New Enhanced Symbiotic Organisms Search for Optimal Location and Sizing of Distributed Generation in Radial Distribution System.

Large distributed generation (DG) penetration into the power system needs to be accompanied by proper planning to maximize the benefits and minimize the negative effects that may arise on the system. Determining the location and size of DGs in power systems is a complex issue because it involves hundreds or even thousands of buses and lines distribution. Various studies have been conducted to overcome these problems, including by developing existing methods or even discovering new methods. This study deals with location optimization and sizing DG in the radial distribution system to minimize power loss and voltage deviation. The location of the DG is identified using a loss reduction sensitivity factor (LRSF) while the size of the DG is determined using the improved method of symbiotic organisms search (SOS) called New Enhanced SOS (NeSOS). There are two methods developed in the NeSOS, namely random weighted inverse vector (RWIV) and dual-phase parasitism (DPP). DPP consists of classic parasitism (CP)and random weight parasitism (RWP). The NeSOS is programmed under MATLAB software and validated using 26 mathematical benchmark functions. NeSOS also tested on IEEE 33 and IEEE 69 bus test system and compared with other methods. The simulation results show that the convergence rate of NeSOS is 30% faster than SOS. NeSOS also provides an average power loss of 1.53% lower than other methods. [ABSTRACT FROM AUTHOR]