Enhancement of distribution system stability using ABC, ANN and SFCL

In this paper, a hybrid approach is proposed for optimizing the location and size of distribution generations (DGs) in power distribution systems. This hybrid approach is the combination of artificial bee colony algorithm (ABC) and artificial neural network (ANN). Here ABC computes the optimal location of the DG systems and ANN is sized the capacity of DG. The optimal location is evaluated as per the voltage deviation, power loss and real power variation of load buses. Then, exact capacity of DG to improve the voltage stability and reduce the power losses of the load buses is done by using ANN. Fitting of DG units in distribution system results in optimistic impacts such as, voltage profile improvement and reduction in power loss and pessimistic impact is, the raise in the short-circuit level which decreases the transient stability of the system. Hence this paper also presented a proposal of transient stability improvement by using Super Conducting Fault Current Limiter (SFCL). The proposed hybrid approach for optimal location and sizing method is implemented in MATLAB working platform and the performance of SFCL is tested on MATLAB Simulink.