IEEE 14 buses input and results are compared to the results of network without DG and network with DG by other methods.