Optimal Placement and Sizing of Distributed Generation for Minimize Losses in Unbalance Radial Distribution Systems Using Quantum Genetic Algorithm
This work exploits Quantum Genetic Algorithm (QGA) to optimize the placement and sizing of Distributed Generators (DGs) in unbalance radial distribution systems. The goal is to minimize losses and at the same time still maintain acceptable voltage profiles. DGs may be placed at any load buses. The proposed method determines which load buses are to have DGs and of what sizes they are respectively. In the method, QGA randomly generates initial population, find network losses and bus voltages of each population member by means of power flow calculations, keep the member with the best configuration as a reference and re-generate the new population for the next iteration based on the current population and based on the reference. Observations were performed based on a modified IEEE Standard 399-1997. All loads in the standard are increased gradually until the point where at least one bus voltage trips below 0.95 pu. Finally, the network with DGs installed as suggested by the proposed method is then compared to this network.
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