Placing distributed generators in distribution system using adaptive quantum inspired evolutionary algorithm

Power being generated in generation system is not meeting demand at load centers, mainly due to losses occurring in distribution networks. The active power losses are reduced either by increasing the size of conductor or by changing transformer taps. However, in present scenario, Distributed Generators (DG) can also play a major role in minimization of losses in distribution network. DGs are different from central or traditional power plants, which are usually large in size and concentrated at a location whereas DGs are relatively small scale power station, which are distributed in the network. Reduction in line losses, increase in overall efficiency, peak shaving, relieved transmission and distribution congestion, environmental impacts are some of the advantages produced by suitably placing a DG in the existing system. Therefore, improved quality of power at reduced cost is the benefit gained by the consumer. However, the sizing and placement of DG in distribution network is a difficult optimization problem. In this paper an adaptive quantum inspired evolutionary algorithm approach is used for sizing and placement of DG and experimental results are compared with some `State of Art' existing algorithms, which shows that the proposed technique outperforms some of the existing techniques.